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Sample records for testing color-based classifications

  1. SPITZER IRS SPECTRA OF LUMINOUS 8 μm SOURCES IN THE LARGE MAGELLANIC CLOUD: TESTING COLOR-BASED CLASSIFICATIONS

    International Nuclear Information System (INIS)

    Buchanan, Catherine L.; Kastner, Joel H.; Hrivnak, Bruce J.; Sahai, Raghvendra

    2009-01-01

    We present archival Spitzer Infrared Spectrograph (IRS) spectra of 19 luminous 8 μm selected sources in the Large Magellanic Cloud (LMC). The object classes derived from these spectra and from an additional 24 spectra in the literature are compared with classifications based on Two Micron All Sky Survey (2MASS)/MSX (J, H, K, and 8 μm) colors in order to test the 'JHK8' (Kastner et al.) classification scheme. The IRS spectra confirm the classifications of 22 of the 31 sources that can be classified under the JHK8 system. The spectroscopic classification of 12 objects that were unclassifiable in the JHK8 scheme allow us to characterize regions of the color-color diagrams that previously lacked spectroscopic verification, enabling refinements to the JHK8 classification system. The results of these new classifications are consistent with previous results concerning the identification of the most infrared-luminous objects in the LMC. In particular, while the IRS spectra reveal several new examples of asymptotic giant branch (AGB) stars with O-rich envelopes, such objects are still far outnumbered by carbon stars (C-rich AGB stars). We show that Spitzer IRAC/MIPS color-color diagrams provide improved discrimination between red supergiants and oxygen-rich and carbon-rich AGB stars relative to those based on 2MASS/MSX colors. These diagrams will enable the most luminous IR sources in Local Group galaxies to be classified with high confidence based on their Spitzer colors. Such characterizations of stellar populations will continue to be possible during Spitzer's warm mission through the use of IRAC [3.6]-[4.5] and 2MASS colors.

  2. 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,…

  3. Testing a polarimetric cloud imager aboard research vessel Polarstern: comparison of color-based and polarimetric cloud detection algorithms.

    Science.gov (United States)

    Barta, András; Horváth, Gábor; Horváth, Ákos; Egri, Ádám; Blahó, Miklós; Barta, Pál; Bumke, Karl; Macke, Andreas

    2015-02-10

    Cloud cover estimation is an important part of routine meteorological observations. Cloudiness measurements are used in climate model evaluation, nowcasting solar radiation, parameterizing the fluctuations of sea surface insolation, and building energy transfer models of the atmosphere. Currently, the most widespread ground-based method to measure cloudiness is based on analyzing the unpolarized intensity and color distribution of the sky obtained by digital cameras. As a new approach, we propose that cloud detection can be aided by the additional use of skylight polarization measured by 180° field-of-view imaging polarimetry. In the fall of 2010, we tested such a novel polarimetric cloud detector aboard the research vessel Polarstern during expedition ANT-XXVII/1. One of our goals was to test the durability of the measurement hardware under the extreme conditions of a trans-Atlantic cruise. Here, we describe the instrument and compare the results of several different cloud detection algorithms, some conventional and some newly developed. We also discuss the weaknesses of our design and its possible improvements. The comparison with cloud detection algorithms developed for traditional nonpolarimetric full-sky imagers allowed us to evaluate the added value of polarimetric quantities. We found that (1) neural-network-based algorithms perform the best among the investigated schemes and (2) global information (the mean and variance of intensity), nonoptical information (e.g., sun-view geometry), and polarimetric information (e.g., the degree of polarization) improve the accuracy of cloud detection, albeit slightly.

  4. Termination Criteria for Computerized Classification Testing

    Directory of Open Access Journals (Sweden)

    Nathan A. Thompson

    2011-02-01

    Full Text Available Computerized classification testing (CCT is an approach to designing tests with intelligent algorithms, similar to adaptive testing, but specifically designed for the purpose of classifying examinees into categories such as - pass- and - fail.- Like adaptive testing for point estimation of ability, the key component is the termination criterion, namely the algorithm that decides whether to classify the examinee and end the test or to continue and administer another item. This paper applies a newly suggested termination criterion, the generalized likelihood ratio (GLR, to CCT. It also explores the role of the indifference region in the specification of likelihood-ratio based termination criteria, comparing the GLR to the sequential probability ratio test. Results from simulation studies suggest that the GLR is always at least as efficient as existing methods.

  5. 26 CFR 1.410(b)-4 - Nondiscriminatory classification test.

    Science.gov (United States)

    2010-04-01

    ..., nature of compensation (i.e., salaried or hourly), geographic location, and similar bona fide business... (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES Pension, Profit-Sharing, Stock Bonus Plans, Etc. § 1.410(b)-4 Nondiscriminatory classification test. (a) In general. A plan satisfies the nondiscriminatory classification test of...

  6. Adaptive testing for making unidimensional and multidimensional classification decisions

    NARCIS (Netherlands)

    van Groen, M.M.

    2014-01-01

    Computerized adaptive tests (CATs) were originally developed to obtain an efficient estimate of the examinee’s ability, but they can also be used to classify the examinee into one of two or more levels (e.g. master/non-master). These computerized classification tests have the advantage that they can

  7. A color based face detection system using multiple templates

    Institute of Scientific and Technical Information of China (English)

    王涛; 卜佳俊; 陈纯

    2003-01-01

    A color based system using multiple templates was developed and implemented for detecting human faces in color images. The algorithm consists of three image processing steps. The first step is human skin color statistics. Then it separates skin regions from non-skin regions. After that, it locates the frontal human face(s) within the skin regions. In the first step, 250 skin samples from persons of different ethnicities are used to determine the color distribution of human skin in chromatic color space in order to get a chroma chart showing likelihoods of skin colors. This chroma chart is used to generate, from the original color image, a gray scale image whose gray value at a pixel shows its likelihood of representing the skin. The algorithm uses an adaptive thresholding process to achieve the optimal threshold value for dividing the gray scale image into separate skin regions from non skin regions. Finally, multiple face templates matching is used to determine if a given skin region represents a frontal human face or not. Test of the system with more than 400 color images showed that the resulting detection rate was 83%, which is better than most color-based face detection systems. The average speed for face detection is 0.8 second/image (400×300 pixels) on a Pentium 3 (800MHz) PC.

  8. 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…

  9. Classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2017-01-01

    This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

  10. Classification of groundwater at the Nevada Test Site

    International Nuclear Information System (INIS)

    Chapman, J.B.

    1994-08-01

    Groundwater occurring at the Nevada Test Site (NTS) has been classified according to the ''Guidelines for Ground-Water Classification Under the US Environmental Protection Agency (EPA) Ground-Water Protection Strategy'' (June 1988). All of the groundwater units at the NTS are Class II, groundwater currently (IIA) or potentially (IIB) a source of drinking water. The Classification Review Area (CRA) for the NTS is defined as the standard two-mile distance from the facility boundary recommended by EPA. The possibility of expanding the CRA was evaluated, but the two-mile distance encompasses the area expected to be impacted by contaminant transport during a 10-year period (EPA,s suggested limit), should a release occur. The CRA is very large as a consequence of the large size of the NTS and the decision to classify the entire site, not individual areas of activity. Because most activities are located many miles hydraulically upgradient of the NTS boundary, the CRA generally provides much more than the usual two-mile buffer required by EPA. The CRA is considered sufficiently large to allow confident determination of the use and value of groundwater and identification of potentially affected users. The size and complex hydrogeology of the NTS are inconsistent with the EPA guideline assumption of a high degree of hydrologic interconnection throughout the review area. To more realistically depict the site hydrogeology, the CRA is subdivided into eight groundwater units. Two main aquifer systems are recognized: the lower carbonate aquifer system and the Cenozoic aquifer system (consisting of aquifers in Quaternary valley fill and Tertiary volcanics). These aquifer systems are further divided geographically based on the location of low permeability boundaries

  11. Nonparametric Bayes Classification and Hypothesis Testing on Manifolds

    Science.gov (United States)

    Bhattacharya, Abhishek; Dunson, David

    2012-01-01

    Our first focus is prediction of a categorical response variable using features that lie on a general manifold. For example, the manifold may correspond to the surface of a hypersphere. We propose a general kernel mixture model for the joint distribution of the response and predictors, with the kernel expressed in product form and dependence induced through the unknown mixing measure. We provide simple sufficient conditions for large support and weak and strong posterior consistency in estimating both the joint distribution of the response and predictors and the conditional distribution of the response. Focusing on a Dirichlet process prior for the mixing measure, these conditions hold using von Mises-Fisher kernels when the manifold is the unit hypersphere. In this case, Bayesian methods are developed for efficient posterior computation using slice sampling. Next we develop Bayesian nonparametric methods for testing whether there is a difference in distributions between groups of observations on the manifold having unknown densities. We prove consistency of the Bayes factor and develop efficient computational methods for its calculation. The proposed classification and testing methods are evaluated using simulation examples and applied to spherical data applications. PMID:22754028

  12. A color based face detection system using multiple templates

    Institute of Scientific and Technical Information of China (English)

    王涛; 卜佳酸; 陈纯

    2003-01-01

    A color based system using multiple templates was developed and implemented for detecting hu-man faces in color images.The algorithm comsists of three image processing steps.The first step is human skin color statistics.Then it separates skin regions from non-skin regions.After that,it locates the frontal human face(s) within the skin regions.In the first step,250 skin samples from persons of different ethnicities are used to determine the color distribution of human skin in chromatic color space in order to get a chroma chart showing likelihoods of skin colors.This chroma chart is used to generate,from the original color image,a gray scale image whose gray value at a pixel shows its likelihood of representing the shin,The algorithm uses an adaptive thresholding process to achieve the optimal threshold value for dividing the gray scale image into sep-arate skin regions from non skin regions.Finally,multiple face templates matching is used to determine if a given skin region represents a frontal human face or not.Test of the system with more than 400 color images showed that the resulting detection rate was 83%,which is better than most colou-based face detection sys-tems.The average speed for face detection is 0.8 second/image(400×300pixels) on a Pentium 3(800MHz) PC.

  13. A Comparison of Computer-Based Classification Testing Approaches Using Mixed-Format Tests with the Generalized Partial Credit Model

    Science.gov (United States)

    Kim, Jiseon

    2010-01-01

    Classification testing has been widely used to make categorical decisions by determining whether an examinee has a certain degree of ability required by established standards. As computer technologies have developed, classification testing has become more computerized. Several approaches have been proposed and investigated in the context of…

  14. Green colorants based on energetic azole borates.

    Science.gov (United States)

    Glück, Johann; Klapötke, Thomas M; Rusan, Magdalena; Stierstorfer, Jörg

    2014-11-24

    The investigation of green-burning boron-based compounds as colorants in pyrotechnic formulations as alternative for barium nitrate, which is a hazard to health and to the environment, is reported. Metal-free and nitrogen-rich dihydrobis(5-aminotetrazolyl)borate salts and dihydrobis(1,3,4-triazolyl)borate salts have been synthesized and characterized by NMR spectroscopy, elemental analysis, mass spectrometry, and vibrational spectroscopy. Their thermal and energetic properties have been determined as well. Several pyrotechnic compositions using selected azolyl borate salts as green colorants were investigated. Formulations with ammonium dinitramide and ammonium nitrate as oxidizers and boron and magnesium as fuels were tested. The burn time, dominant wavelength, spectral purity, luminous intensity, and luminous efficiency as well as the thermal and energetic properties of these compositions were measured. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Test-Enhanced Learning of Natural Concepts: Effects on Recognition Memory, Classification, and Metacognition

    Science.gov (United States)

    Jacoby, Larry L.; Wahlheim, Christopher N.; Coane, Jennifer H.

    2010-01-01

    Three experiments examined testing effects on learning of natural concepts and metacognitive assessments of such learning. Results revealed that testing enhanced recognition memory and classification accuracy for studied and novel exemplars of bird families on immediate and delayed tests. These effects depended on the balance of study and test…

  16. Generalized classification of welds according to defect type based on raidation testing results

    International Nuclear Information System (INIS)

    Adamenko, A.A.; Demidko, V.G.

    1980-01-01

    Constructed is a generalized classification of welds according to defect type, with respect to real danger of defect, which in the first approximation is proportional to relatively decrease of the thickness, and with respect to defect potential danger which can be determined by its pointing. According to this classification the welded joints are divided into five classes according to COMECON guides. The division into classes is carried out according to two-fold numerical criterium which is applicable in case of the presence of experimental data on three defect linear sizes. The above classification is of main importance while automatic data processing of the radiation testing

  17. Integrated testing strategies can be optimal for chemical risk classification.

    Science.gov (United States)

    Raseta, Marko; Pitchford, Jon; Cussens, James; Doe, John

    2017-08-01

    There is an urgent need to refine strategies for testing the safety of chemical compounds. This need arises both from the financial and ethical costs of animal tests, but also from the opportunities presented by new in-vitro and in-silico alternatives. Here we explore the mathematical theory underpinning the formulation of optimal testing strategies in toxicology. We show how the costs and imprecisions of the various tests, and the variability in exposures and responses of individuals, can be assembled rationally to form a Markov Decision Problem. We compute the corresponding optimal policies using well developed theory based on Dynamic Programming, thereby identifying and overcoming some methodological and logical inconsistencies which may exist in the current toxicological testing. By illustrating our methods for two simple but readily generalisable examples we show how so-called integrated testing strategies, where information of different precisions from different sources is combined and where different initial test outcomes lead to different sets of future tests, can arise naturally as optimal policies. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Classification of solid industrial waste based on ecotoxicology tests using Daphnia magna: an alternative

    Directory of Open Access Journals (Sweden)

    William Gerson Matias

    2005-11-01

    Full Text Available The adequate treatment and final disposal of solid industrial wastes depends on their classification into class I or II. This classification is proposed by NBR 10.004; however, it is complex and time-consuming. With a view to facilitating this classification, the use of assays with Daphnia magna is proposed. These assays make possible the identification of toxic chemicals in the leach, which denotes the presence of one of the characteristics described by NBR 10.004, the toxicity, which is a sufficient argument to put the waste into class I. Ecotoxicological tests were carried out with ten samples of solid wastes of frequent production and, on the basis of the results from EC(I50/48h of those samples in comparison with the official classification of NBR 10.004, limits were established for the classification of wastes into class I or II. A coincidence in the classification of 50% of the analyzed samples was observed. In cases in which there is no coherence between the methods, the method proposed in this work classifies the waste into class I. These data are preliminary, but they reveal that the classification system proposed here is promising because of its quickness and economic viability.

  19. Determination of the impact of RGB points cloud attribute quality on color-based segmentation process

    Directory of Open Access Journals (Sweden)

    Bartłomiej Kraszewski

    2015-06-01

    Full Text Available The article presents the results of research on the effect that radiometric quality of point cloud RGB attributes have on color-based segmentation. In the research, a point cloud with a resolution of 5 mm, received from FAROARO Photon 120 scanner, described the fragment of an office’s room and color images were taken by various digital cameras. The images were acquired by SLR Nikon D3X, and SLR Canon D200 integrated with the laser scanner, compact camera Panasonic TZ-30 and a mobile phone digital camera. Color information from images was spatially related to point cloud in FAROARO Scene software. The color-based segmentation of testing data was performed with the use of a developed application named “RGB Segmentation”. The application was based on public Point Cloud Libraries (PCL and allowed to extract subsets of points fulfilling the criteria of segmentation from the source point cloud using region growing method.Using the developed application, the segmentation of four tested point clouds containing different RGB attributes from various images was performed. Evaluation of segmentation process was performed based on comparison of segments acquired using the developed application and extracted manually by an operator. The following items were compared: the number of obtained segments, the number of correctly identified objects and the correctness of segmentation process. The best correctness of segmentation and most identified objects were obtained using the data with RGB attribute from Nikon D3X images. Based on the results it was found that quality of RGB attributes of point cloud had impact only on the number of identified objects. In case of correctness of the segmentation, as well as its error no apparent relationship between the quality of color information and the result of the process was found.[b]Keywords[/b]: terrestrial laser scanning, color-based segmentation, RGB attribute, region growing method, digital images, points cloud

  20. Classification of chronic orofacial pain using an intravenous diagnostic test

    NARCIS (Netherlands)

    Tjakkes, G. -H. E.; De Bont, L. G. M.; van Wijhe, M.; Stegenga, B.

    The aim of this study was to evaluate the ability of a preliminary intravenous diagnostic test to classify chronic orofacial pain patients into different subgroups. Patients with chronic orofacial pain conditions that could not be unambiguously diagnosed. A retrospective evaluation of series of

  1. Screening tests for hazard classification of complex waste materials – Selection of methods

    International Nuclear Information System (INIS)

    Weltens, R.; Vanermen, G.; Tirez, K.; Robbens, J.; Deprez, K.; Michiels, L.

    2012-01-01

    In this study we describe the development of an alternative methodology for hazard characterization of waste materials. Such an alternative methodology for hazard assessment of complex waste materials is urgently needed, because the lack of a validated instrument leads to arbitrary hazard classification of such complex waste materials. False classification can lead to human and environmental health risks and also has important financial consequences for the waste owner. The Hazardous Waste Directive (HWD) describes the methodology for hazard classification of waste materials. For mirror entries the HWD classification is based upon the hazardous properties (H1–15) of the waste which can be assessed from the hazardous properties of individual identified waste compounds or – if not all compounds are identified – from test results of hazard assessment tests performed on the waste material itself. For the latter the HWD recommends toxicity tests that were initially designed for risk assessment of chemicals in consumer products (pharmaceuticals, cosmetics, biocides, food, etc.). These tests (often using mammals) are not designed nor suitable for the hazard characterization of waste materials. With the present study we want to contribute to the development of an alternative and transparent test strategy for hazard assessment of complex wastes that is in line with the HWD principles for waste classification. It is necessary to cope with this important shortcoming in hazardous waste classification and to demonstrate that alternative methods are available that can be used for hazard assessment of waste materials. Next, by describing the pros and cons of the available methods, and by identifying the needs for additional or further development of test methods, we hope to stimulate research efforts and development in this direction. In this paper we describe promising techniques and argument on the test selection for the pilot study that we have performed on different

  2. Applied Chaos Level Test for Validation of Signal Conditions Underlying Optimal Performance of Voice Classification Methods

    Science.gov (United States)

    Liu, Boquan; Polce, Evan; Sprott, Julien C.; Jiang, Jack J.

    2018-01-01

    Purpose: The purpose of this study is to introduce a chaos level test to evaluate linear and nonlinear voice type classification method performances under varying signal chaos conditions without subjective impression. Study Design: Voice signals were constructed with differing degrees of noise to model signal chaos. Within each noise power, 100…

  3. TESTING OF LAND COVER CLASSIFICATION FROM MULTISPECTRAL AIRBORNE LASER SCANNING DATA

    Directory of Open Access Journals (Sweden)

    K. Bakuła

    2016-06-01

    Full Text Available Multispectral Airborne Laser Scanning provides a new opportunity for airborne data collection. It provides high-density topographic surveying and is also a useful tool for land cover mapping. Use of a minimum of three intensity images from a multiwavelength laser scanner and 3D information included in the digital surface model has the potential for land cover/use classification and a discussion about the application of this type of data in land cover/use mapping has recently begun. In the test study, three laser reflectance intensity images (orthogonalized point cloud acquired in green, near-infrared and short-wave infrared bands, together with a digital surface model, were used in land cover/use classification where six classes were distinguished: water, sand and gravel, concrete and asphalt, low vegetation, trees and buildings. In the tested methods, different approaches for classification were applied: spectral (based only on laser reflectance intensity images, spectral with elevation data as additional input data, and spectro-textural, using morphological granulometry as a method of texture analysis of both types of data: spectral images and the digital surface model. The method of generating the intensity raster was also tested in the experiment. Reference data were created based on visual interpretation of ALS data and traditional optical aerial and satellite images. The results have shown that multispectral ALS data are unlike typical multispectral optical images, and they have a major potential for land cover/use classification. An overall accuracy of classification over 90% was achieved. The fusion of multi-wavelength laser intensity images and elevation data, with the additional use of textural information derived from granulometric analysis of images, helped to improve the accuracy of classification significantly. The method of interpolation for the intensity raster was not very helpful, and using intensity rasters with both first and

  4. Estimated accuracy of classification of defects detected in welded joints by radiographic tests

    International Nuclear Information System (INIS)

    Siqueira, M.H.S.; De Silva, R.R.; De Souza, M.P.V.; Rebello, J.M.A.; Caloba, L.P.; Mery, D.

    2004-01-01

    This work is a study to estimate the accuracy of classification of the main classes of weld defects detected by radiography test, such as: undercut, lack of penetration, porosity, slag inclusion, crack or lack of fusion. To carry out this work non-linear pattern classifiers were developed, using neural networks, and the largest number of radiographic patterns as possible was used as well as statistical inference techniques of random selection of samples with and without repositioning (bootstrap) in order to estimate the accuracy of the classification. The results pointed to an estimated accuracy of around 80% for the classes of defects analyzed. (author)

  5. Estimated accuracy of classification of defects detected in welded joints by radiographic tests

    Energy Technology Data Exchange (ETDEWEB)

    Siqueira, M.H.S.; De Silva, R.R.; De Souza, M.P.V.; Rebello, J.M.A. [Federal Univ. of Rio de Janeiro, Dept., of Metallurgical and Materials Engineering, Rio de Janeiro (Brazil); Caloba, L.P. [Federal Univ. of Rio de Janeiro, Dept., of Electrical Engineering, Rio de Janeiro (Brazil); Mery, D. [Pontificia Unversidad Catolica de Chile, Escuela de Ingenieria - DCC, Dept. de Ciencia de la Computacion, Casilla, Santiago (Chile)

    2004-07-01

    This work is a study to estimate the accuracy of classification of the main classes of weld defects detected by radiography test, such as: undercut, lack of penetration, porosity, slag inclusion, crack or lack of fusion. To carry out this work non-linear pattern classifiers were developed, using neural networks, and the largest number of radiographic patterns as possible was used as well as statistical inference techniques of random selection of samples with and without repositioning (bootstrap) in order to estimate the accuracy of the classification. The results pointed to an estimated accuracy of around 80% for the classes of defects analyzed. (author)

  6. A simple subcritical chromatographic test for an extended ODS high performance liquid chromatography column classification.

    Science.gov (United States)

    Lesellier, Eric; Tchapla, Alain

    2005-12-23

    This paper describes a new test designed in subcritical fluid chromatography (SFC) to compare the commercial C18 stationary phase properties. This test provides, from a single analysis of carotenoid pigments, the absolute hydrophobicity, the silanol activity and the steric separation factor of the ODS stationary phases. Both the choice of the analytical conditions and the validation of the information obtained from the chromatographic measurements are detailed. Correlations of the carotenoid test results with results obtained from other tests (Tanaka, Engelhard, Sander and Wise) performed both in SFC and HPLC are discussed. Two separation factors, calculated from the retention of carotenoid pigments used as probe, allowed to draw a first classification diagram. Columns, which present identical chromatographic behaviors are located in the same area on this diagram. This location can be related to the stationary phase properties: endcapping treatments, bonding density, linkage functionality, specific area or silica pore diameter. From the first classification, eight groups of columns are distinguished. One group of polymer coated silica, three groups of polymeric octadecyl phases, depending on the pore size and the endcapping treatment, and four groups of monomeric stationary phases. An additional classification of the four monomeric groups allows the comparison of these stationary phases inside each group by using the total hydrophobicity. One hundred and twenty-nine columns were analysed by this simple and rapid test, which allows a comparison of columns with the aim of helping along their choice in HPLC.

  7. Testing the Potential of Vegetation Indices for Land Use/cover Classification Using High Resolution Data

    Science.gov (United States)

    Karakacan Kuzucu, A.; Bektas Balcik, F.

    2017-11-01

    Accurate and reliable land use/land cover (LULC) information obtained by remote sensing technology is necessary in many applications such as environmental monitoring, agricultural management, urban planning, hydrological applications, soil management, vegetation condition study and suitability analysis. But this information still remains a challenge especially in heterogeneous landscapes covering urban and rural areas due to spectrally similar LULC features. In parallel with technological developments, supplementary data such as satellite-derived spectral indices have begun to be used as additional bands in classification to produce data with high accuracy. The aim of this research is to test the potential of spectral vegetation indices combination with supervised classification methods and to extract reliable LULC information from SPOT 7 multispectral imagery. The Normalized Difference Vegetation Index (NDVI), the Ratio Vegetation Index (RATIO), the Soil Adjusted Vegetation Index (SAVI) were the three vegetation indices used in this study. The classical maximum likelihood classifier (MLC) and support vector machine (SVM) algorithm were applied to classify SPOT 7 image. Catalca is selected region located in the north west of the Istanbul in Turkey, which has complex landscape covering artificial surface, forest and natural area, agricultural field, quarry/mining area, pasture/scrubland and water body. Accuracy assessment of all classified images was performed through overall accuracy and kappa coefficient. The results indicated that the incorporation of these three different vegetation indices decrease the classification accuracy for the MLC and SVM classification. In addition, the maximum likelihood classification slightly outperformed the support vector machine classification approach in both overall accuracy and kappa statistics.

  8. SB certification handout material requirements, test methods, responsibilities, and minimum classification levels for mixture-based specification for flexible base.

    Science.gov (United States)

    2012-10-01

    A handout with tables representing the material requirements, test methods, responsibilities, and minimum classification levels mixture-based specification for flexible base and details on aggregate and test methods employed, along with agency and co...

  9. Development and content validity testing of a comprehensive classification of diagnoses for pediatric nurse practitioners.

    Science.gov (United States)

    Burns, C

    1991-01-01

    Pediatric nurse practitioners (PNPs) need an integrated, comprehensive classification that includes nursing, disease, and developmental diagnoses to effectively describe their practice. No such classification exists. Further, methodologic studies to help evaluate the content validity of any nursing taxonomy are unavailable. A conceptual framework was derived. Then 178 diagnoses from the North American Nursing Diagnosis Association (NANDA) 1986 list, selected diagnoses from the International Classification of Diseases, the Diagnostic and Statistical Manual, Third Revision, and others were selected. This framework identified and listed, with definitions, three domains of diagnoses: Developmental Problems, Diseases, and Daily Living Problems. The diagnoses were ranked using a 4-point scale (4 = highly related to 1 = not related) and were placed into the three domains. The rating scale was assigned by a panel of eight expert pediatric nurses. Diagnoses that were assigned to the Daily Living Problems domain were then sorted into the 11 Functional Health patterns described by Gordon (1987). Reliability was measured using proportions of agreement and Kappas. Content validity of the groups created was measured using indices of content validity and average congruency percentages. The experts used a new method to sort the diagnoses in a new way that decreased overlaps among the domains. The Developmental and Disease domains were judged reliable and valid. The Daily Living domain of nursing diagnoses showed marginally acceptable validity with acceptable reliability. Six Functional Health Patterns were judged reliable and valid, mixed results were determined for four categories, and the Coping/Stress Tolerance category was judged reliable but not valid using either test. There were considerable differences between the panel's, Gordon's (1987), and NANDA's clustering of NANDA diagnoses. This study defines the diagnostic practice of nurses from a holistic, patient

  10. Development and application of test apparatus for classification of sealed source

    International Nuclear Information System (INIS)

    Kim, Dong Hak; Seo, Ki Seog; Bang, Kyoung Sik; Lee, Ju Chan; Son, Kwang Je

    2007-01-01

    Sealed sources have to conducted the tests be done according to the classification requirements for their typical usages in accordance with the relevant domestic notice standard and ISO 2919. After each test, the source shall be examined visually for loss of integrity and pass an appropriate leakage test. Tests to class a sealed source are temperature, external pressure, impact, vibration and puncture test. The environmental test conditions for tests with class numbers are arranged in increasing order of severity. In this study, the apparatus of tests, except the vibration test, were developed and applied to three kinds of sealed source. The conditions of the tests to class a sealed source were stated and the difference between the domestic notice standard and ISO 2919 were considered. And apparatus of the tests were made. Using developed apparatus we conducted the test for 192 Ir brachytherapy sealed source and two kinds of sealed source for industrial radiography. 192 Ir brachytherapy sealed source is classified by temperature class 5, external pressure class 3, impact class 2 and vibration and puncture class 1. Two kinds of sealed source for industrial radiography are classified by temperature class 4, external pressure class 2, impact and puncture class 5 and vibration class 1. After the tests, Liquid nitrogen bubble test and vacuum bubble test were done to evaluate the safety of the sealed sources

  11. Medical Devices; Clinical Chemistry and Clinical Toxicology Devices; Classification of the Organophosphate Test System. Final order.

    Science.gov (United States)

    2017-10-18

    The Food and Drug Administration (FDA or we) is classifying the organophosphate test system into class II (special controls). The special controls that apply to the device type are identified in this order and will be part of the codified language for the organophosphate test system's classification. We are taking this action because we have determined that classifying the device into class II (special controls) will provide a reasonable assurance of safety and effectiveness of the device. We believe this action will also enhance patients' access to beneficial innovative devices, in part by reducing regulatory burdens.

  12. Medical Devices; Hematology and Pathology Devices; Classification of a Cervical Intraepithelial Neoplasia Test System. Final order.

    Science.gov (United States)

    2018-01-03

    The Food and Drug Administration (FDA or we) is classifying the cervical intraepithelial neoplasia (CIN) test system into class II (special controls). The special controls that apply to the device type are identified in this order and will be part of the codified language for the CIN test system's classification. We are taking this action because we have determined that classifying the device into class II (special controls) will provide a reasonable assurance of safety and effectiveness of the device. We believe this action will also enhance patients' access to beneficial innovative devices, in part by reducing regulatory burdens.

  13. The Functional Classification and Field Test Performance in Wheelchair Basketball Players.

    Science.gov (United States)

    Gil, Susana María; Yanci, Javier; Otero, Montserrat; Olasagasti, Jurgi; Badiola, Aduna; Bidaurrazaga-Letona, Iraia; Iturricastillo, Aitor; Granados, Cristina

    2015-06-27

    Wheelchair basketball players are classified in four classes based on the International Wheelchair Basketball Federation (IWBF) system of competition. Thus, the aim of the study was to ascertain if the IWBF classification, the type of injury and the wheelchair experience were related to different performance field-based tests. Thirteen basketball players undertook anthropometric measurements and performance tests (hand dynamometry, 5 m and 20 m sprints, 5 m and 20 m sprints with a ball, a T-test, a Pick-up test, a modified 10 m Yo-Yo intermittent recovery test, a maximal pass and a medicine ball throw). The IWBF class was correlated (pstaff and coaches of the teams when assessing performance of wheelchair basketball players.

  14. A risk-based classification scheme for genetically modified foods. II: Graded testing.

    Science.gov (United States)

    Chao, Eunice; Krewski, Daniel

    2008-12-01

    This paper presents a graded approach to the testing of crop-derived genetically modified (GM) foods based on concern levels in a proposed risk-based classification scheme (RBCS) and currently available testing methods. A graded approach offers the potential for more efficient use of testing resources by focusing less on lower concern GM foods, and more on higher concern foods. In this proposed approach to graded testing, products that are classified as Level I would have met baseline testing requirements that are comparable to what is widely applied to premarket assessment of GM foods at present. In most cases, Level I products would require no further testing, or very limited confirmatory analyses. For products classified as Level II or higher, additional testing would be required, depending on the type of the substance, prior dietary history, estimated exposure level, prior knowledge of toxicity of the substance, and the nature of the concern related to unintended changes in the modified food. Level III testing applies only to the assessment of toxic and antinutritional effects from intended changes and is tailored to the nature of the substance in question. Since appropriate test methods are not currently available for all effects of concern, future research to strengthen the testing of GM foods is discussed.

  15. Neuropsychological Test Selection for Cognitive Impairment Classification: A Machine Learning Approach

    Science.gov (United States)

    Williams, Jennifer A.; Schmitter-Edgecombe, Maureen; Cook, Diane J.

    2016-01-01

    Introduction Reducing the amount of testing required to accurately detect cognitive impairment is clinically relevant. The aim of this research was to determine the fewest number of clinical measures required to accurately classify participants as healthy older adult, mild cognitive impairment (MCI) or dementia using a suite of classification techniques. Methods Two variable selection machine learning models (i.e., naive Bayes, decision tree), a logistic regression, and two participant datasets (i.e., clinical diagnosis, clinical dementia rating; CDR) were explored. Participants classified using clinical diagnosis criteria included 52 individuals with dementia, 97 with MCI, and 161 cognitively healthy older adults. Participants classified using CDR included 154 individuals CDR = 0, 93 individuals with CDR = 0.5, and 25 individuals with CDR = 1.0+. Twenty-seven demographic, psychological, and neuropsychological variables were available for variable selection. Results No significant difference was observed between naive Bayes, decision tree, and logistic regression models for classification of both clinical diagnosis and CDR datasets. Participant classification (70.0 – 99.1%), geometric mean (60.9 – 98.1%), sensitivity (44.2 – 100%), and specificity (52.7 – 100%) were generally satisfactory. Unsurprisingly, the MCI/CDR = 0.5 participant group was the most challenging to classify. Through variable selection only 2 – 9 variables were required for classification and varied between datasets in a clinically meaningful way. Conclusions The current study results reveal that machine learning techniques can accurately classifying cognitive impairment and reduce the number of measures required for diagnosis. PMID:26332171

  16. On the classification of structures, systems and components of nuclear research and test reactors

    International Nuclear Information System (INIS)

    Mattar Neto, Miguel

    2009-01-01

    The classification of structures, systems and components of nuclear reactors is a relevant issue related to their design because it is directly associated with their safety functions. There is an important statement regarding quality standards and records that says Structures, systems, and components important to safety shall be designed, fabricated, erected, and tested to quality standards commensurate with the importance of the safety functions to be performed. The definition of the codes, standards and technical requirements applied to the nuclear reactor design, fabrication, inspection and tests may be seen as the main result from this statement. There are well established guides to classify structures, systems and components for nuclear power reactors such as the Pressurized Water Reactors but one can not say the same for nuclear research and test reactors. The nuclear reactors safety functions are those required to the safe reactor operation, the safe reactor shutdown and continued safe conditions, the response to anticipated transients, the response to potential accidents and the control of radioactive material. So, it is proposed in this paper an approach to develop the classification of structures, systems and components of these reactors based on their intended safety functions in order to define the applicable set of codes, standards and technical requirements. (author)

  17. Classification of user performance in the Ruff Figural Fluency Test based on eye-tracking features

    Directory of Open Access Journals (Sweden)

    Borys Magdalena

    2017-01-01

    Full Text Available Cognitive assessment in neurological diseases represents a relevant topic due to its diagnostic significance in detecting disease, but also in assessing progress of the treatment. Computer-based tests provide objective and accurate cognitive skills and capacity measures. The Ruff Figural Fluency Test (RFFT provides information about non-verbal capacity for initiation, planning, and divergent reasoning. The traditional paper form of the test was transformed into a computer application and examined. The RFFT was applied in an experiment performed among 70 male students to assess their cognitive performance in the laboratory environment. Each student was examined in three sequential series. Besides the students’ performances measured by using in app keylogging, the eye-tracking data obtained by non-invasive video-based oculography were gathered, from which several features were extracted. Eye-tracking features combined with performance measures (a total number of designs and/or error ratio were applied in machine learning classification. Various classification algorithms were applied, and their accuracy, specificity, sensitivity and performance were compared.

  18. SOFTWARE IMPLEMENTATION OF FORMING OF COLOR-BASED CARDS FOR ASSESSMENT OF EARLY STAGES INNOVATION PROJECTS

    Directory of Open Access Journals (Sweden)

    Ekaterina I. Bragina

    2015-01-01

    Full Text Available The article deals with functional program that allows to generate a visualrepresentation of the shareholder tothe innovative project early stage ofdevelopment, formed a color-based cards.

  19. Utility of Intelligence Tests for Treatment Planning, Classification, and Placement Decisions: Recent Empirical Findings and Future Directions.

    Science.gov (United States)

    Gresham, Frank M.; Witt, Joseph C.

    1997-01-01

    Maintains that intelligence tests contribute little to the planning, implementation, and evaluation of instructional interventions for children. Suggests that intelligence tests are not useful in making differential diagnostic and classification determinations for children with mild learning problems and that such testing is not a cost-beneficial…

  20. Ancillary testing, diagnostic/classification criteria and severity grading in Behçet disease.

    Science.gov (United States)

    Okada, Annabelle A; Stanford, Miles; Tabbara, Khalid

    2012-12-01

    Since there is no pathognomonic clinical sign or laboratory test to distinguish Behçet disease from other uveitic entities, the diagnosis must be made based on characteristic ocular and systemic findings in the absence of evidence of other disease that can explain the findings. Ancillary tests, including ocular and brain imaging studies, are used to assess the severity of intraocular inflammation and systemic manifestations of Behçet disease, to identify latent infections and other medical conditions that might worsen with systemic treatment, and to monitor for adverse effects of drugs used. There are two diagnostic or classification criteria in general use by the uveitis community, one from Japan and one from an international group; both rely on a minimum number and/or combination of clinical findings to identify Behçet disease. Finally, several grading schemes have been proposed to assess severity of ocular disease and response to treatment.

  1. Classification by a neural network approach applied to non destructive testing

    International Nuclear Information System (INIS)

    Lefevre, M.; Preteux, F.; Lavayssiere, B.

    1995-01-01

    Radiography is used by EDF for pipe inspection in nuclear power plants in order to detect defects. The radiographs obtained are then digitized in a well-defined protocol. The aim of EDF consists of developing a non destructive testing system for recognizing defects. In this paper, we describe the recognition procedure of areas with defects. We first present the digitization protocol, specifies the poor quality of images under study and propose a procedure to enhance defects. We then examine the problem raised by the choice of good features for classification. After having proved that statistical or standard textural features such as homogeneity, entropy or contrast are not relevant, we develop a geometrical-statistical approach based on the cooperation between signal correlations study and regional extrema analysis. The principle consists of analysing and comparing for areas with defects and without any defect, the evolution of conditional probabilities matrices for increasing neighborhood sizes, the shape of variograms and the location of regional minima. We demonstrate that anisotropy and surface of series of 'comet tails' associated with probability matrices, variograms slope and statistical indices, regional extrema location, are features able to discriminate areas with defects from areas without any. The classification is then realized by a neural network, which structure, properties and learning mechanisms are detailed. Finally we discuss the results. (authors). 21 refs., 5 figs

  2. Hazard classification for the supercritical water oxidation test bed. Revision 1

    International Nuclear Information System (INIS)

    Ramos, A.G.

    1994-10-01

    A hazard classification of ''routinely accepted by the public'' has been determined for the operation of the supercritical water oxidation test bed at the Idaho National Engineering Laboratory. This determination is based on the fact that the design and proposed operation meet or exceed appropriate national standards so that the risks are equivalent to those present in similar activities conducted in private industry. Each of the 17 criteria for hazards ''routinely accepted by the public,'' identified in the EG and G Idaho, Inc., Safety Manual, were analyzed. The supercritical water oxidation (SCWO) test bed will treat simulated mixed waste without the radioactive component. It will be designed to operate with eight test wastes. These test wastes have been chosen to represent a broad cross-section of candidate mixed wastes anticipated for storage or generation by DOE. In particular, the test bed will generate data to evaluate the ability of the technology to treat chlorinated waste and other wastes that have in the past caused severe corrosion and deposition in SCWO reactors

  3. Correlation of the New York Heart Association classification and the cardiopulmonary exercise test: A systematic review.

    Science.gov (United States)

    Lim, Fang Yi; Yap, Jonathan; Gao, Fei; Teo, Ling Li; Lam, Carolyn S P; Yeo, Khung Keong

    2018-07-15

    The New York Heart Association (NYHA) classification is frequently used in the management of heart failure but may be limited by patient and physician subjectivity. Cardiopulmonary exercise testing (CPET) provides a potentially more objective measurement of functional status. We aim to study the correlation between NYHA classification and peak oxygen consumption (pVO 2 ) on Cardiopulmonary Exercise Testing (CPET) within and across published studies. A systematic literature review on all studies reporting both NYHA class and CPET data was performed, and pVO 2 from CPET was correlated to reported NYHA class within and across eligible studies. 38 studies involving 2645 patients were eligible. Heterogenity was assessed by the Q statistic, which is a χ2 test and marker of systematic differences between studies. Within each NYHA class, significant heterogeneity in pVO 2 was seen across studies: NYHA I (n = 17, Q = 486.7, p < 0.0001), II (n = 24, Q = 381.0, p < 0.0001), III (n = 32, Q = 761.3, p < 0.0001) and IV (n = 5, Q = 12.8, p = 0.012). Significant differences in mean pVO 2 were observed between NYHA I and II (23.8 vs 17.6 mL/(kg·min), p < 0.0001) and II and III (17.6 vs 13.3 mL/(kg·min), p < 0.0001); but not between NYHA III and IV (13.3 vs 12.5 mL/(kg·min), p = 0.45). These differences remained significant after adjusting for age, gender, ejection fraction and region of study. There was a general inverse correlation between NYHA class and pVO 2. However, significant heterogeneity in pVO 2 exists across studies within each NYHA class. While the NYHA classification holds clinical value in heart failure management, direct comparison across studies may have its limitations. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. Application of FT-IR Classification Method in Silica-Plant Extracts Composites Quality Testing

    Science.gov (United States)

    Bicu, A.; Drumea, V.; Mihaiescu, D. E.; Purcareanu, B.; Florea, M. A.; Trică, B.; Vasilievici, G.; Draga, S.; Buse, E.; Olariu, L.

    2018-06-01

    Our present work is concerned with the validation and quality testing efforts of mesoporous silica - plant extracts composites, in order to sustain the standardization process of plant-based pharmaceutical products. The synthesis of the silica support were performed by using a TEOS based synthetic route and CTAB as a template, at room temperature and normal pressure. The silica support was analyzed by advanced characterization methods (SEM, TEM, BET, DLS and FT-IR), and loaded with Calendula officinalis and Salvia officinalis standardized extracts. Further desorption studies were performed in order to prove the sustained release properties of the final materials. Intermediate and final product identification was performed by a FT-IR classification method, using the MID-range of the IR spectra, and statistical representative samples from repetitive synthetic stages. The obtained results recommend this analytical method as a fast and cost effective alternative to the classic identification methods.

  5. Explaining Support Vector Machines: A Color Based Nomogram.

    Directory of Open Access Journals (Sweden)

    Vanya Van Belle

    Full Text Available Support vector machines (SVMs are very popular tools for classification, regression and other problems. Due to the large choice of kernels they can be applied with, a large variety of data can be analysed using these tools. Machine learning thanks its popularity to the good performance of the resulting models. However, interpreting the models is far from obvious, especially when non-linear kernels are used. Hence, the methods are used as black boxes. As a consequence, the use of SVMs is less supported in areas where interpretability is important and where people are held responsible for the decisions made by models.In this work, we investigate whether SVMs using linear, polynomial and RBF kernels can be explained such that interpretations for model-based decisions can be provided. We further indicate when SVMs can be explained and in which situations interpretation of SVMs is (hitherto not possible. Here, explainability is defined as the ability to produce the final decision based on a sum of contributions which depend on one single or at most two input variables.Our experiments on simulated and real-life data show that explainability of an SVM depends on the chosen parameter values (degree of polynomial kernel, width of RBF kernel and regularization constant. When several combinations of parameter values yield the same cross-validation performance, combinations with a lower polynomial degree or a larger kernel width have a higher chance of being explainable.This work summarizes SVM classifiers obtained with linear, polynomial and RBF kernels in a single plot. Linear and polynomial kernels up to the second degree are represented exactly. For other kernels an indication of the reliability of the approximation is presented. The complete methodology is available as an R package and two apps and a movie are provided to illustrate the possibilities offered by the method.

  6. Falls classification using tri-axial accelerometers during the five-times-sit-to-stand test.

    Science.gov (United States)

    Doheny, Emer P; Walsh, Cathal; Foran, Timothy; Greene, Barry R; Fan, Chie Wei; Cunningham, Clodagh; Kenny, Rose Anne

    2013-09-01

    The five-times-sit-to-stand test (FTSS) is an established assessment of lower limb strength, balance dysfunction and falls risk. Clinically, the time taken to complete the task is recorded with longer times indicating increased falls risk. Quantifying the movement using tri-axial accelerometers may provide a more objective and potentially more accurate falls risk estimate. 39 older adults, 19 with a history of falls, performed four repetitions of the FTSS in their homes. A tri-axial accelerometer was attached to the lateral thigh and used to identify each sit-stand-sit phase and sit-stand and stand-sit transitions. A second tri-axial accelerometer, attached to the sternum, captured torso acceleration. The mean and variation of the root-mean-squared amplitude, jerk and spectral edge frequency of the acceleration during each section of the assessment were examined. The test-retest reliability of each feature was examined using intra-class correlation analysis, ICC(2,k). A model was developed to classify participants according to falls status. Only features with ICC>0.7 were considered during feature selection. Sequential forward feature selection within leave-one-out cross-validation resulted in a model including four reliable accelerometer-derived features, providing 74.4% classification accuracy, 80.0% specificity and 68.7% sensitivity. An alternative model using FTSS time alone resulted in significantly reduced classification performance. Results suggest that the described methodology could provide a robust and accurate falls risk assessment. Copyright © 2013 Elsevier B.V. All rights reserved.

  7. The Functional Classification and Field Test Performance in Wheelchair Basketball Players

    Directory of Open Access Journals (Sweden)

    Gil Susana María

    2015-06-01

    Full Text Available Wheelchair basketball players are classified in four classes based on the International Wheelchair Basketball Federation (IWBF system of competition. Thus, the aim of the study was to ascertain if the IWBF classification, the type of injury and the wheelchair experience were related to different performance field-based tests. Thirteen basketball players undertook anthropometric measurements and performance tests (hand dynamometry, 5 m and 20 m sprints, 5 m and 20 m sprints with a ball, a T-test, a Pick-up test, a modified 10 m Yo-Yo intermittent recovery test, a maximal pass and a medicine ball throw. The IWBF class was correlated (p<0.05 to the hand dynamometry (r= 0.84, the maximal pass (r=0.67 and the medicine ball throw (r= 0.67. Whereas the years of dependence on the wheelchair were correlated to the velocity (p<0.01: 5 m (r= −0.80 and 20 m (r= −0.77 and agility tests (r= −0.77, p<0.01. Also, the 20 m sprint with a ball (r= 0.68 and the T-test (r= −0.57 correlated (p<0.05 with the experience in playing wheelchair basketball. Therefore, in this team the correlations of the performance variables differed when they were related to the disability class, the years of dependence on the wheelchair and the experience in playing wheelchair basketball. These results should be taken into account by the technical staff and coaches of the teams when assessing performance of wheelchair basketball players.

