WorldWideScience

Sample records for classification

  1. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  2. Nominal classification

    OpenAIRE

    Senft, G.

    2007-01-01

    This handbook chapter summarizes some of the problems of nominal classification in language, presents and illustrates the various systems or techniques of nominal classification, and points out why nominal classification is one of the most interesting topics in Cognitive Linguistics.

  3. Strategic Classification

    OpenAIRE

    Hardt, Moritz; Megiddo, Nimrod; Papadimitriou, Christos; Wootters, Mary

    2015-01-01

    Machine learning relies on the assumption that unseen test instances of a classification problem follow the same distribution as observed training data. However, this principle can break down when machine learning is used to make important decisions about the welfare (employment, education, health) of strategic individuals. Knowing information about the classifier, such individuals may manipulate their attributes in order to obtain a better classification outcome. As a result of this behavior...

  4. Transporter Classification Database (TCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

  5. Tissue Classification

    DEFF Research Database (Denmark)

    Van Leemput, Koen; Puonti, Oula

    2015-01-01

    Computational methods for automatically segmenting magnetic resonance images of the brain have seen tremendous advances in recent years. So-called tissue classification techniques, aimed at extracting the three main brain tissue classes (white matter, gray matter, and cerebrospinal fluid), are no...... software packages such as SPM, FSL, and FreeSurfer....

  6. Classifying Classification

    Science.gov (United States)

    Novakowski, Janice

    2009-01-01

    This article describes the experience of a group of first-grade teachers as they tackled the science process of classification, a targeted learning objective for the first grade. While the two-year process was not easy and required teachers to teach in a new, more investigation-oriented way, the benefits were great. The project helped teachers and…

  7. Classification in Australia.

    Science.gov (United States)

    McKinlay, John

    Despite some inroads by the Library of Congress Classification and short-lived experimentation with Universal Decimal Classification and Bliss Classification, Dewey Decimal Classification, with its ability in recent editions to be hospitable to local needs, remains the most widely used classification system in Australia. Although supplemented at…

  8. Classification in context

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary cla...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

  9. Multi-borders classification

    OpenAIRE

    Mills, Peter

    2014-01-01

    The number of possible methods of generalizing binary classification to multi-class classification increases exponentially with the number of class labels. Often, the best method of doing so will be highly problem dependent. Here we present classification software in which the partitioning of multi-class classification problems into binary classification problems is specified using a recursive control language.

  10. Classification and knowledge

    Science.gov (United States)

    Kurtz, Michael J.

    1989-01-01

    Automated procedures to classify objects are discussed. The classification problem is reviewed, and the relation of epistemology and classification is considered. The classification of stellar spectra and of resolved images of galaxies is addressed.

  11. Hazard classification methodology

    International Nuclear Information System (INIS)

    This document outlines the hazard classification methodology used to determine the hazard classification of the NIF LTAB, OAB, and the support facilities on the basis of radionuclides and chemicals. The hazard classification determines the safety analysis requirements for a facility

  12. Remote Sensing Information Classification

    Science.gov (United States)

    Rickman, Douglas L.

    2008-01-01

    This viewgraph presentation reviews the classification of Remote Sensing data in relation to epidemiology. Classification is a way to reduce the dimensionality and precision to something a human can understand. Classification changes SCALAR data into NOMINAL data.

  13. Classification of the web

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper discusses the challenges faced by investigations into the classification of the Web and outlines inquiries that are needed to use principles for bibliographic classification to construct classifications of the Web. This paper suggests that the classification of the Web meets challenges...

  14. Hand eczema classification

    DEFF Research Database (Denmark)

    Diepgen, T L; Andersen, Klaus Ejner; Brandao, F M;

    2008-01-01

    the disease is rarely evidence based, and a classification system for different subdiagnoses of hand eczema is not agreed upon. Randomized controlled trials investigating the treatment of hand eczema are called for. For this, as well as for clinical purposes, a generally accepted classification system...... classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....

  15. Classification of articulators.

    Science.gov (United States)

    Rihani, A

    1980-03-01

    A simple classification in familiar terms with definite, clear characteristics can be adopted. This classification system is based on the number of records used and the adjustments necessary for the articulator to accept these records. The classification divides the articulators into nonadjustable, semiadjustable, and fully adjustable articulators (Table I). PMID:6928204

  16. Recursive heuristic classification

    Science.gov (United States)

    Wilkins, David C.

    1994-01-01

    The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.

  17. Security classification of information

    Energy Technology Data Exchange (ETDEWEB)

    Quist, A.S.

    1993-04-01

    This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

  18. Classiology and soil classification

    Science.gov (United States)

    Rozhkov, V. A.

    2012-03-01

    Classiology can be defined as a science studying the principles and rules of classification of objects of any nature. The development of the theory of classification and the particular methods for classifying objects are the main challenges of classiology; to a certain extent, they are close to the challenges of pattern recognition. The methodology of classiology integrates a wide range of methods and approaches: from expert judgment to formal logic, multivariate statistics, and informatics. Soil classification assumes generalization of available data and practical experience, formalization of our notions about soils, and their representation in the form of an information system. As an information system, soil classification is designed to predict the maximum number of a soil's properties from the position of this soil in the classification space. The existing soil classification systems do not completely satisfy the principles of classiology. The violation of logical basis, poor structuring, low integrity, and inadequate level of formalization make these systems verbal schemes rather than classification systems sensu stricto. The concept of classification as listing (enumeration) of objects makes it possible to introduce the notion of the information base of classification. For soil objects, this is the database of soil indices (properties) that might be applied for generating target-oriented soil classification system. Mathematical methods enlarge the prognostic capacity of classification systems; they can be applied to assess the quality of these systems and to recognize new soil objects to be included in the existing systems. The application of particular principles and rules of classiology for soil classification purposes is discussed in this paper.

  19. Efficient Pairwise Multilabel Classification

    OpenAIRE

    Loza Mencía, Eneldo

    2013-01-01

    Multilabel classification learning is the task of learning a mapping between objects and sets of possibly overlapping classes and has gained increasing attention in recent times. A prototypical application scenario for multilabel classification is the assignment of a set of keywords to a document, a frequently encountered problem in the text classification domain. With upcoming Web 2.0 technologies, this domain is extended by a wide range of tag suggestion tasks and the trend definitely...

  20. Efficient multivariate sequence classification

    OpenAIRE

    Kuksa, Pavel P.

    2014-01-01

    Kernel-based approaches for sequence classification have been successfully applied to a variety of domains, including the text categorization, image classification, speech analysis, biological sequence analysis, time series and music classification, where they show some of the most accurate results. Typical kernel functions for sequences in these domains (e.g., bag-of-words, mismatch, or subsequence kernels) are restricted to {\\em discrete univariate} (i.e. one-dimensional) string data, such ...

  1. Classifier in Age classification

    OpenAIRE

    B. Santhi; R.Seethalakshmi

    2012-01-01

    Face is the important feature of the human beings. We can derive various properties of a human by analyzing the face. The objective of the study is to design a classifier for age using facial images. Age classification is essential in many applications like crime detection, employment and face detection. The proposed algorithm contains four phases: preprocessing, feature extraction, feature selection and classification. The classification employs two class labels namely child and Old. This st...

  2. Aspects de la classification

    OpenAIRE

    Mari, Jean-François; Napoli, Amedeo

    1996-01-01

    Les techniques de classification numérique ont toujours été présentes en reconnaissance des formes. Les réseaux de neurones montrent chaque jour leurs (très ?) bonnes propriétés de classification, et la classification se fait de plus en plus présente en représentation des connaissances. Ainsi, ce rapport présente, simplement dans un but introductif, les aspects mathématiques, statistiques, neuromimétiques et cognitifs de la classification.

  3. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta...... data sets or for obtaining advanced search facilities. In this paper we will present an attempt at answering these questions. We will give a presentation of various types of ontologies and briefly introduce terminological ontologies. Furthermore we will argue that classification systems, e.g. product...... classification systems and meta data taxonomies, should be based on ontologies....

  4. Concepts of Classification and Taxonomy. Phylogenetic Classification

    CERN Document Server

    Fraix-Burnet, Didier

    2016-01-01

    Phylogenetic approaches to classification have been heavily developed in biology by bioinformaticians. But these techniques have applications in other fields, in particular in linguistics. Their main characteristics is to search for relationships between the objects or species in study, instead of grouping them by similarity. They are thus rather well suited for any kind of evolutionary objects. For nearly fifteen years, astrocladistics has explored the use of Maximum Parsimony (or cladistics) for astronomical objects like galaxies or globular clusters. In this lesson we will learn how it works. 1 Why phylogenetic tools in astrophysics? 1.1 History of classification The need for classifying living organisms is very ancient, and the first classification system can be dated back to the Greeks. The goal was very practical since it was intended to distinguish between eatable and toxic aliments, or kind and dangerous animals. Simple resemblance was used and has been used for centuries. Basically, until the XVIIIth...

  5. Library Classification 2020

    Science.gov (United States)

    Harris, Christopher

    2013-01-01

    In this article the author explores how a new library classification system might be designed using some aspects of the Dewey Decimal Classification (DDC) and ideas from other systems to create something that works for school libraries in the year 2020. By examining what works well with the Dewey Decimal System, what features should be carried…

  6. Musings on galaxy classification

    International Nuclear Information System (INIS)

    Classification schemes and their utility are discussed with a number of examples, particularly for cD galaxies. Data suggest that primordial turbulence rather than tidal torques is responsible for most of the presently observed angular momentum of galaxies. Finally, some of the limitations on present-day schemes for galaxy classification are pointed out. 54 references, 4 figures, 3 tables

  7. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases the...... classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...... datasets. Our model also outperforms A Decision Cluster Classification (ADCC) and the Decision Cluster Forest Classification (DCFC) models on the Reuters-21578 dataset....

  8. Pitch Based Sound Classification

    OpenAIRE

    Nielsen, Andreas Brinch; Hansen, Lars Kai; Kjems, U.

    2006-01-01

    A sound classification model is presented that can classify signals into music, noise and speech. The model extracts the pitch of the signal using the harmonic product spectrum. Based on the pitch estimate and a pitch error measure, features are created and used in a probabilistic model with soft-max output function. Both linear and quadratic inputs are used. The model is trained on 2 hours of sound and tested on publicly available data. A test classification error below 0.05 with 1 s classif...

  9. Learning Apache Mahout classification

    CERN Document Server

    Gupta, Ashish

    2015-01-01

    If you are a data scientist who has some experience with the Hadoop ecosystem and machine learning methods and want to try out classification on large datasets using Mahout, this book is ideal for you. Knowledge of Java is essential.

  10. Classification in Medical Imaging

    DEFF Research Database (Denmark)

    Chen, Chen

    detection in a cardiovascular disease study. The third focus is to deepen the understanding of classification mechanism by visualizing the knowledge learned by a classifier. More specifically, to build the most typical patterns recognized by the Fisher's linear discriminant rule with applications......Classification is extensively used in the context of medical image analysis for the purpose of diagnosis or prognosis. In order to classify image content correctly, one needs to extract efficient features with discriminative properties and build classifiers based on these features. In addition......, a good metric is required to measure distance or similarity between feature points so that the classification becomes feasible. Furthermore, in order to build a successful classifier, one needs to deeply understand how classifiers work. This thesis focuses on these three aspects of classification...

  11. Inhibition in multiclass classification

    OpenAIRE

    Huerta, Ramón; Vembu, Shankar; Amigó, José M.; Nowotny, Thomas; Elkan, Charles

    2012-01-01

    The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and ...

  12. Multiple sparse representations classification

    OpenAIRE

    Plenge, Esben; Klein, Stefan; Niessen, Wiro; Meijering, Erik

    2015-01-01

    textabstractSparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In this empirical study we propose to further leverage the redundancy of the learned dictionaries to achieve a more accurate classifier. In conventional SRC, each image pixel is associated with a small...

  13. Multiple Sparse Representations Classification

    OpenAIRE

    Plenge, Esben; Klein, Stefan S.; Niessen, Wiro J.; Meijering, Erik

    2015-01-01

    Sparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In this empirical study we propose to further leverage the redundancy of the learned dictionaries to achieve a more accurate classifier. In conventional SRC, each image pixel is associated with a small patch surro...

  14. Twitter content classification

    OpenAIRE

    Dann, Stephen

    2010-01-01

    This paper delivers a new Twitter content classification framework based sixteen existing Twitter studies and a grounded theory analysis of a personal Twitter history. It expands the existing understanding of Twitter as a multifunction tool for personal, profession, commercial and phatic communications with a split level classification scheme that offers broad categorization and specific sub categories for deeper insight into the real world application of the service.

  15. Text classification method review

    OpenAIRE

    Mahinovs, Aigars; Tiwari, Ashutosh; Roy, Rajkumar; Baxter, David

    2007-01-01

    With the explosion of information fuelled by the growth of the World Wide Web it is no longer feasible for a human observer to understand all the data coming in or even classify it into categories. With this growth of information and simultaneous growth of available computing power automatic classification of data, particularly textual data, gains increasingly high importance. This paper provides a review of generic text classification process, phases of that process and met...

  16. Automatic Arabic Text Classification

    OpenAIRE

    Al-harbi, S; Almuhareb, A.; Al-Thubaity , A; Khorsheed, M. S.; Al-Rajeh, A.

    2008-01-01

    Automated document classification is an important text mining task especially with the rapid growth of the number of online documents present in Arabic language. Text classification aims to automatically assign the text to a predefined category based on linguistic features. Such a process has different useful applications including, but not restricted to, e-mail spam detection, web page content filtering, and automatic message routing. This paper presents the results of experiments on documen...

  17. Classification of Sleep Disorders

    OpenAIRE

    Michael J. Thorpy

    2012-01-01

    The classification of sleep disorders is necessary to discriminate between disorders and to facilitate an understanding of symptoms, etiology, and pathophysiology that allows for appropriate treatment. The earliest classification systems, largely organized according to major symptoms (insomnia, excessive sleepiness, and abnormal events that occur during sleep), were unable to be based on pathophysiology because the cause of most sleep disorders was unknown. These 3 symptom-based categories ar...

  18. Latent classification models

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre

    2005-01-01

    parametric family ofdistributions.  In this paper we propose a new set of models forclassification in continuous domains, termed latent classificationmodels. The latent classification model can roughly be seen ascombining the \\NB model with a mixture of factor analyzers,thereby relaxing the assumptions of...... classification model, and wedemonstrate empirically that the accuracy of the proposed model issignificantly higher than the accuracy of other probabilisticclassifiers....

  19. Classifications of Software Transfers

    OpenAIRE

    Wohlin, Claes; Smite, Darja

    2012-01-01

    Many companies have development sites around the globe. This inevitably means that development work may be transferred between the sites. This paper defines a classification of software transfer types; it divides transfers into three main types: full, partial and gradual transfers to describe the context of a transfer. The differences between transfer types, and hence the need for a classification, are illustrated with staffing curves for two different transfer types. The staffing curves are ...

  20. A New Classification Approach Based on Multiple Classification Rules

    OpenAIRE

    Zhongmei Zhou

    2014-01-01

    A good classifier can correctly predict new data for which the class label is unknown, so it is important to construct a high accuracy classifier. Hence, classification techniques are much useful in ubiquitous computing. Associative classification achieves higher classification accuracy than some traditional rule-based classification approaches. However, the approach also has two major deficiencies. First, it generates a very large number of association classification rules, especially when t...

  1. Supernova Photometric Lightcurve Classification

    Science.gov (United States)

    Zaidi, Tayeb; Narayan, Gautham

    2016-01-01

    This is a preliminary report on photometric supernova classification. We first explore the properties of supernova light curves, and attempt to restructure the unevenly sampled and sparse data from assorted datasets to allow for processing and classification. The data was primarily drawn from the Dark Energy Survey (DES) simulated data, created for the Supernova Photometric Classification Challenge. This poster shows a method for producing a non-parametric representation of the light curve data, and applying a Random Forest classifier algorithm to distinguish between supernovae types. We examine the impact of Principal Component Analysis to reduce the dimensionality of the dataset, for future classification work. The classification code will be used in a stage of the ANTARES pipeline, created for use on the Large Synoptic Survey Telescope alert data and other wide-field surveys. The final figure-of-merit for the DES data in the r band was 60% for binary classification (Type I vs II).Zaidi was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program (AST-1262829).

  2. Hierarchical classification of social groups

    OpenAIRE

    Витковская, Мария

    2001-01-01

    Classification problems are important for every science, and for sociology as well. Social phenomena, examined from the aspect of classification of social groups, can be examined deeper. At present one common classification of groups does not exist. This article offers the hierarchical classification of social group.

  3. Product Classification in Supply Chain

    OpenAIRE

    Xing, Lihong; Xu, Yaoxuan

    2010-01-01

    Oriflame is a famous international direct sale cosmetics company with complicated supply chain operation but it lacks of a product classification system. It is vital to design a product classification method in order to support Oriflame global supply planning and improve the supply chain performance. This article is aim to investigate and design the multi-criteria of product classification, propose the classification model, suggest application areas of product classification results and intro...

  4. Concepts of Classification and Taxonomy Phylogenetic Classification

    Science.gov (United States)

    Fraix-Burnet, D.

    2016-05-01

    Phylogenetic approaches to classification have been heavily developed in biology by bioinformaticians. But these techniques have applications in other fields, in particular in linguistics. Their main characteristics is to search for relationships between the objects or species in study, instead of grouping them by similarity. They are thus rather well suited for any kind of evolutionary objects. For nearly fifteen years, astrocladistics has explored the use of Maximum Parsimony (or cladistics) for astronomical objects like galaxies or globular clusters. In this lesson we will learn how it works.

  5. The paradox of atheoretical classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2016-01-01

    A distinction can be made between “artificial classifications” and “natural classifications,” where artificial classifications may adequately serve some limited purposes, but natural classifications are overall most fruitful by allowing inference and thus many different purposes. There is strong...... support for the view that a natural classification should be based on a theory (and, of course, that the most fruitful theory provides the most fruitful classification). Nevertheless, atheoretical (or “descriptive”) classifications are often produced. Paradoxically, atheoretical classifications may be...... very successful. The best example of a successful “atheoretical” classification is probably the prestigious Diagnostic and Statistical Manual of Mental Disorders (DSM) since its third edition from 1980. Based on such successes one may ask: Should the claim that classifications ideally are natural and...

  6. Information gathering for CLP classification

    Directory of Open Access Journals (Sweden)

    Ida Marcello

    2011-01-01

    Full Text Available Regulation 1272/2008 includes provisions for two types of classification: harmonised classification and self-classification. The harmonised classification of substances is decided at Community level and a list of harmonised classifications is included in the Annex VI of the classification, labelling and packaging Regulation (CLP. If a chemical substance is not included in the harmonised classification list it must be self-classified, based on available information, according to the requirements of Annex I of the CLP Regulation. CLP appoints that the harmonised classification will be performed for carcinogenic, mutagenic or toxic to reproduction substances (CMR substances and for respiratory sensitisers category 1 and for other hazard classes on a case-by-case basis. The first step of classification is the gathering of available and relevant information. This paper presents the procedure for gathering information and to obtain data. The data quality is also discussed.

  7. Vertebral fracture classification

    Science.gov (United States)

    de Bruijne, Marleen; Pettersen, Paola C.; Tankó, László B.; Nielsen, Mads

    2007-03-01

    A novel method for classification and quantification of vertebral fractures from X-ray images is presented. Using pairwise conditional shape models trained on a set of healthy spines, the most likely unfractured shape is estimated for each of the vertebrae in the image. The difference between the true shape and the reconstructed normal shape is an indicator for the shape abnormality. A statistical classification scheme with the two shapes as features is applied to detect, classify, and grade various types of deformities. In contrast with the current (semi-)quantitative grading strategies this method takes the full shape into account, it uses a patient-specific reference by combining population-based information on biological variation in vertebra shape and vertebra interrelations, and it provides a continuous measure of deformity. Good agreement with manual classification and grading is demonstrated on 204 lateral spine radiographs with in total 89 fractures.

  8. Classification problem in CBIR

    Directory of Open Access Journals (Sweden)

    Tatiana Jaworska

    2013-04-01

    Full Text Available At present a great deal of research is being done in different aspects of Content-Based Im-age Retrieval (CBIR. Image classification is one of the most important tasks in image re-trieval that must be dealt with. The primary issue we have addressed is: how can the fuzzy set theory be used to handle crisp image data. We propose fuzzy rule-based classification of image objects. To achieve this goal we have built fuzzy rule-based classifiers for crisp data. In this paper we present the results of fuzzy rule-based classification in our CBIR. Further-more, these results are used to construct a search engine taking into account data mining.

  9. Supernova Photometric Classification Challenge

    CERN Document Server

    Kessler, Richard; Jha, Saurabh; Kuhlmann, Stephen

    2010-01-01

    We have publicly released a blinded mix of simulated SNe, with types (Ia, Ib, Ic, II) selected in proportion to their expected rate. The simulation is realized in the griz filters of the Dark Energy Survey (DES) with realistic observing conditions (sky noise, point spread function and atmospheric transparency) based on years of recorded conditions at the DES site. Simulations of non-Ia type SNe are based on spectroscopically confirmed light curves that include unpublished non-Ia samples donated from the Carnegie Supernova Project (CSP), the Supernova Legacy Survey (SNLS), and the Sloan Digital Sky Survey-II (SDSS-II). We challenge scientists to run their classification algorithms and report a type for each SN. A spectroscopically confirmed subset is provided for training. The goals of this challenge are to (1) learn the relative strengths and weaknesses of the different classification algorithms, (2) use the results to improve classification algorithms, and (3) understand what spectroscopically confirmed sub-...

  10. Bosniak classification system

    DEFF Research Database (Denmark)

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens;

    2016-01-01

    BACKGROUND: The Bosniak classification was originally based on computed tomographic (CT) findings. Magnetic resonance (MR) and contrast-enhanced ultrasonography (CEUS) imaging may demonstrate findings that are not depicted at CT, and there may not always be a clear correlation between the findings...... at MR and CEUS imaging and those at CT. PURPOSE: To compare diagnostic accuracy of MR, CEUS, and CT when categorizing complex renal cystic masses according to the Bosniak classification. MATERIAL AND METHODS: From February 2011 to June 2012, 46 complex renal cysts were prospectively evaluated by...... three readers. Each mass was categorized according to the Bosniak classification and CT was chosen as gold standard. Kappa was calculated for diagnostic accuracy and data was compared with pathological results. RESULTS: CT images found 27 BII, six BIIF, seven BIII, and six BIV. Forty-three cysts could...

  11. Acoustic classification of dwellings

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2014-01-01

    Schemes for the classification of dwellings according to different building performances have been proposed in the last years worldwide. The general idea behind these schemes relates to the positive impact a higher label, and thus a better performance, should have. In particular, focusing on sound...... insulation performance, national schemes for sound classification of dwellings have been developed in several European countries. These schemes define acoustic classes according to different levels of sound insulation. Due to the lack of coordination among countries, a significant diversity in terms of...... descriptors, number of classes, and class intervals occurred between national schemes. However, a proposal “acoustic classification scheme for dwellings” has been developed recently in the European COST Action TU0901 with 32 member countries. This proposal has been accepted as an ISO work item. This paper...

  12. Classification problem in CBIR

    OpenAIRE

    Tatiana Jaworska

    2013-01-01

    At present a great deal of research is being done in different aspects of Content-Based Im-age Retrieval (CBIR). Image classification is one of the most important tasks in image re-trieval that must be dealt with. The primary issue we have addressed is: how can the fuzzy set theory be used to handle crisp image data. We propose fuzzy rule-based classification of image objects. To achieve this goal we have built fuzzy rule-based classifiers for crisp data. In this paper we present the results ...

  13. Classification of syringomyelia.

    Science.gov (United States)

    Milhorat, T H

    2000-01-01

    Syringomyelia poses special challenges for the clinician because of its complex symptomatology, uncertain pathogenesis, and multiple options of treatment. The purpose of this study was to classify intramedullary cavities according to their most salient pathological and clinical features. Pathological findings obtained in 175 individuals with tubular cavitations of the spinal cord were correlated with clinical and magnetic resonance (MR) imaging findings in a database of 927 patients. A classification system was developed in which the morbid anatomy, cause, and pathogenesis of these lesions are emphasized. The use of a disease-based classification of syringomyelia facilitates diagnosis and the interpretation of MR imaging findings and provides a guide to treatment. PMID:16676921

  14. Classification des rongeurs

    OpenAIRE

    Mignon, Jacques; Hardouin, Jacques

    2003-01-01

    Les lecteurs du Bulletin BEDIM semblent parfois avoir des difficultés avec la classification scientifique des animaux connus comme "rongeurs" dans le langage courant. Vu les querelles existant encore aujourd'hui dans la mise en place de cette classification, nous ne nous en étonnerons guère. La brève synthèse qui suit concerne les animaux faisant ou susceptibles de faire partie du mini-élevage. The note aims at providing the main characteristics of the principal families of rodents relevan...

  15. Pitch Based Sound Classification

    DEFF Research Database (Denmark)

    Nielsen, Andreas Brinch; Hansen, Lars Kai; Kjems, U

    2006-01-01

    A sound classification model is presented that can classify signals into music, noise and speech. The model extracts the pitch of the signal using the harmonic product spectrum. Based on the pitch estimate and a pitch error measure, features are created and used in a probabilistic model with soft...

  16. Shark Teeth Classification

    Science.gov (United States)

    Brown, Tom; Creel, Sally; Lee, Velda

    2009-01-01

    On a recent autumn afternoon at Harmony Leland Elementary in Mableton, Georgia, students in a fifth-grade science class investigated the essential process of classification--the act of putting things into groups according to some common characteristics or attributes. While they may have honed these skills earlier in the week by grouping their own…

  17. Classification system: Netherlands

    NARCIS (Netherlands)

    Hartemink, A.E.

    2006-01-01

    Although people have always classified soils, it is only since the mid 19th century that soil classification emerged as an important topic within soil science. It forced soil scientists to think systematically about soils and its genesis and developed to facilitate communication between soil scienti

  18. Text document classification

    Czech Academy of Sciences Publication Activity Database

    Novovičová, Jana

    č. 62 (2005), s. 53-54. ISSN 0926-4981 R&D Projects: GA AV ČR IAA2075302; GA AV ČR KSK1019101; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : document representation * categorization * classification Subject RIV: BD - Theory of Information

  19. Automated Stellar Spectral Classification

    Science.gov (United States)

    Bailer-Jones, Coryn; Irwin, Mike; von Hippel, Ted

    1996-05-01

    Stellar classification has long been a useful tool for probing important astrophysical phenomena. Beyond simply categorizing stars it yields fundamental stellar parameters, acts as a probe of galactic abundance distributions and gives a first foothold on the cosmological distance ladder. The MK system in particular has survived on account of its robustness to changes in the calibrations of the physical parameters. Nonetheless, if stellar classification is to continue as a useful tool in stellar surveys, then it must adapt to keep pace with the large amounts of data which will be acquired as magnitude limits are pushed ever deeper. We are working on a project to automate the multi-parameter classification of visual stellar spectra, using artificial neural networks and other techniques. Our techniques have been developed with 10,000 spectra (B Analysis as a front-end compression of the data. Our continuing work also looks at the application of synthetic spectra to the direct classification of spectra in terms of the physical parameters of Teff, log g, and [Fe/H].

  20. Classification of waste packages

    Energy Technology Data Exchange (ETDEWEB)

    Mueller, H.P.; Sauer, M.; Rojahn, T. [Versuchsatomkraftwerk GmbH, Kahl am Main (Germany)

    2001-07-01

    A barrel gamma scanning unit has been in use at the VAK for the classification of radioactive waste materials since 1998. The unit provides the facility operator with the data required for classification of waste barrels. Once these data have been entered into the AVK data processing system, the radiological status of raw waste as well as pre-treated and processed waste can be tracked from the point of origin to the point at which the waste is delivered to a final storage. Since the barrel gamma scanning unit was commissioned in 1998, approximately 900 barrels have been measured and the relevant data required for classification collected and analyzed. Based on the positive results of experience in the use of the mobile barrel gamma scanning unit, the VAK now offers the classification of barrels as a service to external users. Depending upon waste quantity accumulation, this measurement unit offers facility operators a reliable and time-saving and cost-effective means of identifying and documenting the radioactivity inventory of barrels scheduled for final storage. (orig.)

  1. The Classification Conundrum.

    Science.gov (United States)

    Granger, Charles R.

    1983-01-01

    Argues against the five-kingdom scheme of classification as using inconsistent criteria, ending up with divisions that are forced, not natural. Advocates an approach using cell type/complexity and modification of the metabolic machinery, recommending the five-kingdom scheme as starting point for class discussion on taxonomy and its conceptual…

  2. Improving Student Question Classification

    Science.gov (United States)

    Heiner, Cecily; Zachary, Joseph L.

    2009-01-01

    Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to provide automated tutorial responses is a challenging problem. This paper analyzes 411 questions from an introductory Java programming course by reducing the natural…

  3. Classifications in popular music

    NARCIS (Netherlands)

    A. van Venrooij; V. Schmutz

    2015-01-01

    The categorical system of popular music, such as genre categories, is a highly differentiated and dynamic classification system. In this article we present work that studies different aspects of these categorical systems in popular music. Following the work of Paul DiMaggio, we focus on four questio

  4. Dynamic Latent Classification Model

    DEFF Research Database (Denmark)

    Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre;

    possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics in...

  5. Classification of myocardial infarction

    DEFF Research Database (Denmark)

    Saaby, Lotte; Poulsen, Tina Svenstrup; Hosbond, Susanne Elisabeth;

    2013-01-01

    The classification of myocardial infarction into 5 types was introduced in 2007 as an important component of the universal definition. In contrast to the plaque rupture-related type 1 myocardial infarction, type 2 myocardial infarction is considered to be caused by an imbalance between demand and...

  6. [Classification of primary bone tumors].

    Science.gov (United States)

    Dominok, G W; Frege, J

    1986-01-01

    An expanded classification for bone tumors is presented based on the well known international classification as well as earlier systems. The current status and future trends in this area are discussed. PMID:3461626

  7. Multiple Sparse Representations Classification.

    Science.gov (United States)

    Plenge, Esben; Klein, Stefan; Klein, Stefan S; Niessen, Wiro J; Meijering, Erik

    2015-01-01

    Sparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In this empirical study we propose to further leverage the redundancy of the learned dictionaries to achieve a more accurate classifier. In conventional SRC, each image pixel is associated with a small patch surrounding it. Using these patches, a dictionary is trained for each class in a supervised fashion. Commonly, redundant/overcomplete dictionaries are trained and image patches are sparsely represented by a linear combination of only a few of the dictionary elements. Given a set of trained dictionaries, a new patch is sparse coded using each of them, and subsequently assigned to the class whose dictionary yields the minimum residual energy. We propose a generalization of this scheme. The method, which we call multiple sparse representations classification (mSRC), is based on the observation that an overcomplete, class specific dictionary is capable of generating multiple accurate and independent estimates of a patch belonging to the class. So instead of finding a single sparse representation of a patch for each dictionary, we find multiple, and the corresponding residual energies provides an enhanced statistic which is used to improve classification. We demonstrate the efficacy of mSRC for three example applications: pixelwise classification of texture images, lumen segmentation in carotid artery magnetic resonance imaging (MRI), and bifurcation point detection in carotid artery MRI. We compare our method with conventional SRC, K-nearest neighbor, and support vector machine classifiers. The results show that mSRC outperforms SRC and the other reference methods. In addition, we present an extensive evaluation of the effect of the main mSRC parameters: patch size, dictionary size, and

  8. Efficient Fingercode Classification

    Science.gov (United States)

    Sun, Hong-Wei; Law, Kwok-Yan; Gollmann, Dieter; Chung, Siu-Leung; Li, Jian-Bin; Sun, Jia-Guang

    In this paper, we present an efficient fingerprint classification algorithm which is an essential component in many critical security application systems e. g. systems in the e-government and e-finance domains. Fingerprint identification is one of the most important security requirements in homeland security systems such as personnel screening and anti-money laundering. The problem of fingerprint identification involves searching (matching) the fingerprint of a person against each of the fingerprints of all registered persons. To enhance performance and reliability, a common approach is to reduce the search space by firstly classifying the fingerprints and then performing the search in the respective class. Jain et al. proposed a fingerprint classification algorithm based on a two-stage classifier, which uses a K-nearest neighbor classifier in its first stage. The fingerprint classification algorithm is based on the fingercode representation which is an encoding of fingerprints that has been demonstrated to be an effective fingerprint biometric scheme because of its ability to capture both local and global details in a fingerprint image. We enhance this approach by improving the efficiency of the K-nearest neighbor classifier for fingercode-based fingerprint classification. Our research firstly investigates the various fast search algorithms in vector quantization (VQ) and the potential application in fingerprint classification, and then proposes two efficient algorithms based on the pyramid-based search algorithms in VQ. Experimental results on DB1 of FVC 2004 demonstrate that our algorithms can outperform the full search algorithm and the original pyramid-based search algorithms in terms of computational efficiency without sacrificing accuracy.

  9. Oral epithelial dysplasia classification systems

    DEFF Research Database (Denmark)

    Warnakulasuriya, S; Reibel, J; Bouquot, J;

    2008-01-01

    report, we review the oral epithelial dysplasia classification systems. The three classification schemes [oral epithelial dysplasia scoring system, squamous intraepithelial neoplasia and Ljubljana classification] were presented and the Working Group recommended epithelial dysplasia grading for routine....... Several studies have shown great interexaminer and intraexaminer variability in the assessment of the presence or absence and the grade of oral epithelial dysplasia. The Working Group considered the two class classification (no/questionable/ mild - low risk; moderate or severe - implying high risk) and...

  10. The paradox of atheoretical classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2016-01-01

    sometimes termed “descriptive” classifications). Paradoxically atheoretical classifications may be very successful. The best example of a successful “atheoretical” classification is probably the prestigious Diagnostic and Statistical Manual of Mental Disorders (DSM) since its third edition from 1980. On the...

  11. Etiologic Classification in Ischemic Stroke

    OpenAIRE

    Hakan Ay

    2011-01-01

    Ischemic stroke is an etiologically heterogenous disorder. Classification of ischemic stroke etiology into categories with discrete phenotypic, therapeutic, and prognostic features is indispensible to generate consistent information from stroke research. In addition, a functional classification of stroke etiology is critical to ensure unity among physicians and comparability among studies. There are two major approaches to etiologic classification in stroke. Phenotypic systems define subtypes...

  12. Sound classification of dwellings

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2012-01-01

    needed, and a European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions", has been established and runs 2009-2013, one of the main objectives being to prepare a proposal for a European sound classification scheme with a number of quality......National schemes for sound classification of dwellings exist in more than ten countries in Europe, typically published as national standards. The schemes define quality classes reflecting different levels of acoustical comfort. Main criteria concern airborne and impact sound insulation between...... dwellings, facade sound insulation and installation noise. The schemes have been developed, implemented and revised gradually since the early 1990s. However, due to lack of coordination between countries, there are significant discrepancies, and new standards and revisions continue to increase the diversity...

  13. Soil Classification Using GATree

    CERN Document Server

    Bhargavi, P

    2010-01-01

    This paper details the application of a genetic programming framework for classification of decision tree of Soil data to classify soil texture. The database contains measurements of soil profile data. We have applied GATree for generating classification decision tree. GATree is a decision tree builder that is based on Genetic Algorithms (GAs). The idea behind it is rather simple but powerful. Instead of using statistic metrics that are biased towards specific trees we use a more flexible, global metric of tree quality that try to optimize accuracy and size. GATree offers some unique features not to be found in any other tree inducers while at the same time it can produce better results for many difficult problems. Experimental results are presented which illustrate the performance of generating best decision tree for classifying soil texture for soil data set.

  14. Short Text Classification: A Survey

    Directory of Open Access Journals (Sweden)

    Ge Song

    2014-05-01

    Full Text Available With the recent explosive growth of e-commerce and online communication, a new genre of text, short text, has been extensively applied in many areas. So many researches focus on short text mining. It is a challenge to classify the short text owing to its natural characters, such as sparseness, large-scale, immediacy, non-standardization. It is difficult for traditional methods to deal with short text classification mainly because too limited words in short text cannot represent the feature space and the relationship between words and documents. Several researches and reviews on text classification are shown in recent times. However, only a few of researches focus on short text classification. This paper discusses the characters of short text and the difficulty of short text classification. Then we introduce the existing popular works on short text classifiers and models, including short text classification using sematic analysis, semi-supervised short text classification, ensemble short text classification, and real-time classification. The evaluations of short text classification are analyzed in our paper. Finally we summarize the existing classification technology and prospect for development trend of short text classification

  15. Estuary Classification Revisited

    OpenAIRE

    Guha, Anirban; Lawrence, Gregory A.

    2012-01-01

    This paper presents the governing equations of a tidally-averaged, width-averaged, rectangular estuary in completely nondimensionalized forms. Subsequently, we discover that the dynamics of an estuary is entirely controlled by only two variables: (i) the Estuarine Froude number, and (ii) a nondimensional number related to the Estuarine Aspect ratio and the Tidal Froude number. Motivated by this new observation, the problem of estuary classification is re-investigated. Our analysis shows that ...

  16. Classification of Arabic Documents

    OpenAIRE

    Elbery, Ahmed

    2012-01-01

    Arabic language is a very rich language with complex morphology, so it has a very different and difficult structure than other languages. So it is important to build an Arabic Text Classifier (ATC) to deal with this complex language. The importance of text or document classification comes from its wide variety of application domains such as text indexing, document sorting, text filtering, and Web page categorization. Due to the immense amount of Arabic documents as well as the number of inter...

  17. Qatar content classification

    OpenAIRE

    Handosa, Mohamed

    2014-01-01

    Short title: Qatar content classification. Long title: Develop methods and software for classifying Arabic texts into a taxonomy using machine learning. Contact person and their contact information: Tarek Kanan, . Project description: Starting 4/1/2012, and running through 12/31/2015, is a project to advance digital libraries in the country of Qatar. This is led by VT, but also involves Penn State, Texas A&M, and Qatar University. Tarek is a GRA on this effort. His di...