  8. Comparison of accuracy of fibrosis degree classifications by liver biopsy and non-invasive tests in chronic hepatitis C.

    Science.gov (United States)

    Boursier, Jérôme; Bertrais, Sandrine; Oberti, Frédéric; Gallois, Yves; Fouchard-Hubert, Isabelle; Rousselet, Marie-Christine; Zarski, Jean-Pierre; Calès, Paul

    2011-11-30

    Non-invasive tests have been constructed and evaluated mainly for binary diagnoses such as significant fibrosis. Recently, detailed fibrosis classifications for several non-invasive tests have been developed, but their accuracy has not been thoroughly evaluated in comparison to liver biopsy, especially in clinical practice and for Fibroscan. Therefore, the main aim of the present study was to evaluate the accuracy of detailed fibrosis classifications available for non-invasive tests and liver biopsy. The secondary aim was to validate these accuracies in independent populations. Four HCV populations provided 2,068 patients with liver biopsy, four different pathologist skill-levels and non-invasive tests. Results were expressed as percentages of correctly classified patients. In population #1 including 205 patients and comparing liver biopsy (reference: consensus reading by two experts) and blood tests, Metavir fibrosis (FM) stage accuracy was 64.4% in local pathologists vs. 82.2% (p blood tests, the discrepancy scores, taking into account the error magnitude, of detailed fibrosis classification were significantly different between FibroMeter2G (0.30 ± 0.55) and FibroMeter3G (0.14 ± 0.37, p blood tests and Fibroscan, accuracies of detailed fibrosis classification were, respectively: Fibrotest: 42.5% (33.5%), Fibroscan: 64.9% (50.7%), FibroMeter2G: 68.7% (68.2%), FibroMeter3G: 77.1% (83.4%), p fibrosis classification of the best-performing blood test outperforms liver biopsy read by a local pathologist, i.e., in clinical practice; however, the classification precision is apparently lesser. This detailed classification accuracy is much lower than that of significant fibrosis with Fibroscan and even Fibrotest but higher with FibroMeter3G. FibroMeter classification accuracy was significantly higher than those of other non-invasive tests. Finally, for hepatitis C evaluation in clinical practice, fibrosis degree can be evaluated using an accurate blood test.

  9. Swimming level classification of young school age children and their success in a long distance swimming test

    OpenAIRE

    Nováková, Martina

    2010-01-01

    Title: Swimming level classification of young school age children and their success in a long distance swimming test Work objectives: The outcome of our work is comparison and evaluation of the initial and final swimming lenght in a test of long distance swimming. This test is taken during one swimming course. Methodology: Data which were obtained by testing a certain group of people and were statistically processed, showed the swimming level and performance of the young school age children. ...

  10. Nuclear Power Plant Thermocouple Sensor-Fault Detection and Classification Using Deep Learning and Generalized Likelihood Ratio Test

    Science.gov (United States)

    Mandal, Shyamapada; Santhi, B.; Sridhar, S.; Vinolia, K.; Swaminathan, P.

    2017-06-01

    In this paper, an online fault detection and classification method is proposed for thermocouples used in nuclear power plants. In the proposed method, the fault data are detected by the classification method, which classifies the fault data from the normal data. Deep belief network (DBN), a technique for deep learning, is applied to classify the fault data. The DBN has a multilayer feature extraction scheme, which is highly sensitive to a small variation of data. Since the classification method is unable to detect the faulty sensor; therefore, a technique is proposed to identify the faulty sensor from the fault data. Finally, the composite statistical hypothesis test, namely generalized likelihood ratio test, is applied to compute the fault pattern of the faulty sensor signal based on the magnitude of the fault. The performance of the proposed method is validated by field data obtained from thermocouple sensors of the fast breeder test reactor.

  11. Column Selection for Biomedical Analysis Supported by Column Classification Based on Four Test Parameters.

    Science.gov (United States)

    Plenis, Alina; Rekowska, Natalia; Bączek, Tomasz

    2016-01-21

    This article focuses on correlating the column classification obtained from the method created at the Katholieke Universiteit Leuven (KUL), with the chromatographic resolution attained in biomedical separation. In the KUL system, each column is described with four parameters, which enables estimation of the FKUL value characterising similarity of those parameters to the selected reference stationary phase. Thus, a ranking list based on the FKUL value can be calculated for the chosen reference column, then correlated with the results of the column performance test. In this study, the column performance test was based on analysis of moclobemide and its two metabolites in human plasma by liquid chromatography (LC), using 18 columns. The comparative study was performed using traditional correlation of the FKUL values with the retention parameters of the analytes describing the column performance test. In order to deepen the comparative assessment of both data sets, factor analysis (FA) was also used. The obtained results indicated that the stationary phase classes, closely related according to the KUL method, yielded comparable separation for the target substances. Therefore, the column ranking system based on the FKUL-values could be considered supportive in the choice of the appropriate column for biomedical analysis.

  12. Genetic parameters for type classification of Nelore cattle on central performance tests at pasture in Brazil.

    Science.gov (United States)

    Lima, Paulo Ricardo Martins; Paiva, Samuel Rezende; Cobuci, Jaime Araujo; Braccini Neto, José; Machado, Carlos Henrique Cavallari; McManus, Concepta

    2013-10-01

    The objective of this study was to characterize Nelore cattle on central performance tests in pasture, ranked by the visual classification method EPMURAS (structure, precocity, muscle, navel, breed, posture, and sexual characteristics), and to estimate genetic and phenotypic correlations between these parameters, including visual as well as production traits (initial and final weight on test, weight gain, and weight corrected for 550 days). The information used in the study was obtained on 21,032 Nelore bulls which were participants in the central performance test at pasture of the Brazilian Association for Zebu Breeders (ABCZ). Heritabilities obtained were from 0.19 to 0.50. Phenotypic correlations were positive from 0.70 to 0.97 between the weight traits, from 0.65 to 0.74 between visual characteristics, and from 0.29 to 0.47 between visual characteristics and weight traits. The genetic correlations were positive ranging from 0.80 to 0.98 between the characteristics of structure, precocity and musculature, from 0.13 to 0.64 between the growth characteristics, and from 0.41 to 0.97 between visual scores and weight gains. Heritability and genetic correlations indicate that the use of visual scores, along with the selection for growth characteristics, can bring positive results in selection of beef cattle for rearing on pasture.

  13. Automated classification of Permanent Scatterers time-series based on statistical characterization tests

    Science.gov (United States)

    Berti, Matteo; Corsini, Alessandro; Franceschini, Silvia; Iannacone, Jean Pascal

    2013-04-01

    The application of space borne synthetic aperture radar interferometry has progressed, over the last two decades, from the pioneer use of single interferograms for analyzing changes on the earth's surface to the development of advanced multi-interferogram techniques to analyze any sort of natural phenomena which involves movements of the ground. The success of multi-interferograms techniques in the analysis of natural hazards such as landslides and subsidence is widely documented in the scientific literature and demonstrated by the consensus among the end-users. Despite the great potential of this technique, radar interpretation of slope movements is generally based on the sole analysis of average displacement velocities, while the information embraced in multi interferogram time series is often overlooked if not completely neglected. The underuse of PS time series is probably due to the detrimental effect of residual atmospheric errors, which make the PS time series characterized by erratic, irregular fluctuations often difficult to interpret, and also to the difficulty of performing a visual, supervised analysis of the time series for a large dataset. In this work is we present a procedure for automatic classification of PS time series based on a series of statistical characterization tests. The procedure allows to classify the time series into six distinctive target trends (0=uncorrelated; 1=linear; 2=quadratic; 3=bilinear; 4=discontinuous without constant velocity; 5=discontinuous with change in velocity) and retrieve for each trend a series of descriptive parameters which can be efficiently used to characterize the temporal changes of ground motion. The classification algorithms were developed and tested using an ENVISAT datasets available in the frame of EPRS-E project (Extraordinary Plan of Environmental Remote Sensing) of the Italian Ministry of Environment (track "Modena", Northern Apennines). This dataset was generated using standard processing, then the

  14. TEXT CLASSIFICATION USING NAIVE BAYES UPDATEABLE ALGORITHM IN SBMPTN TEST QUESTIONS

    Directory of Open Access Journals (Sweden)

    Ristu Saptono

    2017-01-01

    Full Text Available Document classification is a growing interest in the research of text mining. Classification can be done based on the topics, languages, and so on. This study was conducted to determine how Naive Bayes Updateable performs in classifying the SBMPTN exam questions based on its theme. Increment model of one classification algorithm often used in text classification Naive Bayes classifier has the ability to learn from new data introduces with the system even after the classifier has been produced with the existing data. Naive Bayes Classifier classifies the exam questions based on the theme of the field of study by analyzing keywords that appear on the exam questions. One of feature selection method DF-Thresholding is implemented for improving the classification performance. Evaluation of the classification with Naive Bayes classifier algorithm produces 84,61% accuracy.

  15. Spectral multi-energy CT texture analysis with machine learning for tissue classification: an investigation using classification of benign parotid tumours as a testing paradigm.

    Science.gov (United States)

    Al Ajmi, Eiman; Forghani, Behzad; Reinhold, Caroline; Bayat, Maryam; Forghani, Reza

    2018-06-01

    There is a rich amount of quantitative information in spectral datasets generated from dual-energy CT (DECT). In this study, we compare the performance of texture analysis performed on multi-energy datasets to that of virtual monochromatic images (VMIs) at 65 keV only, using classification of the two most common benign parotid neoplasms as a testing paradigm. Forty-two patients with pathologically proven Warthin tumour (n = 25) or pleomorphic adenoma (n = 17) were evaluated. Texture analysis was performed on VMIs ranging from 40 to 140 keV in 5-keV increments (multi-energy analysis) or 65-keV VMIs only, which is typically considered equivalent to single-energy CT. Random forest (RF) models were constructed for outcome prediction using separate randomly selected training and testing sets or the entire patient set. Using multi-energy texture analysis, tumour classification in the independent testing set had accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 92%, 86%, 100%, 100%, and 83%, compared to 75%, 57%, 100%, 100%, and 63%, respectively, for single-energy analysis. Multi-energy texture analysis demonstrates superior performance compared to single-energy texture analysis of VMIs at 65 keV for classification of benign parotid tumours. • We present and validate a paradigm for texture analysis of DECT scans. • Multi-energy dataset texture analysis is superior to single-energy dataset texture analysis. • DECT texture analysis has high accura\\cy for diagnosis of benign parotid tumours. • DECT texture analysis with machine learning can enhance non-invasive diagnostic tumour evaluation.

  16. Validity range of centrifuges for the regulation of nanomaterials: from classification to as-tested coronas

    Science.gov (United States)

    Wohlleben, Wendel

    2012-12-01

    Granulometry is the regulatory category where the differences between traditional materials and nanomaterials culminate. Reported herein is a careful validation of methods for the quantification of dispersability and size distribution in relevant media, and for the classification according to the EC nanodefinition recommendation. Suspension-based techniques can assess the nanodefinition only if the material in question is reasonably well dispersed. Using dispersed material of several chemical compositions (organic, metal, metal-oxide) as test cases we benchmark analytical ultracentrifugation (AUC), dynamic light scattering (DLS), hydrodynamic chromatography, nanoparticle tracking analysis (NTA) against the known content of bimodal suspensions in the commercially relevant range between 20 nm and a few microns. The results validate fractionating techniques, especially AUC, which successfully identifies any dispersed nanoparticle content from 14 to 99.9 nb% with less than 5 nb% deviation. In contrast, our screening casts severe doubt over the reliability of ensemble (scattering) techniques and highlights the potential of NTA to develop into a counting upgrade of DLS. The unique asset of centrifuges with interference, X-ray or absorption detectors—to quantify the dispersed solid content for each size interval from proteins over individualized nanoparticles up to agglomerates, while accounting for their loose packing—addresses also the adsorption/depletion of proteins and (de-)agglomeration of nanomaterials under cell culture conditions as tested for toxicological endpoints.

  17. Validity range of centrifuges for the regulation of nanomaterials: from classification to as-tested coronas

    International Nuclear Information System (INIS)

    Wohlleben, Wendel

    2012-01-01

    Granulometry is the regulatory category where the differences between traditional materials and nanomaterials culminate. Reported herein is a careful validation of methods for the quantification of dispersability and size distribution in relevant media, and for the classification according to the EC nanodefinition recommendation. Suspension-based techniques can assess the nanodefinition only if the material in question is reasonably well dispersed. Using dispersed material of several chemical compositions (organic, metal, metal-oxide) as test cases we benchmark analytical ultracentrifugation (AUC), dynamic light scattering (DLS), hydrodynamic chromatography, nanoparticle tracking analysis (NTA) against the known content of bimodal suspensions in the commercially relevant range between 20 nm and a few microns. The results validate fractionating techniques, especially AUC, which successfully identifies any dispersed nanoparticle content from 14 to 99.9 nb% with less than 5 nb% deviation. In contrast, our screening casts severe doubt over the reliability of ensemble (scattering) techniques and highlights the potential of NTA to develop into a counting upgrade of DLS. The unique asset of centrifuges with interference, X-ray or absorption detectors—to quantify the dispersed solid content for each size interval from proteins over individualized nanoparticles up to agglomerates, while accounting for their loose packing—addresses also the adsorption/depletion of proteins and (de-)agglomeration of nanomaterials under cell culture conditions as tested for toxicological endpoints.

  18. The Dysexecutive Questionnaire advanced: item and test score characteristics, 4-factor solution, and severity classification.

    Science.gov (United States)

    Bodenburg, Sebastian; Dopslaff, Nina

    2008-01-01

    The Dysexecutive Questionnaire (DEX, , Behavioral assessment of the dysexecutive syndrome, 1996) is a standardized instrument to measure possible behavioral changes as a result of the dysexecutive syndrome. Although initially intended only as a qualitative instrument, the DEX has also been used increasingly to address quantitative problems. Until now there have not been more fundamental statistical analyses of the questionnaire's testing quality. The present study is based on an unselected sample of 191 patients with acquired brain injury and reports on the data relating to the quality of the items, the reliability and the factorial structure of the DEX. Item 3 displayed too great an item difficulty, whereas item 11 was not sufficiently discriminating. The DEX's reliability in self-rating is r = 0.85. In addition to presenting the statistical values of the tests, a clinical severity classification of the overall scores of the 4 found factors and of the questionnaire as a whole is carried out on the basis of quartile standards.

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

    Science.gov (United States)

    Czajkowski, Marcin; Grześ, Marek; Kretowski, Marek

    2014-05-01

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

  20. Testing a bedside personal computer Clinical Care Classification System for nursing students using Microsoft Access.

    Science.gov (United States)

    Feeg, Veronica D; Saba, Virginia K; Feeg, Alan N

    2008-01-01

    This study tested a personal computer-based version of the Sabacare Clinical Care Classification System on students' performance of charting patient care plans. The application was designed as an inexpensive alternative to teach electronic charting for use on any laptop or personal computer with Windows and Microsoft Access. The data-based system was tested in a randomized trial with the control group using a type-in text-based-only system also mounted on a laptop at the bedside in the laboratory. Student care plans were more complete using the data-based system over the type-in text version. Students were more positive but not necessarily more efficient with the data-based system. The results demonstrate that the application is effective for improving student nursing care charting using the nursing process and capturing patient care information with a language that is standardized and ready for integration with other patient electronic health record data. It can be implemented on a bedside stand in the clinical laboratory or used to aggregate care planning over a student's clinical experience.

  1. Prognostic classification of MDS is improved by the inclusion of FISH panel testing with conventional cytogenetics.

    Science.gov (United States)

    Kokate, Prajakta; Dalvi, Rupa; Koppaka, Neeraja; Mandava, Swarna

    2017-10-01

    Cytogenetics is a critical independent prognostic factor in myelodysplastic syndromes (MDS). Conventional cytogenetics (CC) and Fluorescence in situ hybridization (FISH) Panel Testing are extensively used for the prognostic stratification of MDS, although the FISH test is not yet a bona fide component of the International Prognostic Scoring System (IPSS). The present study compares the utility of CC and FISH to detect chromosomal anomalies and in prognostic categorization. GTG-Banding and FISH Panel Testing specifically for -5/-5q, -7/-7q, +8 and -20q was performed on whole blood or bone marrow samples from 136 patients with MDS. Chromosomal anomalies were found in 40 cases by CC, including three novel translocations. FISH identified at least one anomaly in 54/136 (39.7%) cases. More than one anomaly was found in 18/54 (33.3%) cases, therefore, overall FISH identified 75 anomalies of which 32 (42.6%) were undetected by CC. FISH provided additional information in cases with CC failure and in cases with a normal karyotype. Further, in ten cases with an abnormal karyotype, FISH could identify additional anomalies, increasing the number of abnormalities per patient. Although CC is the gold standard in the cytogenetic profiling of MDS, FISH has proven to be an asset in identifying additional abnormalities. The number of anomalies per patient can predict the prognosis in MDS and hence, FISH contributed towards prognostic re-categorization. The FISH Panel testing should be used as an adjunct to CC, irrespective of the adequacy of the number of metaphases in CC, as it improves the prognostic classification of MDS. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Challenges to the Use of Artificial Neural Networks for Diagnostic Classifications with Student Test Data

    Science.gov (United States)

    Briggs, Derek C.; Circi, Ruhan

    2017-01-01

    Artificial Neural Networks (ANNs) have been proposed as a promising approach for the classification of students into different levels of a psychological attribute hierarchy. Unfortunately, because such classifications typically rely upon internally produced item response patterns that have not been externally validated, the instability of ANN…

  3. Scalable, ultra-resistant structural colors based on network metamaterials

    KAUST Repository

    Galinski, Henning

    2017-05-05

    Structural colors have drawn wide attention for their potential as a future printing technology for various applications, ranging from biomimetic tissues to adaptive camouflage materials. However, an efficient approach to realize robust colors with a scalable fabrication technique is still lacking, hampering the realization of practical applications with this platform. Here, we develop a new approach based on large-scale network metamaterials that combine dealloyed subwavelength structures at the nanoscale with lossless, ultra-thin dielectric coatings. By using theory and experiments, we show how subwavelength dielectric coatings control a mechanism of resonant light coupling with epsilon-near-zero regions generated in the metallic network, generating the formation of saturated structural colors that cover a wide portion of the spectrum. Ellipsometry measurements support the efficient observation of these colors, even at angles of 70°. The network-like architecture of these nanomaterials allows for high mechanical resistance, which is quantified in a series of nano-scratch tests. With such remarkable properties, these metastructures represent a robust design technology for real-world, large-scale commercial applications.

  4. Differences in physical-fitness test scores between actively and passively recruited older adults : Consequences for norm-based classification

    NARCIS (Netherlands)

    van Heuvelen, M.J.G.; Stevens, M.; Kempen, G.I.J.M.

    This study investigated differences in physical-fitness test scores between actively and passively recruited older adults and the consequences thereof for norm-based classification of individuals. Walking endurance, grip strength, hip flexibility, balance, manual dexterity, and reaction time were

  5. Machine learning for radioxenon event classification for the Comprehensive Nuclear-Test-Ban Treaty

    Energy Technology Data Exchange (ETDEWEB)

    Stocki, Trevor J., E-mail: trevor_stocki@hc-sc.gc.c [Radiation Protection Bureau, 775 Brookfield Road, A.L. 6302D1, Ottawa, ON, K1A 1C1 (Canada); Li, Guichong; Japkowicz, Nathalie [School of Information Technology and Engineering, University of Ottawa, 800 King Edward Avenue, Ottawa, ON, K1N 6N5 (Canada); Ungar, R. Kurt [Radiation Protection Bureau, 775 Brookfield Road, A.L. 6302D1, Ottawa, ON, K1A 1C1 (Canada)

    2010-01-15

    A method of weapon detection for the Comprehensive nuclear-Test-Ban-Treaty (CTBT) consists of monitoring the amount of radioxenon in the atmosphere by measuring and sampling the activity concentration of {sup 131m}Xe, {sup 133}Xe, {sup 133m}Xe, and {sup 135}Xe by radionuclide monitoring. Several explosion samples were simulated based on real data since the measured data of this type is quite rare. These data sets consisted of different circumstances of a nuclear explosion, and are used as training data sets to establish an effective classification model employing state-of-the-art technologies in machine learning. A study was conducted involving classic induction algorithms in machine learning including Naive Bayes, Neural Networks, Decision Trees, k-Nearest Neighbors, and Support Vector Machines, that revealed that they can successfully be used in this practical application. In particular, our studies show that many induction algorithms in machine learning outperform a simple linear discriminator when a signal is found in a high radioxenon background environment.

  6. Machine learning for radioxenon event classification for the Comprehensive Nuclear-Test-Ban Treaty

    International Nuclear Information System (INIS)

    Stocki, Trevor J.; Li, Guichong; Japkowicz, Nathalie; Ungar, R. Kurt

    2010-01-01

    A method of weapon detection for the Comprehensive nuclear-Test-Ban-Treaty (CTBT) consists of monitoring the amount of radioxenon in the atmosphere by measuring and sampling the activity concentration of 131m Xe, 133 Xe, 133m Xe, and 135 Xe by radionuclide monitoring. Several explosion samples were simulated based on real data since the measured data of this type is quite rare. These data sets consisted of different circumstances of a nuclear explosion, and are used as training data sets to establish an effective classification model employing state-of-the-art technologies in machine learning. A study was conducted involving classic induction algorithms in machine learning including Naive Bayes, Neural Networks, Decision Trees, k-Nearest Neighbors, and Support Vector Machines, that revealed that they can successfully be used in this practical application. In particular, our studies show that many induction algorithms in machine learning outperform a simple linear discriminator when a signal is found in a high radioxenon background environment.

  7. Development and test of a classification scheme for human factors in incident reports

    International Nuclear Information System (INIS)

    Miller, R.; Freitag, M.; Wilpert, B.

    1997-01-01

    The Research Center System Safety of the Berlin University of Technology conducted a research project on the analysis of Human Factors (HF) aspects in incident reported by German Nuclear Power Plants. Based on psychological theories and empirical studies a classification scheme was developed which permits the identification of human involvement in incidents. The classification scheme was applied in an epidemiological study to a selection of more than 600 HF - relevant incidents. The results allow insights into HF related problem areas. An additional study proved that the application of the classification scheme produces results which are reliable and independent from raters. (author). 13 refs, 1 fig

  8. Classification of solid industrial waste based on ecotoxicology tests using Daphnia magna: an alternative

    OpenAIRE

    William Gerson Matias; Vanessa Guimarães Machado; Cátia Regina Silva de Carvalho-Pinto; Débora Monteiro Brentano; Letícia Flohr

    2005-01-01

    The adequate treatment and final disposal of solid industrial wastes depends on their classification into class I or II. This classification is proposed by NBR 10.004; however, it is complex and time-consuming. With a view to facilitating this classification, the use of assays with Daphnia magna is proposed. These assays make possible the identification of toxic chemicals in the leach, which denotes the presence of one of the characteristics described by NBR 10.004, the toxicity, which is a s...

  9. Geometric classification of scalp hair for valid drug testing, 6 more reliable than 8 hair curl groups.

    Directory of Open Access Journals (Sweden)

    K Mkentane

    Full Text Available Curly hair is reported to contain higher lipid content than straight hair, which may influence incorporation of lipid soluble drugs. The use of race to describe hair curl variation (Asian, Caucasian and African is unscientific yet common in medical literature (including reports of drug levels in hair. This study investigated the reliability of a geometric classification of hair (based on 3 measurements: the curve diameter, curl index and number of waves.After ethical approval and informed consent, proximal virgin (6cm hair sampled from the vertex of scalp in 48 healthy volunteers were evaluated. Three raters each scored hairs from 48 volunteers at two occasions each for the 8 and 6-group classifications. One rater applied the 6-group classification to 80 additional volunteers in order to further confirm the reliability of this system. The Kappa statistic was used to assess intra and inter rater agreement.Each rater classified 480 hairs on each occasion. No rater classified any volunteer's 10 hairs into the same group; the most frequently occurring group was used for analysis. The inter-rater agreement was poor for the 8-groups (k = 0.418 but improved for the 6-groups (k = 0.671. The intra-rater agreement also improved (k = 0.444 to 0.648 versus 0.599 to 0.836 for 6-groups; that for the one evaluator for all volunteers was good (k = 0.754.Although small, this is the first study to test the reliability of a geometric classification. The 6-group method is more reliable. However, a digital classification system is likely to reduce operator error. A reliable objective classification of human hair curl is long overdue, particularly with the increasing use of hair as a testing substrate for treatment compliance in Medicine.

  10. Comparison of accuracy of fibrosis degree classifications by liver biopsy and non-invasive tests in chronic hepatitis C

    Directory of Open Access Journals (Sweden)

    Boursier Jérôme

    2011-11-01

    Full Text Available Abstract Background Non-invasive tests have been constructed and evaluated mainly for binary diagnoses such as significant fibrosis. Recently, detailed fibrosis classifications for several non-invasive tests have been developed, but their accuracy has not been thoroughly evaluated in comparison to liver biopsy, especially in clinical practice and for Fibroscan. Therefore, the main aim of the present study was to evaluate the accuracy of detailed fibrosis classifications available for non-invasive tests and liver biopsy. The secondary aim was to validate these accuracies in independent populations. Methods Four HCV populations provided 2,068 patients with liver biopsy, four different pathologist skill-levels and non-invasive tests. Results were expressed as percentages of correctly classified patients. Results In population #1 including 205 patients and comparing liver biopsy (reference: consensus reading by two experts and blood tests, Metavir fibrosis (FM stage accuracy was 64.4% in local pathologists vs. 82.2% (p -3 in single expert pathologist. Significant discrepancy (≥ 2FM vs reference histological result rates were: Fibrotest: 17.2%, FibroMeter2G: 5.6%, local pathologists: 4.9%, FibroMeter3G: 0.5%, expert pathologist: 0% (p -3. In population #2 including 1,056 patients and comparing blood tests, the discrepancy scores, taking into account the error magnitude, of detailed fibrosis classification were significantly different between FibroMeter2G (0.30 ± 0.55 and FibroMeter3G (0.14 ± 0.37, p -3 or Fibrotest (0.84 ± 0.80, p -3. In population #3 (and #4 including 458 (359 patients and comparing blood tests and Fibroscan, accuracies of detailed fibrosis classification were, respectively: Fibrotest: 42.5% (33.5%, Fibroscan: 64.9% (50.7%, FibroMeter2G: 68.7% (68.2%, FibroMeter3G: 77.1% (83.4%, p -3 (p -3. Significant discrepancy (≥ 2 FM rates were, respectively: Fibrotest: 21.3% (22.2%, Fibroscan: 12.9% (12.3%, FibroMeter2G: 5.7% (6

  11. Soil classification based on cone penetration test (CPT) data in Western Central Java

    Science.gov (United States)

    Apriyono, Arwan; Yanto, Santoso, Purwanto Bekti; Sumiyanto

    2018-03-01

    This study presents a modified friction ratio range for soil classification i.e. gravel, sand, silt & clay and peat, using CPT data in Western Central Java. The CPT data was obtained solely from Soil Mechanic Laboratory of Jenderal Soedirman University that covers more than 300 sites within the study area. About 197 data were produced from data filtering process. IDW method was employed to interpolated friction ratio values in a regular grid point for soil classification map generation. Soil classification map was generated and presented using QGIS software. In addition, soil classification map with respect to modified friction ratio range was validated using 10% of total measurements. The result shows that silt and clay dominate soil type in the study area, which is in agreement with two popular methods namely Begemann and Vos. However, the modified friction ratio range produces 85% similarity with laboratory measurements whereby Begemann and Vos method yields 70% similarity. In addition, modified friction ratio range can effectively distinguish fine and coarse grains, thus useful for soil classification and subsequently for landslide analysis. Therefore, modified friction ratio range proposed in this study can be used to identify soil type for mountainous tropical region.

  12. Asthma in pregnancy: association between the Asthma Control Test and the Global Initiative for Asthma classification and comparisons with spirometry.

    Science.gov (United States)

    de Araujo, Georgia Véras; Leite, Débora F B; Rizzo, José A; Sarinho, Emanuel S C

    2016-08-01

    The aim of this study was to identify a possible association between the assessment of clinical asthma control using the Asthma Control Test (ACT) and the Global Initiative for Asthma (GINA) classification and to perform comparisons with values of spirometry. Through this cross-sectional study, 103 pregnant women with asthma were assessed in the period from October 2010 to October 2013 in the asthma pregnancy clinic at the Clinical Hospital of the Federal University of Pernambuco. Questionnaires concerning the level of asthma control were administered using the Global Initiative for Asthma classification, the Asthma Control Test validated for asthmatic expectant mothers and spirometry; all three methods of assessing asthma control were performed during the same visit between the twenty-first and twenty-seventh weeks of pregnancy. There was a significant association between clinical asthma control assessment using the Asthma Control Test and the Global Initiative for Asthma classification (pspirometry. This study shows that both the Global Initiative for Asthma classification and the Asthma Control Test can be used for asthmatic expectant mothers to assess the clinical control of asthma, especially at the end of the second trimester, which is assumed to be the period of worsening asthma exacerbations during pregnancy. We highlight the importance of the Asthma Control Test as a subjective instrument with easy application, easy interpretation and good reproducibility that does not require spirometry to assess the level of asthma control and can be used in the primary care of asthmatic expectant mothers. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  13. Conceptual Scoring and Classification Accuracy of Vocabulary Testing in Bilingual Children

    Science.gov (United States)

    Anaya, Jissel B.; Peña, Elizabeth D.; Bedore, Lisa M.

    2018-01-01

    Purpose: This study examined the effects of single-language and conceptual scoring on the vocabulary performance of bilingual children with and without specific language impairment. We assessed classification accuracy across 3 scoring methods. Method: Participants included Spanish-English bilingual children (N = 247) aged 5;1 (years;months) to…

  14. Reliability testing of two classification systems for osteoarthritis and post-traumatic arthritis of the elbow.

    Science.gov (United States)

    Amini, Michael H; Sykes, Joshua B; Olson, Stephen T; Smith, Richard A; Mauck, Benjamin M; Azar, Frederick M; Throckmorton, Thomas W

    2015-03-01

    The severity of elbow arthritis is one of many factors that surgeons must evaluate when considering treatment options for a given patient. Elbow surgeons have historically used the Broberg and Morrey (BM) and Hastings and Rettig (HR) classification systems to radiographically stage the severity of post-traumatic arthritis (PTA) and primary osteoarthritis (OA). We proposed to compare the intraobserver and interobserver reliability between systems for patients with either PTA or OA. The radiographs of 45 patients were evaluated at least 2 weeks apart by 6 evaluators of different levels of training. Intraobserver and interobserver reliability were calculated by Spearman correlation coefficients with 95% confidence intervals. Agreement was considered almost perfect for coefficients >0.80 and substantial for coefficients of 0.61 to 0.80. In patients with both PTA and OA, intraobserver reliability and interobserver reliability were substantial, with no difference between classification systems. There were no significant differences in intraobserver or interobserver reliability between attending physicians and trainees for either classification system (all P > .10). The presence of fracture implants did not affect reliability in the BM system but did substantially worsen reliability in the HR system (intraobserver P = .04 and interobserver P = .001). The BM and HR classifications both showed substantial intraobserver and interobserver reliability for PTA and OA. Training level differences did not affect reliability for either system. Both trainees and fellowship-trained surgeons may easily and reliably apply each classification system to the evaluation of primary elbow OA and PTA, although the HR system was less reliable in the presence of fracture implants. Copyright © 2015 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

  15. Dermal and inhalation acute toxic class methods: test procedures and biometric evaluations for the Globally Harmonized Classification System.

    Science.gov (United States)

    Holzhütter, H G; Genschow, E; Diener, W; Schlede, E

    2003-05-01

    The acute toxic class (ATC) methods were developed for determining LD(50)/LC(50) estimates of chemical substances with significantly fewer animals than needed when applying conventional LD(50)/LC(50) tests. The ATC methods are sequential stepwise procedures with fixed starting doses/concentrations and a maximum of six animals used per dose/concentration. The numbers of dead/moribund animals determine whether further testing is necessary or whether the test is terminated. In recent years we have developed classification procedures for the oral, dermal and inhalation routes of administration by using biometric methods. The biometric approach assumes a probit model for the mortality probability of a single animal and assigns the chemical to that toxicity class for which the best concordance is achieved between the statistically expected and the observed numbers of dead/moribund animals at the various steps of the test procedure. In previous publications we have demonstrated the validity of the biometric ATC methods on the basis of data obtained for the oral ATC method in two-animal ring studies with 15 participants from six countries. Although the test procedures and biometric evaluations for the dermal and inhalation ATC methods have already been published, there was a need for an adaptation of the classification schemes to the starting doses/concentrations of the Globally Harmonized Classification System (GHS) recently adopted by the Organization for Economic Co-operation and Development (OECD). Here we present the biometric evaluation of the dermal and inhalation ATC methods for the starting doses/concentrations of the GHS and of some other international classification systems still in use. We have developed new test procedures and decision rules for the dermal and inhalation ATC methods, which require significantly fewer animals to provide predictions of toxicity classes, that are equally good or even better than those achieved by using the conventional LD(50)/LC

  16. Testing the McSad depression specific classification system in patients with somatic conditions: validity and performance.

    Science.gov (United States)

    Papageorgiou, Katerina; Vermeulen, Karin M; Schroevers, Maya J; Buskens, Erik; Ranchor, Adelita V

    2013-07-26

    Valuations of depression are useful to evaluate depression interventions offered to patients with chronic somatic conditions. The only classification system to describe depression developed specifically for valuation purposes is the McSad, but it has not been used among somatic patients. The aim of this study was to test the construct validity of the McSad among diabetes and cancer patients and then to compare the McSad to the commonly used EuroQol - 5 Dimensions (EQ-5DTM) classification system. The comparison was expected to shed light on their capacity to reflect the range of depression states experienced by somatic patients. Cross-sectional data were collected online from 114 diabetes and 195 cancer patients; additionally, 241 cancer patients completed part of the survey on paper. Correlational analyses were performed to test the construct validity. Specifically, we hypothesized high correlations of the McSad domains with depression (Center for Epidemiological Studies Depression Scale (CES-D) and the Patient Health Questionnaire (PHQ-9)). We also expected low/moderate correlations with self-esteem (Rosenberg Self-Esteem scale - RSE) and extraversion (Eysenck Personality Questionnaire Extraversion scale - EPQ-e). Multiple linear regression analyses were run so that the proportion of variance in depression scores (CES-D, PHQ-9) explained by the McSad could be compared to the proportion explained by the EQ-5D classification system. As expected, among all patients groups, we found moderate to high correlations for the McSad domains with the CES-D (.41 to .70) and the PHQ-9 (.52 to .76); we also found low to moderate correlations with the RSE (-.21 to .-48) and the EPQ-e (.18 to .31). Linear regression analyses showed that the McSad explained a greater proportion of variance in depression (CES-D, PHQ-9) (Diabetes: 73%, 82%; Cancer: 72%, 72%) than the EQ-5D classification system (Diabetes: 47%, 59%; Cancer: 51%, 47%). Findings support the construct validity of the Mc

  17. Literature Review: Validity and Potential Usefulness of Psychomotor Ability Tests for Personnel Selection and Classification

    Science.gov (United States)

    1988-04-01

    processing capabilities. Craik and Lockhart (1972), for example, investigated limitations In the ability to store Information In short-term storage...F. I. M., & Lockhart , R. S. (1972). Levels of processing : A framework for memory research. Journal of Verbal Learning and Verbal Behavior, 11, 671...preferable to an information processing taxonomy for purposes of the current selection and classification research. i-irst, on a theoretical level

  18. Multispectral imaging burn wound tissue classification system: a comparison of test accuracies between several common machine learning algorithms

    Science.gov (United States)

    Squiers, John J.; Li, Weizhi; King, Darlene R.; Mo, Weirong; Zhang, Xu; Lu, Yang; Sellke, Eric W.; Fan, Wensheng; DiMaio, J. Michael; Thatcher, Jeffrey E.

    2016-03-01

    The clinical judgment of expert burn surgeons is currently the standard on which diagnostic and therapeutic decisionmaking regarding burn injuries is based. Multispectral imaging (MSI) has the potential to increase the accuracy of burn depth assessment and the intraoperative identification of viable wound bed during surgical debridement of burn injuries. A highly accurate classification model must be developed using machine-learning techniques in order to translate MSI data into clinically-relevant information. An animal burn model was developed to build an MSI training database and to study the burn tissue classification ability of several models trained via common machine-learning algorithms. The algorithms tested, from least to most complex, were: K-nearest neighbors (KNN), decision tree (DT), linear discriminant analysis (LDA), weighted linear discriminant analysis (W-LDA), quadratic discriminant analysis (QDA), ensemble linear discriminant analysis (EN-LDA), ensemble K-nearest neighbors (EN-KNN), and ensemble decision tree (EN-DT). After the ground-truth database of six tissue types (healthy skin, wound bed, blood, hyperemia, partial injury, full injury) was generated by histopathological analysis, we used 10-fold cross validation to compare the algorithms' performances based on their accuracies in classifying data against the ground truth, and each algorithm was tested 100 times. The mean test accuracy of the algorithms were KNN 68.3%, DT 61.5%, LDA 70.5%, W-LDA 68.1%, QDA 68.9%, EN-LDA 56.8%, EN-KNN 49.7%, and EN-DT 36.5%. LDA had the highest test accuracy, reflecting the bias-variance tradeoff over the range of complexities inherent to the algorithms tested. Several algorithms were able to match the current standard in burn tissue classification, the clinical judgment of expert burn surgeons. These results will guide further development of an MSI burn tissue classification system. Given that there are few surgeons and facilities specializing in burn care

  19. Towards a formal genealogical classification of the Lezgian languages (North Caucasus: testing various phylogenetic methods on lexical data.

    Directory of Open Access Journals (Sweden)

    Alexei Kassian

    Full Text Available A lexicostatistical classification is proposed for 20 languages and dialects of the Lezgian group of the North Caucasian family, based on meticulously compiled 110-item wordlists, published as part of the Global Lexicostatistical Database project. The lexical data have been subsequently analyzed with the aid of the principal phylogenetic methods, both distance-based and character-based: Starling neighbor joining (StarlingNJ, Neighbor joining (NJ, Unweighted pair group method with arithmetic mean (UPGMA, Bayesian Markov chain Monte Carlo (MCMC, Unweighted maximum parsimony (UMP. Cognation indexes within the input matrix were marked by two different algorithms: traditional etymological approach and phonetic similarity, i.e., the automatic method of consonant classes (Levenshtein distances. Due to certain reasons (first of all, high lexicographic quality of the wordlists and a consensus about the Lezgian phylogeny among Caucasologists, the Lezgian database is a perfect testing area for appraisal of phylogenetic methods. For the etymology-based input matrix, all the phylogenetic methods, with the possible exception of UMP, have yielded trees that are sufficiently compatible with each other to generate a consensus phylogenetic tree of the Lezgian lects. The obtained consensus tree agrees with the traditional expert classification as well as some of the previously proposed formal classifications of this linguistic group. Contrary to theoretical expectations, the UMP method has suggested the least plausible tree of all. In the case of the phonetic similarity-based input matrix, the distance-based methods (StarlingNJ, NJ, UPGMA have produced the trees that are rather close to the consensus etymology-based tree and the traditional expert classification, whereas the character-based methods (Bayesian MCMC, UMP have yielded less likely topologies.

  20. Towards a formal genealogical classification of the Lezgian languages (North Caucasus): testing various phylogenetic methods on lexical data.

    Science.gov (United States)

    Kassian, Alexei

    2015-01-01

    A lexicostatistical classification is proposed for 20 languages and dialects of the Lezgian group of the North Caucasian family, based on meticulously compiled 110-item wordlists, published as part of the Global Lexicostatistical Database project. The lexical data have been subsequently analyzed with the aid of the principal phylogenetic methods, both distance-based and character-based: Starling neighbor joining (StarlingNJ), Neighbor joining (NJ), Unweighted pair group method with arithmetic mean (UPGMA), Bayesian Markov chain Monte Carlo (MCMC), Unweighted maximum parsimony (UMP). Cognation indexes within the input matrix were marked by two different algorithms: traditional etymological approach and phonetic similarity, i.e., the automatic method of consonant classes (Levenshtein distances). Due to certain reasons (first of all, high lexicographic quality of the wordlists and a consensus about the Lezgian phylogeny among Caucasologists), the Lezgian database is a perfect testing area for appraisal of phylogenetic methods. For the etymology-based input matrix, all the phylogenetic methods, with the possible exception of UMP, have yielded trees that are sufficiently compatible with each other to generate a consensus phylogenetic tree of the Lezgian lects. The obtained consensus tree agrees with the traditional expert classification as well as some of the previously proposed formal classifications of this linguistic group. Contrary to theoretical expectations, the UMP method has suggested the least plausible tree of all. In the case of the phonetic similarity-based input matrix, the distance-based methods (StarlingNJ, NJ, UPGMA) have produced the trees that are rather close to the consensus etymology-based tree and the traditional expert classification, whereas the character-based methods (Bayesian MCMC, UMP) have yielded less likely topologies.

  1. A low cost color-based bacterial biosensor for measuring arsenic in groundwater.

    Science.gov (United States)

    Huang, Chi-Wei; Wei, Chia-Cheng; Liao, Vivian Hsiu-Chuan

    2015-12-01

    Using arsenic (As) contaminated groundwater for drinking or irrigation has caused major health problems for humans around the world, raising a need to monitor As level efficiently and economically. This study developed a color-based bacterial biosensor which is easy-to-use and inexpensive for measuring As and could be complementary to current As detecting techniques. The arsR-lacZ recombinant gene cassette in nonpathogenic strain Escherichia coli DH5α was used in the color-based biosensor which could be observed by eyes or measured by spectrometer. The developed bacterial biosensor demonstrates a quantitative range from 10 to 500μgL(-1) of As in 3-h reaction time. Furthermore, the biosensor was able to successfully detect and estimate As concentration in groundwater sample by measuring optical density at 595nm (OD595). Among different storage methods used in this study, biosensor in liquid at 4°C showed the longest shelf life about 9d, and liquid storage at RT and cell pellet could also be stored for about 3-5d. In conclusion, this study showed that the As biosensor with reliable color signal and economical preservation methods is useful for rapid screening of As pollutant, providing the potential for large scale screening and better management strategies for environmental quality control. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. TESTING THE GENERALIZATION EFFICIENCY OF OIL SLICK CLASSIFICATION ALGORITHM USING MULTIPLE SAR DATA FOR DEEPWATER HORIZON OIL SPILL

    Directory of Open Access Journals (Sweden)

    C. Ozkan

    2012-07-01

    Full Text Available Marine oil spills due to releases of crude oil from tankers, offshore platforms, drilling rigs and wells, etc. are seriously affecting the fragile marine and coastal ecosystem and cause political and environmental concern. A catastrophic explosion and subsequent fire in the Deepwater Horizon oil platform caused the platform to burn and sink, and oil leaked continuously between April 20th and July 15th of 2010, releasing about 780,000 m3 of crude oil into the Gulf of Mexico. Today, space-borne SAR sensors are extensively used for the detection of oil spills in the marine environment, as they are independent from sun light, not affected by cloudiness, and more cost-effective than air patrolling due to covering large areas. In this study, generalization extent of an object based classification algorithm was tested for oil spill detection using multiple SAR imagery data. Among many geometrical, physical and textural features, some more distinctive ones were selected to distinguish oil and look alike objects from each others. The tested classifier was constructed from a Multilayer Perception Artificial Neural Network trained by ABC, LM and BP optimization algorithms. The training data to train the classifier were constituted from SAR data consisting of oil spill originated from Lebanon in 2007. The classifier was then applied to the Deepwater Horizon oil spill data in the Gulf of Mexico on RADARSAT-2 and ALOS PALSAR images to demonstrate the generalization efficiency of oil slick classification algorithm.

  3. Unspecific chronic low back pain - a simple functional classification tested in a case series of patients with spinal deformities.

    Science.gov (United States)

    Weiss, Hans-Rudolf; Werkmann, Mario

    2009-02-17

    Up to now, chronic low back pain without radicular symptoms is not classified and attributed in international literature as being "unspecific". For specific bracing of this patient group we use simple physical tests to predict the brace type the patient is most likely to benefit from. Based on these physical tests we have developed a simple functional classification of "unspecific" low back pain in patients with spinal deformities. Between January 2006 and July 2007 we have tested 130 patients (116 females and 14 males) with spinal deformities (average age 45 years, ranging from 14 years to 69) and chronic unspecific low back pain (pain for > 24 months) along with the indication for brace treatment for chronic unspecific low back pain. Some of the patients had symptoms of spinal claudication (n = 16). The "sagittal realignment test" (SRT) was applied, a lumbar hyperextension test, and the "sagittal delordosation test" (SDT). Additionally 3 female patients with spondylolisthesis were tested, including one female with symptoms of spinal claudication and 2 of these patients were 14 years of age and the other 43yrs old at the time of testing. 117 Patients reported significant pain release in the SRT and 13 in the SDT (> or = 2 steps in the Roland & Morris VRS). 3 Patients had no significant pain release in both of the tests (manual investigation we found hypermobility at L5/S1 or a spondylolisthesis at level L5/S1. In the other patients who responded well to the SRT loss of lumbar lordosis was the main issue, a finding which, according to scientific literature, correlates well with low back pain. The 3 patients who did not respond to either test had a fair pain reduction in a generally delordosing brace with an isolated small foam pad inserted at the level of L 2/3, leading to a lordosation at this region. With the exception of 3 patients (2.3%) a clear distribution to one of the two classes has been possible. 117 patients were supplied successfully with a sagittal

  4. Exploratory analysis of methods for automated classification of laboratory test orders into syndromic groups in veterinary medicine.

    Directory of Open Access Journals (Sweden)

    Fernanda C Dórea

    Full Text Available BACKGROUND: Recent focus on earlier detection of pathogen introduction in human and animal populations has led to the development of surveillance systems based on automated monitoring of health data. Real- or near real-time monitoring of pre-diagnostic data requires automated classification of records into syndromes--syndromic surveillance--using algorithms that incorporate medical knowledge in a reliable and efficient way, while remaining comprehensible to end users. METHODS: This paper describes the application of two of machine learning (Naïve Bayes and Decision Trees and rule-based methods to extract syndromic information from laboratory test requests submitted to a veterinary diagnostic laboratory. RESULTS: High performance (F1-macro = 0.9995 was achieved through the use of a rule-based syndrome classifier, based on rule induction followed by manual modification during the construction phase, which also resulted in clear interpretability of the resulting classification process. An unmodified rule induction algorithm achieved an F(1-micro score of 0.979 though this fell to 0.677 when performance for individual classes was averaged in an unweighted manner (F(1-macro, due to the fact that the algorithm failed to learn 3 of the 16 classes from the training set. Decision Trees showed equal interpretability to the rule-based approaches, but achieved an F(1-micro score of 0.923 (falling to 0.311 when classes are given equal weight. A Naïve Bayes classifier learned all classes and achieved high performance (F(1-micro= 0.994 and F(1-macro = .955, however the classification process is not transparent to the domain experts. CONCLUSION: The use of a manually customised rule set allowed for the development of a system for classification of laboratory tests into syndromic groups with very high performance, and high interpretability by the domain experts. Further research is required to develop internal validation rules in order to establish

  5. Risk factors for changing test classification in the Danish surveillance program for Salmonella in dairy herds

    DEFF Research Database (Denmark)

    Nielsen, Lennarth Ravn; Warnick, L. D.; Greiner, M.

    2007-01-01

    test positive to negative, whereas the breed and neighbor factors were not found to be important for small herds. Organic production was associated with remaining test positive, but not with becoming test positive. The results emphasize the importance of external and internal biosecurity measures....... The objective of this study was to evaluate risk factors for changing from test negative to positive, which was indicative of herds becoming infected from one quarter of the year to the next, and risk factors for changing from test positive to negative, which was indicative of herds recovering from infection...

  6. General classification of charged test particle circular orbits in Reissner-Nordstroem spacetime

    Energy Technology Data Exchange (ETDEWEB)

    Pugliese, D. [Silesian University in Opava, Institute of Physics, Faculty of Philosophy and Science, Opava (Czech Republic); Quevedo, H. [Universita di Roma ' ' La Sapienza' ' , Dipartimento di Fisica, ICRA, Rome (Italy); Icranet-Pescara, Pescara (Italy); Universidad Nacional Autonoma de Mexico, Instituto de Ciencias Nucleares, Mexico, DF (Mexico); Kazakh National University, Department of Theoretical and Nuclear Physics, Almaty (Kazakhstan); Ruffini, R. [Universita di Roma ' ' La Sapienza' ' , Dipartimento di Fisica, ICRA, Rome (Italy); Icranet-Pescara, Pescara (Italy)

    2017-04-15

    We investigate charged particles' circular motion in the gravitational field of a charged mass distribution described by the Reissner-Nordstroem spacetime. We introduce a set of independent parameters completely characterizing the different spatial regions in which circular motion is allowed. We provide a most complete classification of circular orbits for different sets of particle and source charge-to-mass ratios. We study both black holes and naked singularities and show that the behavior of charged particles depend drastically on the type of source. Our analysis shows in an alternative manner that the behavior of circular orbits can in principle be used to distinguish between black holes and naked singularities. From this analysis, special limiting values for the dimensionless charge of black hole and naked singularity emerge, namely, Q/M = 1/2, Q/M = √(13)/5 and Q/M = √(2/3) for the black hole case and Q/M = 1, Q/M = 5/(2√(6)), Q/M = 3√(6)/7, and finally Q/M = √(9/8) for the naked singularity case. Similarly and surprisingly, analogous limits emerge for the orbiting particles charge-to-mass ratio ε, for positive charges ε = 1, ε = 2 and ε = M/Q. These limits play an important role in the study of the coupled electromagnetic and gravitational interactions, and the investigation of the role of the charge in the gravitational collapse of compact objects. (orig.)

  7. An investigation of classification algorithms for predicting HIV drug resistance without genotype resistance testing

    CSIR Research Space (South Africa)

    Brandt, P

    2014-01-01

    Full Text Available is limited in low-resource settings. In this paper we investigate machine learning techniques for drug resistance prediction from routine treatment and laboratory data to help clinicians select patients for confirmatory genotype testing. The techniques...

  8. Classification with support hyperplanes

    NARCIS (Netherlands)

    G.I. Nalbantov (Georgi); J.C. Bioch (Cor); P.J.F. Groenen (Patrick)

    2006-01-01

    textabstractA new classification method is proposed, called Support Hy- perplanes (SHs). To solve the binary classification task, SHs consider the set of all hyperplanes that do not make classification mistakes, referred to as semi-consistent hyperplanes. A test object is classified using

  9. Field-Testing a PC Electronic Documentation System using the Clinical Care Classification© System with Nursing Students

    Directory of Open Access Journals (Sweden)

    Jennifer E. Mannino

    2011-01-01

    Full Text Available Schools of nursing are slow in training their students to keep up with the fast approaching era of electronic healthcare documentation. This paper discusses the importance of nursing documentation, and describes the field-testing of an electronic health record, the Sabacare Clinical Care Classification (CCC© system. The PC-CCC©, designed as a Microsoft Access® application, is an evidence-based electronic documentation system available via free download from the internet. A sample of baccalaureate nursing students from a mid-Atlantic private college used this program to document the nursing care they provided to patients during their sophomore level clinical experience. This paper summarizes the design, training, and evaluation of using the system in practice.

  10. Unspecific chronic low back pain – a simple functional classification tested in a case series of patients with spinal deformities

    Directory of Open Access Journals (Sweden)

    Werkmann Mario

    2009-02-01

    Full Text Available Abstract Background Up to now, chronic low back pain without radicular symptoms is not classified and attributed in international literature as being "unspecific". For specific bracing of this patient group we use simple physical tests to predict the brace type the patient is most likely to benefit from. Based on these physical tests we have developed a simple functional classification of "unspecific" low back pain in patients with spinal deformities. Methods Between January 2006 and July 2007 we have tested 130 patients (116 females and 14 males with spinal deformities (average age 45 years, ranging from 14 years to 69 and chronic unspecific low back pain (pain for > 24 months along with the indication for brace treatment for chronic unspecific low back pain. Some of the patients had symptoms of spinal claudication (n = 16. The "sagittal realignment test" (SRT was applied, a lumbar hyperextension test, and the "sagittal delordosation test" (SDT. Additionally 3 female patients with spondylolisthesis were tested, including one female with symptoms of spinal claudication and 2 of these patients were 14 years of age and the other 43yrs old at the time of testing. Results 117 Patients reported significant pain release in the SRT and 13 in the SDT (>/= 2 steps in the Roland & Morris VRS. 3 Patients had no significant pain release in both of the tests ( Pain intensity was high (3,29 before performing the physical tests (VRS-scale 0–5 and low (1,37 while performing the physical test for the whole sample of patients. The differences where highly significant in the Wilcoxon test (z = -3,79; p In the 16 patients who did not respond to the SRT in the manual investigation we found hypermobility at L5/S1 or a spondylolisthesis at level L5/S1. In the other patients who responded well to the SRT loss of lumbar lordosis was the main issue, a finding which, according to scientific literature, correlates well with low back pain. The 3 patients who did not

  11. Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data

    Directory of Open Access Journals (Sweden)

    J. Sunil Rao

    2007-01-01

    Full Text Available In gene selection for cancer classifi cation using microarray data, we define an eigenvalue-ratio statistic to measure a gene’s contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalueratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.

  12. Learning Classification Models of Cognitive Conditions from Subtle Behaviors in the Digital Clock Drawing Test.

    Science.gov (United States)

    Souillard-Mandar, William; Davis, Randall; Rudin, Cynthia; Au, Rhoda; Libon, David J; Swenson, Rodney; Price, Catherine C; Lamar, Melissa; Penney, Dana L

    2016-03-01

    The Clock Drawing Test - a simple pencil and paper test - has been used for more than 50 years as a screening tool to differentiate normal individuals from those with cognitive impairment, and has proven useful in helping to diagnose cognitive dysfunction associated with neurological disorders such as Alzheimer's disease, Parkinson's disease, and other dementias and conditions. We have been administering the test using a digitizing ballpoint pen that reports its position with considerable spatial and temporal precision, making available far more detailed data about the subject's performance. Using pen stroke data from these drawings categorized by our software, we designed and computed a large collection of features, then explored the tradeoffs in performance and interpretability in classifiers built using a number of different subsets of these features and a variety of different machine learning techniques. We used traditional machine learning methods to build prediction models that achieve high accuracy. We operationalized widely used manual scoring systems so that we could use them as benchmarks for our models. We worked with clinicians to define guidelines for model interpretability, and constructed sparse linear models and rule lists designed to be as easy to use as scoring systems currently used by clinicians, but more accurate. While our models will require additional testing for validation, they offer the possibility of substantial improvement in detecting cognitive impairment earlier than currently possible, a development with considerable potential impact in practice.

  13. Safety quality classification test of the sealed neutron sources used in start-up neutron source rods for Qinshan Nuclear Power Plant

    International Nuclear Information System (INIS)

    Yao Chunbing; Guo Gang; Chao Jinglan; Duan Liming

    1992-01-01

    According to the regulations listed in the GB4075, the safety quality classification tests have been carried out for the neutron sources. The test items include temperature, external pressure, impact, vibration and puncture, Two dummy sealed sources are used for each test item. The testing equipment used have been examined and verified to be qualified by the measuring department which is admitted by the National standard Bureau. The leak rate of each tested sample is measured by UL-100 Helium Leak Detector (its minimum detectable leak rate is 1 x 10 -10 Pa·m 3 ·s -1 ). The samples with leak rate less than 1.33 x 10 -8 Pa·m 3 ·s -1 are considered up to the standard. The test results show the safety quality classification class of the neutron sources have reached the class of GB/E66545 which exceeds the preset class

  14. JIS Z 3105 (methods of radiographic test and classification of radiographs for aluminium welds) and its explanatory note

    International Nuclear Information System (INIS)

    Senda, Tomio

    1977-01-01

    The paragraphs of JIS Z 3105 revised in 1977 are explained, and the problems that were examined by the special committee before the JIS Z 3105 is put in force are reviewed. The JIS Z 3105 consists of a general rule, a method of radiography, a method of classification of the radiographs, and recording. The main problems which were examined are as follows: The radiation penetration testing method of a circumferencial welding portion of a tube was included in the old specifications JIS Z 3105 (1973), but it is excluded in the new specifications, because another specification JIS Z 3108 was established. The gradation meters of D1, D2, D3 and D4 types are added to the gradation meters of the existing A and B types. A restriction in accordance with both focusing dimension and thickness of the welded material is provided between a distance between the focal point and the penetrometer and a distance between the penetrometer and the film. Radiograph concentration of parts other than the penetrometer discrimination and defects of a testing part are specified in accordance with thickness of the base metal. Inclusion of copper and copper oxides are added to the blowholes, the inclusions, cracks, bad penetration and bad fusion as defects for classifying gradation. The gradation of the revised JIS is classified into four grades in lieu of the old three grades. (Iwakiri, K.)

  15. Classification methods for noise transients in advanced gravitational-wave detectors II: performance tests on Advanced LIGO data

    International Nuclear Information System (INIS)

    Powell, Jade; Heng, Ik Siong; Torres-Forné, Alejandro; Font, José A; Lynch, Ryan; Trifirò, Daniele; Cuoco, Elena; Cavaglià, Marco

    2017-01-01

    The data taken by the advanced LIGO and Virgo gravitational-wave detectors contains short duration noise transients that limit the significance of astrophysical detections and reduce the duty cycle of the instruments. As the advanced detectors are reaching sensitivity levels that allow for multiple detections of astrophysical gravitational-wave sources it is crucial to achieve a fast and accurate characterization of non-astrophysical transient noise shortly after it occurs in the detectors. Previously we presented three methods for the classification of transient noise sources. They are Principal Component Analysis for Transients (PCAT), Principal Component LALInference Burst (PC-LIB) and Wavelet Detection Filter with Machine Learning (WDF-ML). In this study we carry out the first performance tests of these algorithms on gravitational-wave data from the Advanced LIGO detectors. We use the data taken between the 3rd of June 2015 and the 14th of June 2015 during the 7th engineering run (ER7), and outline the improvements made to increase the performance and lower the latency of the algorithms on real data. This work provides an important test for understanding the performance of these methods on real, non stationary data in preparation for the second advanced gravitational-wave detector observation run, planned for later this year. We show that all methods can classify transients in non stationary data with a high level of accuracy and show the benefits of using multiple classifiers. (paper)

  16. Hazard classification test of the cartridge, 120-mm, APFSDS-T, XM829

    Energy Technology Data Exchange (ETDEWEB)

    Hooker, C.D.; Hadlock, D.E.; Mishima, J.; Gilchrist, R.L.

    1983-11-01

    Research was conducted to determine the behavior of the ammunition XM829 when subjected to detonation of an adjacent XM829 cartridge, and a sustained hot fire. It was concluded that the functioning of an XM829 cartridge, in one shipping container, will not cause immediate functioning of XM829 cartridges in adjacent containers. However, if a fire results and is sustained, adjacent cartridges may ignite, resulting in some scattering of debris within a maximum radius of 40 feet. Further, the XM829 cartridge can be expected to remain in a kinetic controlled regime with vigorous oxidation occurring early in such a fire but dropping off as the temperature cools toward ambient. Mass balance analyses data indicated a recovery of at least 80% in the 1982 external heat; in the 1983 test, the recovery percentage was improved to approximately 100% of the original depleted uranium weight volume. Therefore, it may be concluded that a significant airborne release of the depleted uranium material did not occur.

  17. Classifying Classifications

    DEFF Research Database (Denmark)

    Debus, Michael S.

    2017-01-01

    This paper critically analyzes seventeen game classifications. The classifications were chosen on the basis of diversity, ranging from pre-digital classification (e.g. Murray 1952), over game studies classifications (e.g. Elverdam & Aarseth 2007) to classifications of drinking games (e.g. LaBrie et...... al. 2013). The analysis aims at three goals: The classifications’ internal consistency, the abstraction of classification criteria and the identification of differences in classification across fields and/or time. Especially the abstraction of classification criteria can be used in future endeavors...... into the topic of game classifications....

  18. Multivariate Analyses and Classification of Inertial Sensor Data to Identify Aging Effects on the Timed-Up-and-Go Test.

    Directory of Open Access Journals (Sweden)

    Danique Vervoort

    Full Text Available Many tests can crudely quantify age-related mobility decrease but instrumented versions of mobility tests could increase their specificity and sensitivity. The Timed-up-and-Go (TUG test includes several elements that people use in daily life. The test has different transition phases: rise from a chair, walk, 180° turn, walk back, turn, and sit-down on a chair. For this reason the TUG is an often used test to evaluate in a standardized way possible decline in balance and walking ability due to age and or pathology. Using inertial sensors, qualitative information about the performance of the sub-phases can provide more specific information about a decline in balance and walking ability. The first aim of our study was to identify variables extracted from the instrumented timed-up-and-go (iTUG that most effectively distinguished performance differences across age (age 18-75. Second, we determined the discriminative ability of those identified variables to classify a younger (age 18-45 and older age group (age 46-75. From healthy adults (n = 59, trunk accelerations and angular velocities were recorded during iTUG performance. iTUG phases were detected with wavelet-analysis. Using a Partial Least Square (PLS model, from the 72-iTUG variables calculated across phases, those that explained most of the covariance between variables and age were extracted. Subsequently, a PLS-discriminant analysis (DA assessed classification power of the identified iTUG variables to discriminate the age groups. 27 variables, related to turning, walking and the stand-to-sit movement explained 71% of the variation in age. The PLS-DA with these 27 variables showed a sensitivity and specificity of 90% and 85%. Based on this model, the iTUG can accurately distinguish young and older adults. Such data can serve as a reference for pathological aging with respect to a widely used mobility test. Mobility tests like the TUG supplemented with smart technology could be used in

  19. GenColors-based comparative genome databases for small eukaryotic genomes.

    Science.gov (United States)

    Felder, Marius; Romualdi, Alessandro; Petzold, Andreas; Platzer, Matthias; Sühnel, Jürgen; Glöckner, Gernot

    2013-01-01

    Many sequence data repositories can give a quick and easily accessible overview on genomes and their annotations. Less widespread is the possibility to compare related genomes with each other in a common database environment. We have previously described the GenColors database system (http://gencolors.fli-leibniz.de) and its applications to a number of bacterial genomes such as Borrelia, Legionella, Leptospira and Treponema. This system has an emphasis on genome comparison. It combines data from related genomes and provides the user with an extensive set of visualization and analysis tools. Eukaryote genomes are normally larger than prokaryote genomes and thus pose additional challenges for such a system. We have, therefore, adapted GenColors to also handle larger datasets of small eukaryotic genomes and to display eukaryotic gene structures. Further recent developments include whole genome views, genome list options and, for bacterial genome browsers, the display of horizontal gene transfer predictions. Two new GenColors-based databases for two fungal species (http://fgb.fli-leibniz.de) and for four social amoebas (http://sacgb.fli-leibniz.de) were set up. Both new resources open up a single entry point for related genomes for the amoebozoa and fungal research communities and other interested users. Comparative genomics approaches are greatly facilitated by these resources.

  20. The Influence of temporal sampling regime on the WFD classification of catchments within the Eden Demonstration Test Catchment Project

    Science.gov (United States)

    Jonczyk, Jennine; Haygarth, Phil; Quinn, Paul; Reaney, Sim

    2014-05-01

    A high temporal resolution data set from the Eden Demonstration Test Catchment (DTC) project is used to investigate the processes causing pollution and the influence of temporal sampling regime on the WFD classification of three catchments. This data highlights WFD standards may not be fit for purpose. The Eden DTC project is part of a UK government-funded project designed to provide robust evidence regarding how diffuse pollution can be cost-effectively controlled to improve and maintain water quality in rural river catchments. The impact of multiple water quality parameters on ecosystems and sustainable food production are being studied at the catchment scale. Three focus catchments approximately 10 km2 each, have been selected to represent the different farming practices and geophysical characteristics across the Eden catchment, Northern England. A field experimental programme has been designed to monitor the dynamics of agricultural diffuse pollution at multiple scales using state of the art sensors providing continuous real time data. The data set, which includes Total Phosphorus and Total Reactive Phosphorus, Nitrate, Ammonium, pH, Conductivity, Turbidity and Chlorophyll a reveals the frequency and duration of nutrient concentration target exceedance which arises from the prevalence of storm events of increasing magnitude. This data set is sub-sampled at different time intervals to explore how different sampling regimes affects our understanding of nutrient dynamics and the ramification of the different regimes to WFD chemical status. This presentation seeks to identify an optimum temporal resolution of data for effective catchment management and to question the usefulness of the WFD status metric for determining health of a system. Criteria based on high frequency short duration events needs to be accounted for.

  1. Toward the establishment of standardized in vitro tests for lipid-based formulations, part 4: proposing a new lipid formulation performance classification system.

    Science.gov (United States)

    Williams, Hywel D; Sassene, Philip; Kleberg, Karen; Calderone, Marilyn; Igonin, Annabel; Jule, Eduardo; Vertommen, Jan; Blundell, Ross; Benameur, Hassan; Müllertz, Anette; Porter, Christopher J H; Pouton, Colin W

    2014-08-01

    The Lipid Formulation Classification System Consortium looks to develop standardized in vitro tests and to generate much-needed performance criteria for lipid-based formulations (LBFs). This article highlights the value of performing a second, more stressful digestion test to identify LBFs near a performance threshold and to facilitate lead formulation selection in instances where several LBF prototypes perform adequately under standard digestion conditions (but where further discrimination is necessary). Stressed digestion tests can be designed based on an understanding of the factors that affect LBF performance, including the degree of supersaturation generated on dispersion/digestion. Stresses evaluated included decreasing LBF concentration (↓LBF), increasing bile salt, and decreasing pH. Their capacity to stress LBFs was dependent on LBF composition and drug type: ↓LBF was a stressor to medium-chain glyceride-rich LBFs, but not more hydrophilic surfactant-rich LBFs, whereas decreasing pH stressed tolfenamic acid LBFs, but not fenofibrate LBFs. Lastly, a new Performance Classification System, that is, LBF composition independent, is proposed to promote standardized LBF comparisons, encourage robust LBF development, and facilitate dialogue with the regulatory authorities. This classification system is based on the concept that performance evaluations across three in vitro tests, designed to subject a LBF to progressively more challenging conditions, will enable effective LBF discrimination and performance grading. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

  2. Testing the McSad depression specific classification system in patients with somatic conditions : validity and performance

    NARCIS (Netherlands)

    Papageorgiou, Katerina; Vermeulen, Karin M.; Schroevers, Maya J.; Buskens, Erik; Ranchor, Adelita V.

    2013-01-01

    Background: Valuations of depression are useful to evaluate depression interventions offered to patients with chronic somatic conditions. The only classification system to describe depression developed specifically for valuation purposes is the McSad, but it has not been used among somatic patients.

  3. Feasibility of using training cases from International Spinal Cord Injury Core Data Set for testing of International Standards for Neurological Classification of Spinal Cord Injury items

    DEFF Research Database (Denmark)

    Liu, N; Hu, Z W; Zhou, M W

    2014-01-01

    STUDY DESIGN: Descriptive comparison analysis. OBJECTIVE: To evaluate whether five training cases of International Spinal Cord Injury Core Data Set (ISCICDS) are appropriate for testing the facts within the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI...... include information about zone of partial preservation, sensory score or motor score. CONCLUSION: Majority of the facts related to SL, ML and AIS are included in the five training cases of ISCICDS. Thus, using these training cases, it is feasible to test the above facts within the ISNCSCI. It is suggested...

  4. Links between early baseline cortisol, attachment classification, and problem behaviors: A test of differential susceptibility versus diathesis-stress.

    Science.gov (United States)

    Fong, Michelle C; Measelle, Jeffrey; Conradt, Elisabeth; Ablow, Jennifer C

    2017-02-01

    The purpose of the current study was to predict concurrent levels of problem behaviors from young children's baseline cortisol and attachment classification, a proxy for the quality of caregiving experienced. In a sample of 58 children living at or below the federal poverty threshold, children's baseline cortisol levels, attachment classification, and problem behaviors were assessed at 17 months of age. We hypothesized that an interaction between baseline cortisol and attachment classification would predict problem behaviors above and beyond any main effects of baseline cortisol and attachment. However, based on limited prior research, we did not predict whether or not this interaction would be more consistent with diathesis-stress or differential susceptibility models. Consistent with diathesis-stress theory, the results indicated no significant differences in problem behavior levels among children with high baseline cortisol. In contrast, children with low baseline cortisol had the highest level of problem behaviors in the context of a disorganized attachment relationship. However, in the context of a secure attachment relationship, children with low baseline cortisol looked no different, with respect to problem behavior levels, then children with high cortisol levels. These findings have substantive implications for the socioemotional development of children reared in poverty. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Color-Based Image Retrieval from High-Similarity Image Databases

    DEFF Research Database (Denmark)

    Hansen, Michael Adsetts Edberg; Carstensen, Jens Michael

    2003-01-01

    Many image classification problems can fruitfully be thought of as image retrieval in a "high similarity image database" (HSID) characterized by being tuned towards a specific application and having a high degree of visual similarity between entries that should be distinguished. We introduce...... a method for HSID retrieval using a similarity measure based on a linear combination of Jeffreys-Matusita (JM) distances between distributions of color (and color derivatives) estimated from a set of automatically extracted image regions. The weight coefficients are estimated based on optimal retrieval...... performance. Experimental results on the difficult task of visually identifying clones of fungal colonies grown in a petri dish and categorization of pelts show a high retrieval accuracy of the method when combined with standardized sample preparation and image acquisition....

  6. International Classification of Headache Disorders 3rd edition beta-based field testing of vestibular migraine in China: Demographic, clinical characteristics, audiometric findings and diagnosis statues.

    Science.gov (United States)

    Zhang, Yixin; Kong, Qingtao; Chen, Jinjin; Li, Lunxi; Wang, Dayan; Zhou, Jiying

    2016-03-01

    This study explored the clinical characteristics of vestibular migraine in Chinese subjects and performed a field test of the criteria of the International Classification of Headache Disorders 3rd edition beta version. Consecutive patients with vestibular migraine were surveyed and registered in a headache clinic during the study period. The diagnosis of vestibular migraine was made according to International Classification of Headache Disorders 3rd edition beta version. Assessments included standardized neuro-otology bedside examination, pure-tone audiogram, bithermal caloric testing, neurological imaging, cervical X-ray or magnetic resonance imaging, Doppler ultrasound of cerebral arteries and laboratory tests. A total of 67 patients (62 female/five male, 47.8 ± 10.3 years old) were enrolled in this study. The mean ages of migraine and vertigo onset were 32.2 ± 11.5 and 37.9 ± 10.1 years, respectively. The most common migraine subtype was migraine without aura (79%), followed by migraine with aura (12%) and chronic migraine (9%). The duration of vertigo attacks varied from seconds to days and 25% of patients had attacks that lasted less than 5 minutes. Among the patients with short-lasting attacks, 75% of these patients had ≥5 attacks per day within 72 hours. Auditory symptoms were reported in 36% of the patients. Migraine prophylactic treatments were effective in 77% of the patients. Our study showed that the clinical features of vestibular migraine in China were similar to those of Western studies. The definition of vertigo episodes and migraine subtypes of vestibular migraine in International Classification of Headache Disorders 3rd edition beta version might be modified further. More than five vertigo attacks per day within 72 hours might be helpful as far as identifying vestibular migraine patients with short-lasting attacks. © International Headache Society 2015.

  7. Multivariate Analyses and Classification of Inertial Sensor Data to Identify Aging Effects on the Timed-Up-and-Go Test

    NARCIS (Netherlands)

    Vervoort, Danique; Vuillerme, Nicolas; Kosse, Nienke; Hortobágyi, Tibor; Lamoth, Claudine J C

    2016-01-01

    Many tests can crudely quantify age-related mobility decrease but instrumented versions of mobility tests could increase their specificity and sensitivity. The Timed-up-and-Go (TUG) test includes several elements that people use in daily life. The test has different transition phases: rise from a

  8. 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......-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 classification windows is achieved. Further more it is shown that linear input performs as well as a quadratic......, and that even though classification gets marginally better, not much is achieved by increasing the window size beyond 1 s....

  9. Expected Classification Accuracy

    Directory of Open Access Journals (Sweden)

    Lawrence M. Rudner

    2005-08-01

    Full Text Available Every time we make a classification based on a test score, we should expect some number..of misclassifications. Some examinees whose true ability is within a score range will have..observed scores outside of that range. A procedure for providing a classification table of..true and expected scores is developed for polytomously scored items under item response..theory and applied to state assessment data. A simplified procedure for estimating the..table entries is also presented.

  10. 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 review...

  11. Evaluation of physicochemical properties of radioactive cesium in municipal solid waste incineration fly ash by particle size classification and leaching tests.

    Science.gov (United States)

    Fujii, Kengo; Ochi, Kotaro; Ohbuchi, Atsushi; Koike, Yuya

    2018-07-01

    After the Fukushima Daiichi-Nuclear Power Plant accident, environmental recovery was a major issue because a considerable amount of municipal solid waste incineration (MSWI) fly ash was highly contaminated with radioactive cesium. To the best of our knowledge, only a few studies have evaluated the detailed physicochemical properties of radioactive cesium in MSWI fly ash to propose an effective method for the solidification and reuse of MSWI fly ash. In this study, MSWI fly ash was sampled in Fukushima Prefecture. The physicochemical properties of radioactive cesium in MSWI fly ash were evaluated by particle size classification (less than 25, 25-45, 45-100, 100-300, 300-500, and greater than 500 μm) and the Japanese leaching test No. 13 called "JLT-13". These results obtained from the classification of fly ash indicated that the activity concentration of radioactive cesium and the content of the coexisting matter (i.e., chloride and potassium) temporarily change in response to the particle size of fly ash. X-ray diffraction results indicated that water-soluble radioactive cesium exists as CsCl because of the cooling process and that insoluble cesium is bound to the inner sphere of amorphous matter. These results indicated that the distribution of radioactive cesium depends on the characteristics of MSWI fly ash. Copyright © 2018 Elsevier Ltd. All rights reserved.

  12. [Research on developping the spectral dataset for Dunhuang typical colors based on color constancy].

    Science.gov (United States)

    Liu, Qiang; Wan, Xiao-Xia; Liu, Zhen; Li, Chan; Liang, Jin-Xing

    2013-11-01

    The present paper aims at developping a method to reasonably set up the typical spectral color dataset for different kinds of Chinese cultural heritage in color rendering process. The world famous wall paintings dating from more than 1700 years ago in Dunhuang Mogao Grottoes was taken as typical case in this research. In order to maintain the color constancy during the color rendering workflow of Dunhuang culture relics, a chromatic adaptation based method for developping the spectral dataset of typical colors for those wall paintings was proposed from the view point of human vision perception ability. Under the help and guidance of researchers in the art-research institution and protection-research institution of Dunhuang Academy and according to the existing research achievement of Dunhuang Research in the past years, 48 typical known Dunhuang pigments were chosen and 240 representative color samples were made with reflective spectral ranging from 360 to 750 nm was acquired by a spectrometer. In order to find the typical colors of the above mentioned color samples, the original dataset was devided into several subgroups by clustering analysis. The grouping number, together with the most typical samples for each subgroup which made up the firstly built typical color dataset, was determined by wilcoxon signed rank test according to the color inconstancy index comprehensively calculated under 6 typical illuminating conditions. Considering the completeness of gamut of Dunhuang wall paintings, 8 complementary colors was determined and finally the typical spectral color dataset was built up which contains 100 representative spectral colors. The analytical calculating results show that the median color inconstancy index of the built dataset in 99% confidence level by wilcoxon signed rank test was 3.28 and the 100 colors are distributing in the whole gamut uniformly, which ensures that this dataset can provide reasonable reference for choosing the color with highest

  13. TextureCam Field Test Results from the Mojave Desert, California: Autonomous Instrument Classification of Sediment and Rock Surfaces

    Science.gov (United States)

    Castano, R.; Abbey, W. J.; Bekker, D. L.; Cabrol, N. A.; Francis, R.; Manatt, K.; Ortega, K.; Thompson, D. R.; Wagstaff, K.

    2013-12-01

    TextureCam is an intelligent camera that uses integrated image analysis to classify sediment and rock surfaces into basic visual categories. This onboard image understanding can improve the autonomy of exploration spacecraft during the long periods when they are out of contact with operators. This could increase the number of science activities performed in each command cycle by, for example, autonomously targeting science features of opportunity with narrow field of view remote sensing, identifying clean surfaces for autonomous placement of arm-mounted instruments, or by detecting high value images for prioritized downlink. TextureCam incorporates image understanding directly into embedded hardware with a Field Programmable Gate Array (FPGA). This allows the instrument to perform the classification in real time without taxing the primary spacecraft computing resources. We use a machine learning approach in which operators train a statistical model of surface appearance using examples from previously acquired images. A random forest model extrapolates from these training cases, using the statistics of small image patches to characterize the texture of each pixel independently. Applying this model to each pixel in a new image yields a map of surface units. We deployed a prototype instrument in the Cima Volcanic Fields during a series of experiments in May 2013. We imaged each environment with a tripod-mounted RGB camera connected directly to the FPGA board for real time processing. Our first scenario assessed ground surface cover on open terrain atop a weathered volcanic flow. We performed a transect consisting of 16 forward-facing images collected at 1m intervals. We trained the system to categorize terrain into four classes: sediment, basalt cobbles, basalt pebbles, and basalt with iron oxide weathering. Accuracy rates with regards to the fraction of the actual feature that was labeled correctly by the automated system were calculated. Lower accuracy rates were

  14. The synchronous neural interactions test as a functional neuromarker for post-traumatic stress disorder (PTSD): a robust classification method based on the bootstrap

    Science.gov (United States)

    Georgopoulos, A. P.; Tan, H.-R. M.; Lewis, S. M.; Leuthold, A. C.; Winskowski, A. M.; Lynch, J. K.; Engdahl, B.

    2010-02-01

    Traumatic experiences can produce post-traumatic stress disorder (PTSD) which is a debilitating condition and for which no biomarker currently exists (Institute of Medicine (US) 2006 Posttraumatic Stress Disorder: Diagnosis and Assessment (Washington, DC: National Academies)). Here we show that the synchronous neural interactions (SNI) test which assesses the functional interactions among neural populations derived from magnetoencephalographic (MEG) recordings (Georgopoulos A P et al 2007 J. Neural Eng. 4 349-55) can successfully differentiate PTSD patients from healthy control subjects. Externally cross-validated, bootstrap-based analyses yielded >90% overall accuracy of classification. In addition, all but one of 18 patients who were not receiving medications for their disease were correctly classified. Altogether, these findings document robust differences in brain function between the PTSD and control groups that can be used for differential diagnosis and which possess the potential for assessing and monitoring disease progression and effects of therapy.

  15. A Fuzzy Color-Based Approach for Understanding Animated Movies Content in the Indexing Task

    Directory of Open Access Journals (Sweden)

    Vasile Buzuloiu

    2008-04-01

    Full Text Available This paper proposes a method for detecting and analyzing the color techniques used in the animated movies. Each animated movie uses a specific color palette which makes its color distribution one major feature in analyzing the movie content. The color palette is specially tuned by the author in order to convey certain feelings or to express artistic concepts. Deriving semantic or symbolic information from the color concepts or the visual impression induced by the movie should be an ideal way of accessing its content in a content-based retrieval system. The proposed approach is carried out in two steps. The first processing step is the low-level analysis. The movie color content gets represented with several global statistical parameters computed from the movie global weighted color histogram. The second step is the symbolic representation of the movie content. The numerical parameters obtained from the first step are converted into meaningful linguistic concepts through a fuzzy system. They concern mainly the predominant hues of the movie, some of Itten’s color contrasts and harmony schemes, color relationships and color richness. We use the proposed linguistic concepts to link to given animated movies according to their color techniques. In order to make the retrieval task easier, we also propose to represent color properties in a graphical manner which is similar to the color gamut representation. Several tests have been conducted on an animated movie database.

  16. Combining multiple hypothesis testing and affinity propagation clustering leads to accurate, robust and sample size independent classification on gene expression data

    Directory of Open Access Journals (Sweden)

    Sakellariou Argiris

    2012-10-01

    Full Text Available Abstract Background A feature selection method in microarray gene expression data should be independent of platform, disease and dataset size. Our hypothesis is that among the statistically significant ranked genes in a gene list, there should be clusters of genes that share similar biological functions related to the investigated disease. Thus, instead of keeping N top ranked genes, it would be more appropriate to define and keep a number of gene cluster exemplars. Results We propose a hybrid FS method (mAP-KL, which combines multiple hypothesis testing and affinity propagation (AP-clustering algorithm along with the Krzanowski & Lai cluster quality index, to select a small yet informative subset of genes. We applied mAP-KL on real microarray data, as well as on simulated data, and compared its performance against 13 other feature selection approaches. Across a variety of diseases and number of samples, mAP-KL presents competitive classification results, particularly in neuromuscular diseases, where its overall AUC score was 0.91. Furthermore, mAP-KL generates concise yet biologically relevant and informative N-gene expression signatures, which can serve as a valuable tool for diagnostic and prognostic purposes, as well as a source of potential disease biomarkers in a broad range of diseases. Conclusions mAP-KL is a data-driven and classifier-independent hybrid feature selection method, which applies to any disease classification problem based on microarray data, regardless of the available samples. Combining multiple hypothesis testing and AP leads to subsets of genes, which classify unknown samples from both, small and large patient cohorts with high accuracy.

  17. Different effects of color-based and location-based selection on visual working memory.

    Science.gov (United States)

    Li, Qi; Saiki, Jun

    2015-02-01

    In the present study, we investigated how feature- and location-based selection influences visual working memory (VWM) encoding and maintenance. In Experiment 1, cue type (color, location) and cue timing (precue, retro-cue) were manipulated in a change detection task. The stimuli were color-location conjunction objects, and binding memory was tested. We found a significantly greater effect for color precues than for either color retro-cues or location precues, but no difference between location pre- and retro-cues, consistent with previous studies (e.g., Griffin & Nobre in Journal of Cognitive Neuroscience, 15, 1176-1194, 2003). We also found no difference between location and color retro-cues. Experiment 2 replicated the color precue advantage with more complex color-shape-location conjunction objects. Only one retro-cue effect was different from that in Experiment 1: Color retro-cues were significantly less effective than location retro-cues in Experiment 2, which may relate to a structural property of multidimensional VWM representations. In Experiment 3, a visual search task was used, and the result of a greater location than color precue effect suggests that the color precue advantage in a memory task is related to the modulation of VWM encoding rather than of sensation and perception. Experiment 4, using a task that required only memory for individual features but not for feature bindings, further confirmed that the color precue advantage is specific to binding memory. Together, these findings reveal new aspects of the interaction between attention and VWM and provide potentially important implications for the structural properties of VWM representations.

  18. Comparison between two race/skin color classifications in relation to health-related outcomes in Brazil

    Directory of Open Access Journals (Sweden)

    Szwarcwald Celia L

    2011-08-01

    Full Text Available Abstract Background This paper aims to compare the classification of race/skin color based on the discrete categories used by the Demographic Census of the Brazilian Institute of Geography and Statistics (IBGE and a skin color scale with values ranging from 1 (lighter skin to 10 (darker skin, examining whether choosing one alternative or the other can influence measures of self-evaluation of health status, health care service utilization and discrimination in the health services. Methods This is a cross-sectional study based on data from the World Health Survey carried out in Brazil in 2003 with a sample of 5000 individuals older than 18 years. Similarities between the two classifications were evaluated by means of correspondence analysis. The effect of the two classifications on health outcomes was tested through logistic regression models for each sex, using age, educational level and ownership of consumer goods as covariables. Results Both measures of race/skin color represent the same race/skin color construct. The results show a tendency among Brazilians to classify their skin color in shades closer to the center of the color gradient. Women tend to classify their race/skin color as a little lighter than men in the skin color scale, an effect not observed when IBGE categories are used. With regard to health and health care utilization, race/skin color was not relevant in explaining any of them, regardless of the race/skin color classification. Lack of money and social class were the most prevalent reasons for discrimination in healthcare reported in the survey, suggesting that in Brazil the discussion about discrimination in the health care must not be restricted to racial discrimination and should also consider class-based discrimination. The study shows that the differences of the two classifications of race/skin color are small. However, the interval scale measure appeared to increase the freedom of choice of the respondent.

  19. A molecular phylogeny of the Cephinae (Hymenoptera, Cephidae based on mtDNA COI gene: a test of traditional classification

    Directory of Open Access Journals (Sweden)

    Mahir Budak

    2011-09-01

    Full Text Available Cephinae is traditionally divided into three tribes and about 24 genera based on morphology and host utilization. There has been no study testing the monophyly of taxa under a strict phylogenetic criterion. A molecular phylogeny of Cephinae based on a total of 68 sequences of mtDNA COI gene, representing seven genera of Cephinae, is reconstructed to test the traditional limits and relationships of taxa. Monophyly of the traditional tribes is not supported. Monophyly of the genera are largely supported except for Pachycephus. A few host shift events are suggested based on phylogenetic relationships among taxa. These results indicate that a more robust phylogeny is required for a more plausible conclusion. We also report two species of Cephus for the first time from Turkey.

  20. Evaluation of Tests of Processing Speed, Spatial Ability, and Working Memory for use in Military Occupational Classification

    Science.gov (United States)

    2013-12-01

    Reviewed by Tanja Blackstone , Ph.D. Approved and released by D. M. Cashbaugh Director Approved for public release; distribution is unlimited...these tests more favorably if the current stellar military recruiting environment deteriorates. The military has sustained a long running positive...recruiting environment due mainly to (1) the nation’s economic downturn resulting in a high unemployment rate and limited good job opportunities, (2) a

  1. Red radiators versus red tulips : the influence of context on the interpretation and effectiveness of color-based ambient persuasive technology

    NARCIS (Netherlands)

    Lu, S.; Ham, J.R.C.; Midden, C.J.H.; Meschtscherjakov, A.; De Ruyter, B.; Fuchsberger, V.; Murer, M.; Tscheligi, M.

    2016-01-01

    Colors are widely used as feedback in ambient persuasive technology. In current research, we argue that the information that colorbased feedback carries is highly context dependent. Two studies investigated effects of context (in which color-based feedback was presented) on user’s interpretation of

  2. 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 now...... well established. In their simplest form, these methods classify voxels independently based on their intensity alone, although much more sophisticated models are typically used in practice. This article aims to give an overview of often-used computational techniques for brain tissue classification...

  3. Evaluation of classification systems for nonspecific idiopathic orbital inflammation

    NARCIS (Netherlands)

    Bijlsma, Ward R.; van 't Hullenaar, Fleur C.; Mourits, Maarten P.; Kalmann, Rachel

    2012-01-01

    To systematically analyze existing classification systems for idiopathic orbital inflammation (IOI) and propose and test a new best practice classification system. A systematic literature search was conducted to find all studies that described and applied a classification system for IOI.

  4. Mimicking human texture classification

    NARCIS (Netherlands)

    Rogowitz, B.E.; van Rikxoort, Eva M.; van den Broek, Egon; Pappas, T.N.; Schouten, Theo E.; Daly, S.J.

    2005-01-01

    In an attempt to mimic human (colorful) texture classification by a clustering algorithm three lines of research have been encountered, in which as test set 180 texture images (both their color and gray-scale equivalent) were drawn from the OuTex and VisTex databases. First, a k-means algorithm was

  5. Classification of soft-shell materials for leisure outdoor jackets by clo defined from thermal properties testing

    Science.gov (United States)

    Tesinova, P.; Steklova, P.; Duchacova, T.

    2017-10-01

    Materials for outdoor activities are produced in various combinations and lamination helps to combine two or more components for gaining high comfort properties and lighten the structure. Producers can choose exact suitable material for construction of part or set of so called layered clothing for expected activity. Decreasing the weight of materials when preserving of high quality of water-vapour permeability, wind resistivity and hydrostatic resistivity and other comfort and usage properties is a big task nowadays. This paper is focused on thermal properties as an important parameter for being comfort during outdoor activities. Softshell materials were chosen for testing and computation of clo. Results compared with standardised clo table helps us to classify thermal insulation of the set of fabrics when defining proper clothing category.

  6. 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 accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, 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...

  7. Minimum Error Entropy Classification

    CERN Document Server

    Marques de Sá, Joaquim P; Santos, Jorge M F; Alexandre, Luís A

    2013-01-01

    This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of the MEE concept, in its application to solving a variety of classification problems, are presented in the wider realm of risk functionals. Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi‐layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE‐like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.

  8. 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)...

  9. Performance of fusion algorithms for computer-aided detection and classification of mines in very shallow water obtained from testing in navy Fleet Battle Exercise-Hotel 2000

    Science.gov (United States)

    Ciany, Charles M.; Zurawski, William; Kerfoot, Ian

    2001-10-01

    The performance of Computer Aided Detection/Computer Aided Classification (CAD/CAC) Fusion algorithms on side-scan sonar images was evaluated using data taken at the Navy's's Fleet Battle Exercise-Hotel held in Panama City, Florida, in August 2000. A 2-of-3 binary fusion algorithm is shown to provide robust performance. The algorithm accepts the classification decisions and associated contact locations form three different CAD/CAC algorithms, clusters the contacts based on Euclidian distance, and then declares a valid target when a clustered contact is declared by at least 2 of the 3 individual algorithms. This simple binary fusion provided a 96 percent probability of correct classification at a false alarm rate of 0.14 false alarms per image per side. The performance represented a 3.8:1 reduction in false alarms over the best performing single CAD/CAC algorithm, with no loss in probability of correct classification.

  10. 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.

  11. Classification of hand eczema

    DEFF Research Database (Denmark)

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

    2015-01-01

    BACKGROUND: Classification of hand eczema (HE) is mandatory in epidemiological and clinical studies, and also important in clinical work. OBJECTIVES: The aim was to test a recently proposed classification system of HE in clinical practice in a prospective multicentre study. METHODS: Patients were...... 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...... system investigated in the present study was useful, being able to give an appropriate main diagnosis for 89% of HE patients, and for another 7% when using two main diagnoses. The fact that more than half of the patients had one or more additional diagnoses illustrates that HE is a multifactorial disease....

  12. 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)

  13. A comparison of between hyomental distance ratios, ratio of height to thyromental, modified Mallamapati classification test and upper lip bite test in predicting difficult laryngoscopy of patients undergoing general anesthesia

    Directory of Open Access Journals (Sweden)

    Azim Honarmand

    2014-01-01

    Full Text Available Background: Failed intubation is imperative source of anesthetic interrelated patient′s mortality. The aim of this present study was to compare the ability to predict difficult visualization of the larynx from the following pre-operative airway predictive indices, in isolation and combination: Modified Mallampati test (MMT, the ratio of height to thyromental distance (RHTMD, hyomental distance ratios (HMDR, and the upper-lip-bite test (ULBT. Materials and Methods: We collected data on 525 consecutive patients scheduled for elective surgery under general anesthesia requiring endotracheal intubation and then evaluated all four factors before surgery. A skilled anesthesiologist, not imparted of the noted pre-operative airway assessment, did the laryngoscopy and rating (as per Cormack and Lehane′s classification. Sensitivity, specificity, and positive predictive value for every airway predictor in isolation and in combination were established. Results: The most sensitive of the single tests was ULBT with a sensitivity of 90.2%. The hyomental distance extreme of head extension was the least sensitive of the single tests with a sensitivity of 56.9. The HMDR had sensitivity 86.3%. The ULBT had the highest negative predictive value: And the area under a receiver-operating characteristic curve (AUC of ROC curve among single predictors. The AUC of ROC curve for ULBT, HMDR and RHTMD was significantly more than for MMT (P 0.05. Conclusion: The HMDR is comparable with RHTMD and ULBT for prediction of difficult laryngoscopy in the general population, but was significantly more than for MMT.