  18. Maximum mutual information regularized classification

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-09-07

    In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

  19. Classification of Meteorological Drought

    Institute of Scientific and Technical Information of China (English)

    Zhang Qiang; Zou Xukai; Xiao Fengjin; Lu Houquan; Liu Haibo; Zhu Changhan; An Shunqing

    2011-01-01

    Background The national standard of the Classification of Meteorological Drought (GB/T 20481-2006) was developed by the National Climate Center in cooperation with Chinese Academy of Meteorological Sciences,National Meteorological Centre and Department of Forecasting and Disaster Mitigation under the China Meteorological Administration (CMA),and was formally released and implemented in November 2006.In 2008,this Standard won the second prize of the China Standard Innovation and Contribution Awards issued by SAC.Developed through independent innovation,it is the first national standard published to monitor meteorological drought disaster and the first standard in China and around the world specifying the classification of drought.Since its release in 2006,the national standard of Classification of Meteorological Drought has been used by CMA as the operational index to monitor and drought assess,and gradually used by provincial meteorological sureaus,and applied to the drought early warning release standard in the Methods of Release and Propagation of Meteorological Disaster Early Warning Signal.

  20. Histologic classification of gliomas.

    Science.gov (United States)

    Perry, Arie; Wesseling, Pieter

    2016-01-01

    Gliomas form a heterogeneous group of tumors of the central nervous system (CNS) and are traditionally classified based on histologic type and malignancy grade. Most gliomas, the diffuse gliomas, show extensive infiltration in the CNS parenchyma. Diffuse gliomas can be further typed as astrocytic, oligodendroglial, or rare mixed oligodendroglial-astrocytic of World Health Organization (WHO) grade II (low grade), III (anaplastic), or IV (glioblastoma). Other gliomas generally have a more circumscribed growth pattern, with pilocytic astrocytomas (WHO grade I) and ependymal tumors (WHO grade I, II, or III) as the most frequent representatives. This chapter provides an overview of the histology of all glial neoplasms listed in the WHO 2016 classification, including the less frequent "nondiffuse" gliomas and mixed neuronal-glial tumors. For multiple decades the histologic diagnosis of these tumors formed a useful basis for assessment of prognosis and therapeutic management. However, it is now fully clear that information on the molecular underpinnings often allows for a more robust classification of (glial) neoplasms. Indeed, in the WHO 2016 classification, histologic and molecular findings are integrated in the definition of several gliomas. As such, this chapter and Chapter 6 are highly interrelated and neither should be considered in isolation. PMID:26948349

  1. Neuromuscular disease classification system

    Science.gov (United States)

    Sáez, Aurora; Acha, Begoña; Montero-Sánchez, Adoración; Rivas, Eloy; Escudero, Luis M.; Serrano, Carmen

    2013-06-01

    Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns.

  2. On the Classification of Psychology in General Library Classification Schemes.

    Science.gov (United States)

    Soudek, Miluse

    1980-01-01

    Holds that traditional library classification systems are inadequate to handle psychological literature, and advocates the establishment of new theoretical approaches to bibliographic organization. (FM)

  3. SPORT FOOD ADDITIVE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    I. P. Prokopenko

    2015-01-01

    Full Text Available Correctly organized nutritive and pharmacological support is an important component of an athlete's preparation for competitions, an optimal shape maintenance, fast recovery and rehabilitation after traumas and defatigation. Special products of enhanced biological value (BAS for athletes nutrition are used with this purpose. Easy-to-use energy sources are administered into athlete's organism, yielded materials and biologically active substances which regulate and activate exchange reactions which proceed with difficulties during certain physical trainings. The article presents sport supplements classification which can be used before warm-up and trainings, after trainings and in competitions breaks.

  4. Classification of Emergency Scenarios

    CERN Document Server

    Muench, Mathieu

    2011-01-01

    In most of today's emergency scenarios information plays a crucial role. Therefore, information has to be constantly collected and shared among all rescue team members and this requires new innovative technologies. In this paper a classification of emergency scenarios is presented, describing their special characteristics and common strategies employed by rescue units to handle them. Based on interviews with professional firefighters, requirements for new systems are listed. The goal of this article is to support developers designing new systems by providing them a deeper look into the work of first responders.

  5. Classification of hand eczema

    DEFF Research Database (Denmark)

    Agner, T; Aalto-Korte, K; Andersen, K E;

    2015-01-01

    recruited from nine different tertiary referral centres. All patients underwent examination by specialists in dermatology and were checked using relevant allergy testing. Patients were classified into one of the six diagnostic subgroups of HE: allergic contact dermatitis, irritant contact dermatitis, atopic......%) could not be classified. 38% had one additional diagnosis and 26% had two or more additional diagnoses. Eczema on feet was found in 30% of the patients, statistically significantly more frequently associated with hyperkeratotic and vesicular endogenous eczema. CONCLUSION: We find that the classification...

  6. Classification of smooth Fano polytopes

    DEFF Research Database (Denmark)

    Øbro, Mikkel

    A simplicial lattice polytope containing the origin in the interior is called a smooth Fano polytope, if the vertices of every facet is a basis of the lattice. The study of smooth Fano polytopes is motivated by their connection to toric varieties. The thesis concerns the classification of smooth...... Fano polytopes up to isomorphism. A smooth Fano -polytope can have at most vertices. In case of vertices an explicit classification is known. The thesis contains the classification in case of vertices. Classifications of smooth Fano -polytopes for fixed exist only for . In the thesis an algorithm for...... the classification of smooth Fano -polytopes for any given is presented. The algorithm has been implemented and used to obtain the complete classification for ....

  7. Active Learning for Text Classification

    OpenAIRE

    Hu, Rong

    2011-01-01

    Text classification approaches are used extensively to solve real-world challenges. The success or failure of text classification systems hangs on the datasets used to train them, without a good dataset it is impossible to build a quality system. This thesis examines the applicability of active learning in text classification for the rapid and economical creation of labelled training data. Four main contributions are made in this thesis. First, we present two novel selection strategies to cho...

  8. Random Forests for Poverty Classification

    OpenAIRE

    Ruben Thoplan

    2014-01-01

    This paper applies a relatively novel method in data mining to address the issue of poverty classification in Mauritius. The random forests algorithm is applied to the census data in view of improving classification accuracy for poverty status. The analysis shows that the numbers of hours worked, age, education and sex are the most important variables in the classification of the poverty status of an individual. In addition, a clear poverty-gender gap is identified as women have higher chance...

  9. The Revised Classification of Eukaryotes

    OpenAIRE

    Adl, Sina M; Simpson, Alastair G.B.; Lane, Christopher E.; Lukeš, Julius; Bass, David; Bowser, Samuel S.; Brown, Matthew W.; Burki, Fabien; Dunthorn, Micah; Hampl, Vladimir; Heiss, Aaron; Hoppenrath, Mona; Lara, Enrique; Le Gall, Line; Lynn, Denis H.

    2013-01-01

    This revision of the classification of eukaryotes, which updates that of Adl et al. [J. Eukaryot. Microbiol. 52 (2005) 399], retains an emphasis on the protists and incorporates changes since 2005 that have resolved nodes and branches in phylogenetic trees. Whereas the previous revision was successful in re-introducing name stability to the classification, this revision provides a classification for lineages that were then still unresolved. The supergroups have withstood phylogenetic hypothes...

  10. DCC Briefing Paper: Genre classification

    OpenAIRE

    Abbott, Daisy; Kim, Yunhyong

    2008-01-01

    Genre classification is the process of grouping objects together based on defined similarities such as subject, format, style, or purpose. Genre classification as a means of managing information is already established in music (e.g. folk, blues, jazz) and text and is used, alongside topic classification, to organise materials in the commercial sector (the children's section of a bookshop) and intellectually (for example, in the Usenet newsgroup directory hierarchy). However, in the case o...

  11. Classification and Labelling for Biocides

    OpenAIRE

    Rubbiani, Maristella

    2015-01-01

    CLP and biocides The EU Regulation (EC) No 1272/2008 on Classification, Labelling and Packaging of Substances and Mixtures, the CLP-Regulation, entered into force on 20th January, 2009. Since 1st December, 2010 the classification, labelling and packaging of substances has to comply with this Regulation. For mixtures, the rules of this Regulation are mandatory from 1st June, 2015; this means that until this date classification, labelling and packaging could either be carried out according to D...

  12. Classification & Structure of Blood Vessels

    Science.gov (United States)

    ... Thyroid & Parathyroid Glands Adrenal Gland Pancreas Gonads Other Endocrine Glands Review Quiz Cardiovascular System Heart Structure of the Heart Physiology of the Heart Blood Classification & Structure of Blood ...

  13. 78 FR 68983 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-11-18

    ...-Doxey data into the cotton futures classification process in March 2012 (77 FR 5379). When verified by a... October 9, 2013 (78 FR 54970). AMS received two comments: one from a national trade organization... Agricultural Marketing Service 7 CFR Part 27 RIN 0581-AD33 Cotton Futures Classification:...

  14. 78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-09-09

    ... process in March 2012 (77 FR 5379). When verified by a futures classification, Smith-Doxey data serves as...; ] DEPARTMENT OF AGRICULTURE Agricultural Marketing Service 7 CFR Part 27 RIN 0581-AD33 Cotton Futures... for the addition of an optional cotton futures classification procedure--identified and known...

  15. 14 CFR 1203.412 - Classification guides.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Classification guides. 1203.412 Section 1203.412 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION INFORMATION SECURITY PROGRAM Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification...

  16. 22 CFR 9.4 - Original classification.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Original classification. 9.4 Section 9.4... classification. (a) Definition. Original classification is the initial determination that certain information... classification. (b) Classification levels. (1) Top Secret shall be applied to information the...

  17. 22 CFR 9.6 - Derivative classification.

    Science.gov (United States)

    2010-04-01

    ... CFR 2001.22. (c) Department of State Classification Guide. The Department of State Classification... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Derivative classification. 9.6 Section 9.6... classification. (a) Definition. Derivative classification is the incorporating, paraphrasing, restating...

  18. 32 CFR 2400.15 - Classification guides.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Classification guides. 2400.15 Section 2400.15... Derivative Classification § 2400.15 Classification guides. (a) OSTP shall issue and maintain classification guides to facilitate the proper and uniform derivative classification of information. These guides...

  19. 15 CFR 2008.9 - Classification guides.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false Classification guides. 2008.9 Section... REPRESENTATIVE Derivative Classification § 2008.9 Classification guides. Classification guides shall be issued by... direct derivative classification, shall identify the information to be protected in specific and...

  20. Seismic texture classification. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Vinther, R.

    1997-12-31

    The seismic texture classification method, is a seismic attribute that can both recognize the general reflectivity styles and locate variations from these. The seismic texture classification performs a statistic analysis for the seismic section (or volume) aiming at describing the reflectivity. Based on a set of reference reflectivities the seismic textures are classified. The result of the seismic texture classification is a display of seismic texture categories showing both the styles of reflectivity from the reference set and interpolations and extrapolations from these. The display is interpreted as statistical variations in the seismic data. The seismic texture classification is applied to seismic sections and volumes from the Danish North Sea representing both horizontal stratifications and salt diapers. The attribute succeeded in recognizing both general structure of successions and variations from these. Also, the seismic texture classification is not only able to display variations in prospective areas (1-7 sec. TWT) but can also be applied to deep seismic sections. The seismic texture classification is tested on a deep reflection seismic section (13-18 sec. TWT) from the Baltic Sea. Applied to this section the seismic texture classification succeeded in locating the Moho, which could not be located using conventional interpretation tools. The seismic texture classification is a seismic attribute which can display general reflectivity styles and deviations from these and enhance variations not found by conventional interpretation tools. (LN)

  1. Estuary Classification Revisited

    CERN Document Server

    Guha, Anirban

    2012-01-01

    The governing equations of a tidally averaged, width averaged, rectangular estuary has been investigated. It's theoretically shown that the dynamics of an estuary is entirely controlled by three parameters: (i) the Estuarine Froude number, (ii) the Tidal Froude number and (iii) the Estuarine Aspect ratio. The momentum, salinity and integral salt balance equations can be completely expressed in terms of these control variables. The estuary classification problem has also been reinvestigated. It's found that these three control variables can completely specify the estuary type. Comparison with real estuary data shows very good match. Additionally, we show that the well accepted leading order estuarine integral salt balance equation is inconsitent with the leading order salinity equation in an order of magnitude sense.

  2. Classification of enterprise expenditures

    Directory of Open Access Journals (Sweden)

    Tatiana Ostapenko

    2013-05-01

    Full Text Available The need to diversify share of costs is grounded. It is proposed to classify expenditures by types of income (loss of current activity (covered and uncovered expenditures, by the level of costs to its planned size (planned cost; costs that exceed the planned size; costs that are lower than the planned size, with the aim to influence the activity result (effective and ineffective expenditures, by the period of their appearance (intermediate and annual expenditures.The existing classification of expenditures by kinds of activity is improved through emphasizing such feature: by ability to increase enterprise cost (essential and unessential expenditures. The traditional definition of exhausted (consumed and unexhausted (not consumed expenditures that helped to separate expenses in their structure which don’t ensure formation of exhausted and unexhausted expenditures (management costs is criticized

  3. Nonlinear estimation and classification

    CERN Document Server

    Hansen, Mark; Holmes, Christopher; Mallick, Bani; Yu, Bin

    2003-01-01

    Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data This is due in part to recent advances in data collection and computing technologies As a result, fundamental statistical research is being undertaken in a variety of different fields Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future

  4. Classification of radioactive waste

    International Nuclear Information System (INIS)

    Radioactive wastes are generated in a number of different kinds of facilities and arise in a wide range of concentrations of radioactive materials and in a variety of physical and chemical forms. To simplify their management, a number of schemes have evolved for classifying radioactive waste according to the physical, chemical and radiological properties of significance to those facilities managing this waste. These schemes have led to a variety of terminologies, differing from country to country and even between facilities in the same country. This situation makes it difficult for those concerned to communicate with one another regarding waste management practices. This document revises and updates earlier IAEA references on radioactive waste classification systems given in IAEA Technical Reports Series and Safety Series. Guidance regarding exemption of materials from regulatory control is consistent with IAEA Safety Series and the RADWASS documents published under IAEA Safety Series. 11 refs, 2 figs, 2 tab

  5. Classification-based reasoning

    Science.gov (United States)

    Gomez, Fernando; Segami, Carlos

    1991-01-01

    A representation formalism for N-ary relations, quantification, and definition of concepts is described. Three types of conditions are associated with the concepts: (1) necessary and sufficient properties, (2) contingent properties, and (3) necessary properties. Also explained is how complex chains of inferences can be accomplished by representing existentially quantified sentences, and concepts denoted by restrictive relative clauses as classification hierarchies. The representation structures that make possible the inferences are explained first, followed by the reasoning algorithms that draw the inferences from the knowledge structures. All the ideas explained have been implemented and are part of the information retrieval component of a program called Snowy. An appendix contains a brief session with the program.

  6. Predictive Classification Trees

    Science.gov (United States)

    Dlugosz, Stephan; Müller-Funk, Ulrich

    CART (Breiman et al., Classification and Regression Trees, Chapman and Hall, New York, 1984) and (exhaustive) CHAID (Kass, Appl Stat 29:119-127, 1980) figure prominently among the procedures actually used in data based management, etc. CART is a well-established procedure that produces binary trees. CHAID, in contrast, admits multiple splittings, a feature that allows to exploit the splitting variable more extensively. On the other hand, that procedure depends on premises that are questionable in practical applications. This can be put down to the fact that CHAID relies on simultaneous Chi-Square- resp. F-tests. The null-distribution of the second test statistic, for instance, relies on the normality assumption that is not plausible in a data mining context. Moreover, none of these procedures - as implemented in SPSS, for instance - take ordinal dependent variables into account. In the paper we suggest an alternative tree-algorithm that: Requires explanatory categorical variables

  7. Classification of Rainbows

    Science.gov (United States)

    Ricard, J. L.; Peter, A. L.; Barckicke, J.

    2015-12-01

    CLASSIFICATION OF RAINBOWS Jean Louis Ricard,1,2,* Peter Adams ,2 and Jean Barckicke 2,3 1CNRM, Météo-France,42 Avenue Gaspard Coriolis, 31057 Toulouse, France 2CEPAL, 148 Himley Road, Dudley, West Midlands DY1 2QH, United Kingdom 3DP/Compas,Météo-France,42 Avenue Gaspard Coriolis, 31057 Toulouse, France *Corresponding author: Dr_Jean_Ricard@yahoo,co,ukRainbows are the most beautiful and most spectacular optical atmospheric phenomenon. Humphreys (1964) pointedly noted that "the "explanations" generally given of the rainbow [ in textbooks] may well be said to explain beautifully that which does not occur, and to leave unexplained which does" . . . "The records of close observations of rainbows soon show that not even the colors are always the same". Textbooks stress that the main factor affecting the aspect of the rainbow is the radius of the water droplets. In his well-known textbook entitled "the nature of light & colour in the open air", Minnaert (1954) gives the chief features of the rainbow depending on the diameter of the drops producing it. For this study, we have gathered hundreds of pictures of primary bows. We sort out the pictures into classes. The classes are defined in a such way that rainbows belonging to the same class look similar. Our results are surprising and do not confirm Minnaert's classification. In practice, the size of the water droplets is only a minor factor controlling the overall aspect of the rainbow. The main factor appears to be the height of the sun above the horizon. At sunset, the width of the red band increases, while the width of the other bands of colours decreases. The orange, the violet, the blue and the green bands disappear completely in this order. At the end, the primary bow is mainly red and slightly yellow. Picture = Contrast-enhanced photograph of a primary bow picture (prepared by Andrew Dunn).

  8. Vietnamese Document Representation and Classification

    Science.gov (United States)

    Nguyen, Giang-Son; Gao, Xiaoying; Andreae, Peter

    Vietnamese is very different from English and little research has been done on Vietnamese document classification, or indeed, on any kind of Vietnamese language processing, and only a few small corpora are available for research. We created a large Vietnamese text corpus with about 18000 documents, and manually classified them based on different criteria such as topics and styles, giving several classification tasks of different difficulty levels. This paper introduces a new syllable-based document representation at the morphological level of the language for efficient classification. We tested the representation on our corpus with different classification tasks using six classification algorithms and two feature selection techniques. Our experiments show that the new representation is effective for Vietnamese categorization, and suggest that best performance can be achieved using syllable-pair document representation, an SVM with a polynomial kernel as the learning algorithm, and using Information gain and an external dictionary for feature selection.

  9. Small-scale classification schemes

    DEFF Research Database (Denmark)

    Hertzum, Morten

    2004-01-01

    important means of discretely balancing the contractual aspect of requirements engineering against facilitating the users in an open-ended search for their system requirements. The requirements classification is analysed in terms of the complementary concepts of boundary objects and coordination mechanisms......Small-scale classification schemes are used extensively in the coordination of cooperative work. This study investigates the creation and use of a classification scheme for handling the system requirements during the redevelopment of a nation-wide information system. This requirements...... classification inherited a lot of its structure from the existing system and rendered requirements that transcended the framework laid out by the existing system almost invisible. As a result, the requirements classification became a defining element of the requirements-engineering process, though its main...

  10. Agriculture classification using POLSAR data

    DEFF Research Database (Denmark)

    Skriver, Henning; Dall, Jørgen; Ferro-Famil, Laurent;

    2005-01-01

    data, and a very important class of algorithms is the knowledge-based approaches. Here, generic characteristics of different cover types are derived by combining physical reasoning with the available empirical evidence. These are then used to define classification rules. Because of their emphasis on...... the physical content of the SAR data they attempt to generate robust, widely applicable methods, which are nonetheless capable of taking local conditions into account. In this paper a classification approach is presented, that uses a knowledge-based approach, where the crops are first classified into...... crops. This part of the classification process is not as well established as the first part, and both a supervised approach and a knowledge-based approach have been evaluated. Both POLSAR and PolInSAR data may be included in the classification scheme. The classification approach has been evaluated using...

  11. On the classification of Yang Mills fields

    International Nuclear Information System (INIS)

    A scheme of Classification for Yang Mills fields analogous to the Petrov Classification in general relativity is discussed. It is also shown how such a classification is used to obtain explicit solutions of the equations of motion. (author)

  12. 75 FR 10529 - Mail Classification Change

    Science.gov (United States)

    2010-03-08

    ... Mail Classification Change AGENCY: Postal Regulatory Commission. ACTION: Notice. SUMMARY: The... Classification Schedule. The change affects a change in terminology. This notice addresses procedural steps....90 et seq. concerning a change in classification which reflects a change in terminology from...

  13. Nonparametric Bayesian Classification

    CERN Document Server

    Coram, M A

    2002-01-01

    A Bayesian approach to the classification problem is proposed in which random partitions play a central role. It is argued that the partitioning approach has the capacity to take advantage of a variety of large-scale spatial structures, if they are present in the unknown regression function $f_0$. An idealized one-dimensional problem is considered in detail. The proposed nonparametric prior uses random split points to partition the unit interval into a random number of pieces. This prior is found to provide a consistent estimate of the regression function in the $\\L^p$ topology, for any $1 \\leq p < \\infty$, and for arbitrary measurable $f_0:[0,1] \\rightarrow [0,1]$. A Markov chain Monte Carlo (MCMC) implementation is outlined and analyzed. Simulation experiments are conducted to show that the proposed estimate compares favorably with a variety of conventional estimators. A striking resemblance between the posterior mean estimate and the bagged CART estimate is noted and discussed. For higher dimensions, a ...

  14. Classification of titanium dioxide

    International Nuclear Information System (INIS)

    In this work the X-ray diffraction (XRD), Scanning Electron Microscopy (Sem) and the X-ray Dispersive Energy Spectroscopy techniques are used with the purpose to achieve a complete identification of phases and mixture of phases of a crystalline material as titanium dioxide. The problem for solving consists of being able to distinguish a sample of titanium dioxide being different than a titanium dioxide pigment. A standard sample of titanium dioxide with NIST certificate is used, which indicates a purity of 99.74% for the TiO2. The following way is recommended to proceed: a)To make an analysis by means of X-ray diffraction technique to the sample of titanium dioxide pigment and on the standard of titanium dioxide waiting not find differences. b) To make a chemical analysis by the X-ray Dispersive Energy Spectroscopy via in a microscope, taking advantage of the high vacuum since it is oxygen which is analysed and if it is concluded that the aluminium oxide appears in a greater proportion to 1% it is established that is a titanium dioxide pigment, but if it is lesser then it will be only titanium dioxide. This type of analysis is an application of the nuclear techniques useful for the tariff classification of merchandise which is considered as of difficult recognition. (Author)

  15. Aircraft Operations Classification System

    Science.gov (United States)

    Harlow, Charles; Zhu, Weihong

    2001-01-01

    Accurate data is important in the aviation planning process. In this project we consider systems for measuring aircraft activity at airports. This would include determining the type of aircraft such as jet, helicopter, single engine, and multiengine propeller. Some of the issues involved in deploying technologies for monitoring aircraft operations are cost, reliability, and accuracy. In addition, the system must be field portable and acceptable at airports. A comparison of technologies was conducted and it was decided that an aircraft monitoring system should be based upon acoustic technology. A multimedia relational database was established for the study. The information contained in the database consists of airport information, runway information, acoustic records, photographic records, a description of the event (takeoff, landing), aircraft type, and environmental information. We extracted features from the time signal and the frequency content of the signal. A multi-layer feed-forward neural network was chosen as the classifier. Training and testing results were obtained. We were able to obtain classification results of over 90 percent for training and testing for takeoff events.

  16. Classification and Phylogenetics of Myxozoa

    Czech Academy of Sciences Publication Activity Database

    Fiala, Ivan; Bartošová-Sojková, Pavla; Whipps, C. M.

    Cham: Springer International Publishing, 2015 - (Okamura, B.; Gruhl, A.; Bartholomew, J.), s. 85-110 ISBN 978-3-319-14752-9 Institutional support: RVO:60077344 Keywords : Taxonomy * Classification * Myxosporea * Actinosporea * Spore * Phylogeny Subject RIV: EG - Zoology

  17. Text Classification using Artificial Intelligence

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    Text classification is the process of classifying documents into predefined categories based on their content. It is the automated assignment of natural language texts to predefined categories. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, and text understanding systems, which transform text in some way such as producing summaries, answering questions or extracting data. Existing supervised learning algorithms for classifying text need sufficient documents to learn accurately. This paper presents a new algorithm for text classification using artificial intelligence technique that requires fewer documents for training. Instead of using words, word relation i.e. association rules from these words is used to derive feature set from pre-classified text documents. The concept of na\\"ive Bayes classifier is then used on derived features and finally only a single concept of genetic algorithm has been added for final classification. A syste...

  18. CLASSIFICATION FRAMEWORK FOR COASTAL SYSTEMS

    Science.gov (United States)

    U.S. Environmental Protection Agency. Classification Framework for Coastal Systems. EPA/600/R-04/061. U.S. Environmental Protection Agency, National Health and Environmental Effects Research Laboratory, Atlantic Ecology Division, Narragansett, RI, Gulf Ecology Division, Gulf Bree...

  19. Classification of Building Object Types

    DEFF Research Database (Denmark)

    Jørgensen, Kaj Asbjørn

    2011-01-01

    Development of the existing classification systems has been very difficult and time consuming tasks, where many considerations have been taken and many compromises have been made. The results reveal that, although the theoretical foundation was clarified, many deviations and shortcuts have been...... made. This is certainly the case in the Danish development. Based on the theories about these abstraction mechanisms, the basic principles for classification systems are presented and the observed misconceptions are analyses and explained. Furthermore, it is argued that the purpose of classification...... systems has changed and that new opportunities should be explored. Some proposals for new applications are presented and carefully aligned with IT opportunities. Especially, the use of building modelling will give new benefits and many of the traditional uses of classification systems will instead be...

  20. Classification of Magnetic Nanoparticle Systems

    DEFF Research Database (Denmark)

    Bogren, Sara; Fornara, Andrea; Ludwig, Frank;

    2015-01-01

    This study presents classification of different magnetic single- and multi-core particle systems using their measured dynamic magnetic properties together with their nanocrystal and particle sizes. The dynamic magnetic properties are measured with AC (dynamical) susceptometry and magnetorelaxometry...

  1. The classification on short message

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    This paper discusses the importance of the classification of short message, and details some key technologies related. Through implementing a fundamental prototype, some basic models and technical references are provided.

  2. Biogeography based Satellite Image Classification

    CERN Document Server

    Panchal, V K; Kaur, Navdeep; Kundra, Harish

    2009-01-01

    Biogeography is the study of the geographical distribution of biological organisms. The mindset of the engineer is that we can learn from nature. Biogeography Based Optimization is a burgeoning nature inspired technique to find the optimal solution of the problem. Satellite image classification is an important task because it is the only way we can know about the land cover map of inaccessible areas. Though satellite images have been classified in past by using various techniques, the researchers are always finding alternative strategies for satellite image classification so that they may be prepared to select the most appropriate technique for the feature extraction task in hand. This paper is focused on classification of the satellite image of a particular land cover using the theory of Biogeography based Optimization. The original BBO algorithm does not have the inbuilt property of clustering which is required during image classification. Hence modifications have been proposed to the original algorithm and...

  3. Text Classification using Data Mining

    CERN Document Server

    Kamruzzaman, S M; Hasan, Ahmed Ryadh

    2010-01-01

    Text classification is the process of classifying documents into predefined categories based on their content. It is the automated assignment of natural language texts to predefined categories. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, and text understanding systems, which transform text in some way such as producing summaries, answering questions or extracting data. Existing supervised learning algorithms to automatically classify text need sufficient documents to learn accurately. This paper presents a new algorithm for text classification using data mining that requires fewer documents for training. Instead of using words, word relation i.e. association rules from these words is used to derive feature set from pre-classified text documents. The concept of Naive Bayes classifier is then used on derived features and finally only a single concept of Genetic Algorithm has been added for final classification. A system based on the...

  4. The future of general classification

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2013-01-01

    Discusses problems related to accessing multiple collections using a single retrieval language. Surveys the concepts of interoperability and switching language. Finds that mapping between more indexing languages always will be an approximation. Surveys the issues related to general classification...

  5. Incremental classification of invoice documents

    OpenAIRE

    Hamza, Hatem; Belaïd, Yolande; Belaïd, Abdel; Chaudhuri, Bidyut Baran

    2008-01-01

    ISBN : 978-1-4244-2174-9 International audience This paper deals with incremental classification and its particular application to invoice classification. An improved version of an already existant incremental neural network called IGNG (Incremental Growing Neural Gas) is used for this purpose . This neural network tries to cover the space of data by adding or deleting neurons as data is fed to the system. The improved version of the IGNG, called I2GNG used local thresholds in order to ...

  6. Focal mechanism estimation by classification

    OpenAIRE

    Lasscock, Ben G.; Hall, Brendon J.; Glinsky, Michael E.

    2014-01-01

    A classification technique for identifying focal mechanism type and fault plane orientation based on the polarity of P-wave "first motion" data is derived. A support vector machine is used to classify the polarity data in the space of spherical harmonic functions. The classification is non-parametric in the sense that there is no requirement to make a priori assumptions source mechanism. A metric of similarity potentially able to distinguish shear versus tensile dislocation without requiring ...

  7. Optimizing classification in intelligence processing

    OpenAIRE

    Costica, Yinon

    2010-01-01

    Approved for public release; distribution is unlimited The intelligence making process, often described as the intelligence cycle, consists of phases. Congestion may be experienced in phases that require time consuming tasks such as translation, processing and analysis. To ameliorate the performance of those timeconsuming phases, a preliminary classification of intelligence items regarding their relevance and value to an intelligence request is performed. This classification is subject to ...

  8. Psychiatric classification and subjective experience

    OpenAIRE

    Cooper, Rachel

    2012-01-01

    This article does not directly consider the feelings and emotions that occur in mental illness. Rather, it concerns a higher level methodological question: To what extent is an analysis of feelings and felt emotions of importance for psychiatric classification? Some claim that producing a phenomenologically informed descriptive psychopathology is a prerequisite for serious taxonomic endeavor. Others think that classifications of mental disorders may ignore subjective experience. A middle view...

  9. Events Classification in Log Audit

    OpenAIRE

    Sabah Al-Fedaghi; Fahad Mahdi

    2010-01-01

    Information security audit is a monitoring/logging mechanism to ensure compliance with regulations and to detect abnormalities, security breaches, and privacy violations; however, auditing too many events causes overwhelming use of system resources and impacts performance. Consequently, a classification of events is used to prioritize events and configure the log system. Rules can be applied according to this classification to make decisions about events to be archived and types of actions in...

  10. Towards Automatic Classification of Neurons

    OpenAIRE

    Armañanzas, Rubén; Ascoli, Giorgio A.

    2015-01-01

    The classification of neurons into types has been much debated since the inception of modern neuroscience. Recent experimental advances are accelerating the pace of data collection. The resulting information growth of morphological, physiological, and molecular properties encourages efforts to automate neuronal classification by powerful machine learning techniques. We review state-of-the-art analysis approaches and availability of suitable data and resources, highlighting prominent challenge...

  11. Eclipsing variables: Catalogue and classification

    OpenAIRE

    Avvakumova, E. A.; Malkov, O. Y.; Kniazev, A. Y.

    2013-01-01

    A new version of the Catalogue of Eclipsing Variables is presented. The catalogue contains parameters and morphological types of light curves for some 7200 stars. Spectral classification is also given when available. Recently published information about classification of 1352 systems is also included in the catalogue. Thus, the catalogue represents the largest list of eclipsing binaries classified from observations. The analysis of stellar parameter distributions of catalogued eclipsing syste...

  12. Unsolvability Cores in Classification Problems

    OpenAIRE

    Walter, Hermann K. -G.; Brandt, Ulrike

    2014-01-01

    Classification problems have been introduced by M. Ziegler as a generalization of promise problems. In this paper we are concerned with solvability and unsolvability questions with respect to a given set or language family, especially with cores of unsolvability. We generalize the results about unsolvability cores in promise problems to classification problems. Our main results are a characterization of unsolvability cores via cohesiveness and existence theorems for such cores in unsolvable c...

  13. Quantum computing for pattern classification

    OpenAIRE

    Schuld, Maria; Sinayskiy, Ilya; Petruccione, Francesco

    2014-01-01

    It is well known that for certain tasks, quantum computing outperforms classical computing. A growing number of contributions try to use this advantage in order to improve or extend classical machine learning algorithms by methods of quantum information theory. This paper gives a brief introduction into quantum machine learning using the example of pattern classification. We introduce a quantum pattern classification algorithm that draws on Trugenberger's proposal for measuring the Hamming di...

  14. Landcover classification: western Kenya, 2010.

    OpenAIRE

    Wardrop, Nicola A.

    2015-01-01

    Landcover classifications were produced for an area of western Kenya based on ASTER (15m spatial resolution) and Landsat (30m spatial resolution) imagery from 2010 and 2011. The land cover classification was carried out in a hierarchical manner, resulting in two overarching classes (a) vegetated land (versus built up and bare ground) and (b) flooding land (versus non-flooding land); and five lower level classes (c) agricultural land and grassland, (d) swamp, (e) trees and shrubs, (f) rice and...

  15. Information Classification on University Websites

    DEFF Research Database (Denmark)

    Nawaz, Ather; Clemmensen, Torkil; Hertzum, Morten

    2011-01-01

    Websites are increasingly used as a medium for providing information to university students. The quality of a university website depends on how well the students’ information classification fits with the structure of the information on the website. This paper investigates the information classifi......Websites are increasingly used as a medium for providing information to university students. The quality of a university website depends on how well the students’ information classification fits with the structure of the information on the website. This paper investigates the information...... classification of 14 Danish and 14 Pakistani students and compares it with the information classification of their university website. Brainstorming, card sorting, and task exploration activities were used to discover similarities and differences in the participating students’ classification of website...... information and their ability to navigate the websites. The results of the study indicate group differences in user classification and related task-performance differences. The main implications of the study are that (a) the edit distance appears a useful measure in cross-country HCI research and practice and...

  16. Information Classification on University Websites

    DEFF Research Database (Denmark)

    Nawaz, Ather; Clemmensen, Torkil; Hertzum, Morten

    2011-01-01

    Websites are increasingly used as a medium for providing information to university students. The quality of a university website depends on how well the students’ information classification fits with the structure of the information on the website. This paper investigates the information classifi......Websites are increasingly used as a medium for providing information to university students. The quality of a university website depends on how well the students’ information classification fits with the structure of the information on the website. This paper investigates the information...... classification of 14 Danish and 14 Pakistani students and compares it with the information classification of their university website. Brainstorming, card sorting, and task exploration activities were used to discover similarities and differences in the participating students’ classification of website...... information and their ability to navigate the websites. The results of the study indicate group differences in user classification and related taskperformance differences. The main implications of the study are that (a) the edit distance appears a useful measure in cross-country HCI research and practice and...

  17. Progression in nuclear classification

    International Nuclear Information System (INIS)

    In this book, summarize the author's achievements of nuclear classification by new method in latest 30 years, new foundational law of nuclear layer in matter world is found. It is explained with a hypothesis of a nucleus which it is made up of two nucleon's clusters with deuteron and triton. Its concrete content is: to advance a new method which analyze data of nuclei with natural abundance using relationship between the numbers of proton and neutron. The relationship of each nucleus increases to 4 sets: S+H=Z H+Z=N Z+N=A and S-H=K. To expand the similarity between proton and neutron to the similarity among p,n, deuteron, triton, and He-5 clusters. According to the distribution law of same kind of nuclei, it obtains that the upper limits of stable region both should be '44s'. New foundational law of nuclear system is 1,2,4,8,16,8,4,2,1. In order to explain new law, a hypothesis which nucleus is made up of deuteron and triton is developing and nuclear field of whole number is built up. And it relates that unity of matter motion, which is the most foundational form atomic nuclear systematic is similar to the most first-class form chromosome numbers of mankind. These achievements will shake the foundations of traditional nuclear science. These achievements will supply new tasks in developing nuclear theory. And shake the ground of which magic number is the basic of nuclear science. It opens up a new field on foundational research. The book will supply new knowledge for researcher, teachers and students in universities and polytechnic schools. Scientific workers read in works of research and technical exploit. It can be stored up for library and laboratory of society and universities. In nowadays of prosperity our nation by science and education, the book is readable for workers of scientific technology and amateurs of natural science

  18. Classification and clinical assessment

    Directory of Open Access Journals (Sweden)

    F. Cantini

    2012-06-01

    Full Text Available There are at least nine classification criteria for psoriatic arthritis (PsA that have been proposed and used in clinical studies. With the exception of the ESSG and Bennett rules, all of the other criteria sets have a good performance in identifying PsA patients. As the CASPAR criteria are based on a robust study methodology, they are considered the current reference standard. However, if there seems to be no doubt that they are very good to classify PsA patients (very high specificity, they might be not sensitive enough to diagnose patients with unknown early PsA. The vast clinical heterogeneity of PsA makes its assessment very challenging. Peripheral joint involvement is measured by 78/76 joint counts, spine involvement by the instruments used for ankylosing spondylitis (AS, dactylitis by involved digit count or by the Leeds dactylitis index, enthesitis by the number of affected entheses (several indices available and psoriasis by the Psoriasis Area and Severity Index (PASI. Peripheral joint damage can be assessed by a modified van der Heijde-Sharp scoring system and axial damage by the methods used for AS or by the Psoriatic Arthritis Spondylitis Radiology Index (PASRI. As in other arthritides, global evaluation of disease activity and severity by patient and physician and assessment of disability and quality of life are widely used. Finally, composite indices that capture several clinical manifestations of PsA have been proposed and a new instrument, the Psoriatic ARthritis Disease Activity Score (PASDAS, is currently being developed.

  19. Classification of reality in different languages

    OpenAIRE

    Golandam A.; Gholami H.

    2013-01-01

    The article deals with the classification of linguistic realities. There are several classifications of the realities on different grounds. Currently there is no uniform classification of cultural and marked units and researchers propose different classifications of reality, based on certain principles.

  20. 10 CFR 61.55 - Waste classification.

    Science.gov (United States)

    2010-01-01

    ... 10 Energy 2 2010-01-01 2010-01-01 false Waste classification. 61.55 Section 61.55 Energy NUCLEAR... Requirements for Land Disposal Facilities § 61.55 Waste classification. (a) Classification of waste for near surface disposal—(1) Considerations. Determination of the classification of radioactive waste involves...

  1. 32 CFR 2700.22 - Classification guides.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Classification guides. 2700.22 Section 2700.22... SECURITY INFORMATION REGULATIONS Derivative Classification § 2700.22 Classification guides. OMSN shall issue classification guides pursuant to section 2-2 of E.O. 12065. These guides, which shall be used...

  2. 32 CFR 2400.6 - Classification levels.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Classification levels. 2400.6 Section 2400.6... Original Classification § 2400.6 Classification levels. (a) National security information (hereinafter... three authorized classification levels, such as “Secret Sensitive” or “Agency Confidential.” The...

  3. 7 CFR 51.2284 - Size classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Size classification. 51.2284 Section 51.2284... Size classification. The following classifications are provided to describe the size of any lot... shall conform to the requirements of the specified classification as defined below: (a) Halves....

  4. 32 CFR 2001.15 - Classification guides.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Classification guides. 2001.15 Section 2001.15..., NATIONAL ARCHIVES AND RECORDS ADMINISTRATION CLASSIFIED NATIONAL SECURITY INFORMATION Classification § 2001.15 Classification guides. (a) Preparation of classification guides. Originators of...

  5. 45 CFR 601.5 - Derivative classification.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 3 2010-10-01 2010-10-01 false Derivative classification. 601.5 Section 601.5... CLASSIFICATION AND DECLASSIFICATION OF NATIONAL SECURITY INFORMATION § 601.5 Derivative classification. Distinct from “original” classification is the determination that information is in substance the same...

  6. 7 CFR 51.1860 - Color classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Color classification. 51.1860 Section 51.1860... STANDARDS) United States Standards for Fresh Tomatoes 1 Color Classification § 51.1860 Color classification... illustrating the color classification requirements, as set forth in this section. This visual aid may...

  7. 7 CFR 28.911 - Review classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Review classification. 28.911 Section 28.911... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification § 28.911 Review classification. (a) A producer may request one...

  8. 28 CFR 345.20 - Position classification.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Position classification. 345.20 Section... INDUSTRIES (FPI) INMATE WORK PROGRAMS Position Classification § 345.20 Position classification. (a) Inmate... the objectives and principles of pay classification as a part of the routine orientation of new...

  9. HIV classification using coalescent theory

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Ming [Los Alamos National Laboratory; Letiner, Thomas K [Los Alamos National Laboratory; Korber, Bette T [Los Alamos National Laboratory

    2008-01-01

    Algorithms for subtype classification and breakpoint detection of HIV-I sequences are based on a classification system of HIV-l. Hence, their quality highly depend on this system. Due to the history of creation of the current HIV-I nomenclature, the current one contains inconsistencies like: The phylogenetic distance between the subtype B and D is remarkably small compared with other pairs of subtypes. In fact, it is more like the distance of a pair of subsubtypes Robertson et al. (2000); Subtypes E and I do not exist any more since they were discovered to be composed of recombinants Robertson et al. (2000); It is currently discussed whether -- instead of CRF02 being a recombinant of subtype A and G -- subtype G should be designated as a circulating recombination form (CRF) nd CRF02 as a subtype Abecasis et al. (2007); There are 8 complete and over 400 partial HIV genomes in the LANL-database which belong neither to a subtype nor to a CRF (denoted by U). Moreover, the current classification system is somehow arbitrary like all complex classification systems that were created manually. To this end, it is desirable to deduce the classification system of HIV systematically by an algorithm. Of course, this problem is not restricted to HIV, but applies to all fast mutating and recombining viruses. Our work addresses the simpler subproblem to score classifications of given input sequences of some virus species (classification denotes a partition of the input sequences in several subtypes and CRFs). To this end, we reconstruct ancestral recombination graphs (ARG) of the input sequences under restrictions determined by the given classification. These restritions are imposed in order to ensure that the reconstructed ARGs do not contradict the classification under consideration. Then, we find the ARG with maximal probability by means of Markov Chain Monte Carlo methods. The probability of the most probable ARG is interpreted as a score for the classification. To our

  10. Satellite image classification using convolutional learning

    Science.gov (United States)

    Nguyen, Thao; Han, Jiho; Park, Dong-Chul

    2013-10-01

    A satellite image classification method using Convolutional Neural Network (CNN) architecture is proposed in this paper. As a special case of deep learning, CNN classifies classes of images without any feature extraction step while other existing classification methods utilize rather complex feature extraction processes. Experiments on a set of satellite image data and the preliminary results show that the proposed classification method can be a promising alternative over existing feature extraction-based schemes in terms of classification accuracy and classification speed.

  11. Automated Periodontal Diseases Classification System

    Directory of Open Access Journals (Sweden)

    Aliaa A. A. Youssif

    2012-01-01

    Full Text Available This paper presents an efficient and innovative system for automated classification of periodontal diseases, The strength of our technique lies in the fact that it incorporates knowledge from the patients' clinical data, along with the features automatically extracted from the Haematoxylin and Eosin (H&E stained microscopic images. Our system uses image processing techniques based on color deconvolution, morphological operations, and watershed transforms for epithelium & connective tissue segmentation, nuclear segmentation, and extraction of the microscopic immunohistochemical features for the nuclei, dilated blood vessels & collagen fibers. Also, Feedforward Backpropagation Artificial Neural Networks are used for the classification process. We report 100% classification accuracy in correctly identifying the different periodontal diseases observed in our 30 samples dataset.

  12. Rock suitability classification RSC 2012

    International Nuclear Information System (INIS)

    This report presents Posiva's Rock Suitability Classification (RSC) system, developed for locating suitable rock volumes for repository design and construction. The RSC system comprises both the revised rock suitability criteria and the procedure for the suitability classification during the construction of the repository. The aim of the classification is to avoid such features of the host rock that may be detrimental to the favourable conditions within the repository, either initially or in the long term. This report also discusses the implications of applying the RSC system for the fulfilment of the regulatory requirements concerning the host rock as a natural barrier and the site's overall suitability for hosting a final repository of spent nuclear fuel

  13. Hazard classification or risk assessment

    DEFF Research Database (Denmark)

    Hass, Ulla

    to substitute with less toxic compounds. Actually, if exposure is constant across product class, producersmay make substitution decisions based on hazard. Hazard classification is also useful during major accidents where there is no time for risk assessment and the exposure is likely to be......The EU classification of substances for e.g. reproductive toxicants is hazard based and does not to address the risk suchsubstances may pose through normal, or extreme, use. Such hazard classification complies with the consumer's right to know. It is also an incentive to careful use and storage and...... exposure data for other similarly acting substances are needed for assessing the risk for mixture effects. Such data may, however, often be absent. Toxicological potency, i.e. the lowest dose found to cause adverse effects, has been proposed as one of the key characteristics when evaluating safety of a...

  14. Classification systems for stalking behavior.

    Science.gov (United States)

    Racine, Christopher; Billick, Stephen

    2014-01-01

    Stalking is a complex behavioral phenomenon that is unique in that it necessarily involves a prolonged dyadic relationship between both a perpetrator and a victim. Since criminalization of stalking behavior in the 1990s, different conceptual typologies have attempted to classify this behavior to assess risk and aid in management decisions. The authors reviewed the current literature regarding the most recent and accepted stalking classification systems. The three predominant stalker typologies currently in use include Zona's stalker-victim types, Mullen's stalker typology, and the RECON stalker typology. Of these, the RECON classification system alone was developed in an attempt to separate stalkers into groups based on previously known risk factors for behaviorally based phenomenon such as propensity for violence. Understanding and simplifying these classification systems may enhance the potential that new research will lead to evidence-based management and treatment strategies in the stalking situation. PMID:23980606

  15. Rock suitability classification RSC 2012

    Energy Technology Data Exchange (ETDEWEB)

    McEwen, T. (ed.) [McEwen Consulting, Leicester (United Kingdom); Kapyaho, A. [Geological Survey of Finland, Espoo (Finland); Hella, P. [Saanio and Riekkola, Helsinki (Finland); Aro, S.; Kosunen, P.; Mattila, J.; Pere, T.

    2012-12-15

    This report presents Posiva's Rock Suitability Classification (RSC) system, developed for locating suitable rock volumes for repository design and construction. The RSC system comprises both the revised rock suitability criteria and the procedure for the suitability classification during the construction of the repository. The aim of the classification is to avoid such features of the host rock that may be detrimental to the favourable conditions within the repository, either initially or in the long term. This report also discusses the implications of applying the RSC system for the fulfilment of the regulatory requirements concerning the host rock as a natural barrier and the site's overall suitability for hosting a final repository of spent nuclear fuel.

  16. Vehicle Classification by Lane Allowance

    Directory of Open Access Journals (Sweden)

    Vishakha Gaikwad

    2014-12-01

    Full Text Available Classification of vehicles from video is used for analysis of traffic, self-driving systems or security systems. This analysis is based on shape, size, velocity and track of vehicles. These features characterize vehicle in background subtraction and feature extraction methods. Extraction is done by active contours and morphological operations. Extracted vehicles are classified by applying various classification techniques. The combination of features and classification techniques varies with the application. Proposed system, Uses combination of K Nearest Neighbor (KNN and Decision Tree techniques to overcome constraints. These constraints are instances of an object, overlapping of objects, and scaling factor. KNN is utilized to classify vehicle by size and lane. Decision tree manipulates the combination of these two features to classify accurately which results increased performance. This system classifies objects into three classes. These classes are four wheeler, bikers and heavy duty vehicle extracted from video.

  17. Classification Accuracy Is Not Enough

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    A recent review of the research literature evaluating music genre recognition (MGR) systems over the past two decades shows that most works (81\\%) measure the capacity of a system to recognize genre by its classification accuracy. We show here, by implementing and testing three categorically...... different state-of-the-art MGR systems, that classification accuracy does not necessarily reflect the capacity of a system to recognize genre in musical signals. We argue that a more comprehensive analysis of behavior at the level of the music is needed to address the problem of MGR, and that measuring...... classification accuracy obscures the aim of MGR: to select labels indistinguishable from those a person would choose....

  18. Automatic Hierarchical Color Image Classification

    Directory of Open Access Journals (Sweden)

    Jing Huang

    2003-02-01

    Full Text Available Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.

  19. Classification of Medical Brain Images

    Institute of Scientific and Technical Information of China (English)

    Pan Haiwei(潘海为); Li Jianzhong; Zhang Wei

    2003-01-01

    Since brain tumors endanger people's living quality and even their lives, the accuracy of classification becomes more important. Conventional classifying techniques are used to deal with those datasets with characters and numbers. It is difficult, however, to apply them to datasets that include brain images and medical history (alphanumeric data), especially to guarantee the accuracy. For these datasets, this paper combines the knowledge of medical field and improves the traditional decision tree. The new classification algorithm with the direction of the medical knowledge not only adds the interaction with the doctors, but also enhances the quality of classification. The algorithm has been used on real brain CT images and a precious rule has been gained from the experiments. This paper shows that the algorithm works well for real CT data.

  20. [Classification of periprosthetic shoulder fractures].

    Science.gov (United States)

    Kirchhoff, C; Kirchhoff, S; Biberthaler, P

    2016-04-01

    The key targets in the treatment of periprosthetic humeral fractures (PHF) are the preservation of bone, successful bony consolidation and provision of a stable anchoring of the prosthesis with the major goal of restoring the shoulder-arm function. A substantial problem of periprosthetic shoulder fractures is the fact that treatment is determined not only by the fracture itself but also by the implanted prosthesis and its function. Consequently, the exact preoperative shoulder function and, in the case of an implanted anatomical prosthesis, the status and function of the rotator cuff need to be assessed in order to clarify the possibility of a secondarily occurring malfunction. Of equal importance in this context is the type of implanted prosthesis. The existing classification systems of Wright and Cofield, Campbell et al., Groh et al. and Worland et al. have several drawbacks from a shoulder surgeon's point of view, such as a missing reference to the great variability of the available prostheses and the lack of an evaluation of rotator cuff function. The presented 6‑stage classification for the evaluation of periprosthetic fractures of the shoulder can be considered just as simple or complex to understand as the classification of the working group for osteosynthesis problems (AO, Arbeitsgemeinschaft für Osteosynthesefragen), depending on the viewpoint. From our point of view the classification presented here encompasses the essential points of the existing classification systems and also covers the otherwise missing points, which should be considered in the assessment of such periprosthetic fractures. The classification presented here should provide helpful assistance in the daily routine to find the most convenient form of therapy. PMID:26992712

  1. Focal mechanism estimation by classification

    CERN Document Server

    Lasscock, Ben G; Glinsky, Michael E

    2014-01-01

    A classification technique for identifying focal mechanism type and fault plane orientation based on the polarity of P-wave "first motion" data is derived. A support vector machine is used to classify the polarity data in the space of spherical harmonic functions. The classification is non-parametric in the sense that there is no requirement to make a priori assumptions source mechanism. A metric of similarity potentially able to distinguish shear versus tensile dislocation without requiring estimation of the fault plane orientation is a natural consequence of this procedure. Going further, correlation functions between template source mechanism is derived, gives an estimate of fault plane orientation assuming a particular source mechanism.

  2. Facial aging: A clinical classification

    Directory of Open Access Journals (Sweden)

    Shiffman Melvin

    2007-01-01

    Full Text Available The purpose of this classification of facial aging is to have a simple clinical method to determine the severity of the aging process in the face. This allows a quick estimate as to the types of procedures that the patient would need to have the best results. Procedures that are presently used for facial rejuvenation include laser, chemical peels, suture lifts, fillers, modified facelift and full facelift. The physician is already using his best judgment to determine which procedure would be best for any particular patient. This classification may help to refine these decisions.

  3. SHIP CLASSIFICATION FROM MULTISPECTRAL VIDEOS

    Directory of Open Access Journals (Sweden)

    Frederique Robert-Inacio

    2012-05-01

    Full Text Available Surveillance of a seaport can be achieved by different means: radar, sonar, cameras, radio communications and so on. Such a surveillance aims, on the one hand, to manage cargo and tanker traffic, and, on the other hand, to prevent terrorist attacks in sensitive areas. In this paper an application to video-surveillance of a seaport entrance is presented, and more particularly, the different steps enabling to classify mobile shapes. This classification is based on a parameter measuring the similarity degree between the shape under study and a set of reference shapes. The classification result describes the considered mobile in terms of shape and speed.

  4. Proteomic classification of breast cancer.

    LENUS (Irish Health Repository)

    Kamel, Dalia

    2012-11-01

    Being a significant health problem that affects patients in various age groups, breast cancer has been extensively studied to date. Recently, molecular breast cancer classification has advanced significantly with the availability of genomic profiling technologies. Proteomic technologies have also advanced from traditional protein assays including enzyme-linked immunosorbent assay, immunoblotting and immunohistochemistry to more comprehensive approaches including mass spectrometry and reverse phase protein lysate arrays (RPPA). The purpose of this manuscript is to review the current protein markers that influence breast cancer prediction and prognosis and to focus on novel advances in proteomic classification of breast cancer.

  5. Supervised Ensemble Classification of Kepler Variable Stars

    CERN Document Server

    Bass, Gideon

    2016-01-01

    Variable star analysis and classification is an important task in the understanding of stellar features and processes. While historically classifications have been done manually by highly skilled experts, the recent and rapid expansion in the quantity and quality of data has demanded new techniques, most notably automatic classification through supervised machine learning. We present an expansion of existing work on the field by analyzing variable stars in the {\\em Kepler} field using an ensemble approach, combining multiple characterization and classification techniques to produce improved classification rates. Classifications for each of the roughly 150,000 stars observed by {\\em Kepler} are produced separating the stars into one of 14 variable star classes.

  6. Automatic indexing, compiling and classification

    International Nuclear Information System (INIS)

    A review of the principles of automatic indexing, is followed by a comparison and summing-up of work by the authors and by a Soviet staff from the Moscou INFORM-ELECTRO Institute. The mathematical and linguistic problems of the automatic building of thesaurus and automatic classification are examined

  7. Classifications of Linear Controlled Systems

    OpenAIRE

    Li, Jing

    2008-01-01

    This paper is devoted to a study of linear, differential and topological classifications for linear controlled systems governed by ordinary differential equations. The necessary and sufficient conditions for the linear and topological equivalence are given. It is also shown that the differential equivalence is the same as the linear equivalence for the linear controlled systems.

  8. Climatic classification of the Karst

    International Nuclear Information System (INIS)

    Climate is one the main factors in forming or modifying Karsts, or its resulting forms. The determining climatic elements of Karst characteristics are humidity, air circulation and temperature. Many Karstic processes show characteristics corresponding to a given climate sequence. In the present article we discuss the relation between climate and Karst as well as a climate classification based on the structure of the Karsts

  9. Agriculture classification using POLSAR data

    DEFF Research Database (Denmark)

    Skriver, Henning; Dall, Jørgen; Ferro-Famil, Laurent; Le Toan, Thuy; Lumsdon, Parivash; Moshammer, Rolf; Pottier, Eric; Quegan, Shaun

    2005-01-01

    data, and a very important class of algorithms is the knowledge-based approaches. Here, generic characteristics of different cover types are derived by combining physical reasoning with the available empirical evidence. These are then used to define classification rules. Because of their emphasis on...

  10. The classification of minerals deposits

    International Nuclear Information System (INIS)

    In this part of book author present the classification of minerals deposits. Deposit formation take place as a result of complicated and long geology processes in the wide temperature intervals (from 1500 digC to usual) and pressures (from usual and to tens kilobars). Deposits of minerals as other investigation objects require in definite systematization on the base of definite characteristics

  11. Correlation Dimension Estimation for Classification

    Czech Academy of Sciences Publication Activity Database

    Jiřina, Marcel; Jiřina jr., M.

    2006-01-01

    Roč. 1, č. 3 (2006), s. 547-557. ISSN 1895-8648 R&D Projects: GA MŠk(CZ) 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : correlation dimension * probability density estimation * classification * UCI MLR Subject RIV: BA - General Mathematics

  12. Functions in Biological Kind Classification

    Science.gov (United States)

    Lombrozo, Tania; Rehder, Bob

    2012-01-01

    Biological traits that serve functions, such as a zebra's coloration (for camouflage) or a kangaroo's tail (for balance), seem to have a special role in conceptual representations for biological kinds. In five experiments, we investigate whether and why functional features are privileged in biological kind classification. Experiment 1…

  13. Crop Classification by Polarimetric SAR

    DEFF Research Database (Denmark)

    Skriver, Henning; Svendsen, Morten Thougaard; Nielsen, Flemming;

    1999-01-01

    Polarimetric SAR-data of agricultural fields have been acquired by the Danish polarimetric L- and C-band SAR (EMISAR) during a number of missions at the Danish agricultural test site Foulum during 1995. The data are used to study the classification potential of polarimetric SAR data using the...

  14. Aphasia Classification Using Neural Networks

    DEFF Research Database (Denmark)

    Axer, H.; Jantzen, Jan; Berks, G.;

    2000-01-01

    A web-based software model (http://fuzzy.iau.dtu.dk/aphasia.nsf) was developed as an example for classification of aphasia using neural networks. Two multilayer perceptrons were used to classify the type of aphasia (Broca, Wernicke, anomic, global) according to the results in some subtests of the...

  15. Is classification necessary after Google?

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2012-01-01

    Purpose – The purpose of this paper is to examine challenges facing bibliographic classification at both the practical and theoretical levels. At the practical level, libraries are increasingly dispensing with classifying books. At the theoretical level, many researchers, managers, and users beli...

  16. Classification Using the Zipfian Kernel

    Czech Academy of Sciences Publication Activity Database

    Jiřina, Marcel; Jiřina jr., M.

    2015-01-01

    Roč. 32, č. 2 (2015), s. 305-326. ISSN 0176-4268 R&D Projects: GA TA ČR TA01010490 Institutional support: RVO:67985807 Keywords : kernel machine * Zipfian kernel * multivariate data * correlation dimension * harmonic series * classification Subject RIV: JC - Computer Hardware ; Software Impact factor: 0.727, year: 2014

  17. 22 CFR 9.8 - Classification challenges.

    Science.gov (United States)

    2010-04-01

    ... challenges to classification actions shall be in writing to an original classification authority (OCA) with.... The Department (either the OCA or IPS) shall provide an initial response in writing within 60 days....

  18. Efficient segmentation by sparse pixel classification

    DEFF Research Database (Denmark)

    Dam, Erik B; Loog, Marco

    2008-01-01

    Segmentation methods based on pixel classification are powerful but often slow. We introduce two general algorithms, based on sparse classification, for optimizing the computation while still obtaining accurate segmentations. The computational costs of the algorithms are derived, and they are...

  19. The many classification range of flight situations

    Directory of Open Access Journals (Sweden)

    В.П. Харченко

    2008-04-01

    Full Text Available  The multivariate classification principle of flight situation range has been represented. Main parameters of classification flight situation by two parameters (horizontal and vertical deviation from flight planed trajectory has been estimated.

  20. The many classification range of flight situations

    OpenAIRE

    В.П. Харченко; І.В. Остроумов; Зайцев, Ю. В.

    2008-01-01

     The multivariate classification principle of flight situation range has been represented. Main parameters of classification flight situation by two parameters (horizontal and vertical deviation from flight planed trajectory) has been estimated.

  1. Bayesian Classification in Medicine: The Transferability Question *

    OpenAIRE

    Zagoria, Ronald J.; Reggia, James A.; Price, Thomas R.; Banko, Maryann

    1981-01-01

    Using probabilities derived from a geographically distant patient population, we applied Bayesian classification to categorize stroke patients by etiology. Performance was assessed both by error rate and with a new linear accuracy coefficient. This approach to patient classification was found to be surprisingly accurate when compared to classification by two neurologists and to classification by the Bayesian method using “low cost” local and subjective probabilities. We conclude that for some...

  2. PSG-Based Classification of Sleep Phases

    OpenAIRE

    Králík, M.

    2015-01-01

    This work is focused on classification of sleep phases using artificial neural network. The unconventional approach was used for calculation of classification features using polysomnographic data (PSG) of real patients. This approach allows to increase the time resolution of the analysis and, thus, to achieve more accurate results of classification.

  3. Hydropedological insights when considering catchment classification

    NARCIS (Netherlands)

    Bouma, J.; Droogers, P.; Sonneveld, M.P.W.; Ritsema, C.J.; Hunink, J.E.; Immerzeel, W.W.; Kauffman, S.

    2011-01-01

    Soil classification systems are analysed to explore the potential of developing classification systems for catchments. Soil classifications are useful to create systematic order in the overwhelming quantity of different soils in the world and to extrapolate data available for a given soil type to so

  4. The Road Ahead for Library Classification Systems.

    Science.gov (United States)

    Mitchell, Joan S.

    1997-01-01

    Discusses knowledge organization tools in the context of seven challenges facing library classification systems. Highlights include revisions to the Dewey Decimal Classification, the Windows-based CD-ROM version of Dewey, support for machine-assisted classification, multilingual use of Dewey, use of Dewey as a general knowledge organization and…

  5. Audio Classification from Time-Frequency Texture

    OpenAIRE

    Yu, Guoshen; Slotine, Jean-Jacques

    2008-01-01

    Time-frequency representations of audio signals often resemble texture images. This paper derives a simple audio classification algorithm based on treating sound spectrograms as texture images. The algorithm is inspired by an earlier visual classification scheme particularly efficient at classifying textures. While solely based on time-frequency texture features, the algorithm achieves surprisingly good performance in musical instrument classification experiments.

  6. 45 CFR 601.2 - Classification authority.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 3 2010-10-01 2010-10-01 false Classification authority. 601.2 Section 601.2 Public Welfare Regulations Relating to Public Welfare (Continued) NATIONAL SCIENCE FOUNDATION CLASSIFICATION AND DECLASSIFICATION OF NATIONAL SECURITY INFORMATION § 601.2 Classification authority. The Foundation does not have original...

  7. 5 CFR 2500.3 - Original classification.

    Science.gov (United States)

    2010-01-01

    ... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Original classification. 2500.3 Section... SECURITY REGULATION § 2500.3 Original classification. No one in the Office of Administration has been granted authority for original classification of information....

  8. 14 CFR 1203.701 - Classification.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Classification. 1203.701 Section 1203.701... Government Information § 1203.701 Classification. (a) Foreign government information that is classified by a foreign entity shall either retain its original classification designation or be marked with a...

  9. 46 CFR 193.50-5 - Classification.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 7 2010-10-01 2010-10-01 false Classification. 193.50-5 Section 193.50-5 Shipping COAST... Details § 193.50-5 Classification. (a) Hand portable fire extinguishers and semiportable fire...) Classification Type Size Soda-acid and water, gals. Foam, gals. Carbon dioxide, lbs. Dry chemical, lbs. A II...

  10. 32 CFR 1602.7 - Classification.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Classification. 1602.7 Section 1602.7 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM DEFINITIONS § 1602.7 Classification. Classification is the exercise of the power to determine claims or questions with respect...

  11. 5 CFR 1312.7 - Derivative classification.

    Science.gov (United States)

    2010-01-01

    ... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Derivative classification. 1312.7 Section 1312.7 Administrative Personnel OFFICE OF MANAGEMENT AND BUDGET OMB DIRECTIVES CLASSIFICATION, DOWNGRADING, DECLASSIFICATION AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION Classification...

  12. 32 CFR 644.426 - Classification.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 4 2010-07-01 2010-07-01 true Classification. 644.426 Section 644.426 National... HANDBOOK Disposal Disposal of Fee-Owned Real Property and Easement Interests § 644.426 Classification... required by the special acts, classification will be coordinated with the interested Federal agency....

  13. 14 CFR 298.3 - Classification.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Classification. 298.3 Section 298.3... REGULATIONS EXEMPTIONS FOR AIR TAXI AND COMMUTER AIR CARRIER OPERATIONS General § 298.3 Classification. (a) There is hereby established a classification of air carriers, designated as “air taxi operators,”...

  14. 46 CFR 76.50-5 - Classification.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 3 2010-10-01 2010-10-01 false Classification. 76.50-5 Section 76.50-5 Shipping COAST... Classification. (a) Hand portable fire extinguishers and semiportable fire extinguishing systems shall be... extinguishing systems are set forth in table 76.50-5(c). Table 76.50-5(c) Classification Type Size Soda acid...

  15. 7 CFR 51.1904 - Maturity classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Maturity classification. 51.1904 Section 51.1904... STANDARDS) United States Consumer Standards for Fresh Tomatoes Size and Maturity Classification § 51.1904 Maturity classification. Tomatoes which are characteristically red when ripe, but are not overripe or...

  16. 17 CFR 200.506 - Derivative classification.

    Science.gov (United States)

    2010-04-01

    ... 17 Commodity and Securities Exchanges 2 2010-04-01 2010-04-01 false Derivative classification. 200...; CONDUCT AND ETHICS; AND INFORMATION AND REQUESTS Classification and Declassification of National Security Information and Material § 200.506 Derivative classification. Any document that includes...

  17. 32 CFR 1602.13 - Judgmental Classification.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Judgmental Classification. 1602.13 Section 1602.13 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM DEFINITIONS § 1602.13 Judgmental Classification. A classification action relating to a registrant's claim...

  18. 10 CFR 1045.17 - Classification levels.

    Science.gov (United States)

    2010-01-01

    ... 10 Energy 4 2010-01-01 2010-01-01 false Classification levels. 1045.17 Section 1045.17 Energy DEPARTMENT OF ENERGY (GENERAL PROVISIONS) NUCLEAR CLASSIFICATION AND DECLASSIFICATION Identification of Restricted Data and Formerly Restricted Data Information § 1045.17 Classification levels. (a) Restricted...

  19. 15 CFR 4a.3 - Classification levels.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Classification levels. 4a.3 Section 4a.3 Commerce and Foreign Trade Office of the Secretary of Commerce CLASSIFICATION, DECLASSIFICATION, AND PUBLIC AVAILABILITY OF NATIONAL SECURITY INFORMATION § 4a.3 Classification levels. Information...

  20. 7 CFR 51.1402 - Size classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Size classification. 51.1402 Section 51.1402... STANDARDS) United States Standards for Grades of Pecans in the Shell 1 Size Classification § 51.1402 Size classification. Size of pecans may be specified in connection with the grade in accordance with one of...

  1. 12 CFR 403.4 - Derivative classification.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Derivative classification. 403.4 Section 403.4 Banks and Banking EXPORT-IMPORT BANK OF THE UNITED STATES CLASSIFICATION, DECLASSIFICATION, AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION § 403.4 Derivative classification. (a) Use of...

  2. 46 CFR 132.210 - Classification.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 4 2010-10-01 2010-10-01 false Classification. 132.210 Section 132.210 Shipping COAST... Portable and Semiportable Fire Extinguishers § 132.210 Classification. (a) Each portable fire extinguisher... Classification Type Size Halon 1211, 1301, and 1211-1301 mixtures kgs. (lbs.) Foam, liters (gallons)...

  3. 7 CFR 1794.31 - Classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 12 2010-01-01 2010-01-01 false Classification. 1794.31 Section 1794.31 Agriculture... Classification. (a) Electric and telecommunications programs. RUS will normally determine the proper environmental classification of projects based on its evaluation of the project description set forth in...

  4. 6 CFR 7.26 - Derivative classification.

    Science.gov (United States)

    2010-01-01

    ... amended, 32 CFR 2001.22, and internal DHS guidance provided by the Chief Security Officer. ... 6 Domestic Security 1 2010-01-01 2010-01-01 false Derivative classification. 7.26 Section 7.26... INFORMATION Classified Information § 7.26 Derivative classification. (a) Derivative classification is...

  5. 12 CFR 560.160 - Asset classification.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 5 2010-01-01 2010-01-01 false Asset classification. 560.160 Section 560.160... Lending and Investment Provisions Applicable to all Savings Associations § 560.160 Asset classification... consistent with, or reconcilable to, the asset classification system used by OTS in its Thrift...

  6. 32 CFR 2001.22 - Derivative classification.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Derivative classification. 2001.22 Section 2001... Identification and Markings § 2001.22 Derivative classification. (a) General. Information classified derivatively on the basis of source documents or classification guides shall bear all markings prescribed...

  7. 76 FR 47614 - Mail Classification Change

    Science.gov (United States)

    2011-08-05

    ... Mail Classification Change AGENCY: Postal Regulatory Commission. ACTION: Notice. SUMMARY: The Commission is noticing a recently-filed Postal Service request for a change in classification to the ``Reply... Service filed a notice of classification change pursuant to 39 CFR 3020.90 and 3020.91 concerning...

  8. 17 CFR 200.505 - Original classification.

    Science.gov (United States)

    2010-04-01

    ... 17 Commodity and Securities Exchanges 2 2010-04-01 2010-04-01 false Original classification. 200...; CONDUCT AND ETHICS; AND INFORMATION AND REQUESTS Classification and Declassification of National Security Information and Material § 200.505 Original classification. (a) No Commission Member or employee has...

  9. 46 CFR Sec. 18 - Group classification.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 8 2010-10-01 2010-10-01 false Group classification. Sec. 18 Section 18 Shipping... Sec. 18 Group classification. In the preparation of specifications, Job Orders, Supplemental Job... inserted thereon: Number Classification 41 Maintenance Repairs (deck, engine and stewards...

  10. 7 CFR 51.1903 - Size classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Size classification. 51.1903 Section 51.1903... STANDARDS) United States Consumer Standards for Fresh Tomatoes Size and Maturity Classification § 51.1903 Size classification. The following terms may be used for describing the size of the tomatoes in any...

  11. 32 CFR 2001.21 - Original classification.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Original classification. 2001.21 Section 2001.21... Markings § 2001.21 Original classification. (a) Primary markings. At the time of original classification, the following shall be indicated in a manner that is immediately apparent: (1)...

  12. 46 CFR 503.54 - Original classification.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 9 2010-10-01 2010-10-01 false Original classification. 503.54 Section 503.54 Shipping... Program § 503.54 Original classification. (a) No Commission Member or employee has the authority to... require classification, or receives any foreign government information as defined in section 1.1(d)...

  13. 10 CFR 1045.37 - Classification guides.

    Science.gov (United States)

    2010-01-01

    ... 10 Energy 4 2010-01-01 2010-01-01 false Classification guides. 1045.37 Section 1045.37 Energy DEPARTMENT OF ENERGY (GENERAL PROVISIONS) NUCLEAR CLASSIFICATION AND DECLASSIFICATION Generation and Review of Documents Containing Restricted Data and Formerly Restricted Data § 1045.37 Classification...

  14. 46 CFR 95.50-5 - Classification.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 4 2010-10-01 2010-10-01 false Classification. 95.50-5 Section 95.50-5 Shipping COAST... Details § 95.50-5 Classification. (a) Hand portable fire extinguishers and semiportable fire extinguishing... extinguishing systems are set forth in Table 95.50-5(c). Table 95.50-5(c) Classification Type Size Soda-acid...

  15. 32 CFR 2400.34 - Classification.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Classification. 2400.34 Section 2400.34 National... Government Information § 2400.34 Classification. (a) Foreign government information classified by a foreign government or international organization of governments shall retain its original classification...

  16. Teaching Classification and Seriation to Preschoolers.

    Science.gov (United States)

    Ciancio, Dennis; Sadovsky, Adrienne; Malabonga, Valerie; Trueblood, Linda; Pasnak, Robert

    1999-01-01

    Studied use of games to teach simple classification and seriation constructs to 3-1/2-year-old children. Found substantial and maintained improvement on classification and seriation. Found that children generalized their new understanding of classification and seriation to different problems, and found that evidence for a more general cognitive…

  17. Introduction to Relational Networks for Classification

    CERN Document Server

    Marivate, Vukosi

    2008-01-01

    The use of computational intelligence techniques for classification has been used in numerous applications. This paper compares the use of a Multi Layer Perceptron Neural Network and a new Relational Network on classifying the HIV status of women at ante-natal clinics. The paper discusses the architecture of the relational network and its merits compared to a neural network and most other computational intelligence classifiers. Results gathered from the study indicate comparable classification accuracies as well as revealed relationships between data features in the classification data. Much higher classification accuracies are recommended for future research in the area of HIV classification as well as missing data estimation.

  18. CCM: A Text Classification Method by Clustering

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock;

    2011-01-01

    In this paper, a new Cluster based Classification Model (CCM) for suspicious email detection and other text classification tasks, is presented. Comparative experiments of the proposed model against traditional classification models and the boosting algorithm are also discussed. Experimental results...... show that the CCM outperforms traditional classification models as well as the boosting algorithm for the task of suspicious email detection on terrorism domain email dataset and topic categorization on the Reuters-21578 and 20 Newsgroups datasets. The overall finding is that applying a cluster based...... approach to text classification tasks simplifies the model and at the same time increases the accuracy....

  19. Odor Classification using Agent Technology

    Directory of Open Access Journals (Sweden)

    Sigeru OMATU

    2014-03-01

    Full Text Available In order to measure and classify odors, Quartz Crystal Microbalance (QCM can be used. In the present study, seven QCM sensors and three different odors are used. The system has been developed as a virtual organization of agents using an agent platform called PANGEA (Platform for Automatic coNstruction of orGanizations of intElligent Agents. This is a platform for developing open multi-agent systems, specifically those including organizational aspects. The main reason for the use of agents is the scalability of the platform, i.e. the way in which it models the services. The system models functionalities as services inside the agents, or as Service Oriented Approach (SOA architecture compliant services using Web Services. This way the adaptation of the odor classification systems with new algorithms, tools and classification techniques is allowed.

  20. Handling uncertainties in SVM classification

    CERN Document Server

    Niaf, Emilie; Lartizien, Carole; Canu, Stéphane

    2011-01-01

    This paper addresses the pattern classification problem arising when available target data include some uncertainty information. Target data considered here is either qualitative (a class label) or quantitative (an estimation of the posterior probability). Our main contribution is a SVM inspired formulation of this problem allowing to take into account class label through a hinge loss as well as probability estimates using epsilon-insensitive cost function together with a minimum norm (maximum margin) objective. This formulation shows a dual form leading to a quadratic problem and allows the use of a representer theorem and associated kernel. The solution provided can be used for both decision and posterior probability estimation. Based on empirical evidence our method outperforms regular SVM in terms of probability predictions and classification performances.

  1. A clinical classification of hypertension

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    @@ Hypertension is a common cardiovascular problem worldwide. As with any other disease it is important to assess the severity of the disease. However the present classification of hypertension by the Joint National Committee in its seventh report (JNC 7) with numerical values staging the severity of hypertension is theoretically correct but difficult to apply in practice (Table 1).1 Admittedly this is a step in the right direction with lesser number of stages compared to the sixth report.2 The World Health Organization- International Society of Hypertension (WHO-ISH)-1999 3 and the European Society of Hypertension - European Society of Cardiology (ESH-ESC)4 guidelines follow similar numerical classifications (Table 2). All these papers are referred to as 'guidelines' in this article.

  2. Meta Classification for Variable Stars

    CERN Document Server

    Pichara, Karim; León, Daniel

    2016-01-01

    The need for the development of automatic tools to explore astronomical databases has been recognized since the inception of CCDs and modern computers. Astronomers already have developed solutions to tackle several science problems, such as automatic classification of stellar objects, outlier detection, and globular clusters identification, among others. New science problems emerge and it is critical to be able to re-use the models learned before, without rebuilding everything from the beginning when the science problem changes. In this paper, we propose a new meta-model that automatically integrates existing classification models of variable stars. The proposed meta-model incorporates existing models that are trained in a different context, answering different questions and using different representations of data. Conventional mixture of experts algorithms in machine learning literature can not be used since each expert (model) uses different inputs. We also consider computational complexity of the model by ...

  3. Object Classification via Planar Abstraction

    Science.gov (United States)

    Oesau, Sven; Lafarge, Florent; Alliez, Pierre

    2016-06-01

    We present a supervised machine learning approach for classification of objects from sampled point data. The main idea consists in first abstracting the input object into planar parts at several scales, then discriminate between the different classes of objects solely through features derived from these planar shapes. Abstracting into planar shapes provides a means to both reduce the computational complexity and improve robustness to defects inherent to the acquisition process. Measuring statistical properties and relationships between planar shapes offers invariance to scale and orientation. A random forest is then used for solving the multiclass classification problem. We demonstrate the potential of our approach on a set of indoor objects from the Princeton shape benchmark and on objects acquired from indoor scenes and compare the performance of our method with other point-based shape descriptors.

  4. Classification differences and maternal mortality

    DEFF Research Database (Denmark)

    Salanave, B; Bouvier-Colle, M H; Varnoux, N;

    1999-01-01

    change was substantial in three countries (P < 0.05) where statistical offices appeared to attribute fewer deaths to obstetric causes. In the other countries, no differences were detected. According to official published data, the aggregated maternal mortality rate for participating countries was 7.7 per...... 100,000 live births, but it increased to 8.7 after classification by the European panel (P < 0.001). CONCLUSION: The classification of pregnancy-associated deaths differs between European countries. These differences in coding contribute to variations in the reported numbers of maternal deaths and...... sufficient data to complete reclassification of 359 or 82% of the 437 cases for which data were collected. RESULTS: Compared with the statistical offices, the European panel attributed more deaths to obstetric causes. The overall number of deaths attributed to obstetric causes increased from 229 to 260. This...