  14. Differential Classification of Dementia

    Directory of Open Access Journals (Sweden)

    E. Mohr

    1995-01-01

    Full Text Available In the absence of biological markers, dementia classification remains complex both in terms of characterization as well as early detection of the presence or absence of dementing symptoms, particularly in diseases with possible secondary dementia. An empirical, statistical approach using neuropsychological measures was therefore developed to distinguish demented from non-demented patients and to identify differential patterns of cognitive dysfunction in neurodegenerative disease. Age-scaled neurobehavioral test results (Wechsler Adult Intelligence Scale—Revised and Wechsler Memory Scale from Alzheimer's (AD and Huntington's (HD patients, matched for intellectual disability, as well as normal controls were used to derive a classification formula. Stepwise discriminant analysis accurately (99% correct distinguished controls from demented patients, and separated the two patient groups (79% correct. Variables discriminating between HD and AD patient groups consisted of complex psychomotor tasks, visuospatial function, attention and memory. The reliability of the classification formula was demonstrated with a new, independent sample of AD and HD patients which yielded virtually identical results (classification accuracy for dementia: 96%; AD versus HD: 78%. To validate the formula, the discriminant function was applied to Parkinson's (PD patients, 38% of whom were classified as demented. The validity of the classification was demonstrated by significant PD subgroup differences on measures of dementia not included in the discriminant function. Moreover, a majority of demented PD patients (65% were classified as having an HD-like pattern of cognitive deficits, in line with previous reports of the subcortical nature of PD dementia. This approach may thus be useful in classifying presence or absence of dementia and in discriminating between dementia subtypes in cases of secondary or coincidental dementia.

  15. 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...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

  16. 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...... that call for inquiries into the theoretical foundation of bibliographic classification theory....

  17. Hazard classification methodology

    International Nuclear Information System (INIS)

    Brereton, S.J.

    1996-01-01

    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

  18. 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.

  19. 7 CFR 28.910 - Classification of samples and issuance of classification data.

    Science.gov (United States)

    2010-01-01

    ... MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE COMMODITY STANDARDS AND STANDARD CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Cotton Classification...

  20. SAW Classification Algorithm for Chinese Text Classification

    OpenAIRE

    Xiaoli Guo; Huiyu Sun; Tiehua Zhou; Ling Wang; Zhaoyang Qu; Jiannan Zang

    2015-01-01

    Considering the explosive growth of data, the increased amount of text data’s effect on the performance of text categorization forward the need for higher requirements, such that the existing classification method cannot be satisfied. Based on the study of existing text classification technology and semantics, this paper puts forward a kind of Chinese text classification oriented SAW (Structural Auxiliary Word) algorithm. The algorithm uses the special space effect of Chinese text where words...

  1. Radar transmitter classification using non-stationary signal classifier

    CSIR Research Space (South Africa)

    Du Plessis, MC

    2009-07-01

    Full Text Available support vector machine which is applied to the radar pulse's time-frequency representation. The time-frequency representation is refined using particle swarm optimization to increase the classification accuracy. The classification accuracy is tested...

  2. 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...

  3. 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...

  4. Asteroid taxonomic classifications

    International Nuclear Information System (INIS)

    Tholen, D.J.

    1989-01-01

    This paper reports on three taxonomic classification schemes developed and applied to the body of available color and albedo data. Asteroid taxonomic classifications according to two of these schemes are reproduced

  5. Hand eczema classification

    DEFF Research Database (Denmark)

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

    2008-01-01

    of 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...... A classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....

  6. Standard classification: Physics

    International Nuclear Information System (INIS)

    1977-01-01

    This is a draft standard classification of physics. The conception is based on the physics part of the systematic catalogue of the Bayerische Staatsbibliothek and on the classification given in standard textbooks. The ICSU-AB classification now used worldwide by physics information services was not taken into account. (BJ) [de

  7. Classification of refrigerants; Classification des fluides frigorigenes

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-07-01

    This document was made from the US standard ANSI/ASHRAE 34 published in 2001 and entitled 'designation and safety classification of refrigerants'. This classification allows to clearly organize in an international way the overall refrigerants used in the world thanks to a codification of the refrigerants in correspondence with their chemical composition. This note explains this codification: prefix, suffixes (hydrocarbons and derived fluids, azeotropic and non-azeotropic mixtures, various organic compounds, non-organic compounds), safety classification (toxicity, flammability, case of mixtures). (J.S.)

  8. Assessment of nasal spray deposition pattern in a silicone human nose model using a color-based method.

    Science.gov (United States)

    Kundoor, Vipra; Dalby, Richard N

    2010-01-01

    To develop a simple and inexpensive method to visualize and quantify droplet deposition patterns. Deposition pattern was determined by uniformly coating the nose model with Sar-Gel (a paste that changes from white to purple on contact with water) and subsequently discharging sprays into the nose model. The color change was captured using a digital camera and analyzed using Adobe Photoshop. Several tests were conducted to validate the method. Deposition patterns of different nasal sprays (Ayr, Afrin, and Zicam) and different nasal drug delivery devices (Afrin nasal spray and PARI Sinustar nasal nebulizer) were compared. We also used the method to evaluate the effect of inhaled flow rate on nasal spray deposition. There was a significant difference in the deposition area for Ayr, Afrin, and Zicam. The deposition areas of Afrin nasal spray and PARI Sinustar nasal nebulizer (2 min and 5 min) were significantly different. Inhaled flow rate did not have a significant effect on the deposition pattern. Lower viscosity formulations (Ayr, Afrin) provided greater coverage than the higher viscosity formulation (Zicam). The nebulizer covered a greater surface area than the spray pump we evaluated. Aerosol deposition in the nose model was not affected by air flow conditions.

  9. Classification, disease, and diagnosis.

    Science.gov (United States)

    Jutel, Annemarie

    2011-01-01

    Classification shapes medicine and guides its practice. Understanding classification must be part of the quest to better understand the social context and implications of diagnosis. Classifications are part of the human work that provides a foundation for the recognition and study of illness: deciding how the vast expanse of nature can be partitioned into meaningful chunks, stabilizing and structuring what is otherwise disordered. This article explores the aims of classification, their embodiment in medical diagnosis, and the historical traditions of medical classification. It provides a brief overview of the aims and principles of classification and their relevance to contemporary medicine. It also demonstrates how classifications operate as social framing devices that enable and disable communication, assert and refute authority, and are important items for sociological study.

  10. Methodology for classification of the H14 criterion according to the directive 2008/98/EC on waste. Proposal of a biotest battery for the classification of hazardous waste. Ecotoxicological testing with bacterium, algae, crustacean and fish embryo; Metodik foer klassificering av H14-kriteriet i Avfallsfoerordningen. Foerslag till biotestbatteri foer klassificering av farligt avfall. Ekotoxikologisk testning med bakterie, alg, kraeftdjur och fiskembryo

    Energy Technology Data Exchange (ETDEWEB)

    Stiernstroem, Sara; Hemstroem, Kristian; Wik, Ola; Carlsson, Gunnar; Breitholtz, Magnus

    2009-02-15

    Waste, including ashes that can cause ecotoxicological effects, should be classified under criterion H-14 in the Directive on Waste 2008/98/EC. The complex nature of ash production and the fact that it has a complex chemical composition makes ecotoxicological hazard and risk assessment of ashes based on mere chemical analysis insufficient. Biological test systems are thus indispensable tools to support the ecotoxicological characterisation and classification of the properties of ashes. The objectives of this study were (1) to develop a leaching procedure suitable for preparation of water extracts for ecotoxicity testing, and (2) to evaluate an ecotoxicological test battery for the characterisation of ashes. A leaching procedure developed for organic compounds was assumed to be more realistic than existing standard methods for preparation of eluates for ecotoxic tests from complex matrices. A modified version of a recirculation column test, the ER-H method, developed for leaching of nonvolatile organic compounds and validated for PAHs and CPs, was used in this study and compared with the batch test EN 14735 (Characterization of waste - Preparation of waste samples for ecotoxicity tests). The ecotoxicological test battery included species representing different trophic levels; the bacterium Vibrio fisheri, a growth inhibition test with the micro algae Pseudokirchneriella subcapitata formerly known as Selenastrum capricornutum, a larval development test with the copepod Nitocra spinipes and an embryo toxicity test with sebra fish (Danio rerio). These test species show a relatively low sensitivity to elevated salinity levels. This test battery can be used to test a wide variety of matrices (e.g. single chemicals, complex effluents, eluates and sediments), and therefore offers flexible solutions for testing of leachates with differing and difficult properties. Both the ashes and their leachates were also analyzed chemically for organic and inorganic substances. All the

  11. 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.

  12. Ultrasonic Testing

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Hyeong Jun; Kuk, Jeong Han

    2002-02-15

    This book introduces ultrasonic testing, which tells of outline of ultrasonic testing, principle of ultrasonic testing, prosperities of ultrasonic waves, radiographic test and ultrasonic test, basic theory on ultrasonic testing, mode conversion, transmission and diffraction, ultrasonic flaw detection and probe, standard test piece and reference test piece, like KS(JIS) ASME and ASTM, classification and properties of ultrasonic testing, straight beam method, angle beam method, ASME SEC.V.Art.5 ASTMA 388 and KS B 0817 Korean industrial standard.

  13. Classification of Flotation Frothers

    Directory of Open Access Journals (Sweden)

    Jan Drzymala

    2018-02-01

    Full Text Available In this paper, a scheme of flotation frothers classification is presented. The scheme first indicates the physical system in which a frother is present and four of them i.e., pure state, aqueous solution, aqueous solution/gas system and aqueous solution/gas/solid system are distinguished. As a result, there are numerous classifications of flotation frothers. The classifications can be organized into a scheme described in detail in this paper. The frother can be present in one of four physical systems, that is pure state, aqueous solution, aqueous solution/gas and aqueous solution/gas/solid system. It results from the paper that a meaningful classification of frothers relies on choosing the physical system and next feature, trend, parameter or parameters according to which the classification is performed. The proposed classification can play a useful role in characterizing and evaluation of flotation frothers.

  14. Feature-based attention is functionally distinct from relation-based attention: The double dissociation between color-based capture and color-relation-based capture of attention.

    Science.gov (United States)

    Du, Feng; Jiao, Jun

    2016-04-01

    The present study used a spatial blink task and a cuing task to examine the boundary between feature-based capture and relation-based capture. Feature-based capture occurs when distractors match the target feature such as target color. The occurrence of relation-based capture is contingent upon the feature relation between target and distractor (e.g., color relation). The results show that color distractors that match the target-nontarget color relation do not consistently capture attention when they appear outside of the attentional window, but distractors appearing outside the attentional window that match the target color consistently capture attention. In contrast, color distractors that best match the target-nontarget color relation but not the target color, are more likely to capture attention when they appear within the attentional window. Consistently, color cues that match the target-nontarget color relation produce a cuing effect when they appear within the attentional window, while target-color matched cues do not. Such a double dissociation between color-based capture and color-relation-based capture indicates functionally distinct mechanisms for these 2 types of attentional selection. This also indicates that the spatial blink task and the uninformative cuing task are measuring distinctive aspects of involuntary attention. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  15. Using a limited number of dermatomes as a predictor of the 56-dermatome test of the international standards for neurological classification of spinal cord injury in the pediatric population.

    Science.gov (United States)

    Krisa, Laura; Mulcahey, M J; Gaughan, John P; Smith, Brian; Vogel, Lawrence C

    2013-01-01

    For young children with spinal cord injury (SCI), the sensory exam of the International Standards for the Neurological Classification of Spinal Cord Injury (ISNCSCI) is long and arduous, often making it impossible to complete. In this study, we determine whether an abbreviated sensory exam provides comparable information to the full 56-dermatome exam. A total of 726 56-dermatome sensory exams were completed with 190 children and youth with SCI ranging in age from 3 to 21 years. The cohort was randomly split into test and validation groups. For the test group, a principal component analysis (PCA) was carried out separately for pin prick (PP) and light touch (LT) scores. From the PCA, a hierarchical cluster analysis was performed to identify the most influential set of 4, 8, 12, and 16 dermatomes. From the sensory exam data obtained from the validation group, a linear regression was performed to compare the limited-dermatome composite scores to the total 56-dermatome scores. For both LT and PP, the 16-dermatome test resulted in the best fit (0.86 and 0.87, respectively) with the 56-dermatome test and was comprised of dermatomes from both the left (7 dermatomes) and right (9 dermatomes) sides and at least 1 dermatome from each vertebral region bilaterally (cervical, thoracic, lumbar, sacral). A 16-dermatome sensory exam provided a good correlation to the 56-dermatome exam. The shortened exam may be useful for evaluating children with SCI who cannot tolerate the full examination.

  16. 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....

  17. The classification of motor neuron defects in the zebrafish embryo toxicity test (ZFET) as an animal alternative approach to assess developmental neurotoxicity.

    Science.gov (United States)

    Muth-Köhne, Elke; Wichmann, Arne; Delov, Vera; Fenske, Martina

    2012-07-01

    Rodents are widely used to test the developmental neurotoxicity potential of chemical substances. The regulatory test procedures are elaborate and the requirement of numerous animals is ethically disputable. Therefore, non-animal alternatives are highly desirable, but appropriate test systems that meet regulatory demands are not yet available. Hence, we have developed a new developmental neurotoxicity assay based on specific whole-mount immunostainings of primary and secondary motor neurons (using the monoclonal antibodies znp1 and zn8) in zebrafish embryos. By classifying the motor neuron defects, we evaluated the severity of the neurotoxic damage to individual primary and secondary motor neurons caused by chemical exposure and determined the corresponding effect concentration values (EC₅₀). In a proof-of-principle study, we investigated the effects of three model compounds thiocyclam, cartap and disulfiram, which show some neurotoxicity-indicating effects in vertebrates, and the positive controls ethanol and nicotine and the negative controls 3,4-dichloroaniline (3,4-DCA) and triclosan. As a quantitative measure of the neurotoxic potential of the test compounds, we calculated the ratios of the EC₅₀ values for motor neuron defects and the cumulative malformations, as determined in a zebrafish embryo toxicity test (zFET). Based on this index, disulfiram was classified as the most potent and thiocyclam as the least potent developmental neurotoxin. The index also confirmed the control compounds as positive and negative neurotoxicants. Our findings demonstrate that this index can be used to reliably distinguish between neurotoxic and non-neurotoxic chemicals and provide a sound estimate for the neurodevelopmental hazard potential of a chemical. The demonstrated method can be a feasible approach to reduce the number of animals used in developmental neurotoxicity evaluation procedures. Copyright © 2012 Elsevier Inc. All rights reserved.

  18. Test

    DEFF Research Database (Denmark)

    Bendixen, Carsten

    2014-01-01

    Bidrag med en kortfattet, introducerende, perspektiverende og begrebsafklarende fremstilling af begrebet test i det pædagogiske univers.......Bidrag med en kortfattet, introducerende, perspektiverende og begrebsafklarende fremstilling af begrebet test i det pædagogiske univers....

  19. The Application of Classification and Regression Trees for the Triage of Women for Referral to Colposcopy and the Estimation of Risk for Cervical Intraepithelial Neoplasia: A Study Based on 1625 Cases with Incomplete Data from Molecular Tests

    Directory of Open Access Journals (Sweden)

    Abraham Pouliakis

    2015-01-01

    Full Text Available Objective. Nowadays numerous ancillary techniques detecting HPV DNA and mRNA compete with cytology; however no perfect test exists; in this study we evaluated classification and regression trees (CARTs for the production of triage rules and estimate the risk for cervical intraepithelial neoplasia (CIN in cases with ASCUS+ in cytology. Study Design. We used 1625 cases. In contrast to other approaches we used missing data to increase the data volume, obtain more accurate results, and simulate real conditions in the everyday practice of gynecologic clinics and laboratories. The proposed CART was based on the cytological result, HPV DNA typing, HPV mRNA detection based on NASBA and flow cytometry, p16 immunocytochemical expression, and finally age and parous status. Results. Algorithms useful for the triage of women were produced; gynecologists could apply these in conjunction with available examination results and conclude to an estimation of the risk for a woman to harbor CIN expressed as a probability. Conclusions. The most important test was the cytological examination; however the CART handled cases with inadequate cytological outcome and increased the diagnostic accuracy by exploiting the results of ancillary techniques even if there were inadequate missing data. The CART performance was better than any other single test involved in this study.

  20. The Application of Classification and Regression Trees for the Triage of Women for Referral to Colposcopy and the Estimation of Risk for Cervical Intraepithelial Neoplasia: A Study Based on 1625 Cases with Incomplete Data from Molecular Tests.

    Science.gov (United States)

    Pouliakis, Abraham; Karakitsou, Efrossyni; Chrelias, Charalampos; Pappas, Asimakis; Panayiotides, Ioannis; Valasoulis, George; Kyrgiou, Maria; Paraskevaidis, Evangelos; Karakitsos, Petros

    2015-01-01

    Nowadays numerous ancillary techniques detecting HPV DNA and mRNA compete with cytology; however no perfect test exists; in this study we evaluated classification and regression trees (CARTs) for the production of triage rules and estimate the risk for cervical intraepithelial neoplasia (CIN) in cases with ASCUS+ in cytology. We used 1625 cases. In contrast to other approaches we used missing data to increase the data volume, obtain more accurate results, and simulate real conditions in the everyday practice of gynecologic clinics and laboratories. The proposed CART was based on the cytological result, HPV DNA typing, HPV mRNA detection based on NASBA and flow cytometry, p16 immunocytochemical expression, and finally age and parous status. Algorithms useful for the triage of women were produced; gynecologists could apply these in conjunction with available examination results and conclude to an estimation of the risk for a woman to harbor CIN expressed as a probability. The most important test was the cytological examination; however the CART handled cases with inadequate cytological outcome and increased the diagnostic accuracy by exploiting the results of ancillary techniques even if there were inadequate missing data. The CART performance was better than any other single test involved in this study.

  1. Classification of radiological procedures

    International Nuclear Information System (INIS)

    1989-01-01

    A classification for departments in Danish hospitals which use radiological procedures. The classification codes consist of 4 digits, where the first 2 are the codes for the main groups. The first digit represents the procedure's topographical object and the second the techniques. The last 2 digits describe individual procedures. (CLS)

  2. Colombia: Territorial classification

    International Nuclear Information System (INIS)

    Mendoza Morales, Alberto

    1998-01-01

    The article is about the approaches of territorial classification, thematic axes, handling principles and territorial occupation, politician and administrative units and administration regions among other topics. Understanding as Territorial Classification the space distribution on the territory of the country, of the geographical configurations, the human communities, the political-administrative units and the uses of the soil, urban and rural, existent and proposed

  3. Munitions Classification Library

    Science.gov (United States)

    2016-04-04

    members of the community to make their own additions to any, or all, of the classification libraries . The next phase entailed data collection over less......Include area code) 04/04/2016 Final Report August 2014 - August 2015 MUNITIONS CLASSIFICATION LIBRARY Mr. Craig Murray, Parsons Dr. Thomas H. Bell, Leidos

  4. Recursive automatic classification algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Bauman, E V; Dorofeyuk, A A

    1982-03-01

    A variational statement of the automatic classification problem is given. The dependence of the form of the optimal partition surface on the form of the classification objective functional is investigated. A recursive algorithm is proposed for maximising a functional of reasonably general form. The convergence problem is analysed in connection with the proposed algorithm. 8 references.

  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. Spectroscopic classification of transients

    DEFF Research Database (Denmark)

    Stritzinger, M. D.; Fraser, M.; Hummelmose, N. N.

    2017-01-01

    We report the spectroscopic classification of several transients based on observations taken with the Nordic Optical Telescope (NOT) equipped with ALFOSC, over the nights 23-25 August 2017.......We report the spectroscopic classification of several transients based on observations taken with the Nordic Optical Telescope (NOT) equipped with ALFOSC, over the nights 23-25 August 2017....

  7. Automated Decision Tree Classification of Corneal Shape

    Science.gov (United States)

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

    2011-01-01

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

  8. DOE LLW classification rationale

    International Nuclear Information System (INIS)

    Flores, A.Y.

    1991-01-01

    This report was about the rationale which the US Department of Energy had with low-level radioactive waste (LLW) classification. It is based on the Nuclear Regulatory Commission's classification system. DOE site operators met to review the qualifications and characteristics of the classification systems. They evaluated performance objectives, developed waste classification tables, and compiled dose limits on the waste. A goal of the LLW classification system was to allow each disposal site the freedom to develop limits to radionuclide inventories and concentrations according to its own site-specific characteristics. This goal was achieved with the adoption of a performance objectives system based on a performance assessment, with site-specific environmental conditions and engineered disposal systems

  9. Constructing criticality by classification

    DEFF Research Database (Denmark)

    Machacek, Erika

    2017-01-01

    " in the bureaucratic practice of classification: Experts construct material criticality in assessments as they allot information on the materials to the parameters of the assessment framework. In so doing, they ascribe a new set of connotations to the materials, namely supply risk, and their importance to clean energy......, legitimizing a criticality discourse.Specifically, the paper introduces a typology delineating the inferences made by the experts from their produced recommendations in the classification of rare earth element criticality. The paper argues that the classification is a specific process of constructing risk....... It proposes that the expert bureaucratic practice of classification legitimizes (i) the valorisation that was made in the drafting of the assessment framework for the classification, and (ii) political operationalization when enacted that might have (non-)distributive implications for the allocation of public...

  10. A proposal for a test method for assessment of hazard property HP 12 ("Release of an acute toxic gas") in hazardous waste classification - Experience from 49 waste.

    Science.gov (United States)

    Hennebert, Pierre; Samaali, Ismahen; Molina, Pauline

    2016-12-01

    A stepwise method for assessment of the HP 12 is proposed and tested with 49 waste samples. The hazard property HP 12 is defined as "Release of an acute toxic gas": waste which releases acute toxic gases (Acute Tox. 1, 2 or 3) in contact with water or an acid. When a waste contains a substance assigned to one of the following supplemental hazards EUH029, EUH031 and EUH032, it shall be classified as hazardous by HP 12 according to test methods or guidelines (EC, 2014a, 2014b). When the substances with the cited hazard statement codes react with water or an acid, they can release HCl, Cl 2 , HF, HCN, PH 3 , H 2 S, SO 2 (and two other gases very unlikely to be emitted, hydrazoic acid HN 3 and selenium oxide SeO 2 - a solid with low vapor pressure). Hence, a method is proposed:For a set of 49 waste, water addition did not produce gas. Nearly all the solid waste produced a gas in contact with hydrochloric acid in 5 min in an automated calcimeter with a volume >0.1L of gas per kg of waste. Since a plateau of pressure is reached only for half of the samples in 5 min, 6 h trial with calorimetric bombs or glass flasks were done and confirmed the results. Identification of the gases by portable probes showed that most of the tested samples emit mainly CO 2 . Toxic gases are emitted by four waste: metallic dust from the aluminum industry (CO), two air pollution control residue of industrial waste incinerator (H 2 S) and a halogenated solvent (organic volatile(s) compound(s)). HF has not been measured in these trials started before the present definition of HP 12. According to the definition of HP 12, only the H 2 S emission of substances with hazard statement EUH031 is accounted for. In view of the calcium content of the two air pollution control residue, the presence of calcium sulphide (EUH031) can be assumed. These two waste are therefore classified potentially hazardous for HP 12, from a total of 49 waste. They are also classified as hazardous for other properties (HP 7

  11. EXPLORING THE VARIABLE SKY WITH LINEAR. III. CLASSIFICATION OF PERIODIC LIGHT CURVES

    Energy Technology Data Exchange (ETDEWEB)

    Palaversa, Lovro; Eyer, Laurent; Rimoldini, Lorenzo [Observatoire Astronomique de l' Université de Genève, 51 chemin des Maillettes, CH-1290 Sauverny (Switzerland); Ivezić, Željko; Loebman, Sarah; Hunt-Walker, Nicholas; VanderPlas, Jacob; Westman, David; Becker, Andrew C. [Department of Astronomy, University of Washington, P.O. Box 351580, Seattle, WA 98195-1580 (United States); Ruždjak, Domagoj; Sudar, Davor; Božić, Hrvoje [Hvar Observatory, Faculty of Geodesy, Kačićeva 26, 10000 Zagreb (Croatia); Galin, Mario [Faculty of Geodesy, Kačićeva 26, 10000 Zagreb (Croatia); Kroflin, Andrea; Mesarić, Martina; Munk, Petra; Vrbanec, Dijana [Department of Physics, Faculty of Science, University of Zagreb, Bijenička cesta 32, 10000 Zagreb (Croatia); Sesar, Branimir [Division of Physics, Mathematics, and Astronomy, Caltech, Pasadena, CA 91125 (United States); Stuart, J. Scott [Lincoln Laboratory, Massachusetts Institute of Technology, 244 Wood Street, Lexington, MA 02420-9108 (United States); Srdoč, Gregor, E-mail: lovro.palaversa@unige.ch [Saršoni 90, 51216 Viškovo (Croatia); and others

    2013-10-01

    We describe the construction of a highly reliable sample of ∼7000 optically faint periodic variable stars with light curves obtained by the asteroid survey LINEAR across 10,000 deg{sup 2} of the northern sky. The majority of these variables have not been cataloged yet. The sample flux limit is several magnitudes fainter than most other wide-angle surveys; the photometric errors range from ∼0.03 mag at r = 15 to ∼0.20 mag at r = 18. Light curves include on average 250 data points, collected over about a decade. Using Sloan Digital Sky Survey (SDSS) based photometric recalibration of the LINEAR data for about 25 million objects, we selected ∼200,000 most probable candidate variables with r < 17 and visually confirmed and classified ∼7000 periodic variables using phased light curves. The reliability and uniformity of visual classification across eight human classifiers was calibrated and tested using a catalog of variable stars from the SDSS Stripe 82 region and verified using an unsupervised machine learning approach. The resulting sample of periodic LINEAR variables is dominated by 3900 RR Lyrae stars and 2700 eclipsing binary stars of all subtypes and includes small fractions of relatively rare populations such as asymptotic giant branch stars and SX Phoenicis stars. We discuss the distribution of these mostly uncataloged variables in various diagrams constructed with optical-to-infrared SDSS, Two Micron All Sky Survey, and Wide-field Infrared Survey Explorer photometry, and with LINEAR light-curve features. We find that the combination of light-curve features and colors enables classification schemes much more powerful than when colors or light curves are each used separately. An interesting side result is a robust and precise quantitative description of a strong correlation between the light-curve period and color/spectral type for close and contact eclipsing binary stars (β Lyrae and W UMa): as the color-based spectral type varies from K4 to F5, the

  12. Evaluation of the 8th TNM classification on p16-positive oropharyngeal squamous cell carcinomas in the Netherlands, and the importance of additional HPV DNA-testing.

    Science.gov (United States)

    Nauta, I H; Rietbergen, M M; van Bokhoven, A A J D; Bloemena, E; Witte, B I; Heideman, D A M; Baatenburg de Jong, R J; Brakenhoff, R H; Leemans, C R

    2018-02-09

    Oropharyngeal squamous cell carcinomas (OPSCCs) are traditionally caused by smoking and excessive alcohol consumption. However, in the last decades high-risk human papillomavirus (HR-HPV) infections play an increasingly important role in tumorigenesis. HPV-driven OPSCCs are known to have a more favorable prognosis, which has led to important and marked changes in the recently released TNM-8. In this edition, OPSCCs are divided based on p16-immunostaining, with p16-overexpression as surrogate marker for the presence of HPV. The aims of this study are to evaluate TNM-8 on a Dutch consecutive cohort of patients with p16-positive OPSCC and to determine the relevance of additional HPV DNA-testing. All OPSCC patients without distant metastases at diagnosis and treated with curative intent at VU University Medical Center (2000-2015) and Erasmus Medical Center (2000-2006) were included (N = 1,204). HPV-status was established by p16-immunostaining followed by HPV DNA-PCR on the p16-immunopositive cases. We compared TNM-7 and TNM-8 using the Harrell's C index. In total, 388 of 1,204 (32.2%) patients were p16-immunopositive. In these patients, TNM-8 had a markedly better predictive prognostic power than TNM-7 (Harrell's C index 0.63 versus 0.53). Of the 388 p16-positive OPSCCs, 48 tumors (12.4%) were HPV DNA-negative. This subgroup had distinct demographic, clinical and morphologic characteristics and showed a significantly worse five-year overall survival compared to the HPV DNA-positive tumors (P HPV DNA-negative subgroup with distinct features and a worse overall survival, indicating the importance to perform additional HPV DNA-testing when predicting prognosis and particularly for selecting patients for de-intensified treatment regimens. © The Author 2018. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  13. 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)

  14. Image Classification Workflow Using Machine Learning Methods

    Science.gov (United States)

    Christoffersen, M. S.; Roser, M.; Valadez-Vergara, R.; Fernández-Vega, J. A.; Pierce, S. A.; Arora, R.

    2016-12-01

    Recent increases in the availability and quality of remote sensing datasets have fueled an increasing number of scientifically significant discoveries based on land use classification and land use change analysis. However, much of the software made to work with remote sensing data products, specifically multispectral images, is commercial and often prohibitively expensive. The free to use solutions that are currently available come bundled up as small parts of much larger programs that are very susceptible to bugs and difficult to install and configure. What is needed is a compact, easy to use set of tools to perform land use analysis on multispectral images. To address this need, we have developed software using the Python programming language with the sole function of land use classification and land use change analysis. We chose Python to develop our software because it is relatively readable, has a large body of relevant third party libraries such as GDAL and Spectral Python, and is free to install and use on Windows, Linux, and Macintosh operating systems. In order to test our classification software, we performed a K-means unsupervised classification, Gaussian Maximum Likelihood supervised classification, and a Mahalanobis Distance based supervised classification. The images used for testing were three Landsat rasters of Austin, Texas with a spatial resolution of 60 meters for the years of 1984 and 1999, and 30 meters for the year 2015. The testing dataset was easily downloaded using the Earth Explorer application produced by the USGS. The software should be able to perform classification based on any set of multispectral rasters with little to no modification. Our software makes the ease of land use classification using commercial software available without an expensive license.

  15. Classification of movement disorders.

    Science.gov (United States)

    Fahn, Stanley

    2011-05-01

    The classification of movement disorders has evolved. Even the terminology has shifted, from an anatomical one of extrapyramidal disorders to a phenomenological one of movement disorders. The history of how this shift came about is described. The history of both the definitions and the classifications of the various neurologic conditions is then reviewed. First is a review of movement disorders as a group; then, the evolving classifications for 3 of them--parkinsonism, dystonia, and tremor--are covered in detail. Copyright © 2011 Movement Disorder Society.

  16. Update on diabetes classification.

    Science.gov (United States)

    Thomas, Celeste C; Philipson, Louis H

    2015-01-01

    This article highlights the difficulties in creating a definitive classification of diabetes mellitus in the absence of a complete understanding of the pathogenesis of the major forms. This brief review shows the evolving nature of the classification of diabetes mellitus. No classification scheme is ideal, and all have some overlap and inconsistencies. The only diabetes in which it is possible to accurately diagnose by DNA sequencing, monogenic diabetes, remains undiagnosed in more than 90% of the individuals who have diabetes caused by one of the known gene mutations. The point of classification, or taxonomy, of disease, should be to give insight into both pathogenesis and treatment. It remains a source of frustration that all schemes of diabetes mellitus continue to fall short of this goal. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. 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.

  18. CLASSIFICATION OF VIRUSES

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. CLASSIFICATION OF VIRUSES. On basis of morphology. On basis of chemical composition. On basis of structure of genome. On basis of mode of replication. Notes:

  19. Towards secondary fingerprint classification

    CSIR Research Space (South Africa)

    Msiza, IS

    2011-07-01

    Full Text Available an accuracy figure of 76.8%. This small difference between the two figures is indicative of the validity of the proposed secondary classification module. Keywords?fingerprint core; fingerprint delta; primary classifi- cation; secondary classification I..., namely, the fingerprint core and the fingerprint delta. Forensically, a fingerprint core is defined as the innermost turning point where the fingerprint ridges form a loop, while the fingerprint delta is defined as the point where these ridges form a...

  20. 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...... classification model, and wedemonstrate empirically that the accuracy of the proposed model issignificantly higher than the accuracy of other probabilisticclassifiers....

  1. 78 FR 68983 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-11-18

    ...-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing... regulations to allow for the addition of an optional cotton futures classification procedure--identified and... response to requests from the U.S. cotton industry and ICE, AMS will offer a futures classification option...

  2. 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).

  3. Tests for digital classification of orbital and suborbital images in multitemporal examination of recent PCH - Sao Simao, Alegre, ES; Ensaios de classificacao digital de imagens orbital e suborbital na analise multitemporal da recente barragem PCH - Sao Simao

    Energy Technology Data Exchange (ETDEWEB)

    Moraes, Aldeir de O.; Silva, Kmila G. da; Andrade, Monique B.; Areas, Mario L.; Santos, Alexander R. dos [Universidade Federal do Espirito Santo (CCA/UFES), Alegre, ES (Brazil). Centro de Ciencias Agrarias; Ferrari, Jeferson L. [Instituto Federal do Espirito Santo (IFES), Alegre, ES (Brazil)], E-mail: jlferrari@ifes.edu.br

    2010-07-01

    PCH - Sao Simao is a brand new development, located in Alegre - ES, aiming to produce 27 MW of electricity by damming the Rio Itapemirim left arm. The area has a range of thematic classes related to changes both in the aquatic environment and in the adjacent land. The aim of this paper is to present results of tests carried out in Spring, for defining the best parameters resulting from the supervised classification methods, Maxver and Euclidean Distance on two high-resolution images, a suborbital (Ortofoto/2007) and other characteristics (Geoeye/2009) that portray, respectively, the moments leading up to and what happened to that building. It contains six thematic categories: watercourse; Exposed land, pasture, forest fragmentation; material rocky and unpaved roads. The results showed that the classifier that performed better was the Maxver, with average performance and confusion average respectively 85.45% and 15.55% f or the image suborbital (Ortofoto/2007) and 85.13% and 14.87% for the orbital image (Geoeye/2009). Moreover, he realized the importance of applying the technique of linear filtering low-pass 7 x 7, raising the average performance of 67.09% and 84.45% stop reducing confusion average of 32.91% to 15.55%. (author)

  4. Examination of breath alcohol concentration (BrAC) levels, alcohol use disorders identification test (AUDIT-C) classification, and intended plans for getting home among bar-attending college students.

    Science.gov (United States)

    Martin, Ryan J; Chaney, Beth H; Cremeens-Matthews, Jennifer

    2015-06-01

    The college student population is one of the heaviest drinking demographic groups in the US and impaired driving is a serious alcohol-related problem. The objective of this study is to better understand the relationship between alcohol-related behaviors and "plans to get home" among a sample of college students. We conducted four anonymous field studies to examine associations between breath alcohol concentration (BrAC) levels, Alcohol Use Disorders Identification Test (AUDIT-C) classification, and plans for getting home among a sample of bar-attending college students (N = 713). The vast majority of participants in our sample (approximately 95%) were not intending to drive and the average BrAC% of those intending to drive was .041. Our one-way ANOVAs indicated that (1) participants classified by the AUDIT-C as not having an alcohol problem had a significantly lower BrAC% than those classified as having a potential problem and (2) participants planning to drive had a significantly lower BrAC% than those with a plan that did not involve them driving and those without a plan to get home. Although it is encouraging that most of our sample was not intending to drive, it is important to continue to attempt to reduce impaired driving in this population. This study helps college health professionals and administrators to better understand the relationship between alcohol-related behaviors and plans to get home among college students. © American Academy of Addiction Psychiatry.

  5. Employing the International Classification of Functioning, Disability and Health framework to capture user feedback in the design and testing stage of development of home-based arm rehabilitation technology.

    Science.gov (United States)

    Sivan, Manoj; Gallagher, Justin; Holt, Ray; Weightman, Andrew; O'Connor, Rory; Levesley, Martin

    2016-01-01

    The purpose of this study was to evaluate the International Classification of Functioning, Disability and Health (ICF) as a framework to ensure that key aspects of user feedback are identified in the design and testing stages of development of a home-based upper limb rehabilitation system. Seventeen stroke survivors with residual upper limb weakness, and seven healthcare professionals with expertise in stroke rehabilitation, were enrolled in the user-centered design process. Through semi-structured interviews, they provided feedback on the hardware, software and impact of a home-based rehabilitation device to facilitate self-managed arm exercise. Members of the multidisciplinary clinical and engineering research team, based on previous experience and existing literature in user-centred design, developed the topic list for the interviews. Meaningful concepts were extracted from participants' interviews based on existing ICF linking rules and matched to categories within the ICF Comprehensive Core Set for stroke. Most of the interview concepts (except personal factors) matched the existing ICF Comprehensive Core Set categories. Personal factors that emerged from interviews e.g. gender, age, interest, compliance, motivation, choice and convenience that might determine device usability are yet to be categorised within the ICF framework and hence could not be matched to a specific Core Set category.

  6. 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...

  7. Integrating Globality and Locality for Robust Representation Based Classification

    Directory of Open Access Journals (Sweden)

    Zheng Zhang

    2014-01-01

    Full Text Available The representation based classification method (RBCM has shown huge potential for face recognition since it first emerged. Linear regression classification (LRC method and collaborative representation classification (CRC method are two well-known RBCMs. LRC and CRC exploit training samples of each class and all the training samples to represent the testing sample, respectively, and subsequently conduct classification on the basis of the representation residual. LRC method can be viewed as a “locality representation” method because it just uses the training samples of each class to represent the testing sample and it cannot embody the effectiveness of the “globality representation.” On the contrary, it seems that CRC method cannot own the benefit of locality of the general RBCM. Thus we propose to integrate CRC and LRC to perform more robust representation based classification. The experimental results on benchmark face databases substantially demonstrate that the proposed method achieves high classification accuracy.

  8. Fuzzy set classifier for waste classification tracking

    International Nuclear Information System (INIS)

    Gavel, D.T.

    1992-01-01

    We have developed an expert system based on fuzzy logic theory to fuse the data from multiple sensors and make classification decisions for objects in a waste reprocessing stream. Fuzzy set theory has been applied in decision and control applications with some success, particularly by the Japanese. We have found that the fuzzy logic system is rather easy to design and train, a feature that can cut development costs considerably. With proper training, the classification accuracy is quite high. We performed several tests sorting radioactive test samples using a gamma spectrometer to compare fuzzy logic to more conventional sorting schemes

  9. Cosmetics Europe compilation of historical serious eye damage/eye irritation in vivo data analysed by drivers of classification to support the selection of chemicals for development and evaluation of alternative methods/strategies: the Draize eye test Reference Database (DRD).

    Science.gov (United States)

    Barroso, João; Pfannenbecker, Uwe; Adriaens, Els; Alépée, Nathalie; Cluzel, Magalie; De Smedt, Ann; Hibatallah, Jalila; Klaric, Martina; Mewes, Karsten R; Millet, Marion; Templier, Marie; McNamee, Pauline

    2017-02-01

    A thorough understanding of which of the effects assessed in the in vivo Draize eye test are responsible for driving UN GHS/EU CLP classification is critical for an adequate selection of chemicals to be used in the development and/or evaluation of alternative methods/strategies and for properly assessing their predictive capacity and limitations. For this reason, Cosmetics Europe has compiled a database of Draize data (Draize eye test Reference Database, DRD) from external lists that were created to support past validation activities. This database contains 681 independent in vivo studies on 634 individual chemicals representing a wide range of chemical classes. A description of all the ocular effects observed in vivo, i.e. degree of severity and persistence of corneal opacity (CO), iritis, and/or conjunctiva effects, was added for each individual study in the database, and the studies were categorised according to their UN GHS/EU CLP classification and the main effect driving the classification. An evaluation of the various in vivo drivers of classification compiled in the database was performed to establish which of these are most important from a regulatory point of view. These analyses established that the most important drivers for Cat 1 Classification are (1) CO mean ≥ 3 (days 1-3) (severity) and (2) CO persistence on day 21 in the absence of severity, and those for Cat 2 classification are (3) CO mean ≥ 1 and (4) conjunctival redness mean ≥ 2. Moreover, it is shown that all classifiable effects (including persistence and CO = 4) should be present in ≥60 % of the animals to drive a classification. As a consequence, our analyses suggest the need for a critical revision of the UN GHS/EU CLP decision criteria for the Cat 1 classification of chemicals. Finally, a number of key criteria are identified that should be taken into consideration when selecting reference chemicals for the development, evaluation and/or validation of alternative methods and

  10. Cellular image classification

    CERN Document Server

    Xu, Xiang; Lin, Feng

    2017-01-01

    This book introduces new techniques for cellular image feature extraction, pattern recognition and classification. The authors use the antinuclear antibodies (ANAs) in patient serum as the subjects and the Indirect Immunofluorescence (IIF) technique as the imaging protocol to illustrate the applications of the described methods. Throughout the book, the authors provide evaluations for the proposed methods on two publicly available human epithelial (HEp-2) cell datasets: ICPR2012 dataset from the ICPR'12 HEp-2 cell classification contest and ICIP2013 training dataset from the ICIP'13 Competition on cells classification by fluorescent image analysis. First, the reading of imaging results is significantly influenced by one’s qualification and reading systems, causing high intra- and inter-laboratory variance. The authors present a low-order LP21 fiber mode for optical single cell manipulation and imaging staining patterns of HEp-2 cells. A focused four-lobed mode distribution is stable and effective in optical...

  11. 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...

  12. Bosniak Classification system

    DEFF Research Database (Denmark)

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

    2014-01-01

    Background: The Bosniak classification is a diagnostic tool for the differentiation of cystic changes in the kidney. The process of categorizing renal cysts may be challenging, involving a series of decisions that may affect the final diagnosis and clinical outcome such as surgical management....... Purpose: To investigate the inter- and intra-observer agreement among experienced uroradiologists when categorizing complex renal cysts according to the Bosniak classification. Material and Methods: The original categories of 100 cystic renal masses were chosen as “Gold Standard” (GS), established...... to the calculated weighted κ all readers performed “very good” for both inter-observer and intra-observer variation. Most variation was seen in cysts catagorized as Bosniak II, IIF, and III. These results show that radiologists who evaluate complex renal cysts routinely may apply the Bosniak classification...

  13. Acoustic classification of dwellings

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2014-01-01

    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...... exchanging experiences about constructions fulfilling different classes, reducing trade barriers, and finally increasing the sound insulation of dwellings.......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...

  14. Classification of iconic images

    OpenAIRE

    Zrianina, Mariia; Kopf, Stephan

    2016-01-01

    Iconic images represent an abstract topic and use a presentation that is intuitively understood within a certain cultural context. For example, the abstract topic “global warming” may be represented by a polar bear standing alone on an ice floe. Such images are widely used in media and their automatic classification can help to identify high-level semantic concepts. This paper presents a system for the classification of iconic images. It uses a variation of the Bag of Visual Words approach wi...

  15. Casemix classification systems.

    Science.gov (United States)

    Fetter, R B

    1999-01-01

    The idea of using casemix classification to manage hospital services is not new, but has been limited by available technology. It was not until after the introduction of Medicare in the United States in 1965 that serious attempts were made to measure hospital production in order to contain spiralling costs. This resulted in a system of casemix classification known as diagnosis related groups (DRGs). This paper traces the development of DRGs and their evolution from the initial version to the All Patient Refined DRGs developed in 1991.

  16. 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.

  17. 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...

  18. Long range echo classification for minehunting sonars

    NARCIS (Netherlands)

    Theije, P.A.M. de; Groen, J.; Sabel, J.C.

    2006-01-01

    This paper focesus on single-ping classification of sea mines, at a range of about 400 m, and combining a hull mounted sonar (HMS) and a propelled variable-depth sonar (PDVS). The deleoped classifier is trained and tested on a set of simulated realistic echoes of mines and non-mines. As the mines

  19. 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.

  20. Ecosystem classification, Chapter 2

    Science.gov (United States)

    M.J. Robin-Abbott; L.H. Pardo

    2011-01-01

    The ecosystem classification in this report is based on the ecoregions developed through the Commission for Environmental Cooperation (CEC) for North America (CEC 1997). Only ecosystems that occur in the United States are included. CEC ecoregions are described, with slight modifications, below (CEC 1997) and shown in Figures 2.1 and 2.2. We chose this ecosystem...

  1. The classification of phocomelia.

    Science.gov (United States)

    Tytherleigh-Strong, G; Hooper, G

    2003-06-01

    We studied 24 patients with 44 phocomelic upper limbs. Only 11 limbs could be grouped in the classification system of Frantz and O' Rahilly. The non-classifiable limbs were further studied and their characteristics identified. It is confirmed that phocomelia is not an intercalary defect.

  2. Principles for ecological classification

    Science.gov (United States)

    Dennis H. Grossman; Patrick Bourgeron; Wolf-Dieter N. Busch; David T. Cleland; William Platts; G. Ray; C. Robins; Gary Roloff

    1999-01-01

    The principal purpose of any classification is to relate common properties among different entities to facilitate understanding of evolutionary and adaptive processes. In the context of this volume, it is to facilitate ecosystem stewardship, i.e., to help support ecosystem conservation and management objectives.

  3. Classification, confusion and misclassification

    African Journals Online (AJOL)

    The classification of objects and phenomena in science and nature has fascinated academics since Carl Linnaeus, the Swedish botanist and zoologist, created his binomial description of living things in the 1700s and probably long before in accounts of others in textbooks long since gone. It must have concerned human ...

  4. Classifications in popular music

    NARCIS (Netherlands)

    van Venrooij, A.; Schmutz, V.; Wright, J.D.

    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

  5. 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…

  6. 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

  7. Classification in Medical Imaging

    DEFF Research Database (Denmark)

    Chen, Chen

    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...... on characterizing human faces and emphysema disease in lung CT images....

  8. 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…

  9. NOUN CLASSIFICATION IN ESAHIE

    African Journals Online (AJOL)

    The present work deals with noun classification in Esahie (Kwa, Niger ... phonological information influences the noun (form) class system of Esahie. ... between noun classes and (grammatical) Gender is interrogated (in the light of ..... the (A) argument6 precedes the verb and the (P) argument7 follows the verb in a simple.

  10. Dynamic Latent Classification Model

    DEFF Research Database (Denmark)

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

    as 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...

  11. 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...

  12. Event Classification using Concepts

    NARCIS (Netherlands)

    Boer, M.H.T. de; Schutte, K.; Kraaij, W.