  5. Classification of symmetric toroidal orbifolds

    Energy Technology Data Exchange (ETDEWEB)

    Fischer, Maximilian; Ratz, Michael; Torrado, Jesus [Technische Univ. Muenchen, Garching (Germany). Physik-Department; Vaudrevange, Patrick K.S. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

    2012-09-15

    We provide a complete classification of six-dimensional symmetric toroidal orbifolds which yield N{>=}1 supersymmetry in 4D for the heterotic string. Our strategy is based on a classification of crystallographic space groups in six dimensions. We find in total 520 inequivalent toroidal orbifolds, 162 of them with Abelian point groups such as Z{sub 3}, Z{sub 4}, Z{sub 6}-I etc. and 358 with non-Abelian point groups such as S{sub 3}, D{sub 4}, A{sub 4} etc. We also briefly explore the properties of some orbifolds with Abelian point groups and N=1, i.e. specify the Hodge numbers and comment on the possible mechanisms (local or non-local) of gauge symmetry breaking.

  6. Modulation classification based on spectrogram

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The aim of modulation classification (MC) is to identify the modulation type of a communication signal. It plays an important role in many cooperative or noncooperative communication applications. Three spectrogram-based modulation classification methods are proposed. Their reccgnition scope and performance are investigated or evaluated by theoretical analysis and extensive simulation studies. The method taking moment-like features is robust to frequency offset while the other two, which make use of principal component analysis (PCA) with different transformation inputs,can achieve satisfactory accuracy even at low SNR (as low as 2 dB). Due to the properties of spectrogram, the statistical pattern recognition techniques, and the image preprocessing steps, all of our methods are insensitive to unknown phase and frequency offsets, timing errors, and the arriving sequence of symbols.

  7. Functionality Classification Filter for Websites

    OpenAIRE

    Järvstråt, Lotta

    2013-01-01

    The objective of this thesis is to evaluate different models and methods for website classification. The websites are classified based on their functionality, in this case specifically whether they are forums, news sites or blogs. The analysis aims at solving a search engine problem, which means that it is interesting to know from which categories in a information search the results come. The data consists of two datasets, extracted from the web in January and April 2013. Together these data ...

  8. Is classification necessary after Google?

    OpenAIRE

    Hjørland, Birger

    2012-01-01

    Purpose – The purpose of this paper is to examine challenges facing bibliographic classification at both the practical and theoretical levels. At the practical level, libraries are increasingly dispensing with classifying books. At the theoretical level, many researchers, managers, and users believe that the activity of “classification” is not worth the effort, as search engines can be improved without the heavy cost of providing metadata. Design/methodology/approach – The basic issue in clas...

  9. Structural classification of phosphate glasses

    International Nuclear Information System (INIS)

    A structural classification of phosphate glasses is proposed. Following types of phosphate glasses are distinguished: discontinuous polymeric structure glasses (phosphate and mixed chains and rings containing glasses), continuous spatial network structure glasses (ultraphosphate and mixed network glasses) and non-polymeric structure glasses (oxide-halide and halide glasses, stuffed with ortho- and pyrophosphate-like groups). Type of the structure determines in a considerable degree the relation between glass composition and properties. (author). 25 refs

  10. Automated Periodontal Diseases Classification System

    OpenAIRE

    Aliaa A. A. Youssif; Abeer Saad Gawish,; Mohammed Elsaid Moussa

    2012-01-01

    This paper presents an efficient and innovative system for automated classification of periodontal diseases, The strength of our technique lies in the fact that it incorporates knowledge from the patients' clinical data, along with the features automatically extracted from the Haematoxylin and Eosin (H&E) stained microscopic images. Our system uses image processing techniques based on color deconvolution, morphological operations, and watershed transforms for epithelium & connective tissue se...

  11. A classification of prescription errors.

    OpenAIRE

    Neville, R G; Robertson, F; Livingstone, S.; Crombie, I K

    1989-01-01

    Three independent methods of study of prescription errors led to the development of a classification of errors based on the potential effects and inconvenience to patients, pharmacists and doctors. Four types of error are described: type A (potentially serious to patient); type B (major nuisance - pharmacist/doctor contact required); type C (minor nuisance - pharmacist must use professional judgement); and type D (trivial). The types of frequency of errors are detailed for a group of eight pr...

  12. Web Content Classification: A Survey

    OpenAIRE

    Kaur, Prabhjot

    2014-01-01

    As the information contained within the web is increasing day by day, organizing this information could be a necessary requirement.The data mining process is to extract information from a data set and transform it into an understandable structure for further use. Classification of web page content is essential to many tasks in web information retrieval such as maintaining web directories and focused crawling.The uncontrolled type of nature of web content presents additional challenges to web ...

  13. Neuronal Classification of Atria Fibrillation

    OpenAIRE

    Mohamed BEN MESSAOUD

    2008-01-01

    Motivation. In medical field, particularly the cardiology, the diagnosis systems constitute the essential domain of research. In some applications, the traditional methods of classification present some limitations. The neuronal technique is considered as one of the promising algorithms to resolve such problem.Method. In this paper, two approaches of the Artificial Neuronal Network (ANN) technique are investigated to classify the heart beats which are Multi Layer Perception (MLP) and Radial B...

  14. Classification of Simple Current Invariants

    CERN Document Server

    Gato-Rivera, Beatriz

    1991-01-01

    We summarize recent work on the classification of modular invariant partition functions that can be obtained with simple currents in theories with a center (Z_p)^k with p prime. New empirical results for other centers are also presented. Our observation that the total number of invariants is monodromy-independent for (Z_p)^k appears to be true in general as well. (Talk presented in the parallel session on string theory of the Lepton-Photon/EPS Conference, Geneva, 1991.)

  15. Optimal classification of HCI spectra

    OpenAIRE

    Gaigalas, G.; Karpuskiene, R.; Rudzikas, Z.

    2004-01-01

    Energy levels of highly charged ions as a rule cannot be classified using LS coupling due to rapid increase of relativistic effects. It is suggested, for optimal classification of energy spectra, to calculate them in LS coupling and to transform the weights of the wave functions, obtained after diagonalization of the energy matrix, to the other coupling schemes. F-like ions are considered as an example.

  16. Collective Classification in Network Data

    OpenAIRE

    Sen, Prithviraj; Namata, Galileo; Bilgic, Mustafa; Getoor, Lise; University of Maryland; Galligher, Brian; Eliassi-Rad, Tina

    2008-01-01

    Many real-world applications produce networked data such as the world-wide web (hypertext documents connected via hyperlinks), social networks (for example, people connected by friendship links), communication networks (computers connected via communication links) and biological networks (for example, protein interaction networks). A recent focus in machine learning research has been to extend traditional machine learning classification techniques to classify nodes in such networks. In this a...

  17. Cerebral palsy: classification and etiology

    OpenAIRE

    Bialik, Gad M.; Givon, Uri

    2004-01-01

    Cerebral palsy (CP), a common condition of abnormalities in the brain, arises early in life. Since the term was first introduced in 1843, many authors have tried to define and classify CP. The most recent definition was released by the American Academy for Cerebral Palsy and Developmental Medicine (AACPDM) in 2005. This article summarizes the latest and familiar classifications of, and etiologies associated with CP.

  18. Chemical Classification of Space Debris

    Institute of Scientific and Technical Information of China (English)

    LI Chunlai; ZUO Wei; LIU Jianjun; OUYANG Ziyuan

    2004-01-01

    Space debris, here referring to all non-operating orbital objects, has steadily increased in number so that it has become a potential barrier to the exploration of space. The ever-increasing number of space debris pieces in space has created an increasingly threatening hazard to all on-the-orbit spacecraft, and all future space exploration activities have to be designed and operated with respect to the increasing threat posed by space debris. Generally, space debris is classified as large, medium and small debris pieces based on their sizes. The large debris piece is easily catalogued, but medium to small debris pieces are very difficult to track and also quite different in damage mechanisms from the large ones. In this paper, a scheme of chemical classification of space debris is developed. In our scheme, the first-order classification is employed to divide space debris into two groups: natural micrometeoroids and artificial space debris.The second-order classification is based on their chemical patterns and compositions. The natural micrometeoroids are further divided into three types, namely maric, metal and phyllosilicate micrometeorites, while the artificial space debris is divided into seven types, which are polymers, non-metal debris, metals and their alloys, oxides, sulphides and their analogs, halides and carbides. Of the latter seven types, some can also be further divided into several sub-types. Chemical classification of space debris is very useful for the study of the chemical damage mechanism of small debris pieces, and also is of great significance in constraining the origin and source of space debris and assessing their impact on spacecraft and human space activities.

  19. Classifications of Patterned Hair Loss: A Review.

    Science.gov (United States)

    Gupta, Mrinal; Mysore, Venkataram

    2016-01-01

    Patterned hair loss is the most common cause of hair loss seen in both the sexes after puberty. Numerous classification systems have been proposed by various researchers for grading purposes. These systems vary from the simpler systems based on recession of the hairline to the more advanced multifactorial systems based on the morphological and dynamic parameters that affect the scalp and the hair itself. Most of these preexisting systems have certain limitations. Currently, the Hamilton-Norwood classification system for males and the Ludwig system for females are most commonly used to describe patterns of hair loss. In this article, we review the various classification systems for patterned hair loss in both the sexes. Relevant articles were identified through searches of MEDLINE and EMBASE. Search terms included but were not limited to androgenic alopecia classification, patterned hair loss classification, male pattern baldness classification, and female pattern hair loss classification. Further publications were identified from the reference lists of the reviewed articles. PMID:27081243

  20. Hazard classification guidelines and procedures

    International Nuclear Information System (INIS)

    The presence of a dam creates an incremental hazard to the downstream development beyond that of other natural hazards not associated with the dam, due to the potential for dam failure and uncontrolled water release. The general hazard classification system used by Ontario Hydro is documented and further guidance is provided for the identification and classification of downstream hazards. Suggested methods of determining the preliminary hazard category are also documented. Hazard categories are selected for each structure under both normal and flood conditions, examining potential for increase in loss of life, and economic loss, social and environmental impacts. Analysis of downstream areas includes location of existing facilities, existing land usage and zoning, historical flows and water levels, information concerning previous flooding events, and physical parameters of the dam. Detailed analysis develops the probable maximum precipitation and flood information, and flood routing. Final confirmation of the hazard classification uses the definitive water level information to re-examine the probable loss of life and flood damages. 8 refs., 6 figs

  1. Neuronal Classification of Atria Fibrillation

    Directory of Open Access Journals (Sweden)

    Mohamed BEN MESSAOUD

    2008-06-01

    Full Text Available Motivation. In medical field, particularly the cardiology, the diagnosis systems constitute the essential domain of research. In some applications, the traditional methods of classification present some limitations. The neuronal technique is considered as one of the promising algorithms to resolve such problem.Method. In this paper, two approaches of the Artificial Neuronal Network (ANN technique are investigated to classify the heart beats which are Multi Layer Perception (MLP and Radial Basis Function (RBF. A calculation algorithm of the RBF centers is proposed. For the Atria Fibrillation anomalies, an artificial neural network was used as a pattern classifier to distinguish three classes of the cardiac arrhythmias. The different classes consist of the normal beats (N, the Arrhythmia (AFA and Tachycardia (TFA Atria Fibrillation cases. The global and the partition classifier are performed. The arrhythmias of MIT-BIH database are analyzed. The ANN inputs are the temporal and morphological parameters deduced from the electrocardiograph.Results. The simulation results illustrate the performances of the studied versions of the neural network and give the fault detection rate of the tested data, a rate of classification reaching the 3.7%.Conclusion. This system can constitute a mesh in a chain of automated diagnosis and can be a tool for assistance for the classification of the cardiac anomalies in the services of urgencies before the arrival of a qualified personal person.

  2. Enhancement classification of galaxy images

    Science.gov (United States)

    Jenkinson, John

    With the advent of astronomical imaging technology developments, and the increased capacity of digital storage, the production of photographic atlases of the night sky have begun to generate volumes of data which need to be processed autonomously. As part of the Tonantzintla Digital Sky Survey construction, the present work involves software development for the digital image processing of astronomical images, in particular operations that preface feature extraction and classification. Recognition of galaxies in these images is the primary objective of the present work. Many galaxy images have poor resolution or contain faint galaxy features, resulting in the misclassification of galaxies. An enhancement of these images by the method of the Heap transform is proposed, and experimental results are provided which demonstrate the image enhancement to improve the presence of faint galaxy features thereby improving classification accuracy. The feature extraction was performed using morphological features that have been widely used in previous automated galaxy investigations. Principal component analysis was applied to the original and enhanced data sets for a performance comparison between the original and reduced features spaces. Classification was performed by the Support Vector Machine learning algorithm.

  3. A Classification Table for Achondrites

    Science.gov (United States)

    Chennaoui-Aoudjehane, H.; Larouci, N.; Jambon, A.; Mittlefehldt, D. W.

    2014-01-01

    Classifying chondrites is relatively easy and the criteria are well documented. It is based on mineral compositions, textural characteristics and more recently, magnetic susceptibility. It can be more difficult to classify achondrites, especially those that are very similar to terrestrial igneous rocks, because mineralogical, textural and compositional properties can be quite variable. Achondrites contain essentially olivine, pyroxenes, plagioclases, oxides, sulphides and accessory minerals. Their origin is attributed to differentiated parents bodies: large asteroids (Vesta); planets (Mars); a satellite (the Moon); and numerous asteroids of unknown size. In most cases, achondrites are not eye witnessed falls and some do not have fusion crust. Because of the mineralogical and magnetic susceptibility similarity with terrestrial igneous rocks for some achondrites, it can be difficult for classifiers to confirm their extra-terrestrial origin. We -as classifiers of meteorites- are confronted with this problem with every suspected achondrite we receive for identification. We are developing a "grid" of classification to provide an easier approach for initial classification. We use simple but reproducible criteria based on mineralogical, petrological and geochemical studies. We presented the classes: acapulcoites, lodranites, winonaites and Martian meteorites (shergottite, chassignites, nakhlites). In this work we are completing the classification table by including the groups: angrites, aubrites, brachinites, ureilites, HED (howardites, eucrites, and diogenites), lunar meteorites, pallasites and mesosiderites. Iron meteorites are not presented in this abstract.

  4. Concretion morphology, classification and genesis

    Science.gov (United States)

    Sellés-Martínez, J.

    1996-11-01

    A discussion of the most relevant morphological features of concretionary bodies and the different classifications, and the criteria involved in these classifications is presented, together with suggestions for improvements to the various classification schemes. The meaning of syngenetic, diagenetic and epigenetic related to the relative timing and environment of growth of concretionary bodies is also reviewed and discussed. The replacement of mixed morphogenetic classifications, which lead to conflicting results, by classification categories based on textural features is proposed. Because the identification of the genetic environment of a concretionary body tells little about its history, I recommend defining growth patterns in which the successive steps associated with changes in composition and/or texture and the development of new structures are recorded. A new path is presented that accounts for the contradiction between textural and isotope features, which suggests respectively syngenetic and diagenetic (or even epigenetic) signatures. This new path is characterized by the preservation of large porosities over very long time spans and down to depths that are somewhat greater than expected, due to the inhibition of normal compaction caused by early overpressuring. This overpressuring is the result of the development of hydraulic seals since approximately the syngenetic phase times. The concepts of "force of crystallization" and "displacive growth" are also reviewed. It is being suggested to discard some controversial interpretations of their actual importance for true concretionary displacive growth under epigenetic conditions. In accordance with other authors, the conclusion is reached that displacive growth is only possible if the shear strength of the host is very low and the stress field within the host is almost hydrostatic. A new model (the Symcompactional Concretionary Growth Model) is proposed which explains how a concretionary body, generally a nodule

  5. TEXT CLASSIFICATION TOWARD A SCIENTIFIC FORUM

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Text mining, also known as discovering knowledge from the text, which has emerged as a possible solution for the current information explosion, refers to the process of extracting non-trivial and useful patterns from unstructured text. Among the general tasks of text mining such as text clustering,summarization, etc, text classification is a subtask of intelligent information processing, which employs unsupervised learning to construct a classifier from training text by which to predict the class of unlabeled text. Because of its simplicity and objectivity in performance evaluation, text classification was usually used as a standard tool to determine the advantage or weakness of a text processing method, such as text representation, text feature selection, etc. In this paper, text classification is carried out to classify the Web documents collected from XSSC Website (http://www. xssc.ac.cn). The performance of support vector machine (SVM) and back propagation neural network (BPNN) is compared on this task. Specifically, binary text classification and multi-class text classification were conducted on the XSSC documents. Moreover, the classification results of both methods are combined to improve the accuracy of classification. An experiment is conducted to show that BPNN can compete with SVM in binary text classification; but for multi-class text classification, SVM performs much better. Furthermore, the classification is improved in both binary and multi-class with the combined method.

  6. Tumor classification: molecular analysis meets Aristotle

    International Nuclear Information System (INIS)

    Traditionally, tumors have been classified by their morphologic appearances. Unfortunately, tumors with similar histologic features often follow different clinical courses or respond differently to chemotherapy. Limitations in the clinical utility of morphology-based tumor classifications have prompted a search for a new tumor classification based on molecular analysis. Gene expression array data and proteomic data from tumor samples will provide complex data that is unobtainable from morphologic examination alone. The growing question facing cancer researchers is, 'How can we successfully integrate the molecular, morphologic and clinical characteristics of human cancer to produce a helpful tumor classification?' Current efforts to classify cancers based on molecular features ignore lessons learned from millennia of experience in biological classification. A tumor classification must include every type of tumor and must provide a unique place for each tumor within the classification. Groups within a classification inherit the properties of their ancestors and impart properties to their descendants. A classification was prepared grouping tumors according to their histogenetic development. The classification is simple (reducing the complexity of information received from the molecular analysis of tumors), comprehensive (providing a place for every tumor of man), and consistent with recent attempts to characterize tumors by cytogenetic and molecular features. The clinical and research value of this historical approach to tumor classification is discussed. This manuscript reviews tumor classification and provides a new and comprehensive classification for neoplasia that preserves traditional nomenclature while incorporating information derived from the molecular analysis of tumors. The classification is provided as an open access XML document that can be used by cancer researchers to relate tumor classes with heterogeneous experimental and clinical tumor

  7. Classification

    Data.gov (United States)

    National Aeronautics and Space Administration — A supervised learning task involves constructing a mapping from an input data space (normally described by several features) to an output space. A set of training...

  8. Cirrhosis classification based on texture classification of random features.

    Science.gov (United States)

    Liu, Hui; Shao, Ying; Guo, Dongmei; Zheng, Yuanjie; Zhao, Zuowei; Qiu, Tianshuang

    2014-01-01

    Accurate staging of hepatic cirrhosis is important in investigating the cause and slowing down the effects of cirrhosis. Computer-aided diagnosis (CAD) can provide doctors with an alternative second opinion and assist them to make a specific treatment with accurate cirrhosis stage. MRI has many advantages, including high resolution for soft tissue, no radiation, and multiparameters imaging modalities. So in this paper, multisequences MRIs, including T1-weighted, T2-weighted, arterial, portal venous, and equilibrium phase, are applied. However, CAD does not meet the clinical needs of cirrhosis and few researchers are concerned with it at present. Cirrhosis is characterized by the presence of widespread fibrosis and regenerative nodules in the hepatic, leading to different texture patterns of different stages. So, extracting texture feature is the primary task. Compared with typical gray level cooccurrence matrix (GLCM) features, texture classification from random features provides an effective way, and we adopt it and propose CCTCRF for triple classification (normal, early, and middle and advanced stage). CCTCRF does not need strong assumptions except the sparse character of image, contains sufficient texture information, includes concise and effective process, and makes case decision with high accuracy. Experimental results also illustrate the satisfying performance and they are also compared with typical NN with GLCM. PMID:24707317

  9. Radiological classification of mandibular fractures

    International Nuclear Information System (INIS)

    Mandibular fractures present the biggest part (up to 97%) of the facial bone fractures. Method of choice for diagnosing of mandibular fractures is conventional radiography. The aim of the issue is to present an unified radiological classification of mandibular fractures for the clinical practice. This classification includes only those clinical symptoms of mandibular fracture which could be radiologically objectified: exact anatomical localization (F1-F6), teeth in fracture line (Ta,Tb), grade of dislocation (D I, D II), occlusal disturbances (O(+), O(-)). Radiological symptoms expressed by letter and number symbols are systematized in a formula - FTDO of mandibular fractures similar to TNM formula for tumours. FTDO formula expresses radiological diagnose of each mandibular fracture but it doesn't include neither the site (left or right) of the fracture, nor the kind and number of fractures. In order to express topography and number of fractures the radiological formula is transformed into a decimal fraction. The symbols (FTD) of right mandible fracture are written in the numerator and those of the left site - in the denominator. For double and multiple fractures between the symbols for each fracture we put '+'. Symbols for occlusal disturbances are put down opposite, the fractional line. So topographo-anatomical formula (FTD/FTD)xO is formed. In this way the whole radiological information for unilateral, bilateral, single or multiple fractures of the mandible is expressed. The information in the radiological topography anatomic formula, resp. from the unified topography-anatomic classification ensures a quick and exact X-ray diagnose of mandibular fracture. In this way contributes to get better, make easier and faster X-ray diagnostic process concerning mandibular fractures. And all these is a precondition for prevention of retardation of the diagnosis mandibular fracture. (author)

  10. Mechanical equipment classification research of AP1000 nuclear units

    International Nuclear Information System (INIS)

    According to the design features of AP1000, the AP1000 classification definition and seismic classification is described and analyzed. The characteristics of AP1000 mechanical equipment classification list is concluded for safety, seismic and manufacture classification. Through comparing the AP1000 classification and M310 classification, the questions perhaps met are found during the mechanical equipment classification of AP1000 nuclear power plants design and construction in China at future. Finally solution plans are given aiming at the above questions. (authors)

  11. Pattern classification through fuzzy likelihood

    Directory of Open Access Journals (Sweden)

    Rosa M. Pidatella

    2015-12-01

    Full Text Available This paper introduces a novel way to compute the membership function of a fuzzy set approximating the distribution of some observed data starting with their histogram. This membership function is in turn used to obtain a posteriori probability through a suitable version of the Bayesian formula. The ordering imposed by an  overtaking relation between fuzzy numbers translates immediately into a dominance of the a posteriori probability of a class over another for a given observed value. In this way a crisp classification is eventually obtained.

  12. Correlation Integral Decomposition for Classification

    Czech Academy of Sciences Publication Activity Database

    Jiřina, Marcel; Jiřina jr., M.

    Vol. Part II. Berlin : Springer, 2008 - (Kůrková, V.; Neruda, R.; Koutník, J.), s. 62-71 ISBN 978-3-540-87558-1. - (Lecture Notes in Computer Science. 5164). [ICANN 2008. International Conference on Artificial Neural Networks /18./. Prague (CZ), 03.09.2008-06.09.2008] R&D Projects: GA MŠk(CZ) 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : correlation integral decomposition * correlation dimension * distribution mapping exponent * probability density estimation * classification Subject RIV: BA - General Mathematics

  13. SEMANTIC TRANSFERS: CRITERIA FOR CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    Moskvin, V.P.

    2016-03-01

    Full Text Available There is represented the general classification of semantic transfers. As the research has shown, transfers can be systematized based on four parameters: 1 the type of associations lying on their basis: similarity, contiguity and contrast, the associations by similarity and contrast being regarded as the basis for taxonomic transfers (from genus to species, from species to genus, from species to species, etc.; 2 the functional parameter: functionally relevant and irrelevant; 3 the sphere of action: transfer applies both to lexical and grammatical semantics; 4 the degree of ex-pressiveness: thus, the metonymic associations are more predictable than the metaphoric ones.

  14. Unsupervised automatic music genre classification

    OpenAIRE

    Barreira, Luís Filipe Marques

    2010-01-01

    Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática In this study we explore automatic music genre recognition and classification of digital music. Music has always been a reflection of culture di erences and an influence in our society. Today’s digital content development triggered the massive use of digital music. Nowadays,digital music is manually labeled without following a universa...

  15. Real time automatic scene classification

    OpenAIRE

    Israël, Menno; Broek, van den, Wouter; Putten, van, M.J.A.M.; Uyl, den, T.M.; Verbrugge, R.; Taatgen, N.; Schomaker, L.

    2004-01-01

    This work has been done as part of the EU VICAR (IST) project and the EU SCOFI project (IAP). The aim of the first project was to develop a real time video indexing classification annotation and retrieval system. For our systems, we have adapted the approach of Picard and Minka [3], who categorized elements of a scene automatically with so-called ’stuff’ categories (e.g., grass, sky, sand, stone). Campbell et al. [1] use similar concepts to describe certain parts of an image, which they named...

  16. Ordinal Classification with Monotonicity Constraints

    Czech Academy of Sciences Publication Activity Database

    Horváth, T.; Vojtáš, Peter

    Berlin: Springer, 2006 - (Perner, P.), s. 217-225. (Lecture Notes in Artificial Intelligence. 4065). ISBN 978-3-540-36036-0. [ICDM 2006. Industrial Conference on Data Mining /6./. Leipzig (DE), 14.07.2006-15.07.2006] R&D Projects: GA AV ČR 1ET100300517 Grant ostatní: VEGA(SK) 1/3129/06 Institutional research plan: CEZ:AV0Z10300504 Keywords : monotone * monotonicity constraints * classification * ordinal data Subject RIV: IN - Informatics, Computer Science

  17. MINING ACCESS PATTERNS USING CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    Mrs. Kiruthika M,

    2010-07-01

    Full Text Available In day to day life, we see many advertisements aimed at attracting more customers and also changes in marketing schemes. These are done by a company after immense research in the market about the customer. Since, internet became a household phenomenon; it gave rise to creation of many websites. Extracting the usage patterns of usersbecame very important. Thus, websites were required to maintain user profiles for better marketing purposes over the internet. In this paper, we discuss classification of the usage pattern of the users into one or more predefined classes. This may help the company in decision making and also to some extent customer satisfaction can beachieved.

  18. Classification theory of polarized varieties

    CERN Document Server

    Fujita, Takao

    1990-01-01

    A polarised variety is a modern generalization of the notion of a variety in classical algebraic geometry. It consists of a pair: the algebraic variety itself, together with an ample line bundle on it. Using techniques from abstract algebraic geometry that have been developed over recent decades, Professor Fujita develops classification theories of such pairs using invariants that are polarised higher-dimensional versions of the genus of algebraic curves. The heart of the book is the theory of D-genus and sectional genus developed by the author, but numerous related topics are discussed or sur

  19. Simulation of Various Classifications Results using WEKA

    Directory of Open Access Journals (Sweden)

    Ms. Shilpa Dhanjibhai Serasiya

    2012-08-01

    Full Text Available In this paper, we focused on the construction ofclass association rules and classification model. In knowledgediscovery process association rule mining and classification aretwo important techniques of data mining and widely used invarious fields. In order to mine only rules that can be used forprediction, we modified the well known association rule miningalgorithm - Apriori to handle user-defined input constraints. Thepaper tries to explain the basics of class association rule miningand classification through WEKA. This article presents howproblems of classification and prediction can be solved usingclass association rules. In the simulation on WEKA, we haveused selected classification techniques to propose theappropriate result from our training dataset. Thus, by using thesimulated results, we suggest the classification using associationrules.

  20. HYBRID INTERNET TRAFFIC CLASSIFICATION TECHNIQUE1

    Institute of Scientific and Technical Information of China (English)

    Li Jun; Zhang Shunyi; Lu Yanqing; Yan Junrong

    2009-01-01

    Accurate and real-time classification of network traffic is significant to network operation and management such as QoS differentiation, traffic shaping and security surveillance. However, with many newly emerged P2P applications using dynamic port numbers, masquerading techniques, and payload encryption to avoid detection, traditional classification approaches turn to be ineffective. In this paper, we present a layered hybrid system to classify current Internet traffic, motivated by variety of network activities and their requirements of traffic classification. The proposed method could achieve fast and accurate traffic classification with low overheads and robustness to accommodate both known and unknown/encrypted applications. Furthermore, it is feasible to be used in the context of real-time traffic classification. Our experimental results show the distinct advantages of the proposed classification system, compared with the one-step Machine Learning (ML) approach.

  1. Gender classification under extended operating conditions

    Science.gov (United States)

    Rude, Howard N.; Rizki, Mateen

    2014-06-01

    Gender classification is a critical component of a robust image security system. Many techniques exist to perform gender classification using facial features. In contrast, this paper explores gender classification using body features extracted from clothed subjects. Several of the most effective types of features for gender classification identified in literature were implemented and applied to the newly developed Seasonal Weather And Gender (SWAG) dataset. SWAG contains video clips of approximately 2000 samples of human subjects captured over a period of several months. The subjects are wearing casual business attire and outer garments appropriate for the specific weather conditions observed in the Midwest. The results from a series of experiments are presented that compare the classification accuracy of systems that incorporate various types and combinations of features applied to multiple looks at subjects at different image resolutions to determine a baseline performance for gender classification.

  2. Supervised Classification Performance of Multispectral Images

    CERN Document Server

    Perumal, K

    2010-01-01

    Nowadays government and private agencies use remote sensing imagery for a wide range of applications from military applications to farm development. The images may be a panchromatic, multispectral, hyperspectral or even ultraspectral of terra bytes. Remote sensing image classification is one amongst the most significant application worlds for remote sensing. A few number of image classification algorithms have proved good precision in classifying remote sensing data. But, of late, due to the increasing spatiotemporal dimensions of the remote sensing data, traditional classification algorithms have exposed weaknesses necessitating further research in the field of remote sensing image classification. So an efficient classifier is needed to classify the remote sensing images to extract information. We are experimenting with both supervised and unsupervised classification. Here we compare the different classification methods and their performances. It is found that Mahalanobis classifier performed the best in our...

  3. Robust logistic regression for insurance risk classification

    OpenAIRE

    Garrido, José; Flores, Esteban

    2001-01-01

    Risk classification is an important part of the actuarial process in Insurance companies. It allows for the underwriting of the best risks, through an appropriate choice of classification variables, and helps set fair premiums in rate-making. Logistic regression is one of the sophisticated statistical methods used by the banking industry to select credit rating variables. Extending the method to insurance risk classification seems natural. But Insurance risks are usually classified in a large...

  4. Extreme Learning Machine for land cover classification

    OpenAIRE

    Pal, Mahesh

    2008-01-01

    This paper explores the potential of extreme learning machine based supervised classification algorithm for land cover classification. In comparison to a backpropagation neural network, which requires setting of several user-defined parameters and may produce local minima, extreme learning machine require setting of one parameter and produce a unique solution. ETM+ multispectral data set (England) was used to judge the suitability of extreme learning machine for remote sensing classifications...

  5. Arabic Text Mining Using Rule Based Classification

    OpenAIRE

    Fadi Thabtah; Omar Gharaibeh; Rashid Al-Zubaidy

    2012-01-01

    A well-known classification problem in the domain of text mining is text classification, which concerns about mapping textual documents into one or more predefined category based on its content. Text classification arena recently attracted many researchers because of the massive amounts of online documents and text archives which hold essential information for a decision-making process. In this field, most of such researches focus on classifying English documents while there are limited studi...

  6. Towards noise classification of road pavements

    OpenAIRE

    Freitas, Elisabete F.; Paulo, Joel; Coelho, J. L. Bento; Pereira, Paulo A. A.

    2008-01-01

    Noise classification of road surfaces has been addressed in many European countries. This paper presents the first approach towards noise classification of Portuguese road pavements. In this early stage, it aims at establishing guidelines for decision makers to support their noise reduction policies and the development of a classification system adapted to the European recommendations. A ranking to provide guidance on tire-road noise emission levels for immediate use by decisio...

  7. A Dynamical Classification of the Cosmic Web

    OpenAIRE

    Forero-Romero, J. E.; Hoffman, Y.; S. Gottloeber(AIP, Potsdam, Germany); Klypin, A.; Yepes, G.

    2008-01-01

    A dynamical classification of the cosmic web is proposed. The large scale environment is classified into four web types: voids, sheets, filaments and knots. The classification is based on the evaluation of the deformation tensor, i.e. the Hessian of the gravitational potential, on a grid. The classification is based on counting the number of eigenvalues above a certain threshold, lambda_th at each grid point, where the case of zero, one, two or three such eigenvalues corresponds to void, shee...

  8. STUDY ON DECISION TREE COMPETENT DATA CLASSIFICATION

    OpenAIRE

    Vanitha, A.; S.Niraimathi

    2013-01-01

    Data mining is a process where intelligent methods are applied in order to extract data patterns.This is used in cases of discovering patterns and trends among large datasets. Data classification involvescategorization of data into different category according to protocols. They are many classification algorithmsavailable and among the decision tree is the most commonly used method. Classification of data objectsbased on a predefined knowledge of objects is a data mining. This paper discussed...

  9. Wittgensteinian Support for Domain Analysis in Classification

    OpenAIRE

    Wesolek, Andrew

    2012-01-01

    Hjorland contends that in order to further the goal of linking researchers to relevant information ‘domain analysis’ should be used in concept classification. He thinks that concept classification should not strive to classify on the basis of the properties of objects, but rather on descriptions of objects that are loosely derived from human activity and social negotiation. Currently, most information scientists operate under a ‘positivist’ view of concept classification, which, Hjorland main...

  10. Texture Classification based on Gabor Wavelet

    OpenAIRE

    Amandeep Kaur; Savita Gupta

    2012-01-01

    This paper presents the comparison of Texture classification algorithms based on Gabor Wavelets. The focus of this paper is on feature extraction scheme for texture classification. The texture feature for an image can be classified using texture descriptors. In this paper we have used Homogeneous texture descriptor that uses Gabor Wavelets concept. For texture classification, we have used online texture database that is Brodatz’s database and three advanced well known classifiers: Support Vec...

  11. Music Genre Classification Systems - A Computational Approach

    OpenAIRE

    Ahrendt, Peter; Hansen, Lars Kai

    2006-01-01

    Automatic music genre classification is the classification of a piece of music into its corresponding genre (such as jazz or rock) by a computer. It is considered to be a cornerstone of the research area Music Information Retrieval (MIR) and closely linked to the other areas in MIR. It is thought that MIR will be a key element in the processing, searching and retrieval of digital music in the near future. This dissertation is concerned with music genre classification systems and in particular...

  12. Discriminant forest classification method and system

    Science.gov (United States)

    Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

    2012-11-06

    A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

  13. Interagency Security Classification Appeals Panel (ISCAP) Decisions

    Data.gov (United States)

    National Archives and Records Administration — This online collection includes documents decided upon by the Interagency Security Classification Appeals Panel (ISCAP) starting in Fiscal Year 2012. The documents...

  14. Classification system to describe workpieces definitions

    CERN Document Server

    Macconnell, W R

    2013-01-01

    A Classification System to Describe Workpieces provides information pertinent to the fundamental aspects and principles of coding. This book discusses the various applications of the classification system of coding.Organized into three chapters, this book begins with an overview of the requirements of a system of classification pertaining adequately and equally to design, production, and work planning. This text then examines the purpose of the classification system in production to determine the most suitable means of machining a component. Other chapters consider the optimal utilization of m

  15. Domain-Based Classification of CSCW Systems

    Directory of Open Access Journals (Sweden)

    M. Khan

    2011-11-01

    Full Text Available CSCW systems are widely used for group activities in different organizations and setups. This study briefly describes the existing classifications of CSCW systems and their shortcomings. These existing classifications are helpful to categorize systems based on a general set of CSCW characteristics but do not provide any guidance towards system design and evaluation. After literature review of ACM CSCW conference (1986-2010, a new classification is proposed to categorize CSCW systems on the basis of domains. This proposed classification may help researchers to come up with more effective design and evaluation methods for CSCW systems.

  16. Performance of Object Classification Using Zernike Moment

    Institute of Scientific and Technical Information of China (English)

    Ariffuddin Joret; Mohammad Faiz Liew Abdullah; Muhammad Suhaimi Sulong; Asmarashid Ponniran; Siti Zuraidah Zainudin

    2014-01-01

    Moments have been used in all sorts of object classification systems based on image. There are lots of moments studied by many researchers in the area of object classification and one of the most preference moments is the Zernike moment. In this paper, the performance of object classification using the Zernike moment has been explored. The classifier based on neural networks has been used in this study. The results indicate the best performance in identifying the aggregate is at 91.4% with a ten orders of the Zernike moment. This encouraging result has shown that the Zernike moment is a suitable moment to be used as a feature of object classification systems.

  17. A New Geochemical Classification of Elements

    Institute of Scientific and Technical Information of China (English)

    Qi Changmou; L. Lynn Chyi

    2001-01-01

    The geochemical classification proposed by Goldschmidt was based on meteoritic analysis and elemental partition in blast furnace. There are many surprises when applied to the discussion of natural occurrences. A modified classification of elements based on basic chemical properties and their occurrences. A modified classification of elements based on basic chemical properties and their occurrences in nature is, therefore, proposed for students learning geochemistry and geologists working in the field. Elements are classified into six groups including lithophile, oxyphile, siderophile, chalcophile, biophile, and atmophile elements. Five terms are taken from Goldshcmidt's original classification. Oxyphile is a new term.

  18. Personality: Description, Classification and Evaluation

    Directory of Open Access Journals (Sweden)

    Ibrahim Taymur

    2012-06-01

    Full Text Available Many descriptions and classifications of personality have been made to understand and acknowledge human being through out the history. During the developmental process of psychiatry, almost every school defined and assessed personality regarding to their own perspective. As DSM (Diagnostical and Statistical Manual of Mental Disorders and ICD (International Classification of Diseases being available to common usage, scientists conducted studies to set a common terminology for personality. Categorical and dimensional approaches are the most fundamentally different assessment strategies in the research and clinical aspects about personality. While categorical approach views the personality as dichotomies which consists of different groups, dimensional approach aims to describe the personality on the basis of dimensions, thus suggests that the personality is a structure formed by definite dimensions. Several advantages and disadvantages can be noticed when descriptions of personality and tools for the evaluation of personality are reviewed. When the section making suggestions about personality disorder in DSM-5 is evaluated, it is seen that it aims to restructure the personality disorder diagnostic group according to new findings and critiques. In this article, the description of personality throughout the history, dimensional, categorical and cognitive approaches to personality, the features of the tools that are used to assess and measure the personality are reviewed.

  19. Hierarchical classification of glycoside hydrolases.

    Science.gov (United States)

    Naumoff, D G

    2011-06-01

    This review deals with structural and functional features of glycoside hydrolases, a widespread group of enzymes present in almost all living organisms. Their catalytic domains are grouped into 120 amino acid sequence-based families in the international classification of the carbohydrate-active enzymes (CAZy database). At a higher hierarchical level some of these families are combined in 14 clans. Enzymes of the same clan have common evolutionary origin of their genes and share the most important functional characteristics such as composition of the active center, anomeric configuration of cleaved glycosidic bonds, and molecular mechanism of the catalyzed reaction (either inverting, or retaining). There are now extensive data in the literature concerning the relationship between glycoside hydrolase families belonging to different clans and/or included in none of them, as well as information on phylogenetic protein relationship within particular families. Summarizing these data allows us to propose a multilevel hierarchical classification of glycoside hydrolases and their homologs. It is shown that almost the whole variety of the enzyme catalytic domains can be brought into six main folds, large groups of proteins having the same three-dimensional structure and the supposed common evolutionary origin. PMID:21639842

  20. Classification of current anticancer immunotherapies

    Science.gov (United States)

    Vacchelli, Erika; Pedro, José-Manuel Bravo-San; Buqué, Aitziber; Senovilla, Laura; Baracco, Elisa Elena; Bloy, Norma; Castoldi, Francesca; Abastado, Jean-Pierre; Agostinis, Patrizia; Apte, Ron N.; Aranda, Fernando; Ayyoub, Maha; Beckhove, Philipp; Blay, Jean-Yves; Bracci, Laura; Caignard, Anne; Castelli, Chiara; Cavallo, Federica; Celis, Estaban; Cerundolo, Vincenzo; Clayton, Aled; Colombo, Mario P.; Coussens, Lisa; Dhodapkar, Madhav V.; Eggermont, Alexander M.; Fearon, Douglas T.; Fridman, Wolf H.; Fučíková, Jitka; Gabrilovich, Dmitry I.; Galon, Jérôme; Garg, Abhishek; Ghiringhelli, François; Giaccone, Giuseppe; Gilboa, Eli; Gnjatic, Sacha; Hoos, Axel; Hosmalin, Anne; Jäger, Dirk; Kalinski, Pawel; Kärre, Klas; Kepp, Oliver; Kiessling, Rolf; Kirkwood, John M.; Klein, Eva; Knuth, Alexander; Lewis, Claire E.; Liblau, Roland; Lotze, Michael T.; Lugli, Enrico; Mach, Jean-Pierre; Mattei, Fabrizio; Mavilio, Domenico; Melero, Ignacio; Melief, Cornelis J.; Mittendorf, Elizabeth A.; Moretta, Lorenzo; Odunsi, Adekunke; Okada, Hideho; Palucka, Anna Karolina; Peter, Marcus E.; Pienta, Kenneth J.; Porgador, Angel; Prendergast, George C.; Rabinovich, Gabriel A.; Restifo, Nicholas P.; Rizvi, Naiyer; Sautès-Fridman, Catherine; Schreiber, Hans; Seliger, Barbara; Shiku, Hiroshi; Silva-Santos, Bruno; Smyth, Mark J.; Speiser, Daniel E.; Spisek, Radek; Srivastava, Pramod K.; Talmadge, James E.; Tartour, Eric; Van Der Burg, Sjoerd H.; Van Den Eynde, Benoît J.; Vile, Richard; Wagner, Hermann; Weber, Jeffrey S.; Whiteside, Theresa L.; Wolchok, Jedd D.; Zitvogel, Laurence; Zou, Weiping

    2014-01-01

    During the past decades, anticancer immunotherapy has evolved from a promising therapeutic option to a robust clinical reality. Many immunotherapeutic regimens are now approved by the US Food and Drug Administration and the European Medicines Agency for use in cancer patients, and many others are being investigated as standalone therapeutic interventions or combined with conventional treatments in clinical studies. Immunotherapies may be subdivided into “passive” and “active” based on their ability to engage the host immune system against cancer. Since the anticancer activity of most passive immunotherapeutics (including tumor-targeting monoclonal antibodies) also relies on the host immune system, this classification does not properly reflect the complexity of the drug-host-tumor interaction. Alternatively, anticancer immunotherapeutics can be classified according to their antigen specificity. While some immunotherapies specifically target one (or a few) defined tumor-associated antigen(s), others operate in a relatively non-specific manner and boost natural or therapy-elicited anticancer immune responses of unknown and often broad specificity. Here, we propose a critical, integrated classification of anticancer immunotherapies and discuss the clinical relevance of these approaches. PMID:25537519

  1. [[CARDIORENAL SYNDROMES : DEFINITION AND CLASSIFICATION].

    Science.gov (United States)

    Moulin, Bruno

    2016-06-01

    Cardiorenal syndromes refer to clinical and metabolic consequences of acute and chronic heart failure or kidney disease on other organ. Recent studies have further clarified the pathophysiological mechanisms behind the different types of cardiorenal syndromes and propose a new classification. The cardiorenal syndrome type 1 corresponds to an acute heart failure (cardiogenic shock, acute decompensated congestive heart failure) which induces acute renal dysfunction. In the cardiorenal syndrome type 2 heart failure is chronic (congestive heart failure) and induces chronic kidney damages in the long-term. Whereas the renocardiac syndrome type 3 (acute) or 4 (chronic) corresponds to either acute renal failure situation (acute renal failure with tubular necrosis secondary to acute collapsus...) responsible for acute heart failure (left ventricular failure and pulmonary edema) or chronic (chronic glomerulonephritis, polycystic...) leading to chronic heart alteration (left ventricular hypertrophy, heart failure, arrhythmias). Finally, the failure of both organs can be simultaneous and secondary to a systemic or a metabolic disease (amyloidosis, diabetes) and corresponds to cardiorenal syndrome type 5. Epidemiological studies highlight the high incidence of cardiorenal syndromes type 1 and 2 and particularly the deleterious impact of renal impairment on the short and medium-term prognosis of heart failure. This classification is of essential interest for better identification of patients and help for the development of therapeutic studies. PMID:27538311

  2. Circular backpropagation networks for classification.

    Science.gov (United States)

    Ridella, S; Rovetta, S; Zunino, R

    1997-01-01

    The class of mapping networks is a general family of tools to perform a wide variety of tasks. This paper presents a standardized, uniform representation for this class of networks, and introduces a simple modification of the multilayer perceptron with interesting practical properties, especially well suited to cope with pattern classification tasks. The proposed model unifies the two main representation paradigms found in the class of mapping networks for classification, namely, the surface-based and the prototype-based schemes, while retaining the advantage of being trainable by backpropagation. The enhancement in the representation properties and the generalization performance are assessed through results about the worst-case requirement in terms of hidden units and about the Vapnik-Chervonenkis dimension and cover capacity. The theoretical properties of the network also suggest that the proposed modification to the multilayer perceptron is in many senses optimal. A number of experimental verifications also confirm theoretical results about the model's increased performances, as compared with the multilayer perceptron and the Gaussian radial basis functions network. PMID:18255613

  3. Classification Laboratory: A Computer Program Using Clip Art To Demonstrate Classification.

    Science.gov (United States)

    Abramson, Charles I.; French, Donald P.; Huss, Jeanine; Mundis, Matthew

    1999-01-01

    Describes an interactive computer program that provides students with a means for learning classification concepts in the psychology classroom; if computers are not available, clip art can be utilized to study classification. Maintains that the program encourages students to see the importance of modifying any classification system as new data…

  4. Thermo-refrigerating machineries. Classification; Machines thermofrigorifiques. Classification

    Energy Technology Data Exchange (ETDEWEB)

    Duminil, M. [Association Francaise du Froid (AFF), 75 - Paris (France)

    2002-07-01

    Thermo-refrigerating systems transfer the heat extracted from a cold source towards a heat source and consume thermal energy from a third source. This article proposes a classification of thermo-refrigerating systems in three categories: the systems with a changing state working fluid (physical change of the refrigerant: dissociable systems, integrated systems (ejection systems, sorption systems); chemical change of the refrigerant), the systems where the working fluid stays in the same physical state (dissociable systems (Brayton, Siemens, Stirling and Ericsson cycles), integrated systems (Vuilleumier cycle systems, thermochemical systems)) and the other systems (Seebeck thermoelectric generator with Peltier effect modules). Dissociable thermo-refrigerating systems are made of the grouping of two separate thermal machines: a thermal engine and a mechanical-refrigerating machine. (J.S.)

  5. Advancing Towards a Universal Soil Classification System

    Science.gov (United States)

    Owens, Phillip R.; Hempel, Jon; Micheli, Erika; McBratney, Alex

    2014-05-01

    Within the variability of soils across the globe, there are common soil attributes that pedologists have used to group soil within taxonomic classifications. Classification systems are necessary for the communication of information about soils. There are many national classification systems used within designated countries and two classification systems used globally, the US Soil Taxonomy and the World Reference Base. There is a great need for soil scientists to develop one common language or taxonomic system to communicate information within soil science as well as to other scientists in other disciplines. The International Union of Soil Sciences Working Group for Universal Soil Classification was officially established by an IUSS Council decision in August of 2010 at the World Congress of Soil Science in Brisbane, Australia. The charge for the Working Group includes development of common standards for methods and terminology in soil observations and investigations and the development of a universal soil classification system. The Universal Soil Classification Working Group was established and the initial meeting was held at Purdue University in West Lafayette, Indiana USA. The Working Group has evaluated the current national systems and the two international systems to identify gaps in knowledge. Currently, it was determined that gaps in knowledge exists in cold soil, hydromorphic, salt affected, anthropengic, and tropical soil groups. Additionally, several members of the Working Group have utilized taxonomic distance calculations from large databases to determine the clusters of similar taxonomic groupings utilizing the classification. Additionally, the databases are being used to make allocations into logical groups to recognize "Great Soil Groups". The great soil groups will be equivalent to great groups level from Soil Taxonomy along with similar levels in the World Reference Base, Australian Soil Classification and other defined soil classification systems

  6. Sources of variation in hydrological classifications: Time scale, flow series origin and classification procedure

    Science.gov (United States)

    Peñas, Francisco J.; Barquín, José; Álvarez, César

    2016-07-01

    Classification of flow regimes in water management and hydroecological research has grown significantly in recent years. However, depending on available data and the procedures applied, there may be several credible classifications for a specific catchment. In this study, three inductive classifications derived from different initial flow data and one expert-driven classification were defined. The hydrological interpretation, statistical performance and spatial correspondence of these classifications were compared. Daily Gauged Classification (DC) was derived from daily flow data while Monthly Gauged Classification (MC) and Monthly Modeled Classification (MMC) were derived from monthly flow series, using gauged and modeled flow data, respectively. Expert-Driven Classification (EDC) was based on a Spanish nationwide hydrological classification, which is being used in the current River Basin Management Plans. The results showed that MC accounted for much of the critical hydrological information variability comprised within the DC. However, it also presented limitations regarding the inability to represent important hydroecological attributes, especially those related to droughts and high flow events. In addition, DC and MC presented an equivalent performance more than 60% of the time and obtained a mean ARI value of 0.4, indicating a similar classification structure. DC and MC outperformed MMC 100% and more than 50% of the times when they were compared by means of the classification strength and ANOVA, respectively. MMC also showed low correspondence with these classifications (ARI = 0.20). Thus, the use of modeled flow series should be limited to poorly gauged areas. Finally, the significantly reduced performance and the uneven distribution of classes found in EDC questions its application for different management objectives. This study shows that the selection of the most suitable approach according to the available data has significant implications for the

  7. Molecular Classification and Correlates in Colorectal Cancer

    OpenAIRE

    Ogino, Shuji; Goel, Ajay

    2008-01-01

    Molecular classification of colorectal cancer is evolving. As our understanding of colorectal carcinogenesis improves, we are incorporating new knowledge into the classification system. In particular, global genomic status [microsatellite instability (MSI) status and chromosomal instability (CIN) status] and epigenomic status [CpG island methylator phenotype (CIMP) status] play a significant role in determining clinical, pathological and biological characteristics of colorectal cancer. In thi...

  8. On the classification of gradient Ricci solitons

    OpenAIRE

    Petersen, Peter; Wylie, William

    2007-01-01

    We show that the only complete shrinking gradient Ricci solitons with vanishing Weyl tensor are quotients of the standard ones. This gives a new proof of the Hamilton-Ivey-Perel'man classification of 3-dimensional shrinking gradient solitons. We also prove a classification for expanding gradient Ricci solitons with constant scalar curvature and suitably decaying Weyl tensor.

  9. Automated underwater object classification using optical imagery

    OpenAIRE

    Shihavuddin, A.S.M.

    2014-01-01

    This thesis addresses the problem of automated underwater optical image characterization. Remote underwater optical sensing allows the collection and storage of vast amounts of data for which manual classification may take months. Supervised automated classification of such datasets can save time and resources and can also enable extraction of valuableinformation related to marine and geological research

  10. Semantic Annotation to Support Automatic Taxonomy Classification

    DEFF Research Database (Denmark)

    Kim, Sanghee; Ahmed, Saeema; Wallace, Ken

    2006-01-01

    This paper presents a new taxonomy classification method that generates classification criteria from a small number of important sentences identified through semantic annotations, e.g. cause-effect. Rhetorical Structure Theory (RST) is used to discover the semantics (Mann et al. 1988). Specifically...

  11. Computational Intelligence Paradigms in Advanced Pattern Classification

    CERN Document Server

    Jain, Lakhmi

    2012-01-01

    This monograph presents selected areas of application of pattern recognition and classification approaches including handwriting recognition, medical image analysis and interpretation, development of cognitive systems for image computer understanding, moving object detection, advanced image filtration and intelligent multi-object labelling and classification. It is directed to the scientists, application engineers, professors, professors and students will find this book useful.

  12. Hydropedological insights when considering catchment classification

    NARCIS (Netherlands)

    Bouma, J.; Droogers, P.; Sonneveld, M.P.W.; Ritsema, C.J.; Hunink, J.E.; Immerzeel, W.W.; Kauffman, S.

    2011-01-01

    Soil classification systems are analysed in relation to the functioning and characterisation of catchments. Soil classifications are useful to create systematic order in the overwhelming quantity of different soils in the world and to extrapolate data available for a given soil type to soils elsewhe

  13. Computerized Classification Testing with the Rasch Model

    Science.gov (United States)

    Eggen, Theo J. H. M.

    2011-01-01

    If classification in a limited number of categories is the purpose of testing, computerized adaptive tests (CATs) with algorithms based on sequential statistical testing perform better than estimation-based CATs (e.g., Eggen & Straetmans, 2000). In these computerized classification tests (CCTs), the Sequential Probability Ratio Test (SPRT) (Wald,…

  14. 28 CFR 17.30 - Classification challenges.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Classification challenges. 17.30 Section 17.30 Judicial Administration DEPARTMENT OF JUSTICE CLASSIFIED NATIONAL SECURITY INFORMATION AND... DRC shall redact the identity of an individual challenging a classification under paragraph (a)...

  15. Challenges for the present CKD classification system

    NARCIS (Netherlands)

    Gansevoort, Ron T.; de Jong, Paul E.

    2010-01-01

    Purpose of review In 2002 the Kidney Disease Outcomes Quality Initiative (K/DOQI) organization published a guideline on chronic kidney disease (CKD), which contained a classification system for CKD severity, independent of cause. This classification system was immediately widely embraced. However, s

  16. CLASSIFICATION OF CUBIC PARAMETERIZED HOMOGENEOUS VECTOR FIELDS

    Institute of Scientific and Technical Information of China (English)

    Karnal H.Yasir; TANG Yun

    2002-01-01

    In this paper the cubic homogeneous parameterized vector fields are studied.The classification of the phase portrait near the critical point is presented. This classification is an extension of the result given by Takens to the cubic homogeneous parameterized vector fields with six parameters.

  17. CLASSIFICATION OF CUBIC PARAMETERIZED HOMOGENEOUS VECTOR FIELDS

    Institute of Scientific and Technical Information of China (English)

    KamalH.Yasir; TNAGYun

    2002-01-01

    In this paper the cubic homogeneous parameterized vector fields are studied.The classification of the phase portrait near the critical point is presented.This classification is an extension of the result given by takens to the cubic homogeneous parameterized vector fields with six parameters.

  18. 76 FR 65428 - Classification and Program Review

    Science.gov (United States)

    2011-10-21

    ... any new or changed aspects of an inmate's initial classification and participation in recommended... inmate develop skills to transition into prison life and to ultimately make a successful transition back... classification and of the inmate's participation in recommended programs, and it facilitates recommendation...

  19. Experiments in Automatic Library of Congress Classification.

    Science.gov (United States)

    Larson, Ray R.

    1992-01-01

    Presents the results of research into the automatic selection of Library of Congress Classification numbers based on the titles and subject headings in MARC records from a test database at the University of California at Berkeley Library School library. Classification clustering and matching techniques are described. (44 references) (LRW)

  20. Asiago spectroscopic classification of AT 2016cvm

    Science.gov (United States)

    Tomasella, L.; Pastorello, A.; Benetti, S.; Cappellaro, E.; Elias-Rosa, N.; Ochner, P.; Tartaglia, L.; Terreran, G.; Turatto, M.

    2016-06-01

    The Asiago Transient Classification Program (Tomasella et al. 2014, AN, 335, 841) reports the spectroscopic classification of AT 2016cvm (also known as PTSS-16hxs), discovered 20160613.771 by the PMO-Tsinghua Supernova Survey (PTSS) The observation was performed with the Asiago 1.82 m Copernico Telescope (+AFOSC; range 340-820 nm; resolution 1.4 nm).

  1. A Thermodynamic Classification of Real Numbers

    OpenAIRE

    Garrity, Thomas

    2008-01-01

    A new classification scheme for real numbers is given, motivated by ideas from statistical mechanics in general and work of Knauf and of Fiala and Kleban in particular. Critical for this classification of a real number will be the Diophantine properties of its continued fraction expansion.

  2. Classification error of the thresholded independence rule

    DEFF Research Database (Denmark)

    Bak, Britta Anker; Fenger-Grøn, Morten; Jensen, Jens Ledet

    We consider classification in the situation of two groups with normally distributed data in the ‘large p small n’ framework. To counterbalance the high number of variables we consider the thresholded independence rule. An upper bound on the classification error is established which is taylored to a...

  3. Investigating Elementary Teachers' Conceptions of Animal Classification

    Science.gov (United States)

    Burgoon, Jacob N.; Duran, Emilio

    2012-01-01

    Numerous studies have been conducted regarding alternative conceptions about animal diversity and classification, many of which have used a cross-age approach to investigate how students' conceptions change over time. None of these studies, however, have investigated teachers' conceptions of animal classification. This study was intended to…

  4. Developing an Intertextuality-Oriented Fiction Classification

    Science.gov (United States)

    Vernitski, Anat

    2007-01-01

    The purpose of this paper is to suggest a model for an intertextuality-oriented classification scheme for fiction, to be used by Humanities scholars studying fiction. The methodology used includes a literature review to establish background, followed by the development of a classification scheme by modifying and adding to existing fiction…

  5. Classification systems for natural resource management

    Science.gov (United States)

    Kleckner, Richard L.

    1981-01-01

    Resource managers employ various types of resource classification systems in their management activities such as inventory, mapping, and data analysis. Classification is the ordering or arranging of objects into groups or sets on the basis of their relationships, and as such, provide the resource managers with a structure for organizing their needed information. In addition of conforming to certain logical principles, resource classifications should be flexible, widely applicable to a variety of environmental conditions, and useable with minimal training. The process of classification may be approached from the bottom up (aggregation) or the top down (subdivision) or a combination of both, depending on the purpose of the classification. Most resource classification systems in use today focus on a single resource and are used for a single, limited purpose. However, resource managers now must employ the concept of multiple use in their management activities. What they need is an integrated, ecologically based approach to resource classification which would fulfill multiple-use mandates. In an effort to achieve resource-data compatibility and data sharing among Federal agencies, and interagency agreement has been signed by five Federal agencies to coordinate and cooperate in the area of resource classification and inventory.

  6. Sentiment classification with interpolated information diffusion kernels

    NARCIS (Netherlands)

    Raaijmakers, S.

    2007-01-01

    Information diffusion kernels - similarity metrics in non-Euclidean information spaces - have been found to produce state of the art results for document classification. In this paper, we present a novel approach to global sentiment classification using these kernels. We carry out a large array of e

  7. STUDY ON CLASSIFICATION SYSTEM FOR CHINESE COAL

    Institute of Scientific and Technical Information of China (English)

    陈鹏

    1998-01-01

    An integrated coal classification system-technical/commercial and scientific/geneticclassification in China is discussed in this paper. This system shall enable producers, sellers andpurchasers to communicate unambiguously with regard to the quality of coal complying with therequirements of the respective application. The determination of perfect coal classification systemis an important measure for rational utilization of coal resources.

  8. 5 CFR 2500.5 - Derivative classification.

    Science.gov (United States)

    2010-01-01

    ... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Derivative classification. 2500.5 Section 2500.5 Administrative Personnel OFFICE OF ADMINISTRATION, EXECUTIVE OFFICE OF THE PRESIDENT INFORMATION SECURITY REGULATION § 2500.5 Derivative classification. The Office of Administration serves only as...

  9. 28 CFR 17.26 - Derivative classification.

    Science.gov (United States)

    2010-07-01

    ..., the ISOO implementing directives in 32 CFR 2001.22, and internal Department directions provided by the... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Derivative classification. 17.26 Section... ACCESS TO CLASSIFIED INFORMATION Classified Information § 17.26 Derivative classification. (a)...

  10. 18 CFR 367.26 - Departmental classification.

    Science.gov (United States)

    2010-04-01

    ... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Departmental classification. 367.26 Section 367.26 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY... ACT General Instructions § 367.26 Departmental classification. Salaries and wages and all other...

  11. 46 CFR 162.028-2 - Classification.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 6 2010-10-01 2010-10-01 false Classification. 162.028-2 Section 162.028-2 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT, CONSTRUCTION, AND MATERIALS... Classification. (a) Every portable fire extinguisher shall be classified as to type and size as specified in §...

  12. 46 CFR 164.018-3 - Classification.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 6 2010-10-01 2010-10-01 false Classification. 164.018-3 Section 164.018-3 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT, CONSTRUCTION, AND MATERIALS... Classification. The following types of retroreflective material are approved under this specification: (a) Type...

  13. 47 CFR 10.400 - Classification.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 1 2010-10-01 2010-10-01 false Classification. 10.400 Section 10.400 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL COMMERCIAL MOBILE ALERT SYSTEM Alert Message Requirements § 10.400 Classification. A Participating CMS Provider is required to receive and transmit...

  14. 46 CFR 162.039-2 - Classification.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 6 2010-10-01 2010-10-01 false Classification. 162.039-2 Section 162.039-2 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT, CONSTRUCTION, AND MATERIALS... Classification. (a) Every semiportable fire extinguisher shall be classified as to type and size as specified...

  15. 32 CFR 1602.2 - Administrative classification.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Administrative classification. 1602.2 Section 1602.2 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM DEFINITIONS § 1602.2 Administrative classification. A reclassification action relating to a registrant's...

  16. 33 CFR 154.1216 - Facility classification.

    Science.gov (United States)

    2010-07-01

    ... waters near the facility. Navigable waters is defined in 33 CFR part 2.36. (6) The fish, wildlife, and... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false Facility classification. 154.1216... Vegetable Oils Facilities § 154.1216 Facility classification. (a) The Coast Guard classifies facilities...

  17. 22 CFR 9a.4 - Classification.

    Science.gov (United States)

    2010-04-01

    ... State shall follow the standards in E.O. 11652 and the provisions of 22 CFR 9.5 through 9.8. ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Classification. 9a.4 Section 9a.4 Foreign... ENERGY PROGRAMS; RELATED MATERIAL § 9a.4 Classification. (a) Section 1 of E.O. 11932, August 4,...

  18. Hazard classification or risk assessment

    DEFF Research Database (Denmark)

    Hass, Ulla

    2013-01-01

    to substitute with less toxic compounds. Actually, if exposure is constant across product class, producersmay make substitution decisions based on hazard. Hazard classification is also useful during major accidents where there is no time for risk assessment and the exposure is likely to be...... substantial enough to be a risk. A hazard does not necessarily constitute a risk, as efforts can be done to minimize risk by reducing the exposure. Thus, the relationship between hazard and risk must be treated cautiously. Fora robust risk assessment good data on exposure to the substance is needed and...... exposure data for other similarly acting substances are needed for assessing the risk for mixture effects. Such data may, however, often be absent. Toxicological potency, i.e. the lowest dose found to cause adverse effects, has been proposed as one of the key characteristics when evaluating safety of a...

  19. Refining G-structure classifications

    International Nuclear Information System (INIS)

    Using G-structure language, a systematic, iterative formalism for computing necessary and sufficient conditions for the existence of N arbitrary linearly independent Killing spinors, in any supergravity, is presented. The key organizational tool is the common isotropy group of the Killing spinors. The formalism is illustrated for configurations in gauged SU(2) supergravity in seven dimensions admitting at least one null Killing spinor, and the possible isotropy groups are shown to be [SU(2)xR4]xR, SU(2), R5, or the identity. The constraints associated with the existence of certain additional Killing spinors are computed and used to derive numerous solutions. A discussion of the relevance of the formalism to the complete classification of all supersymmetric configurations in d=11 is given

  20. Webcam classification using simple features

    Science.gov (United States)

    Pramoun, Thitiporn; Choe, Jeehyun; Li, He; Chen, Qingshuang; Amornraksa, Thumrongrat; Lu, Yung-Hsiang; Delp, Edward J.

    2015-03-01

    Thousands of sensors are connected to the Internet and many of these sensors are cameras. The "Internet of Things" will contain many "things" that are image sensors. This vast network of distributed cameras (i.e. web cams) will continue to exponentially grow. In this paper we examine simple methods to classify an image from a web cam as "indoor/outdoor" and having "people/no people" based on simple features. We use four types of image features to classify an image as indoor/outdoor: color, edge, line, and text. To classify an image as having people/no people we use HOG and texture features. The features are weighted based on their significance and combined. A support vector machine is used for classification. Our system with feature weighting and feature combination yields 95.5% accuracy.

  1. Nudivirus Genomics: Diversity and Classification

    Institute of Scientific and Technical Information of China (English)

    Yong-jie Wang; John P. Burand; Johannes A. Jehle

    2007-01-01

    Nudiviruses represent a diverse group of arthropod specific, rod-shaped and dsDNA viruses. Due to similarities in pathology and morphology to members of the family Baculoviridae, they have been previously classified as the so-called "non-occluded" baculoviruses. However, presently they are taxonomically orphaned and are not assigned to any virus family because of the lack of genetic relatedness to Baculoviridae,. Here, we report on recent progress in the genomic analysis of Heliothis zea nudivirus 1 (HzNV-1), Oryctes rhinoceros nudivirus (OrNV), Gryllus bimaculatus nudivirus (GbNV) and Heliotis zea nudivirus 2 (HzNV-2). Gene content comparison and phylogenetic analyses indicated that the viruses share 15 core genes with baculoviruses and form a monophyletic sister group to them. Consequences of the genetic relationship are discussed for the classification of nudiviruses.

  2. Families classification including multiopposition asteroids

    Science.gov (United States)

    Milani, Andrea; Spoto, Federica; Knežević, Zoran; Novaković, Bojan; Tsirvoulis, Georgios

    2016-01-01

    In this paper we present the results of our new classification of asteroid families, upgraded by using catalog with > 500,000 asteroids. We discuss the outcome of the most recent update of the family list and of their membership. We found enough evidence to perform 9 mergers of the previously independent families. By introducing an improved method of estimation of the expected family growth in the less populous regions (e.g. at high inclination) we were able to reliably decide on rejection of one tiny group as a probable statistical fluke. Thus we reduced our current list to 115 families. We also present newly determined ages for 6 families, including complex 135 and 221, improving also our understanding of the dynamical vs. collisional families relationship. We conclude with some recommendations for the future work and for the family name problem.

  3. Inclination-Independent Galaxy Classification

    CERN Document Server

    Bailin, Jeremy

    2008-01-01

    We present a new method to classify galaxies from large surveys like the Sloan Digital Sky Survey using inclination-corrected concentration, inclination-corrected location on the color-magnitude diagram, and apparent axis ratio. Explicitly accounting for inclination tightens the distribution of each of these parameters and enables simple boundaries to be drawn that delineate three different galaxy populations: Early-type galaxies, which are red, highly concentrated, and round; Late-type galaxies, which are blue, have low concentrations, and are disk dominated; and Intermediate-type galaxies, which are red, have intermediate concentrations, and have disks. We have validated our method by comparing to visual classifications of high-quality imaging data from the Millennium Galaxy Catalogue. The inclination correction is crucial to unveiling the previously unrecognized Intermediate class. Intermediate-type galaxies, roughly corresponding to lenticulars and early spirals, lie on the red sequence. The red sequence ...

  4. Textural features for image classification

    Science.gov (United States)

    Haralick, R. M.; Dinstein, I.; Shanmugam, K.

    1973-01-01

    Description of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

  5. Idiopathic interstitial pneumonias: Classification revision

    Directory of Open Access Journals (Sweden)

    Demosthenes Bouros MD, PhD, FCCP

    2010-01-01

    Full Text Available The American Thoracic Society (ATS, the European Respiratory Society (ERS and the Japan Respiratory Society (JRS are planning a revision of the 2002 ATS/ERS International Multidisciplinary Classification of Idiopathic Interstitial Pneumonias (IIPs1. In two years’ time it will be 10 years since its publication and with a view to publishing the revision after 10 years (i.e., in 2012, a steering committee has been established, which met in New Orleans during ATS congress in May 2010 and more recently in Barcelona during the ERS congress (Photo. The committee will meet again during the ATS and the ERS congresses that will be held in the next two years, with an additional meeting in Modena, Italy, in Αpril 2011.

  6. Biological signals classification and analysis

    CERN Document Server

    Kiasaleh, Kamran

    2015-01-01

    This authored monograph presents key aspects of signal processing analysis in the biomedical arena. Unlike wireless communication systems, biological entities produce signals with underlying nonlinear, chaotic nature that elude classification using the standard signal processing techniques, which have been developed over the past several decades for dealing primarily with standard communication systems. This book separates what is random from that which appears to be random, and yet is truly deterministic with random appearance. At its core, this work gives the reader a perspective on biomedical signals and the means to classify and process such signals. In particular, a review of random processes along with means to assess the behavior of random signals is also provided. The book also includes a general discussion of biological signals in order to demonstrate the inefficacy of the well-known techniques to correctly extract meaningful information from such signals. Finally, a thorough discussion of recently ...

  7. Autoclass: An automatic classification system

    Science.gov (United States)

    Stutz, John; Cheeseman, Peter; Hanson, Robin

    1991-01-01

    The task of inferring a set of classes and class descriptions most likely to explain a given data set can be placed on a firm theoretical foundation using Bayesian statistics. Within this framework, and using various mathematical and algorithmic approximations, the AutoClass System searches for the most probable classifications, automatically choosing the number of classes and complexity of class descriptions. A simpler version of AutoClass has been applied to many large real data sets, has discovered new independently-verified phenomena, and has been released as a robust software package. Recent extensions allow attributes to be selectively correlated within particular classes, and allow classes to inherit, or share, model parameters through a class hierarchy. The mathematical foundations of AutoClass are summarized.

  8. Projection Classification Based Iterative Algorithm

    Science.gov (United States)

    Zhang, Ruiqiu; Li, Chen; Gao, Wenhua

    2015-05-01

    Iterative algorithm has good performance as it does not need complete projection data in 3D image reconstruction area. It is possible to be applied in BGA based solder joints inspection but with low convergence speed which usually acts with x-ray Laminography that has a worse reconstruction image compared to the former one. This paper explores to apply one projection classification based method which tries to separate the object to three parts, i.e. solute, solution and air, and suppose that the reconstruction speed decrease from solution to two other parts on both side lineally. And then SART and CAV algorithms are improved under the proposed idea. Simulation experiment result with incomplete projection images indicates the fast convergence speed of the improved iterative algorithms and the effectiveness of the proposed method. Less the projection images, more the superiority is also founded.

  9. Morphological classification of nanoceramic aggregates

    Science.gov (United States)

    Crosta, Giovanni F.; Kang, Bongwoo; Ospina, Carolina; Sung, Changmo

    2005-01-01

    Aluminum silicate nanoaggregates grown at near-room temperature on an organic template under a variety of experimental conditions have been imaged by transmission electron microscopy. Images have been automatically classified by an algorithm based on "spectrum enhancement", multivariate statistics and supervised optimization. Spectrum enhancement consists of subtracting, in the log scale, a known function of wavenumber from the angle averaged power spectral density of the image. Enhanced spectra of each image, after polynomial interpolation, have been regarded as morphological descriptors and as such submitted to principal components analysis nested with a multiobjective parameter optimization algorithm. The latter has maximized pairwise discrimination between classes of materials. The role of the organic template and of a reaction parameter on aggregate morphology has been assessed at two magnification scales. Classification results have also been related to crystal structure data derived from selected area electron diffraction patterns.

  10. Sow-activity classification from acceleration patterns

    DEFF Research Database (Denmark)

    Escalante, Hugo Jair; Rodriguez, Sara V.; Cordero, Jorge; Kristensen, Anders Ringgaard; Cornou, Cecile

    2013-01-01

    sow-activity classification can be approached with standard machine learning methods for pattern classification. Individual predictions for elements of times series of arbitrary length are combined to classify it as a whole. An extensive comparison of representative learning algorithms, including......This paper describes a supervised learning approach to sow-activity classification from accelerometer measurements. In the proposed methodology, pairs of accelerometer measurements and activity types are considered as labeled instances of a usual supervised classification task. Under this scenario...... neural networks, support vector machines, and ensemble methods, is presented. Experimental results are reported using a data set for sow-activity classification collected in a real production herd. The data set, which has been widely used in related works, includes measurements from active (Feeding...

  11. The Classification and Indexing of Imaginative Literature

    DEFF Research Database (Denmark)

    Eriksson, Rune

    2005-01-01

    Classification, then analyzes the main structures in the modern classification and indexing in the Library of Congress and in the Danish Bibliographic Centre. It is concluded that the classification of imaginative literature not has changed very much since the days of Dewey and that the indexing largely reflects......With the indexing of imaginative literature included in an expanding number of bibliographic databases, the overall representation of this kind of literature has definitely been improved. Still, in terms of information retrieval and being able to judge the relevance of the titles, it seems that the...... usefulness of classification and indexing alike are still being restricted by some old romantic and objectivistic, or even positivistic, ideas and ideals. In order to argue that point the paper firstly re-examines the classification of imaginative literature in early editions of the Dewey Decimal...

  12. Texture Classification Based on Texton Features

    Directory of Open Access Journals (Sweden)

    U Ravi Babu

    2012-08-01

    Full Text Available Texture Analysis plays an important role in the interpretation, understanding and recognition of terrain, biomedical or microscopic images. To achieve high accuracy in classification the present paper proposes a new method on textons. Each texture analysis method depends upon how the selected texture features characterizes image. Whenever a new texture feature is derived it is tested whether it precisely classifies the textures. Here not only the texture features are important but also the way in which they are applied is also important and significant for a crucial, precise and accurate texture classification and analysis. The present paper proposes a new method on textons, for an efficient rotationally invariant texture classification. The proposed Texton Features (TF evaluates the relationship between the values of neighboring pixels. The proposed classification algorithm evaluates the histogram based techniques on TF for a precise classification. The experimental results on various stone textures indicate the efficacy of the proposed method when compared to other methods.

  13. Classification of Radioactive Waste. General Safety Guide

    International Nuclear Information System (INIS)

    This publication is a revision of an earlier Safety Guide of the same title issued in 1994. It recommends revised waste management strategies that reflect changes in practices and approaches since then. It sets out a classification system for the management of waste prior to disposal and for disposal, driven by long term safety considerations. It includes a number of schemes for classifying radioactive waste that can be used to assist with planning overall national approaches to radioactive waste management and to assist with operational management at facilities. Contents: 1. Introduction; 2. The radioactive waste classification scheme; Appendix: The classification of radioactive waste; Annex I: Evolution of IAEA standards on radioactive waste classification; Annex II: Methods of classification; Annex III: Origin and types of radioactive waste

  14. ACCUWIND - Methods for classification of cup anemometers

    DEFF Research Database (Denmark)

    Dahlberg, J.-Å.; Friis Pedersen, Troels; Busche, P.

    2006-01-01

    the errors associated with the use of cup anemometers, and to develop a classification system for quantification of systematic errors of cup anemometers. This classification system has now been implementedin the IEC 61400-12-1 standard on power performance measurements in annex I and J. The...... classification of cup anemometers requires general external climatic operational ranges to be applied for the analysis of systematic errors. A Class A categoryclassification is connected to reasonably flat sites, and another Class B category is connected to complex terrain, General classification indices are the...... theclassification process in order to assess the robustness of methods. The results of the analysis are presented as classification indices, which are compared and discussed....

  15. Decomposition and classification of electroencephalography data

    DEFF Research Database (Denmark)

    Frølich, Laura

    This thesis is about linear and multi-linear analyses of electroencephalography (EEG) data and classification of estimated EEG sources. One contribution consists of an automatic classification method for independent components (ICs) of EEG data and a freely available implementation as an EEGLab...... plug-in, “IC Classification into Multiple Artefact Classes” (IC_MARC). Four artefact classes (blinks, heart beats, lateral eye movements, and muscle contractions), a neural class, and a mixed class (representing none or a mix of the other classes) were considered. We showed that classification is...... possible between subjects within studies over all classes. When generalising across studies a high classification rate of neural vs. non-neural ICs was retained but the multi-class performance dropped. In another study, we used IC_MARC to compare the ability to separate artefactual from neural sources of...

  16. Human error classification and data collection

    International Nuclear Information System (INIS)

    Analysis of human error data requires human error classification. As the human factors/reliability subject has developed so too has the topic of human error classification. The classifications vary considerably depending on whether it has been developed from a theoretical psychological approach to understanding human behavior or error, or whether it has been based on an empirical practical approach. This latter approach is often adopted by nuclear power plants that need to make practical improvements as soon as possible. This document will review aspects of human error classification and data collection in order to show where potential improvements could be made. It will attempt to show why there are problems with human error classification and data collection schemes and that these problems will not be easy to resolve. The Annex of this document contains the papers presented at the meeting. A separate abstract was prepared for each of these 12 papers. Refs, figs and tabs

  17. Extreme Learning Machine for land cover classification

    CERN Document Server

    Pal, Mahesh

    2008-01-01

    This paper explores the potential of extreme learning machine based supervised classification algorithm for land cover classification. In comparison to a backpropagation neural network, which requires setting of several user-defined parameters and may produce local minima, extreme learning machine require setting of one parameter and produce a unique solution. ETM+ multispectral data set (England) was used to judge the suitability of extreme learning machine for remote sensing classifications. A back propagation neural network was used to compare its performance in term of classification accuracy and computational cost. Results suggest that the extreme learning machine perform equally well to back propagation neural network in term of classification accuracy with this data set. The computational cost using extreme learning machine is very small in comparison to back propagation neural network.