    2013-01-01

    The semantic gap is one of the challenges in the GOOSE project. In this paper a Semantic Event Classification (SEC) system is proposed as an initial step in tackling the semantic gap challenge in the GOOSE project. This system uses semantic text analysis, multiple feature detectors using the BoW

  13. MULTI-TEMPORAL CLASSIFICATION AND CHANGE DETECTION USING UAV IMAGES

    Directory of Open Access Journals (Sweden)

    S. Makuti

    2018-05-01

    Full Text Available In this paper different methodologies for the classification and change detection of UAV image blocks are explored. UAV is not only the cheapest platform for image acquisition but it is also the easiest platform to operate in repeated data collections over a changing area like a building construction site. Two change detection techniques have been evaluated in this study: the pre-classification and the post-classification algorithms. These methods are based on three main steps: feature extraction, classification and change detection. A set of state of the art features have been used in the tests: colour features (HSV, textural features (GLCM and 3D geometric features. For classification purposes Conditional Random Field (CRF has been used: the unary potential was determined using the Random Forest algorithm while the pairwise potential was defined by the fully connected CRF. In the performed tests, different feature configurations and settings have been considered to assess the performance of these methods in such challenging task. Experimental results showed that the post-classification approach outperforms the pre-classification change detection method. This was analysed using the overall accuracy, where by post classification have an accuracy of up to 62.6 % and the pre classification change detection have an accuracy of 46.5 %. These results represent a first useful indication for future works and developments.

  14. Classification of parotidectomy: a proposed modification to the European Salivary Gland Society classification system.

    Science.gov (United States)

    Wong, Wai Keat; Shetty, Subhaschandra

    2017-08-01

    Parotidectomy remains the mainstay of treatment for both benign and malignant lesions of the parotid gland. There exists a wide range of possible surgical options in parotidectomy in terms of extent of parotid tissue removed. There is increasing need for uniformity of terminology resulting from growing interest in modifications of the conventional parotidectomy. It is, therefore, of paramount importance for a standardized classification system in describing extent of parotidectomy. Recently, the European Salivary Gland Society (ESGS) proposed a novel classification system for parotidectomy. The aim of this study is to evaluate this system. A classification system proposed by the ESGS was critically re-evaluated and modified to increase its accuracy and its acceptability. Modifications mainly focused on subdividing Levels I and II into IA, IB, IIA, and IIB. From June 2006 to June 2016, 126 patients underwent 130 parotidectomies at our hospital. The classification system was tested in that cohort of patient. While the ESGS classification system is comprehensive, it does not cover all possibilities. The addition of Sublevels IA, IB, IIA, and IIB may help to address some of the clinical situations seen and is clinically relevant. We aim to test the modified classification system for partial parotidectomy to address some of the challenges mentioned.

  15. NEW CLASSIFICATION OF ECOPOLICES

    Directory of Open Access Journals (Sweden)

    VOROBYOV V. V.

    2016-09-01

    Full Text Available Problem statement. Ecopolices are the newest stage of the urban planning. They have to be consideredsuchas material and energy informational structures, included to the dynamic-evolutionary matrix netsofex change processes in the ecosystems. However, there are not made the ecopolice classifications, developing on suchapproaches basis. And this determined the topicality of the article. Analysis of publications on theoretical and applied aspects of the ecopolices formation showed, that the work on them is managed mainly in the context of the latest scientific and technological achievements in the various knowledge fields. These settlements are technocratic. They are connected with the morphology of space, network structures of regional and local natural ecosystems, without independent stability, can not exist without continuous man support. Another words, they do not work in with an ecopolices idea. It is come to a head for objective, symbiotic searching of ecopolices concept with the development of their classifications. Purpose statement is to develop the objective evidence for ecopolices and to propose their new classification. Conclusion. On the base of the ecopolices classification have to lie an elements correlation idea of their general plans and men activity type according with natural mechanism of accepting, reworking and transmission of material, energy and information between geo-ecosystems, planet, man, ecopolices material part and Cosmos. New ecopolices classification should be based on the principles of multi-dimensional, time-spaced symbiotic clarity with exchange ecosystem networks. The ecopolice function with this approach comes not from the subjective anthropocentric economy but from the holistic objective of Genesis paradigm. Or, otherwise - not from the Consequence, but from the Cause.

  16. 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.

  17. Classification across gene expression microarray studies

    Directory of Open Access Journals (Sweden)

    Kuner Ruprecht

    2009-12-01

    Full Text Available Abstract Background The increasing number of gene expression microarray studies represents an important resource in biomedical research. As a result, gene expression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive and histological grade (low/high of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM, predictive analysis of microarrays (PAM, random forest (RF and k-top scoring pairs (kTSP. Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing. Results For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In

  18. 78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-09-09

    ... Service 7 CFR Part 27 [AMS-CN-13-0043] RIN 0581-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing Service, USDA. ACTION: Proposed rule. SUMMARY: The... optional cotton futures classification procedure--identified and known as ``registration'' by the U.S...

  19. A Robust Geometric Model for Argument Classification

    Science.gov (United States)

    Giannone, Cristina; Croce, Danilo; Basili, Roberto; de Cao, Diego

    Argument classification is the task of assigning semantic roles to syntactic structures in natural language sentences. Supervised learning techniques for frame semantics have been recently shown to benefit from rich sets of syntactic features. However argument classification is also highly dependent on the semantics of the involved lexicals. Empirical studies have shown that domain dependence of lexical information causes large performance drops in outside domain tests. In this paper a distributional approach is proposed to improve the robustness of the learning model against out-of-domain lexical phenomena.

  20. PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING

    International Nuclear Information System (INIS)

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

    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 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.

  1. PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING

    Energy Technology Data Exchange (ETDEWEB)

    Lochner, Michelle; Peiris, Hiranya V.; Lahav, Ofer; Winter, Max K. [Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT (United Kingdom); McEwen, Jason D., E-mail: dr.michelle.lochner@gmail.com [Mullard Space Science Laboratory, University College London, Surrey RH5 6NT (United Kingdom)

    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. 32 CFR 2700.22 - Classification guides.

    Science.gov (United States)

    2010-07-01

    ... SECURITY INFORMATION REGULATIONS Derivative Classification § 2700.22 Classification guides. OMSN shall... direct derivative classification, shall identify the information to be protected in specific and uniform...

  3. DTI measurements for Alzheimer’s classification

    Science.gov (United States)

    Maggipinto, Tommaso; Bellotti, Roberto; Amoroso, Nicola; Diacono, Domenico; Donvito, Giacinto; Lella, Eufemia; Monaco, Alfonso; Antonella Scelsi, Marzia; Tangaro, Sabina; Disease Neuroimaging Initiative, Alzheimer's.

    2017-03-01

    Diffusion tensor imaging (DTI) is a promising imaging technique that provides insight into white matter microstructure integrity and it has greatly helped identifying white matter regions affected by Alzheimer’s disease (AD) in its early stages. DTI can therefore be a valuable source of information when designing machine-learning strategies to discriminate between healthy control (HC) subjects, AD patients and subjects with mild cognitive impairment (MCI). Nonetheless, several studies have reported so far conflicting results, especially because of the adoption of biased feature selection strategies. In this paper we firstly analyzed DTI scans of 150 subjects from the Alzheimer’s disease neuroimaging initiative (ADNI) database. We measured a significant effect of the feature selection bias on the classification performance (p-value  informative content provided by DTI measurements for AD classification. Classification performances and biological insight, concerning brain regions related to the disease, provided by cross-validation analysis were both confirmed on the independent test.

  4. Towards Automatic Classification of Wikipedia Content

    Science.gov (United States)

    Szymański, Julian

    Wikipedia - the Free Encyclopedia encounters the problem of proper classification of new articles everyday. The process of assignment of articles to categories is performed manually and it is a time consuming task. It requires knowledge about Wikipedia structure, which is beyond typical editor competence, which leads to human-caused mistakes - omitting or wrong assignments of articles to categories. The article presents application of SVM classifier for automatic classification of documents from The Free Encyclopedia. The classifier application has been tested while using two text representations: inter-documents connections (hyperlinks) and word content. The results of the performed experiments evaluated on hand crafted data show that the Wikipedia classification process can be partially automated. The proposed approach can be used for building a decision support system which suggests editors the best categories that fit new content entered to Wikipedia.

  5. Exploring different approaches for music genre classification

    Directory of Open Access Journals (Sweden)

    Antonio Jose Homsi Goulart

    2012-07-01

    Full Text Available In this letter, we present different approaches for music genre classification. The proposed techniques, which are composed of a feature extraction stage followed by a classification procedure, explore both the variations of parameters used as input and the classifier architecture. Tests were carried out with three styles of music, namely blues, classical, and lounge, which are considered informally by some musicians as being “big dividers” among music genres, showing the efficacy of the proposed algorithms and establishing a relationship between the relevance of each set of parameters for each music style and each classifier. In contrast to other works, entropies and fractal dimensions are the features adopted for the classifications.

  6. Music genre classification using temporal domain features

    Science.gov (United States)

    Shiu, Yu; Kuo, C.-C. Jay

    2004-10-01

    Music genre provides an efficient way to index songs in the music database, and can be used as an effective means to retrieval music of a similar type, i.e. content-based music retrieval. In addition to other features, the temporal domain features of a music signal are exploited so as to increase the classification rate in this research. Three temporal techniques are examined in depth. First, the hidden Markov model (HMM) is used to emulate the time-varying properties of music signals. Second, to further increase the classification rate, we propose another feature set that focuses on the residual part of music signals. Third, the overall classification rate is enhanced by classifying smaller segments from a test material individually and making decision via majority voting. Experimental results are given to demonstrate the performance of the proposed techniques.

  7. Random forests for classification in ecology

    Science.gov (United States)

    Cutler, D.R.; Edwards, T.C.; 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.

  8. A proposed United States resource classification system

    International Nuclear Information System (INIS)

    Masters, C.D.

    1980-01-01

    Energy is a world-wide problem calling for world-wide communication to resolve the many supply and distribution problems. Essential to a communication problem are a definition and comparability of elements being communicated. The US Geological Survey, with the co-operation of the US Bureau of Mines and the US Department of Energy, has devised a classification system for all mineral resources, the principles of which, it is felt, offer the possibility of world communication. At present several other systems, extant or under development (Potential Gas Committee of the USA, United Nations Resource Committee, and the American Society of Testing and Materials) are internally consistent and provide easy communication linkage. The system in use by the uranium community in the United States of America, however, ties resource quantities to forward-cost dollar values rendering them inconsistent with other classifications and therefore not comparable. This paper develops the rationale for the new USGS resource classification and notes its benefits relative to a forward-cost classification and its relationship specifically to other current classifications. (author)

  9. IAEA Classification of Uranium Deposits

    International Nuclear Information System (INIS)

    Bruneton, Patrice

    2014-01-01

    Classifications of uranium deposits follow two general approaches, focusing on: • descriptive features such as the geotectonic position, the host rock type, the orebody morphology, …… : « geologic classification »; • or on genetic aspects: « genetic classification »

  10. Classification of Osteogenesis Imperfecta revisited

    NARCIS (Netherlands)

    van Dijk, F. S.; Pals, G.; van Rijn, R. R.; Nikkels, P. G. J.; Cobben, J. M.

    2010-01-01

    In 1979 Sillence proposed a classification of Osteogenesis Imperfecta (OI) in OI types I, II, III and IV. In 2004 and 2007 this classification was expanded with OI types V-VIII because of distinct clinical features and/or different causative gene mutations. We propose a revised classification of OI

  11. 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...... and contrasts that to special classifications. Argues for the use of general classifications to provide access to collections nationally and internationally....

  12. [Headache: classification and diagnosis].

    Science.gov (United States)

    Carbaat, P A T; Couturier, E G M

    2016-11-01

    There are many types of headache and, moreover, many people have different types of headache at the same time. Adequate treatment is possible only on the basis of the correct diagnosis. Technically and in terms of content the current diagnostics process for headache is based on the 'International Classification of Headache Disorders' (ICHD-3-beta) that was produced under the auspices of the International Headache Society. This classification is based on a distinction between primary and secondary headaches. The most common primary headache types are the tension type headache, migraine and the cluster headache. Application of uniform diagnostic concepts is essential to come to the most appropriate treatment of the various types of headache.

  13. Sound classification of dwellings

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2012-01-01

    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...... is 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...

  14. Granular loess classification based

    International Nuclear Information System (INIS)

    Browzin, B.S.

    1985-01-01

    This paper discusses how loess might be identified by two index properties: the granulometric composition and the dry unit weight. These two indices are necessary but not always sufficient for identification of loess. On the basis of analyses of samples from three continents, it was concluded that the 0.01-0.5-mm fraction deserves the name loessial fraction. Based on the loessial fraction concept, a granulometric classification of loess is proposed. A triangular chart is used to classify loess

  15. Classification and regression trees

    CERN Document Server

    Breiman, Leo; Olshen, Richard A; Stone, Charles J

    1984-01-01

    The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

  16. CLASSIFICATION OF CRIMINAL GROUPS

    OpenAIRE

    Natalia Romanova

    2013-01-01

    New types of criminal groups are emerging in modern society.  These types have their special criminal subculture. The research objective is to develop new parameters of classification of modern criminal groups, create a new typology of criminal groups and identify some features of their subculture. Research methodology is based on the system approach that includes using the method of analysis of documentary sources (materials of a criminal case), method of conversations with themembers of the...

  17. Decimal Classification Editions

    Directory of Open Access Journals (Sweden)

    Zenovia Niculescu

    2009-01-01

    Full Text Available The study approaches the evolution of Dewey Decimal Classification editions from the perspective of updating the terminology, reallocating and expanding the main and auxilary structure of Dewey indexing language. The comparative analysis of DDC editions emphasizes the efficiency of Dewey scheme from the point of view of improving the informational offer, through basic index terms, revised and developed, as well as valuing the auxilary notations.

  18. Decimal Classification Editions

    OpenAIRE

    Zenovia Niculescu

    2009-01-01

    The study approaches the evolution of Dewey Decimal Classification editions from the perspective of updating the terminology, reallocating and expanding the main and auxilary structure of Dewey indexing language. The comparative analysis of DDC editions emphasizes the efficiency of Dewey scheme from the point of view of improving the informational offer, through basic index terms, revised and developed, as well as valuing the auxilary notations.

  19. Classifications of track structures

    International Nuclear Information System (INIS)

    Paretzke, H.G.

    1984-01-01

    When ionizing particles interact with matter they produce random topological structures of primary activations which represent the initial boundary conditions for all subsequent physical, chemical and/or biological reactions. There are two important aspects of research on such track structures, namely their experimental or theoretical determination on one hand and the quantitative classification of these complex structures which is a basic pre-requisite for the understanding of mechanisms of radiation actions. This paper deals only with the latter topic, i.e. the problems encountered in and possible approaches to quantitative ordering and grouping of these multidimensional objects by their degrees of similarity with respect to their efficiency in producing certain final radiation effects, i.e. to their ''radiation quality.'' Various attempts of taxonometric classification with respect to radiation efficiency have been made in basic and applied radiation research including macro- and microdosimetric concepts as well as track entities and stopping power based theories. In this paper no review of those well-known approaches is given but rather an outline and discussion of alternative methods new to this field of radiation research which have some very promising features and which could possibly solve at least some major classification problems

  20. An automated cirrus classification

    Science.gov (United States)

    Gryspeerdt, Edward; Quaas, Johannes; Goren, Tom; Klocke, Daniel; Brueck, Matthias

    2018-05-01

    Cirrus clouds play an important role in determining the radiation budget of the earth, but many of their properties remain uncertain, particularly their response to aerosol variations and to warming. Part of the reason for this uncertainty is the dependence of cirrus cloud properties on the cloud formation mechanism, which itself is strongly dependent on the local meteorological conditions. In this work, a classification system (Identification and Classification of Cirrus or IC-CIR) is introduced to identify cirrus clouds by the cloud formation mechanism. Using reanalysis and satellite data, cirrus clouds are separated into four main types: orographic, frontal, convective and synoptic. Through a comparison to convection-permitting model simulations and back-trajectory-based analysis, it is shown that these observation-based regimes can provide extra information on the cloud-scale updraughts and the frequency of occurrence of liquid-origin ice, with the convective regime having higher updraughts and a greater occurrence of liquid-origin ice compared to the synoptic regimes. Despite having different cloud formation mechanisms, the radiative properties of the regimes are not distinct, indicating that retrieved cloud properties alone are insufficient to completely describe them. This classification is designed to be easily implemented in GCMs, helping improve future model-observation comparisons and leading to improved parametrisations of cirrus cloud processes.

  1. Remote sensing as a tool for monitoring plant invasions: testing the effects of data resolution and image classification approach on the detection of a model plant species Heracleum mantegazzianum (giant hogweed)

    Czech Academy of Sciences Publication Activity Database

    Müllerová, Jana; Pergl, Jan; Pyšek, Petr

    2013-01-01

    Roč. 25, Dec.2013 (2013), s. 55-65 ISSN 0303-2434 R&D Projects: GA AV ČR IAA600050811 Institutional support: RVO:67985939 Keywords : historical aerial VHR photography * invasion progress * object and pixel-based image classification Subject RIV: EF - Botanics Impact factor: 2.539, year: 2013

  2. Hyperspectral Image Classification Using Kernel Fukunaga-Koontz Transform

    Directory of Open Access Journals (Sweden)

    Semih Dinç

    2013-01-01

    images. In experiment section, the improved performance of HSI classification technique, K-FKT, has been tested comparing other methods such as the classical FKT and three types of support vector machines (SVMs.

  3. Transfer Learning beyond Text Classification

    Science.gov (United States)

    Yang, Qiang

    Transfer learning is a new machine learning and data mining framework that allows the training and test data to come from different distributions or feature spaces. We can find many novel applications of machine learning and data mining where transfer learning is necessary. While much has been done in transfer learning in text classification and reinforcement learning, there has been a lack of documented success stories of novel applications of transfer learning in other areas. In this invited article, I will argue that transfer learning is in fact quite ubiquitous in many real world applications. In this article, I will illustrate this point through an overview of a broad spectrum of applications of transfer learning that range from collaborative filtering to sensor based location estimation and logical action model learning for AI planning. I will also discuss some potential future directions of transfer learning.

  4. 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.

  5. Maximum mutual information regularized classification

    KAUST Repository

    Wang, Jim Jing-Yan; Wang, Yi; Zhao, Shiguang; Gao, Xin

    2014-01-01

    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.

  6. Multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement

    Science.gov (United States)

    Yan, Dan; Bai, Lianfa; Zhang, Yi; Han, Jing

    2018-02-01

    For the problems of missing details and performance of the colorization based on sparse representation, we propose a conceptual model framework for colorizing gray-scale images, and then a multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement (CEMDC) is proposed based on this framework. The algorithm can achieve a natural colorized effect for a gray-scale image, and it is consistent with the human vision. First, the algorithm establishes a multi-sparse dictionary classification colorization model. Then, to improve the accuracy rate of the classification, the corresponding local constraint algorithm is proposed. Finally, we propose a detail enhancement based on Laplacian Pyramid, which is effective in solving the problem of missing details and improving the speed of image colorization. In addition, the algorithm not only realizes the colorization of the visual gray-scale image, but also can be applied to the other areas, such as color transfer between color images, colorizing gray fusion images, and infrared images.

  7. What should an ideal spinal injury classification system consist of? A methodological review and conceptual proposal for future classifications.

    NARCIS (Netherlands)

    Middendorp, J.J. van; Audige, L.; Hanson, B.; Chapman, J.R.; Hosman, A.J.F.

    2010-01-01

    Since Bohler published the first categorization of spinal injuries based on plain radiographic examinations in 1929, numerous classifications have been proposed. Despite all these efforts, however, only a few have been tested for reliability and validity. This methodological, conceptual review

  8. Insensitive Munitions Testing

    Data.gov (United States)

    Federal Laboratory Consortium — Insensitive Munitions Testing at RTC is conducted (IAW MILSTD-2105) at Test Area 4. Our engineers and technicians obtain data for hazards classification and safety...

  9. Tree Classification with Fused Mobile Laser Scanning and Hyperspectral Data

    Science.gov (United States)

    Puttonen, Eetu; Jaakkola, Anttoni; Litkey, Paula; Hyyppä, Juha

    2011-01-01

    Mobile Laser Scanning data were collected simultaneously with hyperspectral data using the Finnish Geodetic Institute Sensei system. The data were tested for tree species classification. The test area was an urban garden in the City of Espoo, Finland. Point clouds representing 168 individual tree specimens of 23 tree species were determined manually. The classification of the trees was done using first only the spatial data from point clouds, then with only the spectral data obtained with a spectrometer, and finally with the combined spatial and hyperspectral data from both sensors. Two classification tests were performed: the separation of coniferous and deciduous trees, and the identification of individual tree species. All determined tree specimens were used in distinguishing coniferous and deciduous trees. A subset of 133 trees and 10 tree species was used in the tree species classification. The best classification results for the fused data were 95.8% for the separation of the coniferous and deciduous classes. The best overall tree species classification succeeded with 83.5% accuracy for the best tested fused data feature combination. The respective results for paired structural features derived from the laser point cloud were 90.5% for the separation of the coniferous and deciduous classes and 65.4% for the species classification. Classification accuracies with paired hyperspectral reflectance value data were 90.5% for the separation of coniferous and deciduous classes and 62.4% for different species. The results are among the first of their kind and they show that mobile collected fused data outperformed single-sensor data in both classification tests and by a significant margin. PMID:22163894

  10. A dynamical classification of the cosmic web

    Science.gov (United States)

    Forero-Romero, J. E.; Hoffman, Y.; Gottlöber, S.; Klypin, A.; Yepes, G.

    2009-07-01

    In this paper, we propose a new dynamical classification of the cosmic web. Each point in space is classified in one of four possible 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, λth, at each grid point, where the case of zero, one, two or three such eigenvalues corresponds to void, sheet, filament or a knot grid point. The collection of neighbouring grid points, friends of friends, of the same web type constitutes voids, sheets, filaments and knots as extended web objects. A simple dynamical consideration of the emergence of the web suggests that the threshold should not be null, as in previous implementations of the algorithm. A detailed dynamical analysis would have found different threshold values for the collapse of sheets, filaments and knots. Short of such an analysis a phenomenological approach has been opted for, looking for a single threshold to be determined by analysing numerical simulations. Our cosmic web classification has been applied and tested against a suite of large (dark matter only) cosmological N-body simulations. In particular, the dependence of the volume and mass filling fractions on λth and on the resolution has been calculated for the four web types. We also study the percolation properties of voids and filaments. Our main findings are as follows. (i) Already at λth = 0.1 the resulting web classification reproduces the visual impression of the cosmic web. (ii) Between 0.2 net of interconnected filaments. This suggests a reasonable choice for λth as the parameter that defines the cosmic web. (iii) The dynamical nature of the suggested classification provides a robust framework for incorporating environmental information into galaxy formation models, and in particular to semi-analytical models.

  11. Classification of IRAS asteroids

    International Nuclear Information System (INIS)

    Tedesco, E.F.; Matson, D.L.; Veeder, G.J.

    1989-01-01

    Albedos and spectral reflectances are essential for classifying asteroids. For example, classes E, M and P are indistinguishable without albedo data. Colorometric data are available for about 1000 asteroids but, prior to IRAS, albedo data was available for only about 200. IRAS broke this bottleneck by providing albedo data on nearly 2000 asteroids. Hence, excepting absolute magnitudes, the albedo and size are now the most common asteroid physical parameters known. In this chapter the authors present the results of analyses of IRAS-derived asteroid albedos, discuss their application to asteroid classification, and mention several studies which might be done to exploit further this data set

  12. 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.

  13. Radioactive facilities classification criteria

    International Nuclear Information System (INIS)

    Briso C, H.A.; Riesle W, J.

    1992-01-01

    Appropriate classification of radioactive facilities into groups of comparable risk constitutes one of the problems faced by most Regulatory Bodies. Regarding the radiological risk, the main facts to be considered are the radioactive inventory and the processes to which these radionuclides are subjected. Normally, operations are ruled by strict safety procedures. Thus, the total activity of the radionuclides existing in a given facility is the varying feature that defines its risk. In order to rely on a quantitative criterion and, considering that the Annual Limits of Intake are widely accepted references, an index based on these limits, to support decisions related to radioactive facilities, is proposed. (author)

  14. Training strategy for convolutional neural networks in pedestrian gender classification

    Science.gov (United States)

    Ng, Choon-Boon; Tay, Yong-Haur; Goi, Bok-Min

    2017-06-01

    In this work, we studied a strategy for training a convolutional neural network in pedestrian gender classification with limited amount of labeled training data. Unsupervised learning by k-means clustering on pedestrian images was used to learn the filters to initialize the first layer of the network. As a form of pre-training, supervised learning for the related task of pedestrian classification was performed. Finally, the network was fine-tuned for gender classification. We found that this strategy improved the network's generalization ability in gender classification, achieving better test results when compared to random weights initialization and slightly more beneficial than merely initializing the first layer filters by unsupervised learning. This shows that unsupervised learning followed by pre-training with pedestrian images is an effective strategy to learn useful features for pedestrian gender classification.

  15. Classification versus inference learning contrasted with real-world categories.

    Science.gov (United States)

    Jones, Erin L; Ross, Brian H

    2011-07-01

    Categories are learned and used in a variety of ways, but the research focus has been on classification learning. Recent work contrasting classification with inference learning of categories found important later differences in category performance. However, theoretical accounts differ on whether this is due to an inherent difference between the tasks or to the implementation decisions. The inherent-difference explanation argues that inference learners focus on the internal structure of the categories--what each category is like--while classification learners focus on diagnostic information to predict category membership. In two experiments, using real-world categories and controlling for earlier methodological differences, inference learners learned more about what each category was like than did classification learners, as evidenced by higher performance on a novel classification test. These results suggest that there is an inherent difference between learning new categories by classifying an item versus inferring a feature.

  16. Asynchronous data-driven classification of weapon systems

    International Nuclear Information System (INIS)

    Jin, Xin; Mukherjee, Kushal; Gupta, Shalabh; Ray, Asok; Phoha, Shashi; Damarla, Thyagaraju

    2009-01-01

    This communication addresses real-time weapon classification by analysis of asynchronous acoustic data, collected from microphones on a sensor network. The weapon classification algorithm consists of two parts: (i) feature extraction from time-series data using symbolic dynamic filtering (SDF), and (ii) pattern classification based on the extracted features using the language measure (LM) and support vector machine (SVM). The proposed algorithm has been tested on field data, generated by firing of two types of rifles. The results of analysis demonstrate high accuracy and fast execution of the pattern classification algorithm with low memory requirements. Potential applications include simultaneous shooter localization and weapon classification with soldier-wearable networked sensors. (rapid communication)

  17. A New Method for Solving Supervised Data Classification Problems

    Directory of Open Access Journals (Sweden)

    Parvaneh Shabanzadeh

    2014-01-01

    Full Text Available Supervised data classification is one of the techniques used to extract nontrivial information from data. Classification is a widely used technique in various fields, including data mining, industry, medicine, science, and law. This paper considers a new algorithm for supervised data classification problems associated with the cluster analysis. The mathematical formulations for this algorithm are based on nonsmooth, nonconvex optimization. A new algorithm for solving this optimization problem is utilized. The new algorithm uses a derivative-free technique, with robustness and efficiency. To improve classification performance and efficiency in generating classification model, a new feature selection algorithm based on techniques of convex programming is suggested. Proposed methods are tested on real-world datasets. Results of numerical experiments have been presented which demonstrate the effectiveness of the proposed algorithms.

  18. Supply chain planning classification

    Science.gov (United States)

    Hvolby, Hans-Henrik; Trienekens, Jacques; Bonde, Hans

    2001-10-01

    Industry experience a need to shift in focus from internal production planning towards planning in the supply network. In this respect customer oriented thinking becomes almost a common good amongst companies in the supply network. An increase in the use of information technology is needed to enable companies to better tune their production planning with customers and suppliers. Information technology opportunities and supply chain planning systems facilitate companies to monitor and control their supplier network. In spite if these developments, most links in today's supply chains make individual plans, because the real demand information is not available throughout the chain. The current systems and processes of the supply chains are not designed to meet the requirements now placed upon them. For long term relationships with suppliers and customers, an integrated decision-making process is needed in order to obtain a satisfactory result for all parties. Especially when customized production and short lead-time is in focus. An effective value chain makes inventory available and visible among the value chain members, minimizes response time and optimizes total inventory value held throughout the chain. In this paper a supply chain planning classification grid is presented based current manufacturing classifications and supply chain planning initiatives.

  19. Waste classification sampling plan

    International Nuclear Information System (INIS)

    Landsman, S.D.

    1998-01-01

    The purpose of this sampling is to explain the method used to collect and analyze data necessary to verify and/or determine the radionuclide content of the B-Cell decontamination and decommissioning waste stream so that the correct waste classification for the waste stream can be made, and to collect samples for studies of decontamination methods that could be used to remove fixed contamination present on the waste. The scope of this plan is to establish the technical basis for collecting samples and compiling quantitative data on the radioactive constituents present in waste generated during deactivation activities in B-Cell. Sampling and radioisotopic analysis will be performed on the fixed layers of contamination present on structural material and internal surfaces of process piping and tanks. In addition, dose rate measurements on existing waste material will be performed to determine the fraction of dose rate attributable to both removable and fixed contamination. Samples will also be collected to support studies of decontamination methods that are effective in removing the fixed contamination present on the waste. Sampling performed under this plan will meet criteria established in BNF-2596, Data Quality Objectives for the B-Cell Waste Stream Classification Sampling, J. M. Barnett, May 1998

  20. 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 ....

  1. Small-scale classification schemes

    DEFF Research Database (Denmark)

    Hertzum, Morten

    2004-01-01

    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...... effects remained largely implicit. The requirements classification contributed to constraining the requirements-engineering process by supporting the software engineers in maintaining some level of control over the process. This way, the requirements classification provided the software engineers...

  2. 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...

  3. Unsupervised Classification Using Immune Algorithm

    OpenAIRE

    Al-Muallim, M. T.; El-Kouatly, R.

    2012-01-01

    Unsupervised classification algorithm based on clonal selection principle named Unsupervised Clonal Selection Classification (UCSC) is proposed in this paper. The new proposed algorithm is data driven and self-adaptive, it adjusts its parameters to the data to make the classification operation as fast as possible. The performance of UCSC is evaluated by comparing it with the well known K-means algorithm using several artificial and real-life data sets. The experiments show that the proposed U...

  4. PROGRESSIVE DENSIFICATION AND REGION GROWING METHODS FOR LIDAR DATA CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    J. L. Pérez-García

    2012-07-01

    Full Text Available At present, airborne laser scanner systems are one of the most frequent methods used to obtain digital terrain elevation models. While having the advantage of direct measurement on the object, the point cloud obtained has the need for classification of their points according to its belonging to the ground. This need for classification of raw data has led to appearance of multiple filters focused LiDAR classification information. According this approach, this paper presents a classification method that combines LiDAR data segmentation techniques and progressive densification to carry out the location of the points belonging to the ground. The proposed methodology is tested on several datasets with different terrain characteristics and data availability. In all case, we analyze the advantages and disadvantages that have been obtained compared with the individual techniques application and, in a special way, the benefits derived from the integration of both classification techniques. In order to provide a more comprehensive quality control of the classification process, the obtained results have been compared with the derived from a manual procedure, which is used as reference classification. The results are also compared with other automatic classification methodologies included in some commercial software packages, highly contrasted by users for LiDAR data treatment.

  5. A simplified immunohistochemical classification of skeletal muscle fibres in mouse

    Directory of Open Access Journals (Sweden)

    M. Kammoun

    2014-06-01

    Full Text Available The classification of muscle fibres is of particular interest for the study of the skeletal muscle properties in a wide range of scientific fields, especially animal phenotyping. It is therefore important to define a reliable method for classifying fibre types. The aim of this study was to establish a simplified method for the immunohistochemical classification of fibres in mouse. To carry it out, we first tested a combination of several anti myosin heavy chain (MyHC antibodies in order to choose a minimum number of antibodies to implement a semi-automatic classification. Then, we compared the classification of fibres to the MyHC electrophoretic pattern on the same samples. Only two anti MyHC antibodies on serial sections with the fluorescent labeling of the Laminin were necessary to classify properly fibre types in Tibialis Anterior and Soleus mouse muscles in normal physiological conditions. This classification was virtually identical to the classification realized by the electrophoretic separation of MyHC. This immunohistochemical classification can be applied to the total area of Tibialis Anterior and Soleus mouse muscles. Thus, we provide here a useful, simple and time-efficient method for immunohistochemical classification of fibres, applicable for research in mouse

  6. High Dimensional Classification Using Features Annealed Independence Rules.

    Science.gov (United States)

    Fan, Jianqing; Fan, Yingying

    2008-01-01

    Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.

  7. Experimental study on multi-sub-classifier for land cover classification: a case study in Shangri-La, China

    Science.gov (United States)

    Wang, Yan-ying; Wang, Jin-liang; Wang, Ping; Hu, Wen-yin; Su, Shao-hua

    2015-12-01

    High accuracy remote sensed image classification technology is a long-term and continuous pursuit goal of remote sensing applications. In order to evaluate single classification algorithm accuracy, take Landsat TM image as data source, Northwest Yunnan as study area, seven types of land cover classification like Maximum Likelihood Classification has been tested, the results show that: (1)the overall classification accuracy of Maximum Likelihood Classification(MLC), Artificial Neural Network Classification(ANN), Minimum Distance Classification(MinDC) is higher, which is 82.81% and 82.26% and 66.41% respectively; the overall classification accuracy of Parallel Hexahedron Classification(Para), Spectral Information Divergence Classification(SID), Spectral Angle Classification(SAM) is low, which is 37.29%, 38.37, 53.73%, respectively. (2) from each category classification accuracy: although the overall accuracy of the Para is the lowest, it is much higher on grasslands, wetlands, forests, airport land, which is 89.59%, 94.14%, and 89.04%, respectively; the SAM, SID are good at forests classification with higher overall classification accuracy, which is 89.8% and 87.98%, respectively. Although the overall classification accuracy of ANN is very high, the classification accuracy of road, rural residential land and airport land is very low, which is 10.59%, 11% and 11.59% respectively. Other classification methods have their advantages and disadvantages. These results show that, under the same conditions, the same images with different classification methods to classify, there will be a classifier to some features has higher classification accuracy, a classifier to other objects has high classification accuracy, and therefore, we may select multi sub-classifier integration to improve the classification accuracy.

  8. Audio stream classification for multimedia database search

    Science.gov (United States)

    Artese, M.; Bianco, S.; Gagliardi, I.; Gasparini, F.

    2013-03-01

    Search and retrieval of huge archives of Multimedia data is a challenging task. A classification step is often used to reduce the number of entries on which to perform the subsequent search. In particular, when new entries of the database are continuously added, a fast classification based on simple threshold evaluation is desirable. In this work we present a CART-based (Classification And Regression Tree [1]) classification framework for audio streams belonging to multimedia databases. The database considered is the Archive of Ethnography and Social History (AESS) [2], which is mainly composed of popular songs and other audio records describing the popular traditions handed down generation by generation, such as traditional fairs, and customs. The peculiarities of this database are that it is continuously updated; the audio recordings are acquired in unconstrained environment; and for the non-expert human user is difficult to create the ground truth labels. In our experiments, half of all the available audio files have been randomly extracted and used as training set. The remaining ones have been used as test set. The classifier has been trained to distinguish among three different classes: speech, music, and song. All the audio files in the dataset have been previously manually labeled into the three classes above defined by domain experts.

  9. Automotive System for Remote Surface Classification.

    Science.gov (United States)

    Bystrov, Aleksandr; Hoare, Edward; Tran, Thuy-Yung; Clarke, Nigel; Gashinova, Marina; Cherniakov, Mikhail

    2017-04-01

    In this paper we shall discuss a novel approach to road surface recognition, based on the analysis of backscattered microwave and ultrasonic signals. The novelty of our method is sonar and polarimetric radar data fusion, extraction of features for separate swathes of illuminated surface (segmentation), and using of multi-stage artificial neural network for surface classification. The developed system consists of 24 GHz radar and 40 kHz ultrasonic sensor. The features are extracted from backscattered signals and then the procedures of principal component analysis and supervised classification are applied to feature data. The special attention is paid to multi-stage artificial neural network which allows an overall increase in classification accuracy. The proposed technique was tested for recognition of a large number of real surfaces in different weather conditions with the average accuracy of correct classification of 95%. The obtained results thereby demonstrate that the use of proposed system architecture and statistical methods allow for reliable discrimination of various road surfaces in real conditions.

  10. General regression and representation model for classification.

    Directory of Open Access Journals (Sweden)

    Jianjun Qian

    Full Text Available Recently, the regularized coding-based classification methods (e.g. SRC and CRC show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients and the specific information (weight matrix of image pixels to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR and robust general regression and representation classifier (R-GRR. The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms.

  11. Observation versus classification in supervised category learning.

    Science.gov (United States)

    Levering, Kimery R; Kurtz, Kenneth J

    2015-02-01

    The traditional supervised classification paradigm encourages learners to acquire only the knowledge needed to predict category membership (a discriminative approach). An alternative that aligns with important aspects of real-world concept formation is learning with a broader focus to acquire knowledge of the internal structure of each category (a generative approach). Our work addresses the impact of a particular component of the traditional classification task: the guess-and-correct cycle. We compare classification learning to a supervised observational learning task in which learners are shown labeled examples but make no classification response. The goals of this work sit at two levels: (1) testing for differences in the nature of the category representations that arise from two basic learning modes; and (2) evaluating the generative/discriminative continuum as a theoretical tool for understand learning modes and their outcomes. Specifically, we view the guess-and-correct cycle as consistent with a more discriminative approach and therefore expected it to lead to narrower category knowledge. Across two experiments, the observational mode led to greater sensitivity to distributional properties of features and correlations between features. We conclude that a relatively subtle procedural difference in supervised category learning substantially impacts what learners come to know about the categories. The results demonstrate the value of the generative/discriminative continuum as a tool for advancing the psychology of category learning and also provide a valuable constraint for formal models and associated theories.

  12. Reliability of Oronasal Fistula Classification.

    Science.gov (United States)

    Sitzman, Thomas J; Allori, Alexander C; Matic, Damir B; Beals, Stephen P; Fisher, David M; Samson, Thomas D; Marcus, Jeffrey R; Tse, Raymond W

    2018-01-01

    Objective Oronasal fistula is an important complication of cleft palate repair that is frequently used to evaluate surgical quality, yet reliability of fistula classification has never been examined. The objective of this study was to determine the reliability of oronasal fistula classification both within individual surgeons and between multiple surgeons. Design Using intraoral photographs of children with repaired cleft palate, surgeons rated the location of palatal fistulae using the Pittsburgh Fistula Classification System. Intrarater and interrater reliability scores were calculated for each region of the palate. Participants Eight cleft surgeons rated photographs obtained from 29 children. Results Within individual surgeons reliability for each region of the Pittsburgh classification ranged from moderate to almost perfect (κ = .60-.96). By contrast, reliability between surgeons was lower, ranging from fair to substantial (κ = .23-.70). Between-surgeon reliability was lowest for the junction of the soft and hard palates (κ = .23). Within-surgeon and between-surgeon reliability were almost perfect for the more general classification of fistula in the secondary palate (κ = .95 and κ = .83, respectively). Conclusions This is the first reliability study of fistula classification. We show that the Pittsburgh Fistula Classification System is reliable when used by an individual surgeon, but less reliable when used among multiple surgeons. Comparisons of fistula occurrence among surgeons may be subject to less bias if they use the more general classification of "presence or absence of fistula of the secondary palate" rather than the Pittsburgh Fistula Classification System.

  13. Using classification and NDVI differencing methods for monitoring sparse vegetation coverage: a case study of saltcedar in Nevada, USA.

    Science.gov (United States)

    A change detection experiment for an invasive species, saltcedar, near Lovelock, Nevada, was conducted with multi-date Compact Airborne Spectrographic Imager (CASI) hyperspectral datasets. Classification and NDVI differencing change detection methods were tested, In the classification strategy, a p...

  14. Classification of perovskites with supervised self-organizing maps

    International Nuclear Information System (INIS)

    Kuzmanovski, Igor; Dimitrovska-Lazova, Sandra; Aleksovska, Slobotka

    2007-01-01

    In this work supervised self-organizing maps were used for structural classification of perovskites. For this purpose, structural data for total number of 286 perovskites, belonging to ABO 3 and/or A 2 BB'O 6 types, were collected from literature: 130 of these are cubic, 85 orthorhombic and 71 monoclinic. For classification purposes, the effective ionic radii of the cations, electronegativities of the cations in B-position, as well as, the oxidation states of these cations, were used as input variables. The parameters of the developed models, as well as, the most suitable variables for classification purposes were selected using genetic algorithms. Two-third of all the compounds were used in the training phase. During the optimization process the performances of the models were checked using cross-validation leave-1/10-out. The performances of obtained solutions were checked using the test set composed of the remaining one-third of the compounds. The obtained models for classification of these three classes of perovskite compounds show very good results. Namely, the classification of the compounds in the test set resulted in small number of discrepancies (4.2-6.4%) between the actual crystallographic class and the one predicted by the models. All these results are strong arguments for the validity of supervised self-organizing maps for performing such types of classification. Therefore, the proposed procedure could be successfully used for crystallographic classification of perovskites in one of these three classes

  15. Magnetic resonance imaging texture analysis classification of primary breast cancer

    International Nuclear Information System (INIS)

    Waugh, S.A.; Lerski, R.A.; Purdie, C.A.; Jordan, L.B.; Vinnicombe, S.; Martin, P.; Thompson, A.M.

    2016-01-01

    Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75 %, AUROC = 0.816; test: 72.5 %, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2 %, AUROC = 0.754; test: 57.0 %, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. (orig.)

  16. Magnetic resonance imaging texture analysis classification of primary breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Waugh, S.A.; Lerski, R.A. [Ninewells Hospital and Medical School, Department of Medical Physics, Dundee (United Kingdom); Purdie, C.A.; Jordan, L.B. [Ninewells Hospital and Medical School, Department of Pathology, Dundee (United Kingdom); Vinnicombe, S. [University of Dundee, Division of Imaging and Technology, Ninewells Hospital and Medical School, Dundee (United Kingdom); Martin, P. [Ninewells Hospital and Medical School, Department of Clinical Radiology, Dundee (United Kingdom); Thompson, A.M. [University of Texas MD Anderson Cancer Center, Department of Surgical Oncology, Houston, TX (United States)

    2016-02-15

    Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75 %, AUROC = 0.816; test: 72.5 %, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2 %, AUROC = 0.754; test: 57.0 %, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. (orig.)

  17. Classification of radioactive waste

    International Nuclear Information System (INIS)

    1994-01-01

    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

  18. 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

  19. Automatic diabetic retinopathy classification

    Science.gov (United States)

    Bravo, María. A.; Arbeláez, Pablo A.

    2017-11-01

    Diabetic retinopathy (DR) is a disease in which the retina is damaged due to augmentation in the blood pressure of small vessels. DR is the major cause of blindness for diabetics. It has been shown that early diagnosis can play a major role in prevention of visual loss and blindness. This work proposes a computer based approach for the detection of DR in back-of-the-eye images based on the use of convolutional neural networks (CNNs). Our CNN uses deep architectures to classify Back-of-the-eye Retinal Photographs (BRP) in 5 stages of DR. Our method combines several preprocessing images of BRP to obtain an ACA score of 50.5%. Furthermore, we explore subproblems by training a larger CNN of our main classification task.

  20. Visualization and classification in biomedical terahertz pulsed imaging

    International Nuclear Information System (INIS)

    Loeffler, Torsten; Siebert, Karsten; Czasch, Stephanie; Bauer, Tobias; Roskos, Hartmut G

    2002-01-01

    'Visualization' in imaging is the process of extracting useful information from raw data in such a way that meaningful physical contrasts are developed. 'Classification' is the subsequent process of defining parameter ranges which allow us to identify elements of images such as different tissues or different objects. In this paper, we explore techniques for visualization and classification in terahertz pulsed imaging (TPI) for biomedical applications. For archived (formalin-fixed, alcohol-dehydrated and paraffin-mounted) test samples, we investigate both time- and frequency-domain methods based on bright- and dark-field TPI. Successful tissue classification is demonstrated

  1. Classification of Polarimetric SAR Data Using Dictionary Learning

    DEFF Research Database (Denmark)

    Vestergaard, Jacob Schack; Nielsen, Allan Aasbjerg; Dahl, Anders Lindbjerg

    2012-01-01

    This contribution deals with classification of multilook fully polarimetric synthetic aperture radar (SAR) data by learning a dictionary of crop types present in the Foulum test site. The Foulum test site contains a large number of agricultural fields, as well as lakes, forests, natural vegetation......, grasslands and urban areas, which make it ideally suited for evaluation of classification algorithms. Dictionary learning centers around building a collection of image patches typical for the classification problem at hand. This requires initial manual labeling of the classes present in the data and is thus...... a method for supervised classification. Sparse coding of these image patches aims to maintain a proficient number of typical patches and associated labels. Data is consecutively classified by a nearest neighbor search of the dictionary elements and labeled with probabilities of each class. Each dictionary...

  2. Classification using diffraction patterns for single-particle analysis

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Hongli; Zhang, Kaiming [Department of Biophysics, the Health Science Centre, Peking University, Beijing 100191 (China); Meng, Xing, E-mail: xmeng101@gmail.com [Wadsworth Centre, New York State Department of Health, Albany, New York 12201 (United States)

    2016-05-15

    An alternative method has been assessed; diffraction patterns derived from the single particle data set were used to perform the first round of classification in creating the initial averages for proteins data with symmetrical morphology. The test protein set was a collection of Caenorhabditis elegans small heat shock protein 17 obtained by Cryo EM, which has a tetrahedral (12-fold) symmetry. It is demonstrated that the initial classification on diffraction patterns is workable as well as the real-space classification that is based on the phase contrast. The test results show that the information from diffraction patterns has the enough details to make the initial model faithful. The potential advantage using the alternative method is twofold, the ability to handle the sets with poor signal/noise or/and that break the symmetry properties. - Highlights: • New classification method. • Create the accurate initial model. • Better in handling noisy data.

  3. Classification using diffraction patterns for single-particle analysis

    International Nuclear Information System (INIS)

    Hu, Hongli; Zhang, Kaiming; Meng, Xing

    2016-01-01

    An alternative method has been assessed; diffraction patterns derived from the single particle data set were used to perform the first round of classification in creating the initial averages for proteins data with symmetrical morphology. The test protein set was a collection of Caenorhabditis elegans small heat shock protein 17 obtained by Cryo EM, which has a tetrahedral (12-fold) symmetry. It is demonstrated that the initial classification on diffraction patterns is workable as well as the real-space classification that is based on the phase contrast. The test results show that the information from diffraction patterns has the enough details to make the initial model faithful. The potential advantage using the alternative method is twofold, the ability to handle the sets with poor signal/noise or/and that break the symmetry properties. - Highlights: • New classification method. • Create the accurate initial model. • Better in handling noisy data.