  18. 14 CFR Section 19 - Uniform Classification of Operating Statistics

    Science.gov (United States)

    2010-01-01

    ... Statistics Section 19 Section 19 Aeronautics and Space OFFICE OF THE SECRETARY, DEPARTMENT OF TRANSPORTATION... AIR CARRIERS Operating Statistics Classifications Section 19 Uniform Classification of Operating Statistics...

  19. La LC classification come linked data

    Directory of Open Access Journals (Sweden)

    Kevin Ford

    2013-01-01

    Full Text Available In 2009 and in 2011, the Library of Congress made two of its largest authority files – Subject Headings and Names – available as linked data via LC’s Linked Data Service, ID.LOC.GOV. Both are offered in MADS/RDF and SKOS. It is LC’s objective, in 2012, to publish another of its largest authority files as linked data: LC Classification. Whereas the source records for Subject Headings and Names are encoded in the MARC Authority format, from which there is a relatively straightforward mapping to MADS/RDF and SKOS, LC Classification records rely on the MARC Classification format. Mapping from LC Classification to MADS/RDF or SKOS has been a little more challenging. For example, records that represent classification ranges, which are not Concepts intended to be assigned, are not easily accommodated in SKOS. This presents additional problems when needing to accurately represent the relationships in RDF for LC Classification. With comparison to the publication of LCSH and Names at ID.LOC.GOV, this paper will examine issues encountered – and how those challenges were addressed – during the conversion of LC Classification to MADS/RDF and SKOS for release as linked data at ID.LOC.GOV.

  20. Pet fur color and texture classification

    Science.gov (United States)

    Yen, Jonathan; Mukherjee, Debarghar; Lim, SukHwan; Tretter, Daniel

    2007-01-01

    Object segmentation is important in image analysis for imaging tasks such as image rendering and image retrieval. Pet owners have been known to be quite vocal about how important it is to render their pets perfectly. We present here an algorithm for pet (mammal) fur color classification and an algorithm for pet (animal) fur texture classification. Per fur color classification can be applied as a necessary condition for identifying the regions in an image that may contain pets much like the skin tone classification for human flesh detection. As a result of the evolution, fur coloration of all mammals is caused by a natural organic pigment called Melanin and Melanin has only very limited color ranges. We have conducted a statistical analysis and concluded that mammal fur colors can be only in levels of gray or in two colors after the proper color quantization. This pet fur color classification algorithm has been applied for peteye detection. We also present here an algorithm for animal fur texture classification using the recently developed multi-resolution directional sub-band Contourlet transform. The experimental results are very promising as these transforms can identify regions of an image that may contain fur of mammals, scale of reptiles and feather of birds, etc. Combining the color and texture classification, one can have a set of strong classifiers for identifying possible animals in an image.

  1. ACCUWIND - Methods for classification of cup anemometers

    Energy Technology Data Exchange (ETDEWEB)

    Dahlberg, J.Aa.; Friis Pedersen, T.; Busche, P.

    2006-05-15

    Errors associated with the measurement of wind speed are the major sources of uncertainties in power performance testing of wind turbines. Field comparisons of well-calibrated anemometers show significant and not acceptable difference. The European CLASSCUP project posed the objectives to quantify the errors associated with the use of cup anemometers, and to develop a classification system for quantification of systematic errors of cup anemometers. This classification system has now been implemented in the IEC 61400-12-1 standard on power performance measurements in annex I and J. The classification of cup anemometers requires general external climatic operational ranges to be applied for the analysis of systematic errors. A Class A category classification is connected to reasonably flat sites, and another Class B category is connected to complex terrain, General classification indices are the result of assessment of systematic deviations. The present report focuses on methods that can be applied for assessment of such systematic deviations. A new alternative method for torque coefficient measurements at inclined flow have been developed, which have then been applied and compared to the existing methods developed in the CLASSCUP project and earlier. A number of approaches including the use of two cup anemometer models, two methods of torque coefficient measurement, two angular response measurements, and inclusion and exclusion of influence of friction have been implemented in the classification process in order to assess the robustness of methods. The results of the analysis are presented as classification indices, which are compared and discussed. (au)

  2. Classifications of patterned hair loss: a review

    Directory of Open Access Journals (Sweden)

    Mrinal Gupta

    2016-01-01

    Full Text Available Patterned hair loss is the most common cause of hair loss seen in both the sexes after puberty. Numerous classification systems have been proposed by various researchers for grading purposes. These systems vary from the simpler systems based on recession of the hairline to the more advanced multifactorial systems based on the morphological and dynamic parameters that affect the scalp and the hair itself. Most of these preexisting systems have certain limitations. Currently, the Hamilton-Norwood classification system for males and the Ludwig system for females are most commonly used to describe patterns of hair loss. In this article, we review the various classification systems for patterned hair loss in both the sexes. Relevant articles were identified through searches of MEDLINE and EMBASE. Search terms included but were not limited to androgenic alopecia classification, patterned hair loss classification, male pattern baldness classification, and female pattern hair loss classification. Further publications were identified from the reference lists of the reviewed articles.

  3. Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification

    Science.gov (United States)

    Hepner, George F.; Logan, Thomas; Ritter, Niles; Bryant, Nevin

    1990-01-01

    Recent research has shown an artificial neural network (ANN) to be capable of pattern recognition and the classification of image data. This paper examines the potential for the application of neural network computing to satellite image processing. A second objective is to provide a preliminary comparison and ANN classification. An artificial neural network can be trained to do land-cover classification of satellite imagery using selected sites representative of each class in a manner similar to conventional supervised classification. One of the major problems associated with recognition and classifications of pattern from remotely sensed data is the time and cost of developing a set of training sites. This reseach compares the use of an ANN back propagation classification procedure with a conventional supervised maximum likelihood classification procedure using a minimal training set. When using a minimal training set, the neural network is able to provide a land-cover classification superior to the classification derived from the conventional classification procedure. This research is the foundation for developing application parameters for further prototyping of software and hardware implementations for artificial neural networks in satellite image and geographic information processing.

  4. Audio-Visual Classification of Sports Types

    DEFF Research Database (Denmark)

    Gade, Rikke; Abou-Zleikha, Mohamed; Christensen, Mads Græsbøll;

    2015-01-01

    In this work we propose a method for classification of sports types from combined audio and visual features ex- tracted from thermal video. From audio Mel Frequency Cepstral Coefficients (MFCC) are extracted, and PCA are applied to reduce the feature space to 10 dimensions. From the visual modality...... short trajectories are constructed to rep- resent the motion of players. From these, four motion fea- tures are extracted and combined directly with audio fea- tures for classification. A k-nearest neighbour classifier is applied for classification of 180 1-minute video sequences from three sports types...

  5. Innovating Web Page Classification Through Reducing Noise

    Institute of Scientific and Technical Information of China (English)

    LI Xiaoli (李晓黎); SHI Zhongzhi(史忠植)

    2002-01-01

    This paper presents a new method that eliminates noise in Web page classification. It first describes the presentation of a Web page based on HTML tags. Then through a novel distance formula, it eliminates the noise in similarity measure. After carefully analyzing Web pages, we design an algorithm that can distinguish related hyperlinks from noisy ones.We can utilize non-noisy hyperlinks to improve the performance of Web page classification (the CAWN algorithm). For any page, wecan classify it through the text and category of neighbor pages related to the page. The experimental results show that our approach improved classification accuracy.

  6. Dental fitness classification in the Canadian forces.

    Science.gov (United States)

    Groves, Richard R

    2008-01-01

    The Canadian Forces Dental Services utilizes a dental classification system to identify those military members dentally fit for an overseas deployment where dental resources may be limited. Although the Canadian Forces Dental Services dental classification system is based on NATO standards, it differs slightly from the dental classification systems of other NATO country dental services. Data collected by dental teams on overseas deployments indicate a low rate of emergency dental visits by Canadian Forces members who were screened as dentally fit to deploy. PMID:18277717

  7. Sports Type Classification using Signature Heatmaps

    DEFF Research Database (Denmark)

    Gade, Rikke; Moeslund, Thomas B.

    Automatic classification of activities in a sports arena is important in order to analyse and optimise the use of the arenas. In this work we classify five sports types based only on occupancy heatmaps produced from position data. Due to privacy issues we use thermal imaging for detecting people...... and then calculate their positions on the court us- ing homography. Heatmaps are produced by summarising Gaussian distributions respresenting people over 10-minute periods. Before classification the heatmaps are projected to a low-dimensional discriminative space using the principle of Fisherfaces....... Our result using two weeks of video are very promising with a correct classification of 90.76 %....

  8. Classification and Analysis of Computer Network Traffic

    DEFF Research Database (Denmark)

    Bujlow, Tomasz

    2014-01-01

    of traffic for academic purposes. We define the objective of this thesis as finding a way to evaluate the performance of various applications in a high-speed Internet infrastructure. To satisfy the objective, we needed to answer a number of research questions. The biggest extent of them concern techniques...... classification (as by using transport layer port numbers, Deep Packet Inspection (DPI), statistical classification) and assessed their usefulness in particular areas. We found that the classification techniques based on port numbers are not accurate anymore as most applications use dynamic port numbers, while...

  9. Towards the automatic classification of neurons.

    Science.gov (United States)

    Armañanzas, Rubén; Ascoli, Giorgio A

    2015-05-01

    The classification of neurons into types has been much debated since the inception of modern neuroscience. Recent experimental advances are accelerating the pace of data collection. The resulting growth of information about morphological, physiological, and molecular properties encourages efforts to automate neuronal classification by powerful machine learning techniques. We review state-of-the-art analysis approaches and the availability of suitable data and resources, highlighting prominent challenges and opportunities. The effective solution of the neuronal classification problem will require continuous development of computational methods, high-throughput data production, and systematic metadata organization to enable cross-laboratory integration. PMID:25765323

  10. Unification as a Measure of Natural Classification

    Directory of Open Access Journals (Sweden)

    Victor Gijsbers

    2014-02-01

    Full Text Available Recent interest in the idea that there can be scientific understanding without explanation lends new relevance to Duhem's notion of natural classification. According to Duhem, a classification that is natural teaches us something about nature without being explanatory. However, Duhem's conception of naturalness leaves much to be desired. In this paper, I argue that we can measure the naturalness of classification by using an amended version of the notion of unification as defined by Schurz and Lambert. If this thesis is correct, it both leads to a better conceptual understanding of scientific understanding, and also gives the nascent literature on this topic some much-needed precision.

  11. Classification, staging and radiotherapy of bronchial carcinoma

    International Nuclear Information System (INIS)

    This thesis reports a study performed to evaluate the stage classification of bronchial carcinoma published by Thomas in 1963. The study was done in the radiotherapy department of a teaching hospital, and had three parts: a comparative analysis of the classifications and stage divisions described in the literature on bronchial carcinoma; an evaluation of the theoretical basis of the classification system introduced by Thomas as well as of the practical applicability of the division into stages, with respect to the assessment of the prognosis and the choice of therapy; and an analysis of various aspects of irradiation as well as of a number of prognostic factors in bronchial carcinoma. (Auth.)

  12. Mapping a classification system to architectural education

    DEFF Research Database (Denmark)

    Hermund, Anders; Klint, Lars; Rostrup, Nicolai

    2015-01-01

    This paper examines to what extent a new classification system, Cuneco Classification System, CCS, proves useful in the education of architects, and to what degree the aim of an architectural education, rather based on an arts and crafts approach than a polytechnic approach, benefits from the...... distinct terminology of the classification system. The method used to examine the relationship between education, practice and the CCS bifurcates in a quantitative and a qualitative exploration: Quantitative comparison of the curriculum with the students’ own descriptions of their studies through a...

  13. Rademacher Complexity in Neyman-Pearson Classification

    Institute of Scientific and Technical Information of China (English)

    Min HAN; Di Rong CHEN; Zhao Xu SUN

    2009-01-01

    Neyman-Pearson(NP) criterion is one of the most important ways in hypothesis testing.It is also a criterion for classification. This paper addresses the problem of bounding the estimation error of NP classification, in terms of Rademacher averages. We investigate the behavior of the global and local Rademacher averages, and present new NP classification error bounds which are based on the localized averages, and indicate how the estimation error can be estimated without a priori knowledge of the class at hand.

  14. Towards a genetic classification of uranium deposits

    International Nuclear Information System (INIS)

    As the IAEA's uranium deposit classification is based on the deposit nature and morphology, some deposits which have been formed by very different genetic processes and located in very different geological environments, are grouped according to this classification. In order to build up a reliable genetic classification based on the mechanism at the origin of the formation of the deposit, the author presents the five main categories according to which uranium deposits can be classified: magmatic, hydrothermal, evapotranspiration, syn-sedimentary, and infiltration of meteoric water

  15. Gender Classification by Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Payman Moallem

    2013-02-01

    Full Text Available Gender classification from face images has many applications and is thus an important research topic. This paper presents an approach to gender classification based on shape and texture information gathered to design a fuzzy decision making system. Beside face shape features, Zernik moments are applied as system inputs to improve the system output which is considered as the probability of being male face image. After parameters tuning of the proposed fuzzy decision making system, 85.05% classification rate on the FERET face database (including 1199 individuals from different poses and facial expressions shows acceptable results compare to other methods.

  16. Neural Networks for Emotion Classification

    CERN Document Server

    Sun, Yafei

    2011-01-01

    It is argued that for the computer to be able to interact with humans, it needs to have the communication skills of humans. One of these skills is the ability to understand the emotional state of the person. This thesis describes a neural network-based approach for emotion classification. We learn a classifier that can recognize six basic emotions with an average accuracy of 77% over the Cohn-Kanade database. The novelty of this work is that instead of empirically selecting the parameters of the neural network, i.e. the learning rate, activation function parameter, momentum number, the number of nodes in one layer, etc. we developed a strategy that can automatically select comparatively better combination of these parameters. We also introduce another way to perform back propagation. Instead of using the partial differential of the error function, we use optimal algorithm; namely Powell's direction set to minimize the error function. We were also interested in construction an authentic emotion databases. This...

  17. Graphical Classification of Entangled Qutrits

    Directory of Open Access Journals (Sweden)

    Kentaro Honda

    2012-10-01

    Full Text Available A multipartite quantum state is entangled if it is not separable. Quantum entanglement plays a fundamental role in many applications of quantum information theory, such as quantum teleportation. Stochastic local quantum operations and classical communication (SLOCC cannot essentially change quantum entanglement without destroying it. Therefore, entanglement can be classified by dividing quantum states into equivalence classes, where two states are equivalent if each can be converted into the other by SLOCC. Properties of this classification, especially in the case of non two-dimensional quantum systems, have not been well studied. Graphical representation is sometimes used to clarify the nature and structural features of entangled states. SLOCC equivalence of quantum bits (qubits has been described graphically via a connection between tripartite entangled qubit states and commutative Frobenius algebras (CFAs in monoidal categories. In this paper, we extend this method to qutrits, i.e., systems that have three basis states. We examine the correspondence between CFAs and tripartite entangled qutrits. Using the symmetry property, which is required by the definition of a CFA, we find that there are only three equivalence classes that correspond to CFAs. We represent qutrits graphically, using the connection to CFAs. We derive equations that characterize the three equivalence classes. Moreover, we show that any qutrit can be represented as a composite of three graphs that correspond to the three classes.

  18. New climatic classification of Nepal

    Science.gov (United States)

    Karki, Ramchandra; Talchabhadel, Rocky; Aalto, Juha; Baidya, Saraju Kumar

    2016-08-01

    Although it is evident that Nepal has an extremely wide range of climates within a short latitudinal distance, there is a lack of comprehensive research in this field. The climatic zoning in a topographically complex country like Nepal has important implications for the selection of scientific station network design and climate model verification, as well as for studies examining the effects of climate change in terms of shifting climatic boundaries and vegetation in highly sensitive environments. This study presents a new high-resolution climate map of Nepal on the basis of long-term (1981-2010) monthly precipitation data for 240 stations and mean air temperature data for 74 stations, using original and modified Köppen-Geiger climate classification systems. Climatic variables used in Köppen-Geiger system were calculated (i) at each station and (ii) interpolated to 1-km spatial resolution using kriging which accounted for latitude, longitude, and elevation. The original Köppen-Geiger scheme could not identify all five types of climate (including tropical) observed in Nepal. Hence, the original scheme was slightly modified by changing the boundary of coldest month mean air temperature value from 18 °C to 14.5 °C in order to delineate the realistic climatic condition of Nepal. With this modification, all five types of climate (including tropical) were identified. The most common dominant type of climate for Nepal is temperate with dry winter and hot summer (Cwa).

  19. Pattern Classification in Kampo Medicine

    Directory of Open Access Journals (Sweden)

    S. Yakubo

    2014-01-01

    Full Text Available Pattern classification is very unique in traditional medicine. Kampo medical patterns have transformed over time during Japan’s history. In the 17th to 18th centuries, Japanese doctors advocated elimination of the Ming medical theory and followed the basic concepts put forth by Shang Han Lun and Jin Gui Yao Lue in the later Han dynasty (25–220 AD. The physician Todo Yoshimasu (1702–1773 emphasized that an appropriate treatment could be administered if a set of patterns could be identified. This principle is still referred to as “matching of pattern and formula” and is the basic concept underlying Kampo medicine today. In 1868, the Meiji restoration occurred, and the new government changed its policies to follow that of the European countries, adopting only Western medicine. Physicians trained in Western medicine played an important role in the revival of Kampo medicine, modernizing Kampo patterns to avoid confusion with Western biomedical terminology. In order to understand the Japanese version of traditional disorders and patterns, background information on the history of Kampo and its role in the current health care system in Japan is important. In this paper we overviewed the formation of Kampo patterns.

  20. Redesigning Language Learning Strategy Classifications

    Directory of Open Access Journals (Sweden)

    Ag. Bambang Setiyadi

    2004-01-01

    Full Text Available In the current study a total of 79 university students of a 3-month English course participated. This study attempted to explore what learning strategies language Indonesian learners used and how the strategies were classified. To increase the internal consistency of the hypotesized scales, Cronbach Alpha coefficients of internal consistency were computed for each scale of skill-based areas, namely: speaking, listening, reading and writing. Correlation analysis was also conducted to see how variance of speaking, listening, reading and writing in language learning strategy questionnare were correlated. The result shows that each skill-based scale has realatively high reliability with alpha .73, .67, .69, .80 for listening, speaking, reading, and writing respectively. It is also found out that the four scales are significantly and positively correlated. The classification of learning strategies based on the language skills is a new way of learning strategy measurement, which may be worth considering in the Indonesian context in which English is learned as a foreign language.

  1. New climatic classification of Nepal

    Science.gov (United States)

    Karki, Ramchandra; Talchabhadel, Rocky; Aalto, Juha; Baidya, Saraju Kumar

    2015-07-01

    Although it is evident that Nepal has an extremely wide range of climates within a short latitudinal distance, there is a lack of comprehensive research in this field. The climatic zoning in a topographically complex country like Nepal has important implications for the selection of scientific station network design and climate model verification, as well as for studies examining the effects of climate change in terms of shifting climatic boundaries and vegetation in highly sensitive environments. This study presents a new high-resolution climate map of Nepal on the basis of long-term (1981-2010) monthly precipitation data for 240 stations and mean air temperature data for 74 stations, using original and modified Köppen-Geiger climate classification systems. Climatic variables used in Köppen-Geiger system were calculated (i) at each station and (ii) interpolated to 1-km spatial resolution using kriging which accounted for latitude, longitude, and elevation. The original Köppen-Geiger scheme could not identify all five types of climate (including tropical) observed in Nepal. Hence, the original scheme was slightly modified by changing the boundary of coldest month mean air temperature value from 18 °C to 14.5 °C in order to delineate the realistic climatic condition of Nepal. With this modification, all five types of climate (including tropical) were identified. The most common dominant type of climate for Nepal is temperate with dry winter and hot summer (Cwa).

  2. Molecular classification of gastric cancer.

    Science.gov (United States)

    Chia, N-Y; Tan, P

    2016-05-01

    Gastric cancer (GC), a heterogeneous disease characterized by epidemiologic and histopathologic differences across countries, is a leading cause of cancer-related death. Treatment of GC patients is currently suboptimal due to patients being commonly treated in a uniform fashion irrespective of disease subtype. With the advent of next-generation sequencing and other genomic technologies, GCs are now being investigated in great detail at the molecular level. High-throughput technologies now allow a comprehensive study of genomic and epigenomic alterations associated with GC. Gene mutations, chromosomal aberrations, differential gene expression and epigenetic alterations are some of the genetic/epigenetic influences on GC pathogenesis. In addition, integrative analyses of molecular profiling data have led to the identification of key dysregulated pathways and importantly, the establishment of GC molecular classifiers. Recently, The Cancer Genome Atlas (TCGA) network proposed a four subtype classification scheme for GC based on the underlying tumor molecular biology of each subtype. This landmark study, together with other studies, has expanded our understanding on the characteristics of GC at the molecular level. Such knowledge may improve the medical management of GC in the future. PMID:26861606

  3. Classification algorithms using adaptive partitioning

    KAUST Repository

    Binev, Peter

    2014-12-01

    © 2014 Institute of Mathematical Statistics. Algorithms for binary classification based on adaptive tree partitioning are formulated and analyzed for both their risk performance and their friendliness to numerical implementation. The algorithms can be viewed as generating a set approximation to the Bayes set and thus fall into the general category of set estimators. In contrast with the most studied tree-based algorithms, which utilize piecewise constant approximation on the generated partition [IEEE Trans. Inform. Theory 52 (2006) 1335.1353; Mach. Learn. 66 (2007) 209.242], we consider decorated trees, which allow us to derive higher order methods. Convergence rates for these methods are derived in terms the parameter - of margin conditions and a rate s of best approximation of the Bayes set by decorated adaptive partitions. They can also be expressed in terms of the Besov smoothness β of the regression function that governs its approximability by piecewise polynomials on adaptive partition. The execution of the algorithms does not require knowledge of the smoothness or margin conditions. Besov smoothness conditions are weaker than the commonly used Holder conditions, which govern approximation by nonadaptive partitions, and therefore for a given regression function can result in a higher rate of convergence. This in turn mitigates the compatibility conflict between smoothness and margin parameters.

  4. Multinomial mixture model with heterogeneous classification probabilities

    Science.gov (United States)

    Holland, M.D.; Gray, B.R.

    2011-01-01

    Royle and Link (Ecology 86(9):2505-2512, 2005) proposed an analytical method that allowed estimation of multinomial distribution parameters and classification probabilities from categorical data measured with error. While useful, we demonstrate algebraically and by simulations that this method yields biased multinomial parameter estimates when the probabilities of correct category classifications vary among sampling units. We address this shortcoming by treating these probabilities as logit-normal random variables within a Bayesian framework. We use Markov chain Monte Carlo to compute Bayes estimates from a simulated sample from the posterior distribution. Based on simulations, this elaborated Royle-Link model yields nearly unbiased estimates of multinomial and correct classification probability estimates when classification probabilities are allowed to vary according to the normal distribution on the logit scale or according to the Beta distribution. The method is illustrated using categorical submersed aquatic vegetation data. ?? 2010 Springer Science+Business Media, LLC.

  5. Texture Classification based on Gabor Wavelet

    Directory of Open Access Journals (Sweden)

    Amandeep Kaur

    2012-07-01

    Full Text Available This paper presents the comparison of Texture classification algorithms based on Gabor Wavelets. The focus of this paper is on feature extraction scheme for texture classification. The texture feature for an image can be classified using texture descriptors. In this paper we have used Homogeneous texture descriptor that uses Gabor Wavelets concept. For texture classification, we have used online texture database that is Brodatz’s database and three advanced well known classifiers: Support Vector Machine, K-nearest neighbor method and decision tree induction method. The results shows that classification using Support vector machines gives better results as compare to the other classifiers. It can accurately discriminate between a testing image data and training data.

  6. Towards automatic classification of all WISE sources

    CERN Document Server

    Kurcz, Agnieszka; Solarz, Aleksandra; Krupa, Magdalena; Pollo, Agnieszka; Małek, Katarzyna

    2016-01-01

    The WISE satellite has detected hundreds of millions sources over the entire sky. Classifying them reliably is however a challenging task due to degeneracies in WISE multicolour space and low levels of detection in its two longest-wavelength bandpasses. Here we aim at obtaining comprehensive and reliable star, galaxy and quasar catalogues based on automatic source classification in full-sky WISE data. This means that the final classification will employ only parameters available from WISE itself, in particular those reliably measured for a majority of sources. For the automatic classification we applied the support vector machines (SVM) algorithm, which requires a training sample with relevant classes already identified, and we chose to use the SDSS spectroscopic dataset for that purpose. By calibrating the classifier on the test data drawn from SDSS, we first established that a polynomial kernel is preferred over a radial one for this particular dataset. Next, using three classification parameters (W1 magnit...

  7. Multivariate Approaches to Classification in Extragalactic Astronomy

    Directory of Open Access Journals (Sweden)

    Didier eFraix-Burnet

    2015-08-01

    Full Text Available Clustering objects into synthetic groups is a natural activity of any science. Astrophysics is not an exception and is now facing a deluge of data. For galaxies, the one-century old Hubble classification and the Hubble tuning fork are still largely in use, together with numerous mono- or bivariate classifications most often made by eye. However, a classification must be driven by the data, and sophisticated multivariate statistical tools are used more and more often. In this paper we review these different approaches in order to situate them in the general context of unsupervised and supervised learning. We insist on the astrophysical outcomes of these studies to show that multivariate analyses provide an obvious path toward a renewal of our classification of galaxies and are invaluable tools to investigate the physics and evolution of galaxies.

  8. Biological couplings:Classification and characteristic rules

    Institute of Scientific and Technical Information of China (English)

    REN LuQuan; LIANG YunHong

    2009-01-01

    introduced from the bionic viewpoint.Constitution,classification and characteristic rules of biological coupling are illuminated,the general modes of biological coupling studies are analyzed,and the prospects of multi-coupling bionics are predicted.

  9. Classification Using Markov Blanket for Feature Selection

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Luo, Jian

    Selecting relevant features is in demand when a large data set is of interest in a classification task. It produces a tractable number of features that are sufficient and possibly improve the classification performance. This paper studies a statistical method of Markov blanket induction algorithm...... for filtering features and then applies a classifier using the Markov blanket predictors. The Markov blanket contains a minimal subset of relevant features that yields optimal classification performance. We experimentally demonstrate the improved performance of several classifiers using a Markov...... blanket induction as a feature selection method. In addition, we point out an important assumption behind the Markov blanket induction algorithm and show its effect on the classification performance....

  10. Automatic classification of defects in weld pipe

    International Nuclear Information System (INIS)

    With the advancement of computer imaging technology, the image on hard radiographic film can be digitized and stored in a computer and the manual process of defect recognition and classification may be replace by the computer. In this paper a computerized method for automatic detection and classification of common defects in film radiography of weld pipe is described. The detection and classification processes consist of automatic selection of interest area on the image and then classify common defects using image processing and special algorithms. Analysis of the attributes of each defect such as area, size, shape and orientation are carried out by the feature analysis process. These attributes reveal the type of each defect. These methods of defect classification result in high success rate. Our experience showed that sharp film images produced better results

  11. Land Cover - Minnesota Land Cover Classification System

    Data.gov (United States)

    Minnesota Department of Natural Resources — Land cover data set based on the Minnesota Land Cover Classification System (MLCCS) coding scheme. This data was produced using a combination of aerial photograph...

  12. The Multidimensional Audioconferencing Classification System (MACS).

    Science.gov (United States)

    Cookson, Peter S.; Chang, Yu-bi

    1995-01-01

    Describes the development of the Multidimensional Audioconferencing Classification System (MACS), an instrument for the tabulation, analysis, and interpretation of audioconferencing instructional interactions. MACS draws on three theoretical and empirical streams: (1) systematic small group interaction analysis; (2) systematic classroom…

  13. 28 CFR 524.73 - Classification procedures.

    Science.gov (United States)

    2010-07-01

    ... of Prisons from state or territorial jurisdictions. All state prisoners while solely in service of... classification may be made at any level to achieve the immediate effect of requiring prior clearance for...

  14. Seafloor backscatter signal simulation and classification

    Digital Repository Service at National Institute of Oceanography (India)

    Mahale, V.; El Dine, W.G.; Chakraborty, B.

    . In this model a smooth echo envelope is generated then mixed up with multiplicative and additive noise. Several such echo signals were simulated for three types of seafloor. An Artificial Neural Network based classification technique is conceived to classify...

  15. Music Genre Classification Systems - A Computational Approach

    DEFF Research Database (Denmark)

    Ahrendt, Peter

    2006-01-01

    Automatic music genre classification is the classification of a piece of music into its corresponding genre (such as jazz or rock) by a computer. It is considered to be a cornerstone of the research area Music Information Retrieval (MIR) and closely linked to the other areas in MIR. It is thought...... that MIR will be a key element in the processing, searching and retrieval of digital music in the near future. This dissertation is concerned with music genre classification systems and in particular systems which use the raw audio signal as input to estimate the corresponding genre. This is in...... contrast to systems which use e.g. a symbolic representation or textual information about the music. The approach to music genre classification systems has here been system-oriented. In other words, all the different aspects of the systems have been considered and it is emphasized that the systems should...

  16. Bagging Support Vector Machines for Leukemia Classification

    Directory of Open Access Journals (Sweden)

    Gokmen Zararsiz

    2012-11-01

    Full Text Available Leukemia is one of the most common cancer type, and its diagnosis and classification is becoming increasingly complex and important. Here, we used a gene expression dataset and adapted bagging support vector machines (bSVM for leukemia classification. bSVM trains each SVM seperately using bootstrap technique, then aggregates the performances of each SVM by majority voting. bSVM showed accuracy between 87.5% - 92.5%, area under ROC curve between 98.0% - 99.2%, F-measure between 90.5% - 92.7% and outperformed single SVM and other classification methods. We also compared our results with other study results which used the same dataset for leukemia classification. Experimental results revealed that bSVM showed the best performance and can be used as a biomarker for the diagnose of leukemia disease.

  17. Multivariate Approaches to Classification in Extragalactic Astronomy

    CERN Document Server

    Fraix-Burnet, Didier; Chattopadhyay, Asis Kumar

    2015-01-01

    Clustering objects into synthetic groups is a natural activity of any science. Astrophysics is not an exception and is now facing a deluge of data. For galaxies, the one-century old Hubble classification and the Hubble tuning fork are still largely in use, together with numerous mono-or bivariate classifications most often made by eye. However, a classification must be driven by the data, and sophisticated multivariate statistical tools are used more and more often. In this paper we review these different approaches in order to situate them in the general context of unsupervised and supervised learning. We insist on the astrophysical outcomes of these studies to show that multivariate analyses provide an obvious path toward a renewal of our classification of galaxies and are invaluable tools to investigate the physics and evolution of galaxies.

  18. Enterprise Potential: Essence, Classification and Types

    Directory of Open Access Journals (Sweden)

    Turylo Anatolii M.

    2014-02-01

    Full Text Available The article considers existing approaches to classification of the enterprise potential as an economic notion. It offers own vision of classification of enterprise potential, which meets modern tendencies of enterprise development. Classification ensures a possibility of a wider description and assessment of enterprise potential and also allows identification of its most significant characteristics. Classification of the enterprise potential is developed by different criteria: by functions, by resource support, by ability to adapt, by the level of detection, by the spectrum of taking into account possibilities, by the period of coverage of possibilities and by the level of use. Analysis of components of the enterprise potential allows obtaining a complete and trustworthy assessment of the state of an enterprise. Adaptation potential of an enterprise is based on principles systemacy and dynamism, it characterises possibilities of adjustment of an enterprise to external and internal economic conditions.

  19. Beneficiation of industrial minerals by air classification

    OpenAIRE

    Mitchell, Clive John; Inglethorpe, Simon; Morgan, David

    1992-01-01

    Workshop handout accompanying poster which summarises the use of air classification for the beneficiation (mineral processing) of industrial minerals. Illustrated with examples of processing trials on graphite, feldspar and diatomite.

  20. Classification with global, local and shared features

    OpenAIRE

    Bilen, Hakan; Namboodiri, Vinay; Van Gool, Luc

    2012-01-01

    Bilen H., Namboodiri V.P., Van Gool L., ''Classification with global, local and shared features'', Lecture notes in computer science, vol. 7476, pp. 134-143, 2012 (DAGM-OAGM 2012, August 28-31, 2012, Graz, Austria).

  1. Classification and Measurement of Multipartite Quantum Entanglements

    OpenAIRE

    Sheikholeslam, Seyed Arash; Gulliver, Thomas Aaron

    2012-01-01

    This paper presents a new measure of entanglement which can be employed for multipartite entangled systems. The classification of multipartite entangled systems based on this measure is considered. Two approaches to applying this measure to mixed quantum states are discussed.

  2. The International Classification of Headache Disorders

    DEFF Research Database (Denmark)

    Olesen, J.

    2008-01-01

    A set of related medical disorders that lack a proper classification system and diagnostic criteria is like a society without laws. The result is incoherence at best, chaos at worst. For this reason, the International Classification of Headache Disorders (ICHD) is arguably the single most important...... universally accepted, and criticism of the classification has been minor relative to that directed at other disease classification systems. Over the 20 years following publication of the first edition of the ICHD, headache research has rapidly accelerated despite sparse allocation of resources to that effort...... breakthrough in headache medicine over the last 50 years. The ICHD identifies and categorizes more than a hundred different kinds of headache in a logical, hierarchal system. Even more important, it has provided explicit diagnostic criteria for all of the headache disorders listed. The ICHD quickly became...

  3. Specific Property of Ultrafine Particle Classification

    Institute of Scientific and Technical Information of China (English)

    LI Guo-hua; HUANG Zhi-chu; ZHANG You-lin

    2003-01-01

    In the process of ultrafine particle classification,the separation curve,which reflects the characteristics of separating process,is frequently influenced by the characteristics of separation flow field and operating parameters,etc.This paper introduces the concept of system deviation and deduces the calculating method of the separation curves.Meanwhile,it analyses the influences of classification flow field's specific properties and some operating parameters on the separation curves.The results show that,in the process of ultrafine particle classification,the local vortex in the separation field improves the separation efficiency to a certain degree,but the accuracy will decrease;the coacervation action of particles will seriously influence the classification accuracy.

  4. Classification using Hierarchical Naive Bayes models

    DEFF Research Database (Denmark)

    Langseth, Helge; Dyhre Nielsen, Thomas

    2006-01-01

    Classification problems have a long history in the machine learning literature. One of the simplest, and yet most consistently well-performing set of classifiers is the Naïve Bayes models. However, an inherent problem with these classifiers is the assumption that all attributes used to describe an...... instance are conditionally independent given the class of that instance. When this assumption is violated (which is often the case in practice) it can reduce classification accuracy due to “information double-counting” and interaction omission. In this paper we focus on a relatively new set of models...... context of classification. Experimental results show that the learned models can significantly improve classification accuracy as compared to other frameworks....

  5. Classification of ASKAP Vast Radio Light Curves

    Science.gov (United States)

    Rebbapragada, Umaa; Lo, Kitty; Wagstaff, Kiri L.; Reed, Colorado; Murphy, Tara; Thompson, David R.

    2012-01-01

    The VAST survey is a wide-field survey that observes with unprecedented instrument sensitivity (0.5 mJy or lower) and repeat cadence (a goal of 5 seconds) that will enable novel scientific discoveries related to known and unknown classes of radio transients and variables. Given the unprecedented observing characteristics of VAST, it is important to estimate source classification performance, and determine best practices prior to the launch of ASKAP's BETA in 2012. The goal of this study is to identify light curve characterization and classification algorithms that are best suited for archival VAST light curve classification. We perform our experiments on light curve simulations of eight source types and achieve best case performance of approximately 90% accuracy. We note that classification performance is most influenced by light curve characterization rather than classifier algorithm.

  6. The evolving classification of renal cell neoplasia.

    Science.gov (United States)

    Delahunt, Brett; Srigley, John R

    2015-03-01

    The classification of renal cell neoplasia is morphologically based; however, this has evolved over the last 35 years with the incorporation of genetic characteristics into the diagnostic features of some tumors. The 2013 Vancouver classification recognized 17 morphotypes of renal parenchymal malignancy and two benign tumors. This classification included the newly established entities tubulocystic renal cell carcinoma (RCC)), acquired cystic disease-associated RCC, clear cell (tubulo) papillary RCC, microphthalmia transcription factor family translocation RCC and hereditary leiomyomatosis RCC syndrome-associated RCC. In addition to these newly described forms of RCC there are a number of novel tumors that are currently recognized as emerging entities. These are likely to be incorporated into subsequent classifications and include thyroid-like follicular RCC, succinate dehydrogenase B mutation-associated RCC, ALK translocation RCC, tuberous sclerosis complex-associated RCC, and RCC with (angio) leiomyomatous stroma. PMID:25753529

  7. Evaluation for Uncertain Image Classification and Segmentation

    CERN Document Server

    Martin, Arnaud; Arnold-Bos, Andreas

    2008-01-01

    Each year, numerous segmentation and classification algorithms are invented or reused to solve problems where machine vision is needed. Generally, the efficiency of these algorithms is compared against the results given by one or many human experts. However, in many situations, the location of the real boundaries of the objects as well as their classes are not known with certainty by the human experts. Furthermore, only one aspect of the segmentation and classification problem is generally evaluated. In this paper we present a new evaluation method for classification and segmentation of image, where we take into account both the classification and segmentation results as well as the level of certainty given by the experts. As a concrete example of our method, we evaluate an automatic seabed characterization algorithm based on sonar images.

  8. Biological sequence classification with multivariate string kernels.

    Science.gov (United States)

    Kuksa, Pavel P

    2013-01-01

    String kernel-based machine learning methods have yielded great success in practical tasks of structured/sequential data analysis. They often exhibit state-of-the-art performance on many practical tasks of sequence analysis such as biological sequence classification, remote homology detection, or protein superfamily and fold prediction. However, typical string kernel methods rely on the analysis of discrete 1D string data (e.g., DNA or amino acid sequences). In this paper, we address the multiclass biological sequence classification problems using multivariate representations in the form of sequences of features vectors (as in biological sequence profiles, or sequences of individual amino acid physicochemical descriptors) and a class of multivariate string kernels that exploit these representations. On three protein sequence classification tasks, the proposed multivariate representations and kernels show significant 15-20 percent improvements compared to existing state-of-the-art sequence classification methods. PMID:24384708

  9. A non-linear learning & classification algorithm that achieves full training accuracy with stellar classification accuracy

    OpenAIRE

    Khogali, Rashid

    2014-01-01

    A fast Non-linear and non-iterative learning and classification algorithm is synthesized and validated. This algorithm named the "Reverse Ripple Effect(R.R.E)", achieves 100% learning accuracy but is computationally expensive upon classification. The R.R.E is a (deterministic) algorithm that super imposes Gaussian weighted functions on training points. In this work, the R.R.E algorithm is compared against known learning and classification techniques/algorithms such as: the Perceptron Criterio...

  10. Dense Iterative Contextual Pixel Classification using Kriging

    DEFF Research Database (Denmark)

    Ganz, Melanie; Loog, Marco; Brandt, Sami;

    2009-01-01

    In medical applications, segmentation has become an ever more important task. One of the competitive schemes to perform such segmentation is by means of pixel classification. Simple pixel-based classification schemes can be improved by incorporating contextual label information. Various methods h...... relatively long range interactions may play a role. We propose a new method based on Kriging that makes it possible to include such long range interactions, while keeping the computations manageable when dealing with large medical images....

  11. Learning Interpretable SVMs for Biological Sequence Classification

    OpenAIRE

    Sonnenburg Sören; Rätsch Gunnar; Schäfer Christin

    2006-01-01

    Abstract Background Support Vector Machines (SVMs) – using a variety of string kernels – have been successfully applied to biological sequence classification problems. While SVMs achieve high classification accuracy they lack interpretability. In many applications, it does not suffice that an algorithm just detects a biological signal in the sequence, but it should also provide means to interpret its solution in order to gain biological insight. Results We propose novel and efficient algorith...

  12. Consensus Decision for Protein Structure Classification

    OpenAIRE

    Khaddouja Boujenfa; Mohamed Limam

    2012-01-01

    The fundamental aim of protein classification is to recognize the family of a given protein and determine its biological function. In the literature, the most common approaches are based on sequence or structure similarity comparisons. Other methods use evolutionary distances between proteins. In order to increase classification performance, this work proposes a novel method, namely Consensus, which combines the decisions of several sequence and structure comparison tools to classify a given ...

  13. Tumor classification: molecular analysis meets Aristotle

    OpenAIRE

    Berman Jules J

    2004-01-01

    Abstract Background Traditionally, tumors have been classified by their morphologic appearances. Unfortunately, tumors with similar histologic features often follow different clinical courses or respond differently to chemotherapy. Limitations in the clinical utility of morphology-based tumor classifications have prompted a search for a new tumor classification based on molecular analysis. Gene expression array data and proteomic data from tumor samples will provide complex data that is unobt...

  14. Multiview matrix completion for multilabel image classification.

    Science.gov (United States)

    Yong Luo; Tongliang Liu; Dacheng Tao; Chao Xu

    2015-08-01

    There is growing interest in multilabel image classification due to its critical role in web-based image analytics-based applications, such as large-scale image retrieval and browsing. Matrix completion (MC) has recently been introduced as a method for transductive (semisupervised) multilabel classification, and has several distinct advantages, including robustness to missing data and background noise in both feature and label space. However, it is limited by only considering data represented by a single-view feature, which cannot precisely characterize images containing several semantic concepts. To utilize multiple features taken from different views, we have to concatenate the different features as a long vector. However, this concatenation is prone to over-fitting and often leads to very high time complexity in MC-based image classification. Therefore, we propose to weightedly combine the MC outputs of different views, and present the multiview MC (MVMC) framework for transductive multilabel image classification. To learn the view combination weights effectively, we apply a cross-validation strategy on the labeled set. In particular, MVMC splits the labeled set into two parts, and predicts the labels of one part using the known labels of the other part. The predicted labels are then used to learn the view combination coefficients. In the learning process, we adopt the average precision (AP) loss, which is particular suitable for multilabel image classification, since the ranking-based criteria are critical for evaluating a multilabel classification system. A least squares loss formulation is also presented for the sake of efficiency, and the robustness of the algorithm based on the AP loss compared with the other losses is investigated. Experimental evaluation on two real-world data sets (PASCAL VOC' 07 and MIR Flickr) demonstrate the effectiveness of MVMC for transductive (semisupervised) multilabel image classification, and show that MVMC can exploit

  15. Multi-engine packet classification hardware accelerator

    OpenAIRE

    Kennedy, Alan; Liu, Zhen; Wang, Xiaojun; Liu, Bin

    2009-01-01

    As line rates increase, the task of designing high performance architectures with reduced power consumption for the processing of router traffic remains important. In this paper, we present a multi-engine packet classification hardware accelerator, which gives increased performance and reduced power consumption. It follows the basic idea of decision-tree based packet classification algorithms, such as HiCuts and HyperCuts, in which the hyperspace represented by the ruleset is recursively divi...

  16. Interactive multiclass segmentation using superpixel classification

    OpenAIRE

    Mathieu, Bérengère; Crouzil, Alain; Puel, Jean-Baptiste

    2015-01-01

    This paper adresses the problem of interactive multiclass segmentation. We propose a fast and efficient new interactive segmentation method called Superpixel Classification-based Interactive Segmentation (SCIS). From a few strokes drawn by a human user over an image, this method extracts relevant semantic objects. To get a fast calculation and an accurate segmentation, SCIS uses superpixel over-segmentation and support vector machine classification. In this paper, we demonstrate that SCIS sig...

  17. Reproducibility of histologic classification of gastric cancer.

    OpenAIRE

    Palli, D; Bianchi, S.; Cipriani, F; Duca, P; Amorosi, A; C. Avellini; A. Russo; Saragoni, A; P. Todde; Valdes, E.

    1991-01-01

    A panel review of histologic specimens was carried out as part of a multi-centre case-control study of gastric cancer (GC) and diet. Comparisons of diagnoses of 100 GCs by six pathologists revealed agreement in histologic classification for about 70-80% of the cancers. Concordance was somewhat higher when using the Lauren rather than the Ming or World Health Organization classification systems. Histologic types from reading biopsy tissue agreed with those derived from surgical specimens for 6...

  18. An Authentication Technique Based on Classification

    Institute of Scientific and Technical Information of China (English)

    李钢; 杨杰

    2004-01-01

    We present a novel watermarking approach based on classification for authentication, in which a watermark is embedded into the host image. When the marked image is modified, the extracted watermark is also different to the original watermark, and different kinds of modification lead to different extracted watermarks. In this paper, different kinds of modification are considered as classes, and we used classification algorithm to recognize the modifications with high probability. Simulation results show that the proposed method is potential and effective.

  19. Monstrous moonshine and the classification of CFT

    OpenAIRE

    Gannon, Terry

    1999-01-01

    In these notes, based on lectures given in Istanbul, we give an introduction both to Monstrous Moonshine and to the classification of rational conformal field theories, using this as an excuse to explore several related structures and go on a little tour of modern math. We will discuss Lie algebras, modular functions, the finite simple group classification, vertex operator algebras, Fermat's Last Theorem, category theory, (generalised) Kac-Moody algebras, denominator identities, the A-D-E met...

  20. Extreme Entropy Machines: Robust information theoretic classification

    OpenAIRE

    Czarnecki, Wojciech Marian; Tabor, Jacek

    2015-01-01

    Most of the existing classification methods are aimed at minimization of empirical risk (through some simple point-based error measured with loss function) with added regularization. We propose to approach this problem in a more information theoretic way by investigating applicability of entropy measures as a classification model objective function. We focus on quadratic Renyi's entropy and connected Cauchy-Schwarz Divergence which leads to the construction of Extreme Entropy Machines (EEM). ...

  1. Fingerprint Classification based on Orientaion Estimation

    Directory of Open Access Journals (Sweden)

    Manish Mathuria

    2013-06-01

    Full Text Available The geometric characteristics of an object make it distinguishable. The objects present in the Environment known by their features and properties. The fingerprint image as object may classify into sub classes based on minutiae structure. The minutiae structure may categorize as ridge curves generated by the orientation estimation. The extracted curves are invariant to location, rotation and scaling. This classification approach helps to manage fingerprints along their classes. This research provides a better collaboration of data mining based on classification.

  2. Design evaluaion: pneumatic transport and classification

    International Nuclear Information System (INIS)

    This report describes the evaluation of selected design features of the cold engineering scale pneumatic transport and classification subsystems used in the development of the head-end equipment for HTGR fuel reprocessing. The report identifies areas that require further design effort and evaluation of alternatives prior to the design of the HTGR reference recycle facility (HRRF). Seven areas in the transport subsystem and three in the classification subsystem were selected for evaluation. Seventeen specific recommendations are presented for further design effort

  3. ONLINE REGULARIZED GENERALIZED GRADIENT CLASSIFICATION ALGORITHMS

    Institute of Scientific and Technical Information of China (English)

    Leilei Zhang; Baohui Sheng; Jianli Wang

    2010-01-01

    This paper considers online classification learning algorithms for regularized classification schemes with generalized gradient.A novel capacity independent approach is presented.It verifies the strong convergence of sizes and yields satisfactory convergence rates for polynomially decaying step sizes.Compared with the gradient schemes,this al-gorithm needs only less additional assumptions on the loss function and derives a stronger result with respect to the choice of step sizes and the regularization parameters.

  4. Recent Approaches to Arabic Dialogue Acts Classifications

    OpenAIRE

    Elmadany, Abdelrahim A; Abdou, Sherif M.; Mervat Gheith

    2015-01-01

    Building Arabic dialogue systems (Spoken or Written) has gained an increasing interest in the last few. For this reasons, there are more interest for Arabic dialogue acts classification task because it a key player in Arabic language understanding to buil ding this systems. This paper describes the results of the recent approaches of Arabic dialogue acts classifications and covers Arabic dialogue acts corpora, annotation schema, utterance segmentation, and classi...

  5. Analysis of thematic map classification error matrices.

    Science.gov (United States)

    Rosenfield, G.H.

    1986-01-01

    The classification error matrix expresses the counts of agreement and disagreement between the classified categories and their verification. Thematic mapping experiments compare variables such as multiple photointerpretation or scales of mapping, and produce one or more classification error matrices. This paper presents a tutorial to implement a typical problem of a remotely sensed data experiment for solution by the linear model method.-from Author

  6. Random Forests for Classification in Ecology

    OpenAIRE

    Cutler, D. R.; EDWARDS, T C; Beard, Karen H.; Cutler, A.; Hess, K. T.; Gibson, J C; Lawler, J. J.

    2007-01-01

    Classification procedures are some of the most widely used statistical methods in ecology. Random forests (RF) is a new and powerful statistical classifier that is well established in other disciplines but is relatively unknown in ecology. Advantages of RF compared to other statistical classifiers include (1) very high classification accuracy; (2) a novel method of determining variable importance; (3) ability to model complex interactions among predictor variables; (4) flexibility to perform ...

  7. Intrusion Detection Using Cost-Sensitive Classification

    OpenAIRE

    Mitrokotsa, Aikaterini; Dimitrakakis, Christos; Douligeris, Christos

    2008-01-01

    Intrusion Detection is an invaluable part of computer networks defense. An important consideration is the fact that raising false alarms carries a significantly lower cost than not detecting at- tacks. For this reason, we examine how cost-sensitive classification methods can be used in Intrusion Detection systems. The performance of the approach is evaluated under different experimental conditions, cost matrices and different classification models, in terms of expected cost, as well as detect...

  8. 'Araphid' diatom classification and the 'absolute standard'

    OpenAIRE

    Williams, David M.

    2009-01-01

    'Araphid' diatom classification is discussed from the point of view of an 'absolute standard' for taxonomic rank. The 'absolute standard' is the phylogenetic tree, its nodes, the included monophyletic groups and sub-groups. To illustrate this point a few species from the genus Licmophora are re-analysed and the resulting phylogenetic tree is discussed in terms of a possible classification, the groups and sub-groups and their ranks.

  9. Enhanced Search Method for Ontology Classification

    OpenAIRE

    Je Min Kim; Soon Hyen Kwon; Young Tack Park

    2012-01-01

    The web ontology language (OWL) has become a W3C recommendation to publish and share ontologies on the semantic web. In order to infer implicit information (classification, satisfiability and realization) of OWL ontology, a number of OWL reasoners have been introduced. Ontology classification is to compute a partial ordering or hierarchy of named concepts in the ontology using the subsumption testing. Most of the reasoners use both top-down and bottom-up searches using subsumption testing for...

  10. Classification of neocortical interneurons using affinity propagation

    OpenAIRE

    Santana, Roberto; McGarry, Laura M.; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

    2013-01-01

    In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. In fact, neuronal classification is a difficult problem because it is unclear how to designate a neuronal cell class and what are the best characteristics to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological, or molecular characteristics, have provided quantitative and unbiased identification of distinct neu...

  11. Classification of neocortical interneurons using affinity propagation

    OpenAIRE

    Roberto eSantana; Laura eMcGarry; Concha eBielza; Pedro eLarrañaga; Rafael eYuste

    2013-01-01

    In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. Neuronal classification has been a difficult problem because it is unclear what a neuronal cell class actually is and what are the best characteristics are to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological or molecular characteristics, when applied to selected datasets, have provided quantitative and unbi...

  12. Histological classification of mesial temporal sclerosis

    OpenAIRE

    D. V. Dmitrenko; M. A. Stroganova; N. A. Shnaider; G. P. Martynova; K. A. Gazenkampf; A. V. Dyuzhakova; Yu. S. Panina

    2016-01-01

    Mesial temporal sclerosis (MTS) is the most common histopathology occurring in patients with drug-resistant temporal lobe epilepsy. Over the past decades, there have been various attempts to classify the variants of hippocampal neuronal cell loss in relation to postoperative outcome. However, no consensus on the common international definition and classification of MTS has been reached. The article describes the modern histological classification based on a semiquantitative hippocampal cell l...

  13. Towards functional classification of neuronal types

    OpenAIRE

    Sharpee, Tatyana O.

    2014-01-01

    How many types of neurons are there in the brain? This basic neuroscience question remains unsettled despite many decades of research. Classification schemes have been proposed based on anatomical, electrophysiological or molecular properties. However, different schemes do not always agree with each other. This raises the question of whether one can classify neurons based on their function directly. For example, among sensory neurons, can a classification scheme be devised that is based on th...

  14. Biogeographic classification of the Caspian Sea

    OpenAIRE

    F. Fendereski; M. Vogt; Payne, M. R.; Z. Lachkar; Gruber, N.; Salmanmahiny, A.; S. A. Hosseini

    2014-01-01

    Like other inland seas, the Caspian Sea (CS) has been influenced by climate change and anthropogenic disturbance during recent decades, yet the scientific understanding of this water body remains poor. In this study, an eco-geographical classification of the CS based on physical information derived from space and in-situ data is developed and tested against a set of biological observations. We used a two-step classification procedure, consisting of (i) a data reduction with self-organizing ma...

  15. The DSM-5: Classification and criteria changes

    OpenAIRE

    Regier, Darrel A; Kuhl, Emily A; Kupfer, David J.

    2013-01-01

    The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) marks the first significant revision of the publication since the DSM-IV in 1994. Changes to the DSM were largely informed by advancements in neuroscience, clinical and public health need, and identified problems with the classification system and criteria put forth in the DSM-IV. Much of the decision-making was also driven by a desire to ensure better alignment with the International Classification of Diseases a...

  16. Fuzzy classification rules based on similarity

    Czech Academy of Sciences Publication Activity Database

    Holeňa, Martin; Štefka, D.

    Seňa : PONT s.r.o., 2012 - (Horváth, T.), s. 25-31 ISBN 978-80-971144-0-4. [ITAT 2012. Conference on Theory and Practice of Information Technologies. Ždiar (SK), 17.09.2012-21.09.2012] R&D Projects: GA ČR GA201/08/0802 Institutional support: RVO:67985807 Keywords : classification rules * fuzzy classification * fuzzy integral * fuzzy measure * similarity Subject RIV: IN - Informatics, Computer Science

  17. Web Page Classification Using SVM and FURIA

    OpenAIRE

    P. Madhubala; K. Murugesan

    2015-01-01

    Text Classification classifies a document, under a predefined category. Mostly, an automatic text classification is an important application taken as a research topic, since the inception of digital documents. In this study, Hypernyms, superordinate words are identified in web and clubbed with entailment rule acquisition. Available tree of hyponym words in the document has been created and used with dependency tree. Features extraction is performed with weighted Term Frequency-Inverse Documen...

  18. Automatic document classification of biological literature

    OpenAIRE

    Sternberg Paul W; Müller Hans-Michael; Chen David

    2006-01-01

    Abstract Background Document classification is a wide-spread problem with many applications, from organizing search engine snippets to spam filtering. We previously described Textpresso, a text-mining system for biological literature, which marks up full text according to a shallow ontology that includes terms of biological interest. This project investigates document classification in the context of biological literature, making use of the Textpresso markup of a corpus of Caenorhabditis eleg...

  19. Clustering Analysis within Text Classification Techniques

    OpenAIRE

    Madalina ZURINI; Catalin SBORA

    2011-01-01

    The paper represents a personal approach upon the main applications of classification which are presented in the area of knowledge based society by means of methods and techniques widely spread in the literature. Text classification is underlined in chapter two where the main techniques used are described, along with an integrated taxonomy. The transition is made through the concept of spatial representation. Having the elementary elements of geometry and the artificial intelligence analysis,...

  20. Deep neural networks for spam classification

    OpenAIRE

    Kasmani, Mohamed Khizer

    2013-01-01

    This project elucidates the development of a spam filtering method using deep neural networks. A classification model employing algorithms such as Error Back Propagation (EBP) and Restricted Boltzmann Machines (RBM) is used to identify spam and non-spam emails. Moreover, a spam classification system employing deep neural network algorithms is developed, which has been tested on Enron email dataset in order to help users manage large volumes of email and, furthermore, their email folders. The ...

  1. ACCUWIND - Methods for classification of cup anemometers

    OpenAIRE

    Dahlberg, J.-Å.; Friis Pedersen, Troels; Busche, P.

    2006-01-01

    Errors associated with the measurement of wind speed are the major sources of uncertainties in power performance testing of wind turbines. Field comparisons of well-calibrated anemometers show significant and not acceptable difference. The EuropeanCLASSCUP project posed the objectives to quantify the errors associated with the use of cup anemometers, and to develop a classification system for quantification of systematic errors of cup anemometers. This classification system has now been imple...

  2. On music genre classification via compressive sampling

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    Recent work \\cite{Chang2010} combines low-level acoustic features and random projection (referred to as ``compressed sensing'' in \\cite{Chang2010}) to create a music genre classification system showing an accuracy among the highest reported for a benchmark dataset. This not only contradicts...... previous findings that suggest low-level features are inadequate for addressing high-level musical problems, but also that a random projection of features can improve classification. We reproduce this work and resolve these contradictions....

  3. Gender Classification by Fuzzy Inference System

    OpenAIRE

    Payman Moallem; B. Somayeh Mousavi

    2013-01-01

    Gender classification from face images has many applications and is thus an important research topic. This paper presents an approach to gender classification based on shape and texture information gathered to design a fuzzy decision making system. Beside face shape features, Zernik moments are applied as system inputs to improve the system output which is considered as the probability of being male face image. After parameters tuning of the proposed fuzzy decision making system, 85.05% class...

  4. Incrementally Maintaining Classification using an RDBMS

    OpenAIRE

    Koc, Mehmet Levent; Ré, Christopher

    2011-01-01

    The proliferation of imprecise data has motivated both researchers and the database industry to push statistical techniques into relational database management systems (RDBMSs). We study algorithms to maintain model-based views for a popular statistical technique, classification, inside an RDBMS in the presence of updates to the training examples. We make three technical contributions: (1) An algorithm that incrementally maintains classification inside an RDBMS. (2) An analysis of the above a...

  5. COMPARISON OF SOME LIMITS FOR STABILITY CLASSIFICATION

    Institute of Scientific and Technical Information of China (English)

    BI Xue-yan; LIU Feng; WU Dui

    2005-01-01

    Stability parameters (Monin-Obukhov length L, gradient Richardson number Ri and bulk Rischardson number Ri), which are applicable in urban environment, were discussed for ways of calculating classification standards. Gradient observations from a 325-m meteorological tower in Beijing are used to categorize Rib based on three different standards of stability proposed by D. Golder, Irwin and Houghton. The results show that it is relatively reasonable for the region of Beijing to apply the classification standard by Irwin.

  6. SUPERVISED TERM WEIGHTING METHODS FOR URL CLASSIFICATION

    OpenAIRE

    R. Rajalakshmi

    2014-01-01

    Many term weighting methods are suggested in the literature for Information Retrieval and Text Categorization. Term weighting method, a part of feature selection process is not yet explored for URL classification problem. We classify a web page using its URL alone without fetching its content and hence URL based classification is faster than other methods. In this study, we investigate the use of term weighting methods for selecting relevant URL features and their impact on the performance of...

  7. Deep Bottleneck Feature for Image Classification

    OpenAIRE

    Song, Yan; McLoughlin, Ian Vince; Dai, Lirong

    2015-01-01

    Effective image representation plays an important role for image classification and retrieval. Bag-of-Features (BoF) is well known as an effective and robust visual representation. However, on large datasets, convolutional neural networks (CNN) tend to perform much better, aided by the availability of large amounts of training data. In this paper, we propose a bag of Deep Bottleneck Features (DBF) for image classification, effectively combining the strengths of a CNN within a BoF framework. T...

  8. Wavelet features in motion data classification

    Science.gov (United States)

    Szczesna, Agnieszka; Świtoński, Adam; Słupik, Janusz; Josiński, Henryk; Wojciechowski, Konrad

    2016-06-01

    The paper deals with the problem of motion data classification based on result of multiresolution analysis implemented in form of quaternion lifting scheme. Scheme processes directly on time series of rotations coded in form of unit quaternion signal. In the work new features derived from wavelet energy and entropy are proposed. To validate the approach gait database containing data of 30 different humans is used. The obtained results are satisfactory. The classification has over than 91% accuracy.

  9. Software Design Level Vulnerability Classification Model

    OpenAIRE

    Shabana Rehman; Khurram Mustafa

    2012-01-01

    Classification of software security vulnerability no doubt facilitates the understanding of security-related information and accelerates vulnerability analysis. The lack of proper classification not only hinders its understanding but also renders the strategy of developing mitigation mechanism for clustered vulnerabilities. Now software developers and researchers are agreed on the fact that requirement and design phase of the software are the phases where security incorporation yields maximum...

  10. A statistical approach to root system classification.

    Directory of Open Access Journals (Sweden)

    Gernot eBodner

    2013-08-01

    Full Text Available Plant root systems have a key role in ecology and agronomy. In spite of fast increase in root studies, still there is no classification that allows distinguishing among distinctive characteristics within the diversity of rooting strategies. Our hypothesis is that a multivariate approach for plant functional type identification in ecology can be applied to the classification of root systems. We demonstrate that combining principal component and cluster analysis yields a meaningful classification of rooting types based on morphological traits. The classification method presented is based on a data-defined statistical procedure without a priori decision on the classifiers. Biplot inspection is used to determine key traits and to ensure stability in cluster based grouping. The classification method is exemplified with simulated root architectures and morphological field data. Simulated root architectures showed that morphological attributes with spatial distribution parameters capture most distinctive features within root system diversity. While developmental type (tap vs. shoot-borne systems is a strong, but coarse classifier, topological traits provide the most detailed differentiation among distinctive groups. Adequacy of commonly available morphologic traits for classification is supported by field data. Three rooting types emerged from measured data, distinguished by diameter/weight, density and spatial distribution respectively. Similarity of root systems within distinctive groups was the joint result of phylogenetic relation and environmental as well as human selection pressure. We concluded that the data-define classification is appropriate for integration of knowledge obtained with different root measurement methods and at various scales. Currently root morphology is the most promising basis for classification due to widely used common measurement protocols. To capture details of root diversity efforts in architectural measurement

  11. Support Vector Machines for Pattern Classification

    CERN Document Server

    Abe, Shigeo

    2010-01-01

    A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empir

  12. Improvement of Classification of Enterprise Circulating Funds

    Directory of Open Access Journals (Sweden)

    Rohanova Hanna O.

    2014-02-01

    Full Text Available The goal of the article lies in revelation of possibilities of increase of efficiency of managing enterprise circulating funds by means of improvement of their classification features. Having analysed approaches of many economists to classification of enterprise circulating funds, systemised and supplementing them, the article offers grouping classification features of enterprise circulating funds. In the result of the study the article offers an expanded classification of circulating funds, which clearly shows the role of circulating funds in managing enterprise finance and economy in general. The article supplements and groups classification features of enterprise circulating funds by: the organisation level, functioning character, sources of formation and their cost, and level of management efficiency. The article shows that the provided grouping of classification features of circulating funds allows exerting all-sided and purposeful influence upon indicators of efficiency of circulating funds functioning and facilitates their rational management in general. The prospect of further studies in this direction is identification of the level of attraction of loan resources by production enterprises for financing circulating funds.

  13. Normalization Benefits Microarray-Based Classification

    Directory of Open Access Journals (Sweden)

    Chen Yidong

    2006-01-01

    Full Text Available When using cDNA microarrays, normalization to correct labeling bias is a common preliminary step before further data analysis is applied, its objective being to reduce the variation between arrays. To date, assessment of the effectiveness of normalization has mainly been confined to the ability to detect differentially expressed genes. Since a major use of microarrays is the expression-based phenotype classification, it is important to evaluate microarray normalization procedures relative to classification. Using a model-based approach, we model the systemic-error process to generate synthetic gene-expression values with known ground truth. These synthetic expression values are subjected to typical normalization methods and passed through a set of classification rules, the objective being to carry out a systematic study of the effect of normalization on classification. Three normalization methods are considered: offset, linear regression, and Lowess regression. Seven classification rules are considered: 3-nearest neighbor, linear support vector machine, linear discriminant analysis, regular histogram, Gaussian kernel, perceptron, and multiple perceptron with majority voting. The results of the first three are presented in the paper, with the full results being given on a complementary website. The conclusion from the different experiment models considered in the study is that normalization can have a significant benefit for classification under difficult experimental conditions, with linear and Lowess regression slightly outperforming the offset method.

  14. Normalization Benefits Microarray-Based Classification

    Directory of Open Access Journals (Sweden)

    Edward R. Dougherty

    2006-08-01

    Full Text Available When using cDNA microarrays, normalization to correct labeling bias is a common preliminary step before further data analysis is applied, its objective being to reduce the variation between arrays. To date, assessment of the effectiveness of normalization has mainly been confined to the ability to detect differentially expressed genes. Since a major use of microarrays is the expression-based phenotype classification, it is important to evaluate microarray normalization procedures relative to classification. Using a model-based approach, we model the systemic-error process to generate synthetic gene-expression values with known ground truth. These synthetic expression values are subjected to typical normalization methods and passed through a set of classification rules, the objective being to carry out a systematic study of the effect of normalization on classification. Three normalization methods are considered: offset, linear regression, and Lowess regression. Seven classification rules are considered: 3-nearest neighbor, linear support vector machine, linear discriminant analysis, regular histogram, Gaussian kernel, perceptron, and multiple perceptron with majority voting. The results of the first three are presented in the paper, with the full results being given on a complementary website. The conclusion from the different experiment models considered in the study is that normalization can have a significant benefit for classification under difficult experimental conditions, with linear and Lowess regression slightly outperforming the offset method.

  15. Hydropedological insights when considering catchment classification

    Directory of Open Access Journals (Sweden)

    J. Bouma

    2011-06-01

    Full Text Available Soil classification systems are analysed to explore the potential of developing classification systems for catchments. Soil classifications are useful to create systematic order in the overwhelming quantity of different soils in the world and to extrapolate data available for a given soil type to soils elsewhere with identical classifications. This principle also applies to catchments. However, to be useful, soil classifications have to be based on permanent characteristics as formed by the soil forming factors over often very long periods of time. When defining permanent catchment characteristics, discharge data would therefore appear to be less suitable. But permanent soil characteristics do not necessarily match with characteristics and parameters needed for functional soil characterization focusing, for example, on catchment hydrology. Hydropedology has made contributions towards the required functional characterization of soils as is illustrated for three recent hydrological catchment studies. However, much still needs to be learned about the physical behaviour of anisotropic, heterogeneous soils with varying soil structures during the year and about spatial and temporal variability. The suggestion is made therefore to first focus on improving simulation of catchment hydrology, possibly incorporating hydropedological expertise, before embarking on a catchment classification effort which involves major input of time and involves the risk of distraction. In doing so, we suggest to also define other characteristics for catchment performance than the traditionally measured discharge rates. Such characteristics may well be derived from societal issues being studied, as is illustrated for the Green Water Credits program.

  16. Modern approaches to classification of economic risks

    Directory of Open Access Journals (Sweden)

    Larisa Radzykhovskaya

    2014-04-01

    Full Text Available The author substantiated necessity of detailed classification of economic risks, formulated principles, which should be considered in a process ofdevelopment of classifications. The author described characteristics, which may be used for creation of a classification of economic risks. Classificationsdeveloped by modern scientists are proposed. The author offers to reduce characterization of a risk to such positions as uncertainty,danger, losses, and probability. Construction of a detailed classification of risks enable to most thoroughly attack the problem of appearance offactors that contribute a risk and to research risks as a whole. Thus, further researches in this branch continue to be actual and necessary, especiallyfor a practical activity. Basing on a classification, each type of a risk can be thoroughly analyzed, modeled, separated into elements. Theseprocesses enable to decrease uncertainty of a situation, making an appropriate decision. The classifications of risks considered in the article enableto determine a position of each type of risks in their general system and also effectively use particular techniques and methods of minimizationand management of risks.

  17. Statistical physics for materials classification

    Science.gov (United States)

    Lassalle, Hugues Jean

    Genetic algorithms (GA) and clustering techniques are used to study and classify materials. An analysis of the convergence speed of GA is carried out using advanced probability theory and random walk concepts. The determination of the ground-state of multicomponent alloys and Ising models with long-range interactions is accomplished using a genetic algorithm. A new GA operator, the domain-flip, is introduced and its efficiency is compared to that of traditional GA operators, crossover and mutation. The domain-flip operator destroys phase-boundaries by flipping all bits of a given domain at the same time. This operator turns out to be crucial in extracting the system from low local minima. Therefore its presence is rather essential to speed up the GA convergence. A study of GA convergence in its last stages, where all chromosomes present in the population are assumed to consist of two well-ordered domains, is performed using random walk theory and probability theory. Exact expressions for the average time needed for at least one chromosome to find the ground-state are derived. Also, the probability for two chromosomes to undergo a successful crossover, meaning the result is the ground-state, are given. Finally, clustering techniques, which belong to the field of Data Mining, are applied to the classification of materials. An improved version of the widely-used clustering algorithm, K-means, is developed. A comparison of the two clustering techniques on a two-dimensional data set shows that the guide-point approach is more powerful than the K-means algorithm. The guide-point algorithm is used successfully to partition a materials data set. This clustering results in extracting useful information from the data set for which no a priori knowledge was assumed.

  18. 46 CFR 8.220 - Recognition of a classification society.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 1 2010-10-01 2010-10-01 false Recognition of a classification society. 8.220 Section 8... INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.220 Recognition of a classification society. (a) A classification society must be recognized by the Commandant before it may receive...

  19. 46 CFR 90.10-35 - Recognized classification society.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 4 2010-10-01 2010-10-01 false Recognized classification society. 90.10-35 Section 90... classification society. The term recognized classification society means the American Bureau of Shipping or other classification society recognized by the Commandant....

  20. 7 CFR 27.31 - Classification of Cotton.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Classification of Cotton. 27.31 Section 27.31... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.31 Classification of Cotton. For the purposes of subsection 15b (f) of the...

  1. Scientific and General Subject Classifications in the Digital World

    OpenAIRE

    De Robbio, Antonella; Maguolo, Dario; Marini, Alberto

    2001-01-01

    In the present work we discuss opportunities, problems, tools and techniques encountered when interconnecting discipline-specific subject classifications, primarily organized as search devices in bibliographic databases, with general classifications originally devised for book shelving in public libraries. We first state the fundamental distinction between topical (or subject) classifications and object classifications. Then we trace the structural limitations that have constrained subject...

  2. 7 CFR 28.15 - Classification and comparison; requests.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Classification and comparison; requests. 28.15 Section... Standards Act Requests for Classification and Comparison § 28.15 Classification and comparison; requests. All requests for classification and comparison shall be in writing on a form supplied by the...

  3. 7 CFR 30.31 - Classification of leaf tobacco.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Classification of leaf tobacco. 30.31 Section 30.31... REGULATIONS TOBACCO STOCKS AND STANDARDS Classification of Leaf Tobacco Covering Classes, Types and Groups of Grades § 30.31 Classification of leaf tobacco. For the purpose of this classification leaf tobacco...

  4. An Extension of the Behavioral Classification Project Upward to Adults.

    Science.gov (United States)

    Marullo, Sam, Jr.; Dreger, Ralph Mason

    For two decades the Behavioral Classification Project (BCP) has been developing instruments of a behavioral nature for the classification of emotional disorders and the classification of persons with specified patterns of emotional disorders. The BCP has four subprojects: the Pre-school Behavioral Classification Project (PBCP), the Children's…

  5. 24 CFR 3285.202 - Soil classifications and bearing capacity.

    Science.gov (United States)

    2010-04-01

    ... 24 Housing and Urban Development 5 2010-04-01 2010-04-01 false Soil classifications and bearing... Soil classifications and bearing capacity. The soil classification and bearing capacity of the soil must be determined before the foundation is constructed and anchored. The soil classification...

  6. 7 CFR 27.80 - Fees; classification, Micronaire, and supervision.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Fees; classification, Micronaire, and supervision. 27... Classification and Micronaire § 27.80 Fees; classification, Micronaire, and supervision. For services rendered by... classification and Micronaire determination results certified on cotton class certificates.) (e) Supervision,...

  7. A Systematic Approach to Subgroup Classification in Intellectual Disability

    Science.gov (United States)

    Schalock, Robert L.; Luckasson, Ruth

    2015-01-01

    This article describes a systematic approach to subgroup classification based on a classification framework and sequential steps involved in the subgrouping process. The sequential steps are stating the purpose of the classification, identifying the classification elements, using relevant information, and using clearly stated and purposeful…

  8. 42 CFR 412.620 - Patient classification system.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.620 Section 412... Inpatient Rehabilitation Hospitals and Rehabilitation Units § 412.620 Patient classification system. (a) Classification methodology. (1) A patient classification system is used to classify patients in...

  9. 42 CFR 412.513 - Patient classification system.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS... LTC-DRG classification system provides a LTC-DRG, and an appropriate weighting factor, for those...

  10. 14 CFR 1203.407 - Duration of classification.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Duration of classification. 1203.407... PROGRAM Guides for Original Classification § 1203.407 Duration of classification. (a) Information shall be... date or event for declassification shall be set by the original classification authority at the...

  11. 14 CFR 1203.500 - Use of derivative classification.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Use of derivative classification. 1203.500... PROGRAM Derivative Classification § 1203.500 Use of derivative classification. The application of derivative classification markings is a responsibility of those who incorporate, paraphrase, restate,...

  12. 28 CFR 524.76 - Appeals of CIM classification.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Appeals of CIM classification. 524.76..., CLASSIFICATION, AND TRANSFER CLASSIFICATION OF INMATES Central Inmate Monitoring (CIM) System § 524.76 Appeals of CIM classification. An inmate may at any time appeal (through the Administrative Remedy Program)...

  13. Application of Data Mining in Protein Sequence Classification

    Directory of Open Access Journals (Sweden)

    Suprativ Saha

    2012-11-01

    Full Text Available Protein sequence classification involves feature selection for accurate classification. Popular protein sequence classification techniques involve extraction of specific features from the sequences. Researchers apply some well-known classification techniques like neural networks, Genetic algorithm, Fuzzy ARTMAP,Rough Set Classifier etc for accurate classification. This paper presents a review is with three different classification models such as neural network model, fuzzy ARTMAP model and Rough set classifier model.This is followed by a new technique for classifying protein sequences. The proposed model is typicallyimplemented with an own designed tool and tries to reduce the computational overheads encountered by earlier approaches and increase the accuracy of classification.

  14. Hyperspectral Data Classification Using Factor Graphs

    Science.gov (United States)

    Makarau, A.; Müller, R.; Palubinskas, G.; Reinartz, P.

    2012-07-01

    Accurate classification of hyperspectral data is still a competitive task and new classification methods are developed to achieve desired tasks of hyperspectral data use. The objective of this paper is to develop a new method for hyperspectral data classification ensuring the classification model properties like transferability, generalization, probabilistic interpretation, etc. While factor graphs (undirected graphical models) are unfortunately not widely employed in remote sensing tasks, these models possess important properties such as representation of complex systems to model estimation/decision making tasks. In this paper we present a new method for hyperspectral data classification using factor graphs. Factor graph (a bipartite graph consisting of variables and factor vertices) allows factorization of a more complex function leading to definition of variables (employed to store input data), latent variables (allow to bridge abstract class to data), and factors (defining prior probabilities for spectral features and abstract classes; input data mapping to spectral features mixture and further bridging of the mixture to an abstract class). Latent variables play an important role by defining two-level mapping of the input spectral features to a class. Configuration (learning) on training data of the model allows calculating a parameter set for the model to bridge the input data to a class. The classification algorithm is as follows. Spectral bands are separately pre-processed (unsupervised clustering is used) to be defined on a finite domain (alphabet) leading to a representation of the data on multinomial distribution. The represented hyperspectral data is used as input evidence (evidence vector is selected pixelwise) in a configured factor graph and an inference is run resulting in the posterior probability. Variational inference (Mean field) allows to obtain plausible results with a low calculation time. Calculating the posterior probability for each class

  15. A survey on phrase structure learning methods for text classification

    OpenAIRE

    Prasad, Reshma; Sebastian, Mary Priya

    2014-01-01

    Text classification is a task of automatic classification of text into one of the predefined categories. The problem of text classification has been widely studied in different communities like natural language processing, data mining and information retrieval. Text classification is an important constituent in many information management tasks like topic identification, spam filtering, email routing, language identification, genre classification, readability assessment etc. The performance o...

  16. Cause of Death Affects Racial Classification on Death Certificates

    OpenAIRE

    Andrew Noymer; Penner, Andrew M.; Aliya Saperstein

    2011-01-01

    Recent research suggests racial classification is responsive to social stereotypes, but how this affects racial classification in national vital statistics is unknown. This study examines whether cause of death influences racial classification on death certificates. We analyze the racial classifications from a nationally representative sample of death certificates and subsequent interviews with the decedents' next of kin and find notable discrepancies between the two racial classifications by...

  17. Mining Online Store Client Assessment Classification Rules with Genetic Algorithms

    OpenAIRE

    Galinina, A; Paršutins, S

    2011-01-01

    The paper presents the results of the research into algorithms that are not meant to mine classification rules, yet they contain all the necessary functions which allow us to use them for mining classification rules such as Genetic algorithm (GA). The main task of the research is associated with the application of GA to classification rule mining. A classic GA was modified to match the chosen classification task and was compared with other popular classification algorithms – JRip, J48 and Nai...

  18. The Impact of Industry Classification Schemes on Financial Research

    OpenAIRE

    Weiner, Christian

    2005-01-01

    This paper investigates industry classification systems. During the last 50 years there has been a considerable discussion of problems regarding the classification of economic data by industries. From my perspective, the central point of each classification is to determine a balance between aggregation of similar firms and differentiation between industries. This paper examines the structure and content of industrial classification schemes and how they affect financial research. I use classif...

  19. A SYSTEMATIC APPROACH TO THE CLASSIFICATION OF DISEASES

    OpenAIRE

    Murthy, A. R. V.

    1993-01-01

    Ayurvedic texts have adopted multiple approaches to the classification of diseases. Caraka while choosing a binary classification in Vimana sthana declares that the classifications may be numerable and innumerable basing on the criteria chosen for such classification. He gives full liberty to the individual to go in for the newer and newer classification, provided the criteria are different. Taking cue from this statement an attempt has been made at categorizing the diseases mentioned in Ayur...

  20. A Rorschach Test for Visual Classification Strategies

    Science.gov (United States)

    Watson, Andrew B.; Rosenholtz, Ruth; Null, Cynthia H. (Technical Monitor)

    1996-01-01

    Contemporary models of pattern, detection and discrimination often employ template matching, but there have been few direct tests of this proposition. Adopting a method developed by Ahumada, we have analyzed how human observers discriminate between two letters of the alphabet ('c' and 'x'). The stimulus consisted of a one degree tall letter plus a four degree field of static white noise, both displayed for 16 frames at a 67 Hz frame rate. Our font and display dimensions approximated those of Solomon and Pelli. The observer identified the letter presented. A QUEST staircase varied letter contrast to maintain a 75% correct rate. For each trial, we preserved the information required to reconstruct the noise field. Possible trial categories based on (signal, response) pairs are: (c,c), (c,x), (x,c), (x,x). Noise fields were averaged separately for each category, and a final classification image was obtained by averaging the four mean images after inverting the sign of categories in which x was the response. If the observer employs a template, it should be revealed in the classification image. The lowpass-filtered classification image derived from 2048 responses of one observer is shown here, along with the corresponding ideal template. An approximation to the ideal template can be seen appropriately located within the classification image. We have also simulated and will discuss the classification images expected from various discrimination models in this experimental context. The construction of classification images appears to be a powerful tool for studying classification strategies used by human observers. Like a Rorschach test, it surreptitiously discovers the inner desires of the visual system.

  1. Photometric Supernova Classification with Machine Learning

    Science.gov (United States)

    Lochner, Michelle; McEwen, Jason D.; Peiris, Hiranya V.; Lahav, Ofer; Winter, Max K.

    2016-08-01

    Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k-nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.

  2. A New Value Classification and Values to Be Acquired by Students Related to This Classification

    Science.gov (United States)

    Acat, M. Bahaddin; Aslan, Mecit

    2012-01-01

    The aim of this study is to access a new value classification and analyse the views of teacher and parents related to this classification. The general survey model was employed in this study. The population of this study is composed of school teachers working in primary schools and parents of their students in Eskisehir. The present study adopted…

  3. Classification techniques based on AI application to defect classification in cast aluminum

    Science.gov (United States)

    Platero, Carlos; Fernandez, Carlos; Campoy, Pascual; Aracil, Rafael

    1994-11-01

    This paper describes the Artificial Intelligent techniques applied to the interpretation process of images from cast aluminum surface presenting different defects. The whole process includes on-line defect detection, feature extraction and defect classification. These topics are discussed in depth through the paper. Data preprocessing process, as well as segmentation and feature extraction are described. At this point, algorithms employed along with used descriptors are shown. Syntactic filter has been developed to modelate the information and to generate the input vector to the classification system. Classification of defects is achieved by means of rule-based systems, fuzzy models and neural nets. Different classification subsystems perform together for the resolution of a pattern recognition problem (hybrid systems). Firstly, syntactic methods are used to obtain the filter that reduces the dimension of the input vector to the classification process. Rule-based classification is achieved associating a grammar to each defect type; the knowledge-base will be formed by the information derived from the syntactic filter along with the inferred rules. The fuzzy classification sub-system uses production rules with fuzzy antecedent and their consequents are ownership rates to every defect type. Different architectures of neural nets have been implemented with different results, as shown along the paper. In the higher classification level, the information given by the heterogeneous systems as well as the history of the process is supplied to an Expert System in order to drive the casting process.

  4. Classification Based on Hierarchical Linear Models: The Need for Incorporation of Social Contexts in Classification Analysis

    Science.gov (United States)

    Vaughn, Brandon K.; Wang, Qui

    2009-01-01

    Many areas in educational and psychological research involve the use of classification statistical analysis. For example, school districts might be interested in attaining variables that provide optimal prediction of school dropouts. In psychology, a researcher might be interested in the classification of a subject into a particular psychological…

  5. Learning features for tissue classification with the classification restricted Boltzmann machine

    DEFF Research Database (Denmark)

    van Tulder, Gijs; de Bruijne, Marleen

    Performance of automated tissue classification in medical imaging depends on the choice of descriptive features. In this paper, we show how restricted Boltzmann machines (RBMs) can be used to learn features that are especially suited for texture-based tissue classification. We introduce the...

  6. Automatic classification of blank substrate defects

    Science.gov (United States)

    Boettiger, Tom; Buck, Peter; Paninjath, Sankaranarayanan; Pereira, Mark; Ronald, Rob; Rost, Dan; Samir, Bhamidipati

    2014-10-01

    Mask preparation stages are crucial in mask manufacturing, since this mask is to later act as a template for considerable number of dies on wafer. Defects on the initial blank substrate, and subsequent cleaned and coated substrates, can have a profound impact on the usability of the finished mask. This emphasizes the need for early and accurate identification of blank substrate defects and the risk they pose to the patterned reticle. While Automatic Defect Classification (ADC) is a well-developed technology for inspection and analysis of defects on patterned wafers and masks in the semiconductors industry, ADC for mask blanks is still in the early stages of adoption and development. Calibre ADC is a powerful analysis tool for fast, accurate, consistent and automatic classification of defects on mask blanks. Accurate, automated classification of mask blanks leads to better usability of blanks by enabling defect avoidance technologies during mask writing. Detailed information on blank defects can help to select appropriate job-decks to be written on the mask by defect avoidance tools [1][4][5]. Smart algorithms separate critical defects from the potentially large number of non-critical defects or false defects detected at various stages during mask blank preparation. Mechanisms used by Calibre ADC to identify and characterize defects include defect location and size, signal polarity (dark, bright) in both transmitted and reflected review images, distinguishing defect signals from background noise in defect images. The Calibre ADC engine then uses a decision tree to translate this information into a defect classification code. Using this automated process improves classification accuracy, repeatability and speed, while avoiding the subjectivity of human judgment compared to the alternative of manual defect classification by trained personnel [2]. This paper focuses on the results from the evaluation of Automatic Defect Classification (ADC) product at MP Mask

  7. Agricultural Land Use classification from Envisat MERIS

    Science.gov (United States)

    Brodsky, L.; Kodesova, R.

    2009-04-01

    This study focuses on evaluation of a crop classification from middle-resolution images (Envisat MERIS) at national level. The main goal of such Land Use product is to provid spatial data for optimisation of monitoring of surface and groundwater pollution in the Czech Republic caused by pesticides use in agriculture. As there is a lack of spatial data on the pesticide use and their distribution, the localisation can be done according to the crop cover on arable land derived from the remote sensing images. Often high resolution data are used for agricultural Land Use classification but only at regional or local level. Envisat MERIS data, due to the wide satellite swath, can be used also at national level. The high temporal and also spectral resolution of MERIS data has indisputable advantage for crop classification. Methodology of a pixel-based MERIS classification applying an artificial neural-network (ANN) technique was proposed and performed at a national level, the Czech Republic. Five crop groups were finally selected - winter crops, spring crops, summer crops and other crops to be classified. Classification models included a linear, radial basis function (RBF) and a multi-layer percepton (MLP) ANN with 50 networks tested in training. The training data set consisted of about 200 samples per class, on which bootstrap resampling was applied. Selection of a subset of independent variables (Meris spectral channels) was used in the procedure. The best selected ANN model (MLP: 3 in, 13 hidden, 3 out) resulted in very good performance (correct classification rate 0.974, error 0.103) applying three crop types data set. In the next step data set with five crop types was evaluated. The ANN model (MLP: 5 in, 12 hidden, 5 out) performance was also very good (correct classification rate 0.930, error 0.370). The study showed, that while accuracy of about 80 % was achieved at pixel level when classifying only three crops, accuracy of about 70 % was achieved for five crop

  8. PASTEC: an automatic transposable element classification tool.

    Directory of Open Access Journals (Sweden)

    Claire Hoede

    Full Text Available SUMMARY: The classification of transposable elements (TEs is key step towards deciphering their potential impact on the genome. However, this process is often based on manual sequence inspection by TE experts. With the wealth of genomic sequences now available, this task requires automation, making it accessible to most scientists. We propose a new tool, PASTEC, which classifies TEs by searching for structural features and similarities. This tool outperforms currently available software for TE classification. The main innovation of PASTEC is the search for HMM profiles, which is useful for inferring the classification of unknown TE on the basis of conserved functional domains of the proteins. In addition, PASTEC is the only tool providing an exhaustive spectrum of possible classifications to the order level of the Wicker hierarchical TE classification system. It can also automatically classify other repeated elements, such as SSR (Simple Sequence Repeats, rDNA or potential repeated host genes. Finally, the output of this new tool is designed to facilitate manual curation by providing to biologists with all the evidence accumulated for each TE consensus. AVAILABILITY: PASTEC is available as a REPET module or standalone software (http://urgi.versailles.inra.fr/download/repet/REPET_linux-x64-2.2.tar.gz. It requires a Unix-like system. There are two standalone versions: one of which is parallelized (requiring Sun grid Engine or Torque, and the other of which is not.

  9. Retinal vasculature classification using novel multifractal features

    International Nuclear Information System (INIS)

    Retinal blood vessels have been implicated in a large number of diseases including diabetic retinopathy and cardiovascular diseases, which cause damages to retinal blood vessels. The availability of retinal vessel imaging provides an excellent opportunity for monitoring and diagnosis of retinal diseases, and automatic analysis of retinal vessels will help with the processes. However, state of the art vascular analysis methods such as counting the number of branches or measuring the curvature and diameter of individual vessels are unsuitable for the microvasculature. There has been published research using fractal analysis to calculate fractal dimensions of retinal blood vessels, but so far there has been no systematic research extracting discriminant features from retinal vessels for classifications. This paper introduces new methods for feature extraction from multifractal spectra of retinal vessels for classification. Two publicly available retinal vascular image databases are used for the experiments, and the proposed methods have produced accuracies of 85.5% and 77% for classification of healthy and diabetic retinal vasculatures. Experiments show that classification with multiple fractal features produces better rates compared with methods using a single fractal dimension value. In addition to this, experiments also show that classification accuracy can be affected by the accuracy of vessel segmentation algorithms. (paper)

  10. Hydropedological insights when considering catchment classification

    Directory of Open Access Journals (Sweden)

    J. Bouma

    2011-02-01

    Full Text Available Soil classification systems are analysed in relation to the functioning and characterisation of catchments. Soil classifications are useful to create systematic order in the overwhelming quantity of different soils in the world and to extrapolate data available for a given soil type to soils elsewhere with identical classifications. However, such classifications are based on permanent characteristics as formed by the soil forming factors over often very long periods of time and this does not necessarily match with characteristics and parameters needed for functional soil characterization focusing, for example, on catchment hydrology. Hydropedology has made contributions towards functional characterization of soils as is illustrated for recent hydrological catchment studies. However, much still needs to be learned about the physical behaviour of anisotropic, heterogeneous field soils with varying soil structures during the year and the suggestion is made to first focus on improving simulation of catchment hydrology, incorporating hydropedological expertise, before embarking on a classification effort which involves major input of time and involves the risk of distraction. In doing so, we advise to also define other characteristics for catchment performance than the traditionally measured discharge rates.

  11. Acute Pancreatitis Classifications: Basis and Key Goals.

    Science.gov (United States)

    Xu, Xiao Dong; Wang, Zhe Yuan; Zhang, Ling Yi; Ni, Rui; Wei, Feng Xian; Han, Wei; Zhang, Hui Han; Zhang, Ya Wu; Wei, Zhen Gang; Guo, Xiao Hu; Guo, Liu Qiang; Ma, Jian Zhong; Zhang, You Cheng

    2015-12-01

    To explore the efficacy of the revised Atlanta classification (RACAP) and the determinant-based classification of acute pancreatitis severity (DBCAPS) on the basis of clinical data and feedback from patients with acute pancreatitis (AP). The authors retrospectively investigated a total of 573 patients with AP admitted to our hospital between December 2011 and December 2014. The definitions of severity and local complications in AP using RACAP and DBCAPS are presented and common points and mutual differences between the 2 groups are analyzed and discussed. Classification according to RACAP and DBCAPS found 86 (15%) and 178 (31.1%) mild cases (P peripancreatic fluid collection (236 patients, 75.40%), pancreatic pseudocysts (20 patients, 6.4%), acute necrotic collection (42 patients, 13.4%), and walled-off necrosis (15 patients, 4.8%) were observed. Among the 153 DBCAPS-defined cases, sterile peripancreatic necrosis (105 patients, 68.6%), sterile pancreatic necrosis (44 patients, 28.8%), infected peripancreatic necrosis (2 patients, 1.3%), and infected pancreatic necrosis (2/153 patients, 1.3%) were observed. Both classifications adopted organ failure and complications as determinants of severity. Revised Atlanta classification refined local complications and DBCAPS modified severity to include critical AP. In accordance with the demands of precision medicine, a combination of the 2 could be important for further clinical practice and scientific research. PMID:26632905

  12. Enhancing Accuracy of Plant Leaf Classification Techniques

    Directory of Open Access Journals (Sweden)

    C. S. Sumathi

    2014-03-01

    Full Text Available Plants have become an important source of energy, and are a fundamental piece in the puzzle to solve the problem of global warming. Living beings also depend on plants for their food, hence it is of great importance to know about the plants growing around us and to preserve them. Automatic plant leaf classification is widely researched. This paper investigates the efficiency of learning algorithms of MLP for plant leaf classification. Incremental back propagation, Levenberg–Marquardt and batch propagation learning algorithms are investigated. Plant leaf images are examined using three different Multi-Layer Perceptron (MLP modelling techniques. Back propagation done in batch manner increases the accuracy of plant leaf classification. Results reveal that batch training is faster and more accurate than MLP with incremental training and Levenberg– Marquardt based learning for plant leaf classification. Various levels of semi-batch training used on 9 species of 15 sample each, a total of 135 instances show a roughly linear increase in classification accuracy.

  13. Random forests for classification in ecology

    Science.gov (United States)

    Cutler, D.R.; Edwards, T.C., Jr.; Beard, K.H.; Cutler, A.; Hess, K.T.; Gibson, J.; Lawler, J.J.

    2007-01-01

    Classification procedures are some of the most widely used statistical methods in ecology. Random forests (RF) is a new and powerful statistical classifier that is well established in other disciplines but is relatively unknown in ecology. Advantages of RF compared to other statistical classifiers include (1) very high classification accuracy; (2) a novel method of determining variable importance; (3) ability to model complex interactions among predictor variables; (4) flexibility to perform several types of statistical data analysis, including regression, classification, survival analysis, and unsupervised learning; and (5) an algorithm for imputing missing values. We compared the accuracies of RF and four other commonly used statistical classifiers using data on invasive plant species presence in Lava Beds National Monument, California, USA, rare lichen species presence in the Pacific Northwest, USA, and nest sites for cavity nesting birds in the Uinta Mountains, Utah, USA. We observed high classification accuracy in all applications as measured by cross-validation and, in the case of the lichen data, by independent test data, when comparing RF to other common classification methods. We also observed that the variables that RF identified as most important for classifying invasive plant species coincided with expectations based on the literature. ?? 2007 by the Ecological Society of America.

  14. Scientific and General Subject Classifications in the Digital World

    CERN Document Server

    De Robbio, Antonella; Marini, A

    2001-01-01

    In the present work we discuss opportunities, problems, tools and techniques encountered when interconnecting discipline-specific subject classifications, primarily organized as search devices in bibliographic databases, with general classifications originally devised for book shelving in public libraries. We first state the fundamental distinction between topical (or subject) classifications and object classifications. Then we trace the structural limitations that have constrained subject classifications since their library origins, and the devices that were used to overcome the gap with genuine knowledge representation. After recalling some general notions on structure, dynamics and interferences of subject classifications and of the objects they refer to, we sketch a synthetic overview on discipline-specific classifications in Mathematics, Computing and Physics, on one hand, and on general classifications on the other. In this setting we present The Scientific Classifications Page, which collects groups of...

  15. Classification of sudden and arrhythmic death

    DEFF Research Database (Denmark)

    Torp-Pedersen, C; Køber, L; Elming, H;

    1997-01-01

    Since all death is (eventually) sudden and associated with cardiac arrhythmias, the concept of sudden death is only meaningful if it is unexpected, while arrhythmic death is only meaningful if life could have continued had the arrhythmia been prevented or treated. Current classifications of death...... as being arrhythmic or sudden are all biased by the difficulty of having to decide on the degree of unexpectedness or the likelihood that life could continue without the arrhythmia. The uncertainties are enlarged by the fact that critical data (such as knowledge of arrhythmias at the time of death or...... autopsy) are available in only a few percent of cases. A main problem in using classifications is the lack of validation data. This situation has, with the MADIT trial, changed in the case of the Thaler and Hinkle classification of arrhythmic death. The MADIT trial demonstrated that arrhythmic death was...

  16. Reproducibility of histologic classification of gastric cancer.

    Science.gov (United States)

    Palli, D.; Bianchi, S.; Cipriani, F.; Duca, P.; Amorosi, A.; Avellini, C.; Russo, A.; Saragoni, A.; Todde, P.; Valdes, E.

    1991-01-01

    A panel review of histologic specimens was carried out as part of a multi-centre case-control study of gastric cancer (GC) and diet. Comparisons of diagnoses of 100 GCs by six pathologists revealed agreement in histologic classification for about 70-80% of the cancers. Concordance was somewhat higher when using the Lauren rather than the Ming or World Health Organization classification systems. Histologic types from reading biopsy tissue agreed with those derived from surgical specimens for 65-75% of the 100 tumours. Intra-observer agreement in histologic classification, assessed by repeat readings up to 3 years apart by one pathologist, was 95%. The findings indicate that, although overall concordance was good, it is important to standardise diagnoses in multi-centre epidemiologic studies of GC by histologic type. PMID:2039701

  17. Using Genetic Algorithms for Texts Classification Problems

    Directory of Open Access Journals (Sweden)

    A. A. Shumeyko

    2009-01-01

    Full Text Available The avalanche quantity of the information developed by mankind has led to concept of automation of knowledge extraction – Data Mining ([1]. This direction is connected with a wide spectrum of problems - from recognition of the fuzzy set to creation of search machines. Important component of Data Mining is processing of the text information. Such problems lean on concept of classification and clustering ([2]. Classification consists in definition of an accessory of some element (text to one of in advance created classes. Clustering means splitting a set of elements (texts on clusters which quantity are defined by localization of elements of the given set in vicinities of these some natural centers of these clusters. Realization of a problem of classification initially should lean on the given postulates, basic of which – the aprioristic information on primary set of texts and a measure of affinity of elements and classes.

  18. A Physiologically Inspired Method for Audio Classification

    Directory of Open Access Journals (Sweden)

    David V. Anderson

    2005-06-01

    Full Text Available We explore the use of physiologically inspired auditory features with both physiologically motivated and statistical audio classification methods. We use features derived from a biophysically defensible model of the early auditory system for audio classification using a neural network classifier. We also use a Gaussian-mixture-model (GMM-based classifier for the purpose of comparison and show that the neural-network-based approach works better. Further, we use features from a more advanced model of the auditory system and show that the features extracted from this model of the primary auditory cortex perform better than the features from the early auditory stage. The features give good classification performance with only one-second data segments used for training and testing.

  19. Classification of hematologic malignancies using texton signatures.

    Science.gov (United States)

    Tuzel, Oncel; Yang, Lin; Meer, Peter; Foran, David J

    2007-10-01

    We describe a decision support system to distinguish among hematology cases directly from microscopic specimens. The system uses an image database containing digitized specimens from normal and four different hematologic malignancies. Initially, the nuclei and cytoplasmic components of the specimens are segmented using a robust color gradient vector flow active contour model. Using a few cell images from each class, the basic texture elements (textons) for the nuclei and cytoplasm are learned, and the cells are represented through texton histograms. We propose to use support vector machines on the texton histogram based cell representation and achieve major improvement over the commonly used classification methods in texture research. Experiments with 3,691 cell images from 105 patients which originated from four different hospitals indicate more than 84% classification performance for individual cells and 89% for case based classification for the five class problem. PMID:19890460

  20. Photometric Supernova Classification With Machine Learning

    CERN Document Server

    Lochner, Michelle; Peiris, Hiranya V; Lahav, Ofer; Winter, Max K

    2016-01-01

    Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Telescope (LSST), given that spectroscopic confirmation of type for all supernovae discovered with these surveys will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques fitting parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k-nearest neighbors, support vector machines, artificial neural networks and boosted decision trees. We test the pipeline on simulated multi-ba...

  1. Data Driven Hierarchical Serial Scene Classification Framework

    Institute of Scientific and Technical Information of China (English)

    FENG Wen-Gang

    2014-01-01

    Scene classification is a complicated task, because it includes much content and it is difficult to capture its distribution. A novel hierarchical serial scene classification framework is presented in this paper. At first, we use hierarchical feature to present both the global scene and local patches containing specific objects. Hierarchy is presented by space pyramid match, and our own codebook is built by two different types of words. Secondly, we train the visual words by generative and discriminative methods respectively based on space pyramid match, which could obtain the local patch labels efficiently. Then, we use a neural network to simulate the human decision process, which leads to the final scene category from local labels. Experiments show that the hierarchical serial scene image representation and classification model obtains superior results with respect to accuracy.

  2. The International Classification for Nursing Practice (ICNP)

    DEFF Research Database (Denmark)

    Mortensen, Randi A.; Nielsen, Gunnar Haase

    2001-01-01

    This publication deals with the general field of health informatics and some issues particular to nursing. It starts with an introduction to health care, discussing the ‘classification and management in nursing information technology’ and the ‘nursing minimum data set’, health concepts......, an introduction to nursing science and the International Classification for Nursing Practice (ICNP). The textbook continues with an information technology aspects’ section. in this section important aspects of health informatics and hospital information systems are discussed, like data protection...... and confidentiality, telecare service for nurses, data analysis methods and classification methods. The last section of this book deals with the organizational impact of health informatics. Major topics are: impacts of communications, information and technology on organizations, impact in nursing environment, quality...

  3. Automatic Classification of Attacks on IP Telephony

    Directory of Open Access Journals (Sweden)

    Jakub Safarik

    2013-01-01

    Full Text Available This article proposes an algorithm for automatic analysis of attack data in IP telephony network with a neural network. Data for the analysis is gathered from variable monitoring application running in the network. These monitoring systems are a typical part of nowadays network. Information from them is usually used after attack. It is possible to use an automatic classification of IP telephony attacks for nearly real-time classification and counter attack or mitigation of potential attacks. The classification use proposed neural network, and the article covers design of a neural network and its practical implementation. It contains also methods for neural network learning and data gathering functions from honeypot application.

  4. Hyperspectral Image Classification Using Discriminative Dictionary Learning

    International Nuclear Information System (INIS)

    The hyperspectral image (HSI) processing community has witnessed a surge of papers focusing on the utilization of sparse prior for effective HSI classification. In sparse representation based HSI classification, there are two phases: sparse coding with an over-complete dictionary and classification. In this paper, we first apply a novel fisher discriminative dictionary learning method, which capture the relative difference in different classes. The competitive selection strategy ensures that atoms in the resulting over-complete dictionary are the most discriminative. Secondly, motivated by the assumption that spatially adjacent samples are statistically related and even belong to the same materials (same class), we propose a majority voting scheme incorporating contextual information to predict the category label. Experiment results show that the proposed method can effectively strengthen relative discrimination of the constructed dictionary, and incorporating with the majority voting scheme achieve generally an improved prediction performance

  5. Text Classification Using Sentential Frequent Itemsets

    Institute of Scientific and Technical Information of China (English)

    Shi-Zhu Liu; He-Ping Hu

    2007-01-01

    Text classification techniques mostly rely on single term analysis of the document data set, while more concepts,especially the specific ones, are usually conveyed by set of terms. To achieve more accurate text classifier, more informative feature including frequent co-occurring words in the same sentence and their weights are particularly important in such scenarios. In this paper, we propose a novel approach using sentential frequent itemset, a concept comes from association rule mining, for text classification, which views a sentence rather than a document as a transaction, and uses a variable precision rough set based method to evaluate each sentential frequent itemset's contribution to the classification. Experiments over the Reuters and newsgroup corpus are carried out, which validate the practicability of the proposed system.

  6. Global change and climate-vegetation classification

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Three phrases of the quantitative study of climate-vegetation classification and their characteristics are presented based on the review of advance in climate-vegetation interaction, a key issue of "global change and terrestrial ecosystems (GCTE)" which is the core project of International Geosphere-Biosphere Programme (IGBP): (ⅰ) characterized by the correlation between natural vegetation types and climate; (ⅱ) characterized by climatic indices which have obviously been restricted to plant ecophysiology; (ⅲ) characterized by coupling both structure and function of vegetation. Thus, the prospective of climate-vegetation classification for global change study in China was proposed, especially the study coupling climate-vegetation classification models with atmospheric general circulation models (GCMs) was emphasized.

  7. AGN Zoo and Classifications of Active Galaxies

    Science.gov (United States)

    Mickaelian, Areg M.

    2015-07-01

    We review the variety of Active Galactic Nuclei (AGN) classes (so-called "AGN zoo") and classification schemes of galaxies by activity types based on their optical emission-line spectrum, as well as other parameters and other than optical wavelength ranges. A historical overview of discoveries of various types of active galaxies is given, including Seyfert galaxies, radio galaxies, QSOs, BL Lacertae objects, Starbursts, LINERs, etc. Various kinds of AGN diagnostics are discussed. All known AGN types and subtypes are presented and described to have a homogeneous classification scheme based on the optical emission-line spectra and in many cases, also other parameters. Problems connected with accurate classifications and open questions related to AGN and their classes are discussed and summarized.

  8. A Gameplay Definition through Videogame Classification

    Directory of Open Access Journals (Sweden)

    Damien Djaouti

    2008-01-01

    Full Text Available This paper is part of an experimental approach aimed to raise a videogames classification. Being inspired by the methodology that Propp used for the classification of Russian fairy tales, we have identified recurrent diagrams within rules of videogames, that we called “Gameplay Bricks”. The combinations of these different bricks should allow us to represent a classification of all videogames in accordance with their rules. In this article, we will study the nature of these bricks, especially the link they seem to have with two types of game rules: the rules that allow the player to “manipulate” the elements of the game, and the rules defining the “goal” of the game. This study will lead to an hypothesis about the nature of gameplay.

  9. Myelodysplastic syndrome: classification and prognostic systems

    Directory of Open Access Journals (Sweden)

    Rosangela Invernizzi

    2011-12-01

    Full Text Available Myelodysplastic syndromes (MDS are acquired clonal disorders of hematopoiesis, that are characterized most frequently by normocellular or hypercellular bone marrow specimens, and maturation that is morphologically and functionally dysplastic. MDS constitute a complex hematological problem: differences in disease presentation, progression and outcome have made it necessary to use classification systems to improve diagnosis, prognostication and treatment selection. On the basis of new scientific and clinical information, classification and prognostic systems have recently been updated and minimal diagnostic criteria forMDS have been proposed by expert panels. In addition, in the last few years our ability to define the prognosis of the individual patient with MDS has improved. In this paper World Health Organization (WHO classification refinements and recent prognostic scoring systems for the definition of individual risk are highlighted and current criteria are discussed. The recommendations should facilitate diagnostic and prognostic evaluations in MDS and selection of patients for new effective targeted therapies.

  10. A new classification of geological resources

    International Nuclear Information System (INIS)

    The traditional definition of the geological resource term excludes all those elements or processes of the physical environment that show a scientific, didactic, or cultural interest, but do not offer, in principle, an economic potential. The so called cultural geo-resources have traditionally not been included within a classification that puts them in the same hierarchical and semantic ranking than the rest of the resources, and there has been no attempt to define a classification of these resources under a more didactic and modern perspective. Hence, in order to catalogue all those geological elements that show a cultural, patrimonial, scientific, or didactic interest as a resource, this paper proposes a new classification in which geo-resources stand in the same hierarchical and semantic ranking than the rest of the resources traditionally catalogued as such.

  11. Structural classification of galaxies in clusters

    CERN Document Server

    Andreon, S; Andreon, Stefano; Davoust, Emmanuel

    1996-01-01

    The traditional method of morphological classification, by visual inspection of images of uniform quality and by reference to standards for each type, is critically examined. The rate of agreement among traditional morphologists on the morphological type of galaxies is estimated from published classification works, and is estimated at about 20 %, when galaxies are classified into three bins (E, S0, S+Irr). The advantages of the quantitative method of structural classification for classifying galaxies in clusters are outlined. This method is based on the isophotal analysis of galaxy images, and on the examination of quantitative structural parameters derived from this analysis, such as the profiles of luminosity, ellipticity and deviations from ellipticity of the galaxy. The structural and traditional methods are compared on a complete sample of 190 galaxies in the Coma cluster. The morphological types derived by both methods agree to within 15 or 20 %, the same rate as among traditional morphologists alone, t...

  12. Combinatorial Classification for Chunking Arabic Texts

    Directory of Open Access Journals (Sweden)

    Fériel Ben Fraj

    2012-09-01

    Full Text Available Text parsing has always benefited from special attention since the first applications of natural language processing (NLP. The problem gets worse for the Arabic language because of its specific features that make it quite different and even more ambiguous than other natural languages when processed. In this paper, we discuss a new approach for chunking Arabic texts based on a combinatorial classification process. It is a modular chunker that identifies the chunk heads using a combinatorial binary classification before recognizing their types based on the parts-of-speech of the chunk heads, already identified. For the experimentation, we use over than 2300 words as training data. The evaluation of the chunker consists of two steps and gives results that we consider very satisfactory (average accuracy of 89,60% for the classification step and 80,46% for the full chunking process.

  13. Developing classification indices for Chinese pulse diagnosis

    CERN Document Server

    Shu, Jian-Jun

    2014-01-01

    Aim: To develop classification criteria for Chinese pulse diagnosis and to objectify the ancient diagnostic technique. Methods: Chinese pulse curves are treated as wave signals. Multidimensional variable analysis is performed to provide the best curve fit between the recorded Chinese pulse waveforms and the collective Gamma density functions. Results: Chinese pulses can be recognized quantitatively by the newly-developed four classification indices, that is, the wave length, the relative phase difference, the rate parameter, and the peak ratio. The new quantitative classification not only reduces the dependency of pulse diagnosis on Chinese physician's experience, but also is able to interpret pathological wrist-pulse waveforms more precisely. Conclusions: Traditionally, Chinese physicians use fingertips to feel the wrist-pulses of patients in order to determine their health conditions. The qualitative theory of the Chinese pulse diagnosis is based on the experience of Chinese physicians for thousands of year...

  14. Clustering Analysis within Text Classification Techniques

    Directory of Open Access Journals (Sweden)

    Madalina ZURINI

    2011-01-01

    Full Text Available The paper represents a personal approach upon the main applications of classification which are presented in the area of knowledge based society by means of methods and techniques widely spread in the literature. Text classification is underlined in chapter two where the main techniques used are described, along with an integrated taxonomy. The transition is made through the concept of spatial representation. Having the elementary elements of geometry and the artificial intelligence analysis, spatial representation models are presented. Using a parallel approach, spatial dimension is introduced in the process of classification. The main clustering methods are described in an aggregated taxonomy. For an example, spam and ham words are clustered and spatial represented, when the concepts of spam, ham and common and linkage word are presented and explained in the xOy space representation.

  15. An Ensemble Classification Algorithm for Hyperspectral Images

    Directory of Open Access Journals (Sweden)

    K.Kavitha

    2014-04-01

    Full Text Available Hyperspectral image analysis has been used for many purposes in environmental monitoring, remote sensing, vegetation research and also for land cover classification. A hyperspectral image consists of many layers in which each layer represents a specific wavelength. The layers stack on top of one another making a cube-like image for entire spectrum. This work aims to classify the hyperspectral images and to produce a thematic map accurately. Spatial information of hyperspectral images is collected by applying morphological profile and local binary pattern. Support vector machine is an efficient classification algorithm for classifying the hyperspectral images. Genetic algorithm is used to obtain the best feature subjected for classification. Selected features are classified for obtaining the classes and to produce a thematic map. Experiment is carried out with AVIRIS Indian Pines and ROSIS Pavia University. Proposed method produces accuracy as 93% for Indian Pines and 92% for Pavia University.

  16. Interobserver variation in classification of malleolar fractures

    Energy Technology Data Exchange (ETDEWEB)

    Verhage, S.M.; Hoogendoorn, J.M. [MC Haaglanden, Department of Surgery, The Hague (Netherlands); Secretariaat Heelkunde, MC Haaglanden, locatie Westeinde, Postbus 432, CK, The Hague (Netherlands); Rhemrev, S.J. [MC Haaglanden, Department of Surgery, The Hague (Netherlands); Keizer, S.B. [MC Haaglanden, Department of Orthopaedic Surgery, The Hague (Netherlands); Quarles van Ufford, H.M.E. [MC Haaglanden, Department of Radiology, The Hague (Netherlands)

    2015-10-15

    Classification of malleolar fractures is a matter of debate. In the ideal situation, a classification system is easy to use, shows good inter- and intraobserver agreement, and has implications for treatment or research. Interobserver study. Four observers distributed 100 X-rays to the Weber, AO and Lauge-Hansen classification. In case of a trimalleolar fracture, the size of the posterior fragment was measured. Interobserver agreement was calculated with Cohen's kappa. Agreement on the size of the posterior fragment was calculated with the intraclass correlation coefficient. Moderate agreement was found with all classification systems: the Weber (K = 0.49), AO (K = 0.45) and Lauge-Hansen (K = 0.47). Interobserver agreement on the presence of a posterior fracture was substantial (K = 0.63). Estimation of the size of the fragment showed moderate agreement (ICC = 0.57). Classification according to the classical systems showed moderate interobserver agreement, probably due to an unclear trauma mechanism or the difficult relation between the level of the fibular fracture and syndesmosis. Substantial agreement on posterior malleolar fractures is mostly due to small (<5 %) posterior fragments. A classification system that describes the presence and location of fibular fractures, presence of medial malleolar fractures or deep deltoid ligament injury, and presence of relevant and dislocated posterior malleolar fractures is more useful in the daily setting than the traditional systems. In case of a trimalleolar fracture, a CT scan is in our opinion very useful in the detection of small posterior fragments and preoperative planning. (orig.)

  17. Interobserver variation in classification of malleolar fractures

    International Nuclear Information System (INIS)

    Classification of malleolar fractures is a matter of debate. In the ideal situation, a classification system is easy to use, shows good inter- and intraobserver agreement, and has implications for treatment or research. Interobserver study. Four observers distributed 100 X-rays to the Weber, AO and Lauge-Hansen classification. In case of a trimalleolar fracture, the size of the posterior fragment was measured. Interobserver agreement was calculated with Cohen's kappa. Agreement on the size of the posterior fragment was calculated with the intraclass correlation coefficient. Moderate agreement was found with all classification systems: the Weber (K = 0.49), AO (K = 0.45) and Lauge-Hansen (K = 0.47). Interobserver agreement on the presence of a posterior fracture was substantial (K = 0.63). Estimation of the size of the fragment showed moderate agreement (ICC = 0.57). Classification according to the classical systems showed moderate interobserver agreement, probably due to an unclear trauma mechanism or the difficult relation between the level of the fibular fracture and syndesmosis. Substantial agreement on posterior malleolar fractures is mostly due to small (<5 %) posterior fragments. A classification system that describes the presence and location of fibular fractures, presence of medial malleolar fractures or deep deltoid ligament injury, and presence of relevant and dislocated posterior malleolar fractures is more useful in the daily setting than the traditional systems. In case of a trimalleolar fracture, a CT scan is in our opinion very useful in the detection of small posterior fragments and preoperative planning. (orig.)

  18. Classification of spontaneous EEG signals in migraine

    Science.gov (United States)

    Bellotti, R.; De Carlo, F.; de Tommaso, M.; Lucente, M.

    2007-08-01

    We set up a classification system able to detect patients affected by migraine without aura, through the analysis of their spontaneous EEG patterns. First, the signals are characterized by means of wavelet-based features, than a supervised neural network is used to classify the multichannel data. For the feature extraction, scale-dependent and scale-independent methods are considered with a variety of wavelet functions. Both the approaches provide very high and almost comparable classification performances. A complete separation of the two groups is obtained when the data are plotted in the plane spanned by two suitable neural outputs.

  19. Automated Classification of Seedlings Using Computer Vision

    DEFF Research Database (Denmark)

    Dyrmann, Mads; Christiansen, Peter

    on seven different species. The segmentation process finds plant elements through a colour segmentation method combining excessive green and excessive red and the Plant Stem Emerging Point algorithm to separate leaves from plants. These plant elements are then described by 50 different feature...... Multivariate Gaussian classifier, the k-Nearest Neighbour classifier and the Support Vector Machine classifier. Finally, classifier fusion is performed by using Bayes Belief Integration to combine the classification for the whole plant with the individual classifications of the leaves of the plant in order to...

  20. Complex classification of global geomagnetic disturbances

    Science.gov (United States)

    Barkhatov, N. A.; Levitin, A. E.; Revunov, S. E.

    2006-12-01

    Based on the Kohonen algorithm, a self-training neural network is constructed which allows one to classify geomagnetic disturbances using the data on parameters of the solar wind and interplanetary magnetic field. Such an approach permits one to consider the suggested classification simultaneously as space and physical, since the space origin of disturbances of different kinds is considered within the framework of the classification. As a result of numerical experiments, we have succeeded in isolating basic classes of complexes of disturbed parameters accounting for various events of the space weather, each of which is responsible for corresponding global magnetospheric conditions.