  4. Hazard classification or risk assessment

    DEFF Research Database (Denmark)

    Hass, Ulla

    2013-01-01

    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...

  5. Efficient AUC optimization for classification

    NARCIS (Netherlands)

    Calders, T.; Jaroszewicz, S.; Kok, J.N.; Koronacki, J.; Lopez de Mantaras, R.; Matwin, S.; Mladenic, D.; Skowron, A.

    2007-01-01

    In this paper we show an efficient method for inducing classifiers that directly optimize the area under the ROC curve. Recently, AUC gained importance in the classification community as a mean to compare the performance of classifiers. Because most classification methods do not optimize this

  6. Dewey Decimal Classification: A Quagmire.

    Science.gov (United States)

    Gamaluddin, Ahmad Fouad

    1980-01-01

    A survey of 660 Pennsylvania school librarians indicates that, though there is limited professional interest in the Library of Congress Classification system, Dewey Decimal Classification (DDC) appears to be firmly entrenched. This article also discusses the relative merits of DDC, the need for a uniform system, librarianship preparation, and…

  7. Latent class models for classification

    NARCIS (Netherlands)

    Vermunt, J.K.; Magidson, J.

    2003-01-01

    An overview is provided of recent developments in the use of latent class (LC) and other types of finite mixture models for classification purposes. Several extensions of existing models are presented. Two basic types of LC models for classification are defined: supervised and unsupervised

  8. 45 CFR 601.5 - Derivative classification.

    Science.gov (United States)

    2010-10-01

    ... CLASSIFICATION AND DECLASSIFICATION OF NATIONAL SECURITY INFORMATION § 601.5 Derivative classification. Distinct... 45 Public Welfare 3 2010-10-01 2010-10-01 false Derivative classification. 601.5 Section 601.5... classification guide, need not possess original classification authority. (a) If a person who applies derivative...

  9. 12 CFR 403.4 - Derivative classification.

    Science.gov (United States)

    2010-01-01

    ... SAFEGUARDING OF NATIONAL SECURITY INFORMATION § 403.4 Derivative classification. (a) Use of derivative classification. (1) Unlike original classification which is an initial determination, derivative classification... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Derivative classification. 403.4 Section 403.4...

  10. 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 classification...

  11. A Classification Framework for Large-Scale Face Recognition Systems

    OpenAIRE

    Zhou, Ziheng; Deravi, Farzin

    2009-01-01

    This paper presents a generic classification framework for large-scale face recognition systems. Within the framework, a data sampling strategy is proposed to tackle the data imbalance when image pairs are sampled from thousands of face images for preparing a training dataset. A modified kernel Fisher discriminant classifier is proposed to make it computationally feasible to train the kernel-based classification method using tens of thousands of training samples. The framework is tested in an...

  12. [New International Classification of Chronic Pancreatitis (M-ANNHEIM multifactor classification system, 2007): principles, merits, and demerits].

    Science.gov (United States)

    Tsimmerman, Ia S

    2008-01-01

    The new International Classification of Chronic Pancreatitis (designated as M-ANNHEIM) proposed by a group of German specialists in late 2007 is reviewed. All its sections are subjected to analysis (risk group categories, clinical stages and phases, variants of clinical course, diagnostic criteria for "established" and "suspected" pancreatitis, instrumental methods and functional tests used in the diagnosis, evaluation of the severity of the disease using a scoring system, stages of elimination of pain syndrome). The new classification is compared with the earlier classification proposed by the author. Its merits and demerits are discussed.

  13. Content Abstract Classification Using Naive Bayes

    Science.gov (United States)

    Latif, Syukriyanto; Suwardoyo, Untung; Aldrin Wihelmus Sanadi, Edwin

    2018-03-01

    This study aims to classify abstract content based on the use of the highest number of words in an abstract content of the English language journals. This research uses a system of text mining technology that extracts text data to search information from a set of documents. Abstract content of 120 data downloaded at www.computer.org. Data grouping consists of three categories: DM (Data Mining), ITS (Intelligent Transport System) and MM (Multimedia). Systems built using naive bayes algorithms to classify abstract journals and feature selection processes using term weighting to give weight to each word. Dimensional reduction techniques to reduce the dimensions of word counts rarely appear in each document based on dimensional reduction test parameters of 10% -90% of 5.344 words. The performance of the classification system is tested by using the Confusion Matrix based on comparative test data and test data. The results showed that the best classification results were obtained during the 75% training data test and 25% test data from the total data. Accuracy rates for categories of DM, ITS and MM were 100%, 100%, 86%. respectively with dimension reduction parameters of 30% and the value of learning rate between 0.1-0.5.

  14. Reprodutibilidade na classificação do teste de cristalização do filme lacrimal em pacientes com síndrome de Sjögren Reproducibility of the classification of ocular ferning patterns in Sjogren's syndrome patients

    Directory of Open Access Journals (Sweden)

    Sergio Felberg

    2008-04-01

    Full Text Available OBJETIVO: Verificar a reprodutibilidade da classificação dos padrões do teste de cristalização do filme lacrimal utilizando cinco examinadores diferentes e comparar os padrões de cristalização de pacientes portadores da síndrome de Sjögren com os de indivíduos não portadores de doenças da superfície ocular. MÉTODOS: Análise da cristalização da lágrima de 29 pacientes com Sjögren e 45 pacientes sem doenças da superfície ocular, através de microscópio com luz polarizada, utilizando a classificação de Rolando. Para fins estatísticos foi estudada a curva ROC (Receiver Operating Characteristic para determinar a melhor nota de corte do exame que separa indivíduos normais dos portadores da síndrome, índice de concordância Kappa (pPURPOSE: To verify the reproducibility of Rolando's classification of the tear ferning test using five different examiners and to compare the patterns of crystallization found in Sjögren's syndrome patients and normal subjects. METHODS: Tear ferning analysis of 29 patients with Sjögren's syndrome and of 45 patients without ocular disease were done using polarized light microscopy and the Rolando classification for tear ferning. Five examiners classified the ferning patterns of all the patients. ROC curve (Receiver Operating Characteristic was used to find out the best score for the correct syndrome diagnosis. Kappa index (p<0.0001 was used to compare the results of the examiners among them and check the test's reproducibility. Charts were drawn to compare the two groups' results. RESULTS: Throught the ROC curve the score of 2.50 for diagnosis of Sjögren's syndrome was stabilished. Considering the aggregated patterns I with II and III with IV, the examinors' level of pattern agreement was excellent (Kappa ranging from 0.82 to 0.97, p<0.0001. The group with Sjögren's syndrome was classified mostly as patterns III and IV and the patients without ocular disease mostly as I and II. CONCLUSION: The

  15. Intelligent Computer Vision System for Automated Classification

    International Nuclear Information System (INIS)

    Jordanov, Ivan; Georgieva, Antoniya

    2010-01-01

    In this paper we investigate an Intelligent Computer Vision System applied for recognition and classification of commercially available cork tiles. The system is capable of acquiring and processing gray images using several feature generation and analysis techniques. Its functionality includes image acquisition, feature extraction and preprocessing, and feature classification with neural networks (NN). We also discuss system test and validation results from the recognition and classification tasks. The system investigation also includes statistical feature processing (features number and dimensionality reduction techniques) and classifier design (NN architecture, target coding, learning complexity and performance, and training with our own metaheuristic optimization method). The NNs trained with our genetic low-discrepancy search method (GLPτS) for global optimisation demonstrated very good generalisation abilities. In our view, the reported testing success rate of up to 95% is due to several factors: combination of feature generation techniques; application of Analysis of Variance (ANOVA) and Principal Component Analysis (PCA), which appeared to be very efficient for preprocessing the data; and use of suitable NN design and learning method.

  16. Testing Testing Testing.

    Science.gov (United States)

    Deville, Craig; O'Neill, Thomas; Wright, Benjamin D.; Woodcock, Richard W.; Munoz-Sandoval, Ana; Gershon, Richard C.; Bergstrom, Betty

    1998-01-01

    Articles in this special section consider (1) flow in test taking (Craig Deville); (2) testwiseness (Thomas O'Neill); (3) test length (Benjamin Wright); (4) cross-language test equating (Richard W. Woodcock and Ana Munoz-Sandoval); (5) computer-assisted testing and testwiseness (Richard Gershon and Betty Bergstrom); and (6) Web-enhanced testing…

  17. Classification of sports types from tracklets

    DEFF Research Database (Denmark)

    Gade, Rikke; Moeslund, Thomas B.

    Automatic analysis of video is important in order to process and exploit large amounts of data, e.g. for sports analysis. Classification of sports types is one of the first steps to- wards a fully automatic analysis of the activities performed at sports arenas. In this work we test the idea...... that sports types can be classified from features extracted from short trajectories of the players. From tracklets created by a Kalman filter tracker we extract four robust features; Total distance, lifespan, distance span and mean speed. For clas- sification we use a quadratic discriminant analysis. In our...... experiments we use 30 2-minutes thermal video sequences from each of five different sports types. By applying a 10- fold cross validation we obtain a correct classification rate of 94.5 %....

  18. Biogeographic classification of the Caspian Sea

    DEFF Research Database (Denmark)

    Fendereski, F.; Vogt, M.; Payne, Mark

    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 deriv...... confirms the relevance of the ecoregions as proxies for habitats with common biological characteristics....... 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 maps (SOMs) and (ii) a synthesis of the most relevant features into a reduced number of marine ecoregions...... in phytoplankton phenology, with differences in the date of bloom initiation, its duration and amplitude between ecoregions. A first qualitative evaluation of differences in community composition based on recorded presence-absence patterns of 27 different species of plankton, fish and benthic invertebrate also...

  19. Signal classification for acoustic neutrino detection

    International Nuclear Information System (INIS)

    Neff, M.; Anton, G.; Enzenhöfer, A.; Graf, K.; Hößl, J.; Katz, U.; Lahmann, R.; Richardt, C.

    2012-01-01

    This article focuses on signal classification for deep-sea acoustic neutrino detection. In the deep sea, the background of transient signals is very diverse. Approaches like matched filtering are not sufficient to distinguish between neutrino-like signals and other transient signals with similar signature, which are forming the acoustic background for neutrino detection in the deep-sea environment. A classification system based on machine learning algorithms is analysed with the goal to find a robust and effective way to perform this task. For a well-trained model, a testing error on the level of 1% is achieved for strong classifiers like Random Forest and Boosting Trees using the extracted features of the signal as input and utilising dense clusters of sensors instead of single sensors.

  20. Classifications of objects on hyperspectral images

    DEFF Research Database (Denmark)

    Kucheryavskiy, Sergey

    . In the present work a classification method that combines classic image classification approach and MIA is proposed. The basic idea is to group all pixels and calculate spectral properties of the pixel group to be used further as a vector of predictors for calibration and class prediction. The grouping can...... be done with mathematical morphology methods applied to a score image where objects are well separated. In the case of small overlapping a watershed transformation can be applied to disjoint the objects. The method has been tested on several simulated and real cases and showed good results and significant...... improvements in comparison with a standard MIA approach. The results as well as method details will be reported....

  1. Face classification using electronic synapses

    Science.gov (United States)

    Yao, Peng; Wu, Huaqiang; Gao, Bin; Eryilmaz, Sukru Burc; Huang, Xueyao; Zhang, Wenqiang; Zhang, Qingtian; Deng, Ning; Shi, Luping; Wong, H.-S. Philip; Qian, He

    2017-05-01

    Conventional hardware platforms consume huge amount of energy for cognitive learning due to the data movement between the processor and the off-chip memory. Brain-inspired device technologies using analogue weight storage allow to complete cognitive tasks more efficiently. Here we present an analogue non-volatile resistive memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue synapses for each iteration is 1,000 × (20 ×) lower compared to an implementation using Intel Xeon Phi processor with off-chip memory (with hypothetical on-chip digital resistive random access memory). The accuracy on test sets is close to the result using a central processing unit. These experimental results consolidate the feasibility of analogue synaptic array and pave the way toward building an energy efficient and large-scale neuromorphic system.

  2. Classification of titanium dioxide

    International Nuclear Information System (INIS)

    Macias B, L.R.; Garcia C, R.M.; Maya M, M.E.; Ita T, A. De; Palacios G, J.

    2002-01-01

    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 TiO 2 . 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)

  3. Classification of new particles

    International Nuclear Information System (INIS)

    Karl, G.

    1976-01-01

    A classification of the new particles is proposed. Hadrons are constructed from quarks corresponding to several different representations of an SU 3 color group, with confined color. The new family of resonances, related to psi/J, is assigned to color-antisextet quarks Q. These new quarks Q do not form mixed mesons q-barQ with old antiquarks but can form mixed baryons Qqq. We speculate on the relation between color and mass. High-mass recurrences of the psi/J family are expected to have associated large changes in the cross section for electron-positron annihilation (ΔR > 4). A conjectured mass formula, which relates the masses of psi/J and ω, predicts the masses of possible recurrences of the psi/J particle. Other experimental implications at presently available energies are discussed, especially the necessity for an isovector partner for psi/J, and for pseudoscalar mesons at 1.8--2.2 GeV, some of which can decay into two photons

  4. Automatic detection and classification of malarial retinopathy- associated retinal whitening in digital retinal images

    International Nuclear Information System (INIS)

    Akram, M.U.; Alvi, A.B.N.; Khan, S.A.

    2017-01-01

    Malarial retinopathy addresses diseases that are characterized by abnormalities in retinal fundus imaging. Macular whitening is one of the distinct signs of cerebral malaria but has hardly been explored as a critical bio-marker. The paper proposes a computerized detection and classification method for malarial retinopathy using retinal whitening as a bio-marker. The paper combines various statistical and color based features to form a sound feature set for accurate detection of retinal whitening. All features are extracted at image level and feature selection is performed to detect most discriminate features. A new method for macula location is also presented. The detected macula location is further used for grading of whitening as macular or peripheral whitening. Support vector machine along with radial basis function is used for classification of normal and malarial retinopathy patients. The evaluation is performed using a locally gathered dataset from malarial patients and it achieves an accuracy of 95% for detection of retinal whitening and 100% accuracy for grading of retinal whitening as macular or non-macular. One of the major contributions of proposed method is grading of retinal whitening into macular or peripheral whitening. (author)

  5. Music classification with MPEG-7

    Science.gov (United States)

    Crysandt, Holger; Wellhausen, Jens

    2003-01-01

    Driven by increasing amount of music available electronically the need and possibility of automatic classification systems for music becomes more and more important. Currently most search engines for music are based on textual descriptions like artist or/and title. This paper presents a system for automatic music description, classification and visualization for a set of songs. The system is designed to extract significant features of a piece of music in order to find songs of similar genre or a similar sound characteristics. The description is done with the help of MPEG-7 only. The classification and visualization is done with the self organizing map algorithm.

  6. Systema Naturae. Classification of living things.

    OpenAIRE

    Alexey Shipunov

    2007-01-01

    Original classification of living organisms containing four kingdoms (Monera, Protista, Vegetabilia and Animalia), 60 phyla and 254 classes, is presented. The classification is based on latest available information.

  7. Building and Solving Odd-One-Out Classification Problems: A Systematic Approach

    Science.gov (United States)

    Ruiz, Philippe E.

    2011-01-01

    Classification problems ("find the odd-one-out") are frequently used as tests of inductive reasoning to evaluate human or animal intelligence. This paper introduces a systematic method for building the set of all possible classification problems, followed by a simple algorithm for solving the problems of the R-ASCM, a psychometric test derived…

  8. 1968 Prototype Diagnostic Test.

    Science.gov (United States)

    Veterans Administration Hospital, Bedford, MA.

    This true-false diagnostic test was used for pretesting of employees at a Veterans Administration Hospital. The test is comprised of 20 items. An alternate test--Classification Questionnaire--was used for testing after remedial training. (For related document, see TM 002 334.) (DB)

  9. The value of laparoscopic classifications in decision on definitive ...

    African Journals Online (AJOL)

    The value of laparoscopic classifications in decision on definitive surgery in patients with nonpalpable testes: our ... present our clinical experience with the laparoscopic approach in patients with nonpalpable testes (NPTs) and .... decision making during the procedure. Gatti and. Ostlie [3] have pointed out that laparoscopic ...

  10. A Novel Vehicle Classification Using Embedded Strain Gauge Sensors

    Directory of Open Access Journals (Sweden)

    Qi Wang

    2008-11-01

    Full Text Available Abstract: This paper presents a new vehicle classification and develops a traffic monitoring detector to provide reliable vehicle classification to aid traffic management systems. The basic principle of this approach is based on measuring the dynamic strain caused by vehicles across pavement to obtain the corresponding vehicle parameters – wheelbase and number of axles – to then accurately classify the vehicle. A system prototype with five embedded strain sensors was developed to validate the accuracy and effectiveness of the classification method. According to the special arrangement of the sensors and the different time a vehicle arrived at the sensors one can estimate the vehicle’s speed accurately, corresponding to the estimated vehicle wheelbase and number of axles. Because of measurement errors and vehicle characteristics, there is a lot of overlap between vehicle wheelbase patterns. Therefore, directly setting up a fixed threshold for vehicle classification often leads to low-accuracy results. Using the machine learning pattern recognition method to deal with this problem is believed as one of the most effective tools. In this study, support vector machines (SVMs were used to integrate the classification features extracted from the strain sensors to automatically classify vehicles into five types, ranging from small vehicles to combination trucks, along the lines of the Federal Highway Administration vehicle classification guide. Test bench and field experiments will be introduced in this paper. Two support vector machines classification algorithms (one-against-all, one-against-one are used to classify single sensor data and multiple sensor combination data. Comparison of the two classification method results shows that the classification accuracy is very close using single data or multiple data. Our results indicate that using multiclass SVM-based fusion multiple sensor data significantly improves

  11. A Data Mining Classification Approach for Behavioral Malware Detection

    Directory of Open Access Journals (Sweden)

    Monire Norouzi

    2016-01-01

    Full Text Available Data mining techniques have numerous applications in malware detection. Classification method is one of the most popular data mining techniques. In this paper we present a data mining classification approach to detect malware behavior. We proposed different classification methods in order to detect malware based on the feature and behavior of each malware. A dynamic analysis method has been presented for identifying the malware features. A suggested program has been presented for converting a malware behavior executive history XML file to a suitable WEKA tool input. To illustrate the performance efficiency as well as training data and test, we apply the proposed approaches to a real case study data set using WEKA tool. The evaluation results demonstrated the availability of the proposed data mining approach. Also our proposed data mining approach is more efficient for detecting malware and behavioral classification of malware can be useful to detect malware in a behavioral antivirus.

  12. Progression in nuclear classification

    International Nuclear Information System (INIS)

    Wang Yuying

    1999-01-01

    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

  13. 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.

  14. The classification of easement

    Directory of Open Access Journals (Sweden)

    Popov Danica D.

    2015-01-01

    Full Text Available Easement means, a right enjoyed by the owner of land over the lands of another: such as rights of way, right of light, rights of support, rights to a flow of air or water etc. The dominant tenement is the land owned by the possessor of the easement, and the servient tenement is the land over which the right is enjoyed. An easement must exist for the accommodation and better enjoyment to which it is annexed, otherwise it may amount to mere licence. An easement benefits and binds the land itself and therefore countinious despite any change of ownership of either dominant or servient tenement, although it will be extinguished if the two tenemants come into common ownership. An easement can only be enjoyed in respect of land. This means two parcels of land. First there must be a 'dominant tenement' and a 'servient tenement'. Dominant tenement to which the benefit of the easement attaches, and another (servient tenement which bears the burden of the easement. A positive easement consist of a right to do something on the land of another; a negative easement restrict the use of owner of the serviant tenement may make of his land. An easement may be on land or on the house made on land. The next classification is on easement on the ground, and the other one under the ground. An easement shall be done in accordance with the principle of restrictions. This means that the less burden the servient tenement. When there is doubt about the extent of the actual easement shall take what easier the servient tenement. The new needs of the dominant estate does not result in the expansion of servitude. In the article is made comparison between The Draft Code of property and other real estate, and The Draft of Civil Code of Serbia.

  15. Functional classifications for cerebral palsy: correlations between the gross motor function classification system (GMFCS), the manual ability classification system (MACS) and the communication function classification system (CFCS).

    Science.gov (United States)

    Compagnone, Eliana; Maniglio, Jlenia; Camposeo, Serena; Vespino, Teresa; Losito, Luciana; De Rinaldis, Marta; Gennaro, Leonarda; Trabacca, Antonio

    2014-11-01

    This study aimed to investigate a possible correlation between the gross motor function classification system-expanded and revised (GMFCS-E&R), the manual abilities classification system (MACS) and the communication function classification system (CFCS) functional levels in children with cerebral palsy (CP) by CP subtype. It was also geared to verify whether there is a correlation between these classification systems and intellectual functioning (IF) and parental socio-economic status (SES). A total of 87 children (47 males and 40 females, age range 4-18 years, mean age 8.9±4.2) were included in the study. A strong correlation was found between the three classifications: Level V of the GMFCS-E&R corresponds to Level V of the MACS (rs=0.67, p=0.001); the same relationship was found for the CFCS and the MACS (rs=0.73, p<0.001) and for the GMFCS-E&R and the CFCS (rs=0.61, p=0.001). The correlations between the IQ and the global functional disability profile were strong or moderate (GMFCS and IQ: rs=0.66, p=0.001; MACS and IQ: rs=0.58, p=0.001; CFCS and MACS: rs=0.65, p=0.001). The Kruskal-Wallis test was used to determine if there were differences between the GMFCS-E&R, the CFCS and the MACS by CP type. CP types showed different scores for the IQ level (Chi-square=8.59, df=2, p=0.014), the GMFCS-E&R (Chi-square=36.46, df=2, p<0.001), the CFCS (Chi-square=12.87, df=2, p=0.002), and the MACS Level (Chi-square=13.96, df=2, p<0.001) but no significant differences emerged for the SES (Chi-square=1.19, df=2, p=0.554). This study shows how the three functional classifications (GMFCS-E&R, CFCS and MACS) complement each other to provide a better description of the functional profile of CP. The systematic evaluation of the IQ can provide useful information about a possible future outcome for every functional level. The SES does not appear to affect functional profiles. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Critical Evaluation of Headache Classifications.

    Science.gov (United States)

    Özge, Aynur

    2013-08-01

    Transforming a subjective sense like headache into an objective state and establishing a common language for this complaint which can be both a symptom and a disease all by itself have kept the investigators busy for years. Each recommendation proposed has brought along a set of patients who do not meet the criteria. While almost the most ideal and most comprehensive classification studies continued at this point, this time criticisims about withdrawing from daily practice came to the fore. In this article, the classification adventure of scientists who work in the area of headache will be summarized. More specifically, 2 classifications made by the International Headache Society (IHS) and the point reached in relation with the 3rd classification which is still being worked on will be discussed together with headache subtypes. It has been presented with the wish and belief that it will contribute to the readers and young investigators who are interested in this subject.

  17. The last classification of vasculitis

    NARCIS (Netherlands)

    Kallenberg, Cees G. M.

    2008-01-01

    Systemic vasculitides are a group of diverse conditions characterized by inflammation of the blood vessels. To obtain homogeneity in clinical characteristics, prognosis, and response to treatment, patients with vasculitis should be classified into defined disease categories. Many classification

  18. Radon classification of building ground

    International Nuclear Information System (INIS)

    Slunga, E.

    1988-01-01

    The Laboratories of Building Technology and Soil Mechanics and Foundation Engineering at the Helsinki University of Technology in cooperation with The Ministry of the Environment have proposed a radon classification for building ground. The proposed classification is based on the radon concentration in soil pores and on the permeability of the foundation soil. The classification includes four radon classes: negligible, normal, high and very high. Depending on the radon class the radon-technical solution for structures is chosen. It is proposed that the classification be done in general terms in connection with the site investigations for the planning of land use and in more detail in connection with the site investigations for an individual house. (author)

  19. Deep Learning for ECG Classification

    Science.gov (United States)

    Pyakillya, B.; Kazachenko, N.; Mikhailovsky, N.

    2017-10-01

    The importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG data. However, the main disadvantages of these ML results is use of heuristic hand-crafted or engineered features with shallow feature learning architectures. The problem relies in the possibility not to find most appropriate features which will give high classification accuracy in this ECG problem. One of the proposing solution is to use deep learning architectures where first layers of convolutional neurons behave as feature extractors and in the end some fully-connected (FCN) layers are used for making final decision about ECG classes. In this work the deep learning architecture with 1D convolutional layers and FCN layers for ECG classification is presented and some classification results are showed.

  20. Vehicle classification using mobile sensors.

    Science.gov (United States)

    2013-04-01

    In this research, the feasibility of using mobile traffic sensors for binary vehicle classification on arterial roads is investigated. Features (e.g. : speed related, acceleration/deceleration related, etc.) are extracted from vehicle traces (passeng...

  1. Classification of remotely sensed images

    CSIR Research Space (South Africa)

    Dudeni, N

    2008-10-01

    Full Text Available For this research, the researchers examine various existing image classification algorithms with the aim of demonstrating how these algorithms can be applied to remote sensing images. These algorithms are broadly divided into supervised...

  2. Classification of Building Object Types

    DEFF Research Database (Denmark)

    Jørgensen, Kaj Asbjørn

    2011-01-01

    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 managed by software applications and on the basis of building models. Classification systems with taxonomies of building object types have many application opportunities but can still be beneficial in data exchange between building construction partners. However, this will be performed by new methods...

  3. VT Biodiversity Project - Bedrock Classification

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) This dataset is a five category, nine sub-category classification of the bedrock units appearing on the Centennial Geologic Map of Vermont. The...

  4. Classification of Cortical Brain Malformations

    Directory of Open Access Journals (Sweden)

    J Gordon Millichap

    2008-03-01

    Full Text Available Clinical, radiological, and genetic classifications of 113 cases of malformations of cortical development (MCD were evaluated at the Erasmus Medical Center-Sophia Children's Hospital, Rotterdam, the Netherlands.

  5. Comparison of Danish dichotomous and BI-RADS classifications of mammographic density

    DEFF Research Database (Denmark)

    Hodge, Rebecca; Hellmann, Sophie Sell; von Euler-Chelpin, My

    2014-01-01

    BACKGROUND: In the Copenhagen mammography screening program from 1991 to 2001, mammographic density was classified either as fatty or mixed/dense. This dichotomous mammographic density classification system is unique internationally, and has not been validated before. PURPOSE: To compare the Danish...... dichotomous mammographic density classification system from 1991 to 2001 with the density BI-RADS classifications, in an attempt to validate the Danish classification system. MATERIAL AND METHODS: The study sample consisted of 120 mammograms taken in Copenhagen in 1991-2001, which tested false positive......, and which were in 2012 re-assessed and classified according to the BI-RADS classification system. We calculated inter-rater agreement between the Danish dichotomous mammographic classification as fatty or mixed/dense and the four-level BI-RADS classification by the linear weighted Kappa statistic. RESULTS...

  6. Phylogenetic classification of bony fishes.

    Science.gov (United States)

    Betancur-R, Ricardo; Wiley, Edward O; Arratia, Gloria; Acero, Arturo; Bailly, Nicolas; Miya, Masaki; Lecointre, Guillaume; Ortí, Guillermo

    2017-07-06

    Fish classifications, as those of most other taxonomic groups, are being transformed drastically as new molecular phylogenies provide support for natural groups that were unanticipated by previous studies. A brief review of the main criteria used by ichthyologists to define their classifications during the last 50 years, however, reveals slow progress towards using an explicit phylogenetic framework. Instead, the trend has been to rely, in varying degrees, on deep-rooted anatomical concepts and authority, often mixing taxa with explicit phylogenetic support with arbitrary groupings. Two leading sources in ichthyology frequently used for fish classifications (JS Nelson's volumes of Fishes of the World and W. Eschmeyer's Catalog of Fishes) fail to adopt a global phylogenetic framework despite much recent progress made towards the resolution of the fish Tree of Life. The first explicit phylogenetic classification of bony fishes was published in 2013, based on a comprehensive molecular phylogeny ( www.deepfin.org ). We here update the first version of that classification by incorporating the most recent phylogenetic results. The updated classification presented here is based on phylogenies inferred using molecular and genomic data for nearly 2000 fishes. A total of 72 orders (and 79 suborders) are recognized in this version, compared with 66 orders in version 1. The phylogeny resolves placement of 410 families, or ~80% of the total of 514 families of bony fishes currently recognized. The ordinal status of 30 percomorph families included in this study, however, remains uncertain (incertae sedis in the series Carangaria, Ovalentaria, or Eupercaria). Comments to support taxonomic decisions and comparisons with conflicting taxonomic groups proposed by others are presented. We also highlight cases were morphological support exist for the groups being classified. This version of the phylogenetic classification of bony fishes is substantially improved, providing resolution

  7. A classification of chinese culture

    OpenAIRE

    Fan, Y

    2000-01-01

    This paper presents a classification of Chinese Cultural Values (CCVs). Although there exist great differences between the Mainland China, Hong Kong and Taiwan, it is still possible to identify certain core cultural values that are shared by the Chinese people no matter where they live. Based on the original list by the Chinese Cultural Connection (1987), the paper creates a new list that contains 71 core values against 40 in the old. The implications and limitations of the classification are...

  8. Classification of pyodestructive pulmonary diseases

    International Nuclear Information System (INIS)

    Muromskij, Yu.A.; Semivolkov, V.I.; Shlenova, L.A.

    1993-01-01

    Classification of pyodestructive lungs diseases, thier complications and outcomes is proposed which makes it possible for physioians engaged in studying respiratory organs pathology to orient themselves in problems of diagnosis and treatment tactics. The above classification is developed on the basis of studying the disease anamnesis and its clinical process, as well as on the basis of roentgenological and morphological study results by more than 10000 patients

  9. 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...

  10. Track classification within wireless sensor network

    Science.gov (United States)

    Doumerc, Robin; Pannetier, Benjamin; Moras, Julien; Dezert, Jean; Canevet, Loic

    2017-05-01

    In this paper, we present our study on track classification by taking into account environmental information and target estimated states. The tracker uses several motion model adapted to different target dynamics (pedestrian, ground vehicle and SUAV, i.e. small unmanned aerial vehicle) and works in centralized architecture. The main idea is to explore both: classification given by heterogeneous sensors and classification obtained with our fusion module. The fusion module, presented in his paper, provides a class on each track according to track location, velocity and associated uncertainty. To model the likelihood on each class, a fuzzy approach is used considering constraints on target capability to move in the environment. Then the evidential reasoning approach based on Dempster-Shafer Theory (DST) is used to perform a time integration of this classifier output. The fusion rules are tested and compared on real data obtained with our wireless sensor network.In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of this system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

  11. 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...

  12. Ototoxicity (cochleotoxicity) classifications: A review.

    Science.gov (United States)

    Crundwell, Gemma; Gomersall, Phil; Baguley, David M

    2016-01-01

    Drug-mediated ototoxicity, specifically cochleotoxicity, is a concern for patients receiving medications for the treatment of serious illness. A number of classification schemes exist, most of which are based on pure-tone audiometry, in order to assist non-audiological/non-otological specialists in the identification and monitoring of iatrogenic hearing loss. This review identifies the primary classification systems used in cochleototoxicity monitoring. By bringing together classifications published in discipline-specific literature, the paper aims to increase awareness of their relative strengths and limitations in the assessment and monitoring of ototoxic hearing loss and to indicate how future classification systems may improve upon the status-quo. Literature review. PubMed identified 4878 articles containing the search term ototox*. A systematic search identified 13 key classification systems. Cochleotoxicity classification systems can be divided into those which focus on hearing change from a baseline audiogram and those that focus on the functional impact of the hearing loss. Common weaknesses of these grading scales included a lack of sensitivity to small adverse changes in hearing thresholds, a lack of high-frequency audiometry (>8 kHz), and lack of indication of which changes are likely to be clinically significant for communication and quality of life.

  13. 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...

  14. Biogeographic classification of the Caspian Sea

    Science.gov (United States)

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

    2014-11-01

    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 maps (SOMs) and (ii) a synthesis of the most relevant features into a reduced number of marine ecoregions using the hierarchical agglomerative clustering (HAC) method. From an initial set of 12 potential physical variables, 6 independent variables were selected for the classification algorithm, i.e., sea surface temperature (SST), bathymetry, sea ice, seasonal variation of sea surface salinity (DSSS), total suspended matter (TSM) and its seasonal variation (DTSM). The classification results reveal a robust separation between the northern and the middle/southern basins as well as a separation of the shallow nearshore waters from those offshore. The observed patterns in ecoregions can be attributed to differences in climate and geochemical factors such as distance from river, water depth and currents. A comparison of the annual and monthly mean Chl a concentrations between the different ecoregions shows significant differences (one-way ANOVA, P qualitative evaluation of differences in community composition based on recorded presence-absence patterns of 25 different species of plankton, fish and benthic invertebrate also confirms the relevance of the ecoregions as proxies for habitats with common biological characteristics.

  15. AUTOMATIC APPROACH TO VHR SATELLITE IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    P. Kupidura

    2016-06-01

    preliminary step of recalculation of pixel DNs to reflectance is required. Thanks to this, the proposed approach is in theory universal, and might be applied to different satellite system images of different acquisition dates. The test data consists of 3 Pleiades images captured on different dates. Research allowed to determine optimal indices values. Using the same parameters, we obtained a very good accuracy of extraction of 5 land cover/use classes: water, low vegetation, bare soil, wooded area and built-up area in all the test images (kappa from 87% to 96%. What constitutes important, even significant changes in parameter values, did not cause a significant declination of classification accuracy, which demonstrates how robust the proposed method is.

  16. 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

  17. 5 CFR 1312.7 - Derivative classification.

    Science.gov (United States)

    2010-01-01

    ..., DOWNGRADING, DECLASSIFICATION AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION Classification and Declassification of National Security Information § 1312.7 Derivative classification. A derivative classification... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Derivative classification. 1312.7 Section...

  18. 32 CFR 2400.15 - Classification guides.

    Science.gov (United States)

    2010-07-01

    ... REGULATIONS TO IMPLEMENT E.O. 12356; OFFICE OF SCIENCE AND TECHNOLOGY POLICY INFORMATION SECURITY PROGRAM 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 shall...

  19. 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 be...

  20. 22 CFR 42.11 - Classification symbols.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Classification symbols. 42.11 Section 42.11... NATIONALITY ACT, AS AMENDED Classification and Foreign State Chargeability § 42.11 Classification symbols. A... visa symbol to show the classification of the alien. Immigrants Symbol Class Section of law Immediate...

  1. 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 FPI...

  2. 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. Lot...

  3. 22 CFR 9.8 - Classification challenges.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Classification challenges. 9.8 Section 9.8 Foreign Relations DEPARTMENT OF STATE GENERAL SECURITY INFORMATION REGULATIONS § 9.8 Classification... classification status is improper are expected and encouraged to challenge the classification status of the...

  4. 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... classification, it shall be sent to the appropriate agency with original classification authority over the...

  5. 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... authority. The name and position, or personal identifier, of the original classification authority shall...

  6. Intra- and Interobserver Reliability of Three Classification Systems for Hallux Rigidus.

    Science.gov (United States)

    Dillard, Sarita; Schilero, Christina; Chiang, Sharon; Pham, Peter

    2018-04-18

    There are over ten classification systems currently used in the staging of hallux rigidus. This results in confusion and inconsistency with radiographic interpretation and treatment. The reliability of hallux rigidus classification systems has not yet been tested. The purpose of this study was to evaluate intra- and interobserver reliability using three commonly used classifications for hallux rigidus. Twenty-one plain radiograph sets were presented to ten ACFAS board-certified foot and ankle surgeons. Each physician classified each radiograph based on clinical experience and knowledge according to the Regnauld, Roukis, and Hattrup and Johnson classification systems. The two-way mixed single-measure consistency intraclass correlation was used to calculate intra- and interrater reliability. The intrarater reliability of individual sets for the Roukis and Hattrup and Johnson classification systems was "fair to good" (Roukis, 0.62±0.19; Hattrup and Johnson, 0.62±0.28), whereas the intrarater reliability of individual sets for the Regnauld system bordered between "fair to good" and "poor" (0.43±0.24). The interrater reliability of the mean classification was "excellent" for all three classification systems. Conclusions Reliable and reproducible classification systems are essential for treatment and prognostic implications in hallux rigidus. In our study, Roukis classification system had the best intrarater reliability. Although there are various classification systems for hallux rigidus, our results indicate that all three of these classification systems show reliability and reproducibility.

  7. Application of ant colony optimization in NPP classification fault location

    International Nuclear Information System (INIS)

    Xie Chunli; Liu Yongkuo; Xia Hong

    2009-01-01

    Nuclear Power Plant is a highly complex structural system with high safety requirements. Fault location appears to be particularly important to enhance its safety. Ant Colony Optimization is a new type of optimization algorithm, which is used in the fault location and classification of nuclear power plants in this paper. Taking the main coolant system of the first loop as the study object, using VB6.0 programming technology, the NPP fault location system is designed, and is tested against the related data in the literature. Test results show that the ant colony optimization can be used in the accurate classification fault location in the nuclear power plants. (authors)

  8. Dry eye disease: pathophysiology, classification, and diagnosis.

    Science.gov (United States)

    Perry, Henry D

    2008-04-01

    Dry eye disease (DED) is a multifactorial disorder of the tear film and ocular surface that results in eye discomfort, visual disturbance, and often ocular surface damage. Although recent research has made progress in elucidating DED pathophysiology, currently there are no uniform diagnostic criteria. This article discusses the normal anatomy and physiology of the lacrimal functional unit and the tear film; the pathophysiology of DED; DED etiology, classification, and risk factors; and DED diagnosis, including symptom assessment and the roles of selected diagnostic tests.

  9. Lenke and King classification systems for adolescent idiopathic scoliosis: interobserver agreement and postoperative results

    Directory of Open Access Journals (Sweden)

    Hosseinpour-Feizi H

    2011-12-01

    Full Text Available Hojjat Hosseinpour-Feizi, Jafar Soleimanpour, Jafar Ganjpour Sales, Ali ArzroumchilarDepartment of Orthopedics, Shohada Hospital, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, IranPurpose: The aim of this study was to investigate the interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis, and to compare the results of surgery performed based on classification of the scoliosis according to each of these classification systems.Methods: The study was conducted in Shohada Hospital in Tabriz, Iran, between 2009 and 2010. First, a reliability assessment was undertaken to assess interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis. Second, postoperative efficacy and safety of surgery performed based on the Lenke and King classifications were compared. Kappa coefficients of agreement were calculated to assess the agreement. Outcomes were compared using bivariate tests and repeated measures analysis of variance.Results: A low to moderate interobserver agreement was observed for the King classification; the Lenke classification yielded mostly high agreement coefficients. The outcome of surgery was not found to be substantially different between the two systems.Conclusion: Based on the results, the Lenke classification method seems advantageous. This takes into consideration the Lenke classification’s priority in providing details of curvatures in different anatomical surfaces to explain precise intensity of scoliosis, that it has higher interobserver agreement scores, and also that it leads to noninferior postoperative results compared with the King classification method.Keywords: test reliability, scoliosis classification, postoperative efficacy, adolescents

  10. Comprehensive Application of the International Classification of Headache Disorders Third Edition, Beta Version

    OpenAIRE

    Kim, Byung-Kun; Cho, Soo-Jin; Kim, Byung-Su; Sohn, Jong-Hee; Kim, Soo-Kyoung; Cha, Myoung-Jin; Song, Tae-Jin; Kim, Jae-Moon; Park, Jeong Wook; Chu, Min Kyung; Park, Kwang-Yeol; Moon, Heui-Soo

    2015-01-01

    The purpose of this study was to test the feasibility and usefulness of the International Classification of Headache Disorders, third edition, beta version (ICHD-3?), and compare the differences with the International Classification of Headache Disorders, second edition (ICHD-2). Consecutive first-visit patients were recruited from 11 headache clinics in Korea. Headache classification was performed in accordance with ICHD-3?. The characteristics of headaches were analyzed and the feasibility ...

  11. Tweet-based Target Market Classification Using Ensemble Method

    Directory of Open Access Journals (Sweden)

    Muhammad Adi Khairul Anshary

    2016-09-01

    Full Text Available Target market classification is aimed at focusing marketing activities on the right targets. Classification of target markets can be done through data mining and by utilizing data from social media, e.g. Twitter. The end result of data mining are learning models that can classify new data. Ensemble methods can improve the accuracy of the models and therefore provide better results. In this study, classification of target markets was conducted on a dataset of 3000 tweets in order to extract features. Classification models were constructed to manipulate the training data using two ensemble methods (bagging and boosting. To investigate the effectiveness of the ensemble methods, this study used the CART (classification and regression tree algorithm for comparison. Three categories of consumer goods (computers, mobile phones and cameras and three categories of sentiments (positive, negative and neutral were classified towards three target-market categories. Machine learning was performed using Weka 3.6.9. The results of the test data showed that the bagging method improved the accuracy of CART with 1.9% (to 85.20%. On the other hand, for sentiment classification, the ensemble methods were not successful in increasing the accuracy of CART. The results of this study may be taken into consideration by companies who approach their customers through social media, especially Twitter.

  12. IRIS COLOUR CLASSIFICATION SCALES--THEN AND NOW.

    Science.gov (United States)

    Grigore, Mariana; Avram, Alina

    2015-01-01

    Eye colour is one of the most obvious phenotypic traits of an individual. Since the first documented classification scale developed in 1843, there have been numerous attempts to classify the iris colour. In the past centuries, iris colour classification scales has had various colour categories and mostly relied on comparison of an individual's eye with painted glass eyes. Once photography techniques were refined, standard iris photographs replaced painted eyes, but this did not solve the problem of painted/ printed colour variability in time. Early clinical scales were easy to use, but lacked objectivity and were not standardised or statistically tested for reproducibility. The era of automated iris colour classification systems came with the technological development. Spectrophotometry, digital analysis of high-resolution iris images, hyper spectral analysis of the human real iris and the dedicated iris colour analysis software, all accomplished an objective, accurate iris colour classification, but are quite expensive and limited in use to research environment. Iris colour classification systems evolved continuously due to their use in a wide range of studies, especially in the fields of anthropology, epidemiology and genetics. Despite the wide range of the existing scales, up until present there has been no generally accepted iris colour classification scale.

  13. IRIS COLOUR CLASSIFICATION SCALES – THEN AND NOW

    Science.gov (United States)

    Grigore, Mariana; Avram, Alina

    2015-01-01

    Eye colour is one of the most obvious phenotypic traits of an individual. Since the first documented classification scale developed in 1843, there have been numerous attempts to classify the iris colour. In the past centuries, iris colour classification scales has had various colour categories and mostly relied on comparison of an individual’s eye with painted glass eyes. Once photography techniques were refined, standard iris photographs replaced painted eyes, but this did not solve the problem of painted/ printed colour variability in time. Early clinical scales were easy to use, but lacked objectivity and were not standardised or statistically tested for reproducibility. The era of automated iris colour classification systems came with the technological development. Spectrophotometry, digital analysis of high-resolution iris images, hyper spectral analysis of the human real iris and the dedicated iris colour analysis software, all accomplished an objective, accurate iris colour classification, but are quite expensive and limited in use to research environment. Iris colour classification systems evolved continuously due to their use in a wide range of studies, especially in the fields of anthropology, epidemiology and genetics. Despite the wide range of the existing scales, up until present there has been no generally accepted iris colour classification scale. PMID:27373112

  14. Featureless classification of light curves

    Science.gov (United States)

    Kügler, S. D.; Gianniotis, N.; Polsterer, K. L.

    2015-08-01

    In the era of rapidly increasing amounts of time series data, classification of variable objects has become the main objective of time-domain astronomy. Classification of irregularly sampled time series is particularly difficult because the data cannot be represented naturally as a vector which can be directly fed into a classifier. In the literature, various statistical features serve as vector representations. In this work, we represent time series by a density model. The density model captures all the information available, including measurement errors. Hence, we view this model as a generalization to the static features which directly can be derived, e.g. as moments from the density. Similarity between each pair of time series is quantified by the distance between their respective models. Classification is performed on the obtained distance matrix. In the numerical experiments, we use data from the OGLE (Optical Gravitational Lensing Experiment) and ASAS (All Sky Automated Survey) surveys and demonstrate that the proposed representation performs up to par with the best currently used feature-based approaches. The density representation preserves all static information present in the observational data, in contrast to a less-complete description by features. The density representation is an upper boundary in terms of information made available to the classifier. Consequently, the predictive power of the proposed classification depends on the choice of similarity measure and classifier, only. Due to its principled nature, we advocate that this new approach of representing time series has potential in tasks beyond classification, e.g. unsupervised learning.

  15. A Semisupervised Cascade Classification Algorithm

    Directory of Open Access Journals (Sweden)

    Stamatis Karlos

    2016-01-01

    Full Text Available Classification is one of the most important tasks of data mining techniques, which have been adopted by several modern applications. The shortage of enough labeled data in the majority of these applications has shifted the interest towards using semisupervised methods. Under such schemes, the use of collected unlabeled data combined with a clearly smaller set of labeled examples leads to similar or even better classification accuracy against supervised algorithms, which use labeled examples exclusively during the training phase. A novel approach for increasing semisupervised classification using Cascade Classifier technique is presented in this paper. The main characteristic of Cascade Classifier strategy is the use of a base classifier for increasing the feature space by adding either the predicted class or the probability class distribution of the initial data. The classifier of the second level is supplied with the new dataset and extracts the decision for each instance. In this work, a self-trained NB∇C4.5 classifier algorithm is presented, which combines the characteristics of Naive Bayes as a base classifier and the speed of C4.5 for final classification. We performed an in-depth comparison with other well-known semisupervised classification methods on standard benchmark datasets and we finally reached to the point that the presented technique has better accuracy in most cases.

  16. Motor Oil Classification using Color Histograms and Pattern Recognition Techniques.

    Science.gov (United States)

    Ahmadi, Shiva; Mani-Varnosfaderani, Ahmad; Habibi, Biuck

    2018-04-20

    Motor oil classification is important for quality control and the identification of oil adulteration. In thiswork, we propose a simple, rapid, inexpensive and nondestructive approach based on image analysis and pattern recognition techniques for the classification of nine different types of motor oils according to their corresponding color histograms. For this, we applied color histogram in different color spaces such as red green blue (RGB), grayscale, and hue saturation intensity (HSI) in order to extract features that can help with the classification procedure. These color histograms and their combinations were used as input for model development and then were statistically evaluated by using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and support vector machine (SVM) techniques. Here, two common solutions for solving a multiclass classification problem were applied: (1) transformation to binary classification problem using a one-against-all (OAA) approach and (2) extension from binary classifiers to a single globally optimized multilabel classification model. In the OAA strategy, LDA, QDA, and SVM reached up to 97% in terms of accuracy, sensitivity, and specificity for both the training and test sets. In extension from binary case, despite good performances by the SVM classification model, QDA and LDA provided better results up to 92% for RGB-grayscale-HSI color histograms and up to 93% for the HSI color map, respectively. In order to reduce the numbers of independent variables for modeling, a principle component analysis algorithm was used. Our results suggest that the proposed method is promising for the identification and classification of different types of motor oils.

  17. 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.

  18. Rock suitability classification RSC 2012

    International Nuclear Information System (INIS)

    McEwen, T.; Kapyaho, A.; Hella, P.; Aro, S.; Kosunen, P.; Mattila, J.; Pere, T.

    2012-12-01

    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

  19. 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.

  20. Oral epithelial dysplasia classification systems

    DEFF Research Database (Denmark)

    Warnakulasuriya, S; Reibel, J; Bouquot, J

    2008-01-01

    At a workshop coordinated by the WHO Collaborating Centre for Oral Cancer and Precancer in the United Kingdom issues related to potentially malignant disorders of the oral cavity were discussed by an expert group. The consensus views of the Working Group are presented in a series of papers....... In this 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...... use. Although most oral pathologists possibly recognize and accept the criteria for grading epithelial dysplasia, firstly based on architectural features and then of cytology, there is great variability in their interpretation of the presence, degree and significance of the individual criteria...

  1. FULLY CONVOLUTIONAL NETWORKS FOR GROUND CLASSIFICATION FROM LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    A. Rizaldy

    2018-05-01

    Full Text Available Deep Learning has been massively used for image classification in recent years. The use of deep learning for ground classification from LIDAR point clouds has also been recently studied. However, point clouds need to be converted into an image in order to use Convolutional Neural Networks (CNNs. In state-of-the-art techniques, this conversion is slow because each point is converted into a separate image. This approach leads to highly redundant computation during conversion and classification. The goal of this study is to design a more efficient data conversion and ground classification. This goal is achieved by first converting the whole point cloud into a single image. The classification is then performed by a Fully Convolutional Network (FCN, a modified version of CNN designed for pixel-wise image classification. The proposed method is significantly faster than state-of-the-art techniques. On the ISPRS Filter Test dataset, it is 78 times faster for conversion and 16 times faster for classification. Our experimental analysis on the same dataset shows that the proposed method results in 5.22 % of total error, 4.10 % of type I error, and 15.07 % of type II error. Compared to the previous CNN-based technique and LAStools software, the proposed method reduces the total error and type I error (while type II error is slightly higher. The method was also tested on a very high point density LIDAR point clouds resulting in 4.02 % of total error, 2.15 % of type I error and 6.14 % of type II error.

  2. Fully Convolutional Networks for Ground Classification from LIDAR Point Clouds

    Science.gov (United States)

    Rizaldy, A.; Persello, C.; Gevaert, C. M.; Oude Elberink, S. J.

    2018-05-01

    Deep Learning has been massively used for image classification in recent years. The use of deep learning for ground classification from LIDAR point clouds has also been recently studied. However, point clouds need to be converted into an image in order to use Convolutional Neural Networks (CNNs). In state-of-the-art techniques, this conversion is slow because each point is converted into a separate image. This approach leads to highly redundant computation during conversion and classification. The goal of this study is to design a more efficient data conversion and ground classification. This goal is achieved by first converting the whole point cloud into a single image. The classification is then performed by a Fully Convolutional Network (FCN), a modified version of CNN designed for pixel-wise image classification. The proposed method is significantly faster than state-of-the-art techniques. On the ISPRS Filter Test dataset, it is 78 times faster for conversion and 16 times faster for classification. Our experimental analysis on the same dataset shows that the proposed method results in 5.22 % of total error, 4.10 % of type I error, and 15.07 % of type II error. Compared to the previous CNN-based technique and LAStools software, the proposed method reduces the total error and type I error (while type II error is slightly higher). The method was also tested on a very high point density LIDAR point clouds resulting in 4.02 % of total error, 2.15 % of type I error and 6.14 % of type II error.

  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. Deep learning for image classification

    Science.gov (United States)

    McCoppin, Ryan; Rizki, Mateen

    2014-06-01

    This paper provides an overview of deep learning and introduces the several subfields of deep learning including a specific tutorial of convolutional neural networks. Traditional methods for learning image features are compared to deep learning techniques. In addition, we present our preliminary classification results, our basic implementation of a convolutional restricted Boltzmann machine on the Mixed National Institute of Standards and Technology database (MNIST), and we explain how to use deep learning networks to assist in our development of a robust gender classification system.

  6. 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.

  7. Project implementation : classification of organic soils and classification of marls - training of INDOT personnel.

    Science.gov (United States)

    2012-09-01

    This is an implementation project for the research completed as part of the following projects: SPR3005 Classification of Organic Soils : and SPR3227 Classification of Marl Soils. The methods developed for the classification of both soi...

  8. Failure diagnosis using deep belief learning based health state classification

    International Nuclear Information System (INIS)

    Tamilselvan, Prasanna; Wang, Pingfeng

    2013-01-01

    Effective health diagnosis provides multifarious benefits such as improved safety, improved reliability and reduced costs for operation and maintenance of complex engineered systems. This paper presents a novel multi-sensor health diagnosis method using deep belief network (DBN). DBN has recently become a popular approach in machine learning for its promised advantages such as fast inference and the ability to encode richer and higher order network structures. The DBN employs a hierarchical structure with multiple stacked restricted Boltzmann machines and works through a layer by layer successive learning process. The proposed multi-sensor health diagnosis methodology using DBN based state classification can be structured in three consecutive stages: first, defining health states and preprocessing sensory data for DBN training and testing; second, developing DBN based classification models for diagnosis of predefined health states; third, validating DBN classification models with testing sensory dataset. Health diagnosis using DBN based health state classification technique is compared with four existing diagnosis techniques. Benchmark classification problems and two engineering health diagnosis applications: aircraft engine health diagnosis and electric power transformer health diagnosis are employed to demonstrate the efficacy of the proposed approach

  9. APPLICATION OF SENSOR FUSION TO IMPROVE UAV IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    S. Jabari

    2017-08-01

    Full Text Available Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan camera along with either a colour camera or a four-band multi-spectral (MS camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC. We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

  10. Application of Sensor Fusion to Improve Uav Image Classification

    Science.gov (United States)

    Jabari, S.; Fathollahi, F.; Zhang, Y.

    2017-08-01

    Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan) camera along with either a colour camera or a four-band multi-spectral (MS) camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC). We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

  11. Classification of Strawberry Fruit Shape by Machine Learning

    Science.gov (United States)

    Ishikawa, T.; Hayashi, A.; Nagamatsu, S.; Kyutoku, Y.; Dan, I.; Wada, T.; Oku, K.; Saeki, Y.; Uto, T.; Tanabata, T.; Isobe, S.; Kochi, N.

    2018-05-01

    Shape is one of the most important traits of agricultural products due to its relationships with the quality, quantity, and value of the products. For strawberries, the nine types of fruit shape were defined and classified by humans based on the sampler patterns of the nine types. In this study, we tested the classification of strawberry shapes by machine learning in order to increase the accuracy of the classification, and we introduce the concept of computerization into this field. Four types of descriptors were extracted from the digital images of strawberries: (1) the Measured Values (MVs) including the length of the contour line, the area, the fruit length and width, and the fruit width/length ratio; (2) the Ellipse Similarity Index (ESI); (3) Elliptic Fourier Descriptors (EFDs), and (4) Chain Code Subtraction (CCS). We used these descriptors for the classification test along with the random forest approach, and eight of the nine shape types were classified with combinations of MVs + CCS + EFDs. CCS is a descriptor that adds human knowledge to the chain codes, and it showed higher robustness in classification than the other descriptors. Our results suggest machine learning's high ability to classify fruit shapes accurately. We will attempt to increase the classification accuracy and apply the machine learning methods to other plant species.

  12. FACET CLASSIFICATIONS OF E-LEARNING TOOLS

    Directory of Open Access Journals (Sweden)

    Olena Yu. Balalaieva

    2013-12-01

    Full Text Available The article deals with the classification of e-learning tools based on the facet method, which suggests the separation of the parallel set of objects into independent classification groups; at the same time it is not assumed rigid classification structure and pre-built finite groups classification groups are formed by a combination of values taken from the relevant facets. An attempt to systematize the existing classification of e-learning tools from the standpoint of classification theory is made for the first time. Modern Ukrainian and foreign facet classifications of e-learning tools are described; their positive and negative features compared to classifications based on a hierarchical method are analyzed. The original author's facet classification of e-learning tools is proposed.

  13. Definition and classification of epilepsy. Classification of epileptic seizures 2016

    Directory of Open Access Journals (Sweden)

    K. Yu. Mukhin

    2017-01-01

    Full Text Available Epilepsy is one of the most common neurological diseases, especially in childhood and adolescence. The incidence varies from 15 to 113 cases per 100 000 population with the maximum among children under 1 year old. The prevalence of epilepsy is high, ranging from 5 to 8 cases (in some regions – 10 cases per 1000 children under 15 years old. Classification of the disease has great importance for diagnosis, treatment and prognosis. The article presents a novel strategy for classification of epileptic seizures, developed in 2016. It contains a number of brand new concepts, including a very important one, saying that some seizures, previously considered as generalized or focal only, can be, in fact, both focal and generalized. They include tonic, atonic, myoclonic seizures and epileptic spasms. The term “secondarily generalized seizure” is replace by the term “bilateral tonic-clonic seizure” (as soon as it is not a separate type of epileptic seizures, and the term reflects the spread of discharge from any area of cerebral cortex and evolution of any types of focal seizures. International League Against Epilepsy recommends to abandon the term “pseudo-epileptic seizures” and replace it by the term “psychogenic non-epileptic seizures”. If a doctor is not sure that seizures have epileptic nature, the term “paroxysmal event” should be used without specifying the disease. The conception of childhood epileptic encephalopathies, developed within this novel classification project, is one of the most significant achievements, since in this case not only the seizures, but even epileptiform activity can induce severe disorders of higher mental functions. In addition to detailed description of the new strategy for classification of epileptic seizures, the article contains a comprehensive review of the existing principles of epilepsy and epileptic seizures classification.

  14. A proposal for a test method for assessment of hazard property HP 12 (“Release of an acute toxic gas”) in hazardous waste classification - Experience from 49 waste

    OpenAIRE

    Hennebert , Pierre; Samaali , Ismahen; Molina , Pauline

    2016-01-01

    International audience; A stepwise method for assessment of the HP 12 is proposed and tested with 49 waste samples. The hazard property HP 12 is defined as “Release of an acute toxic gas”: waste which releases acute toxic gases (Acute Tox. 1, 2 or 3) in contact with water or an acid. When a waste contains a substance assigned to one of the following supplemental hazards EUH029, EUH031 and EUH032, it shall be classified as hazardous by HP 12 according to test methods or guidelines (EC, 2014a, ...

  15. Can Automatic Classification Help to Increase Accuracy in Data Collection?

    Directory of Open Access Journals (Sweden)

    Frederique Lang

    2016-09-01

    Full Text Available Purpose: The authors aim at testing the performance of a set of machine learning algorithms that could improve the process of data cleaning when building datasets. Design/methodology/approach: The paper is centered on cleaning datasets gathered from publishers and online resources by the use of specific keywords. In this case, we analyzed data from the Web of Science. The accuracy of various forms of automatic classification was tested here in comparison with manual coding in order to determine their usefulness for data collection and cleaning. We assessed the performance of seven supervised classification algorithms (Support Vector Machine (SVM, Scaled Linear Discriminant Analysis, Lasso and elastic-net regularized generalized linear models, Maximum Entropy, Regression Tree, Boosting, and Random Forest and analyzed two properties: accuracy and recall. We assessed not only each algorithm individually, but also their combinations through a voting scheme. We also tested the performance of these algorithms with different sizes of training data. When assessing the performance of different combinations, we used an indicator of coverage to account for the agreement and disagreement on classification between algorithms. Findings: We found that the performance of the algorithms used vary with the size of the sample for training. However, for the classification exercise in this paper the best performing algorithms were SVM and Boosting. The combination of these two algorithms achieved a high agreement on coverage and was highly accurate. This combination performs well with a small training dataset (10%, which may reduce the manual work needed for classification tasks. Research limitations: The dataset gathered has significantly more records related to the topic of interest compared to unrelated topics. This may affect the performance of some algorithms, especially in their identification of unrelated papers. Practical implications: Although the

  16. Lenke and King classification systems for adolescent idiopathic scoliosis: interobserver agreement and postoperative results.

    Science.gov (United States)

    Hosseinpour-Feizi, Hojjat; Soleimanpour, Jafar; Sales, Jafar Ganjpour; Arzroumchilar, Ali

    2011-01-01

    The aim of this study was to investigate the interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis, and to compare the results of surgery performed based on classification of the scoliosis according to each of these classification systems. The study was conducted in Shohada Hospital in Tabriz, Iran, between 2009 and 2010. First, a reliability assessment was undertaken to assess interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis. Second, postoperative efficacy and safety of surgery performed based on the Lenke and King classifications were compared. Kappa coefficients of agreement were calculated to assess the agreement. Outcomes were compared using bivariate tests and repeated measures analysis of variance. A low to moderate interobserver agreement was observed for the King classification; the Lenke classification yielded mostly high agreement coefficients. The outcome of surgery was not found to be substantially different between the two systems. Based on the results, the Lenke classification method seems advantageous. This takes into consideration the Lenke classification's priority in providing details of curvatures in different anatomical surfaces to explain precise intensity of scoliosis, that it has higher interobserver agreement scores, and also that it leads to noninferior postoperative results compared with the King classification method.

  17. Applications of Diagnostic Classification Models: A Literature Review and Critical Commentary

    Science.gov (United States)

    Sessoms, John; Henson, Robert A.

    2018-01-01

    Diagnostic classification models (DCMs) classify examinees based on the skills they have mastered given their test performance. This classification enables targeted feedback that can inform remedial instruction. Unfortunately, applications of DCMs have been criticized (e.g., no validity support). Generally, these evaluations have been brief and…

  18. Comparison analysis for classification algorithm in data mining and the study of model use

    Science.gov (United States)

    Chen, Junde; Zhang, Defu

    2018-04-01

    As a key technique in data mining, classification algorithm was received extensive attention. Through an experiment of classification algorithm in UCI data set, we gave a comparison analysis method for the different algorithms and the statistical test was used here. Than that, an adaptive diagnosis model for preventive electricity stealing and leakage was given as a specific case in the paper.

  19. Ligand and structure-based classification models for Prediction of P-glycoprotein inhibitors

    DEFF Research Database (Denmark)

    Klepsch, Freya; Poongavanam, Vasanthanathan; Ecker, Gerhard Franz

    2014-01-01

    an algorithm based on Euclidean distance. Results show that random forest and SVM performed best for classification of P-gp inhibitors and non-inhibitors, correctly predicting 73/75 % of the external test set compounds. Classification based on the docking experiments using the scoring function Chem...

  20. [Analysis of binary classification repeated measurement data with GEE and GLMMs using SPSS software].

    Science.gov (United States)

    An, Shengli; Zhang, Yanhong; Chen, Zheng

    2012-12-01

    To analyze binary classification repeated measurement data with generalized estimating equations (GEE) and generalized linear mixed models (GLMMs) using SPSS19.0. GEE and GLMMs models were tested using binary classification repeated measurement data sample using SPSS19.0. Compared with SAS, SPSS19.0 allowed convenient analysis of categorical repeated measurement data using GEE and GLMMs.

  1. 18 CFR 3a.11 - Classification of official information.

    Science.gov (United States)

    2010-04-01

    ... classified Top Secret, Secret or Confidential, depending upon the degree of its significance to national... classification categories are defined as follows: (1) Top Secret. Top Secret refers to national security information or material which requires the highest degree of protection. The test for assigning Top Secret...

  2. The value of laparoscopic classifications in decision on definitive ...

    African Journals Online (AJOL)

    The value of laparoscopic classifications in decision on definitive surgery in patients ... was to present our clinical experience with the laparoscopic approach in patients ... in 10 cases in whom cord structures were seen entering the internal inguinal ring. ... Four canalicular testes (peeping) were treated with open orchiopexy.

  3. Discriminant function for classification of genuine and counterfeit ...

    African Journals Online (AJOL)

    Findings of the research revealed that the naira notes are to be classified as counterfeit or genuine according to the model: Z = 440.3007X - 858.8366Y + 147.5228Z such that Z > Z0 where Z0 is the end point of classification. Hotelling's T2 and Mahalanobis quantity were also computed. The test result showed that ...

  4. Benchmarking protein classification algorithms via supervised cross-validation

    NARCIS (Netherlands)

    Kertész-Farkas, A.; Dhir, S.; Sonego, P.; Pacurar, M.; Netoteia, S.; Nijveen, H.; Kuzniar, A.; Leunissen, J.A.M.; Kocsor, A.; Pongor, S.

    2008-01-01

    Development and testing of protein classification algorithms are hampered by the fact that the protein universe is characterized by groups vastly different in the number of members, in average protein size, similarity within group, etc. Datasets based on traditional cross-validation (k-fold,

  5. Latent Partially Ordered Classification Models and Normal Mixtures

    Science.gov (United States)

    Tatsuoka, Curtis; Varadi, Ferenc; Jaeger, Judith

    2013-01-01

    Latent partially ordered sets (posets) can be employed in modeling cognitive functioning, such as in the analysis of neuropsychological (NP) and educational test data. Posets are cognitively diagnostic in the sense that classification states in these models are associated with detailed profiles of cognitive functioning. These profiles allow for…

  6. The Performance of EEG-P300 Classification using Backpropagation Neural Networks

    Directory of Open Access Journals (Sweden)

    Arjon Turnip

    2013-12-01

    Full Text Available Electroencephalogram (EEG recordings signal provide an important function of brain-computer communication, but the accuracy of their classification is very limited in unforeseeable signal variations relating to artifacts. In this paper, we propose a classification method entailing time-series EEG-P300 signals using backpropagation neural networks to predict the qualitative properties of a subject’s mental tasks by extracting useful information from the highly multivariate non-invasive recordings of brain activity. To test the improvement in the EEG-P300 classification performance (i.e., classification accuracy and transfer rate with the proposed method, comparative experiments were conducted using Bayesian Linear Discriminant Analysis (BLDA. Finally, the result of the experiment showed that the average of the classification accuracy was 97% and the maximum improvement of the average transfer rate is 42.4%, indicating the considerable potential of the using of EEG-P300 for the continuous classification of mental tasks.

  7. Agriculture classification using POLSAR data

    DEFF Research Database (Denmark)

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

    2005-01-01

    of their components) show strongly preferred orientations, such as the stalks or ears of cereals. The importance of SAR polarimetry in crop classification arises principally because polarisation is sen-sitive to orientation. Hence it provides a means to distinguish crops with different canopy archi-tectures. Detailed...

  8. Urogenital tuberculosis: definition and classification.

    Science.gov (United States)

    Kulchavenya, Ekaterina

    2014-10-01

    To improve the approach to the diagnosis and management of urogenital tuberculosis (UGTB), we need clear and unique classification. UGTB remains an important problem, especially in developing countries, but it is often an overlooked disease. As with any other infection, UGTB should be cured by antibacterial therapy, but because of late diagnosis it may often require surgery. Scientific literature dedicated to this problem was critically analyzed and juxtaposed with the author's own more than 30 years' experience in tuberculosis urology. The conception, terms and definition were consolidated into one system; classification stage by stage as well as complications are presented. Classification of any disease includes dispersion on forms and stages and exact definitions for each stage. Clinical features and symptoms significantly vary between different forms and stages of UGTB. A simple diagnostic algorithm was constructed. UGTB is multivariant disease and a standard unified approach to it is impossible. Clear definition as well as unique classification are necessary for real estimation of epidemiology and the optimization of therapy. The term 'UGTB' has insufficient information in order to estimate therapy, surgery and prognosis, or to evaluate the epidemiology.

  9. Real time automatic scene classification

    NARCIS (Netherlands)

    Verbrugge, R.; Israël, Menno; Taatgen, N.; van den Broek, Egon; van der Putten, Peter; Schomaker, L.; den Uyl, Marten J.

    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

  10. Unsupervised classification of variable stars

    Science.gov (United States)

    Valenzuela, Lucas; Pichara, Karim

    2018-03-01

    During the past 10 years, a considerable amount of effort has been made to develop algorithms for automatic classification of variable stars. That has been primarily achieved by applying machine learning methods to photometric data sets where objects are represented as light curves. Classifiers require training sets to learn the underlying patterns that allow the separation among classes. Unfortunately, building training sets is an expensive process that demands a lot of human efforts. Every time data come from new surveys; the only available training instances are the ones that have a cross-match with previously labelled objects, consequently generating insufficient training sets compared with the large amounts of unlabelled sources. In this work, we present an algorithm that performs unsupervised classification of variable stars, relying only on the similarity among light curves. We tackle the unsupervised classification problem by proposing an untraditional approach. Instead of trying to match classes of stars with clusters found by a clustering algorithm, we propose a query-based method where astronomers can find groups of variable stars ranked by similarity. We also develop a fast similarity function specific for light curves, based on a novel data structure that allows scaling the search over the entire data set of unlabelled objects. Experiments show that our unsupervised model achieves high accuracy in the classification of different types of variable stars and that the proposed algorithm scales up to massive amounts of light curves.

  11. Automatic indexing, compiling and classification

    International Nuclear Information System (INIS)

    Andreewsky, Alexandre; Fluhr, Christian.

    1975-06-01

    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 [fr

  12. 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...

  13. 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…

  14. Is classification necessary after Google?

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2012-01-01

    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 classification is seen as providing criteria for deciding whether A should be classified as X...

  15. Data Augmentation for Plant Classification

    NARCIS (Netherlands)

    Pawara, Pornntiwa; Okafor, Emmanuel; Schomaker, Lambertus; Wiering, Marco

    2017-01-01

    Data augmentation plays a crucial role in increasing the number of training images, which often aids to improve classification performances of deep learning techniques for computer vision problems. In this paper, we employ the deep learning framework and determine the effects of several

  16. Climatic classification of the Karst

    International Nuclear Information System (INIS)

    Eslava Ramirez Jesus Antonio; Bahamon Ayala, Sandra Marcela; Lopez Romero Maria Ines

    2000-01-01

    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

  17. CLASSIFICATION OF LEARNING MANAGEMENT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Yu. B. Popova

    2016-01-01

    Full Text Available Using of information technologies and, in particular, learning management systems, increases opportunities of teachers and students in reaching their goals in education. Such systems provide learning content, help organize and monitor training, collect progress statistics and take into account the individual characteristics of each user. Currently, there is a huge inventory of both paid and free systems are physically located both on college servers and in the cloud, offering different features sets of different licensing scheme and the cost. This creates the problem of choosing the best system. This problem is partly due to the lack of comprehensive classification of such systems. Analysis of more than 30 of the most common now automated learning management systems has shown that a classification of such systems should be carried out according to certain criteria, under which the same type of system can be considered. As classification features offered by the author are: cost, functionality, modularity, keeping the customer’s requirements, the integration of content, the physical location of a system, adaptability training. Considering the learning management system within these classifications and taking into account the current trends of their development, it is possible to identify the main requirements to them: functionality, reliability, ease of use, low cost, support for SCORM standard or Tin Can API, modularity and adaptability. According to the requirements at the Software Department of FITR BNTU under the guidance of the author since 2009 take place the development, the use and continuous improvement of their own learning management system.

  18. Emotions Classification for Arabic Tweets

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... learning methods for referring to all areas of detecting, analyzing, and classifying ... In this paper, an adaptive model is proposed for emotions classification of ... WEKA data mining tool is used to implement this model and evaluate the ... defined using vector representation, storing a numerical. "importance" ...

  19. 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

  20. Piroxicam derivatives THz classification

    Science.gov (United States)

    Sterczewski, Lukasz A.; Grzelczak, Michal P.; Nowak, Kacper; Szlachetko, Bogusław; Plinska, Stanislawa; Szczesniak-Siega, Berenika; Malinka, Wieslaw; Plinski, Edward F.

    2016-02-01

    In this paper we report a new approach to linking the terahertz spectral shapes of drug candidates having a similar molecular structure to their chemical and physical parameters. We examined 27 newly-synthesized derivatives of a well-known nonsteroidal anti-inflammatory drug Piroxicam used for treatment of inflammatory arthritis and chemoprevention of colon cancer. The testing was carried out by means of terahertz pulsed spectroscopy (TPS). Using chemometric techniques we evaluated their spectral similarity in the terahertz range and attempted to link the position on the principal component analysis (PCA) score map to the similarity of molecular descriptors. A simplified spectral model preserved 75% and 85.1% of the variance in 2 and 3 dimensions respectively, compared to the input 1137. We have found that in 85% of the investigated samples a similarity of the physical and chemical parameters corresponds to a similarity in the terahertz spectra. The effects of data preprocessing on the generated maps are also discussed. The technique presented can support the choice of the most promising drug candidates for clinical trials in pharmacological research.

  1. Retrieval and classification of food images.

    Science.gov (United States)

    Farinella, Giovanni Maria; Allegra, Dario; Moltisanti, Marco; Stanco, Filippo; Battiato, Sebastiano

    2016-10-01

    Automatic food understanding from images is an interesting challenge with applications in different domains. In particular, food intake monitoring is becoming more and more important because of the key role that it plays in health and market economies. In this paper, we address the study of food image processing from the perspective of Computer Vision. As first contribution we present a survey of the studies in the context of food image processing from the early attempts to the current state-of-the-art methods. Since retrieval and classification engines able to work on food images are required to build automatic systems for diet monitoring (e.g., to be embedded in wearable cameras), we focus our attention on the aspect of the representation of the food images because it plays a fundamental role in the understanding engines. The food retrieval and classification is a challenging task since the food presents high variableness and an intrinsic deformability. To properly study the peculiarities of different image representations we propose the UNICT-FD1200 dataset. It was composed of 4754 food images of 1200 distinct dishes acquired during real meals. Each food plate is acquired multiple times and the overall dataset presents both geometric and photometric variabilities. The images of the dataset have been manually labeled considering 8 categories: Appetizer, Main Course, Second Course, Single Course, Side Dish, Dessert, Breakfast, Fruit. We have performed tests employing different representations of the state-of-the-art to assess the related performances on the UNICT-FD1200 dataset. Finally, we propose a new representation based on the perceptual concept of Anti-Textons which is able to encode spatial information between Textons outperforming other representations in the context of food retrieval and Classification. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Whewell on classification and consilience.

    Science.gov (United States)

    Quinn, Aleta

    2017-08-01

    In this paper I sketch William Whewell's attempts to impose order on classificatory mineralogy, which was in Whewell's day (1794-1866) a confused science of uncertain prospects. Whewell argued that progress was impeded by the crude reductionist assumption that all macroproperties of crystals could be straightforwardly explained by reference to the crystals' chemical constituents. By comparison with biological classification, Whewell proposed methodological reforms that he claimed would lead to a natural classification of minerals, which in turn would support advances in causal understanding of the properties of minerals. Whewell's comparison to successful biological classification is particularly striking given that classificatory biologists did not share an understanding of the causal structure underlying the natural classification of life (the common descent with modification of all organisms). Whewell's key proposed methodological reform is consideration of multiple, distinct principles of classification. The most powerful evidence in support of a natural classificatory claim is the consilience of claims arrived at through distinct lines of reasoning, rooted in distinct conceptual approaches to the target objects. Mineralogists must consider not only elemental composition and chemical affinities, but also symmetry and polarity. Geometrical properties are central to what makes an individual mineral the type of mineral that it is. In Whewell's view, function and organization jointly define life, and so are the keys to understanding what makes an organism the type of organism that it is. I explain the relationship between Whewell's teleological account of life and his natural theology. I conclude with brief comments about the importance of Whewell's classificatory theory for the further development of his philosophy of science and in particular his account of consilience. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Functional Basis of Microorganism Classification.

    Science.gov (United States)

    Zhu, Chengsheng; Delmont, Tom O; Vogel, Timothy M; Bromberg, Yana

    2015-08-01

    Correctly identifying nearest "neighbors" of a given microorganism is important in industrial and clinical applications where close relationships imply similar treatment. Microbial classification based on similarity of physiological and genetic organism traits (polyphasic similarity) is experimentally difficult and, arguably, subjective. Evolutionary relatedness, inferred from phylogenetic markers, facilitates classification but does not guarantee functional identity between members of the same taxon or lack of similarity between different taxa. Using over thirteen hundred sequenced bacterial genomes, we built a novel function-based microorganism classification scheme, functional-repertoire similarity-based organism network (FuSiON; flattened to fusion). Our scheme is phenetic, based on a network of quantitatively defined organism relationships across the known prokaryotic space. It correlates significantly with the current taxonomy, but the observed discrepancies reveal both (1) the inconsistency of functional diversity levels among different taxa and (2) an (unsurprising) bias towards prioritizing, for classification purposes, relatively minor traits of particular interest to humans. Our dynamic network-based organism classification is independent of the arbitrary pairwise organism similarity cut-offs traditionally applied to establish taxonomic identity. Instead, it reveals natural, functionally defined organism groupings and is thus robust in handling organism diversity. Additionally, fusion can use organism meta-data to highlight the specific environmental factors that drive microbial diversification. Our approach provides a complementary view to cladistic assignments and holds important clues for further exploration of microbial lifestyles. Fusion is a more practical fit for biomedical, industrial, and ecological applications, as many of these rely on understanding the functional capabilities of the microbes in their environment and are less concerned with

  4. Functional Basis of Microorganism Classification

    Science.gov (United States)

    Zhu, Chengsheng; Delmont, Tom O.; Vogel, Timothy M.; Bromberg, Yana

    2015-01-01

    Correctly identifying nearest “neighbors” of a given microorganism is important in industrial and clinical applications where close relationships imply similar treatment. Microbial classification based on similarity of physiological and genetic organism traits (polyphasic similarity) is experimentally difficult and, arguably, subjective. Evolutionary relatedness, inferred from phylogenetic markers, facilitates classification but does not guarantee functional identity between members of the same taxon or lack of similarity between different taxa. Using over thirteen hundred sequenced bacterial genomes, we built a novel function-based microorganism classification scheme, functional-repertoire similarity-based organism network (FuSiON; flattened to fusion). Our scheme is phenetic, based on a network of quantitatively defined organism relationships across the known prokaryotic space. It correlates significantly with the current taxonomy, but the observed discrepancies reveal both (1) the inconsistency of functional diversity levels among different taxa and (2) an (unsurprising) bias towards prioritizing, for classification purposes, relatively minor traits of particular interest to humans. Our dynamic network-based organism classification is independent of the arbitrary pairwise organism similarity cut-offs traditionally applied to establish taxonomic identity. Instead, it reveals natural, functionally defined organism groupings and is thus robust in handling organism diversity. Additionally, fusion can use organism meta-data to highlight the specific environmental factors that drive microbial diversification. Our approach provides a complementary view to cladistic assignments and holds important clues for further exploration of microbial lifestyles. Fusion is a more practical fit for biomedical, industrial, and ecological applications, as many of these rely on understanding the functional capabilities of the microbes in their environment and are less concerned

  5. Value of multi-slice CT in the classification diagnosis of hilar cholangiocarcinoma

    International Nuclear Information System (INIS)

    Qian Yi; Zeng Mengsu; Ling Zhiqing; Rao Shengxiang; Liu Yalan

    2008-01-01

    Objective: To evaluate the value of multi-slice CT (MSCT) classification in the assessment of the hilar cholangiocarcinoma resectability. Methods: Thirty patients with surgically and histopathologically proved hilar cholangiocarcinomas who underwent preoperative MSCT and were diagnosed correctly were included in present study. Transverse images and reconstructed MPR images were reviewed for Bismuth-Corlette classification and morphological classification of hilar cholangiocarcinoma. Then MSCT classification was compared with findings of surgery and histopathology. Curative resectabilty of different types according to Bismuth-Corlette classification and morphological classification were analyzed with chi-square test. Results: In 30 cases, the numbers of Type I, II, IIIa, IIIb and IV according to Bismuth-Corlette classification were 1, 3, 4, 5 and 17. Seventeen patients underwent curative resections, among which 1, 2, 1, 4 and 9 belonged to Type I, II, IIIa, IIIb and IV respectively. However, there was no significant difference in curative resectability among different types of Bismuth-Corlette classification (χ 2 = 0.9875, P>0.05). In present study, the accuracy of MSCT in Bismuth-Corlette classification reached 86.7% (26/30). The numbers of periductal infiltrating, mass forming and intraductal growing type were 13, 13 and 4, while 6, 8 and 3 cases of each type underwent curative resections. There was no significant difference in curative resectability among different types of morphological classification (χ 2 =1.2583, P>0.05). The accuracy of MSCT in morphological classification was 100% (30/30) in this study group. Conclusion: MSCT can make accurate diagnosis of Bismuth-Corlette classification and morphological classification, which is helpful in preoperative respectability assessment of hilar cholangiocarcinoma. (authors)

  6. Automated classification of Acid Rock Drainage potential from Corescan drill core imagery

    Science.gov (United States)

    Cracknell, M. J.; Jackson, L.; Parbhakar-Fox, A.; Savinova, K.

    2017-12-01

    Classification of the acid forming potential of waste rock is important for managing environmental hazards associated with mining operations. Current methods for the classification of acid rock drainage (ARD) potential usually involve labour intensive and subjective assessment of drill core and/or hand specimens. Manual methods are subject to operator bias, human error and the amount of material that can be assessed within a given time frame is limited. The automated classification of ARD potential documented here is based on the ARD Index developed by Parbhakar-Fox et al. (2011). This ARD Index involves the combination of five indicators: A - sulphide content; B - sulphide alteration; C - sulphide morphology; D - primary neutraliser content; and E - sulphide mineral association. Several components of the ARD Index require accurate identification of sulphide minerals. This is achieved by classifying Corescan Red-Green-Blue true colour images into the presence or absence of sulphide minerals using supervised classification. Subsequently, sulphide classification images are processed and combined with Corescan SWIR-based mineral classifications to obtain information on sulphide content, indices representing sulphide textures (disseminated versus massive and degree of veining), and spatially associated minerals. This information is combined to calculate ARD Index indicator values that feed into the classification of ARD potential. Automated ARD potential classifications of drill core samples associated with a porphyry Cu-Au deposit are compared to manually derived classifications and those obtained by standard static geochemical testing and X-ray diffractometry analyses. Results indicate a high degree of similarity between automated and manual ARD potential classifications. Major differences between approaches are observed in sulphide and neutraliser mineral percentages, likely due to the subjective nature of manual estimates of mineral content. The automated approach

  7. Woven fabric defects detection based on texture classification algorithm

    International Nuclear Information System (INIS)

    Ben Salem, Y.; Nasri, S.

    2011-01-01

    In this paper we have compared two famous methods in texture classification to solve the problem of recognition and classification of defects occurring in a textile manufacture. We have compared local binary patterns method with co-occurrence matrix. The classifier used is the support vector machines (SVM). The system has been tested using TILDA database. The results obtained are interesting and show that LBP is a good method for the problems of recognition and classifcation defects, it gives a good running time especially for the real time applications.

  8. Statistical methods for segmentation and classification of images

    DEFF Research Database (Denmark)

    Rosholm, Anders

    1997-01-01

    The central matter of the present thesis is Bayesian statistical inference applied to classification of images. An initial review of Markov Random Fields relates to the modeling aspect of the indicated main subject. In that connection, emphasis is put on the relatively unknown sub-class of Pickard...... with a Pickard Random Field modeling of a considered (categorical) image phenomemon. An extension of the fast PRF based classification technique is presented. The modification introduces auto-correlation into the model of an involved noise process, which previously has been assumed independent. The suitability...... of the extended model is documented by tests on controlled image data containing auto-correlated noise....

  9. Co-occurrence Models in Music Genre Classification

    DEFF Research Database (Denmark)

    Ahrendt, Peter; Goutte, Cyril; Larsen, Jan

    2005-01-01

    Music genre classification has been investigated using many different methods, but most of them build on probabilistic models of feature vectors x\\_r which only represent the short time segment with index r of the song. Here, three different co-occurrence models are proposed which instead consider...... genre data set with a variety of modern music. The basis was a so-called AR feature representation of the music. Besides the benefit of having proper probabilistic models of the whole song, the lowest classification test errors were found using one of the proposed models....

  10. IMPROVING CLASSIFICATIONS OF ECONOMIC SCIENCES IN A THESAURUS

    Directory of Open Access Journals (Sweden)

    Sergey Vladimirovich Lesnikov

    2013-09-01

    Full Text Available The goal is to study thesaurus as an instrument to define the classification of economic sciences, to adapt their classification to the increased information flow, to increase accuracy of allocation of information resources with consideration of the users’ needs, to suggest making alterations in the classification of economic sciences made by the Institute of Scientific Information for Social Sciences of the Russian Academy of Sciences (INION RAN in 2001.The authors see the classification of economic sciences as a product of social communications theory – a differentiated aspect of social research. Modern science is subdivided into various aspects with varied subjects and methods. The latter overlap and form a hierarchy of concepts in science within the same research subject. The authors stress the importance of information retrieval systems for developing scientific knowledge. Information retrieval systems can immediately deliver data from different areas of science to the user who can then integrate the information and obtain a vivid picture of the research subject. Search engines and rubricators are becoming increasingly important as there is a tendency to isolated thinking with many Internet users.The authors have devised a certain approach to using the thesaurus as the means of sciences classification and as a hyper language of science. The suggested methodological approach to structuring terms and notions via thesaurus have been tested at Syktyvkar State University and Syktyvkar branch of Saint-Petersburg Economic University.Methods: deduction, induction, analysis, synthesis, abstraction technique, classification.Results: there have been defined stages and main sections of the information-retrieval thesaurus of the hyperlanguage of economic science on the basis of existing classification systems of scientific knowledge.Scope of application of results: library services, information technology, education.DOI: http://dx.doi.org/10.12731/2218-7405-2013-8-22

  11. Neural attractor network for application in visual field data classification

    International Nuclear Information System (INIS)

    Fink, Wolfgang

    2004-01-01

    The purpose was to introduce a novel method for computer-based classification of visual field data derived from perimetric examination, that may act as a ' counsellor', providing an independent 'second opinion' to the diagnosing physician. The classification system consists of a Hopfield-type neural attractor network that obtains its input data from perimetric examination results. An iterative relaxation process determines the states of the neurons dynamically. Therefore, even 'noisy' perimetric output, e.g., early stages of a disease, may eventually be classified correctly according to the predefined idealized visual field defect (scotoma) patterns, stored as attractors of the network, that are found with diseases of the eye, optic nerve and the central nervous system. Preliminary tests of the classification system on real visual field data derived from perimetric examinations have shown a classification success of over 80%. Some of the main advantages of the Hopfield-attractor-network-based approach over feed-forward type neural networks are: (1) network architecture is defined by the classification problem; (2) no training is required to determine the neural coupling strengths; (3) assignment of an auto-diagnosis confidence level is possible by means of an overlap parameter and the Hamming distance. In conclusion, the novel method for computer-based classification of visual field data, presented here, furnishes a valuable first overview and an independent 'second opinion' in judging perimetric examination results, pointing towards a final diagnosis by a physician. It should not be considered a substitute for the diagnosing physician. Thanks to the worldwide accessibility of the Internet, the classification system offers a promising perspective towards modern computer-assisted diagnosis in both medicine and tele-medicine, for example and in particular, with respect to non-ophthalmic clinics or in communities where perimetric expertise is not readily available

  12. Screening and classification of ceramic powders

    Science.gov (United States)

    Miwa, S.

    1983-01-01

    A summary is given of the classification technology of ceramic powders. Advantages and disadvantages of the wet and dry screening and classification methods are discussed. Improvements of wind force screening devices are described.

  13. 5 CFR 1312.3 - Classification requirements.

    Science.gov (United States)

    2010-01-01

    ..., DOWNGRADING, DECLASSIFICATION AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION Classification and Declassification of National Security Information § 1312.3 Classification requirements. United States citizens must...; (5) Scientific, technological, or economic matters relating to the national security; (6) United...

  14. 14 CFR 1203.412 - Classification guides.

    Science.gov (United States)

    2010-01-01

    ... of the classification designations (i.e., Top Secret, Secret or Confidential) apply to the identified... writing by an official with original Top Secret classification authority; the identity of the official...

  15. Classification guide: Paralympic Games London 2012

    OpenAIRE

    2013-01-01

    The London 2012 Paralympic Games Classification Guide is designed to provide National Paralympic Committees (NPCs) and International Paralympic Sport Federations (IPSFs) with information about the classification policies and procedures that will apply to the London 2012 Paralympic Games.

  16. Classification guide: Sochi 2014 Paralympic Winter Games

    OpenAIRE

    2014-01-01

    The Sochi 2014 Paralympic Winter Games classification guide is designed to provide National Paralympic Committees (NPCs) and International Federations (IFs) with information about the classification policies and procedures that will apply to the Sochi 2014 Paralympic Winter Games.

  17. Lacie phase 1 Classification and Mensuration Subsystem (CAMS) rework experiment

    Science.gov (United States)

    Chhikara, R. S.; Hsu, E. M.; Liszcz, C. J.

    1976-01-01

    An experiment was designed to test the ability of the Classification and Mensuration Subsystem rework operations to improve wheat proportion estimates for segments that had been processed previously. Sites selected for the experiment included three in Kansas and three in Texas, with the remaining five distributed in Montana and North and South Dakota. The acquisition dates were selected to be representative of imagery available in actual operations. No more than one acquisition per biophase were used, and biophases were determined by actual crop calendars. All sites were worked by each of four Analyst-Interpreter/Data Processing Analyst Teams who reviewed the initial processing of each segment and accepted or reworked it for an estimate of the proportion of small grains in the segment. Classification results, acquisitions and classification errors and performance results between CAMS regular and ITS rework are tabulated.

  18. Can the Ni classification of vessels predict neoplasia?

    DEFF Research Database (Denmark)

    Mehlum, Camilla Slot; Rosenberg, Tine; Dyrvig, Anne-Kirstine

    2018-01-01

    OBJECTIVES: The Ni classification of vascular change from 2011 is well documented for evaluating pharyngeal and laryngeal lesions, primarily focusing on cancer. In the planning of surgery it may be more relevant to differentiate neoplasia from non-neoplasia. We aimed to evaluate the ability...... of the Ni classification to predict laryngeal or hypopharyngeal neoplasia and to investigate if a changed cutoff value would support the recent European Laryngological Society (ELS) proposal of perpendicular vascular changes as indicative of neoplasia. DATA SOURCES: PubMed, Embase, Cochrane, and Scopus....... The pooled sensitivity and specificity of the Ni classification with two different cutoffs were calculated, and bubble and summary receiver operating characteristics plots were created. RESULTS: The combined sensitivity of five studies (n = 687) with Ni type IV-V defined as test-positive was 0.89 (95...

  19. AUTOMATIC CLASSIFICATION OF VARIABLE STARS IN CATALOGS WITH MISSING DATA

    International Nuclear Information System (INIS)

    Pichara, Karim; Protopapas, Pavlos

    2013-01-01

    We present an automatic classification method for astronomical catalogs with missing data. We use Bayesian networks and a probabilistic graphical model that allows us to perform inference to predict missing values given observed data and dependency relationships between variables. To learn a Bayesian network from incomplete data, we use an iterative algorithm that utilizes sampling methods and expectation maximization to estimate the distributions and probabilistic dependencies of variables from data with missing values. To test our model, we use three catalogs with missing data (SAGE, Two Micron All Sky Survey, and UBVI) and one complete catalog (MACHO). We examine how classification accuracy changes when information from missing data catalogs is included, how our method compares to traditional missing data approaches, and at what computational cost. Integrating these catalogs with missing data, we find that classification of variable objects improves by a few percent and by 15% for quasar detection while keeping the computational cost the same

  20. Unsupervised feature learning for autonomous rock image classification

    Science.gov (United States)

    Shu, Lei; McIsaac, Kenneth; Osinski, Gordon R.; Francis, Raymond

    2017-09-01

    Autonomous rock image classification can enhance the capability of robots for geological detection and enlarge the scientific returns, both in investigation on Earth and planetary surface exploration on Mars. Since rock textural images are usually inhomogeneous and manually hand-crafting features is not always reliable, we propose an unsupervised feature learning method to autonomously learn the feature representation for rock images. In our tests, rock image classification using the learned features shows that the learned features can outperform manually selected features. Self-taught learning is also proposed to learn the feature representation from a large database of unlabelled rock images of mixed class. The learned features can then be used repeatedly for classification of any subclass. This takes advantage of the large dataset of unlabelled rock images and learns a general feature representation for many kinds of rocks. We show experimental results supporting the feasibility of self-taught learning on rock images.

  1. AUTOMATIC CLASSIFICATION OF VARIABLE STARS IN CATALOGS WITH MISSING DATA

    Energy Technology Data Exchange (ETDEWEB)

    Pichara, Karim [Computer Science Department, Pontificia Universidad Católica de Chile, Santiago (Chile); Protopapas, Pavlos [Institute for Applied Computational Science, Harvard University, Cambridge, MA (United States)

    2013-11-10

    We present an automatic classification method for astronomical catalogs with missing data. We use Bayesian networks and a probabilistic graphical model that allows us to perform inference to predict missing values given observed data and dependency relationships between variables. To learn a Bayesian network from incomplete data, we use an iterative algorithm that utilizes sampling methods and expectation maximization to estimate the distributions and probabilistic dependencies of variables from data with missing values. To test our model, we use three catalogs with missing data (SAGE, Two Micron All Sky Survey, and UBVI) and one complete catalog (MACHO). We examine how classification accuracy changes when information from missing data catalogs is included, how our method compares to traditional missing data approaches, and at what computational cost. Integrating these catalogs with missing data, we find that classification of variable objects improves by a few percent and by 15% for quasar detection while keeping the computational cost the same.

  2. Classification of urine sediment based on convolution neural network

    Science.gov (United States)

    Pan, Jingjing; Jiang, Cunbo; Zhu, Tiantian

    2018-04-01

    By designing a new convolution neural network framework, this paper breaks the constraints of the original convolution neural network framework requiring large training samples and samples of the same size. Move and cropping the input images, generate the same size of the sub-graph. And then, the generated sub-graph uses the method of dropout, increasing the diversity of samples and preventing the fitting generation. Randomly select some proper subset in the sub-graphic set and ensure that the number of elements in the proper subset is same and the proper subset is not the same. The proper subsets are used as input layers for the convolution neural network. Through the convolution layer, the pooling, the full connection layer and output layer, we can obtained the classification loss rate of test set and training set. In the red blood cells, white blood cells, calcium oxalate crystallization classification experiment, the classification accuracy rate of 97% or more.

  3. Rational kernels for Arabic Root Extraction and Text Classification

    Directory of Open Access Journals (Sweden)

    Attia Nehar

    2016-04-01

    Full Text Available In this paper, we address the problems of Arabic Text Classification and root extraction using transducers and rational kernels. We introduce a new root extraction approach on the basis of the use of Arabic patterns (Pattern Based Stemmer. Transducers are used to model these patterns and root extraction is done without relying on any dictionary. Using transducers for extracting roots, documents are transformed into finite state transducers. This document representation allows us to use and explore rational kernels as a framework for Arabic Text Classification. Root extraction experiments are conducted on three word collections and yield 75.6% of accuracy. Classification experiments are done on the Saudi Press Agency dataset and N-gram kernels are tested with different values of N. Accuracy and F1 report 90.79% and 62.93% respectively. These results show that our approach, when compared with other approaches, is promising specially in terms of accuracy and F1.

  4. Robust tissue classification for reproducible wound assessment in telemedicine environments

    Science.gov (United States)

    Wannous, Hazem; Treuillet, Sylvie; Lucas, Yves

    2010-04-01

    In telemedicine environments, a standardized and reproducible assessment of wounds, using a simple free-handled digital camera, is an essential requirement. However, to ensure robust tissue classification, particular attention must be paid to the complete design of the color processing chain. We introduce the key steps including color correction, merging of expert labeling, and segmentation-driven classification based on support vector machines. The tool thus developed ensures stability under lighting condition, viewpoint, and camera changes, to achieve accurate and robust classification of skin tissues. Clinical tests demonstrate that such an advanced tool, which forms part of a complete 3-D and color wound assessment system, significantly improves the monitoring of the healing process. It achieves an overlap score of 79.3 against 69.1% for a single expert, after mapping on the medical reference developed from the image labeling by a college of experts.

  5. Link prediction boosted psychiatry disorder classification for functional connectivity network

    Science.gov (United States)

    Li, Weiwei; Mei, Xue; Wang, Hao; Zhou, Yu; Huang, Jiashuang

    2017-02-01

    Functional connectivity network (FCN) is an effective tool in psychiatry disorders classification, and represents cross-correlation of the regional blood oxygenation level dependent signal. However, FCN is often incomplete for suffering from missing and spurious edges. To accurate classify psychiatry disorders and health control with the incomplete FCN, we first `repair' the FCN with link prediction, and then exact the clustering coefficients as features to build a weak classifier for every FCN. Finally, we apply a boosting algorithm to combine these weak classifiers for improving classification accuracy. Our method tested by three datasets of psychiatry disorder, including Alzheimer's Disease, Schizophrenia and Attention Deficit Hyperactivity Disorder. The experimental results show our method not only significantly improves the classification accuracy, but also efficiently reconstructs the incomplete FCN.

  6. Improvement of Classification of Enterprise Circulating Funds

    OpenAIRE

    Rohanova Hanna O.

    2014-01-01

    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, ...

  7. Detecting Hijacked Journals by Using Classification Algorithms.

    Science.gov (United States)

    Andoohgin Shahri, Mona; Jazi, Mohammad Davarpanah; Borchardt, Glenn; Dadkhah, Mehdi

    2018-04-01

    Invalid journals are recent challenges in the academic world and many researchers are unacquainted with the phenomenon. The number of victims appears to be accelerating. Researchers might be suspicious of predatory journals because they have unfamiliar names, but hijacked journals are imitations of well-known, reputable journals whose websites have been hijacked. Hijacked journals issue calls for papers via generally laudatory emails that delude researchers into paying exorbitant page charges for publication in a nonexistent journal. This paper presents a method for detecting hijacked journals by using a classification algorithm. The number of published articles exposing hijacked journals is limited and most of them use simple techniques that are limited to specific journals. Hence we needed to amass Internet addresses and pertinent data for analyzing this type of attack. We inspected the websites of 104 scientific journals by using a classification algorithm that used criteria common to reputable journals. We then prepared a decision tree that we used to test five journals we knew were authentic and five we knew were hijacked.

  8. Large margin image set representation and classification

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-07-06

    In this paper, we propose a novel image set representation and classification method by maximizing the margin of image sets. The margin of an image set is defined as the difference of the distance to its nearest image set from different classes and the distance to its nearest image set of the same class. By modeling the image sets by using both their image samples and their affine hull models, and maximizing the margins of the images sets, the image set representation parameter learning problem is formulated as an minimization problem, which is further optimized by an expectation - maximization (EM) strategy with accelerated proximal gradient (APG) optimization in an iterative algorithm. To classify a given test image set, we assign it to the class which could provide the largest margin. Experiments on two applications of video-sequence-based face recognition demonstrate that the proposed method significantly outperforms state-of-the-art image set classification methods in terms of both effectiveness and efficiency.

  9. Diabetes classification using a redundancy reduction preprocessor

    Directory of Open Access Journals (Sweden)

    Áurea Celeste Ribeiro

    Full Text Available Introduction Diabetes patients can benefit significantly from early diagnosis. Thus, accurate automated screening is becoming increasingly important due to the wide spread of that disease. Previous studies in automated screening have found a maximum accuracy of 92.6%. Methods This work proposes a classification methodology based on efficient coding of the input data, which is carried out by decreasing input data redundancy using well-known ICA algorithms, such as FastICA, JADE and INFOMAX. The classifier used in the task to discriminate diabetics from non-diaibetics is the one class support vector machine. Classification tests were performed using noninvasive and invasive indicators. Results The results suggest that redundancy reduction increases one-class support vector machine performance when discriminating between diabetics and nondiabetics up to an accuracy of 98.47% while using all indicators. By using only noninvasive indicators, an accuracy of 98.28% was obtained. Conclusion The ICA feature extraction improves the performance of the classifier in the data set because it reduces the statistical dependence of the collected data, which increases the ability of the classifier to find accurate class boundaries.

  10. Discriminative Bayesian Dictionary Learning for Classification.

    Science.gov (United States)

    Akhtar, Naveed; Shafait, Faisal; Mian, Ajmal

    2016-12-01

    We propose a Bayesian approach to learn discriminative dictionaries for sparse representation of data. The proposed approach infers probability distributions over the atoms of a discriminative dictionary using a finite approximation of Beta Process. It also computes sets of Bernoulli distributions that associate class labels to the learned dictionary atoms. This association signifies the selection probabilities of the dictionary atoms in the expansion of class-specific data. Furthermore, the non-parametric character of the proposed approach allows it to infer the correct size of the dictionary. We exploit the aforementioned Bernoulli distributions in separately learning a linear classifier. The classifier uses the same hierarchical Bayesian model as the dictionary, which we present along the analytical inference solution for Gibbs sampling. For classification, a test instance is first sparsely encoded over the learned dictionary and the codes are fed to the classifier. We performed experiments for face and action recognition; and object and scene-category classification using five public datasets and compared the results with state-of-the-art discriminative sparse representation approaches. Experiments show that the proposed Bayesian approach consistently outperforms the existing approaches.

  11. Large margin image set representation and classification

    KAUST Repository

    Wang, Jim Jing-Yan; Alzahrani, Majed A.; Gao, Xin

    2014-01-01

    In this paper, we propose a novel image set representation and classification method by maximizing the margin of image sets. The margin of an image set is defined as the difference of the distance to its nearest image set from different classes and the distance to its nearest image set of the same class. By modeling the image sets by using both their image samples and their affine hull models, and maximizing the margins of the images sets, the image set representation parameter learning problem is formulated as an minimization problem, which is further optimized by an expectation - maximization (EM) strategy with accelerated proximal gradient (APG) optimization in an iterative algorithm. To classify a given test image set, we assign it to the class which could provide the largest margin. Experiments on two applications of video-sequence-based face recognition demonstrate that the proposed method significantly outperforms state-of-the-art image set classification methods in terms of both effectiveness and efficiency.

  12. Text mining in the classification of digital documents

    Directory of Open Access Journals (Sweden)

    Marcial Contreras Barrera

    2016-11-01

    Full Text Available Objective: Develop an automated classifier for the classification of bibliographic material by means of the text mining. Methodology: The text mining is used for the development of the classifier, based on a method of type supervised, conformed by two phases; learning and recognition, in the learning phase, the classifier learns patterns across the analysis of bibliographical records, of the classification Z, belonging to library science, information sciences and information resources, recovered from the database LIBRUNAM, in this phase is obtained the classifier capable of recognizing different subclasses (LC. In the recognition phase the classifier is validated and evaluates across classification tests, for this end bibliographical records of the classification Z are taken randomly, classified by a cataloguer and processed by the automated classifier, in order to obtain the precision of the automated classifier. Results: The application of the text mining achieved the development of the automated classifier, through the method classifying documents supervised type. The precision of the classifier was calculated doing the comparison among the assigned topics manually and automated obtaining 75.70% of precision. Conclusions: The application of text mining facilitated the creation of automated classifier, allowing to obtain useful technology for the classification of bibliographical material with the aim of improving and speed up the process of organizing digital documents.

  13. Machine-learning methods in the classification of water bodies

    Directory of Open Access Journals (Sweden)

    Sołtysiak Marek

    2016-06-01

    Full Text Available Amphibian species have been considered as useful ecological indicators. They are used as indicators of environmental contamination, ecosystem health and habitat quality., Amphibian species are sensitive to changes in the aquatic environment and therefore, may form the basis for the classification of water bodies. Water bodies in which there are a large number of amphibian species are especially valuable even if they are located in urban areas. The automation of the classification process allows for a faster evaluation of the presence of amphibian species in the water bodies. Three machine-learning methods (artificial neural networks, decision trees and the k-nearest neighbours algorithm have been used to classify water bodies in Chorzów – one of 19 cities in the Upper Silesia Agglomeration. In this case, classification is a supervised data mining method consisting of several stages such as building the model, the testing phase and the prediction. Seven natural and anthropogenic features of water bodies (e.g. the type of water body, aquatic plants, the purpose of the water body (destination, position of the water body in relation to any possible buildings, condition of the water body, the degree of littering, the shore type and fishing activities have been taken into account in the classification. The data set used in this study involved information about 71 different water bodies and 9 amphibian species living in them. The results showed that the best average classification accuracy was obtained with the multilayer perceptron neural network.

  14. Reliability of classification for post-traumatic ankle osteoarthritis.

    Science.gov (United States)

    Claessen, Femke M A P; Meijer, Diederik T; van den Bekerom, Michel P J; Gevers Deynoot, Barend D J; Mallee, Wouter H; Doornberg, Job N; van Dijk, C Niek

    2016-04-01

    The purpose of this study was to identify the most reliable classification system for clinical outcome studies to categorize post-traumatic-fracture-osteoarthritis. A total of 118 orthopaedic surgeons and residents-gathered in the Ankle Platform Study Collaborative Science of Variation Group-evaluated 128 anteroposterior and lateral radiographs of patients after a bi- or trimalleolar ankle fracture on a Web-based platform in order to rate post-traumatic osteoarthritis according to the classification systems coined by (1) van Dijk, (2) Kellgren, and (3) Takakura. Reliability was evaluated with the use of the Siegel and Castellan's multirater kappa measure. Differences between classification systems were compared using the two-sample Z-test. Interobserver agreement of surgeons who participated in the survey was fair for the van Dijk osteoarthritis scale (k = 0.24), and poor for the Takakura (k = 0.19) and the Kellgren systems (k = 0.18) according to the categorical rating of Landis and Koch. This difference in one categorical rating was found to be significant (p osteoarthritis scale, and poor interobserver agreement for the Takakura and Kellgren osteoarthritis classification systems. Because of the low interobserver agreement for the van Dijk, Kellgren, and Takakura classification systems, those systems cannot be used for clinical decision-making. Development of diagnostic criteria on basis of consecutive patients, Level II.

  15. Classification of Hyperspectral Images Using Kernel Fully Constrained Least Squares

    Directory of Open Access Journals (Sweden)

    Jianjun Liu

    2017-11-01

    Full Text Available As a widely used classifier, sparse representation classification (SRC has shown its good performance for hyperspectral image classification. Recent works have highlighted that it is the collaborative representation mechanism under SRC that makes SRC a highly effective technique for classification purposes. If the dimensionality and the discrimination capacity of a test pixel is high, other norms (e.g., ℓ 2 -norm can be used to regularize the coding coefficients, except for the sparsity ℓ 1 -norm. In this paper, we show that in the kernel space the nonnegative constraint can also play the same role, and thus suggest the investigation of kernel fully constrained least squares (KFCLS for hyperspectral image classification. Furthermore, in order to improve the classification performance of KFCLS by incorporating spatial-spectral information, we investigate two kinds of spatial-spectral methods using two regularization strategies: (1 the coefficient-level regularization strategy, and (2 the class-level regularization strategy. Experimental results conducted on four real hyperspectral images demonstrate the effectiveness of the proposed KFCLS, and show which way to incorporate spatial-spectral information efficiently in the regularization framework.

  16. ICF-based classification and measurement of functioning.

    Science.gov (United States)

    Stucki, G; Kostanjsek, N; Ustün, B; Cieza, A

    2008-09-01

    If we aim towards a comprehensive understanding of human functioning and the development of comprehensive programs to optimize functioning of individuals and populations we need to develop suitable measures. The approval of the International Classification, Disability and Health (ICF) in 2001 by the 54th World Health Assembly as the first universally shared model and classification of functioning, disability and health marks, therefore an important step in the development of measurement instruments and ultimately for our understanding of functioning, disability and health. The acceptance and use of the ICF as a reference framework and classification has been facilitated by its development in a worldwide, comprehensive consensus process and the increasing evidence regarding its validity. However, the broad acceptance and use of the ICF as a reference framework and classification will also depend on the resolution of conceptual and methodological challenges relevant for the classification and measurement of functioning. This paper therefore describes first how the ICF categories can serve as building blocks for the measurement of functioning and then the current state of the development of ICF based practical tools and international standards such as the ICF Core Sets. Finally it illustrates how to map the world of measures to the ICF and vice versa and the methodological principles relevant for the transformation of information obtained with a clinical test or a patient-oriented instrument to the ICF as well as the development of ICF-based clinical and self-reported measurement instruments.

  17. Automatic structure classification of small proteins using random forest

    Directory of Open Access Journals (Sweden)

    Hirst Jonathan D

    2010-07-01

    Full Text Available Abstract Background Random forest, an ensemble based supervised machine learning algorithm, is used to predict the SCOP structural classification for a target structure, based on the similarity of its structural descriptors to those of a template structure with an equal number of secondary structure elements (SSEs. An initial assessment of random forest is carried out for domains consisting of three SSEs. The usability of random forest in classifying larger domains is demonstrated by applying it to domains consisting of four, five and six SSEs. Results Random forest, trained on SCOP version 1.69, achieves a predictive accuracy of up to 94% on an independent and non-overlapping test set derived from SCOP version 1.73. For classification to the SCOP Class, Fold, Super-family or Family levels, the predictive quality of the model in terms of Matthew's correlation coefficient (MCC ranged from 0.61 to 0.83. As the number of constituent SSEs increases the MCC for classification to different structural levels decreases. Conclusions The utility of random forest in classifying domains from the place-holder classes of SCOP to the true Class, Fold, Super-family or Family levels is demonstrated. Issues such as introduction of a new structural level in SCOP and the merger of singleton levels can also be addressed using random forest. A real-world scenario is mimicked by predicting the classification for those protein structures from the PDB, which are yet to be assigned to the SCOP classification hierarchy.

  18. Performance-scalable volumetric data classification for online industrial inspection

    Science.gov (United States)

    Abraham, Aby J.; Sadki, Mustapha; Lea, R. M.

    2002-03-01

    Non-intrusive inspection and non-destructive testing of manufactured objects with complex internal structures typically requires the enhancement, analysis and visualization of high-resolution volumetric data. Given the increasing availability of fast 3D scanning technology (e.g. cone-beam CT), enabling on-line detection and accurate discrimination of components or sub-structures, the inherent complexity of classification algorithms inevitably leads to throughput bottlenecks. Indeed, whereas typical inspection throughput requirements range from 1 to 1000 volumes per hour, depending on density and resolution, current computational capability is one to two orders-of-magnitude less. Accordingly, speeding up classification algorithms requires both reduction of algorithm complexity and acceleration of computer performance. A shape-based classification algorithm, offering algorithm complexity reduction, by using ellipses as generic descriptors of solids-of-revolution, and supporting performance-scalability, by exploiting the inherent parallelism of volumetric data, is presented. A two-stage variant of the classical Hough transform is used for ellipse detection and correlation of the detected ellipses facilitates position-, scale- and orientation-invariant component classification. Performance-scalability is achieved cost-effectively by accelerating a PC host with one or more COTS (Commercial-Off-The-Shelf) PCI multiprocessor cards. Experimental results are reported to demonstrate the feasibility and cost-effectiveness of the data-parallel classification algorithm for on-line industrial inspection applications.

  19. Full-motion video analysis for improved gender classification

    Science.gov (United States)

    Flora, Jeffrey B.; Lochtefeld, Darrell F.; Iftekharuddin, Khan M.

    2014-06-01

    The ability of computer systems to perform gender classification using the dynamic motion of the human subject has important applications in medicine, human factors, and human-computer interface systems. Previous works in motion analysis have used data from sensors (including gyroscopes, accelerometers, and force plates), radar signatures, and video. However, full-motion video, motion capture, range data provides a higher resolution time and spatial dataset for the analysis of dynamic motion. Works using motion capture data have been limited by small datasets in a controlled environment. In this paper, we explore machine learning techniques to a new dataset that has a larger number of subjects. Additionally, these subjects move unrestricted through a capture volume, representing a more realistic, less controlled environment. We conclude that existing linear classification methods are insufficient for the gender classification for larger dataset captured in relatively uncontrolled environment. A method based on a nonlinear support vector machine classifier is proposed to obtain gender classification for the larger dataset. In experimental testing with a dataset consisting of 98 trials (49 subjects, 2 trials per subject), classification rates using leave-one-out cross-validation are improved from 73% using linear discriminant analysis to 88% using the nonlinear support vector machine classifier.

  20. 10 CFR 61.55 - Waste classification.

    Science.gov (United States)

    2010-01-01

    ... REGULATORY COMMISSION (CONTINUED) LICENSING REQUIREMENTS FOR LAND DISPOSAL OF RADIOACTIVE WASTE Technical 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 two...

  1. 6 CFR 7.26 - Derivative classification.

    Science.gov (United States)

    2010-01-01

    ... 6 Domestic Security 1 2010-01-01 2010-01-01 false Derivative classification. 7.26 Section 7.26 Domestic Security DEPARTMENT OF HOMELAND SECURITY, OFFICE OF THE SECRETARY CLASSIFIED NATIONAL SECURITY INFORMATION Classified Information § 7.26 Derivative classification. (a) Derivative classification is defined...

  2. 22 CFR 9.6 - Derivative classification.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Derivative classification. 9.6 Section 9.6 Foreign Relations DEPARTMENT OF STATE GENERAL SECURITY INFORMATION REGULATIONS § 9.6 Derivative classification. (a) Definition. Derivative classification is the incorporating, paraphrasing, restating or...

  3. 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 and...

  4. 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 Activities...

  5. 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,” which...

  6. 6 CFR 7.30 - Classification challenges.

    Science.gov (United States)

    2010-01-01

    ... 6 Domestic Security 1 2010-01-01 2010-01-01 false Classification challenges. 7.30 Section 7.30... INFORMATION Classified Information § 7.30 Classification challenges. (a) Authorized holders of information... classified are encouraged and expected to challenge the classification status of that information pursuant to...

  7. 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 United...

  8. 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 to...

  9. 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. The...

  10. 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 department...

  11. 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 guides...

  12. 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 21/2...

  13. Border Lakes land-cover classification

    Science.gov (United States)

    Marvin Bauer; Brian Loeffelholz; Doug. Shinneman

    2009-01-01

    This document contains metadata and description of land-cover classification of approximately 5.1 million acres of land bordering Minnesota, U.S.A. and Ontario, Canada. The classification focused on the separation and identification of specific forest-cover types. Some separation of the nonforest classes also was performed. The classification was derived from multi-...

  14. 22 CFR 9a.4 - Classification.

    Science.gov (United States)

    2010-04-01

    ... 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, 1976.... If the officer determines that the information or material warrants classification, he shall assign...

  15. 75 FR 10529 - Mail Classification Change

    Science.gov (United States)

    2010-03-08

    ... POSTAL REGULATORY COMMISSION [Docket Nos. MC2010-19; Order No. 415] Mail Classification Change...-filed Postal Service request to make a minor modification to the Mail Classification Schedule. The.... concerning a change in classification which reflects a change in terminology from Bulk Mailing Center (BMC...

  16. 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 lot...

  17. 33 CFR 154.1216 - Facility classification.

    Science.gov (United States)

    2010-07-01

    ... 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 that... classification of a facility that handles, stores, or transports animal fats or vegetable oils. The COTP may...

  18. 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 the...

  19. 76 FR 47614 - Mail Classification Change

    Science.gov (United States)

    2011-08-05

    ... POSTAL REGULATORY COMMISSION [Docket No. MC2011-27; Order No. 785] Mail Classification Change...-filed Postal Service request for a change in classification to the ``Reply Rides Free'' program. The... Service filed a notice of classification change pursuant to 39 CFR 3020.90 and 3020.91 concerning the...

  20. 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 for...

  1. 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 soft...

  2. Pattern Classification with Memristive Crossbar Circuits

    Science.gov (United States)

    2016-03-31

    Pattern Classification with Memristive Crossbar Circuits Dmitri B. Strukov Department of Electrical and Computer Engineering Department UC Santa...pattern classification ; deep learning; convolutional neural network networks. Introduction Deep-learning convolutional neural networks (DLCNN), which...the best classification performances on a variety of benchmark tasks [1]. The major challenge in building fast and energy- efficient networks of this

  3. 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) Carbon...

  4. 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 designation...

  5. 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 the...

  6. Maxillectomy defects: a suggested classification scheme.

    Science.gov (United States)

    Akinmoladun, V I; Dosumu, O O; Olusanya, A A; Ikusika, O F

    2013-06-01

    The term "maxillectomy" has been used to describe a variety of surgical procedures for a spectrum of diseases involving a diverse anatomical site. Hence, classifications of maxillectomy defects have often made communication difficult. This article highlights this problem, emphasises the need for a uniform system of classification and suggests a classification system which is simple and comprehensive. Articles related to this subject, especially those with specified classifications of maxillary surgical defects were sourced from the internet through Google, Scopus and PubMed using the search terms maxillectomy defects classification. A manual search through available literature was also done. The review of the materials revealed many classifications and modifications of classifications from the descriptive, reconstructive and prosthodontic perspectives. No globally acceptable classification exists among practitioners involved in the management of diseases in the mid-facial region. There were over 14 classifications of maxillary defects found in the English literature. Attempts made to address the inadequacies of previous classifications have tended to result in cumbersome and relatively complex classifications. A single classification that is based on both surgical and prosthetic considerations is most desirable and is hereby proposed.

  7. Angle′s Molar Classification Revisited

    Directory of Open Access Journals (Sweden)

    Devanshi Yadav

    2014-01-01

    Results: Of the 500 pretreatment study casts assessed 52.4% were definitive Class I, 23.6% were Class II, 2.6% were Class III and the ambiguous cases were 21%. These could be easily classified with our method of classification. Conclusion: This improvised classification technique will help orthodontists in making classification of malocclusion accurate and simple.

  8. New guidelines for dam safety classification

    International Nuclear Information System (INIS)

    Dascal, O.

    1999-01-01

    Elements are outlined of recommended new guidelines for safety classification of dams. Arguments are provided for the view that dam classification systems should require more than one system as follows: (a) classification for selection of design criteria, operation procedures and emergency measures plans, based on potential consequences of a dam failure - the hazard classification of water retaining structures; (b) classification for establishment of surveillance activities and for safety evaluation of dams, based on the probability and consequences of failure - the risk classification of water retaining structures; and (c) classification for establishment of water management plans, for safety evaluation of the entire project, for preparation of emergency measures plans, for definition of the frequency and extent of maintenance operations, and for evaluation of changes and modifications required - the hazard classification of the project. The hazard classification of the dam considers, as consequence, mainly the loss of lives or persons in jeopardy and the property damages to third parties. Difficulties in determining the risk classification of the dam lie in the fact that no tool exists to evaluate the probability of the dam's failure. To overcome this, the probability of failure can be substituted for by a set of dam characteristics that express the failure potential of the dam and its foundation. The hazard classification of the entire project is based on the probable consequences of dam failure influencing: loss of life, persons in jeopardy, property and environmental damage. The classification scheme is illustrated for dam threatening events such as earthquakes and floods. 17 refs., 5 tabs

  9. Stellar Spectral Classification with Locality Preserving Projections ...

    Indian Academy of Sciences (India)

    With the help of computer tools and algorithms, automatic stellar spectral classification has become an area of current interest. The process of stellar spectral classification mainly includes two steps: dimension reduction and classification. As a popular dimensionality reduction technique, Principal Component Analysis (PCA) ...

  10. Classification of high resolution satellite images

    OpenAIRE

    Karlsson, Anders

    2003-01-01

    In this thesis the Support Vector Machine (SVM)is applied on classification of high resolution satellite images. Sveral different measures for classification, including texture mesasures, 1st order statistics, and simple contextual information were evaluated. Additionnally, the image was segmented, using an enhanced watershed method, in order to improve the classification accuracy.

  11. The Classification of Romanian High-Schools

    Science.gov (United States)

    Ivan, Ion; Milodin, Daniel; Naie, Lucian

    2006-01-01

    The article tries to tackle the issue of high-schools classification from one city, district or from Romania. The classification criteria are presented. The National Database of Education is also presented and the application of criteria is illustrated. An algorithm for high-school multi-rang classification is proposed in order to build classes of…

  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 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

  13. 28 CFR 524.73 - Classification procedures.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Classification procedures. 524.73 Section 524.73 Judicial Administration BUREAU OF PRISONS, DEPARTMENT OF JUSTICE INMATE ADMISSION, CLASSIFICATION, AND TRANSFER CLASSIFICATION OF INMATES Central Inmate Monitoring (CIM) System § 524.73...

  14. 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 Foreign Relations DEPARTMENT OF STATE GENERAL SECURITY INFORMATION REGULATIONS § 9.4 Original classification. (a) Definition. Original classification is the initial determination that certain information...

  15. 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. ...

  16. 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.

  17. 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.

  18. Classification differences and maternal mortality

    DEFF Research Database (Denmark)

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

    1999-01-01

    OBJECTIVES: To compare the ways maternal deaths are classified in national statistical offices in Europe and to evaluate the ways classification affects published rates. METHODS: Data on pregnancy-associated deaths were collected in 13 European countries. Cases were classified by a European panel....... This change was substantial in three countries (P 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...... of experts into obstetric or non-obstetric causes. An ICD-9 code (International Classification of Diseases) was attributed to each case. These were compared to the codes given in each country. Correction indices were calculated, giving new estimates of maternal mortality rates. SUBJECTS: There were...

  19. Critical Evaluation of Headache Classifications

    OpenAIRE

    ?ZGE, Aynur

    2013-01-01

    Transforming a subjective sense like headache into an objective state and establishing a common language for this complaint which can be both a symptom and a disease all by itself have kept the investigators busy for years. Each recommendation proposed has brought along a set of patients who do not meet the criteria. While almost the most ideal and most comprehensive classification studies continued at this point, this time criticisims about withdrawing from daily practice came to the fore. I...

  20. Classification of simple current invariants

    CERN Document Server

    Gato-Rivera, Beatriz

    1992-01-01

    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.)

  1. 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...

  2. Texture classification using autoregressive filtering

    Science.gov (United States)

    Lawton, W. M.; Lee, M.

    1984-01-01

    A general theory of image texture models is proposed and its applicability to the problem of scene segmentation using texture classification is discussed. An algorithm, based on half-plane autoregressive filtering, which optimally utilizes second order statistics to discriminate between texture classes represented by arbitrary wide sense stationary random fields is described. Empirical results of applying this algorithm to natural and sysnthesized scenes are presented and future research is outlined.

  3. Classification of posterior vitreous detachment

    OpenAIRE

    Kakehashi, Akihiro; Takezawa, Mikiko; Akiba, Jun

    2013-01-01

    Akihiro Kakehashi,1 Mikiko Takezawa,1 Jun Akiba21Department of Ophthalmology, Jichi Medical University, Saitama Medical Center, Saitama, 2Kanjodori Eye Clinic, Asahikawa, JapanAbstract: Diagnosing a posterior vitreous detachment (PVD) is important for predicting the prognosis and determining the indication for vitreoretinal surgery in many vitreoretinal diseases. This article presents both classifications of a PVD by slit-lamp biomicroscopy and of a shallow PVD by optical coherence tomography...

  4. 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.

  5. Design of a hybrid model for cardiac arrhythmia classification based on Daubechies wavelet transform.

    Science.gov (United States)

    Rajagopal, Rekha; Ranganathan, Vidhyapriya

    2018-06-05

    Automation in cardiac arrhythmia classification helps medical professionals make accurate decisions about the patient's health. The aim of this work was to design a hybrid classification model to classify cardiac arrhythmias. The design phase of the classification model comprises the following stages: preprocessing of the cardiac signal by eliminating detail coefficients that contain noise, feature extraction through Daubechies wavelet transform, and arrhythmia classification using a collaborative decision from the K nearest neighbor classifier (KNN) and a support vector machine (SVM). The proposed model is able to classify 5 arrhythmia classes as per the ANSI/AAMI EC57: 1998 classification standard. Level 1 of the proposed model involves classification using the KNN and the classifier is trained with examples from all classes. Level 2 involves classification using an SVM and is trained specifically to classify overlapped classes. The final classification of a test heartbeat pertaining to a particular class is done using the proposed KNN/SVM hybrid model. The experimental results demonstrated that the average sensitivity of the proposed model was 92.56%, the average specificity 99.35%, the average positive predictive value 98.13%, the average F-score 94.5%, and the average accuracy 99.78%. The results obtained using the proposed model were compared with the results of discriminant, tree, and KNN classifiers. The proposed model is able to achieve a high classification accuracy.

  6. Multi-view Multi-sparsity Kernel Reconstruction for Multi-class Image Classification

    KAUST Repository

    Zhu, Xiaofeng; Xie, Qing; Zhu, Yonghua; Liu, Xingyi; Zhang, Shichao

    2015-01-01

    This paper addresses the problem of multi-class image classification by proposing a novel multi-view multi-sparsity kernel reconstruction (MMKR for short) model. Given images (including test images and training images) representing with multiple

  7. Interobserver Agreement of the Eaton-Glickel Classification for Trapeziometacarpal and Scaphotrapezial Arthrosis

    NARCIS (Netherlands)

    Becker, Stéphanie J. E.; Bruinsma, Wendy E.; Guitton, Thierry G.; van der Horst, Chantal M. A. M.; Strackee, Simon D.; Ring, David; Abdel-Ghany, Mahmoud I.; Abzug, Joshua M.; Adams, Julie; Akabudike, Ngozi M.; Apard, Thomas; Bainbridge, L. C.; Bamberger, H. Brent; Baratz, Mark; Romero Barreto, Camilo Jose; Baxamusa, Taizoon; de Bedout, Ramon; Beldner, Steven; Benhaim, Prosper; Blazar, Philip; Boyer, Martin; Calcagni, Maurizio; Calfee, Ryan P.; Capo, John T.; Cassidy, Charles; Catalano, Louis; Chivers, Karel; DeSilva, Gregory; Dodds, Seth; Edelstein, David M.; Erickson, John M.; Evans, Peter J.; Fernandes, Carlos H.; Gaston, R. Glenn; GIlbert, Richard S.; Grafe, Michael W.; Gray, Robert R. L.; Grunwald, H. W.; Gutow, Andrew P.; Hahn, Peter; Hammert, Warren C.; Hauck, Randy; Hilliard, Stuart M.; Hofmeister, Eric; Huang, Jerry I.; Hutchison, Richard L.; Ilyas, Asif; Jacoby, Sidney M.; Jebson, Peter; Jones, Christopher M.; Kalainov, David M.; Kaplan, F. Thomas D.; Kaplan, Saul; Kennedy, Stephen A.; Kessler, Michael W.; Klinefelter, Ryan; Ko, Jason H.; Kraan, Gerald A.; Kronlage, Steve; Ladd, Amy; Lane, Lewis B.; Lee, Kendrick; Martineau, Paul A.; McAuliffe, John; Merrell, Greg; van Minnen, L. P.; Oliveira Miranda, Cesar Dario; Moreno-Serrano, Constanza L.; Nancollas, Michael; Naquira Escobar, Luis Felipe; Osei, Daniel A.; Owens, Patrick W.; Palmer, Bradley A.; Palmer, M. Jason; Polatsch, Daniel; Rizzo, Marco; Rodner, Craig; Rozental, Tamara D.; Ruchelsman, David; Rumball, Kevin M.; Semenkin, Oleg M.; Shatford, Russell; Siff, Todd; Slater, Robert R.; Soong, Maximillian; Spruijt, Sander; Suarez, Fabio; Swigart, Carrie; Taras, John; Terrono, Andrew L.; Varecka, Thomas F.; Walbeehm, Erik T.; Walter, Frank L.; Weiss, Lawrence; Wills, Brian P. D.; Wint, Jeffrey; Wolf, Jennifer Moriatis; Wyrick, Theresa

    2016-01-01

    To determine whether simplification of the Eaton-Glickel (E-G) classification of trapeziometacarpal (TMC) joint arthrosis (eliminating evaluation of the scaphotrapezial [ST] joint) and information about the patient's symptoms and examination influence interobserver reliability. We also tested the

  8. Minimum acceptable face velocities of laboratory fume hoods and guidelines for their classification

    International Nuclear Information System (INIS)

    Bolton, N.E.; Porter, W.E.; Alcorn, S.P.; Everett, W.S.; Hunt, J.B.; Morehead, J.F.; Higdon, H.F.

    1978-06-01

    Data developed to support the requirement of a 100 LFM minimum face velocity requirement for laboratory fume hoods are summarized. Also included is a description of the Y-12 test hood as well as guidelines for a hood classification scheme

  9. Nuclear reactors transients identification and classification system

    International Nuclear Information System (INIS)

    Bianchi, Paulo Henrique

    2008-01-01

    This work describes the study and test of a system capable to identify and classify transients in thermo-hydraulic systems, using a neural network technique of the self-organizing maps (SOM) type, with the objective of implanting it on the new generations of nuclear reactors. The technique developed in this work consists on the use of multiple networks to do the classification and identification of the transient states, being each network a specialist at one respective transient of the system, that compete with each other using the quantization error, that is a measure given by this type of neural network. This technique showed very promising characteristics that allow the development of new functionalities in future projects. One of these characteristics consists on the potential of each network, besides responding what transient is in course, could give additional information about that transient. (author)

  10. [Landscape classification: research progress and development trend].

    Science.gov (United States)

    Liang, Fa-Chao; Liu, Li-Ming

    2011-06-01

    Landscape classification is the basis of the researches on landscape structure, process, and function, and also, the prerequisite for landscape evaluation, planning, protection, and management, directly affecting the precision and practicability of landscape research. This paper reviewed the research progress on the landscape classification system, theory, and methodology, and summarized the key problems and deficiencies of current researches. Some major landscape classification systems, e. g. , LANMAP and MUFIC, were introduced and discussed. It was suggested that a qualitative and quantitative comprehensive classification based on the ideology of functional structure shape and on the integral consideration of landscape classification utility, landscape function, landscape structure, physiogeographical factors, and human disturbance intensity should be the major research directions in the future. The integration of mapping, 3S technology, quantitative mathematics modeling, computer artificial intelligence, and professional knowledge to enhance the precision of landscape classification would be the key issues and the development trend in the researches of landscape classification.

  11. 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.

  12. Classification of huminite-ICCP System 1994

    Energy Technology Data Exchange (ETDEWEB)

    Sykorova, I. [Institute of Rock Structure and Mechanics, Academy of Science of the Czech Republic, V Holesovicka 41, 182 09 Prague 8 (Czech Republic); Pickel, W. [Coal and Organic Petrology Services Pty Ltd, 23/80 Box Road, Taren Point, NSW 2229 (Australia); Christanis, K. [Department of Geology, University of Patras, 26500 Rio-Patras (Greece); Wolf, M. [Mergelskull 29, 47802 Krefeld (Germany); Taylor, G.H. [15 Hawkesbury Cres, Farrer Act 2607 (Australia); Flores, D. [Departamento de Geologia, Faculdade de Ciencias do Porto, Praca de Gomes Teixeira, 4099-002 Porto (Portugal)

    2005-04-12

    In the new classification (ICCP System 1994), the maceral group huminite has been revised from the previous classification (ICCP, 1971. Int. Handbook Coal Petr., suppl. to 2nd ed.) to accommodate the nomenclature to changes in the other maceral groups, especially the changes in the vitrinite classification (ICCP, 1998. The new vitrinite classification (ICCP System 1994). Fuel 77, 349-358.). The vitrinite and huminite systems have been correlated so that down to the level of sub-maceral groups, the two systems can be used in parallel. At the level of macerals and for finer classifications, the analyst now has, according to the nature of the coal and the purpose of the analysis, a choice of using either of the two classification systems for huminite and vitrinite. This is in accordance with the new ISO Coal Classification that covers low rank coals as well and allows for the simultaneous use of the huminite and vitrinite nomenclature for low rank coals.

  13. Protist classification and the kingdoms of organisms.

    Science.gov (United States)

    Whittaker, R H; Margulis, L

    1978-04-01

    Traditional classification imposed a division into plant-like and animal-like forms on the unicellular eukaryotes, or protists; in a current view the protists are a diverse assemblage of plant-, animal- and fungus-like groups. Classification of these into phyla is difficult because of their relatively simple structure and limited geological record, but study of ultrastructure and other characteristics is providing new insight on protist classification. Possible classifications are discussed, and a summary classification of the living world into kingdoms (Monera, Protista, Fungi, Animalia, Plantae) and phyla is suggested. This classification also suggests groupings of phyla into superphyla and form-superphyla, and a broadened kingdom Protista (including green algae, oomycotes and slime molds but excluding red and brown algae). The classification thus seeks to offer a compromise between the protist and protoctist kingdoms of Whittaker and Margulis and to combine a full listing of phyla with grouping of these for synoptic treatment.

  14. NIM: A Node Influence Based Method for Cancer Classification

    Directory of Open Access Journals (Sweden)

    Yiwen Wang

    2014-01-01

    Full Text Available The classification of different cancer types owns great significance in the medical field. However, the great majority of existing cancer classification methods are clinical-based and have relatively weak diagnostic ability. With the rapid development of gene expression technology, it is able to classify different kinds of cancers using DNA microarray. Our main idea is to confront the problem of cancer classification using gene expression data from a graph-based view. Based on a new node influence model we proposed, this paper presents a novel high accuracy method for cancer classification, which is composed of four parts: the first is to calculate the similarity matrix of all samples, the second is to compute the node influence of training samples, the third is to obtain the similarity between every test sample and each class using weighted sum of node influence and similarity matrix, and the last is to classify each test sample based on its similarity between every class. The data sets used in our experiments are breast cancer, central nervous system, colon tumor, prostate cancer, acute lymphoblastic leukemia, and lung cancer. experimental results showed that our node influence based method (NIM is more efficient and robust than the support vector machine, K-nearest neighbor, C4.5, naive Bayes, and CART.

  15. Improved RMR Rock Mass Classification Using Artificial Intelligence Algorithms

    Science.gov (United States)

    Gholami, Raoof; Rasouli, Vamegh; Alimoradi, Andisheh

    2013-09-01

    Rock mass classification systems such as rock mass rating (RMR) are very reliable means to provide information about the quality of rocks surrounding a structure as well as to propose suitable support systems for unstable regions. Many correlations have been proposed to relate measured quantities such as wave velocity to rock mass classification systems to limit the associated time and cost of conducting the sampling and mechanical tests conventionally used to calculate RMR values. However, these empirical correlations have been found to be unreliable, as they usually overestimate or underestimate the RMR value. The aim of this paper is to compare the results of RMR classification obtained from the use of empirical correlations versus machine-learning methodologies based on artificial intelligence algorithms. The proposed methods were verified based on two case studies located in northern Iran. Relevance vector regression (RVR) and support vector regression (SVR), as two robust machine-learning methodologies, were used to predict the RMR for tunnel host rocks. RMR values already obtained by sampling and site investigation at one tunnel were taken into account as the output of the artificial networks during training and testing phases. The results reveal that use of empirical correlations overestimates the predicted RMR values. RVR and SVR, however, showed more reliable results, and are therefore suggested for use in RMR classification for design purposes of rock structures.

  16. A proposal of criteria for the classification of systemic sclerosis.

    Science.gov (United States)

    Nadashkevich, Oleg; Davis, Paul; Fritzler, Marvin J

    2004-11-01

    Sensitive and specific criteria for the classification of systemic sclerosis are required by clinicians and investigators to achieve higher quality clinical studies and approaches to therapy. A clinical study of systemic sclerosis patients in Europe and Canada led to a set of criteria that achieve high sensitivity and specificity. Both clinical and laboratory investigations of patients with systemic sclerosis, related conditions and diseases with clinical features that can be mistaken as part of the systemic sclerosis spectrum were undertaken. Laboratory investigations included the detection of autoantibodies to centromere proteins, Scl-70 (topoisomerase I), and fibrillarin (U3-RNP). Based on the investigation of 269 systemic sclerosis patients and 720 patients presenting with related and confounding conditions, the following set of criteria for the classification of systemic sclerosis was proposed: 1) autoantibodies to: centromere proteins, Scl-70 (topo I), fibrillarin; 2) bibasilar pulmonary fibrosis; 3) contractures of the digital joints or prayer sign; 4) dermal thickening proximal to the wrists; 5) calcinosis cutis; 6) Raynaud's phenomenon; 7) esophageal distal hypomotility or reflux-esophagitis; 8) sclerodactyly or non-pitting digital edema; 9) teleangiectasias. The classification of definite SSc requires at least three of the above criteria. Criteria for the classification of systemic sclerosis have been proposed. Preliminary testing has defined the sensitivity and specificity of these criteria as high as 99% and 100%, respectively. Testing and validation of the proposed criteria by other clinical centers is required.

  17. Automated retinal vessel type classification in color fundus images

    Science.gov (United States)

    Yu, H.; Barriga, S.; Agurto, C.; Nemeth, S.; Bauman, W.; Soliz, P.

    2013-02-01

    Automated retinal vessel type classification is an essential first step toward machine-based quantitative measurement of various vessel topological parameters and identifying vessel abnormalities and alternations in cardiovascular disease risk analysis. This paper presents a new and accurate automatic artery and vein classification method developed for arteriolar-to-venular width ratio (AVR) and artery and vein tortuosity measurements in regions of interest (ROI) of 1.5 and 2.5 optic disc diameters from the disc center, respectively. This method includes illumination normalization, automatic optic disc detection and retinal vessel segmentation, feature extraction, and a partial least squares (PLS) classification. Normalized multi-color information, color variation, and multi-scale morphological features are extracted on each vessel segment. We trained the algorithm on a set of 51 color fundus images using manually marked arteries and veins. We tested the proposed method in a previously unseen test data set consisting of 42 images. We obtained an area under the ROC curve (AUC) of 93.7% in the ROI of AVR measurement and 91.5% of AUC in the ROI of tortuosity measurement. The proposed AV classification method has the potential to assist automatic cardiovascular disease early detection and risk analysis.

  18. The reliability and reproducibility of the Hertel classification for comminuted proximal humeral fractures compared with the Neer classification

    NARCIS (Netherlands)

    Iordens, Gijs I. T.; Mahabier, Kiran C.; Buisman, Florian E.; Schep, Niels W. L.; Muradin, Galied S. R.; Beenen, Ludo F. M.; Patka, Peter; van Lieshout, Esther M. M.; den Hartog, Dennis

    2016-01-01

    The Neer classification is the most commonly used fracture classification system for proximal humeral fractures. Inter- and intra-observer agreement is limited, especially for comminuted fractures. A possibly more straightforward and reliable classification system is the Hertel classification. The

  19. Behavioral state classification in epileptic brain using intracranial electrophysiology

    Science.gov (United States)

    Kremen, Vaclav; Duque, Juliano J.; Brinkmann, Benjamin H.; Berry, Brent M.; Kucewicz, Michal T.; Khadjevand, Fatemeh; Van Gompel, Jamie; Stead, Matt; St. Louis, Erik K.; Worrell, Gregory A.

    2017-04-01

    Objective. Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. Approach. Data from seven patients (age 34+/- 12 , 4 women) who underwent intracranial depth electrode implantation for iEEG monitoring were included. Spectral power features (0.1-600 Hz) spanning several frequency bands from a single electrode were used to train and test a support vector machine classifier. Main results. Classification accuracy of 97.8  ±  0.3% (normal tissue) and 89.4  ±  0.8% (epileptic tissue) across seven subjects using multiple spectral power features from a single electrode was achieved. Spectral power features from electrodes placed in normal temporal neocortex were found to be more useful (accuracy 90.8  ±  0.8%) for sleep-wake state classification than electrodes located in normal hippocampus (87.1  ±  1.6%). Spectral power in high frequency band features (Ripple (80-250 Hz), Fast Ripple (250-600 Hz)) showed comparable performance for AW and SWS classification as the best performing Berger bands (Alpha, Beta, low Gamma) with accuracy  ⩾90% using a single electrode contact and single spectral feature. Significance. Automated classification of wake and SWS should prove useful for future implantable epilepsy devices with limited computational power, memory, and number of electrodes. Applications include quantifying patient sleep patterns and behavioral state dependent detection, prediction, and electrical stimulation therapies.

  20. Hydrologic landscape regionalisation using deductive classification and random forests.

    Directory of Open Access Journals (Sweden)

    Stuart C Brown

    Full Text Available Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic