WorldWideScience

Sample records for testing color-based classifications

  1. Classification of Serranidae Species Using Color Based Statistical Features

    Directory of Open Access Journals (Sweden)

    Bilal İşçimen

    2017-02-01

    Full Text Available In this study 6 species (Epinephelus aeneus, Epinephelus caninus, Epinephelus costae, Epinephelus marginatus, Hyporthodus haifensis, Mycteroperca rubra of Serranidae family were classified by using a color based feature extraction method. A database which consists of 112 fish images was used in this study. In each image, a fish was located on a white background floor with the same position and the images were taken from different distances. A combination of manual processes and automatic algorithms were applied on images until obtaining colored fish sample images with a black background. Since the presented color based feature extraction method avoids including background, these images were processed by using an automatic algorithm in order to obtain a solid texture image from the fish and extract features. The obtained solid texture image was in HSV color space and used due to extract meaningful information about fish sample. Each of the hue, saturation and value components of the HSV color space was used separately in order to extract 7 statistical features. Hence, totally 21 features were extracted for each fish sample. The extracted features were used within Nearest Neighbor algorithm and 112 fish samples from 6 species were classified with an overall accuracy achievement of 86%.

  2. Disposable platform provides visual and color-based point-of-care anemia self-testing.

    Science.gov (United States)

    Tyburski, Erika A; Gillespie, Scott E; Stoy, William A; Mannino, Robert G; Weiss, Alexander J; Siu, Alexa F; Bulloch, Rayford H; Thota, Karthik; Cardenas, Anyela; Session, Wilena; Khoury, Hanna J; O'Connor, Siobhán; Bunting, Silvia T; Boudreaux, Jeanne; Forest, Craig R; Gaddh, Manila; Leong, Traci; Lyon, L Andrew; Lam, Wilbur A

    2014-10-01

    Anemia, or low blood hemoglobin (Hgb) levels, afflicts 2 billion people worldwide. Currently, Hgb levels are typically measured from blood samples using hematology analyzers, which are housed in hospitals, clinics, or commercial laboratories and require skilled technicians to operate. A reliable, inexpensive point-of-care (POC) Hgb test would enable cost-effective anemia screening and chronically anemic patients to self-monitor their disease. We present a rapid, stand-alone, and disposable POC anemia test that, via a single drop of blood, outputs color-based visual results that correlate with Hgb levels. We tested blood from 238 pediatric and adult patients with anemia of varying degrees and etiologies and compared hematology analyzer Hgb levels with POC Hgb levels, which were estimated via visual interpretation using a color scale and an optional smartphone app for automated analysis. POC Hgb levels correlated with hematology analyzer Hgb levels (r = 0.864 and r = 0.856 for visual interpretation and smartphone app, respectively), and both POC test methods yielded comparable sensitivity and specificity for detecting any anemia (n = 178) (<11 g/dl) (sensitivity: 90.2% and 91.1%, specificity: 83.7% and 79.2%, respectively) and severe anemia (n = 10) (<7 g/dl) (sensitivity: 90.0% and 100%, specificity: 94.6% and 93.9%, respectively). These results demonstrate the feasibility of this POC color-based diagnostic test for self-screening/self-monitoring of anemia. Not applicable. This work was funded by the FDA-funded Atlantic Pediatric Device Consortium, the Georgia Research Alliance, Children's Healthcare of Atlanta, the Georgia Center of Innovation for Manufacturing, and the InVenture Prize and Ideas to Serve competitions at the Georgia Institute of Technology.

  3. A Rorschach Test for Visual Classification Strategies

    Science.gov (United States)

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

    1996-01-01

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

  4. Computerized Classification Testing and Its Relationship to the Testing Goal

    NARCIS (Netherlands)

    van Groen, Maaike; Eggen, Theodorus Johannes Hendrikus Maria; Veldkamp, Bernard P.

    2012-01-01

    Assessment can serve different goals. If the aim of testing is to classify respondents into one of multiple levels instead of obtaining a precise estimate of the respondent’s ability, computerized classification testing can be used. This type of testing requires algorithms for item selection and

  5. 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.

  6. Use of Diagnostic Testing in a Classification Information Program.

    Science.gov (United States)

    Veterans Administration Hospital, Bedford, MA.

    The three parts of this study concern the application of diagnostic testing to measure the effectiveness of classification training, the development of a systematic approach to applying the results, and a long-term study of employee retention of classification information. The measurement instrument selected for diagnostic testing of employees of…

  7. CLASSIFICATION OF CERVICAL CANCER CELLS IN PAP SMEAR SCREENING TEST

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    S. Athinarayanan

    2016-05-01

    Full Text Available Cervical cancer is second topmost cancers among women but also, it was a curable one. Regular smear test can discover the sign of precancerous cell and treated the patient according to the result. However sometimes the detection errors can be occurred by smear thickness, cell overlapping or by un-wanted particles in the smear and cytotechnologists faulty diagnosis. Therefore the reason automatic cancer detection was developed. This was help to increase cancer cell mindfulness, diagnosis accuracy with low cost. This detection process consists of some techniques of the image preprocessing that is segmentation and effective texture feature extraction with SVM classification. Then the Final Classification Results of this proposed technique was compared to the previous classification techniques of KNN and ANN and the result would be very useful to cytotechnologists for their further analysis

  8. Public Value Dimensions: Developing and Testing a Multidimensional Classification

    DEFF Research Database (Denmark)

    Andersen, Lotte Bøgh; Beck Jørgensen, Torben; Kjeldsen, Anne Mette

    2012-01-01

    keeping, efficient supply, professionalism and user focus), and we find systematic differences between organizations at different levels and with different tasks, indicating that the classification is fruitful. The aspiration is to enable more precise analyses of value conflicts and improve......Further integration of the public value literature with other strands of literature within Public Administration necessitates a more specific classification of public values. This paper applies a typology linked to organizational design principles, because this is useful for empirical public...... administration studies. Based on an existing typology of modes of governance, we develop a classification and test it empirically, using survey data from a study of the values of 501 public managers. We distinguish between seven value dimensions (the public at large, rule abidance, societal interests, budget...

  9. Item Overexposure in Computerized Classification Tests Using Sequential Item Selection

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    Alan Huebner

    2012-06-01

    Full Text Available Computerized classification tests (CCTs often use sequential item selection which administers items according to maximizing psychometric information at a cut point demarcating passing and failing scores. This paper illustrates why this method of item selection leads to the overexposure of a significant number of items, and the performances of three different methods for controlling maximum item exposure rates in CCTs are compared. Specifically, the Sympson-Hetter, restricted, and item eligibility methods are examined in two studies realistically simulating different types of CCTs and are evaluated based upon criteria including classification accuracy, the number of items exceeding the desired maximum exposure rate, and test overlap. The pros and cons of each method are discussed from a practical perspective.

  10. Color Based Bags-of-Emotions

    Science.gov (United States)

    Solli, Martin; Lenz, Reiner

    In this paper we describe how to include high level semantic information, such as aesthetics and emotions, into Content Based Image Retrieval. We present a color-based emotion-related image descriptor that can be used for describing the emotional content of images. The color emotion metric used is derived from psychophysical experiments and based on three variables: activity, weight and heat. It was originally designed for single-colors, but recent research has shown that the same emotion estimates can be applied in the retrieval of multi-colored images. Here we describe a new approach, based on the assumption that perceived color emotions in images are mainly affected by homogenous regions, defined by the emotion metric, and transitions between regions. RGB coordinates are converted to emotion coordinates, and for each emotion channel, statistical measurements of gradient magnitudes within a stack of low-pass filtered images are used for finding interest points corresponding to homogeneous regions and transitions between regions. Emotion characteristics are derived for patches surrounding each interest point, and saved in a bag-of-emotions, that, for instance, can be used for retrieving images based on emotional content.

  11. A Biochar Classification System and Associated Test Methods

    Energy Technology Data Exchange (ETDEWEB)

    Camps-Arbestain, Marta; Amonette, James E.; Singh, Balwant; Wang, Tao; Schmidt, Hans-Peter

    2015-02-18

    In this chapter, a biochar classification system related to its use as soil amendment is proposed. This document builds upon previous work and constrains its scope to materials with properties that satisfy the criteria for biochar as defined by either the International Biochar Initiative (IBI) Biochar Standards or the European Biochar Community (EBC) Standards, and it is intended to minimise the need for testing in addition to those required according to the above-mentioned standards. The classification system envisions enabling stakeholders and commercial entities to (i) identify the most suitable biochar to fulfil the requirements for a particular soil and/or land-use, and (ii) distinguish the application of biochar for specific niches (e.g., soilless agriculture). It is based on the best current knowledge and the intention is to periodically review and update the document based on new data and knowledge that become available in the scientific literature. The main thrust of this classification system is based on the direct or indirect beneficial effects that biochar provides from its application to soil. We have classified the potential beneficial effects of biochar application to soils into five categories with their corresponding classes, where applicable: (i) carbon (C) storage value, (ii) fertiliser value, (iii) liming value, (iv) particle-size, and (v) use in soil-less agriculture. A summary of recommended test methods is provided at the end of the chapter.

  12. A Practitioner's Guide for Variable-length Computerized Classification Testing

    Directory of Open Access Journals (Sweden)

    Nathan A. Thompson

    2007-01-01

    Full Text Available Variable-length computerized classification tests, CCTs, (Lin & Spray, 2000; Thompson, 2006 are a powerful and efficient approach to testing for the purpose of classifying examinees into groups. CCTs are designed by the specification of at least five technical components: psychometric model, calibrated item bank, starting point, item selection algorithm, and termination criterion. Several options exist for each of these CCT components, creating a myriad of possible designs. Confusion among designs is exacerbated by the lack of a standardized nomenclature. This article outlines the components of a CCT, common options for each component, and the interaction of options for different components, so that practitioners may more efficiently design CCTs. It also offers a suggestion of nomenclature.

  13. Testing the validity of the ATLS classification of hypovolaemic shock.

    Science.gov (United States)

    Guly, H R; Bouamra, O; Little, R; Dark, P; Coats, T; Driscoll, P; Lecky, F E

    2010-09-01

    The Advanced Trauma Life Support system classifies the severity of shock. The aim of this study is to test the validity of this classification. Admission physiology, injury and outcome variables from adult injured patients presenting to hospitals in England and Wales between 1989 and 2007 and stored on the Trauma Audit and Research Network (TARN) database, were studied. Patients were divided into groups representing the four ATLS classes of shock, based on heart rate (HR) systolic blood pressure (SBP), respiratory rate (RR) and Glasgow Coma Score (GCS). The relationships between variables were examined by classifying the cohort by each recorded variable in turn and deriving the median and interquartile range (IQR) of the remaining three variables. Patients with penetrating trauma and major injuries were examined in sub-group analyses. In blunt trauma patients grouped by HR, the median SBP decreased from 128 mmHg in patients with HR140 BPM. The median RR increased from 18 to 22 bpm and the GCS reduced from 15 to 14. The median HR in hypotensive patients was 88 BPM compared to 83 BPM in normotensive patients and the RR was the same. When grouped by RR, the HR increased with increasing RR but there were no changes in SBP. In trauma patients there is an inter-relationship between derangements of HR, SBP, RR and GCS but not to the same degree as that suggested by the ATLS classification of shock. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

  14. 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…

  15. Classification of groundwater at the Nevada Test Site

    Energy Technology Data Exchange (ETDEWEB)

    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.

  16. 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...

  17. Application of classification principles to improve the reliability of incident classification systems: A test case using HFACS-ADF.

    Science.gov (United States)

    Olsen, Nikki; Williamson, Ann

    2017-09-01

    Accident classification systems are important tools for safety management. Unfortunately, many of the tools available have demonstrated poor reliability of coding, making their validity and usefulness questionable. This paper demonstrates the application of four strategies to improve the reliability of accident and incident classification systems. The strategies include creating a domain-specific system with limitations on system size and careful selection of codes, specifically the reduction of abstract concepts and bias-causing terminology. Using HFACS-ADF as a test case, the system was adapted using the strategies and validated using comprehension and comprehensiveness testing. The new system was then assessed for reliability. The reliability of the system increased by at least 20% at all levels of the classification system following the changes made. The results provide evidence that the application of theoretically and empirically-derived classification principles are effective for improving the reliability of accident and incident classification systems in high hazard industries. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Classification based hypothesis testing in neuroscience: Below-chance level classification rates and overlooked statistical properties of linear parametric classifiers.

    Science.gov (United States)

    Jamalabadi, Hamidreza; Alizadeh, Sarah; Schönauer, Monika; Leibold, Christian; Gais, Steffen

    2016-05-01

    Multivariate pattern analysis (MVPA) has recently become a popular tool for data analysis. Often, classification accuracy as quantified by correct classification rate (CCR) is used to illustrate the size of the effect under investigation. However, we show that in low sample size (LSS), low effect size (LES) data, which is typical in neuroscience, the distribution of CCRs from cross-validation of linear MVPA is asymmetric and can show classification rates considerably below what would be expected from chance classification. Conversely, the mode of the distribution in these cases is above expected chance levels, leading to a spuriously high number of above chance CCRs. This unexpected distribution has strong implications when using MVPA for hypothesis testing. Our analyses warrant the conclusion that CCRs do not well reflect the size of the effect under investigation. Moreover, the skewness of the null-distribution precludes the use of many standard parametric tests to assess significance of CCRs. We propose that MVPA results should be reported in terms of P values, which are estimated using randomization tests. Also, our results show that cross-validation procedures using a low number of folds, e.g. twofold, are generally more sensitive, even though the average CCRs are often considerably lower than those obtained using a higher number of folds. Hum Brain Mapp 37:1842-1855, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  19. Diagnostic Classification Models and Multidimensional Adaptive Testing: A Commentary on Rupp and Templin

    Science.gov (United States)

    Frey, Andreas; Carstensen, Claus H.

    2009-01-01

    On a general level, the objective of diagnostic classifications models (DCMs) lies in a classification of individuals regarding multiple latent skills. In this article, the authors show that this objective can be achieved by multidimensional adaptive testing (MAT) as well. The authors discuss whether or not the restricted applicability of DCMs can…

  20. A New Color-based Lawn Weed Detection Method and Its Integration with Texture-based Methods: A Hybrid Approach

    Science.gov (United States)

    Watchareeruetai, Ukrit; Ohnishi, Noboru

    We propose a color-based weed detection method specifically designed for detecting lawn weeds in winter. The proposed method exploits fuzzy logic to make inference from color information. Genetic algorithm is adopted to search for the optimal combination of color information, fuzzy membership functions, as well as fuzzy rules used in the method. Experimental results show that the proposed color-based method outperforms the conventional texture-based methods when testing with a winter dataset. In addition, we propose a hybrid system that incorporates both texture-based and color-based weed detection methods. It can automatically select a better method to perform weed detection, depending on an input image. The results show that the use of the hybrid system can significantly improve weed control performances for the overall datasets.

  1. 16 CFR 1610.7 - Test sequence and classification criteria.

    Science.gov (United States)

    2010-01-01

    ... test specimens, the test is inconclusive. The fabric cannot be classified. (2) Step 2, Plain Surface... REGULATIONS STANDARD FOR THE FLAMMABILITY OF CLOTHING TEXTILES The Standard § 1610.7 Test sequence and...

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

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    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

  3. Hierarchical colorant-based direct binary search halftoning.

    Science.gov (United States)

    He, Zhen

    2010-07-01

    Colorant-based direct binary search (CB-DBS) halftoning proposed in provides an image quality benchmark for dispersed-dot halftoning algorithms. The objective of this paper is to further push the image quality limit. An algorithm called hierarchical colorant-based direct binary search (HCB-DBS) is developed in this paper. By appropriately integrating yellow colorant into dot-overlapping and dot-positioning controls, it is demonstrated that HCB-DBS can achieve better halftone texture of both individual and joint dot-color planes, without compromising the dot distribution of more visible halftone of cyan and magenta colorants. The input color specification is first converted from colorant space to dot-color space with minimum brightness variation principle for full dot-overlapping control. The dot-colors are then split into groups based upon dot visibility. Hierarchical monochrome DBS halftoning is applied to make dot-positioning decision for each group, constrained on the already generated halftone of the groups with higher priority. And dot-coloring is decided recursively with joint monochrome DBS halftoning constrained on the related total dot distribution. Experiments show HCB-DBS improves halftone texture for both individual and joint dot-color planes. And it reduces the halftone graininess and free of color mottle artifacts, comparing to CB-DBS.

  4. Classification of weld defect based on information fusion technology for radiographic testing system

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Hongquan; Liang, Zeming, E-mail: heavenlzm@126.com; Gao, Jianmin; Dang, Changying [State Key Laboratory for Manufacturing System Engineering, Department of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049 (China)

    2016-03-15

    Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster–Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defect feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.

  5. Project A: Specification of the Predictor Domain and Development of New Selection/Classification Tests.

    Science.gov (United States)

    Peterson, Norman G.; And Others

    1990-01-01

    Describes characteristics of experimental predictor battery of tests developed to supplement the Armed Forces Vocational Aptitude Battery for making selection and classification decisions for entry-level enlisted personnel. Explains procedures used to develop new test battery. Basic psychometric properties of each measure, as determine by large…

  6. 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

  7. A Stochastic Method for Balancing Item Exposure Rates in Computerized Classification Tests

    Science.gov (United States)

    Huebner, Alan; Li, Zhushan

    2012-01-01

    Computerized classification tests (CCTs) classify examinees into categories such as pass/fail, master/nonmaster, and so on. This article proposes the use of stochastic methods from sequential analysis to address item overexposure, a practical concern in operational CCTs. Item overexposure is traditionally dealt with in CCTs by the Sympson-Hetter…

  8. 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

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

    OpenAIRE

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

    2015-01-01

    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-t...

  10. TESTING THE POTENTIAL OF VEGETATION INDICES FOR LAND USE/COVER CLASSIFICATION USING HIGH RESOLUTION DATA

    Directory of Open Access Journals (Sweden)

    A. Karakacan Kuzucu

    2017-11-01

    Full Text Available 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.

  11. 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.

  12. Medical Devices; Immunology and Microbiology Devices; Classification of the BCR–ABL Quantitation Test. Final order.

    Science.gov (United States)

    2017-11-01

    The Food and Drug Administration (FDA or we) is classifying the BCR-ABL quantitation test 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 BCR-ABL quantitation test'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. 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.

  14. 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.

  15. Object Recognition using Feature- and Color-Based Methods

    Science.gov (United States)

    Duong, Tuan; Duong, Vu; Stubberud, Allen

    2008-01-01

    An improved adaptive method of processing image data in an artificial neural network has been developed to enable automated, real-time recognition of possibly moving objects under changing (including suddenly changing) conditions of illumination and perspective. The method involves a combination of two prior object-recognition methods one based on adaptive detection of shape features and one based on adaptive color segmentation to enable recognition in situations in which either prior method by itself may be inadequate. The chosen prior feature-based method is known as adaptive principal-component analysis (APCA); the chosen prior color-based method is known as adaptive color segmentation (ACOSE). These methods are made to interact with each other in a closed-loop system to obtain an optimal solution of the object-recognition problem in a dynamic environment. One of the results of the interaction is to increase, beyond what would otherwise be possible, the accuracy of the determination of a region of interest (containing an object that one seeks to recognize) within an image. Another result is to provide a minimized adaptive step that can be used to update the results obtained by the two component methods when changes of color and apparent shape occur. The net effect is to enable the neural network to update its recognition output and improve its recognition capability via an adaptive learning sequence. In principle, the improved method could readily be implemented in integrated circuitry to make a compact, low-power, real-time object-recognition system. It has been proposed to demonstrate the feasibility of such a system by integrating a 256-by-256 active-pixel sensor with APCA, ACOSE, and neural processing circuitry on a single chip. It has been estimated that such a system on a chip would have a volume no larger than a few cubic centimeters, could operate at a rate as high as 1,000 frames per second, and would consume in the order of milliwatts of power.

  16. Perceptual and linguistic interactions in speeded classification: tests of the semantic coding hypothesis.

    Science.gov (United States)

    Martino, G; Marks, L E

    1999-01-01

    We tested the semantic coding hypothesis, which states that cross-modal interactions observed in speeded classification tasks arise after perceptual information is recoded into an abstract format common to perceptual and linguistic systems. Using a speeded classification task, we first confirmed the presence of congruence interactions between auditory pitch and visual lightness and observed Garner-type interference with nonlinguistic (perceptual) stimuli (low-frequency and high-frequency tones, black and white squares). Subsequently, we found that modifying the visual stimuli by (a) making them lexical (related words) or (b) reducing their compactness or figural 'goodness' altered congruence effects and Garner interference. The results are consistent with the semantic coding hypothesis, but only in part, and suggest the need for additional assumptions regarding the role of perceptual organization in cross-modal dimensional interactions.

  17. Testing simulation theory with cross-modal multivariate classification of fMRI data.

    Directory of Open Access Journals (Sweden)

    Joset A Etzel

    Full Text Available The discovery of mirror neurons has suggested a potential neural basis for simulation and common coding theories of action perception, theories which propose that we understand other people's actions because perceiving their actions activates some of our neurons in much the same way as when we perform the actions. We propose testing this model directly in humans with functional magnetic resonance imaging (fMRI by means of cross-modal classification. Cross-modal classification evaluates whether a classifier that has learned to separate stimuli in the sensory domain can also separate the stimuli in the motor domain. Successful classification provides support for simulation theories because it means that the fMRI signal, and presumably brain activity, is similar when perceiving and performing actions. In this paper we demonstrate the feasibility of the technique by showing that classifiers which have learned to discriminate whether a participant heard a hand or a mouth action, based on the activity patterns in the premotor cortex, can also determine, without additional training, whether the participant executed a hand or mouth action. This provides direct evidence that, while perceiving others' actions, (1 the pattern of activity in premotor voxels with sensory properties is a significant source of information regarding the nature of these actions, and (2 that this information shares a common code with motor execution.

  18. Testing simulation theory with cross-modal multivariate classification of fMRI data.

    Science.gov (United States)

    Etzel, Joset A; Gazzola, Valeria; Keysers, Christian

    2008-01-01

    The discovery of mirror neurons has suggested a potential neural basis for simulation and common coding theories of action perception, theories which propose that we understand other people's actions because perceiving their actions activates some of our neurons in much the same way as when we perform the actions. We propose testing this model directly in humans with functional magnetic resonance imaging (fMRI) by means of cross-modal classification. Cross-modal classification evaluates whether a classifier that has learned to separate stimuli in the sensory domain can also separate the stimuli in the motor domain. Successful classification provides support for simulation theories because it means that the fMRI signal, and presumably brain activity, is similar when perceiving and performing actions. In this paper we demonstrate the feasibility of the technique by showing that classifiers which have learned to discriminate whether a participant heard a hand or a mouth action, based on the activity patterns in the premotor cortex, can also determine, without additional training, whether the participant executed a hand or mouth action. This provides direct evidence that, while perceiving others' actions, (1) the pattern of activity in premotor voxels with sensory properties is a significant source of information regarding the nature of these actions, and (2) that this information shares a common code with motor execution.

  19. 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.

  20. 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

  1. Selection and classification of high school volleyball players from performance tests.

    Science.gov (United States)

    Thissen-Milder, M; Mayhew, J L

    1991-09-01

    The purpose of this study were to determine the accuracy of general and specific tests for identifying the players on freshmen (FR), junior varsity (JV), and varsity (VR) teams and the precision of tests to differentiate between starters and nonstarters at each level of play. Fifty high school volleyball players were tested during the first week of practice for six general and four specific motor performance tests. The specific tests included the overhead volley, forearm pass, wall spike, and self bump/set test. The general tests included height, weight, percent body fat, agility run, vertical jump, and two flexibility maneuvers. VR players were significantly better in vertical jump, agility, and all specific ball-handling tests than FR and VJ players. The combination of forearm pass, overhead volley, vertical jump, and weight correctly classified 68% of the players to their team level. The combination of bump-set, height, weight, and shoulder flexibility allowed correct classification of 78% of the starters and nonstarters. General and specific tests can successfully select and classify high school volleyball players.

  2. 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.

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

    Science.gov (United States)

    2011-01-01

    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 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. PMID:22129438

  4. Detecting suboptimal cognitive effort: classification accuracy of the Conner's Continuous Performance Test-II, Brief Test Of Attention, and Trail Making Test.

    Science.gov (United States)

    Busse, Michelle; Whiteside, Douglas

    2012-01-01

    Many cognitive measures have been studied for their ability to detect suboptimal cognitive effort; however, attention measures have not been extensively researched. The current study evaluated the classification accuracy of commonly used attention/concentration measures, the Brief Test of Attention (BTA), Trail Making Test (TMT), and the Conners' Continuous Performance Test (CPT-II). Participants included 413 consecutive patients who completed a comprehensive neuropsychological evaluation. Participants were separated into two groups, identified as either unbiased responders or biased responders as determined by performance on the TOMM. Based on Mann-Whitney U results, the two groups differed significantly on all attentional measures. Classification accuracy of the BTA (.83), CPT-II omission errors (OE; .76) and TMT B (.75) were acceptable; however, classification accuracy of CPT-II commission errors (CE; .64) and TMT A (.62) were poor. When variables were combined in different combinations, sensitivity did not significantly increase. Results indicated for optimal cut-off scores, sensitivity ranged from 48% to 64% when specificity was at least 85%. Given that sensitivity rates were not adequate, there remains a need to utilize highly sensitive measures in addition to these embedded measures. Results were discussed within the context of research promoting the need for multiple measures of cognitive effort.

  5. A color based rangefinder for an omnidirectional camera

    NARCIS (Netherlands)

    Nguyen, Q.; Visser, A.; Balakirsky, S.; Carpin, S.; Lewis, M.

    2009-01-01

    This paper proposes a method to use the omnidirectional camera as a rangefinder by using color detection. The omnicam rangefinder has been tested in USARSim for its accuracy and for its practical use to build maps of the environment. The results of the test shows that an omnidirectional camera can

  6. 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 (pbasketball. 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.

  7. 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.

  8. Determinants of Global Color-Based Selection in Human Visual Cortex.

    Science.gov (United States)

    Bartsch, Mandy V; Boehler, Carsten N; Stoppel, Christian M; Merkel, Christian; Heinze, Hans-Jochen; Schoenfeld, Mircea A; Hopf, Jens-Max

    2015-09-01

    Feature attention operates in a spatially global way, with attended feature values being prioritized for selection outside the focus of attention. Accounts of global feature attention have emphasized feature competition as a determining factor. Here, we use magnetoencephalographic recordings in humans to test whether competition is critical for global feature selection to arise. Subjects performed a color/shape discrimination task in one visual field (VF), while irrelevant color probes were presented in the other unattended VF. Global effects of color attention were assessed by analyzing the response to the probe as a function of whether or not the probe's color was a target-defining color. We find that global color selection involves a sequence of modulations in extrastriate cortex, with an initial phase in higher tier areas (lateral occipital complex) followed by a later phase in lower tier retinotopic areas (V3/V4). Importantly, these modulations appeared with and without color competition in the focus of attention. Moreover, early parts of the modulation emerged for a task-relevant color not even present in the focus of attention. All modulations, however, were eliminated during simple onset-detection of the colored target. These results indicate that global color-based attention depends on target discrimination independent of feature competition in the focus of attention. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. A score test for the agronomical overlap effect in a two-way classification model

    Directory of Open Access Journals (Sweden)

    Aquiles Darghan

    2014-12-01

    Full Text Available In some agricultural research, a treatment applied to an experimental unit may affect the response in the neighboring experimental units. This phenomenon is known as overlap. In this article, a test to evaluate this effect in the Draper and Guttman model was developed by imposing side conditions on the parameters of a two-way classification model to obtain a re-parameterized model which can be used in different neighboring patterns of experimental units, usually plants within a crop, whenever the nearest neighbor is considered a directly affected experimental unit and the two-way model is used. Three methods, namely maximum likelihood, least squares with side conditions and generalized inverse, were used to estimate the parameters of the original model in order to calculate the value of the test statistics for the null hypothesis associated with the absence of the overlapping effect. The three alternatives were invariant with respect to the use of test. The proposed test is simple to adopt and can be implemented in agronomy since its asymptotic nature is in agreement with the large number of experimental units which generally exist in this type of research, where each plant represents the experimental unit being assessed.

  10. 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.

  11. 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. ...

  12. 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.

  13. Classification of spray nozzles based on droplet size distributions and wind tunnel tests.

    Science.gov (United States)

    De Schamphelerie, M; Spanoghe, P; Nuyttens, D; Baetens, K; Cornelis, W; Gabriels, D; Van der Meeren, P

    2006-01-01

    Droplet size distribution of a pesticide spray is recognised as a main factor affecting spray drift. As a first approximation, nozzles can be classified based on their droplet size spectrum. However, the risk of drift for a given droplet size distribution is also a function of spray structure, droplet velocities and entrained air conditions. Wind tunnel tests to determine actual drift potentials of the different nozzles have been proposed as a method of adding an indication of the risk of spray drift to the existing classification based on droplet size distributions (Miller et al, 1995). In this research wind tunnel tests were performed in the wind tunnel of the International Centre for Eremology (I.C.E.), Ghent University, to determine the drift potential of different types and sizes of nozzles at various spray pressures. Flat Fan (F) nozzles Hardi ISO 110 02, 110 03, 110 04, 110 06; Low-Drift (LD) nozzles Hardi ISO 110 02, 110 03, 110 04 and Injet Air Inclusion (AI) nozzles Hardi ISO 110 02, 110 03, 110 04 were tested at a spray pressures of 2, 3 and 4 bar. The droplet size spectra of the F and the LD nozzles were measured with a Malvern Mastersizer at spray pressures 2 bar, 3 bar and 4 bar. The Malvern spectra were used to calculate the Volume Median Diameters (VMD) of the sprays.

  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. Brain fingerprinting classification concealed information test detects US Navy military medical information with P300

    Directory of Open Access Journals (Sweden)

    Lawrence A. Farwell

    2014-12-01

    Full Text Available A classification concealed information test (CIT used the brain fingerprinting method of applying P300 event-related potential (ERP in detecting information that is 1 acquired in real life and 2 unique to US Navy experts in military medicine. Military medicine experts and non-experts were asked to push buttons in response to 3 types of text stimuli. Targets contain known information relevant to military medicine, are identified to subjects as relevant, and require pushing one button. Subjects are told to push another button to all other stimuli. Probes contain concealed information relevant to military medicine, and are not identified to subjects. Irrelevants contain equally plausible, but incorrect/irrelevant information. Error rate was 0%. Median and mean statistical confidences for individual determinations were 99.9% with no indeterminates (results lacking sufficiently high statistical confidence to be classified. We compared error rate and statistical confidence for determinations of both information present and information absent produced by classification CIT (Is a probe ERP more similar to a target or to an irrelevant ERP? versus comparison CIT (Does a probe produce a larger ERP than an irrelevant? using P300 plus the late negative component (LNP; together, P300-MERMER. Comparison CIT produced a significantly higher error rate (20% and lower statistical confidences -- mean 67%; information-absent mean was 28.9%, less than chance (50%. We compared analysis using P300 alone with the P300 + LNP. P300 alone produced the same 0% error rate but significantly lower statistical confidences. These findings add to the evidence that the brain fingerprinting methods as described here provide sufficient conditions to produce less than 1% error rate and greater than 95% median statistical confidence in a CIT on information obtained in the course of real life that is characteristic of individuals with specific training, expertise, or organizational

  16. Brain fingerprinting classification concealed information test detects US Navy military medical information with P300

    Science.gov (United States)

    Farwell, Lawrence A.; Richardson, Drew C.; Richardson, Graham M.; Furedy, John J.

    2014-01-01

    A classification concealed information test (CIT) used the “brain fingerprinting” method of applying P300 event-related potential (ERP) in detecting information that is (1) acquired in real life and (2) unique to US Navy experts in military medicine. Military medicine experts and non-experts were asked to push buttons in response to three types of text stimuli. Targets contain known information relevant to military medicine, are identified to subjects as relevant, and require pushing one button. Subjects are told to push another button to all other stimuli. Probes contain concealed information relevant to military medicine, and are not identified to subjects. Irrelevants contain equally plausible, but incorrect/irrelevant information. Error rate was 0%. Median and mean statistical confidences for individual determinations were 99.9% with no indeterminates (results lacking sufficiently high statistical confidence to be classified). We compared error rate and statistical confidence for determinations of both information present and information absent produced by classification CIT (Is a probe ERP more similar to a target or to an irrelevant ERP?) vs. comparison CIT (Does a probe produce a larger ERP than an irrelevant?) using P300 plus the late negative component (LNP; together, P300-MERMER). Comparison CIT produced a significantly higher error rate (20%) and lower statistical confidences: mean 67%; information-absent mean was 28.9%, less than chance (50%). We compared analysis using P300 alone with the P300 + LNP. P300 alone produced the same 0% error rate but significantly lower statistical confidences. These findings add to the evidence that the brain fingerprinting methods as described here provide sufficient conditions to produce less than 1% error rate and greater than 95% median statistical confidence in a CIT on information obtained in the course of real life that is characteristic of individuals with specific training, expertise, or organizational

  17. Testing the performances of different image representations for mass classification in digital mammograms

    OpenAIRE

    Angelini, Enrico; Campanini, Renato; Iampieri, Emiro; Lanconelli, Nico; Masotti, Matteo; Roffilli, Matteo

    2006-01-01

    The classification of tumoral masses and normal breast tissue is targeted. A mass detection algorithm which does not refer explicitly to shape, border, size, contrast or texture of mammographic suspicious regions is evaluated. In the present approach, classification features are embodied by the image representation used to encode suspicious regions. Classification is performed by means of a support vector machine (SVM) classifier. To investigate whether improvements can be achieved with respe...

  18. 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.

  19. 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

    2018-01-02

    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.

  20. 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.

  1. 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.

  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. Colorants based on renewable resources and food-grade colorants for application in thermoplastics

    NARCIS (Netherlands)

    Oever, van den M.J.A.; Boeriu, C.G.; Blaauw, R.; Haveren, van J.

    2004-01-01

    A series of colorants based on renewable resources and food-grade colorants have been evaluated for use in polypropylene (PP) and polyvinylchloride (PVC). It has been found that most of these colorants can be processed in PP at 200degreesC or even 260degreesC while maintaining good color intensity

  4. Two-Color-Based Nanoflares for Multiplexed MicroRNAs Imaging in Live Cells.

    Science.gov (United States)

    Li, Jing; Huang, Jin; Yang, Xiaohai; Yang, Yanjing; Quan, Ke; Xie, Nuli; Wu, Yanan; Ma, Changbei; Wang, Kemin

    2018-01-01

    MicroRNAs (miRNAs) have become an ideal biomarker candidate for early diagnosis of diseases. But various diseases involve changes in the expression of different miRNAs. Therefore, multiplexed assay of miRNAs in live cells can provide critical information for our better understanding of their roles in cells and further validating of their function in clinical diagnoses. Simultaneous detection of multiple biomarkers could effectively improve the accuracy of early cancer diagnosis. Here, we develop the two-color-based nanoflares for simultaneously detecting two distinct miRNA targets inside live cells. The nanoflares consist of gold nanoparticles (AuNPs) functionalized with a dense shell of recognition sequences hybridized to two short fluorophore-labeled DNA molecules, termed "flares". In this conformation, the close proximity of the fluorophore to the AuNPs surface leads to quenching of the fluorescence. However, when target miRNAs bind to the recognition sequence, the concomitant displacement of the flare can be detected as a corresponding increase in fluorescence. The results demonstrate that the two-color-based nanoflares can simultaneously detect miR-21 and miR-141 expression levels in various live cancer cells successfully. Compared to the traditional single-color-based nanoflares, the two-color-based nanoflares could offer more reliable and practical information for cancer detection, improving the accuracy of early disease diagnosis.

  5. Implementation and testing of WELD and automatic spectral rule-based classifications for Landsat ETM+ in South Africa

    CSIR Research Space (South Africa)

    Wessels, Konrad J

    2013-04-01

    Full Text Available International Symposium on Remote Sensing of Environment, Beijing, China, 22 - 26 April 2013 Implementation and testing of WELD and automatic spectral rule-based classifications for Landsat ETM+ in South Africa KJ Wessels1, BP Salmon1, F van den Bergh1...

  6. [CT-based classification aid for acetabular fractures: evaluation and clinical testing].

    Science.gov (United States)

    Schäffler, A; Fensky, F; Knöschke, D; Haas, N P; Becken, A G; Stöckle, U; König, B

    2013-11-01

    The basis for the classification of acetabular fractures depends on accurate radiological diagnostics. The use of conventional X-rays alone implicates a low intrapersonal reproducibility and interpersonal reliability. By applying computed tomography (CT) at an early stage in the emergency room, the typical diagonal X-rays of ala and obturator, on which the classification is based, are no longer recommended. The aim of this study was to develop a new reliable classification system based on standardized CT slices according to the system of Judet and Letournel without using diagonal X-rays. In this study 12 select cases with acetabular fractures were peer reviewed. In each case eight characteristic CT slices (five axial, two coronal and one sagittal) were selected as well as the conventional anteroposterior X-ray of the pelvis. All cases were peer reviewed by 14 members of the "AG Becken" (working group pelvis). The classification of the acetabular fractures was based on Judet and Letournel and the results were compared with the reference classification. The results were scaled according to differences to the original classification and the relevance to the approach as well as the medical qualification of the member. A total of 167 out of 168 possible classifications were conducted, 90 cases (54 %) were in accordance with the reference classification. In 69 cases (41 %) the outcome was different, which would have had no influence on the choice of the surgical approach. A wrong classification was present eight times (5 %). According to the medical qualification status the senior physicians were right in 54%, the residents in 53 %. Within the group of senior physicians 7.5 % of the classifications were completely wrong and 93 % of the participating members would have preferred to have more CT slices. The CT-based classification developed represents an adaption to the current standard of diagnostics of acetabular fractures and represents a step towards

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

    Science.gov (United States)

    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 Naïve 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.

  8. Suitability of the isolated chicken eye test for classification of extreme pH detergents and cleaning products.

    Science.gov (United States)

    Cazelle, Elodie; Eskes, Chantra; Hermann, Martina; Jones, Penny; McNamee, Pauline; Prinsen, Menk; Taylor, Hannah; Wijnands, Marcel V W

    2015-04-01

    A.I.S.E. investigated the suitability of the regulatory adopted ICE in vitro test method (OECD TG 438) with or without histopathology to identify detergent and cleaning formulations having extreme pH that require classification as EU CLP/UN GHS Category 1. To this aim, 18 extreme pH detergent and cleaning formulations were tested covering both alkaline and acidic extreme pHs. The ICE standard test method following OECD Test Guideline 438 showed good concordance with in vivo classification (83%) and good and balanced specificity and sensitivity values (83%) which are in line with the performances of currently adopted in vitro test guidelines, confirming its suitability to identify Category 1 extreme pH detergent and cleaning products. In contrast to previous findings obtained with non-extreme pH formulations, the use of histopathology did not improve the sensitivity of the assay whilst it strongly decreased its specificity for the extreme pH formulations. Furthermore, use of non-testing prediction rules for classification showed poor concordance values (33% for the extreme pH rule and 61% for the EU CLP additivity approach) with high rates of over-prediction (100% for the extreme pH rule and 50% for the additivity approach), indicating that these non-testing prediction rules are not suitable to predict Category 1 hazards of extreme pH detergent and cleaning formulations. Copyright © 2015 Elsevier Ltd. All rights reserved.

  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. 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 (pTest 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.

  11. Segment-Based Land Cover Mapping of a Suburban Area—Comparison of High-Resolution Remotely Sensed Datasets Using Classification Trees and Test Field Points

    Directory of Open Access Journals (Sweden)

    Kirsi Karila

    2011-08-01

    Full Text Available In order to better understand and exploit the rich information content of new remotely sensed datasets, there is a need for comparative land cover classification studies. In this study, the automatic classification of a suburban area was investigated by using (1 digital aerial image data; (2 digital aerial image data and laser scanner data; (3 a high-resolution optical QuickBird satellite image; (4 high-resolution airborne synthetic aperture radar (SAR data; and (5 SAR data and laser scanner data. A segment-based approach was applied. The classification rules for distinguishing buildings, trees, vegetated ground, and non-vegetated ground were created automatically by using permanent test field points in a training area and the classification tree method. The accuracy of the results was evaluated by using test field points in validation areas. The highest overall accuracies were obtained when laser scanner data were used to separate high and low objects: 97% in Test 2, and 82% in Test 5. The overall accuracies in the other tests were 74% (Test 1, 67% (Test 3, and 68% (Test 4. An important contributing factor for the lower accuracy in Tests 3 and 4 was the lower spatial resolution of the datasets. The classification tree method and test field points provided a feasible and automated means of comparing the classifications. The approach is well suited for rapid analyses of new datasets to predict their quality and potential for land cover classification.

  12. Tests of an Exemplar-Memory Model of Classification Learning in a High-Dimensional Natural-Science Category Domain.

    Science.gov (United States)

    Nosofsky, Robert M; Sanders, Craig A; McDaniel, Mark A

    2017-10-23

    Experiments were conducted in which novice participants learned to classify pictures of rocks into real-world, scientifically defined categories. The experiments manipulated the distribution of training instances during an initial study phase, and then tested for correct classification and generalization performance during a transfer phase. The similarity structure of the to-be-learned categories was also manipulated across the experiments. A low-parameter version of an exemplar-memory model, used in combination with a high-dimensional feature-space representation for the rock stimuli, provided good overall accounts of the categorization data. The successful accounts included (a) predicting how performance on individual item types within the categories varied with the distributions of training examples, (b) predicting the overall levels of classification accuracy across the different rock categories, and (c) predicting the patterns of between-category confusions that arose when classification errors were made. The work represents a promising initial step in scaling up the application of formal models of perceptual classification learning to complex natural-category domains. We discuss further steps for making use of the model and its associated feature-space representation to search for effective techniques of teaching categories in the science classroom. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  13. Medical Devices; Immunology and Microbiology Devices; Classification of the Aquaporin-4 Autoantibody Immunological Test System. Final order.

    Science.gov (United States)

    2017-10-30

    The Food and Drug Administration (FDA or we) is classifying the Aquaporin-4 autoantibody immunological 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 Aquaporin-4 autoantibody immunological 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.

  14. Medical Devices; Immunology and Microbiology Devices; Classification of the Zinc Transporter 8 Autoantibody Immunological Test System. Final order.

    Science.gov (United States)

    2017-10-24

    The Food and Drug Administration (FDA or we) is classifying the zinc transporter 8 autoantibody immunological 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 zinc transporter 8 autoantibody immunological 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.

  15. Medical Devices; Immunology and Microbiology Devices; Classification of the Newborn Screening Test for Severe Combined Immunodeficiency Disorder. Final order.

    Science.gov (United States)

    2017-10-30

    The Food and Drug Administration (FDA or we) is classifying the newborn screening test for severe combined immunodeficiency disorder (SCID) 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 newborn screening test for SCID'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.

  16. Reliability testing of the Larsen and Sharp classifications for rheumatoid arthritis of the elbow.

    Science.gov (United States)

    Jew, Nicholas B; Hollins, Anthony M; Mauck, Benjamin M; Smith, Richard A; Azar, Frederick M; Miller, Robert H; Throckmorton, Thomas W

    2017-01-01

    Two popular systems for classifying rheumatoid arthritis affecting the elbow are the Larsen and Sharp schemes. To our knowledge, no study has investigated the reliability of these 2 systems. We compared the intraobserver and interobserver agreement of the 2 systems to determine whether one is more reliable than the other. The radiographs of 45 patients diagnosed with rheumatoid arthritis affecting the elbow were evaluated. Anteroposterior and lateral radiographs were deidentified and distributed to 6 evaluators (4 fellowship-trained upper extremity surgeons and 2 orthopedic trainees). Each evaluator graded all 45 radiographs according to the Larsen and Sharp scoring methods on 2 occasions, at least 2 weeks apart. Overall intraobserver reliability was 0.93 (95% confidence interval [CI], 0.90-0.95) for the Larsen system and 0.92 (95% CI, 0.86-0.96) for the Sharp classification, both indicating substantial agreement. Overall interobserver reliability was 0.70 (95% CI, 0.60-0.80) for the Larsen classification and 0.68 (95% CI, 0.54-0.81) for the Sharp system, both indicating good agreement. There were no significant differences in the intraobserver or interobserver reliability of the systems overall and no significant differences in reliability between attending surgeons and trainees for either classification system. The Larsen and Sharp systems both show substantial intraobserver reliability and good interobserver agreement for the radiographic classification of rheumatoid arthritis affecting the elbow. Differences in training level did not result in substantial variances in reliability for either system. We conclude that both systems can be reliably used to evaluate rheumatoid arthritis of the elbow by observers of varying training levels. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

  17. 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

  18. 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.

  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. Rural landscape and cultural routes: a multicriteria spatial classification method tested on an Italian case study

    Directory of Open Access Journals (Sweden)

    Irene Diti

    2015-04-01

    Full Text Available Europe is characterised by a rich net of itineraries that during the Middle Ages were taken by pilgrims head toward the holy places of Christianity. In Italy the main pilgrimage route is the Via Francigena (the road that comes from France, which starts from Canterbury and arrives in Rome, running through Europe for about 1800 km. Municipalities and local associations are focused on purposes and actions aimed at the promotion of those routes, rich in history and spirituality. Also for the European Union the enhancement of those itineraries, nowadays used both by pilgrims and tourists, is crucial, as shown by the various projects aimed at the identification of tools for the development of sustainable cultural tourism. It is important to understand how landscape, that according to the European Landscape Convention reflects the sense of places and represents the image of their history, has evolved along those roads, and to analyse the relationships between the built and natural environments, since they maintain a remarkable symbolic connection between places and peoples over time and history. This study focuses on the Italian section of the Via Francigena that crosses the Emilia-Romagna region, in the province of Piacenza. A land classification method is proposed, with the aim to take into account different indicators: land zoning provided by regional laws, elements of relevant historical and natural value, urban elements, type of agriculture. The analyses are carried out on suitable buffers around the path, thus allowing to create landscape profiles. As nature is a key element for the spirituality character of these pilgrimage routes, the classification process takes into account both protected and other valuable natural elements, besides agricultural activities. The outcomes can be useful to define tools aimed to help pilgrims and tourists to understand the surrounding places along their walk, as well as to lend support to rural and urban planning

  1. 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.

  2. Reliability of a Shuttle Run Test for Children with Cerebral Palsy Who Are Classified at Gross Motor Function Classification System Level III

    Science.gov (United States)

    Verschuren, Olaf; Bosma, Liesbeth; Takken, Tim

    2011-01-01

    For children and adolescents with cerebral palsy (CP) classified as Gross Motor Function Classification System (GMFCS) level III there is no running-based field test available to assess their cardiorespiratory fitness. The current study investigated whether a shuttle run test can be reliably (test-retest) performed in a group of children with…

  3. 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

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

    Science.gov (United States)

    Dórea, Fernanda C; Muckle, C Anne; Kelton, David; McClure, J T; McEwen, Beverly J; McNab, W Bruce; Sanchez, Javier; Revie, Crawford W

    2013-01-01

    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. 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. 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. 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 automated methods to update model rules without user

  5. The National Shipbuilding Research Program. Acceptance Standards for Nondestructive Test Not Required by Classification (Phase 2)

    National Research Council Canada - National Science Library

    Stern, I. L; Wheatcroft, M; Ku, D. Y; Cantore, D

    1985-01-01

    Current ABS requirements relative to nondestructive test and acceptance standards for radiographic and ultrasonic inspection are mainly intended for intersecting full penetration welds within the midship...

  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. Biomechanical analysis of the different classifications of the Functional Movement Screen deep squat test.

    Science.gov (United States)

    Butler, Robert J; Plisky, Phillip J; Southers, Corey; Scoma, Christopher; Kiesel, Kyle B

    2010-11-01

    The purpose of this study is to examine the peak sagittal plane joint angles and joint moments of the lower extremity during the deep squat (DS) movement of the Functional Movement Screen (FMS) to assess differences between the classifications (1,2,3). Twenty-eight participants volunteered for the study and were screened to assess their FMS score on the DS task. All participants underwent a quantitative movement analysis performing the FMS DS movement at a self-selected speed. The participants in Group 3 exhibited greater dorsiflexion excursion compared to those in Group 1. Participants in Group 3 had greater peak knee flexion and knee flexion excursion than those in Group 2 who exhibited more than the participants in Group 1. Group 3 also exhibited a greater peak knee extension moment compared to Group 1. At the hip, Groups 3 and 2 exhibited greater peak hip flexion, hip flexion excursion and peak hip extension moment compared to Group 1. Thus, it appears that individuals who score differently on the deep squat as determined by the FMS exhibit differences in mechanics that may be beneficial in assessing strategies for interventions. Future research should assess how fundamental changes in mobility and stability independently affect DS performance.

  8. Data quality associated with handwritten laboratory test requests: classification and frequency of data-entry errors for outpatient serology tests.

    Science.gov (United States)

    Vecellio, Elia; Malley, Michael W; Toouli, George; Georgiou, Andrew; Westbrook, Johanna I

    2015-01-01

    Manual data-entry of handwritten laboratory test requests into electronic information systems has implications for data accuracy. This study sought to identify the types and number of errors occurring for handwritten serology test requests received from outpatient clinics. A 15-day audit at a serology laboratory in Sydney, Australia, compared the content of all transcribed serology outpatient test requests in the laboratory information system with the handwritten request form. One or more errors were detected in 67/627 (10.7%) audited requests (N=68 errors). Fifty-one of the errors (75.0%) were transcription errors: the wrong test was transcribed in 40/68 cases (58.8%)--ten of these occurred when the abbreviations 'HBsAb' and 'HBsAg' were confounded for one another--and transcribed requests were missing a test in 11/68 cases (16.2%). The remaining 17 non-transcription errors (25.0%) described request forms not signed by the ordering clinician, mislabelled specimens, and wrong tests due to computer algorithm errors. Manual data-entry of handwritten serology requests is an error-prone process. Electronic ordering has the potential to eliminate illegible handwriting and transcription errors, thus improving data accuracy in hospital information systems.

  9. 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

    A surveillance program in which all cattle herds in Denmark are classified into Salmonella infection categories has been in place since 2002. Dairy herds were considered test negative and thus most likely free of infection if Salmonella antibody measurements were consistently low in bulk tank milk...... samples collected every 3 mo. Herds were considered test positive and thus most likely infected if the 4-quarter moving average bulk tank milk antibody concentration was high or if there was a large increase in the most recent measurement compared with the average value from the previous 3 samples....... 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...

  10. 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.

  11. 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

  12. 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.

  13. Multidimensional Classification of Examinees Using the Mixture Random Weights Linear Logistic Test Model

    Science.gov (United States)

    Choi, In-Hee; Wilson, Mark

    2015-01-01

    An essential feature of the linear logistic test model (LLTM) is that item difficulties are explained using item design properties. By taking advantage of this explanatory aspect of the LLTM, in a mixture extension of the LLTM, the meaning of latent classes is specified by how item properties affect item difficulties within each class. To improve…

  14. 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 , including binary relevance, HOMER, MLkNN, predictive clustering trees (PCT), RAkEL and ensemble of classifier chains were tested on a dataset of 252 medical records of patients enrolled in an HIV treatment failure clinic in rural KwaZulu-Natal in South...

  15. Comparative Study on the Different Testing Techniques in Tree Classification for Detecting the Learning Motivation

    Science.gov (United States)

    Juliane, C.; Arman, A. A.; Sastramihardja, H. S.; Supriana, I.

    2017-03-01

    Having motivation to learn is a successful requirement in a learning process, and needs to be maintained properly. This study aims to measure learning motivation, especially in the process of electronic learning (e-learning). Here, data mining approach was chosen as a research method. For the testing process, the accuracy comparative study on the different testing techniques was conducted, involving Cross Validation and Percentage Split. The best accuracy was generated by J48 algorithm with a percentage split technique reaching at 92.19 %. This study provided an overview on how to detect the presence of learning motivation in the context of e-learning. It is expected to be good contribution for education, and to warn the teachers for whom they have to provide motivation.

  16. Wingate Anaerobic Test Peak Power and Anaerobic Capacity Classification for Men and Women Intercollegiate Athletes

    Science.gov (United States)

    2009-12-01

    Female firefighters Tae kwon do national team 7 endurance trained (ET) 6 sprinters (ST) 18-28 years old High school athletes Olympiclevel jodokas...results. men, 64 women). These data were preexisting data from the quarterly, semi-annual, or annual testing that these teams perform for training ...biathletes Trained cyclists Judo Soccer Rowers Nonathletes Olympic-level jodokas Competitive cyclists University hockey players (age: 20 years) Active

  17. Multistage Adaptive Testing for a Large-Scale Classification Test: Design, Heuristic Assembly, and Comparison with Other Testing Modes. ACT Research Report Series, 2012 (6)

    Science.gov (United States)

    Zheng, Yi; Nozawa, Yuki; Gao, Xiaohong; Chang, Hua-Hua

    2012-01-01

    Multistage adaptive tests (MSTs) have gained increasing popularity in recent years. MST is a balanced compromise between linear test forms (i.e., paper-and-pencil testing and computer-based testing) and traditional item-level computer-adaptive testing (CAT). It combines the advantages of both. On one hand, MST is adaptive (and therefore more…

  18. Using a multilocus phylogeny to test morphology-based classifications of Polystichum (Dryopteridaceae), one of the largest fern genera.

    Science.gov (United States)

    Le Péchon, Timothée; He, Hai; Zhang, Liang; Zhou, Xin-Mao; Gao, Xin-Fen; Zhang, Li-Bing

    2016-02-29

    Polystichum (Dryopteridaceae) is probably the third largest fern genus in the world and contains ca. 500 species. Species of Polystichum occur on all continents except Antarctica, but its highest diversity is found in East Asia, especially Southwest China and adjacent regions. Previous studies typically had sparse taxon sampling and used limited DNA sequence data. Consequently, the majority of morphological hypotheses/classifications have never been tested using molecular data. In this study, DNA sequences of five plastid loci of 177 accessions representing ca. 140 species of Polystichum and 13 species of the closely related genera were used to infer a phylogeny using maximum likelihood, Bayesian inference, and maximum parsimony. Our analyses show that (1) Polystichum is monophyletic, this being supported by not only molecular data but also morphological features and distribution information; (2) Polystichum is resolved into two strongly supported monophyletic clades, corresponding to the two subgenera, P. subg. Polystichum and P. subg. Haplopolystichum; (3) Accessions of P. subg. Polystichum are resolved into three major clades: clade K (P. sect. Xiphophyllum), clade L (P. sect. Polystichum), and the HYMASO superclade dominated by accessions of P. sect. Hypopeltis, P. sect. Macropolystichum, and P. sect. Sorolepidium, while those of P. subg. Haplopolystichum are resolved into eight major clades; and (4) The monophyly of the Afra clade (weakly supported), the Australasian clade (weakly supported), and the North American clade (strongly supported) is confirmed. Of the 23 sections of Polystichum recognized in a recent classification of the genus, four (P. sect. Hypopeltis, P. sect. Neopolystichum, P. sect. Sorolepidium, P. sect. Sphaenopolystichum) are resolved as non-monophyletic, 16 are recovered as monophyletic, and three are monospecific. Of the 16 monophyletic sections, two (P. sect. Adenolepia, P. sect. Cyrtogonellum) are weakly supported and 14 are strongly

  19. A Position Controller Model on Color-Based Object Tracking using Fuzzy Logic

    Science.gov (United States)

    Cahyo Wibowo, Budi; Much Ibnu Subroto, Imam; Arifin, Bustanul

    2017-04-01

    Robotics vision is applying technology on the camera to view the environmental conditions as well as the function of the human eye. Colour object tracking system is one application of robotics vision technology with the ability to follow the object being detected. Several methods have been used to generate a good response position control, but most are still using conventional control approach. Fuzzy logic which includes several step of which is to determine the value of crisp input must be fuzzification. The output of fuzzification is forwarded to the process of inference in which there are some fuzzy logic rules. The inference output forwarded to the process of defuzzification to be transformed into outputs (crisp output) to drive the servo motors on the X-axis and Y-axis. Fuzzy logic control is applied to the color-based object tracking system, the system is successful to follow a moving object with average speed of 7.35 cm/s in environments with 117 lux light intensity.

  20. Xenolog classification.

    Science.gov (United States)

    Darby, Charlotte A; Stolzer, Maureen; Ropp, Patrick J; Barker, Daniel; Durand, Dannie

    2017-03-01

    Orthology analysis is a fundamental tool in comparative genomics. Sophisticated methods have been developed to distinguish between orthologs and paralogs and to classify paralogs into subtypes depending on the duplication mechanism and timing, relative to speciation. However, no comparable framework exists for xenologs: gene pairs whose history, since their divergence, includes a horizontal transfer. Further, the diversity of gene pairs that meet this broad definition calls for classification of xenologs with similar properties into subtypes. We present a xenolog classification that uses phylogenetic reconciliation to assign each pair of genes to a class based on the event responsible for their divergence and the historical association between genes and species. Our classes distinguish between genes related through transfer alone and genes related through duplication and transfer. Further, they separate closely-related genes in distantly-related species from distantly-related genes in closely-related species. We present formal rules that assign gene pairs to specific xenolog classes, given a reconciled gene tree with an arbitrary number of duplications and transfers. These xenology classification rules have been implemented in software and tested on a collection of ∼13 000 prokaryotic gene families. In addition, we present a case study demonstrating the connection between xenolog classification and gene function prediction. The xenolog classification rules have been implemented in N otung 2.9, a freely available phylogenetic reconciliation software package. http://www.cs.cmu.edu/~durand/Notung . Gene trees are available at http://dx.doi.org/10.7488/ds/1503 . durand@cmu.edu. Supplementary data are available at Bioinformatics online.

  1. Clinical features of allergic rhinitis and skin prick test analysis based on the ARIA classification: a preliminary study in Malaysia.

    Science.gov (United States)

    Asha'ari, Zamzil Amin; Yusof, Suhaimi; Ismail, Rushdan; Che Hussin, Che Maraina

    2010-08-01

    Allergic rhinitis (AR) is a prevalent disease worldwide but is still underdiagnosed in many parts of Asia. We studied the clinical profiles of AR patients in our community based on the new ARIA classification and investigated the aetiological allergens using a skin prick test. In 2008, 142 newly diagnosed patients with AR were seen and underwent skin prick testing with 90 patients completing the study. Intermittent mild and moderate/severe AR were evident in 10% and 21.1% of the patients, while persistent mild and moderate/severe were seen in 20% and 48.9%, respectively. Rhinitis and asthma co-morbidity occurred in 28.8% with asthma incidence significantly higher in persistent AR (P = 0.002). There was no significant association between AR severity, city living and asthma co-morbidity. Nasal itchiness and sneezing were the main presenting complaints and were more common in intermittent AR (P Sleep disturbance was associated with moderate-severe AR (P <0.05). Polypoidal mucosa was associated with asthma co-morbidity (P <0.05). Monosensitivity reaction occurred in 12.2% of patients and was associated with fungi sensitivity (P <0.05). Majority of patients were oligosensitive (52.8%) and polysensitive (34.4%) and were significantly associated with moderate-severe persistent AR (P <0.01). The highest positive skin prick reaction and the largest average wheal diameter were for the house dust mites and cat allergen (P <0.05). Our results reflected the AR profiles in our country, which was comparable with typical profiles of the neighbouring country and other Mediterranean countries with a similar temperate climate.

  2. Cardiac resynchronisation therapy optimisation strategies: systematic classification, detailed analysis, minimum standards and a roadmap for development and testing.

    Science.gov (United States)

    Sohaib, S M Afzal; Whinnett, Zachary I; Ellenbogen, Kenneth A; Stellbrink, Christoph; Quinn, T Alexander; Bogaard, Margot D; Bordachar, Pierre; van Gelder, Berry M; van Geldorp, Irene E; Linde, Cecilia; Meine, Mathias; Prinzen, Frits W; Turcott, Robert G; Spotnitz, Henry M; Wichterle, Dan; Francis, Darrel P

    2013-12-10

    In this article an international group of CRT specialists presents a comprehensive classification system for present and future schemes for optimising CRT. This system is neutral to the measurement technology used, but focuses on little-discussed quantitative physiological requirements. We then present a rational roadmap for reliable cost-effective development and evaluation of schemes. A widely recommended approach for AV optimisation is to visually select the ideal pattern of transmitral Doppler flow. Alternatively, one could measure a variable (such as Doppler velocity time integral) and "pick the highest". More complex would be to make measurements across a range of settings and "fit a curve". In this report we provide clinicians with a critical approach to address any recommendations presented to them, as they may be many, indistinct and conflicting. We present a neutral scientific analysis of each scheme, and equip the reader with simple tools for critical evaluation. Optimisation protocols should deliver: (a) singularity, with only one region of optimality rather than several; (b) blinded test-retest reproducibility; (c) plausibility; (d) concordance between independent methods; and (e) transparency, with all steps open to scrutiny. This simple information is still not available for many optimisation schemes. Clinicians developing the habit of asking about each property in turn will find it easier to win now down the broad range of protocols currently promoted. Expectation of a sophisticated enquiry from the clinical community will encourage optimisation protocol-designers to focus on testing early (and cheaply) the basic properties that are vital for any chance of long term efficacy. © 2013.

  3. 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.

  4. 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......) and could thus be used for testing its training effectiveness. METHODS: The authors reviewed the five training cases from the ISCICDS and determined the sensory level (SL), motor level (ML) and American Spinal Injury Association Impairment Scale (AIS) for the training cases. The key points from the training...... cases were compared with our interpretation of the key aspects of the ISNCSCI. RESULTS: For determining SL, three principles of ML, sacral sparing, complete injury, classification of AIS A, B, C and D, determining motor incomplete status through sparing of motor function more than three levels below...

  5. Suitability of histopathology as an additional endpoint to the Isolated Chicken Eye Test for classification of non-extreme pH detergent and cleaning products.

    Science.gov (United States)

    Cazelle, Elodie; Eskes, Chantra; Hermann, Martina; Jones, Penny; McNamee, Pauline; Prinsen, Menk; Taylor, Hannah; Wijnands, Marcel V W

    2014-06-01

    A.I.S.E. investigated the suitability of histopathological evaluations as an additional endpoint to the regulatory adopted ICE in vitro test method (OECD TG 438) to identify non-extreme pH detergent and cleaning products that require classification as EU CLP/UN GHS Category 1 (serious eye damage). To this aim, a total of 30 non-extreme pH products covering the range of in vivo classifications for eye irritation, and representing various product categories were tested. Epithelium vacuolation (mid and lower layers) and erosion (at least moderate) were found to be the most relevant histopathological effects induced by products classified in vivo as Category 1. Histopathology criteria specifically developed for non-extreme pH detergent and cleaning products were shown to correctly identify materials classified as Category 1 based on in vivo persistent effects, and to significantly increase the overall sensitivity of the standard ICE prediction model for Category 1 identification (to 75%) whilst maintaining a good concordance (73%). In contrast, use of EU CLP additivity approach for classification of mixtures was considerably less predictive, with a concordance of only 27%, and 100% over-predictions of non-Category 1 products. As such, use of histopathology as an addition to the ICE test method was found suitable to identify EU CLP/UN GHS Category 1 non-extreme pH detergent and cleaning products and to allow a better discrimination from Category 2 products. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. 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.

    Science.gov (United States)

    Liu, N; Hu, Z W; Zhou, M W; Biering-Sørensen, F

    2014-12-01

    Descriptive comparison analysis. 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) and could thus be used for testing its training effectiveness. The authors reviewed the five training cases from the ISCICDS and determined the sensory level (SL), motor level (ML) and American Spinal Injury Association Impairment Scale (AIS) for the training cases. The key points from the training cases were compared with our interpretation of the key aspects of the ISNCSCI. For determining SL, three principles of ML, sacral sparing, complete injury, classification of AIS A, B, C and D, determining motor incomplete status through sparing of motor function more than three levels below the ML, there are corresponding case scenarios in ISCICDS. However, no case scenario shows classification of AIS E and the use of voluntary anal sphincter contraction for determination of motor incomplete status. Neurological level of injury could be deduced from the SL and ML. Finally, none of the cases include information about zone of partial preservation, sensory score or motor score. 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 that the missing fact should be included in an update of the training cases.

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

    DEFF Research Database (Denmark)

    Hansen, Michael Adsetts Edberg

    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...

  8. 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...

  9. The Effects of Gender and Employee Classification Level on Communication-Related Outcomes: A Test of Structuralist and Socialization Hypotheses.

    Science.gov (United States)

    Griffeth, Rodger W.; And Others

    1994-01-01

    Finds significant main effects of gender and employee classification level as predicted by structuralist theory: women reported lower job satisfaction and less desirable interaction than men; and hourly workers reported lower supervisory support, teamwork, communication satisfaction, and accuracy of information than salaried workers. (SR)

  10. 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.

  11. Prediction of ease of laryngoscopy and intubation-role of upper lip bite test, modified mallampati classification, and thyromental distance in various combination

    Directory of Open Access Journals (Sweden)

    Anjana S Wajekar

    2015-01-01

    Full Text Available Background: The incidence of difficult intubation in patients undergoing general anaesthesia is estimated to be approximately 1-18% whereas that of failure to intubate is 0.05-0.35%.1,2,3 Various methods have been used for prediction of difficult laryngoscopy. Although, upper lip bite has been shown to be a promising test in its introductory article, repeated validation in various populations is required for any test to be accepted as a routine test. We have compared upper lip bite test (ULBT, modified Mallampati test (MMC and thyromental distance (TMD individually and in various combinations to verify which of these predictor tests are significantly associated with difficult glottic exposure. Methods: After obtaining institutional ethics committee approval, 402 ASA I and II adult patients undergoing elective surgical procedures requiring endotracheal intubation were included. All the three test were performed in all the patients preoperatively and their glottic exposure was recorded by Cormack-Lehane classification during intubation. Sensitivity, specificity, positive predictive value and negative predictive value were used for comparison. Results: In our study, the incidence of difficult laryngoscopy was 11.4% and failure to intubate 0.49%. None of the three are a suitable predictive test when used alone. Combination of tests added incremental diagnostic value. Conclusion: We conclude that all three screening tests for difficult intubation have only poor to moderate discriminative power when used alone. Combinations of individual tests add some incremental diagnostic value.

  12. High Stringency Evaluation of the Automated BD Phoenix™ CPO Detect and RAPIDEC® CARBA NP Tests for Detection and Classification of Carbapenemases.

    Science.gov (United States)

    Thomson, Gina; Turner, David; Brasso, William; Kircher, Susan; Guillet, Thierry; Thomson, Kenneth

    2017-10-04

    There is an urgent need for rapid, accurate detection and classification of carbapenemases. The current study evaluated the automated BD Phoenix™ CPO Detect and the manual bioMérieux RAPIDEC® CARBA NP for meeting these needs. Both tests were challenged with 294 Enterobacteriaceae, Pseudomonas aeruginosa and Acinetobacter baumannii chosen to provide extreme diagnostic difficulty. Carbapenemases such as KPC, NMC-A, IMI, SME, NDM, SPM, IMP, VIM, OXA-23, 40, 48, 58, 72, 181, and 232 were produced by 243 isolates and 51 carbapenemase-negative isolates included porin mutants and producers of ESBLs, AmpCs, K1, and broad spectrum β-lactamases. Both tests exhibited high sensitivity of carbapenemase detection (> 97%). Due to the highly challenging carbapenemase-negative isolates, specificities were lower than typical of evaluations involving mostly routine clinical isolates. BD Phoenix™ CPO Detect was 68.6% specific and RAPIDEC® CARBA NP was 60.8% to 78.4% specific depending on how borderline results were interpreted. Only BD Phoenix™ CPO Detect classified carbapenemases. It correctly classified 85.0% of class A, 72.4% of class B, and 88.6% of class D carbapenemases. Importantly with respect to empirical therapy with new β-lactamase inhibitor combinations such as ceftazidime/avibactam, no class B carbapenemases were misclassified as class A carbapenemases. Both tests offer advantages. Used alone, without initial susceptibility tests, RAPIDEC® CARBA NP can provide positive results for some isolates after only 10 to 30 minutes incubation. BD Phoenix™ CPO Detect provides novel advantages such as automated carbapenemase detection, inclusion in susceptibility panels to eliminate delays and subjectivity in initiating carbapenemase tests, and classification of most carbapenemases. Copyright © 2017 Thomson et al.

  13. Pitch Based Sound Classification

    DEFF Research Database (Denmark)

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

    2006-01-01

    -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......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......, and that even though classification gets marginally better, not much is achieved by increasing the window size beyond 1 s....

  14. Limited-Information Goodness-of-Fit Testing of Diagnostic Classification Item Response Theory Models. CRESST Report 840

    Science.gov (United States)

    Hansen, Mark; Cai, Li; Monroe, Scott; Li, Zhen

    2014-01-01

    It is a well-known problem in testing the fit of models to multinomial data that the full underlying contingency table will inevitably be sparse for tests of reasonable length and for realistic sample sizes. Under such conditions, full-information test statistics such as Pearson's X[superscript 2]?? and the likelihood ratio statistic…

  15. 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.

  16. Diagnosing Teachers' Understandings of Rational Numbers: Building a Multidimensional Test within the Diagnostic Classification Framework

    Science.gov (United States)

    Bradshaw, Laine; Izsák, Andrew; Templin, Jonathan; Jacobson, Erik

    2014-01-01

    We report a multidimensional test that examines middle grades teachers' understanding of fraction arithmetic, especially multiplication and division. The test is based on four attributes identified through an analysis of the extensive mathematics education research literature on teachers' and students' reasoning in this content…

  17. [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

  18. Vital signs and estimated blood loss in patients with major trauma: testing the validity of the ATLS classification of hypovolaemic shock.

    Science.gov (United States)

    Guly, H R; Bouamra, O; Spiers, M; Dark, P; Coats, T; Lecky, F E

    2011-05-01

    The Advanced Trauma Life Support (ATLS) system classifies the severity of shock. The aim of this study is to test the validity of this classification. Admission physiology, injury and outcome variables from adult injured patients presenting to hospitals in England and Wales between 1989 and 2007 and stored on the Trauma Audit and Research Network (TARN) database, were studied. For each patient, the blood loss was estimated and patients were divided into four groups based on the estimated blood loss corresponding to the ATLS classes of shock. The median and interquartile ranges (IQR) of the heart rate (HR) systolic blood pressure (SBP), respiratory rate (RR) and Glasgow Coma Score (GCS) were calculated for each group. The median HR rose from 82 beats per minute (BPM) in estimated class 1 shock to 95 BPM in estimated class 4 shock. The median SBP fell from 135 mm Hg to 120 mm Hg. There was no significant change in RR or GCS. With increasing estimated blood loss there is a trend to increasing heart rate and a reduction in SBP but not to the degree suggested by the ATLS classification of shock. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  19. Testing the Hydrological Landscape Unit Classification System and Other Terrain Analysis Measures for Predicting Low-Flow Nitrate and Chloride in Watersheds

    Science.gov (United States)

    Poor, Cara J.; McDonnell, Jeffrey J.; Bolte, John

    2008-11-01

    Elevated nitrate concentrations in streamwater are a major environmental management problem. While land use exerts a large control on stream nitrate, hydrology often plays an equally important role. To date, predictions of low-flow nitrate in ungauged watersheds have been poor because of the difficulty in describing the uniqueness of watershed hydrology over large areas. Clearly, hydrologic response varies depending on the states and stocks of water, flow pathways, and residence times. How to capture the dominant hydrological controls that combine with land use to define streamwater nitrate concentration is a major research challenge. This paper tests the new Hydrologic Landscape Regions (HLRs) watershed classification scheme of Wolock and others (Environmental Management 34:S71-S88, 2004) to address the question: Can HLRs be used as a way to predict low-flow nitrate? We also test a number of other indexes including inverse-distance weighting of land use and the well-known topographic index (TI) to address the question: How do other terrain and land use measures compare to HLR in terms of their ability to predict low-flow nitrate concentration? We test this for 76 watersheds in western Oregon using the U.S. Environmental Protection Agency’s Environmental Monitoring and Assessment Program and Regional Environmental Monitoring and Assessment Program data. We found that HLRs did not significantly improve nitrate predictions beyond the standard TI and land-use metrics. Using TI and inverse-distance weighting did not improve nitrate predictions; the best models were the percentage land use—elevation models. We did, however, see an improvement of chloride predictions using HLRs, TI, and inverse-distance weighting; adding HLRs and TI significantly improved model predictions and the best models used inverse-distance weighting and elevation. One interesting result of this study is elevation consistently predicted nitrate better than TI or the hydrologic classification

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    Buzuloiu Vasile

    2008-01-01

    Full Text Available Abstract 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.

  2. Evaluation of Tests of Perceptual Speed/Accuracy and Spatial Ability for Use in Military Occupational Classification

    Science.gov (United States)

    2014-08-22

    measures of noncognitive characteristics, a technical knowledge test of information/ communications technology literacy, and en- hanced measurement of...predominantly in Project A, but also in their more recent evaluation of noncognitive measures that map better to job performance than to training...test also has demonstrated incremen- tal validity for Army occupations. A study of many cognitive and noncognitive measures from the Army’s Project A

  3. A Review on Mutagenicity Testing for Hazard Classification of Chemicals at Work: Focusing on in vivo Micronucleus Test for Allyl Chloride

    Directory of Open Access Journals (Sweden)

    Kyung-Taek Rim

    2015-09-01

    Full Text Available Chemical mutagenicity is a major hazard that is important to workers' health. Despite the use of large amounts of allyl chloride, the available mutagenicity data for this chemical remains controversial. To clarify the mutagenicity of allyl chloride and because a micronucleus (MN test had not yet been conducted, we screened for MN induction by using male ICR mice bone marrow cells. The test results indicated that this chemical is not mutagenic under the test conditions. In this paper, the regulatory test battery and several assay combinations used to determine the genotoxic potential of chemicals in the workplace have been described. Further application of these assays may prove useful in future development strategies of hazard evaluations of industrial chemicals. This study also should help to improve the testing of this chemical by commonly used mutagenicity testing methods and investigations on the underlying mechanisms and could be applicable for workers' health.

  4. Cost-effectiveness of IDH testing in diffuse gliomas according to the 2016 WHO classification of tumors of the central nervous system recommendations.

    Science.gov (United States)

    DeWitt, John C; Jordan, Justin T; Frosch, Matthew P; Samore, Wesley R; Iafrate, A John; Louis, David N; Lennerz, Jochen K

    2017-11-29

    Due to the decreasing prevalence of IDH1 mutations in older patients, the 2016 World Health Organization (WHO) classification of brain tumors proposed not to perform sequencing for isocitrate dehydrogenase (IDH) in glioblastoma patients ≥55 years old. We present a cost-effectiveness analysis to estimate the financial impact of these guidelines. From 2010 to 2015 we performed 1023 IDH tests in gliomas, amounting to ~$1.09 million in direct laboratory test costs. Samples were tested using R132H-specific immunohistochemistry, DNA sequencing validated for detection of noncanonical IDH1/2 mutations, or both methods. In cases tested by DNA sequencing, the fraction of non-R132H mutations was 5.4%, which included only 2 high-grade gliomas in patients ≥55 years (0.9%). When remodeling the optimal age cutoff in our patient population using 5-year age-binning, we found a 10-times higher pretest probability for the presence of a noncanonical IDH1 mutation in the setting of a negative IDH1-R132H immunohistochemistry result in patients IDH mutations in glioblastoma patients ≥55 years argues against universal IDH sequencing in this population. We predict that adoption of this age-based sequencing cutoff recommendation from the 2016 WHO guidelines will result in significant cost and time savings throughout the global health care system.

  5. A classification tree approach for improving the utilization of flow cytometry testing of blood specimens for B-cell non-Hodgkin lymphoproliferative disorders.

    Science.gov (United States)

    Healey, Ryan; Naugler, Christopher; de Koning, Lawrence; Patel, Jay L

    2015-01-01

    We sought to improve the diagnostic efficiency of flow cytometry investigation on blood by developing data-driven ordering guidelines. Our goal was to improve flow cytometry utilization by decreasing negative testing, therefore reducing healthcare costs. We investigated several laboratory tests performed alongside flow cytometry to identify biomarkers useful in excluding non-leukemic bloods. Test results and patient demographic features were subjected to receiver-operator characteristic (ROC) curve, logistic regression and classification tree analyses to find significant predictors and develop decision rules. Our data show that, in the absence of a compelling clinical indication, flow cytometry testing is largely non-informative on bloods from patients less than 50 years of age having an absolute lymphocyte count (ALC) below 5.0 × 10(9)/L. For patients over age 50 having an ALC below this value, a ferritin value above 450 μg/L is counter-indicative of B-cell clonality. Using these guidelines, 26% of cases were correctly predicted as negative with greater than 97% accuracy.

  6. Leave-one-out-training and leave-one-out-testing hidden markov models for a handwritten numeral recognizer: the implications of a single classifier and multiple classifications.

    Science.gov (United States)

    Ko, Albert Hung-Ren; Cavalin, Paulo Rodrigo; Sabourin, Robert; de Souza Britto, Alceu

    2009-12-01

    Hidden Markov Models (HMMs) have been shown to be useful in handwritten pattern recognition. However, owing to their fundamental structure, they have little resistance to unexpected noise among observation sequences. In other words, unexpected noise in a sequence might "break" the normal transmission of states for this sequence, making it unrecognizable to trained models. To resolve this problem, we propose a leave-one-out-training strategy, which will make the models more robust. We also propose a leave-one-out-testing method, which will compensate for some of the negative effects of this noise. The latter is actually an example of a system with a single classifier and multiple classifications. Compared with the 98.00 percent accuracy of the benchmark HMMs, the new system achieves a 98.88 percent accuracy rate on handwritten digits.

  7. 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.

  8. ISSVA classification.

    Science.gov (United States)

    Dasgupta, Roshni; Fishman, Steven J

    2014-08-01

    Mulliken and Glowacki, in 1982 created a classification system of vascular anomalies which divided vascular anomalies into tumors and malformations which provided the framework for great advances in the management of these patients. This classification system was recently expanded at the 2014 ISSVA workshop in Melbourne. This revision again provides much greater detail including newly named anomalies and identified genes to account for recent advances in knowledge and clinical associations. Copyright © 2014. Published by Elsevier Inc.

  9. 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.

  10. 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.

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

    Science.gov (United States)

    2013-12-01

    research involves the Raven Advanced Progressive Matrices (RAPM) ( Raven , Raven , & Court, 1998), an instrument thought to be highly reflective of gF...interference-control ability brain activity” (I-CA) as part of both WM and gF (Burgess et al., 2011). WM, measured by several types of span tasks and...gF, measured by the RAPM and the Cattell Culture Fair Test (Cattell, 1973) produced I-CA brain activity that was depicted in a path model with both

  12. 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.

  13. 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...

  14. RBF-Neural Network Applied to the Quality Classification of Tempered 100Cr6 Steel Cams by the Multi-Frequency Nondestructive Eddy Current Testing

    Directory of Open Access Journals (Sweden)

    Víctor Martínez-Martínez

    2017-09-01

    Full Text Available This article proposes a Radial Basis Function Artificial Neural Network (RBF-ANN to classify tempered steel cams as correctly or incorrectly treated pieces by using multi-frequency nondestructive eddy current testing. Impedances at five frequencies between 10 kHz and 300 kHz were employed to perform the binary sorting. The ANalysis Of VAriance (ANOVA test was employed to check the significance of the differences between the impedance samples for the two classification groups. Afterwards, eleven classifiers were implemented and compared with one RBF-ANN classifier: ten linear discriminant analysis classifiers and one Euclidean distance classifier. When employing the proposed RBF-ANN, the best performance was achieved with a precision of 95% and an area under the Receiver Operating Characteristic (ROC curve of 0.98. The obtained results suggest RBF-ANN classifiers processing multi-frequency impedance data could be employed to classify tempered steel DIN 100Cr6 cams with a better performance than other classical classifiers.

  15. 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...

  16. Analysis of SATIR test for the qualification of high heat flux components: defect detection and classification by signal-to-noise ratio maximization

    Science.gov (United States)

    Cismondi, F.; Xerri, B.; Jauffret, C.; Schlosser, J.; Vignal, N.; Durocher, A.

    2007-03-01

    Plasma facing components (PFC) in Tore Supra and W7X adopt the flat tile concept using carbon fibre composite (CFC) material for the plasma facing material. As the cooling structure is made of a copper alloy material (CuCrZr), the bonding technique between CFC tiles and CuCrZr is critical. Currently, a soft metallic compliant layer is interposed between the two; in such a way the significant thermal expansion mismatch between carbon and copper can be accomodated. The development of a reliable non-destructive inspection technique (NDT) for the bond, to be performed during the manufacturing process, is obviously of great importance. The SATIR (infrared thermography) test bed operating at Commisariat à l'Energie Atomique (CEA) Cadarache performs this function using transient infrared thermography: the thermal excitation is realized in the cooling channel and the presence of a faulty tile is detected in the form of a delayed thermal response. With this technique, the evolution of the surface temperature of an inspected element was compared to that of a defined free-defect element, using the so-called DTref criterion (maximum of the transient temperature difference). The defect detection capability of the SATIR test bed can be improved using signal processing methods. A first treatment based on spatial image autocorrelation allows a better localization of the bond defect. Moreover, the problem of detection and classification of random signals (like the thin defect signature) can be solved maximizing the signal-to-noise ratio (SNR). Two filters maximizing this ratio were optimized: the stochastic matched filter (SMF) aims at defect detection, while the constrained SMF aims at defect classification. These methods assume that the second-order properties of the process at play are known, through covariance matrices. All these methods process the SATIR signal utilizing any free-defect element as reference signal. The tile temperature signal is either processed by itself or

  17. Analysis of SATIR test for the qualification of high heat flux components: defect detection and classification by signal-to-noise ratio maximization

    Energy Technology Data Exchange (ETDEWEB)

    Cismondi, F [Association Euratom-CEA, CEA/DSM/DRFC, CEA Cadarache, F-13108 Saint Paul Lez Durance (France); Xerri, B [Universite de Toulon et du Var, BP 132, 83957, La Garde (France); Jauffret, C [Universite de Toulon et du Var, BP 132, 83957, La Garde (France); Schlosser, J [Association Euratom-CEA, CEA/DSM/DRFC, CEA Cadarache, F-13108 Saint Paul Lez Durance (France); Vignal, N [Association Euratom-CEA, CEA/DSM/DRFC, CEA Cadarache, F-13108 Saint Paul Lez Durance (France); Durocher, A [Association Euratom-CEA, CEA/DSM/DRFC, CEA Cadarache, F-13108 Saint Paul Lez Durance (France)

    2007-03-15

    Plasma facing components (PFC) in Tore Supra and W7X adopt the flat tile concept using carbon fibre composite (CFC) material for the plasma facing material. As the cooling structure is made of a copper alloy material (CuCrZr), the bonding technique between CFC tiles and CuCrZr is critical. Currently, a soft metallic compliant layer is interposed between the two; in such a way the significant thermal expansion mismatch between carbon and copper can be accomodated. The development of a reliable non-destructive inspection technique (NDT) for the bond, to be performed during the manufacturing process, is obviously of great importance. The SATIR (infrared thermography) test bed operating at Commisariat a l'Energie Atomique (CEA) Cadarache performs this function using transient infrared thermography: the thermal excitation is realized in the cooling channel and the presence of a faulty tile is detected in the form of a delayed thermal response. With this technique, the evolution of the surface temperature of an inspected element was compared to that of a defined free-defect element, using the so-called DTref criterion (maximum of the transient temperature difference). The defect detection capability of the SATIR test bed can be improved using signal processing methods. A first treatment based on spatial image autocorrelation allows a better localization of the bond defect. Moreover, the problem of detection and classification of random signals (like the thin defect signature) can be solved maximizing the signal-to-noise ratio (SNR). Two filters maximizing this ratio were optimized: the stochastic matched filter (SMF) aims at defect detection, while the constrained SMF aims at defect classification. These methods assume that the second-order properties of the process at play are known, through covariance matrices. All these methods process the SATIR signal utilizing any free-defect element as reference signal. The tile temperature signal is either processed by itself

  18. 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)...

  19. 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...... HE, protein contact dermatitis/contact urticaria, hyperkeratotic endogenous eczema and vesicular endogenous eczema, respectively. An additional diagnosis was given if symptoms indicated that factors additional to the main diagnosis were of importance for the disease. RESULTS: Four hundred and twenty......%) could not be classified. 38% had one additional diagnosis and 26% had two or more additional diagnoses. Eczema on feet was found in 30% of the patients, statistically significantly more frequently associated with hyperkeratotic and vesicular endogenous eczema. CONCLUSION: We find that the classification...

  20. 7 CFR 28.911 - Review classification.

    Science.gov (United States)

    2010-01-01

    ... by the producer. After classification, the samples shall become the property of the Government unless... 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...

  1. Circulation pattern classification for climate change studies

    Science.gov (United States)

    Stehlik, J.; Bardossy, A.

    2003-04-01

    Several circulation pattern classifications developed for different European regions were compared regarding their mutual dependence. Circulation pattern (CP) classifications, both subjective and objective, for the British Isles, Germany and Greece were taken into account. Statistical tests were applied in order to investigate the relationships between each pair of CP classifications. It was found that each pair of classifications can not be considered to be independent. Time dependence of the relationship between CP classifications shows anomaleous behavior only when one of the classifications is subjective. This can be due to a gradual change in the methodology. Thus, one should use these classifications for climate evolution studies with care. Results showing the inter-dependence of different CP classifications were motivation for developing one classification which would be valid in every European region. For this purpose an objective and automated classification was applied. By means of daily 700 hPa data, 13 CPs were defined which explain the variability of local precipitation in 27 stations spread over the whole of Europe. The validation of this classification proved that there is almost no information lost when comparing this classification with local classifications. Based on this classification method the air pressure outputs from Global Circulation Models will be classified. Subsequently the classified circulation patterns will be used for climate change studies. For this purpose statistical downscaling of precipitation will be applied.

  2. Field testing the Unified Classification System for peri-prosthetic fractures of the pelvis and femur around a total hip replacement : an international collaboration.

    Science.gov (United States)

    Vioreanu, M H; Parry, M C; Haddad, F S; Duncan, C P

    2014-11-01

    The Unified Classification System (UCS) emphasises the key principles in the assessment and management of peri-prosthetic fractures complicating partial or total joint replacement. We tested the inter- and intra-observer agreement for the UCS as applied to the pelvis and femur using 20 examples of peri-prosthetic fracture in 17 patients. Each subtype of the UCS was represented by at least one case. Specialist orthopaedic surgeons (experts) and orthopaedic residents (pre-experts) assessed reliability on two separate occasions. For the pelvis, the UCS showed inter-observer agreement of 0.837 (95% confidence intervals (CI) 0.798 to 0.876) for the experts and 0.728 (95% CI 0.689 to 0.767) for the pre-experts. The intra-observer agreement for the experts was 0.861 (95% CI 0.760 to 0.963) and 0.803 (95% 0.688 to 0.918) for the pre-experts. For the femur, the UCS showed an inter-observer kappa value of 0.805 (95% CI 0.765 to 0.845) for the experts and a value of 0.732 (95% CI 0.690 to 0.773) for the pre-experts. The intra-observer agreement was 0.920 (95% CI 0.867 to 0.973) for the experts, and 0.772 (95% CI 0.652 to 0.892) for the pre-experts. This corresponds to a substantial and 'almost perfect' inter- and intra-observer agreement for the UCS for peri-prosthetic fractures of the pelvis and femur. We hope that unifying the terminology of these injuries will assist in their assessment, treatment and outcome. ©2014 The British Editorial Society of Bone & Joint Surgery.

  3. 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.

  4. 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.

  5. Classification in Australia.

    Science.gov (United States)

    McKinlay, John

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

  6. The Connections between Students Self-Motivation, Their Classification (Typical Learners, Academic Intervention Services Learners, and Gifted), and Gender in a Standardized Social Studies Test

    Science.gov (United States)

    Dupree, Jeffrey J.; Morote, Elsa Sofia

    2011-01-01

    This study examines differences, if any, between gender, level of motivation, and students' classification (typical learners, academic intervention services learners, and gifted) in scores upon DBQ (document-based questions) among the sixth grade students. 64 grade students were given a DBQ as part of their final examination. Students' scores were…

  7. Remote Sensing Information Classification

    Science.gov (United States)

    Rickman, Douglas L.

    2008-01-01

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

  8. Classification in context

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...

  9. Short Time Exposure (STE) test in conjunction with Bovine Corneal Opacity and Permeability (BCOP) assay including histopathology to evaluate correspondence with the Globally Harmonized System (GHS) eye irritation classification of textile dyes.

    Science.gov (United States)

    Oliveira, Gisele Augusto Rodrigues; Ducas, Rafael do Nascimento; Teixeira, Gabriel Campos; Batista, Aline Carvalho; Oliveira, Danielle Palma; Valadares, Marize Campos

    2015-09-01

    Eye irritation evaluation is mandatory for predicting health risks in consumers exposed to textile dyes. The two dyes, Reactive Orange 16 (RO16) and Reactive Green 19 (RG19) are classified as Category 2A (irritating to eyes) based on the UN Globally Harmonized System for classification (UN GHS), according to the Draize test. On the other hand, animal welfare considerations and the enforcement of a new regulation in the EU are drawing much attention in reducing or replacing animal experiments with alternative methods. This study evaluated the eye irritation of the two dyes RO16 and RG19 by combining the Short Time Exposure (STE) and the Bovine Corneal Opacity and Permeability (BCOP) assays and then comparing them with in vivo data from the GHS classification. The STE test (first level screening) categorized both dyes as GHS Category 1 (severe irritant). In the BCOP, dye RG19 was also classified as GHS Category 1 while dye RO16 was classified as GHS no prediction can be made. Both dyes caused damage to the corneal tissue as confirmed by histopathological analysis. Our findings demonstrated that the STE test did not contribute to arriving at a better conclusion about the eye irritation potential of the dyes when used in conjunction with the BCOP test. Adding the histopathology to the BCOP test could be an appropriate tool for a more meaningful prediction of the eye irritation potential of dyes. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. 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.

  11. 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...

  12. Reliability of regression-based normative data for the oral symbol digit modalities test: an evaluation of demographic influences, construct validity, and impairment classification rates in multiple sclerosis samples.

    Science.gov (United States)

    Berrigan, Lindsay I; Fisk, John D; Walker, Lisa A S; Wojtowicz, Magdalena; Rees, Laura M; Freedman, Mark S; Marrie, Ruth Ann

    2014-01-01

    The oral Symbol Digit Modalities Test (SDMT) has been recommended to assess cognition for multiple sclerosis (MS) patients. However, the lack of adequate normative data has limited its clinical utility. Recently published regression-based norms may resolve this limitation but, because these norms were derived from a relatively small sample, their stability is unclear. We aimed to evaluate the stability of regression-based SDMT norms by comparing existing norms to a cross-validation dataset. First, regression-based normative data were created from a similarly-sized, independent, control sample (n = 94). Next the original and cross-validation norms were compared for equivalency, management of demographic influences, construct validity, and impairment classification rates in a mildly affected MS sample (n = 70). Lastly, similar comparisons were made for a large, representative MS clinic sample (n = 354). We found construct validity and management of demographic influences were equivalent for the two sets of regression-based norms but lower T-scores were obtained using the original dataset, resulting in discrepancies in impairment classification. In conclusion, regression-based norms for the oral SDMT attenuate demographic influences and possess adequate construct validity. However, norms generated using small samples may yield unreliable classification of cognitive impairment. Larger, representative databases will be necessary to improve the clinical utility of regression-based norms.

  13. Field testing the Unified Classification System for periprosthetic fractures of the femur, tibia and patella in association with knee replacement: an international collaboration.

    Science.gov (United States)

    Van der Merwe, J M; Haddad, F S; Duncan, C P

    2014-12-01

    The Unified Classification System (UCS) was introduced because of a growing need to have a standardised universal classification system of periprosthetic fractures. It combines and simplifies many existing classification systems, and can be applied to any fracture around any partial or total joint replacement occurring during or after operation. Our goal was to assess the inter- and intra-observer reliability of the UCS in association with knee replacement when classifying fractures affecting one or more of the femur, tibia or patella. We used an international panel of ten orthopaedic surgeons with subspecialty fellowship training and expertise in adult hip and knee reconstruction ('experts') and ten residents of orthopaedic surgery in the last two years of training ('pre-experts'). They each received 15 radiographs for evaluation. After six weeks they evaluated the same radiographs again but in a different order. The reliability was assessed using the Kappa and weighted Kappa values. The Kappa values for inter-observer reliability for the experts and the pre-experts were 0.741 (95% confidence interval (CI) 0.707 to 0.774) and 0.765 (95% CI 0.733 to 0.797), respectively. The weighted Kappa values for intra-observer reliability for the experts and pre-experts were 0.898 (95% CI 0.846 to 0.950) and 0.878 (95% CI 0.815 to 0.942) respectively. The UCS has substantial inter-observer reliability and 'near perfect' intra-observer reliability when used for periprosthetic fractures in association with knee replacement in the hands of experienced and inexperienced users. ©2014 The British Editorial Society of Bone & Joint Surgery.

  14. 7 CFR 58.132 - Basis for classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 3 2010-01-01 2010-01-01 false Basis for classification. 58.132 Section 58.132... Milk § 58.132 Basis for classification. The quality classification of raw milk for manufacturing... residue test, and quality control tests for sediment content, bacterial estimate and somatic cell count...

  15. SAW Classification Algorithm for Chinese Text Classification

    Directory of Open Access Journals (Sweden)

    Xiaoli Guo

    2015-02-01

    Full Text Available 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 have an implied correlation between text information mining and text categorization for high-correlation matching. Experiments show that SAW classification algorithm on the premise of ensuring precision in classification, significantly improve the classification precision and recall, obviously improving the performance of information retrieval, and providing an effective means of data use in the era of big data information extraction.

  16. 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...

  17. [Classification and diagnostics of unstable shoulders].

    Science.gov (United States)

    Greiner, S; Herrmann, S; Gerhardt, C; Scheibel, M

    2009-01-01

    Shoulder instability includes a vast spectrum of different manifestations ranging from painful hyperlaxity to chronic locked shoulder dislocations. A correct diagnosis and classification is essential to establish an adequate treatment strategy. The correct use of different clinical tests and signs in combination with the corresponding imaging diagnostics allows an explicit classification and therefore the correct choice of treatment regimes in the majority of cases.

  18. Probabilistic drought classification using gamma mixture models

    Science.gov (United States)

    Mallya, Ganeshchandra; Tripathi, Shivam; Govindaraju, Rao S.

    2015-07-01

    Drought severity is commonly reported using drought classes obtained by assigning pre-defined thresholds on drought indices. Current drought classification methods ignore modeling uncertainties and provide discrete drought classification. However, the users of drought classification are often interested in knowing inherent uncertainties in classification so that they can make informed decisions. Recent studies have used hidden Markov models (HMM) for quantifying uncertainties in drought classification. The HMM method conceptualizes drought classes as distinct hydrological states that are not observed (hidden) but affect observed hydrological variables. The number of drought classes or hidden states in the model is pre-specified, which can sometimes result in model over-specification problem. This study proposes an alternate method for probabilistic drought classification where the number of states in the model is determined by the data. The proposed method adapts Standard Precipitation Index (SPI) methodology of drought classification by employing gamma mixture model (Gamma-MM) in a Bayesian framework. The method alleviates the problem of choosing a suitable distribution for fitting data in SPI analysis, quantifies modeling uncertainties, and propagates them for probabilistic drought classification. The method is tested on rainfall data over India. Comparison of the results with standard SPI show important differences particularly when SPI assumptions on data distribution are violated. Further, the new method is simpler and more parsimonious than HMM based drought classification method and can be a viable alternative for probabilistic drought classification.

  19. 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...

  20. Selecting Color-based Tracers and Classifying Sediment Sources in the Assessment of Sediment Dynamics Using Sediment Source Fingerprinting.

    Science.gov (United States)

    Barthod, Louise R M; Liu, Kui; Lobb, David A; Owens, Philip N; Martínez-Carreras, Núria; Koiter, Alexander J; Petticrew, Ellen L; McCullough, Gregory K; Liu, Cenwei; Gaspar, Leticia

    2015-09-01

    The use of sediment color as a fingerprint property to determine sediment sources is an emerging technique that can provide a rapid and inexpensive means of investigating sediment sources. The present study aims to test the feasibility of color fingerprint properties to apportion sediment sources within the South Tobacco Creek Watershed (74 km) in Manitoba, Canada. Suspended sediment from 2009 to 2011 at six monitoring stations and potential source samples along the main stem of the creek were collected. Reflectance spectra of sediments and source materials were quantified using a diffuse reflectance spectrometry, and 16 color coefficients were derived from several color space models. Canonical discriminant analysis was used to reclassify and downsize sediment source groups. After the linear additive test and stepwise discriminant function analysis, four color coefficients were chosen to fit the Stable Isotope Analysis in R model. Consistent with the conventional fingerprinting approach, the color fingerprint results demonstrated a switch in the dominant sediment source between the headwaters and the outlet of the watershed, with the main sources being topsoil in the upper reaches, whereas outcrop shale and stream bank materials dominated in the lower reaches. The color fingerprinting approach can be integrated with conventional fingerprints (e.g., geochemical and fallout radionuclide properties) to improve source discrimination, which is a key component for source ascription modeling. We concluded that the use of color fingerprints is a promising, cost-effective technique for sediment source fingerprinting. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  1. A classification of ecological boundaries

    Science.gov (United States)

    Strayer, D.L.; Power, M.E.; Fagan, W.F.; Pickett, S.T.A.; Belnap, J.

    2003-01-01

    Ecologists use the term boundary to refer to a wide range of real and conceptual structures. Because imprecise terminology may impede the search for general patterns and theories about ecological boundaries, we present a classification of the attributes of ecological boundaries to aid in communication and theory development. Ecological boundaries may differ in their origin and maintenance, their spatial structure, their function, and their temporal dynamics. A classification system based on these attributes should help ecologists determine whether boundaries are truly comparable. This system can be applied when comparing empirical studies, comparing theories, and testing theoretical predictions against empirical results.

  2. Unidimensional Approximations for a Computerized Classification Test When the Item Pool and Latent Space Are Multidimensional. ACT Research Report Series 97-5.

    Science.gov (United States)

    Spray, Judith A.; Abdel-fattah, Abdel-fattah A.; Huang, Chi-Yu; Lau, C. Allen

    The primary concern or focus of a certification or licensure test is to obtain valid criterion-referenced information regarding a candidate's competence to practice. When the test is administered by computer, a valid pass/fail decision can be made with fewer items than an equivalent paper/pencil test by targeting items at the passing score and…

  3. Classification of cultivated plants.

    NARCIS (Netherlands)

    Brandenburg, W.A.

    1986-01-01

    Agricultural practice demands principles for classification, starting from the basal entity in cultivated plants: the cultivar. In establishing biosystematic relationships between wild, weedy and cultivated plants, the species concept needs re-examination. Combining of botanic classification, based

  4. Clinical evaluation of hand-arm-vibration syndrome in shipyard workers: sensitivity and specificity as compared to Stockholm classification and vibrometry testing.

    Science.gov (United States)

    Kent, D C; Allen, R; Bureau, P; Cherniack, M; Hans, J; Robinson, M

    1998-02-01

    The hand-arm-vibration syndrome (HAVS) is a complex entity composed of circulatory, sensory, and motor disturbances, as well as associated musculoskeletal components. This study was performed to find a diagnostic testing modality with sufficient sensitivity, specificity, and predictive value to be utilized as a screening test for this disorder in a working population. A full range of testing modalities was utilized in the shipyard medical department. In addition, a clinical diagnosis of vascular and sensorineural disease was established in the workers by a combination of plethysmography, vibrometry, two point discrimination, and monofilament testing in an independent occupational medicine clinic. No one test modality met the requirements for such a definitive diagnostic test. Rather, a range of modalities was required to reach any acceptable level of predictive value, with sufficient degrees of specificity and sensitivity.

  5. [Another seizure classification--Semiological Seizure Classification].

    Science.gov (United States)

    Lin, Ji-Ho; Kwan, Shang-Yeong; Wu, Dean; Su, Min-Shin; Yiu, Chun-Hing

    2004-09-01

    The International League Against Epilepsy (ILAE) introduced in 1981 a seizure classification based on clinical semiology, interictal EEG findings, and ictal EEG patterns. Such classification depends heavily on detailed electroclinical correlation. After 20 years' progress in epileptology, many clinicians have found it difficult to make a "definite" seizure diagnosis clinically without a series of electrophysiological examinations, particularly in the infants, and further advancement in epileptology has findings have made the previous classification inefficient. Lüders and colleagues have proposed a classification, Semiological Seizure Classification (SSC), based exclusively on ictal semiology, which was published in the official journal of ILAE-EPILEPSIA in 1998. The EEG, neuroimaging and other laboratory results should be analyzed separately and then integrated to define the epileptic syndromes. The seizure diagnosis is thus made through a "what-you-see-is-what-you-get" way. It has also provoked an extensive discussion about the necessity of this new classification. In this review, we present the original guideline, which has been used at The Cleveland Clinic Foundation for years, to introduce another method of epileptic seizure classification.

  6. Drug-related problem classification systems.

    Science.gov (United States)

    van Mil, J W Foppe; Westerlund, L O Tommy; Hersberger, Kurt E; Schaefer, Marion A

    2004-05-01

    To provide an overview of and critically appraise classifications of drug-related problems (DRPs) for use during the pharmaceutical care process and research in pharmacy. A literature search was conducted using MEDLINE and Yahoo (January 2003) and manually. The search terms included DRP, drug-related problem, drug-therapy problem, and medicine-related problem. English- and German-language articles on pharmaceutical care and DRPs were reviewed. Most classifications of DRPs were identified through searching publications on pharmaceutical care and DRPs. Fourteen classifications with different focuses were found. Some classifications were hierarchical, categorized into main groups and subgroups. Various terminologies and definitions for DRPs were revealed, as well as guidelines for an optimal DRP classification. Classifications were assessed according to a clear definition, published validation method, and results reflecting process and outcomes, usability in pharmaceutical care practice, and a hierarchical structure with main groups and subgroups. Finding DRP classifications by computerized search of the biomedical literature with the help of PubMed proved to be difficult. No classification could be found that met all of our criteria for an optimal system. Few classifications have been validated. Three have been tested as to their usability in practice and internal consistency. The Pharmaceutical Care Network Europe system Version 4 comes closest to the defined requirements.

  7. 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....

  8. 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

  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. Classification of remotely sensed images

    CSIR Research Space (South Africa)

    Dudeni, N

    2008-10-01

    Full Text Available images N. Dudeni, P. Debba Introduction to Remote Sensing Introduction to Image Classification Objective of the study Classification algorithms by group Unsupervised algorithms Supervised classification algorithms Spatial... of remotely sensed images N. Dudeni, P. Debba Introduction to Remote Sensing Introduction to Image Classification Objective of the study Classification algorithms by group Unsupervised algorithms Supervised classification algorithms...

  11. 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.

  12. Classification of anemia for gastroenterologists.

    Science.gov (United States)

    Moreno Chulilla, Jose Antonio; Romero Colás, Maria Soledad; Gutiérrez Martín, Martín

    2009-10-07

    Most anemia is related to the digestive system by dietary deficiency, malabsorption, or chronic bleeding. We review the World Health Organization definition of anemia, its morphological classification (microcytic, macrocytic and normocytic) and pathogenic classification (regenerative and hypo regenerative), and integration of these classifications. Interpretation of laboratory tests is included, from the simplest (blood count, routine biochemistry) to the more specific (iron metabolism, vitamin B12, folic acid, reticulocytes, erythropoietin, bone marrow examination and Schilling test). In the text and various algorithms, we propose a hierarchical and logical way to reach a diagnosis as quickly as possible, by properly managing the medical interview, physical examination, appropriate laboratory tests, bone marrow examination, and other complementary tests. The prevalence is emphasized in all sections so that the gastroenterologist can direct the diagnosis to the most common diseases, although the tables also include rare diseases. Digestive diseases potentially causing anemia have been studied in preference, but other causes of anemia have been included in the text and tables. Primitive hematological diseases that cause anemia are only listed, but are not discussed in depth. The last section is dedicated to simplifying all items discussed above, using practical rules to guide diagnosis and medical care with the greatest economy of resources and time.

  13. Recursive heuristic classification

    Science.gov (United States)

    Wilkins, David C.

    1994-01-01

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

  14. 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.

  15. Association of Stress Test Risk Classification With Health Status After Chronic Total Occlusion Angioplasty (from the Outcomes, Patient Health Status and Efficiency in Chronic Total Occlusion Hybrid Procedures [OPEN-CTO] Study).

    Science.gov (United States)

    Salisbury, Adam C; Sapontis, James; Saxon, John T; Gosch, Kensey L; Lombardi, William L; Karmpaliotis, Dimitri; Moses, Jeffery W; Qintar, Mohammed; Kirtane, Ajay J; Spertus, John A; Cohen, David J; Grantham, J Aaron

    2018-03-01

    Stress testing is endorsed by the American College of Cardiology/American Heart Association Appropriate Use Criteria to identify appropriate candidates for Chronic Total Occlusion (CTO) Percutaneous Coronary Intervention (PCI). However, the relation between stress test risk classification and health status after CTO PCI is not known. We studied 449 patients in the 12-center OPEN CTO registry who underwent stress testing before successful CTO PCI, comparing outcomes of patients with low-risk (LR) versus intermediate to high-risk (IHR) findings. Health status was assessed using the Seattle Angina Questionnaire Angina Frequency (SAQ AF), Quality of Life (SAQ QoL), and Summary Scores (SAQ SS). Stress tests were LR in 40 (8.9%) and IHR in 409 (91.1%) patients. There were greater improvements on the SAQ AF (LR vs IHR 14.2 ± 2.7 vs 23.3 ± 1.3 points, p <0.001) and SAQ SS (LR vs IHR 20.8 ± 2.3 vs 25.4 ± 1.1 points, p = 0.03) in patients with IHR findings, but there was no difference between groups on the SAQ QoL domain (LR vs IHR 24.8 ± 3.4 vs 27.3 ± 1.6 points, p = 0.42). We observed large health status improvements after CTO PCI in both the LR and IHR groups, with the greatest reduction in angina among those with IHR stress tests. Although patients with higher risk studies may experience greater reduction in angina symptoms, on average, patients with LR stress tests also experienced large improvements in symptoms after CTO PCI, suggesting patients with refractory symptoms should be considered appropriate candidates for CTO PCI regardless of stress test findings. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Building a Joint-Service Classification Research Roadmap: Methodological Issues in Selection and Classification

    Science.gov (United States)

    1994-02-01

    NEW METHODS FOR ESTIMATING GAINS DUE TO CLASSIFICATION AND NEW PROCEDURES FOR MAKING D!FFERENTIAL JOB ASSIGNMENTS Paul J. Sticha Classification...people, assumed to be reflected in test performance" (Cronbach & Meehl , 1955, p. 283). Methods for establishing and testing a latent structure will be...and Meehl ). Because of this close tie to theory development and testing, and the ability to explicitly account for measurement error in the observed

  17. Porphyrin Tests

    Science.gov (United States)

    ... safe and unsafe drugs, different sites use different classifications and the lists are not the same. Why ... Kathleen D. & Pagana, Timothy J. (2001). M osby's Diagnostic and Laboratory Test Reference 5th Edition: Mosby, Inc., ...

  18. Hierarchical classification as relational framing.

    Science.gov (United States)

    Slattery, Brian; Stewart, Ian

    2014-01-01

    The purpose of this study was to model hierarchical classification as contextually controlled, generalized relational responding or relational framing. In Experiment 1, a training procedure involving nonarbitrarily related multidimensional stimuli was used to establish two arbitrary shapes as contextual cues for 'member of' and 'includes' relational responding, respectively. Subsequently those cues were used to establish a network of arbitrary stimuli in particular hierarchical relations with each other, and then test for derivation of further untrained hierarchical relations as well as for transformation of functions. Resultant patterns of relational framing showed properties of transitive class containment, asymmetrical class containment, and unilateral property induction, consistent with conceptions of hierarchical classification as described within the cognitive developmental literature. Experiment 2 extended the basic model by using "fuzzy category" stimuli and providing a better controlled test of transformation of functions. Limitations and future research directions are discussed. © Society for the Experimental Analysis of Behavior.

  19. 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.

  20. Statistical classification of images

    OpenAIRE

    Giuliodori, María Andrea

    2011-01-01

    Image classification is a burgeoning field of study. Despite the advances achieved in this camp, there is no general agreement about what is the most effective methods for the classification of digital images. This dissertation contributes to this line of research by developing different statistical methods aim to classifying digital images. In Chapter 1 we introduce basic concepts of image classification and review some results and methodologies proposed previously in the literature. In Chap...

  1. Towards secondary fingerprint classification

    CSIR Research Space (South Africa)

    Msiza, IS

    2011-07-01

    Full Text Available fingerprints that have a ?x that is greater than 30 pixels, and the same reasoning can be attributed to the mis-classification of some of the RL class fingerprints. Possible 2011 International Conference on Computer Engineering and Applications (ICCEA 2011...]. Even though the concept of sample classification applies to systems that use almost any biometric modality, this manuscript focuses on fingerprint classification, with immediate application to an automated fingerprint recog- nition system...

  2. 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)

    Karakitsou, Efrossyni; Chrelias, Charalampos; Pappas, Asimakis; Panayiotides, Ioannis; Kyrgiou, Maria; Paraskevaidis, Evangelos

    2015-01-01

    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. PMID:26339651

  3. 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.

  4. 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

  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. Linear Classification Functions.

    Science.gov (United States)

    Huberty, Carl J.; Smith, Jerry D.

    Linear classification functions (LCFs) arise in a predictive discriminant analysis for the purpose of classifying experimental units into criterion groups. The relative contribution of the response variables to classification accuracy may be based on LCF-variable correlations for each group. It is proved that, if the raw response measures are…

  7. 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

  8. Comparison of Classification Algorithms and Training Sample Sizes in Urban Land Classification with Landsat Thematic Mapper Imagery

    Directory of Open Access Journals (Sweden)

    Congcong Li

    2014-01-01

    Full Text Available Although a large number of new image classification algorithms have been developed, they are rarely tested with the same classification task. In this research, with the same Landsat Thematic Mapper (TM data set and the same classification scheme over Guangzhou City, China, we tested two unsupervised and 13 supervised classification algorithms, including a number of machine learning algorithms that became popular in remote sensing during the past 20 years. Our analysis focused primarily on the spectral information provided by the TM data. We assessed all algorithms in a per-pixel classification decision experiment and all supervised algorithms in a segment-based experiment. We found that when sufficiently representative training samples were used, most algorithms performed reasonably well. Lack of training samples led to greater classification accuracy discrepancies than classification algorithms themselves. Some algorithms were more tolerable to insufficient (less representative training samples than others. Many algorithms improved the overall accuracy marginally with per-segment decision making.

  9. Challenges in prosthesis classification.

    Science.gov (United States)

    Robertsson, Otto; Mendenhall, Stan; Paxton, Elizabeth W; Inacio, Maria C S; Graves, Stephen

    2011-12-21

    Accurate prosthesis classification is critical for total joint arthroplasty surveillance and assessment of comparative effectiveness. Historically, prosthesis classification was based solely on the names of the prosthesis manufacturers. As a result, prosthesis designs changed without corresponding name changes, and other prostheses' names changed over time without substantial design modifications. As the number of prostheses used in total joint arthroplasty on the market increased, catalog and lot numbers associated with prosthesis descriptions were introduced by manufacturers. Currently, these catalog and lot numbers are not standardized, and there is no consensus on categorization of these numbers into brands or subbrands. Classification of the attributes of a prosthesis also varies, limiting comparisons of prostheses across studies and reports. The development of a universal prosthesis classification system would standardize prosthesis classification and enhance total joint arthroplasty research collaboration worldwide. This is a current area of focus for the International Consortium of Orthopaedic Registries (ICOR).

  10. Kappa Coefficients for Circular Classifications

    NARCIS (Netherlands)

    Warrens, Matthijs J.; Pratiwi, Bunga C.

    2016-01-01

    Circular classifications are classification scales with categories that exhibit a certain periodicity. Since linear scales have endpoints, the standard weighted kappas used for linear scales are not appropriate for analyzing agreement between two circular classifications. A family of kappa

  11. 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.

  12. 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)

  13. 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.

  14. 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)

  15. 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.

  16. [Classification of cardiomyopathy].

    Science.gov (United States)

    Asakura, Masanori; Kitakaze, Masafumi

    2014-01-01

    Cardiomyopathy is a group of cardiovascular diseases with poor prognosis. Some patients with dilated cardiomyopathy need heart transplantations due to severe heart failure. Some patients with hypertrophic cardiomyopathy die unexpectedly due to malignant ventricular arrhythmias. Various phenotypes of cardiomyopathies are due to the heterogeneous group of diseases. The classification of cardiomyopathies is important and indispensable in the clinical situation. However, their classification has not been established, because the causes of cardiomyopathies have not been fully elucidated. We usually use definition and classification offered by WHO/ISFC task force in 1995. Recently, several new definitions and classifications of the cardiomyopathies have been published by American Heart Association, European Society of Cardiology and Japanese Circulation Society.

  17. 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.

  18. Classification in Medical Imaging

    DEFF Research Database (Denmark)

    Chen, Chen

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

  19. 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.

  20. Hand eczema classification

    DEFF Research Database (Denmark)

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

    2008-01-01

    Summary Background Hand eczema is a long-lasting disease with a high prevalence in the background population. The disease has severe, negative effects on quality of life and sometimes on social status. Epidemiological studies have identified risk factors for onset and prognosis, but treatment...... 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....

  1. 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....

  2. Snake classification from images

    OpenAIRE

    James, Alex.

    2017-01-01

    Incorrect snake identification from the observable visual traits is a major reason of death resulting from snake bites. So far no automatic classification method has been proposed to distinguish snakes by deciphering the taxonomy features of snake for the two major species of snakes i.e. Elapidae and Viperidae. We present a parallel processed inter-feature product similarity fusion based automatic classification of Spectacled Cobra, Russel's Viper, King Cobra, Common Krait, Saw Scaled Viper, ...

  3. 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.

  4. 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...

  5. 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

  6. Crop Classification by Polarimetric SAR

    DEFF Research Database (Denmark)

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

    1999-01-01

    Polarimetric SAR-data of agricultural fields have been acquired by the Danish polarimetric L- and C-band SAR (EMISAR) during a number of missions at the Danish agricultural test site Foulum during 1995. The data are used to study the classification potential of polarimetric SAR data using...... the Wishart distributed covariance matrix. In general, the improvement of using polarimetric SAR data compared to multipolarization SAR data is larger at L-band compared to C-band. On the other hand, the variability due to natural variation and different incidence angles is larger at L-band compared to C-band...

  7. Classification of normal sagittal spine alignment: refounding the Roussouly classification.

    Science.gov (United States)

    Laouissat, Féthi; Sebaaly, Amer; Gehrchen, Martin; Roussouly, Pierre

    2017-04-28

    Although the Roussouly classification of common variants in spinal sagittal alignment is well accepted, no studies have implemented it in an asymptomatic adult population. In addition, no study investigated the radiographic features of asymptomatic patients with an anteverted pelvis. The aim of this prospective radiographic study of 296 asymptomatic adults without spinal pathology was to investigate how the Roussouly classification could include the anteverted pelvis concept. Pelvic incidence (PI), sacral slope (SS), pelvic tilt (PT), and the lumbar parameters lumbar lordosis (Global LL), lordosis tilt angle (LTA), total number of lordotic vertebra (LL verteb), and C7 plumbline/sacrofemoral distance ratio (C7PL ratio) were evaluated in 296 healthy volunteers (126 males, 170 females; mean age, 27 years; range 18-48 years). Comparison between the five types of the Roussouly classification used Student, ANOVA, and Tukey tests for quantitative variables and χ (2), Fischer, and Holm tests for qualitative variables. Mean PI and PT were, respectively, (39°, 10°) for type 1, (41°, 10°) for type 2, (53°, 13°) for type 3, and (62°, 12°) for type 4 (p  35°. PT was low or negative (mean 4° ± 3°). C7PL ratio was >1 (in front of the hip axis) in 13% of all cases, and between 0 and 1 (between sacrum and hip axis) in 49%. Although asymptomatic adults stood with stable global balance, the sagittal spinal alignment of healthy subjects, newly divided in 5 sagittal types, varied significantly. Type 3 AP appears as a new and unusual sagittal shape with low-grade PI, very low or negative PT, and hyperlordosis. Whereas most asymptomatic adults stood with C7PL behind the hip axis, a sizeable portion had C7 in front of the hip axis. This could be a new controversial aspect of ideal spinal balance.

  8. Oral glucose tolerance test is needed for appropriate classification of glucose regulation in patients with coronary artery disease: a report from the Euro Heart Survey on Diabetes and the Heart.

    Science.gov (United States)

    Bartnik, M; Rydén, L; Malmberg, K; Ohrvik, J; Pyörälä, K; Standl, E; Ferrari, R; Simoons, M; Soler-Soler, J

    2007-01-01

    Patients with coronary artery disease (CAD) and abnormal glucose regulation (AGR) are at high risk for subsequent cardiovascular events, underlining the importance of accurate glucometabolic assessment in clinical practice. To investigate different methods to identify glucose disturbances among patients with acute and stable coronary heart disease. Consecutive patients referred to cardiologists were prospectively enrolled at 110 centres in 25 countries (n = 4961). Fasting plasma glucose (FPG) and glycaemia 2 h after a 75-g glucose load were requested in patients without known glucose abnormalities (n = 3362). Glucose metabolism was classified according to the World Health Organization and American Diabetes Association (ADA; 1997, 2004) criteria as normal, impaired fasting glucose (IFG), impaired glucose tolerance (IGT) or diabetes. Data on FPG and 2-h post-load glycaemia were available for 1867 patients, of whom 870 (47%) had normal glucose regulation, 87 (5%) had IFG, 591 (32%) had IGT and 319 (17%) had diabetes. If classification had been based on the ADA criterion from 1997, the proportion of misclassified (underdiagnosed) patients would have been 39%. The ADA 2004 criterion would have overdiagnosed 8% and underdiagnosed 33% of the patients, resulting in a total misclassification rate of 41%. For ethical concerns and practical reasons, oral glucose tolerance test (OGTT) was not conducted in 1495 of eligible patients. These patients were more often women, had higher age and waist circumference, and were therefore more likely to have AGR than those who were included. A model based on easily available clinical and laboratory variables, including FPG, high-density lipoprotein cholesterol, age and the logarithm of glycated haemoglobin A1c, misclassified 44% of the patients, of whom 18% were overdiagnosed and 26% were underdiagnosed. An OGTT is still the most appropriate method for the clinical assessment of glucometabolic status in patients with coronary heart

  9. 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...

  10. Medical imbalanced data classification

    Directory of Open Access Journals (Sweden)

    Sara Belarouci

    2017-04-01

    Full Text Available In general, the imbalanced dataset is a problem often found in health applications. In medical data classification, we often face the imbalanced number of data samples where at least one of the classes constitutes only a very small minority of the data. In the same time, it represent a difficult problem in most of machine learning algorithms. There have been many works dealing with classification of imbalanced dataset. In this paper, we proposed a learning method based on a cost sensitive extension of Least Mean Square (LMS algorithm that penalizes errors of different samples with different weights and some rules of thumb to determine those weights. After the balancing phase, we apply the different techniques (Support Vector Machine [SVM], K- Nearest Neighbor [K-NN] and Multilayer perceptron [MLP] for the balanced datasets. We have also compared the obtained results before and after balancing method. We have obtained best results compared to literature with a classification accuracy of 100%.

  11. 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...... of descriptors, number of classes, and class intervals occurred between national schemes. However, a proposal “acoustic classification scheme for dwellings” has been developed recently in the European COST Action TU0901 with 32 member countries. This proposal has been accepted as an ISO work item. This paper...

  12. 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...

  13. 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.

  14. DNA sequence analysis using hierarchical ART-based classification networks

    Energy Technology Data Exchange (ETDEWEB)

    LeBlanc, C.; Hruska, S.I. [Florida State Univ., Tallahassee, FL (United States); Katholi, C.R.; Unnasch, T.R. [Univ. of Alabama, Birmingham, AL (United States)

    1994-12-31

    Adaptive resonance theory (ART) describes a class of artificial neural network architectures that act as classification tools which self-organize, work in real-time, and require no retraining to classify novel sequences. We have adapted ART networks to provide support to scientists attempting to categorize tandem repeat DNA fragments from Onchocerca volvulus. In this approach, sequences of DNA fragments are presented to multiple ART-based networks which are linked together into two (or more) tiers; the first provides coarse sequence classification while the sub- sequent tiers refine the classifications as needed. The overall rating of the resulting classification of fragments is measured using statistical techniques based on those introduced to validate results from traditional phylogenetic analysis. Tests of the Hierarchical ART-based Classification Network, or HABclass network, indicate its value as a fast, easy-to-use classification tool which adapts to new data without retraining on previously classified data.

  15. Dynamic time warping and sparse representation classification for birdsong phrase classification using limited training data.

    Science.gov (United States)

    Tan, Lee N; Alwan, Abeer; Kossan, George; Cody, Martin L; Taylor, Charles E

    2015-03-01

    Annotation of phrases in birdsongs can be helpful to behavioral and population studies. To reduce the need for manual annotation, an automated birdsong phrase classification algorithm for limited data is developed. Limited data occur because of limited recordings or the existence of rare phrases. In this paper, classification of up to 81 phrase classes of Cassin's Vireo is performed using one to five training samples per class. The algorithm involves dynamic time warping (DTW) and two passes of sparse representation (SR) classification. DTW improves the similarity between training and test phrases from the same class in the presence of individual bird differences and phrase segmentation inconsistencies. The SR classifier works by finding a sparse linear combination of training feature vectors from all classes that best approximates the test feature vector. When the class decisions from DTW and the first pass SR classification are different, SR classification is repeated using training samples from these two conflicting classes. Compared to DTW, support vector machines, and an SR classifier without DTW, the proposed classifier achieves the highest classification accuracies of 94% and 89% on manually segmented and automatically segmented phrases, respectively, from unseen Cassin's Vireo individuals, using five training samples per class.

  16. 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…

  17. 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...

  18. 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 finding...

  19. Bosniak classification system

    DEFF Research Database (Denmark)

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

    2015-01-01

    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. PU...

  20. Equivalent Diagnostic Classification Models

    Science.gov (United States)

    Maris, Gunter; Bechger, Timo

    2009-01-01

    Rupp and Templin (2008) do a good job at describing the ever expanding landscape of Diagnostic Classification Models (DCM). In many ways, their review article clearly points to some of the questions that need to be answered before DCMs can become part of the psychometric practitioners toolkit. Apart from the issues mentioned in this article that…

  1. 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

  2. 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...

  3. Classification, confusion and misclassification

    African Journals Online (AJOL)

    It must have concerned human beings and animals since they first became aware. Classification is designed to assist understanding. The response to a phenomenon ... endometrial hyperplasia changed and was simplified to include two categories, compared with four previously: from with atypia and without (each of those ...

  4. Classification of waste packages

    Energy Technology Data Exchange (ETDEWEB)

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

    2001-07-01

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

  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. Repulsive-SVDD Classification

    Science.gov (United States)

    2015-05-22

    all abnormal data samples outside the hypersphere. This SVDD has been a successful approach to solving one-class problems such as outlier detection...Classification 279 is maximised, similar to the maximal margin philosophy of a support vector machine. A visualisation of RSVC is demonstrated in Fig

  7. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    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...

  8. Anticipation of coincidence, gender, and sports classification.

    Science.gov (United States)

    Brady, F

    1996-02-01

    This study investigated the effects of sport classification and gender on anticipation of coincidence. 102 undergraduate male and female students from open skills, closed skills, and nonathletic groups were tested on the Bassin Anticipation Timer. The dependent measures of absolute error, constant error, and variable error were analyzed in a 2 (gender) x 3 (sport classification) x 4 (speeds) design. Men had lower absolute and constant error scores than women. Open skills athletes were less variable in their responses while male open skills athletes were more accurate and less variable at the faster speeds. Performance on the Bassin Anticipation Timer may not be representative of athletic skills.

  9. 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.

  10. Diagnosis and classification of autoimmune hemolytic anemia.

    Science.gov (United States)

    Bass, Garrett F; Tuscano, Emily T; Tuscano, Joseph M

    2014-01-01

    Uncompensated autoantibody-mediated red blood cell (RBC) consumption is the hallmark of autoimmune hemolytic anemia (AIHA). Classification of AIHA is pathophysiologically based and divides AIHA into warm, mixed or cold-reactive subtypes. This thermal-based classification is based on the optimal autoantibody-RBC reactivity temperatures. AIHA is further subcategorized into idiopathic and secondary with the later being associated with a number of underlying infectious, neoplastic and autoimmune disorders. In most cases AIHA is confirmed by a positive direct antiglobulin test (DAT). The standard therapeutic approaches to treatment of AIHA include corticosteroids, splenectomy, immunosuppressive agents and monoclonal antibodies. Published by Elsevier B.V.

  11. Photometric Supernova Classification with Machine Learning

    Science.gov (United States)

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

    2016-08-01

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

  12. [Classification of primary bone tumors].

    Science.gov (United States)

    Dominok, G W; Frege, J

    1986-01-01

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

  13. An Ecological Diagnostic Classification Plan.

    Science.gov (United States)

    Hurst, James C.; McKinley, Donna L.

    1988-01-01

    Discusses the value of diagnostic classification systems to counseling professionals. Describes the Ecological Diagnostic Classification Plan, an approach to diagnosis that includes the environment as a possible cause of pathology and target of intervention. (Author/KS)

  14. Automated spectral classification and the GAIA project

    Science.gov (United States)

    Lasala, Jerry; Kurtz, Michael J.

    1995-01-01

    Two dimensional spectral types for each of the stars observed in the global astrometric interferometer for astrophysics (GAIA) mission would provide additional information for the galactic structure and stellar evolution studies, as well as helping in the identification of unusual objects and populations. The classification of the large quantity generated spectra requires that automated techniques are implemented. Approaches for the automatic classification are reviewed, and a metric-distance method is discussed. In tests, the metric-distance method produced spectral types with mean errors comparable to those of human classifiers working at similar resolution. Data and equipment requirements for an automated classification survey, are discussed. A program of auxiliary observations is proposed to yield spectral types and radial velocities for the GAIA-observed stars.

  15. Graduates employment classification using data mining approach

    Science.gov (United States)

    Aziz, Mohd Tajul Rizal Ab; Yusof, Yuhanis

    2016-08-01

    Data Mining is a platform to extract hidden knowledge in a collection of data. This study investigates the suitable classification model to classify graduates employment for one of the MARA Professional College (KPM) in Malaysia. The aim is to classify the graduates into either as employed, unemployed or further study. Five data mining algorithms offered in WEKA were used; Naïve Bayes, Logistic regression, Multilayer perceptron, k-nearest neighbor and Decision tree J48. Based on the obtained result, it is learned that the Logistic regression produces the highest classification accuracy which is at 92.5%. Such result was obtained while using 80% data for training and 20% for testing. The produced classification model will benefit the management of the college as it provides insight to the quality of graduates that they produce and how their curriculum can be improved to cater the needs from the industry.

  16. Low Complexity Kolmogorov-Smirnov Modulation Classification

    CERN Document Server

    Wang, Fanggang; Zhong, Zhangdui

    2011-01-01

    Kolmogorov-Smirnov (K-S) test-a non-parametric method to measure the goodness of fit, is applied for automatic modulation classification (AMC) in this paper. The basic procedure involves computing the empirical cumulative distribution function (ECDF) of some decision statistic derived from the received signal, and comparing it with the CDFs of the signal under each candidate modulation format. The K-S-based modulation classifier is first developed for AWGN channel, then it is applied to OFDM-SDMA systems to cancel multiuser interference. Regarding the complexity issue of K-S modulation classification, we propose a low-complexity method based on the robustness of the K-S classifier. Extensive simulation results demonstrate that compared with the traditional cumulant-based classifiers, the proposed K-S classifier offers superior classification performance and requires less number of signal samples (thus is fast).

  17. 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.

  18. Automated source classification of new transient sources

    Science.gov (United States)

    Oertel, M.; Kreikenbohm, A.; Wilms, J.; DeLuca, A.

    2017-10-01

    The EXTraS project harvests the hitherto unexplored temporal domain information buried in the serendipitous data collected by the European Photon Imaging Camera (EPIC) onboard the ESA XMM-Newton mission since its launch. This includes a search for fast transients, missed by standard image analysis, and a search and characterization of variability in hundreds of thousands of sources. We present an automated classification scheme for new transient sources in the EXTraS project. The method is as follows: source classification features of a training sample are used to train machine learning algorithms (performed in R; randomForest (Breiman, 2001) in supervised mode) which are then tested on a sample of known source classes and used for classification.

  19. 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...

  20. Catchment classification as a learning framework

    Science.gov (United States)

    Wagener, T.; Sawicz, K. A.; Sivapalan, M.; Troch, P. A.; Carrillo, G. A.; Kelleher, C.

    2012-12-01

    Catchment classification is an efficient method to synthesize our understanding of how climate variability and catchment characteristics interact in defining hydrological response and therefore similarity/dissimilarity between catchments. The search for a common and generally accepted catchment classification framework is ongoing and will likely continue for a while. However, the search itself is an important milestone in hydrology since it provides an environment in which we can place local behavior in its regional or even global context. This effort by itself tests and has the potential to significantly advance our ability for generalizing our understanding of hydrological processes. Here, we present results of a joint bottom-up and top-down modeling study focused on catchment classification through understanding dominant controls on hydrologic signatures, including the causes for their spatial and temporal variability. We analyzed over 300 US watersheds with over 40 years of data. Results demonstrate that different modeling strategies provide different insights, and that their relative comparison is important for gaining confidence in the conclusions made. Hydrologic similarity is not just the basis for catchment classification, but also for transferability of information, for generalization of our hydrologic understanding and also for understanding the potential impacts of environmental change. It is at the heart of our science and catchment classification is one important way to understand it.

  1. Lissencephaly: Expanded imaging and clinical classification.

    Science.gov (United States)

    Di Donato, Nataliya; Chiari, Sara; Mirzaa, Ghayda M; Aldinger, Kimberly; Parrini, Elena; Olds, Carissa; Barkovich, A James; Guerrini, Renzo; Dobyns, William B

    2017-06-01

    Lissencephaly ("smooth brain," LIS) is a malformation of cortical development associated with deficient neuronal migration and abnormal formation of cerebral convolutions or gyri. The LIS spectrum includes agyria, pachygyria, and subcortical band heterotopia. Our first classification of LIS and subcortical band heterotopia (SBH) was developed to distinguish between the first two genetic causes of LIS-LIS1 (PAFAH1B1) and DCX. However, progress in molecular genetics has led to identification of 19 LIS-associated genes, leaving the existing classification system insufficient to distinguish the increasingly diverse patterns of LIS. To address this challenge, we reviewed clinical, imaging and molecular data on 188 patients with LIS-SBH ascertained during the last 5 years, and reviewed selected archival data on another ∼1,400 patients. Using these data plus published reports, we constructed a new imaging based classification system with 21 recognizable patterns that reliably predict the most likely causative genes. These patterns do not correlate consistently with the clinical outcome, leading us to also develop a new scale useful for predicting clinical severity and outcome. Taken together, our work provides new tools that should prove useful for clinical management and genetic counselling of patients with LIS-SBH (imaging and severity based classifications), and guidance for prioritizing and interpreting genetic testing results (imaging based- classification). © 2017 Wiley Periodicals, Inc.

  2. Clinical and radiographic degenerative spondylolisthesis (CARDS) classification.

    Science.gov (United States)

    Kepler, Christopher K; Hilibrand, Alan S; Sayadipour, Amir; Koerner, John D; Rihn, Jeffrey A; Radcliff, Kristen E; Vaccaro, Alexander R; Albert, Todd J; Anderson, D Greg

    2015-08-01

    Lumbar degenerative spondylolisthesis (DS) is a common, acquired condition leading to disabling back and/or leg pain. Although surgery is common used to treat patients with severe symptoms, there are no universally accepted treatment guidelines. Wide variation in vertebral translation, disc collapse, sagittal alignment, and vertebral mobility suggests this is a heterogeneous disease. A classification scheme would be useful to differentiate homogenous subgroups that may benefit from different treatment strategies. To develop and test the reliability of a simple, clinically useful classification scheme for lumbar DS. Retrospective case series. One hundred twenty-six patients. Proposed radiographic classification system. A classification system is proposed that considers disc space height, sagittal alignment and translation, and the absence or presence of unilateral or bilateral leg pain. Test cases were graded by six observers to establish interobserver reliability and regraded in a different order 1 month later to establish intraobserver reliability using Kappa analysis. To establish the relative prevalence of each subtype, a series of 100 consecutive patients presenting with L4-L5 DS were classified. Four radiographic subtypes were identified: Type A: advanced Disc space collapse without kyphosis; Type B: disc partially preserved with translation of 5 mm or less; Type C: disc partially preserved with translation of more than 5 mm; and Type D: kyphotic alignment. The leg pain modifier 0 denotes no leg pain, 1 denotes unilateral leg pain, and 2 represents bilateral leg pain. The Kappa value describing interobserver reliability was 0.82, representing near-perfect agreement. Intraobserver reliability analysis demonstrated Kappa=0.83, representing near-perfect agreement. Grading of the consecutive series of 100 patients revealed the following distribution: 16% Type A, 37% Type B, 33% Type C, and 14% Type D. A new radiographic and clinical classification scheme for

  3. 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....

  4. The role of classification of chronic low back pain.

    Science.gov (United States)

    Fairbank, Jeremy; Gwilym, Stephen E; France, John C; Daffner, Scott D; Dettori, Joseph; Hermsmeyer, Jeff; Andersson, Gunnar

    2011-10-01

    Systematic review. To describe the various ways chronic low back pain (CLBP) is classified, to determine if the classification systems are reliable and to assess whether classification-specific interventions have been shown to be effective in treating CLBP. A classification system by which individual patients with CLBP could be identified and directed to an effective treatment protocol would be beneficial. Those systems that direct treatment have the greatest potential influence on patient outcomes. A systematic search was conducted in MEDLINE and the Cochrane Collaboration Library for English language literature published through January 2011. We included articles that specifically described a clinical classification system for CLBP, reported on the reliability of a classification system, or evaluated the effectiveness of classification-specific interventions. A total of 60 articles were initially reviewed. We identified 28 classification systems that met inclusion criteria: 16 diagnostic systems, 7 prognostic systems, and 5 treatment-based systems. In addition, we found 10 randomized controlled trials of CLBP treatment from which we compared inclusion and exclusion criteria. Treatment-based systems were all directed at nonoperative management. Four of the 5 treatment-based systems underwent reliability testing and were found to have interobserver agreement of 70% to 100%. Reliability increased with training and familiarity with a given classification. As the number of subgroups within a classification increased, interobserver agreement decreased. Function and pain were similar between patients treated with the McKenzie classification system and those treated with dynamic strengthening training after 8 months of follow-up in one randomized controlled trial. One prospective cohort study reported better pain and function using the Canadian Back Institute Classification system than with standard rehabilitation. An analysis of the admission criteria to recent

  5. 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...

  6. Vehicle Maneuver Detection with Accelerometer-Based Classification

    National Research Council Canada - National Science Library

    Cervantes-Villanueva, Javier; Carrillo-Zapata, Daniel; Terroso-Saenz, Fernando; Valdes-Vela, Mercedes; Skarmeta, Antonio

    2016-01-01

    .... For its realization, we have evaluated different classification algorithms to act as agents within the architecture. Finally, our approach has been tested with a real-world dataset collected by means of the ad hoc mobile application developed.

  7. Clinical classification and treatment of cubital tunnel syndrome.

    Science.gov (United States)

    Qing, Cui; Zhang, Jianhua; Wu, Shidong; Ling, Zhao; Wang, Shuanchi; Li, Haoran; Li, Haiqing

    2014-11-01

    The aim of the present study was to investigate a new clinical classification of cubital tunnel syndrome that provides an improved basis for the clinical diagnosis and treatment of the disease. Retrospective analysis was performed on 341 patients with cubital tunnel syndrome. Based on the etiology, signs and symptoms, neurophysiological tests and computed tomography (CT) imaging, a new clinical classification was proposed. The patients enrolled in the study were treated according to the new classification. According to the new classification, cubital tunnel syndrome cases were divided into types I-IV. Treatment for patients with type I consisted of rest, immobilization or physiotherapy, while patients with type II received simple ulnar neurolysis. Type III patients underwent ulnar neurolysis with expansion of the ulnar nerve sulcus or ulnar nerve anterior transposition surgery. Type IV patients represented a subgroup of cubital tunnel syndrome cases caused by factors other than degenerative joint diseases, including cysts, tumors, traumatic fracture, deformity and elbow deformity. Patients of this type received appropriate surgical treatment according to the specific etiology. Based on previous classifications that relied on sensation and strength symptoms, a new clinical classification of elbow tunnel syndrome has been established in the present study that adopts a CT imaging evaluation index. The new classification is reasonable, simple and practical, and therapies based on this classification are more targeted than those based on previous classifications.

  8. 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...

  9. 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.

  10. Classification of myocardial infarction

    DEFF Research Database (Denmark)

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

    2013-01-01

    The classification of myocardial infarction into 5 types was introduced in 2007 as an important component of the universal definition. In contrast to the plaque rupture-related type 1 myocardial infarction, type 2 myocardial infarction is considered to be caused by an imbalance between demand...... and supply of oxygen in the myocardium. However, no specific criteria for type 2 myocardial infarction have been established....

  11. Seismic event classification system

    Science.gov (United States)

    Dowla, Farid U.; Jarpe, Stephen P.; Maurer, William

    1994-01-01

    In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities.

  12. [Morphological classification of glioblastomas].

    Science.gov (United States)

    Figarella-Branger, D; Bouvier, C; Moroch, J; Michalak, S; F Burel-Vandenbos

    2010-12-01

    In the 2007 WHO classification, glioblastomas are classified among the group of astrocytic tumors. They are highly malignant (grade IV). This group of tumors is morphologically heterogeneous. The WHO distinguishes between clinico-pathological entities, variants of entities and histological pattern. Variants are defined as being reliably indentified histologically and having some relevance for clinical outcome but as still being part of a previously defined overarching entity. Patterns of differentiation are identifiable by histological appearances but without clinical or pathological significance. The description of the histological and immunohistochemical features is based on the 2007 WHO classification. In addition to the classic form of glioblastoma, two variants exist: the giant cell GBM and the gliosarcoma. The first but not the second would have a better outcome than the classic glioblastoma. The WHO classification also distinguishes several patterns of differentiation: small cells glioblastoma; glioblastoma with lipidized cells; glioblastoma with oligodendroglioma component; glioblastoma with heterologous differentiation. These patterns have to be recognized because they represent sometimes a diagnostic challenge. GFAP, Olig2 and Mib1/Ki67 are the most relevant immunohistochemical markers. Diagnostic value of neuronal markers is still controversial. EGFR or p53 expression can be detected and their prognosis value is discussed in this chapter. A systematic analysis of some markers in routine, for example IDH1 or internexin-a, could help to define more homogeneous groups of patients. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

  13. [Myelodysplastic syndrome classification].

    Science.gov (United States)

    Ghariani, Ines; Braham, Najia; Hassine, Mohsen; Kortas, Mondher

    2013-01-01

    Myelodysplastic syndromes (MDS) are myeloid disorders with various clinical and biological presentations. The French-American-British (FAB-1982) classification included five categories basing on morphology and bone marrow blast count. Three criteria are taken into account: 1) the percentage of blasts in peripheral blood and bone marrow, 2) the percentage of ringed sideroblasts, and 3) the number of monocytes in peripheral blood. The World Health Organization classification (WHO 2001, 2008) modifies the FAB system by also taking cytogenetic characteristics and molecular biology into consideration. The last classification (WHO-2008) takes into account: 1) the number of peripheral cytopenia, 2) the percentage of blasts in peripheral blood and bone marrow, 3) the percentage of ringed sideroblasts, 4) the possible presence of Auer Rods, and 5) the detection of a cytogenetic abnormality (the isolated 5q deletion). The following subgroups are defined: refractory cytopenia with unilineage dysplasia, refractory anemia with ringed sideroblasts, refractory cytopenia with multilineage dysplasia, refractory anemia with excess blasts, myelodysplastic syndrome unclassifiable and myelodysplastic syndrome with isolated del(5q).

  14. Agricultural Land Use classification from Envisat MERIS

    Science.gov (United States)

    Brodsky, L.; Kodesova, R.

    2009-04-01

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

  15. 7 CFR 28.177 - Request for classification and comparison of cotton.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Request for classification and comparison of cotton... STANDARD CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.177 Request for classification and comparison of cotton. The applicant shall make a separate...

  16. Megaureter: classification, pathophysiology, and management.

    Science.gov (United States)

    Simoni, F; Vino, L; Pizzini, C; Benini, D; Fanos, V

    2000-01-01

    The term megaureter does not define a specific pathological condition, because it can be due to different underlying abnormalities. The most used classification includes three groups: refluxing megaureter, associated with vesicoureteral reflux (VUR); obstructive megaureter, associated with urine flow impairment at the vesicoureteral junction; non-refluxing non-obstructive megaureter, if neither obstruction nor reflux can be identified. Each group can be divided into two subgroups: primary megaureter; secondary megaureter. With the advent of antenatal ultrasound an increased number of cases are identified prior to the onset of symptoms. The common used investigation are: urinary tract ultrasound, voiding cystourethrography, urography, serial diuretic renography and pressure-perfusion studies (Whitaker test). The advent of prenatal and neonatal echography has modified the natural history of megaureter. Nowadays non operative management is preferred. Operative intervention is indicated only in these cases: significant impairment to urine flow; worsening renal function during the observation time; recurrent UTI in spite of adequate antibiotic prophylaxis.

  17. Detection and Classification of Objects in Synthetic Aperture Radar Imagery

    Science.gov (United States)

    2006-02-01

    geo-spatial and video data. Because of this potential for general application, a number of CSSIP (CRC for Sensor Signals and Information Processing...test set. Secondly, since the back- propagation method for determining the network weights is based on the principle of steepest descent, there is no...classification results In order to test the performance of the various classification methods described in this section, the “ banana ” data set has been

  18. 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

  19. Pulmonary CT image classification with evolutionary programming.

    Science.gov (United States)

    Madsen, M T; Uppaluri, R; Hoffman, E A; McLennan, G

    1999-12-01

    It is often difficult to classify information in medical images from derived features. The purpose of this research was to investigate the use of evolutionary programming as a tool for selecting important features and generating algorithms to classify computed tomographic (CT) images of the lung. Training and test sets consisting of 11 features derived from multiple lung CT images were generated, along with an indicator of the target area from which features originated. The images included five parameters based on histogram analysis, 11 parameters based on run length and co-occurrence matrix measures, and the fractal dimension. Two classification experiments were performed. In the first, the classification task was to distinguish between the subtle but known differences between anterior and posterior portions of transverse lung CT sections. The second classification task was to distinguish normal lung CT images from emphysematous images. The performance of the evolutionary programming approach was compared with that of three statistical classifiers that used the same training and test sets. Evolutionary programming produced solutions that compared favorably with those of the statistical classifiers. In separating the anterior from the posterior lung sections, the evolutionary programming results were better than two of the three statistical approaches. The evolutionary programming approach correctly identified all the normal and abnormal lung images and accomplished this by using less features than the best statistical method. The results of this study demonstrate the utility of evolutionary programming as a tool for developing classification algorithms.

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    Juha Hyyppä

    2011-05-01

    Full Text Available 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.

  2. 40 CFR 152.164 - Classification procedures.

    Science.gov (United States)

    2010-07-01

    ... physical properties, in common. (b) Classification reviews. The Agency may conduct classification reviews... 40 Protection of Environment 23 2010-07-01 2010-07-01 false Classification procedures. 152.164... PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.164 Classification...

  3. 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.

  4. 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.

  5. Classification in Medical Imaging

    DEFF Research Database (Denmark)

    Chen, Chen

    to segment breast tissue and pectoral muscle area from the background in mammogram. The second focus is the choices of metric and its influence to the feasibility of a classifier, especially on k-nearest neighbors (k-NN) algorithm, with medical applications on breast cancer prediction and calcification...... and explores these challenging areas. The first focus of the thesis is to properly combine different local feature experts and prior information to design an effective classifier. The preliminary classification results, provided by the experts, are fused in order to develop an automatic segmentation method...

  6. Constructing criticality by classification

    DEFF Research Database (Denmark)

    Machacek, Erika

    2017-01-01

    This paper explores the role of expertise, the nature of criticality, and their relationship to securitisation as mineral raw materials are classified. It works with the construction of risk along the liberal logic of security to explore how "key materials" are turned into "critical materials......" 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...

  7. 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.

  8. Robust spike classification based on frequency domain neural waveform features.

    Science.gov (United States)

    Yang, Chenhui; Yuan, Yuan; Si, Jennie

    2013-12-01

    We introduce a new spike classification algorithm based on frequency domain features of the spike snippets. The goal for the algorithm is to provide high classification accuracy, low false misclassification, ease of implementation, robustness to signal degradation, and objectivity in classification outcomes. In this paper, we propose a spike classification algorithm based on frequency domain features (CFDF). It makes use of frequency domain contents of the recorded neural waveforms for spike classification. The self-organizing map (SOM) is used as a tool to determine the cluster number intuitively and directly by viewing the SOM output map. After that, spike classification can be easily performed using clustering algorithms such as the k-Means. In conjunction with our previously developed multiscale correlation of wavelet coefficient (MCWC) spike detection algorithm, we show that the MCWC and CFDF detection and classification system is robust when tested on several sets of artificial and real neural waveforms. The CFDF is comparable to or outperforms some popular automatic spike classification algorithms with artificial and real neural data. The detection and classification of neural action potentials or neural spikes is an important step in single-unit-based neuroscientific studies and applications. After the detection of neural snippets potentially containing neural spikes, a robust classification algorithm is applied for the analysis of the snippets to (1) extract similar waveforms into one class for them to be considered coming from one unit, and to (2) remove noise snippets if they do not contain any features of an action potential. Usually, a snippet is a small 2 or 3 ms segment of the recorded waveform, and differences in neural action potentials can be subtle from one unit to another. Therefore, a robust, high performance classification system like the CFDF is necessary. In addition, the proposed algorithm does not require any assumptions on statistical

  9. Objective Tests and Their Construction

    Science.gov (United States)

    Dimes, R. E.

    1973-01-01

    Summarizes classifications of educational objectives, types of test items, and principles underlying the construction of tests. Indicates that a combination of essay and objective tests is preferable in the overall evaluation of a course. (CC)

  10. 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 ....

  11. 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 classificat....... This difference between the written requirements specification and the oral discussions at the meetings may help explain software engineers’ general preference for people, rather than documents, as their information sources.......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....... While coordination mechanisms focus on how classification schemes enable cooperation among people pursuing a common goal, boundary objects embrace the implicit consequences of classification schemes in situations involving conflicting goals. Moreover, the requirements specification focused on functional...

  12. 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

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

    Science.gov (United States)

    Kammoun, M; Cassar-Malek, I; Meunier, B; Picard, B

    2014-06-24

    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.

  14. Machine Learning for Biological Trajectory Classification Applications

    Science.gov (United States)

    Sbalzarini, Ivo F.; Theriot, Julie; Koumoutsakos, Petros

    2002-01-01

    Machine-learning techniques, including clustering algorithms, support vector machines and hidden Markov models, are applied to the task of classifying trajectories of moving keratocyte cells. The different algorithms axe compared to each other as well as to expert and non-expert test persons, using concepts from signal-detection theory. The algorithms performed very well as compared to humans, suggesting a robust tool for trajectory classification in biological applications.

  15. 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.

  16. Automatic vehicle classification using linked visual words

    Science.gov (United States)

    Watcharapinchai, Nattachai; Aramvith, Supavadee; Siddhichai, Supakorn

    2017-07-01

    An improvement in the method of automatic vehicle classification is investigated. The challenges are to correctly classify vehicles regardless of changes in illumination, differences in points of view of the camera, and variations in the types of vehicles. Our proposed appearance-based feature extraction algorithm is called linked visual words (LVWs) and is based on the existing technique bag-of-visual word (BoVW) with the addition of spatial information to improve accuracy of classification. In addition, to prevent over-fitting due to a large number of LVWs, four common sampling techniques with LVWs are investigated. Our results suggest that the sampling of LVWs using TF-IDF with grouping improved the accuracy of classification for the test dataset. In summary, the proposed system is able to classify nine types of vehicles and work with surveillance cameras in real-world scenarios. The classification accuracy of the proposed system is 5.58% and 4.27% higher on average for three datasets when compared with BoVW + SVM and Lenet-5, respectively.

  17. 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.

  18. Pulmonary nodule classification with deep residual networks.

    Science.gov (United States)

    Nibali, Aiden; He, Zhen; Wollersheim, Dennis

    2017-10-01

    PURPOSE  : Lung cancer has the highest death rate among all cancers in the USA. In this work we focus on improving the ability of computer-aided diagnosis (CAD) systems to predict the malignancy of nodules from cropped CT images of lung nodules. We evaluate the effectiveness of very deep convolutional neural networks at the task of expert-level lung nodule malignancy classification. Using the state-of-the-art ResNet architecture as our basis, we explore the effect of curriculum learning, transfer learning, and varying network depth on the accuracy of malignancy classification. Due to a lack of public datasets with standardized problem definitions and train/test splits, studies in this area tend to not compare directly against other existing work. This makes it hard to know the relative improvement in the new solution. In contrast, we directly compare our system against two state-of-the-art deep learning systems for nodule classification on the LIDC/IDRI dataset using the same experimental setup and data set. The results show that our system achieves the highest performance in terms of all metrics measured including sensitivity, specificity, precision, AUROC, and accuracy. The proposed method of combining deep residual learning, curriculum learning, and transfer learning translates to high nodule classification accuracy. This reveals a promising new direction for effective pulmonary nodule CAD systems that mirrors the success of recent deep learning advances in other image-based application domains.

  19. Classification of neocortical interneurons using affinity propagation

    Directory of Open Access Journals (Sweden)

    Roberto eSantana

    2013-12-01

    Full Text Available In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. Neuronal classification has been a difficult problem because it is unclear what a neuronal cell class actually is and what are the best characteristics are to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological or molecular characteristics, when applied to selected datasets, have provided quantitative and unbiased identification of distinct neuronal subtypes. However, better and more robust classification methods are needed for increasingly complex and larger datasets. We explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. In fact, using a combined anatomical/physiological dataset, our algorithm differentiated parvalbumin from somatostatin interneurons in 49 out of 50 cases. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits.

  20. Classification of neocortical interneurons using affinity propagation

    Science.gov (United States)

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

    2013-01-01

    In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. In fact, neuronal classification is a difficult problem because it is unclear how to designate a neuronal cell class and what are the best characteristics to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological, or molecular characteristics, have provided quantitative and unbiased identification of distinct neuronal subtypes, when applied to selected datasets. However, better and more robust classification methods are needed for increasingly complex and larger datasets. Here, we explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. Affinity propagation outperformed Ward's method, a current standard clustering approach, in classifying the neurons into 4 subtypes. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits. PMID:24348339

  1. 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.

  2. 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...

  3. 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.

  4. 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.)

  5. Pap-smear Benchmark Data For Pattern Classification

    DEFF Research Database (Denmark)

    Jantzen, Jan; Norup, Jonas; Dounias, Georgios

    2005-01-01

    includes scatter plots and linear classification results, in order to provide domain knowledge and lower bounds on the acceptable performance of future classifiers. Students and researchers can access the database on the Internet, and use it to test and compare their own classification methods.......This case study provides data and a baseline for comparing classification methods. The data consists of 917 images of Pap-smear cells, classified carefully by cyto-technicians and doctors. Each cell is described by 20 numerical features, and the cells fall into 7 classes. A basic data analysis...

  6. 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...

  7. 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.

  8. 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

  9. Classification of extraterrestrial civilizations

    Science.gov (United States)

    Tang, Tong B.; Chang, Grace

    1991-06-01

    A scheme of classification of extraterrestrial intelligence (ETI) communities based on the scope of energy accessible to the civilization in question is proposed as an alternative to the Kardeshev (1964) scheme that includes three types of civilization, as determined by their levels of energy expenditure. The proposed scheme includes six classes: (1) a civilization that runs essentially on energy exerted by individual beings or by domesticated lower life forms, (2) harnessing of natural sources on planetary surface with artificial constructions, like water wheels and wind sails, (3) energy from fossils and fissionable isotopes, mined beneath the planet surface, (4) exploitation of nuclear fusion on a large scale, whether on the planet, in space, or from primary solar energy, (5) extensive use of antimatter for energy storage, and (6) energy from spacetime, perhaps via the action of naked singularities.

  10. 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.

  11. Nursing interventions classification (NIC).

    Science.gov (United States)

    Bulechek, G M; McCloskey, J C

    1995-01-01

    The Nursing Interventions Classification (NIC) is the first comprehensive classification of treatments that nurses perform. It is a standardized language of both nurse-initiated and physician-initiated nursing treatments. An alphabetical listing of 336 interventions was published in a book in May 1992 [Iowa Intervention Project, McCloskey, J. C., & Bulechek, G. M. (eds). Nursing Interventions Classification (NIC). St. Louis: Mosby-Year Book]. Each NIC intervention is composed of a label, a definition, a set of activities that a nurse does to carry out the intervention, and a short list of background readings. NIC interventions include: the physiological (e.g., Acid-Base Management, Airway Suctioning, Pressure Ulcer Care) and the psychosocial (e.g., Anxiety Reduction, Preparatory Sensory Information, Home Maintenance Assistance); illness treatment (e.g., Hyperglycemia Management, Ostomy Care, Shock Management), illness prevention (e.g., Fall Prevention, Infection Protection, Immunization/Vaccination Administration), and health promotion (e.g., Exercise Promotion, Nutrition Management, Smoking Cessation Assistance); and those used for individuals and those for families (e.g., Family Integrity Promotion, Family Support). Most recently, indirect care interventions (e.g., Emergency Cart Checking, Supply Management) have been developed. Research methods used to develop the classification include content analysis, expert survey, focus group review, similarity analysis, and hierarchical cluster analysis. The research, conducted by a large team of investigators at the University of Iowa and supported by the National Institute of Nursing Research, is ongoing. Since the 1992 publication, approximately 50 additional interventions have been developed, a taxonomic structure has been constructed and validated, a feedback and review system has been established and implemented, NIC interventions have been linked to nursing diagnoses, and five clinical agencies are serving as field

  12. 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

  13. A support vector machine approach for classification of welding defects from ultrasonic signals

    Science.gov (United States)

    Chen, Yuan; Ma, Hong-Wei; Zhang, Guang-Ming

    2014-07-01

    Defect classification is an important issue in ultrasonic non-destructive evaluation. A layered multi-class support vector machine (LMSVM) classification system, which combines multiple SVM classifiers through a layered architecture, is proposed in this paper. The proposed LMSVM classification system is applied to the classification of welding defects from ultrasonic test signals. The measured ultrasonic defect echo signals are first decomposed into wavelet coefficients by the wavelet packet transform. The energy of the wavelet coefficients at different frequency channels are used to construct the feature vectors. The bees algorithm (BA) is then used for feature selection and SVM parameter optimisation for the LMSVM classification system. The BA-based feature selection optimises the energy feature vectors. The optimised feature vectors are input to the LMSVM classification system for training and testing. Experimental results of classifying welding defects demonstrate that the proposed technique is highly robust, precise and reliable for ultrasonic defect classification.

  14. Robotic Rock Classification

    Science.gov (United States)

    Hebert, Martial

    1999-01-01

    This report describes a three-month research program undertook jointly by the Robotics Institute at Carnegie Mellon University and Ames Research Center as part of the Ames' Joint Research Initiative (JRI.) The work was conducted at the Ames Research Center by Mr. Liam Pedersen, a graduate student in the CMU Ph.D. program in Robotics under the supervision Dr. Ted Roush at the Space Science Division of the Ames Research Center from May 15 1999 to August 15, 1999. Dr. Martial Hebert is Mr. Pedersen's research adviser at CMU and is Principal Investigator of this Grant. The goal of this project is to investigate and implement methods suitable for a robotic rover to autonomously identify rocks and minerals in its vicinity, and to statistically characterize the local geological environment. Although primary sensors for these tasks are a reflection spectrometer and color camera, the goal is to create a framework under which data from multiple sensors, and multiple readings on the same object, can be combined in a principled manner. Furthermore, it is envisioned that knowledge of the local area, either a priori or gathered by the robot, will be used to improve classification accuracy. The key results obtained during this project are: The continuation of the development of a rock classifier; development of theoretical statistical methods; development of methods for evaluating and selecting sensors; and experimentation with data mining techniques on the Ames spectral library. The results of this work are being applied at CMU, in particular in the context of the Winter 99 Antarctica expedition in which the classification techniques will be used on the Nomad robot. Conversely, the software developed based on those techniques will continue to be made available to NASA Ames and the data collected from the Nomad experiments will also be made available.

  15. Automatic document classification of biological literature

    Directory of Open Access Journals (Sweden)

    Sternberg Paul W

    2006-08-01

    Full Text Available Abstract Background Document classification is a wide-spread problem with many applications, from organizing search engine snippets to spam filtering. We previously described Textpresso, a text-mining system for biological literature, which marks up full text according to a shallow ontology that includes terms of biological interest. This project investigates document classification in the context of biological literature, making use of the Textpresso markup of a corpus of Caenorhabditis elegans literature. Results We present a two-step text categorization algorithm to classify a corpus of C. elegans papers. Our classification method first uses a support vector machine-trained classifier, followed by a novel, phrase-based clustering algorithm. This clustering step autonomously creates cluster labels that are descriptive and understandable by humans. This clustering engine performed better on a standard test-set (Reuters 21578 compared to previously published results (F-value of 0.55 vs. 0.49, while producing cluster descriptions that appear more useful. A web interface allows researchers to quickly navigate through the hierarchy and look for documents that belong to a specific concept. Conclusion We have demonstrated a simple method to classify biological documents that embodies an improvement over current methods. While the classification results are currently optimized for Caenorhabditis elegans papers by human-created rules, the classification engine can be adapted to different types of documents. We have demonstrated this by presenting a web interface that allows researchers to quickly navigate through the hierarchy and look for documents that belong to a specific concept.

  16. Unsupervised Classification of MESSENGER MASC Data

    Science.gov (United States)

    de Sanctis, M. Cristina; Capaccioni, Fabrizio; Filacchione, Gianrico; Ammannito, Eleonora

    2010-05-01

    The MESSENGER spacecraft flew by Mercury as part of its journey to Mercury orbit insertion. The Mercury At-mospheric and Surface Composition Spectrometer (MASCS) observed Mercury during the first two flybys, includ-ing high-spatial-and spectral-resolution visible to near-infrared (IR) spectra of the Mercury surface. The Visible and InfraRed Spectrograph (VIRS) component of MASCS consists of two linear photodiode arrays covering a spectral range 320-1450 nm. We applied classification method to MASCS data in order to extract information on the mineralogy of Mercury. The classification of the Messenger data will permit to obtain maps of Mercury surface, giving us indication of the different mineralogy and maturity present on the Hermean surface. The data were pre-processed applying photometric correction and the VIS and NIR data were collected in a single spectrum. The data set show very similar featureless spectra. The main differences are in the reflectance levels and in the spectral slopes. To emphasize the spectral differences we have normalized the spectra to an average reflectance spectrum for each flyby. This allows to point out variation of different regions with respect to the aver-age spectral behaviour. Two different approaches have been used to analyze MASCS data of the two Messenger flybys: ISODATA unsupervised classification and a classification based on three different spectral slopes (in the wavelengths' ranges 0.3-0.55, 0.55-0.8 and 0.95-1.49 µm). The identified classes shows differences linked with slopes and reflectance's level: the proposed methods allows to correlate the most important classes with different morphological features on Mercury's surface which differ for weathering, maturity and composition. Our analysis is done in order to test and verify these classification methods that shall be necessary to analyze similar data harvested by SIMBIO-SYS/VIHI (Visible and Infrared Hyper-spectral Imager) aboard the future ESA's BepiColombo mission

  17. Information analysis of a spatial database for ecological land classification

    Science.gov (United States)

    Davis, Frank W.; Dozier, Jeff

    1990-01-01

    An ecological land classification was developed for a complex region in southern California using geographic information system techniques of map overlay and contingency table analysis. Land classes were identified by mutual information analysis of vegetation pattern in relation to other mapped environmental variables. The analysis was weakened by map errors, especially errors in the digital elevation data. Nevertheless, the resulting land classification was ecologically reasonable and performed well when tested with higher quality data from the region.

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

    OpenAIRE

    Kammoun, M.; Cassar-malek, I.; Meunier, B; Picard, B.

    2014-01-01

    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 c...

  19. 15 CFR 2008.9 - Classification guides.

    Science.gov (United States)

    2010-01-01

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

  20. 32 CFR 2400.15 - Classification guides.

    Science.gov (United States)

    2010-07-01

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

  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... INFORMATION Classified Information § 7.26 Derivative classification. (a) Derivative classification is defined... classification guides. (c) Persons who apply derivative classification markings shall observe original...

  2. 12 CFR 403.4 - Derivative classification.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Derivative classification. 403.4 Section 403.4... 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...

  3. 46 CFR 503.55 - Derivative classification.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 9 2010-10-01 2010-10-01 false Derivative classification. 503.55 Section 503.55... Security Program § 503.55 Derivative classification. (a) In accordance with Part 2 of Executive Order 12958... derivative classification. (1) Derivative classification includes the classification of information based on...

  4. 45 CFR 601.5 - Derivative classification.

    Science.gov (United States)

    2010-10-01

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

  5. 5 CFR 1312.7 - Derivative classification.

    Science.gov (United States)

    2010-01-01

    ... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Derivative classification. 1312.7 Section... Declassification of National Security Information § 1312.7 Derivative classification. A derivative classification... another agency or classification authority. The application of derivative classification markings is the...

  6. Arteriosclerosis: rethinking the current classification.

    Science.gov (United States)

    Fishbein, Gregory A; Fishbein, Michael C

    2009-08-01

    Arteriosclerosis is the vascular disease that is the leading cause of mortality in industrialized countries. Currently, there are 3 lesions within the broader category of arteriosclerosis: atherosclerosis, Mönckeberg medial calcific sclerosis, and arteriolosclerosis. In this review, we discuss the history of the terminology and current classification of arteriosclerosis and problems with the current classification. We also discuss recently described new arterial lesions that are not in the current classification. In spite of the prevalence and importance of arteriosclerotic vascular disease, and the widespread use of the current terminology, there are major problems with the current classification: (1) the current classification has an inconsistent naming convention, (2) the classification fails to use terms that accurately describe the lesions, and (3) important arterial lesions are absent from the classification. In addition, although the terms arteriosclerosis and atherosclerosis describe different lesions, these terms are often used interchangeably. Consideration should be given for a new more inclusive and accurate classification of "arteriosclerotic" lesions that more accurately reflects the pathology of these important vascular lesions.

  7. Pulsed-flow air classification for waste to energy production. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Peirce, J.J.; Vesilind, P.A.

    1983-09-30

    The development and testing of pulsed-flow air classification for waste-to-energy production are discussed. Standard designs generally permit large amounts of combustible material to escape as reject while producing a fuel that is high in metal and glass contaminants. Pulsed-flow classification is presented as a concept which can avoid both pitfalls. Each aspect of theory and laboratory testing is summarized: particle characteristics, theory of pulsed-flow classification, laboratory testing, and pulsed-flow air classification for waste-to-energy production. Conclusions from the research are summarized.

  8. [Classification of viruses by computer].

    Science.gov (United States)

    Ageeva, O N; Andzhaparidze, O G; Kibardin, V M; Nazarova, G M; Pleteneva, E A

    1982-01-01

    The study used the information mass containing information on 83 viruses characterized by 41 markers. The suitability of one of the variants of cluster analysis for virus classification was demonstrated. It was established that certain stages of automatic allotment of viruses into groups by the degree of similarity of their properties end the formation of groups which consist of viruses sufficiently close to each other by their properties and are sufficiently isolated. Comparison of these groups with the classification proposed by the ICVT established their correspondence to individual families. Analysis of the obtained classification system permits sufficiently grounded conclusions to be drawn with regard to the classification position of certain viruses, the classification of which has not yet been completed by the ICVT.

  9. 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...... 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...

  10. 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...... 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...

  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...... 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 indicated group differences in user classification and related task performances differences. The main implications of the study were that (a) the edit distance appears a useful measure in cross-country HCI research and practice...

  12. New classification of Herlyn-Werner-Wunderlich syndrome.

    Science.gov (United States)

    Zhu, Lan; Chen, Na; Tong, Jia-Li; Wang, Wei; Zhang, Lei; Lang, Jing-He

    2015-01-20

    Uterus didelphys and blind hemivagina associated with ipsilateral renal agenesis are collectively known as Herlyn-Werner-Wunderlich syndrome (HWWS). In the literature, the syndrome often appears as a single case report or as a small series. In our study, we reviewed the characteristics of all HWWS patients at Peking Union Medical College Hospital (PUMCH) and suggested a new classification for this syndrome because the clinical characteristics differed significantly between the completely and incompletely obstructed vaginal septum. This new classification allows for earlier diagnosis and treatment. From January 1986 to March 2013, all diagnosed cases of HWWS at PUMCH were reviewed. A retrospective long-term follow-up study of the clinical presentation, surgical prognosis, and pregnancy outcomes was performed. Statistical analyses were performed using SPSS, version 15.0 (IBM, Armonk, NY, USA). Between-group comparisons were performed using the χ2 test, Fisher's exact test, and the t-test. The significance level for all analyses was set at P syndrome be classified by the complete or incomplete obstruction of the hemivagina as follows: Classification 1, a completely obstructed hemivagina and Classification 2, an incompletely obstructed hemivagina. The clinical details associated with these two types are distinctly different. HWWS patients should be differentiated according to these two classifications. The two classifications could be generalized by gynecologists world-wide.

  13. Some Basic Elements in Clustering and Classification

    Science.gov (United States)

    Grégoire, G.

    2016-05-01

    This chapter deals with basic tools useful in clustering and classification and present some commonly used approaches for these two problems. Since several chapters in these proceedings are devoted to approaches to deal with classification, we give more attention in this chapter to clustering issues. We are first concerned with notions of distances or dissimilarities between objects we are to group in clusters. Then based on these inter-objects distances we define distances between sets of objects, such as single linkage, complete linkage or Ward distance. Three clustering algorithms are presented with some details and compared: Kmeans, Ascendant Hierarchical and DBSCAN algorithms. The comparison between partitions and the issue of choosing the correct number of clusters are investigated and the proposed procedures are tested on two data sets. We emphasize the fact that the results provided by the numerous indices available in the literature for selecting the number of clusters is largely depending upon the shape and the dispersion we are assuming for these clusters. Finally the last section is devoted to classification. Some basic notions such as training sets, test sets and cross-validation are discussed. Two particular approaches are detailed, the K-nearest neighbors method and the logistic regression, and comparisons with LDA (Linear Discriminant Analysis) and QDA (Quadratic Discriminant Analysis) are analyzed.

  14. 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  <  0.01), leading to overoptimistic results (10% up to 30% relative increase in AUC). We observed that this effect is manifest regardless of the choice of diffusion index, specifically fractional anisotropy and mean diffusivity. Secondly, we performed a test on an independent mixed cohort consisting of 119 ADNI scans; thus, we evaluated the 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.

  15. A comparative classification of coal reactivity

    Energy Technology Data Exchange (ETDEWEB)

    Zolin, A.; Jensen, A.; Storm Pedersen, L. [Technical Univ. Lyngby (Denmark). Dept. of Chemical Engineering; Toerslev Jensen, P.; Dam-Johansen, K. [Elsam I/S, Fredericia (Denmark)

    1997-12-31

    Based on thermogravimetric analysis (TGA) tests, a qualitative reactivity classification of nine different coals ranking from subbituminous to low volatile bituminous with respect to one coal, Cerrejon, is presented. The classification agrees well with a corresponding one obtained from another study by entrained flow reactor (EFR) experiments. Two Southern Hemisphere coals (Australia), however, showed a higher reactivity with respect to the Northern Hemisphere coal Cerrejon (Colombia) in the low temperature TGA experiments. It appears that TGA can provide a simple means for determining a fuel reactivity classification that may be applied to full scale suspension fired plants. The combustion behaviour of the Cerrejon coals was investigated at different temperatures and oxygen concentrations to determine the activation energy and reaction order. In addition, TGA tests revealed that for this coal, increasing values of the heat treatment temperature and holding time during pyrolysis result in lower char reactivities. This is attributed to the severity of the pyrolysis process and thereby the influence of thermal annealing effects. (orig.)

  16. 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 %....

  17. Advances in metals classification under the United Nations globally harmonized system of classification and labeling.

    Science.gov (United States)

    Skeaff, James; Adams, William J; Rodriguez, Patricio; Brouwers, Tony; Waeterschoot, Hugo

    2011-10-01

    This article shows how regulatory obligations mandated for metal substances can be met with a laboratory-based transformation/dissolution (T/D) method for deriving relevant hazard classification outcomes, which can then be linked to attendant environmental protection management decisions. We report the results of a ring-test at 3 laboratories conducted to determine the interlaboratory precision of the United Nations T/D Protocol (T/DP) in generating data for classifying 4 metal-bearing substances for acute and chronic toxicity under the United Nations Globally Harmonized System of Classification and Labelling (GHS) criteria with respect to the aquatic environment. The test substances were Ni metal powder, cuprous oxide (Cu(2) O) powder, tricobalt tetroxide (Co(3) O(4) ) powder, and cuttings of a NILO K Ni-Co-Fe alloy. Following GHS Annex 10 guidelines, we tested 3 loadings (1, 10, and 100 mg/L) of each substance at pH 6 and 8 for 7 or 28 d to yield T/D data for acute and chronic classification, respectively. We compared the T/DP results (dissolved metal in aqueous media) against acute and chronic ecotoxicity reference values (ERVs) for each substance to assess GHS classification outcomes. For dissolved metal ions, the respective acute and chronic ERVs established at the time of the T/D testing were: 29 and 8 µg/L for Cu; 185 and 1.5 µg/L for Co; and 13.3 and 1.0 mg/L for Fe. The acute ERVs for Ni were pH-dependent: 120 and 68 µg/L at pH 6 and 8, respectively, whereas the chronic ERV for Ni was 2.4 µg/L. The acute classification outcomes were consistent among 3 laboratories: cuprous oxide, Acute 1; Ni metal powder, Acute 3; Co(3) O(4) and the NILO K alloy, no classification. We obtained similar consistent results in chronic classifications: Cu(2) O, Ni metal powder, and Co(3) O(4) , Chronic 4; and the NILO K alloy, no classification. However, we observed equivocal results only in 2 of a possible 48 cases where the coefficient of variation of final T

  18. Classification systems in Gestational trophoblastic neoplasia - Sentiment or evidenced based?

    Science.gov (United States)

    Parker, V L; Pacey, A A; Palmer, J E; Tidy, J A; Winter, M C; Hancock, B W

    2017-05-01

    The classification system for Gestational trophoblastic neoplasia (GTN) has proved a controversial topic for over 100years. Numerous systems simultaneously existed in different countries, with three main rival classifications gaining popularity, namely histological, anatomical and clinical prognostic systems. Until 2000, prior to the combination of the FIGO and WHO classifications, there was no worldwide consensus on the optimal classification system, largely due to a lack of high quality data proving the merit of one system over another. Remarkably, a validated, prospectively tested classification system is yet to be conducted. Over time, increasing criticisms have emerged regarding the currently adopted combined FIGO/WHO classification system, and its ability to identify patients most likely to develop primary chemotherapy resistance or disease relapse. This is particularly pertinent for patients with low-risk disease, whereby one in three patients are resistant to first line therapy, rising to four out of five women who score 5 or 6. This review aims to examine the historical basis of the GTN classification systems and critically appraise the evidence on which they were based. This culminates in a critique of the current FIGO/WHO prognostic system and discussion surrounding clinical preference versus evidence based practice. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Weighted data gravitation classification for standard and imbalanced data.

    Science.gov (United States)

    Cano, Alberto; Zafra, Amelia; Ventura, Sebastián

    2013-12-01

    Gravitation is a fundamental interaction whose concept and effects applied to data classification become a novel data classification technique. The simple principle of data gravitation classification (DGC) is to classify data samples by comparing the gravitation between different classes. However, the calculation of gravitation is not a trivial problem due to the different relevance of data attributes for distance computation, the presence of noisy or irrelevant attributes, and the class imbalance problem. This paper presents a gravitation-based classification algorithm which improves previous gravitation models and overcomes some of their issues. The proposed algorithm, called DGC+, employs a matrix of weights to describe the importance of each attribute in the classification of each class, which is used to weight the distance between data samples. It improves the classification performance by considering both global and local data information, especially in decision boundaries. The proposal is evaluated and compared to other well-known instance-based classification techniques, on 35 standard and 44 imbalanced data sets. The results obtained from these experiments show the great performance of the proposed gravitation model, and they are validated using several nonparametric statistical tests.

  20. Geographical classification of Chilean wines by an electronic nose

    Directory of Open Access Journals (Sweden)

    Nicolás H Beltrán

    2009-08-01

    Full Text Available Nicolás H Beltrán, Manuel A Duarte-Mermoud, Ricardo E MuñozDepartment of Electrical Engineering, University of Chile, Santiago, ChileAbstract: This paper discusses the classification of Chilean wines by geographical origin based only on aroma information. The varieties of Cabernet Sauvignon, Merlot, and Carménère analyzed here are produced in four different valleys in the central part of Chile (Colchagua, Maipo, Maule, and Rapel. Aroma information was obtained with a zNoseTM (fast gas chromatograph and the data was analyzed by applying wavelet transform for feature extraction followed by an analysis with support vector machines for classification. Two evaluations of the classification technique were performed; the average percentage of correct classification performed on the validation set was obtained by means of cross-validation against the percentage of correct classification obtained on the test set. This developed technique obtained results on classification rates over 94% in both cases. The geographical origin of a Chilean wine can be resolved rapidly with fast gas chromatography and data processing.Keywords: geographical origin, origin denomination, wine classification, pattern recognition, support vector machines, wavelet analysis, feature extraction

  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. DESCRIPTION OF CLASSIFICATION SYSTEMS OF LIBRARY CATALOGUES

    Directory of Open Access Journals (Sweden)

    Zoya V. Savchenko

    2010-08-01

    Full Text Available The description of the most widespread universal library classifications (Decimal Classification of D'yui (DKD, Universal Decimal Classification (UDK, Classification of Library of Congress (KBK, Library-Bibliographic Classification (BBK are analysed in the article. Histories of these systems development and features of their use in modern informative services as well as the example of construction of electronic library classifiers on the base of the library classifications of DKD and KBK are given.

  3. DESCRIPTION OF CLASSIFICATION SYSTEMS OF LIBRARY CATALOGUES

    OpenAIRE

    Zoya V. Savchenko

    2010-01-01

    The description of the most widespread universal library classifications (Decimal Classification of D'yui (DKD), Universal Decimal Classification (UDK), Classification of Library of Congress (KBK), Library-Bibliographic Classification (BBK)) are analysed in the article. Histories of these systems development and features of their use in modern informative services as well as the example of construction of electronic library classifiers on the base of the library classifications of DKD and KBK...

  4. Image classification using eigenpaxels

    Science.gov (United States)

    McGuire, Peter Frederick

    The intelligent control of robotic is a major limiting factor in the utilization of current robotic technology. Although the technology to accurately position robotic manipulators is well developed, practical applications are often limited by the controller's ability to interact with a complex environment. Central to this plight is the integration of sensory signals, such as vision, into the control structure. Recently, a number of promising approaches to visual information processing have been developed using artificial neural networks (ANNs). These approaches, however, are often tailored to particular applications and are therefore disparate and limited in scope. In contrast, biological neural networks perform a wide range of visual tasks yet this behavior arises from a single integrated neural structure. The work presented in this thesis details a biologically inspired image processing algorithm and its application to an image classification problem. Based on the organization of cells in the primary visual cortex of primates, this algorithm utilizes key neural mechanisms to produce efficient representations of images. Dubbed the "eigenpaxel" algorithm, excellent results are obtained despite the relative simplicity of the method. In addition, the relationship between the algorithm and biological vision may help to shed light on the processing occurring within the brain and the basis of the organization found therein.

  5. Supervised DNA Barcodes species classification: analysis, comparisons and results.

    Science.gov (United States)

    Weitschek, Emanuel; Fiscon, Giulia; Felici, Giovanni

    2014-04-11

    Specific fragments, coming from short portions of DNA (e.g., mitochondrial, nuclear, and plastid sequences), have been defined as DNA Barcode and can be used as markers for organisms of the main life kingdoms. Species classification with DNA Barcode sequences has been proven effective on different organisms. Indeed, specific gene regions have been identified as Barcode: COI in animals, rbcL and matK in plants, and ITS in fungi. The classification problem assigns an unknown specimen to a known species by analyzing its Barcode. This task has to be supported with reliable methods and algorithms. In this work the efficacy of supervised machine learning methods to classify species with DNA Barcode sequences is shown. The Weka software suite, which includes a collection of supervised classification methods, is adopted to address the task of DNA Barcode analysis. Classifier families are tested on synthetic and empirical datasets belonging to the animal, fungus, and plant kingdoms. In particular, the function-based method Support Vector Machines (SVM), the rule-based RIPPER, the decision tree C4.5, and the Naïve Bayes method are considered. Additionally, the classification results are compared with respect to ad-hoc and well-established DNA Barcode classification methods. A software that converts the DNA Barcode FASTA sequences to the Weka format is released, to adapt different input formats and to allow the execution of the classification procedure. The analysis of results on synthetic and real datasets shows that SVM and Naïve Bayes outperform on average the other considered classifiers, although they do not provide a human interpretable classification model. Rule-based methods have slightly inferior classification performances, but deliver the species specific positions and nucleotide assignments. On synthetic data the supervised machine learning methods obtain superior classification performances with respect to the traditional DNA Barcode classification methods. On

  6. Comparison between different papillary recession classification systems

    Directory of Open Access Journals (Sweden)

    Li-Ching Chang

    2012-12-01

    Conclusion: This study confirmed a significant correlation between the two existing classification methods. The proposed PR classification system characterizes open embrasures in greater detail than previous systems.

  7. 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.

  8. Target Decomposition Techniques & Role of Classification Methods for Landcover Classification

    Science.gov (United States)

    Singh, Dharmendra; Mittal, Gunjan

    Target decomposition techniques aims at analyzing the received scattering matrix from polari-metric data to extract information about the scattering processes. Incoherent techniques have been modeled in recent years for providing more general approach for decomposition of natural targets. Therefore, there is a need to study and critically analyze the developing models for their suitability in classification of land covers. Moreover, the classification methods used for the segmentation of various landcovers from the decomposition techniques need to be examined as the appropriate selection of these methods affect the performance of the decomposition tech-niques for landcover classification. Therefore in the present paper, it is attempted to check the performance of various model based and an eigen vector based decomposition techniques for decomposition of Polarimetric PALSAR (Phased array type L band SAR) data. Few generic supervised classifiers were used for classification of decomposed images into three broad classes of water, urban and agriculture lands. For the purpose, algorithms had been applied twice on pre-processed PALSAR raw data once on spatial averaged (mean filtering on 33 window) data and the other on data, multilooked in azimuth direction by six looks and then filtered using Wishart Gamma MAP on 55 window. Classification of the decomposed images from each of the methods had been done using four supervised classifiers (parallelepiped, minimum distance, Mahalanobis and maximum likelihood). Ground truth data generated with the help of ground survey points, topographic sheet and google earth was used for the computation of classification accuracy. Parallelepiped classifier gave better classification accuracy of water class for all the models excluding H/A/Alpha. Minimum distance classifier gave better classification results for urban class. Maximum likelihood classifier performed well as compared to other classifiers for classification of vegetation class

  9. 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.

  10. A Novel Vehicle Classification Using Embedded Strain Gauge Sensors.

    Science.gov (United States)

    Zhang, Wenbin; Wang, Qi; Suo, Chunguang

    2008-11-05

    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 the results of a single sensor data, which is trained on the whole

  11. 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

  12. 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

    , 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......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...

  13. Automatic classification of human sperm head morphology.

    Science.gov (United States)

    Chang, Violeta; Heutte, Laurent; Petitjean, Caroline; Härtel, Steffen; Hitschfeld, Nancy

    2017-05-01

    Infertility is a problem that affects up to 15% of couples worldwide with emotional and physiological implications and semen analysis is the first step in the evaluation of an infertile couple. Indeed the morphology of human sperm cells is considered to be a clinical tool dedicated to the fertility prognosis and serves, mainly, for making decisions regarding the options of assisted reproduction technologies. Therefore, a complete analysis of not only normal sperm but also abnormal sperm turns out to be critical in this context. This paper sets out to develop, implement and calibrate a novel methodology to characterize and classify sperm heads towards morphological sperm analysis. Our work is aimed at focusing on a depth analysis of abnormal sperm heads for fertility diagnosis, prognosis, reproductive toxicology, basic research or public health studies. We introduce a morphological characterization for human sperm heads based on shape measures. We also present a pipeline for sperm head classification, according to the last Laboratory Manual for the Examination and Processing of Human Semen of the World Health Organization (WHO). In this sense, we propose a two-stage classification scheme that permits to classify sperm heads among five different classes (one class for normal sperm heads and four classes for abnormal sperm heads) combining an ensemble strategy for feature selection and a cascade approach with several support vector machines dedicated to the verification of each class. We use Fisher's exact test to demonstrate that there is no statistically significant differences between our results and those achieved by domain experts. Experimental evaluation shows that our two-stage classification scheme outperforms some state-of-the-art monolithic classifiers, exhibiting 58% of average accuracy. More interestingly, on the subset of data for which there is a total agreement between experts for the label of the samples, our system is able to provide 73% of average

  14. Digital image colorization based on distance transformation

    Science.gov (United States)

    Lagodzinski, Przemyslaw; Smolka, Bogdan

    2008-01-01

    Colorization is a term introduced by W. Markle1 to describe a computerized process for adding color to black and white pictures, movies or TV programs. The task involves replacing a scalar value stored at each pixel of the gray scale image by a vector in a three dimensional color space with luminance, saturation and hue or simply RGB. Since different colors may carry the same luminance value but vary in hue and/or saturation, the problem of colorization has no inherently "correct" solution. Due to these ambiguities, human interaction usually plays a large role. In this paper we present a novel colorization method that takes advantage of the morphological distance transformation, changes of neighboring pixel intensities and gradients to propagate the color within the gray scale image. The proposed method frees the user of segmenting the image, as color is provided simply by scribbles which are next automatically propagated within the image. The effectiveness of the algorithm allows the user to work interactively and to obtain the desired results promptly after providing the color scribbles. In the paper we show that the proposed method allows for high quality colorization results for still images.

  15. 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.

  16. 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.

  17. Breast density classification to reduce false positives in CADe systems.

    Science.gov (United States)

    Vállez, Noelia; Bueno, Gloria; Déniz, Oscar; Dorado, Julián; Seoane, José Antonio; Pazos, Alejandro; Pastor, Carlos

    2014-02-01

    This paper describes a novel weighted voting tree classification scheme for breast density classification. Breast parenchymal density is an important risk factor in breast cancer. Moreover, it is known that mammogram interpretation is more difficult when dense tissue is involved. Therefore, automated breast density classification may aid in breast lesion detection and analysis. Several classification methods have been compared and a novel hierarchical classification procedure of combined classifiers with linear discriminant analysis (LDA) is proposed as the best solution to classify the mammograms into the four BIRADS tissue classes. The classification scheme is based on 298 texture features. Statistical analysis to test the normality and homoscedasticity of the data was carried out for feature selection. Thus, only features that are influenced by the tissue type were considered. The novel classification techniques have been incorporated into a CADe system to drive the detection algorithms and tested with 1459 images. The results obtained on the 322 screen-film mammograms (SFM) of the mini-MIAS dataset show that 99.75% of samples were correctly classified. On the 1137 full-field digital mammograms (FFDM) dataset results show 91.58% agreement. The results of the lesion detection algorithms were obtained from modules integrated within the CADe system developed by the authors and show that using breast tissue classification prior to lesion detection leads to an improvement of the detection results. The tools enhance the detectability of lesions and they are able to distinguish their local attenuation without local tissue density constraints. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  18. Accurate molecular classification of cancer using simple rules

    Directory of Open Access Journals (Sweden)

    Gotoh Osamu

    2009-10-01

    Full Text Available Abstract Background One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often hampers the interpretability of the models. For a better understanding of the classification results, it is desirable to develop simpler rule-based models with as few marker genes as possible. Methods We screened a small number of informative single genes and gene pairs on the basis of their depended degrees proposed in rough sets. Applying the decision rules induced by the selected genes or gene pairs, we constructed cancer classifiers. We tested the efficacy of the classifiers by leave-one-out cross-validation (LOOCV of training sets and classification of independent test sets. Results We applied our methods to five cancerous gene expression datasets: leukemia (acute lymphoblastic leukemia [ALL] vs. acute myeloid leukemia [AML], lung cancer, prostate cancer, breast cancer, and leukemia (ALL vs. mixed-lineage leukemia [MLL] vs. AML. Accurate classification outcomes were obtained by utilizing just one or two genes. Some genes that correlated closely with the pathogenesis of relevant cancers were identified. In terms of both classification performance and algorithm simplicity, our approach outperformed or at least matched existing methods. Conclusion In cancerous gene expression datasets, a small number of genes, even one or two if selected correctly, is capable of achieving an ideal cancer classification effect. This finding also means that very simple rules may perform well for cancerous class prediction.

  19. 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.

  20. 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...

  1. Classification of spacetimes with symmetry

    Science.gov (United States)

    Hicks, Jesse W.

    Spacetimes with symmetry play a critical role in Einstein's Theory of General Relativity. Missing from the literature is a correct, usable, and computer accessible classification of such spacetimes. This dissertation fills this gap; specifically, we. i) give a new and different approach to the classification of spacetimes with symmetry using modern methods and tools such as the Schmidt method and computer algebra systems, resulting in ninety-two spacetimes; ii) create digital databases of the classification for easy access and use for researchers; iii) create software to classify any spacetime metric with symmetry against the new database; iv) compare results of our classification with those of Petrov and find that Petrov missed six cases and incorrectly normalized a significant number of metrics; v) classify spacetimes with symmetry in the book Exact Solutions to Einstein's Field Equations Second Edition by Stephani, Kramer, Macallum, Hoenselaers, and Herlt and in Komrakov's paper Einstein-Maxwell equation on four-dimensional homogeneous spaces using the new software.

  2. 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...

  3. 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.

  4. [Definition and classification of epilepsy].

    Science.gov (United States)

    Jibiki, Itsuki

    2014-05-01

    The concept or definition of epilepsy was mentioned as a chronic disease of the brain consisting of repetitions of EEG paroxysm and clinical seizures caused by excessive discharges of the cerebral neurons, in reference with Gastaut's opinion and the other statements. Further, we referred to diseases to be excluded from epilepsy such as isolated, occasional and subclinical seizures and so on. Next, new classifications of seizures and epilepsies were explained on the basis of revised terminology and concepts for organization of seizures and epilepsies in Report of the ILAE Communication in Classification and Terminology, 2005-09, in comparison with the Classification of Epileptic Seizures in 1981 and the Classification of Epilepsies and Epileptic Syndromes in 1989.

  5. SCOPE - Stellar Classification Online Public Exploration

    Science.gov (United States)

    Harenberg, Steven

    2010-01-01

    The Astronomical Photographic Data Archive (APDA) has been established to be the primary North American archive for the collections of astronomical photographic plates. Located at the Pisgah Astronomical Research Institute (PARI) in Rosman, NC, the archive contains hundreds of thousands stellar spectra, many of which have never before been classified. To help classify the vast number of stars, the public is invited to participate in a distributed computing online environment called Stellar Classification Online - Public Exploration (SCOPE). Through a website, the participants will have a tutorial on stellar spectra and practice classifying. After practice, the participants classify spectra on photographic plates uploaded online from APDA. These classifications will be recorded in a database where the results from many users will be statistically analyzed. Stars with known spectral types will be included to test the reliability of classifications. The process of building the database of stars from APDA, which the citizen scientist will be able to classify, includes: scanning the photographic plates, orienting the plate to correct for the change in right ascension/declination using Aladin, stellar HD catalog identification using Simbad, marking the boundaries for each spectrum, and setting up the image for use on the website. We will describe the details of this process.

  6. Texture classification of lung computed tomography images

    Science.gov (United States)

    Pheng, Hang See; Shamsuddin, Siti M.

    2013-03-01

    Current development of algorithms in computer-aided diagnosis (CAD) scheme is growing rapidly to assist the radiologist in medical image interpretation. Texture analysis of computed tomography (CT) scans is one of important preliminary stage in the computerized detection system and classification for lung cancer. Among different types of images features analysis, Haralick texture with variety of statistical measures has been used widely in image texture description. The extraction of texture feature values is essential to be used by a CAD especially in classification of the normal and abnormal tissue on the cross sectional CT images. This paper aims to compare experimental results using texture extraction and different machine leaning methods in the classification normal and abnormal tissues through lung CT images. The machine learning methods involve in this assessment are Artificial Immune Recognition System (AIRS), Naive Bayes, Decision Tree (J48) and Backpropagation Neural Network. AIRS is found to provide high accuracy (99.2%) and sensitivity (98.0%) in the assessment. For experiments and testing purpose, publicly available datasets in the Reference Image Database to Evaluate Therapy Response (RIDER) are used as study cases.

  7. Meta-classification for Variable Stars

    Science.gov (United States)

    Pichara, Karim; Protopapas, Pavlos; León, Daniel

    2016-03-01

    The need for the development of automatic tools to explore astronomical databases has been recognized since the inception of CCDs and modern computers. Astronomers already have developed solutions to tackle several science problems, such as automatic classification of stellar objects, outlier detection, and globular clusters identification, among others. New scientific problems emerge, and it is critical to be able to reuse the models learned before, without rebuilding everything from the beginning when the sciencientific problem changes. In this paper, we propose a new meta-model that automatically integrates existing classification models of variable stars. The proposed meta-model incorporates existing models that are trained in a different context, answering different questions and using different representations of data. A conventional mixture of expert algorithms in machine learning literature cannot be used since each expert (model) uses different inputs. We also consider the computational complexity of the model by using the most expensive models only when it is necessary. We test our model with EROS-2 and MACHO data sets, and we show that we solve most of the classification challenges only by training a meta-model to learn how to integrate the previous experts.

  8. Spectral feature classification and spatial pattern recognition

    Science.gov (United States)

    Sivertson, W. E., Jr.; Wilson, R. G.

    1979-01-01

    This paper introduces a spatial pattern recognition processing concept involving the use of spectral feature classification technology and coherent optical correlation. The concept defines a hybrid image processing system incorporating both digital and optical technology. The hybrid instrument provides simplified pseudopattern images as functions of pixel classification from information embedded within a real-scene image. These pseudoimages become simplified inputs to an optical correlator for use in a subsequent pattern identification decision useful in executing landmark pointing, tracking, or navigating functions. Real-time classification is proposed as a research tool for exploring ways to enhance input signal-to-noise ratio as an aid in improving optical correlation. The approach can be explored with developing technology, including a current NASA Langley Research Center technology plan that involves a series of related Shuttle-borne experiments. A first-planned experiment, Feature Identification and Location Experiment (FILE), is undergoing final ground testing, and is scheduled for flight on the NASA Shuttle (STS2/flight OSTA-1) in 1980. FILE will evaluate a technique for autonomously classifying earth features into the four categories: bare land; water; vegetation; and clouds, snow, or ice.

  9. 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).

  10. Toward a systematic classification of textile damages.

    Science.gov (United States)

    Schulman, T G; Samlal-Soedhoe, R S; van der Weerd, J

    2018-01-01

    The accuracy of textile damage analyses was evaluated by laboratory tests carried out by trained experts. The analyzed damages were prepared by various methods, including stabbing, cutting, shooting, heating/burning, etc. A number of damages were aged by household washing and tumble-drying procedures, addition of blood, or burying. The samples were analyzed by routine laboratory evaluation. The results indicate that the properties of a damage provide a good indication of the way a textile had been damaged. Nevertheless, scoring of the answers is not straightforward. Results indicated that examiners evaluated damages on different levels of specificity and thereby showed the latent need for a more systematic approach to damage classification. The second part of the current contribution therefore presents the classification scheme we developed. This classification scheme aims to guide examiners during examination and accommodates the vast majority of textile damages observed in forensic casework. Each of the proposed classes is defined, relevant literature in each of the classes is reviewed, and the characteristics that can be expected after different damaging actions are explained. Finally, we share some ideas for further investigations. Copyright © 2018 Central Police University.

  11. Deep learning for brain tumor classification

    Science.gov (United States)

    Paul, Justin S.; Plassard, Andrew J.; Landman, Bennett A.; Fabbri, Daniel

    2017-03-01

    Recent research has shown that deep learning methods have performed well on supervised machine learning, image classification tasks. The purpose of this study is to apply deep learning methods to classify brain images with different tumor types: meningioma, glioma, and pituitary. A dataset was publicly released containing 3,064 T1-weighted contrast enhanced MRI (CE-MRI) brain images from 233 patients with either meningioma, glioma, or pituitary tumors split across axial, coronal, or sagittal planes. This research focuses on the 989 axial images from 191 patients in order to avoid confusing the neural networks with three different planes containing the same diagnosis. Two types of neural networks were used in classification: fully connected and convolutional neural networks. Within these two categories, further tests were computed via the augmentation of the original 512×512 axial images. Training neural networks over the axial data has proven to be accurate in its classifications with an average five-fold cross validation of 91.43% on the best trained neural network. This result demonstrates that a more general method (i.e. deep learning) can outperform specialized methods that require image dilation and ring-forming subregions on tumors.

  12. Auditory free classification of nonnative speech.

    Science.gov (United States)

    Atagi, Eriko; Bent, Tessa

    2013-11-01

    Through experience with speech variability, listeners build categories of indexical speech characteristics including categories for talker, gender, and dialect. The auditory free classification task-a task in which listeners freely group talkers based on audio samples-has been a useful tool for examining listeners' representations of some of these characteristics including regional dialects and different languages. The free classification task was employed in the current study to examine the perceptual representation of nonnative speech. The category structure and salient perceptual dimensions of nonnative speech were investigated from two perspectives: general similarity and perceived native language background. Talker intelligibility and whether native talkers were included were manipulated to test stimulus set effects. Results showed that degree of accent was a highly salient feature of nonnative speech for classification based on general similarity and on perceived native language background. This salience, however, was attenuated when listeners were listening to highly intelligible stimuli and attending to the talkers' native language backgrounds. These results suggest that the context in which nonnative speech stimuli are presented-such as the listeners' attention to the talkers' native language and the variability of stimulus intelligibility-can influence listeners' perceptual organization of nonnative speech.

  13. Nominated Texture Based Cervical Cancer Classification

    Directory of Open Access Journals (Sweden)

    Edwin Jayasingh Mariarputham

    2015-01-01

    Full Text Available Accurate classification of Pap smear images becomes the challenging task in medical image processing. This can be improved in two ways. One way is by selecting suitable well defined specific features and the other is by selecting the best classifier. This paper presents a nominated texture based cervical cancer (NTCC classification system which classifies the Pap smear images into any one of the seven classes. This can be achieved by extracting well defined texture features and selecting best classifier. Seven sets of texture features (24 features are extracted which include relative size of nucleus and cytoplasm, dynamic range and first four moments of intensities of nucleus and cytoplasm, relative displacement of nucleus within the cytoplasm, gray level cooccurrence matrix, local binary pattern histogram, tamura features, and edge orientation histogram. Few types of support vector machine (SVM and neural network (NN classifiers are used for the classification. The performance of the NTCC algorithm is tested and compared to other algorithms on public image database of Herlev University Hospital, Denmark, with 917 Pap smear images. The output of SVM is found to be best for the most of the classes and better results for the remaining classes.

  14. Gene expression based cancer classification

    OpenAIRE

    Sara Tarek; Reda Abd Elwahab; Mahmoud Shoman

    2017-01-01

    Cancer classification based on molecular level investigation has gained the interest of researches as it provides a systematic, accurate and objective diagnosis for different cancer types. Several recent researches have been studying the problem of cancer classification using data mining methods, machine learning algorithms and statistical methods to reach an efficient analysis for gene expression profiles. Studying the characteristics of thousands of genes simultaneously offered a deep in...

  15. 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

  16. Patient-specific ECG beat classification technique.

    Science.gov (United States)

    Das, Manab K; Ari, Samit

    2014-09-01

    Electrocardiogram (ECG) beat classification plays an important role in the timely diagnosis of the critical heart condition. An automated diagnostic system is proposed to classify five types of ECG classes, namely normal (N), ventricular ectopic beat (V), supra ventricular ectopic beat (S), fusion (F) and unknown (Q) as recommended by the Association for the Advancement of Medical Instrumentation (AAMI). The proposed method integrates the Stockwell transform (ST), a bacteria foraging optimisation (BFO) algorithm and a least mean square (LMS)-based multiclass support vector machine (SVM) classifier. The ST is utilised to extract the important morphological features which are concatenated with four timing features. The resultant combined feature vector is optimised by removing the redundant and irrelevant features using the BFO algorithm. The optimised feature vector is applied to the LMS-based multiclass SVM classifier for automated diagnosis. In the proposed technique, the LMS algorithm is used to modify the Lagrange multiplier, which in turn modifies the weight vector to minimise the classification error. The updated weights are used during the testing phase to classify ECG beats. The classification performances are evaluated using the MIT-BIH arrhythmia database. Average accuracy and sensitivity performances of the proposed system for V detection are 98.6% and 91.7%, respectively, and for S detections, 98.2% and 74.7%, respectively over the entire database. To generalise the capability, the classification performance is also evaluated using the St. Petersburg Institute of Cardiological Technics (INCART) database. The proposed technique performs better than other reported heartbeat techniques, with results suggesting better generalisation capability.

  17. 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.

  18. 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

  19. 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 derived...... 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 (Kruskal–Wallis rank test, P

  20. [Diabetes mellitus: definition, classification and diagnosis].

    Science.gov (United States)

    Roden, Michael

    2016-04-01

    Diabetes mellitus comprises of a group of heterogeneous disorders, which have an increase in blood glucose concentrations in common. The current classifications for diabetes mellitus type 1-4 are described and the main features of type 1 and type 2 diabetes are compared to allow for better discrimination between these diabetes types. Furthermore, the criteria for the correct biochemical diagnosis during fasting and oral glucose tolerance tests as well as the use of hemoglobin A1c (HbA1c) are summarized. These data form the basis of the recommendations of the Austrian Diabetes Association for the clinical praxis of diabetes treatment.

  1. [Diabetes mellitus--definition, classification and diagnosis].

    Science.gov (United States)

    Roden, Michael

    2004-01-01

    Diabetes mellitus comprises of a group of heterogeneous disorders which have an increase in blood glucose concentrations in common. The current classifications for diabetes mellitus type 1-4 are described and the main features of type 1 and type 2 diabetes are compared to allow for better discrimination between these diabetes types. Furthermore, the criteria for the correct biochemical diagnosis during fasting and during oral glucose tolerance tests are summarized. These data form the basis of the recommendations of the Austrian Diabetes Association for the clinical practice in diabetes.

  2. 32 CFR 644.426 - Classification.

    Science.gov (United States)

    2010-07-01

    ... HANDBOOK Disposal Disposal of Fee-Owned Real Property and Easement Interests § 644.426 Classification... classification will be recorded on ENG Form 1825 (Real Property Classification), with sufficient information to justify the classification. Surplus property may be reclassified from time to time whenever such action is...

  3. 32 CFR 2400.6 - Classification levels.

    Science.gov (United States)

    2010-07-01

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

  4. 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...

  5. 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...

  6. 32 CFR 2001.15 - Classification guides.

    Science.gov (United States)

    2010-07-01

    .... (b) General content of classification guides. Classification guides shall, at a minimum: (1) Identify... 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...

  7. 28 CFR 17.26 - Derivative classification.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Derivative classification. 17.26 Section... ACCESS TO CLASSIFIED INFORMATION Classified Information § 17.26 Derivative classification. (a) Persons... documents or classification guides. (b) Persons who apply derivative classification markings shall observe...

  8. A new classification of developmental language disorders (DLD).

    Science.gov (United States)

    Korkman, M; Häkkinen-Rihu, P

    1994-07-01

    Eighty children with DLD were examined with 18 language tests, mainly derived from a neuropsychological investigation called NEPSY (NEuroPSYchological Investigation for Children). The children were 6-0 to 7-9 years old and attended kindergarten. The test profiles of the first 40 children, Group 1, were utilized for the elaboration of a classification of DLD. The test profiles were grouped into five subgroups with the aid of a Q-type factor analysis. Then the classification was modified to suit clinical application by collapsing two pairs of subgroups. The resulting categories were called: the Global Subtype, the Specific Dyspraxia Subtype, and the Specific Comprehension Subtype. The classification was validated, first, by a follow-up study. It was predicted that spelling problems would occur in the Global and the Specific Comprehension Subtypes, but not in the Specific Dyspraxia Subtype. At follow-up, 3 years later, the hit rate was found to be 80.5%. In a second validation procedure, the classification was tried out on the 40 children examined later, Group 2. The coverage of the classification was 85%. Five outliers (12.5%) seemed to form a fourth category, called the Specific Dysnomia Subtype. An expressive subtype was not observed.

  9. Superiority of Classification Tree versus Cluster, Fuzzy and Discriminant Models in a Heartbeat Classification System.

    Science.gov (United States)

    Krasteva, Vessela; Jekova, Irena; Leber, Remo; Schmid, Ramun; Abächerli, Roger

    2015-01-01

    This study presents a 2-stage heartbeat classifier of supraventricular (SVB) and ventricular (VB) beats. Stage 1 makes computationally-efficient classification of SVB-beats, using simple correlation threshold criterion for finding close match with a predominant normal (reference) beat template. The non-matched beats are next subjected to measurement of 20 basic features, tracking the beat and reference template morphology and RR-variability for subsequent refined classification in SVB or VB-class by Stage 2. Four linear classifiers are compared: cluster, fuzzy, linear discriminant analysis (LDA) and classification tree (CT), all subjected to iterative training for selection of the optimal feature space among extended 210-sized set, embodying interactive second-order effects between 20 independent features. The optimization process minimizes at equal weight the false positives in SVB-class and false negatives in VB-class. The training with European ST-T, AHA, MIT-BIH Supraventricular Arrhythmia databases found the best performance settings of all classification models: Cluster (30 features), Fuzzy (72 features), LDA (142 coefficients), CT (221 decision nodes) with top-3 best scored features: normalized current RR-interval, higher/lower frequency content ratio, beat-to-template correlation. Unbiased test-validation with MIT-BIH Arrhythmia database rates the classifiers in descending order of their specificity for SVB-class: CT (99.9%), LDA (99.6%), Cluster (99.5%), Fuzzy (99.4%); sensitivity for ventricular ectopic beats as part from VB-class (commonly reported in published beat-classification studies): CT (96.7%), Fuzzy (94.4%), LDA (94.2%), Cluster (92.4%); positive predictivity: CT (99.2%), Cluster (93.6%), LDA (93.0%), Fuzzy (92.4%). CT has superior accuracy by 0.3-6.8% points, with the advantage for easy model complexity configuration by pruning the tree consisted of easy interpretable 'if-then' rules.

  10. Superiority of Classification Tree versus Cluster, Fuzzy and Discriminant Models in a Heartbeat Classification System.

    Directory of Open Access Journals (Sweden)

    Vessela Krasteva

    Full Text Available This study presents a 2-stage heartbeat classifier of supraventricular (SVB and ventricular (VB beats. Stage 1 makes computationally-efficient classification of SVB-beats, using simple correlation threshold criterion for finding close match with a predominant normal (reference beat template. The non-matched beats are next subjected to measurement of 20 basic features, tracking the beat and reference template morphology and RR-variability for subsequent refined classification in SVB or VB-class by Stage 2. Four linear classifiers are compared: cluster, fuzzy, linear discriminant analysis (LDA and classification tree (CT, all subjected to iterative training for selection of the optimal feature space among extended 210-sized set, embodying interactive second-order effects between 20 independent features. The optimization process minimizes at equal weight the false positives in SVB-class and false negatives in VB-class. The training with European ST-T, AHA, MIT-BIH Supraventricular Arrhythmia databases found the best performance settings of all classification models: Cluster (30 features, Fuzzy (72 features, LDA (142 coefficients, CT (221 decision nodes with top-3 best scored features: normalized current RR-interval, higher/lower frequency content ratio, beat-to-template correlation. Unbiased test-validation with MIT-BIH Arrhythmia database rates the classifiers in descending order of their specificity for SVB-class: CT (99.9%, LDA (99.6%, Cluster (99.5%, Fuzzy (99.4%; sensitivity for ventricular ectopic beats as part from VB-class (commonly reported in published beat-classification studies: CT (96.7%, Fuzzy (94.4%, LDA (94.2%, Cluster (92.4%; positive predictivity: CT (99.2%, Cluster (93.6%, LDA (93.0%, Fuzzy (92.4%. CT has superior accuracy by 0.3-6.8% points, with the advantage for easy model complexity configuration by pruning the tree consisted of easy interpretable 'if-then' rules.

  11. Genetic programming and serial processing for time series classification.

    Science.gov (United States)

    Alfaro-Cid, Eva; Sharman, Ken; Esparcia-Alcázar, Anna I

    2014-01-01

    This work describes an approach devised by the authors for time series classification. In our approach genetic programming is used in combination with a serial processing of data, where the last output is the result of the classification. The use of genetic programming for classification, although still a field where more research in needed, is not new. However, the application of genetic programming to classification tasks is normally done by considering the input data as a feature vector. That is, to the best of our knowledge, there are not examples in the genetic programming literature of approaches where the time series data are processed serially and the last output is considered as the classification result. The serial processing approach presented here fills a gap in the existing literature. This approach was tested in three different problems. Two of them are real world problems whose data were gathered for online or conference competitions. As there are published results of these two problems this gives us the chance to compare the performance of our approach against top performing methods. The serial processing of data in combination with genetic programming obtained competitive results in both competitions, showing its potential for solving time series classification problems. The main advantage of our serial processing approach is that it can easily handle very large datasets.

  12. 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.

  13. A comparison of methods for three-class mammograms classification.

    Science.gov (United States)

    Milosevic, Marina; Jovanovic, Zeljko; Jankovic, Dragan

    2017-08-09

    Mammography is considered the gold standard for early breast cancer detection but it is very difficult to interpret mammograms for many reason. Computer aided diagnosis (CAD) is an important development that may help to improve the performance in breast cancer detection. We present a CAD system based on feature extraction techniques for detecting abnormal patterns in digital mammograms. Computed features based on gray-level co-occurrence matrices (GLCM) are used to evaluate the effectiveness of textural information possessed by mass regions. A total of 20 texture features are extracted from each mammogram. The ability of feature set in differentiating normal, benign and malign tissue is investigated using a Support Vector Machine (SVM) classifier, Naive Bayes classifier and K-Nearest Neighbor (k-NN) classifier. The efficiency of classification is provided using cross-validation technique. Support Vector Machine was originally designed for binary classification. We constructed a three-class SVM classifier by combining two binary classifiers and then compared his performance with classifiers intended for multi-class classification. To evaluate the classification performance, confusion matrix and Receiver Operating Characteristic (ROC) analysis were performed. Obtained results indicate that SVM classification results are better than the k-NN and Naive Bayes classification results, with accuracy ratio of 65% according to 51.6% and 38.1%, respectively.The unbalanced classification that occurs in all three classification tests is reason for unsatisfactory accuracy. Obtained experimental results indicate that the proposed three-class SVM classifier is more suitable for practical use than the other two methods.

  14. A HMM text classification model with learning capacity

    Directory of Open Access Journals (Sweden)

    Eva L. IGLESIAS

    2015-05-01

    Full Text Available In this paper a method of classifying biomedical text documents based on Hidden Markov Model is proposed and evaluated. The method is integrated into a framework named BioClass. Bioclass is composed of intelligent text classification tools and facilitates the comparison between them because it has several views of the results. The main goal is to propose a more effective based-on content classifier than current methods in this environment To test the effectiveness of the classifier presented, a set of experiments performed on the OSHUMED corpus are preseted. Our model is tested adding it learning capacity and without it, and it is compared with other classification techniques. The results suggest that the adaptive HMM model is indeed more suitable for document classification.

  15. Entanglement classification with algebraic geometry

    Science.gov (United States)

    Sanz, M.; Braak, D.; Solano, E.; Egusquiza, I. L.

    2017-05-01

    We approach multipartite entanglement classification in the symmetric subspace in terms of algebraic geometry, its natural language. We show that the class of symmetric separable states has the structure of a Veronese variety and that its k-secant varieties are SLOCC invariants. Thus SLOCC classes gather naturally into families. This classification presents useful properties such as a linear growth of the number of families with the number of particles, and nesting, i.e. upward consistency of the classification. We attach physical meaning to this classification through the required interaction length of parent Hamiltonians. We show that the states W N and GHZ N are in the same secant family and that, effectively, the former can be obtained in a limit from the latter. This limit is understood in terms of tangents, leading to a refinement of the previous families. We compute explicitly the classification of symmetric states with N≤slant4 qubits in terms of both secant families and its refinement using tangents. This paves the way to further use of projective varieties in algebraic geometry to solve open problems in entanglement theory.

  16. 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.

  17. Biomarker Selection and Classification of “-Omics” Data Using a Two-Step Bayes Classification Framework

    Directory of Open Access Journals (Sweden)

    Anunchai Assawamakin

    2013-01-01

    Full Text Available Identification of suitable biomarkers for accurate prediction of phenotypic outcomes is a goal for personalized medicine. However, current machine learning approaches are either too complex or perform poorly. Here, a novel two-step machine-learning framework is presented to address this need. First, a Naïve Bayes estimator is used to rank features from which the top-ranked will most likely contain the most informative features for prediction of the underlying biological classes. The top-ranked features are then used in a Hidden Naïve Bayes classifier to construct a classification prediction model from these filtered attributes. In order to obtain the minimum set of the most informative biomarkers, the bottom-ranked features are successively removed from the Naïve Bayes-filtered feature list one at a time, and the classification accuracy of the Hidden Naïve Bayes classifier is checked for each pruned feature set. The performance of the proposed two-step Bayes classification framework was tested on different types of -omics datasets including gene expression microarray, single nucleotide polymorphism microarray (SNParray, and surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF proteomic data. The proposed two-step Bayes classification framework was equal to and, in some cases, outperformed other classification methods in terms of prediction accuracy, minimum number of classification markers, and computational time.

  18. 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.

  19. Familial filicide and filicide classification.

    Science.gov (United States)

    Guileyardo, J M; Prahlow, J A; Barnard, J J

    1999-09-01

    Filicide is the killing of a child by his or her parent. Despite the disturbing nature of these crimes, a study of filicide classification can provide insight into their causes. Furthermore, a study of filicide classification provides information essential to accurate death certification. We report a rare case of familial filicide in which twin sisters both attempted to kill their respective children. We then suggest a detailed classification of filicide subtypes that provides a framework of motives and precipitating factors leading to filicide. We identify 16 subtypes of filicide, each of which is sufficiently characteristic to warrant a separate category. We describe in some detail the characteristic features of these subtypes. A knowledge of filicide subtypes contributes to interpretation of difficult cases. Furthermore, to protect potential child homicide victims, it is necessary to know how and why they are killed. Epidemiologic studies using filicide subtypes as their basis could provide information leading to strategies for prevention.

  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. Classification systems for stalking behavior.

    Science.gov (United States)

    Racine, Christopher; Billick, Stephen

    2014-01-01

    Stalking is a complex behavioral phenomenon that is unique in that it necessarily involves a prolonged dyadic relationship between both a perpetrator and a victim. Since criminalization of stalking behavior in the 1990s, different conceptual typologies have attempted to classify this behavior to assess risk and aid in management decisions. The authors reviewed the current literature regarding the most recent and accepted stalking classification systems. The three predominant stalker typologies currently in use include Zona's stalker-victim types, Mullen's stalker typology, and the RECON stalker typology. Of these, the RECON classification system alone was developed in an attempt to separate stalkers into groups based on previously known risk factors for behaviorally based phenomenon such as propensity for violence. Understanding and simplifying these classification systems may enhance the potential that new research will lead to evidence-based management and treatment strategies in the stalking situation. © 2013 American Academy of Forensic Sciences.

  2. 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.

  3. Influence of Speckle Filtering on Polarimetric SAR Data Classification

    Science.gov (United States)

    Shitole, Sanjay; Rao, Y. S.; Mohan, B. Krishna

    2013-08-01

    PolSAR data without speckle reduction provide insufficient accuracy for the segmentation and classification. Fully Polarimetric ALOS PALSAR and Radarsat-2 data acquired over Mumbai, India are used to test the effect of speckle filtering on the classification. Wishart supervised classifier algorithm is used for classification of the filtered and unfiltered data. Boxcar, Refined Lee, Lopez, IDAN, Improved Sigma and newly introduced Sequential Filter are analysed for improvement of classification accuracy. Selection of the most suitable moving window size of speckle reducing algorithms is an important step during speckle filtering. Boxcar and Refined Lee filters are used to test the effect of speckle filtering on classification with varying moving window size of the filter. Boxcar filter has a good noise smoothing capability. Speckle in the image can be minimized by increasing size of scanning window in the process of speckle reduction. However, this undiscriminating averaging using Boxcar filter causes a resolution loss in the vicinity of sharp edges and point targets in the image. As the edges in the image need to be maintained, well known Kohonens Self-Organizing Feature Map (SOFM) is used for this purpose.

  4. A skull stripping method using deformable surface and tissue classification

    Science.gov (United States)

    Tao, Xiaodong; Chang, Ming-Ching

    2010-03-01

    Many neuroimaging applications require an initial step of skull stripping to extract the cerebrum, cerebellum, and brain stem. We approach this problem by combining deformable surface models and a fuzzy tissue classification technique. Our assumption is that contrast exists between brain tissue (gray matter and white matter) and cerebrospinal fluid, which separates the brain from the extra-cranial tissue. We first analyze the intensity of the entire image to find an approximate centroid of the brain and initialize an ellipsoidal surface around it. We then perform a fuzzy tissue classification with bias field correction within the surface. Tissue classification and bias field are extrapolated to the entire image. The surface iteratively deforms under a force field computed from the tissue classification and the surface smoothness. Because of the bias field correction and tissue classification, the proposed algorithm depends less on particular imaging contrast and is robust to inhomogeneous intensity often observed in magnetic resonance images. We tested the algorithm on all T1 weighted images in the OASIS database, which includes skull stripping results using Brain Extraction Tool; the Dice scores have an average of 0.948 with a standard deviation of 0.017, indicating a high degree of agreement. The algorithm takes on average 2 minutes to run on a typical PC and produces a brain mask and membership functions for gray matter, white matter, and cerebrospinal fluid. We also tested the algorithm on T2 images to demonstrate its generality, where the same algorithm without parameter adjustment gives satisfactory results.

  5. Concept-based semi-automatic classification of drugs.

    Science.gov (United States)

    Gurulingappa, Harsha; Kolárik, Corinna; Hofmann-Apitius, Martin; Fluck, Juliane

    2009-08-01

    The anatomical therapeutic chemical (ATC) classification system maintained by the World Health Organization provides a global standard for the classification of medical substances and serves as a source for drug repurposing research. Nevertheless, it lacks several drugs that are major players in the global drug market. In order to establish classifications for yet unclassified drugs, this paper presents a newly developed approach based on a combination of information extraction (IE) and machine learning (ML) techniques. Most of the information about drugs is published in the scientific articles. Therefore, an IE-based framework is employed to extract terms from free text that express drug's chemical, pharmacological, therapeutic, and systemic effects. The extracted terms are used as features within a ML framework to predict putative ATC class labels for unclassified drugs. The system was tested on a portion of ATC containing drugs with an indication on the cardiovascular system. The class prediction turned out to be successful with the best predictive accuracy of 89.47% validated by a 100-fold bootstrapping of the training set and an accuracy of 77.12% on an independent test set. The presented concept-based classification system outperformed state-of-the-art classification methods based on chemical structure properties.

  6. Thermal bioaerosol cloud tracking with Bayesian classification

    Science.gov (United States)

    Smith, Christian W.; Dupuis, Julia R.; Schundler, Elizabeth C.; Marinelli, William J.

    2017-05-01

    The development of a wide area, bioaerosol early warning capability employing existing uncooled thermal imaging systems used for persistent perimeter surveillance is discussed. The capability exploits thermal imagers with other available data streams including meteorological data and employs a recursive Bayesian classifier to detect, track, and classify observed thermal objects with attributes consistent with a bioaerosol plume. Target detection is achieved based on similarity to a phenomenological model which predicts the scene-dependent thermal signature of bioaerosol plumes. Change detection in thermal sensor data is combined with local meteorological data to locate targets with the appropriate thermal characteristics. Target motion is tracked utilizing a Kalman filter and nearly constant velocity motion model for cloud state estimation. Track management is performed using a logic-based upkeep system, and data association is accomplished using a combinatorial optimization technique. Bioaerosol threat classification is determined using a recursive Bayesian classifier to quantify the threat probability of each tracked object. The classifier can accept additional inputs from visible imagers, acoustic sensors, and point biological sensors to improve classification confidence. This capability was successfully demonstrated for bioaerosol simulant releases during field testing at Dugway Proving Grounds. Standoff detection at a range of 700m was achieved for as little as 500g of anthrax simulant. Developmental test results will be reviewed for a range of simulant releases, and future development and transition plans for the bioaerosol early warning platform will be discussed.

  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. 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.

  9. 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.

  10. 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.

  11. Is classification necessary after Google?

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2012-01-01

    . Such decisions are considered to be dependent on the purpose and values inherent in the specific classification process. These decisions are not independent of theories and values in the document being classified, but are dependent on an interpretation of the discourses within those documents. Findings...... and purposes. Evidence-based practice provides an example of the importance of classifying documents according to research methods. Originality/value – Solving both the practical (organisational) and the theoretical problems facing classification is necessary if the field is to survive both as a practice...... and as an academic subject within library and information science. This article presents strategies designed to tackle these challenges....

  12. 78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-09-09

    ...) The average price paid to producers for cotton from the 2012 crop was 72.05 cents per pound, making a 500 pound bale of cotton worth an average of $360.25. The current user fee for futures classification...-Doxey data to verify that submitted bales meet more restrictive quality requirements and age parameters...

  13. 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.

  14. The Relationship of Skills of Elite Wheelchair Basketball Competitors to the International Functional Classification System.

    Science.gov (United States)

    Brasile, Frank M.; Hedrick, Bradley N.

    1996-01-01

    This study investigated the relationship between skill performance levels of 31 elite male wheelchair basketball players and their international player classification level. Analysis of a skills test of each athlete indicated that there is a need to reevaluate the functional classification system used in wheelchair basketball competitions. (SM)

  15. Classification and diagnosis of acute isolated syndesmotic injuries: ESSKA-AFAS consensus and guidelines

    NARCIS (Netherlands)

    van Dijk, C. Niek; Longo, Umile Giuseppe; Loppini, Mattia; Florio, Pino; Maltese, Ludovica; Ciuffreda, Mauro; Denaro, Vincenzo

    2016-01-01

    The aim of the present study was to perform a systematic review of the current classification systems, and the clinical and radiological tests for the acute isolated syndesmotic injuries to identify the best method of classification and diagnosis allowing the surgeon to choose the appropriate

  16. [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.

  17. 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.

  18. Taxonomic Classification of Asteroids via Broadband Near-Infrared Photometry

    NARCIS (Netherlands)

    Petersen, Eric; Thomas, C.; Trilling, D.; Emery, J.; Delbo, M.; Mueller, M.; Dave, R.

    2010-01-01

    For faint asteroids, it is not practical to obtain near-infrared spectra. However, it may be possible to use broadband photometry to infer spectral classifications and study composition. As a test of this, we processed SpeX near-infrared asteroid spectral data to simulate colors that would be

  19. Landsat TM Classifications For SAFIS Using FIA Field Plots

    Science.gov (United States)

    William H. Cooke; Andrew J. Hartsell

    2001-01-01

    Wall-to-wall Landsat Thematic Mapper (TM) classification efforts in Georgia require field validation. We developed a new crown modeling procedure based on Forest Health Monitoring (FHM) data to test Forest Inventory and Analysis (FIA) data. These models simulate the proportion of tree crowns that reflect light on a FIA subplot basis. We averaged subplot crown...

  20. An intelligent temporal pattern classification system using fuzzy ...

    Indian Academy of Sciences (India)

    The main focus of experimental analysis is with heart and diabetic data sets. In addition to that, some other data sets from the UCI Machine Learning Repository Data Set such as Glass,. Wine and PID are used to test the classification accuracy and the number of rules generated by. TFMM-PSO system. The medical dataset ...

  1. 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,

  2. Logical Rules and the Classification of Integral-Dimension Stimuli

    Science.gov (United States)

    Little, Daniel R.; Nosofsky, Robert M.; Donkin, Christopher; Denton, Stephen E.

    2013-01-01

    A classic distinction in perceptual information processing is whether stimuli are composed of separable dimensions, which are highly analyzable, or integral dimensions, which are processed holistically. Previous tests of a set of logical-rule models of classification have shown that separable-dimension stimuli are processed serially if the…

  3. Physical fitness classification standards for polish early education ...

    African Journals Online (AJOL)

    Physical fitness classification standards for polish early education teachers. ... South African Journal for Research in Sport, Physical Education and Recreation ... This study determined the general fitness level of female early education teachers (EETs) (N=217) based on fitness test standards, and compared the results with ...

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

    African Journals Online (AJOL)

    Background/purpose The aim of the study was to present our clinical experience with the laparoscopic approach in patients with nonpalpable testes (NPTs) and review the literature on laparoscopic classifications. Materials and methods Between May 2010 and August 2012, 30 boys with NPT (mean age 3.9 years) ...

  5. Detection of Acanthamoeba on the ocular surface in a Spanish population using the Schirmer strip test: pathogenic potential, molecular classification and evaluation of the sensitivity to chlorhexidine and voriconazole of the isolated Acanthamoeba strains.

    Science.gov (United States)

    Rocha-Cabrera, Pedro; Reyes-Batlle, María; Martín-Navarro, Carmen María; Dorta-Gorrín, Alexis; López-Arencibia, Atteneri; Sifaoui, Ines; Martínez-Carretero, Enrique; Piñero, José E; Martín-Barrera, Fernando; Valladares, Basilio; Lorenzo-Morales, Jacob

    2015-08-01

    Pathogenic strains of Acanthamoeba are causative agents of a sight-threatening infection of the cornea known as Acanthamoeba keratitis, which is often associated with the misuse of contact lenses. However, there is still a question remaining to be answered, which is whether these micro-organisms are present on the ocular surface of healthy individuals. Therefore, the aim of this study was to determine the presence of Acanthamoeba on the ocular surface in healthy patients and also in those with other ocular surface infections. Sterile Schirmer test strips were used to collect samples from a group of patients who attended an ophthalmology consultation at the Hospital del Norte, Icod de los Vinos, Tenerife, Canary Islands. Most of the patients (46 individuals, 79.31  %) presented ocular surface pathologies such as blepharitis or conjunctivitis; the rest did not present any pathology. None of the patients included in the study wore contact lenses. The collected samples were cultured in 2  % non-nutrient agar plates and positive plates were then cultured in axenic conditions for further analyses. Molecular analysis classified all isolated strains as belonging to Acanthamoeba genotype tbl4, and osmotolerance and thermotolerance assays revealed that all strains were potentially pathogenic. Furthermore, all strains were assayed for sensitivity against voriconazole and chlorhexidine. Assays showed that both drugs were active against the tested strains. In conclusion, the Schirmer strip test is proposed as an effective tool for the detection of Acanthamoeba on the ocular surface.

  6. Matched-pair classification

    Energy Technology Data Exchange (ETDEWEB)

    Theiler, James P [Los Alamos National Laboratory

    2009-01-01

    Following an analogous distinction in statistical hypothesis testing, we investigate variants of machine learning where the training set comes in matched pairs. We demonstrate that even conventional classifiers can exhibit improved performance when the input data has a matched-pair structure. Online algorithms, in particular, converge quicker when the data is presented in pairs. In some scenarios (such as the weak signal detection problem), matched pairs can be generated from independent samples, with the effect not only doubling the nominal size of the training set, but of providing the structure that leads to better learning. A family of 'dipole' algorithms is introduced that explicitly takes advantage of matched-pair structure in the input data and leads to further performance gains. Finally, we illustrate the application of matched-pair learning to chemical plume detection in hyperspectral imagery.

  7. 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.

  8. Expert Reliability for the World Health Organization Standardized Ultrasound Classification of Cystic Echinococcosis.

    Science.gov (United States)

    Solomon, Nadia; Fields, Paul J; Tamarozzi, Francesca; Brunetti, Enrico; Macpherson, Calum N L

    2017-03-01

    AbstractCystic echinococcosis (CE), a parasitic zoonosis, results in cyst formation in the viscera. Cyst morphology depends on developmental stage. In 2003, the World Health Organization (WHO) published a standardized ultrasound (US) classification for CE, for use among experts as a standard of comparison. This study examined the reliability of this classification. Eleven international CE and US experts completed an assessment of eight WHO classification images and 88 test images representing cyst stages. Inter- and intraobserver reliability and observer performance were assessed using Fleiss' and Cohen's kappa. Interobserver reliability was moderate for WHO images (κ = 0.600, P classification for each image were significant for WHO (0.413 classification, with substantial to almost perfect interobserver reliability for pathognomonic stages. This confirms experts' abilities to reliably identify WHO-defined pathognomonic signs of CE, demonstrating that the WHO classification provides a reproducible way of staging CE.

  9. Fast deterministic algorithm for EEE components classification

    Science.gov (United States)

    Kazakovtsev, L. A.; Antamoshkin, A. N.; Masich, I. S.

    2015-10-01

    Authors consider the problem of automatic classification of the electronic, electrical and electromechanical (EEE) components based on results of the test control. Electronic components of the same type used in a high- quality unit must be produced as a single production batch from a single batch of the raw materials. Data of the test control are used for splitting a shipped lot of the components into several classes representing the production batches. Methods such as k-means++ clustering or evolutionary algorithms combine local search and random search heuristics. The proposed fast algorithm returns a unique result for each data set. The result is comparatively precise. If the data processing is performed by the customer of the EEE components, this feature of the algorithm allows easy checking of the results by a producer or supplier.

  10. New Classification of Herlyn-Werner-Wunderlich Syndrome

    Directory of Open Access Journals (Sweden)

    Lan Zhu

    2015-01-01

    Full Text Available Background: Uterus didelphys and blind hemivagina associated with ipsilateral renal agenesis are collectively known as Herlyn-Werner-Wunderlich syndrome (HWWS. In the literature, the syndrome often appears as a single case report or as a small series. In our study, we reviewed the characteristics of all HWWS patients at Peking Union Medical College Hospital (PUMCH and suggested a new classification for this syndrome because the clinical characteristics differed significantly between the completely and incompletely obstructed vaginal septum. This new classification allows for earlier diagnosis and treatment. Methods: From January 1986 to March 2013, all diagnosed cases of HWWS at PUMCH were reviewed. A retrospective long-term follow-up study of the clinical presentation, surgical prognosis, and pregnancy outcomes was performed. Statistical analyses were performed using SPSS, version 15.0 (IBM, Armonk, NY, USA. Between-group comparisons were performed using the χ2 test, Fisher′s exact test, and the t-test. The significance level for all analyses was set at P < 0.05. Results: The clinical data from 79 patients with HWWS were analyzed until March 31, 2013. According to our newly identified characteristics, we recommend that the syndrome be classified by the complete or incomplete obstruction of the hemivagina as follows: Classification 1, a completely obstructed hemivagina and Classification 2, an incompletely obstructed hemivagina. The clinical details associated with these two types are distinctly different. Conclusions: HWWS patients should be differentiated according to these two classifications. The two classifications could be generalized by gynecologists world-wide.

  11. 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

  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. Petrov classification: An elementary approach

    Energy Technology Data Exchange (ETDEWEB)

    Kalotas, T.M.; Eliezer, C.J.

    1983-01-01

    We reduce the length of the usual algebraic classification scheme of the Weyl tensor by avoiding the step centered around its reduction to canonical form. Instead the different algebraic types are established more economically via the elementary approach of constructing explicit examples.

  14. Classification using Bayesian neural nets

    NARCIS (Netherlands)

    J.C. Bioch (Cor); O. van der Meer; R. Potharst (Rob)

    1995-01-01

    textabstractRecently, Bayesian methods have been proposed for neural networks to solve regression and classification problems. These methods claim to overcome some difficulties encountered in the standard approach such as overfitting. However, an implementation of the full Bayesian approach to

  15. Galaxy Classifications with Deep Learning

    Science.gov (United States)

    Lukic, Vesna; Brüggen, Marcus

    2017-06-01

    Machine learning techniques have proven to be increasingly useful in astronomical applications over the last few years, for example in object classification, estimating redshifts and data mining. One example of object classification is classifying galaxy morphology. This is a tedious task to do manually, especially as the datasets become larger with surveys that have a broader and deeper search-space. The Kaggle Galaxy Zoo competition presented the challenge of writing an algorithm to find the probability that a galaxy belongs in a particular class, based on SDSS optical spectroscopy data. The use of convolutional neural networks (convnets), proved to be a popular solution to the problem, as they have also produced unprecedented classification accuracies in other image databases such as the database of handwritten digits (MNIST †) and large database of images (CIFAR ‡). We experiment with the convnets that comprised the winning solution, but using broad classifications. The effect of changing the number of layers is explored, as well as using a different activation function, to help in developing an intuition of how the networks function and to see how they can be applied to radio galaxy images.

  16. 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…

  17. Classification of Building Object Types

    DEFF Research Database (Denmark)

    Jørgensen, Kaj Asbjørn

    2011-01-01

    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...... and in strong connection with databases holding a wide range of object types....

  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...

  19. RT-qPCR reveals opsin gene upregulation associated with age and sex in guppies (Poecilia reticulata - a species with color-based sexual selection and 11 visual-opsin genes

    Directory of Open Access Journals (Sweden)

    Taylor John S

    2011-03-01

    Full Text Available Abstract Background PCR-based surveys have shown that guppies (Poecilia reticulata have an unusually large visual-opsin gene repertoire. This has led to speculation that opsin duplication and divergence has enhanced the evolution of elaborate male coloration because it improves spectral sensitivity and/or discrimination in females. However, this conjecture on evolutionary connections between opsin repertoire, vision, mate choice, and male coloration was generated with little data on gene expression. Here, we used RT-qPCR to survey visual-opsin gene expression in the eyes of males, females, and juveniles in order to further understand color-based sexual selection from the perspective of the visual system. Results Juvenile and adult (male and female guppies express 10 visual opsins at varying levels in the eye. Two opsin genes in juveniles, SWS2B and RH2-2, accounted for >85% of all visual-opsin transcripts in the eye, excluding RH1. This relative abundance (RA value dropped to about 65% in adults, as LWS-A180 expression increased from approximately 3% to 20% RA. The juvenile-to-female transition also showed LWS-S180 upregulation from about 1.5% to 7% RA. Finally, we found that expression in guppies' SWS2-LWS gene cluster is negatively correlated with distance from a candidate locus control region (LCR. Conclusions Selective pressures influencing visual-opsin gene expression appear to differ among age and sex. LWS upregulation in females is implicated in augmenting spectral discrimination of male coloration and courtship displays. In males, enhanced discrimination of carotenoid-rich food and possibly rival males are strong candidate selective pressures driving LWS upregulation. These developmental changes in expression suggest that adults possess better wavelength discrimination than juveniles. Opsin expression within the SWS2-LWS gene cluster appears to be regulated, in part, by a common LCR. Finally, by comparing our RT-qPCR data to MSP data, we

  20. RT-qPCR reveals opsin gene upregulation associated with age and sex in guppies (Poecilia reticulata) - a species with color-based sexual selection and 11 visual-opsin genes.

    Science.gov (United States)

    Laver, Christopher R J; Taylor, John S

    2011-03-29

    PCR-based surveys have shown that guppies (Poecilia reticulata) have an unusually large visual-opsin gene repertoire. This has led to speculation that opsin duplication and divergence has enhanced the evolution of elaborate male coloration because it improves spectral sensitivity and/or discrimination in females. However, this conjecture on evolutionary connections between opsin repertoire, vision, mate choice, and male coloration was generated with little data on gene expression. Here, we used RT-qPCR to survey visual-opsin gene expression in the eyes of males, females, and juveniles in order to further understand color-based sexual selection from the perspective of the visual system. Juvenile and adult (male and female) guppies express 10 visual opsins at varying levels in the eye. Two opsin genes in juveniles, SWS2B and RH2-2, accounted for > 85% of all visual-opsin transcripts in the eye, excluding RH1. This relative abundance (RA) value dropped to about 65% in adults, as LWS-A180 expression increased from approximately 3% to 20% RA. The juvenile-to-female transition also showed LWS-S180 upregulation from about 1.5% to 7% RA. Finally, we found that expression in guppies' SWS2-LWS gene cluster is negatively correlated with distance from a candidate locus control region (LCR). Selective pressures influencing visual-opsin gene expression appear to differ among age and sex. LWS upregulation in females is implicated in augmenting spectral discrimination of male coloration and courtship displays. In males, enhanced discrimination of carotenoid-rich food and possibly rival males are strong candidate selective pressures driving LWS upregulation. These developmental changes in expression suggest that adults possess better wavelength discrimination than juveniles. Opsin expression within the SWS2-LWS gene cluster appears to be regulated, in part, by a common LCR. Finally, by comparing our RT-qPCR data to MSP data, we were able to propose the first opsin

  1. A multicenter comparative study of two classification systems for radial polydactyly.

    Science.gov (United States)

    Dijkman, Robert R; van Nieuwenhoven, Christianne A; Selles, Ruud W; Habenicht, Rolf; Hovius, Steven E R

    2014-11-01

    The aim of this study was to compare type occurrence and reliability of the Wassel and Rotterdam classifications for radial polydactyly. The authors classified a large population of radial polydactyly patients from two European clinics using both classification systems, and compared the incidences of the different types to a population derived from a systematic literature review. The authors further assessed intraobserver and interobserver reliability of both classification systems in a test-retest design with seven observers, using kappa statistics. Forty percent of the 520 cases with available radiographs could not be classified using the Wassel classification, whereas all cases could be classified using the Rotterdam classification. All unclassifiable cases had aberrant components; the majority were of the triphalangeal (63 percent), deviating (43 percent), or hypoplastic (39 percent) kind. Types III, IV, and VI occurred more often when using the Rotterdam classification. Intraobserver and interobserver reliability was comparable for both classification systems (κ=0.87 versus κ=0.83, and κ=0.65 versus κ=0.70). Types II and IV had the lowest reliability in both the Wassel and Rotterdam classifications (κ=0.30 to 0.59). Aberrant components indicating deviation and hypoplasia had the lowest reliability in the Rotterdam classification (κ=0.19 to 0.45). The Rotterdam classification has broader classification possibilities and similar intraobserver and interobserver reliability compared with the Wassel classification. Although it is more complex and the aberrant components should be more strictly defined to increase its clinical relevance, we recommend using the Rotterdam classification. Diagnostic, I.

  2. 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.

  3. AUTOMATIC CLASSIFICATION OF STRUCTURAL MRI FOR DIAGNOSIS OF NEURODEGENERATIVE DISEASES

    Directory of Open Access Journals (Sweden)

    Hernández-Tamames Juan Antonio

    2010-12-01

    Full Text Available This paper presents an automatic approach which classifies structural Magnetic Resonance images into pathological or healthy controls. A classification model was trained to find the boundaries that allow to separate the study groups. The method uses the deformation values from a set of regions, automatically identified as relevant, in a process that selects the statistically significant regions of a t-test under the restriction that this significance must be spatially coherent within a neighborhood of 5 voxels. The proposed method was assessed to distinguish healthy controls from schizophrenia patients. Classification results showed accuracy between 74% and 89%, depending on the stage of the disease and number of training samples.

  4. Melancholia EEG classification based on CSSD and SVM

    Science.gov (United States)

    Shi, Jian-Jun; Yuan, Qing-Wu; Zhou, La-Wu

    2011-10-01

    It takes an important role to get the disease information from melancholia electroencephalograph (EEG). Firstly, A common spatial subspace decomposition (CSSD) method was used to extract features from 16-channel EEG of melancholia and normal healthy persons. Then based on support vector machines (SVM), a classifier was designed to train and test its classification capability between Melancholia and healthy persons. The results indicated that the proposed method can reach a higher accuracy as 95% in EEG classification, while the accuracy of the method based on wavelet is only 88%.That is, the proposed method is feasible for the melancholia diagnosis and research.

  5. 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...... the whole song as an integrated part of the probabilistic model. This was achieved by considering a song as a set of independent co-occurrences (s, x\\_r) (s is the song index) instead of just a set of independent (x\\_r)'s. The models were tested against two baseline classification methods on a difficult 11...

  6. 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.

  7. 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

  8. Discovery and Classification in Astronomy

    Science.gov (United States)

    Dick, Steven J.

    2012-01-01

    Three decades after Martin Harwit's pioneering Cosmic Discovery (1981), and following on the recent IAU Symposium "Accelerating the Rate of Astronomical Discovery,” we have revisited the problem of discovery in astronomy, emphasizing new classes of objects. 82 such classes have been identified and analyzed, including 22 in the realm of the planets, 36 in the realm of the stars, and 24 in the realm of the galaxies. We find an extended structure of discovery, consisting of detection, interpretation and understanding, each with its own nuances and a microstructure including conceptual, technological and social roles. This is true with a remarkable degree of consistency over the last 400 years of telescopic astronomy, ranging from Galileo's discovery of satellites, planetary rings and star clusters, to the discovery of quasars and pulsars. Telescopes have served as "engines of discovery” in several ways, ranging from telescope size and sensitivity (planetary nebulae and spiral galaxies), to specialized detectors (TNOs) and the opening of the electromagnetic spectrum for astronomy (pulsars, pulsar planets, and most active galaxies). A few classes (radiation belts, the solar wind and cosmic rays), were initially discovered without the telescope. Classification also plays an important role in discovery. While it might seem that classification marks the end of discovery, or a post-discovery phase, in fact it often marks the beginning, even a pre-discovery phase. Nowhere is this more clearly seen than in the classification of stellar spectra, long before dwarfs, giants and supergiants were known, or their evolutionary sequence recognized. Classification may also be part of a post-discovery phase, as in the MK system of stellar classification, constructed after the discovery of stellar luminosity classes. Some classes are declared rather than discovered, as in the case of gas and ice giant planets, and, infamously, Pluto as a dwarf planet.

  9. Single-trial EEG RSVP classification using convolutional neural networks

    Science.gov (United States)

    Shamwell, Jared; Lee, Hyungtae; Kwon, Heesung; Marathe, Amar R.; Lawhern, Vernon; Nothwang, William

    2016-05-01

    Traditionally, Brain-Computer Interfaces (BCI) have been explored as a means to return function to paralyzed or otherwise debilitated individuals. An emerging use for BCIs is in human-autonomy sensor fusion where physiological data from healthy subjects is combined with machine-generated information to enhance the capabilities of artificial systems. While human-autonomy fusion of physiological data and computer vision have been shown to improve classification during visual search tasks, to date these approaches have relied on separately trained classification models for each modality. We aim to improve human-autonomy classification performance by developing a single framework that builds codependent models of human electroencephalograph (EEG) and image data to generate fused target estimates. As a first step, we developed a novel convolutional neural network (CNN) architecture and applied it to EEG recordings of subjects classifying target and non-target image presentations during a rapid serial visual presentation (RSVP) image triage task. The low signal-to-noise ratio (SNR) of EEG inherently limits the accuracy of single-trial classification and when combined with the high dimensionality of EEG recordings, extremely large training sets are needed to prevent overfitting and achieve accurate classification from raw EEG data. This paper explores a new deep CNN architecture for generalized multi-class, single-trial EEG classification across subjects. We compare classification performance from the generalized CNN architecture trained across all subjects to the individualized XDAWN, HDCA, and CSP neural classifiers which are trained and tested on single subjects. Preliminary results show that our CNN meets and slightly exceeds the performance of the other classifiers despite being trained across subjects.

  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. 22 CFR 9.4 - Original classification.

    Science.gov (United States)

    2010-04-01

    ... classification. (a) Definition. Original classification is the initial determination that certain information... Government programs for safeguarding nuclear materials or facilities; (vii) Vulnerabilities or capabilities... reference to classified documents that does not directly or indirectly disclose classified information may...

  12. Sow-activity classification from acceleration patterns

    DEFF Research Database (Denmark)

    Escalante, Hugo Jair; Rodriguez, Sara V.; Cordero, Jorge

    2013-01-01

    This paper describes a supervised learning approach to sow-activity classification from accelerometer measurements. In the proposed methodology, pairs of accelerometer measurements and activity types are considered as labeled instances of a usual supervised classification task. Under this scenari...

  13. EEG Signal Classification: Introduction to the Problem

    Directory of Open Access Journals (Sweden)

    A. Stancak

    2003-09-01

    Full Text Available The contribution describes the design, optimization and verificationof the off-line single-trial movement classification system. Four typesof movements are used for the classification: the right index fingerextension vs. flexion as well as the right shoulder (proximal vs.right index finger (distal movement. The classification systemutilizes hidden information stored in the characteristic shapes ofhuman brain activity (EEG signal. The great variability of EEGpotentials requires using of context information and hence theclassifier based on Hidden Markov Models (HMM. The suitableparameterization, model structure as well as training andclassification process are suggested on the base of spectral analysisresults and experience with the speech recognition. The training andthe classification are performed with the disjoint sets of EEGrealizations. Classification experiments are performed with 10 randomlychosen sets of EEG realizations. The final average score of thedistal/proximal movement classification is 80%; the standard deviationof classification results is 9%. The classification of the extension /flexion gives comparable results.

  14. 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.

  15. Mexican Hat Wavelet Kernel ELM for Multiclass Classification.

    Science.gov (United States)

    Wang, Jie; Song, Yi-Fan; Ma, Tian-Lei

    2017-01-01

    Kernel extreme learning machine (KELM) is a novel feedforward neural network, which is widely used in classification problems. To some extent, it solves the existing problems of the invalid nodes and the large computational complexity in ELM. However, the traditional KELM classifier usually has a low test accuracy when it faces multiclass classification problems. In order to solve the above problem, a new classifier, Mexican Hat wavelet KELM classifier, is proposed in this paper. The proposed classifier successfully improves the training accuracy and reduces the training time in the multiclass classification problems. Moreover, the validity of the Mexican Hat wavelet as a kernel function of ELM is rigorously proved. Experimental results on different data sets show that the performance of the proposed classifier is significantly superior to the compared classifiers.

  16. Estimating classification images with generalized linear and additive models.

    Science.gov (United States)

    Knoblauch, Kenneth; Maloney, Laurence T

    2008-12-22

    Conventional approaches to modeling classification image data can be described in terms of a standard linear model (LM). We show how the problem can be characterized as a Generalized Linear Model (GLM) with a Bernoulli distribution. We demonstrate via simulation that this approach is more accurate in estimating the underlying template in the absence of internal noise. With increasing internal noise, however, the advantage of the GLM over the LM decreases and GLM is no more accurate than LM. We then introduce the Generalized Additive Model (GAM), an extension of GLM that can be used to estimate smooth classification images adaptively. We show that this approach is more robust to the presence of internal noise, and finally, we demonstrate that GAM is readily adapted to estimation of higher order (nonlinear) classification images and to testing their significance.

  17. Halftone image classification using LMS algorithm and naive Bayes.

    Science.gov (United States)

    Liu, Yun-Fu; Guo, Jing-Ming; Lee, Jiann-Der

    2011-10-01

    Former research on inverse halftoning most focus on developing a general-purpose method for all types of halftone patterns, such as error diffusion, ordered dithering, etc., while fail to consider the natural discrepancies among various halftoning methods. To achieve optimal image quality for each halftoning method, the classification of halftone images is highly demanded. This study employed the least mean-square filter for improving the robustness of the extracted features, and employed the naive Bayes classifier to verify all the extracted features for classification. Nine of the most well-known halftoning methods were involved for testing. The experimental results demonstrated that the classification performance can achieve a 100% accuracy rate, and the number of distinguishable halftoning methods is more than that of a former method established by Chang and Yu. © 2011 IEEE

  18. 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.

  19. Mexican Hat Wavelet Kernel ELM for Multiclass Classification

    Directory of Open Access Journals (Sweden)

    Jie Wang

    2017-01-01

    Full Text Available Kernel extreme learning machine (KELM is a novel feedforward neural network, which is widely used in classification problems. To some extent, it solves the existing problems of the invalid nodes and the large computational complexity in ELM. However, the traditional KELM classifier usually has a low test accuracy when it faces multiclass classification problems. In order to solve the above problem, a new classifier, Mexican Hat wavelet KELM classifier, is proposed in this paper. The proposed classifier successfully improves the training accuracy and reduces the training time in the multiclass classification problems. Moreover, the validity of the Mexican Hat wavelet as a kernel function of ELM is rigorously proved. Experimental results on different data sets show that the performance of the proposed classifier is significantly superior to the compared classifiers.

  20. Classification of Aerial Photogrammetric 3d Point Clouds

    Science.gov (United States)

    Becker, C.; Häni, N.; Rosinskaya, E.; d'Angelo, E.; Strecha, C.

    2017-05-01

    We present a powerful method to extract per-point semantic class labels from aerial photogrammetry data. Labelling this kind of data is important for tasks such as environmental modelling, object classification and scene understanding. Unlike previous point cloud classification methods that rely exclusively on geometric features, we show that incorporating color information yields a significant increase in accuracy in detecting semantic classes. We test our classification method on three real-world photogrammetry datasets that were generated with Pix4Dmapper Pro, and with varying point densities. We show that off-the-shelf machine learning techniques coupled with our new features allow us to train highly accurate classifiers that generalize well to unseen data, processing point clouds containing 10 million points in less than 3 minutes on a desktop computer.

  1. Classification of visemes using visual cues

    Science.gov (United States)

    Alothmany, Nazeeh Shuja

    Studies have shown that visual features extracted from the lips of a speaker (visemes) can be used to automatically classify the visual representation of phonemes. Different visual features were extracted from the audio-visual recordings of a set of phonemes and used to define Linear Discriminant Analysis (LDA) functions to classify the phonemes. Audio-visual recordings from 18 speakers of Native American English for 12 Vowel-Consonant-Vowel (VCV) sounds were obtained using the consonants /b,v,w,th,d,z/ and the vowels /alpha,i/. The visual features used in this study were related to the lip height, lip width, motion in upper lips and the rate at which lips move while producing the VCV sequences. Features extracted from half of the speakers were used to design the classifier and features extracted from the other half were used in testing the classifiers. When each VCV sound was treated as an independent class, resulting in 12 classes, the percentage of correct recognition was 55.3% in the training set and 43.1% in the testing set. This percentage increased as classes were merged based on the level of confusion appearing between them in the results. When the same consonants with different vowels were treated as one class, resulting in 6 classes, the percentage of correct classification was 65.2% in the training set and 61.6% in the testing set. This is consistent with psycho-visual experiments in which subjects were unable to distinguish between visemes associated with VCV words with the same consonant but different vowels. When the VCV sounds were grouped into 3 classes, the percentage of correct classification in the training set was 84.4% and 81.1% in the testing set. In the second part of the study, linear discriminant functions were developed for every speaker resulting in 18 different sets of LDA functions. For every speaker, five VCV utterances were used to design the LDA functions, and 3 different VCV utterances were used to test these functions. For the

  2. 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.

  3. 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.

  4. Strength in Numbers: Using Big Data to Simplify Sentiment Classification.

    Science.gov (United States)

    Filippas, Apostolos; Lappas, Theodoros

    2017-09-01

    Sentiment classification, the task of assigning a positive or negative label to a text segment, is a key component of mainstream applications such as reputation monitoring, sentiment summarization, and item recommendation. Even though the performance of sentiment classification methods has steadily improved over time, their ever-increasing complexity renders them comprehensible by only a shrinking minority of expert practitioners. For all others, such highly complex methods are black-box predictors that are hard to tune and even harder to justify to decision makers. Motivated by these shortcomings, we introduce BigCounter: a new algorithm for sentiment classification that substitutes algorithmic complexity with Big Data. Our algorithm combines standard data structures with statistical testing to deliver accurate and interpretable predictions. It is also parameter free and suitable for use virtually "out of the box," which makes it appealing for organizations wanting to leverage their troves of unstructured data without incurring the significant expense of creating in-house teams of data scientists. Finally, BigCounter's efficient and parallelizable design makes it applicable to very large data sets. We apply our method on such data sets toward a study on the limits of Big Data for sentiment classification. Our study finds that, after a certain point, predictive performance tends to converge and additional data have little benefit. Our algorithmic design and findings provide the foundations for future research on the data-over-computation paradigm for classification problems.

  5. Exploring Deep Learning and Transfer Learning for Colonic Polyp Classification

    Directory of Open Access Journals (Sweden)

    Eduardo Ribeiro

    2016-01-01

    Full Text Available Recently, Deep Learning, especially through Convolutional Neural Networks (CNNs has been widely used to enable the extraction of highly representative features. This is done among the network layers by filtering, selecting, and using these features in the last fully connected layers for pattern classification. However, CNN training for automated endoscopic image classification still provides a challenge due to the lack of large and publicly available annotated databases. In this work we explore Deep Learning for the automated classification of colonic polyps using different configurations for training CNNs from scratch (or full training and distinct architectures of pretrained CNNs tested on 8-HD-endoscopic image databases acquired using different modalities. We compare our results with some commonly used features for colonic polyp classification and the good results suggest that features learned by CNNs trained from scratch and the “off-the-shelf” CNNs features can be highly relevant for automated classification of colonic polyps. Moreover, we also show that the combination of classical features and “off-the-shelf” CNNs features can be a good approach to further improve the results.

  6. Simple Open Stance Classification for Rumour Analysis

    OpenAIRE

    Aker, Ahmet; Derczynski, Leon; Bontcheva, Kalina

    2017-01-01

    Stance classification determines the attitude, or stance, in a (typically short) text. The task has powerful applications, such as the detection of fake news or the automatic extraction of attitudes toward entities or events in the media. This paper describes a surprisingly simple and efficient classification approach to open stance classification in Twitter, for rumour and veracity classification. The approach profits from a novel set of automatically identifiable problem-specific features, ...

  7. 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.

  8. 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.

  9. Detecting Hijacked Journals by Using Classification Algorithms.

    Science.gov (United States)

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

    2017-04-10

    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.

  10. The Road Ahead for Library Classification Systems.

    Science.gov (United States)

    Mitchell, Joan S.

    1997-01-01

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

  11. 37 CFR 2.85 - Classification schedules.

    Science.gov (United States)

    2010-07-01

    ... Intellectual Property Organization, unless the International Bureau corrects the classification. Classes cannot... Intellectual Property Organization. (1) If international classification changes pursuant to the Nice Agreement... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Classification schedules. 2...

  12. 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...

  13. 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...

  14. 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. ...

  15. 75 FR 10529 - Mail Classification Change

    Science.gov (United States)

    2010-03-08

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

  16. 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...

  17. 46 CFR 503.54 - Original classification.

    Science.gov (United States)

    2010-10-01

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

  18. 76 FR 47614 - Mail Classification Change

    Science.gov (United States)

    2011-08-05

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

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 17 CFR 200.505 - Original classification.

    Science.gov (United States)

    2010-04-01

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

  9. 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...

  10. 32 CFR 1602.7 - Classification.

    Science.gov (United States)

    2010-07-01

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

  11. 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...

  12. 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...

  13. 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.

  14. Review Of Lymphoma Classification | Mayun | Highland Medical ...

    African Journals Online (AJOL)

    Lymphoma have been broadly classified into two main categories; Hodkin disease (HD) and non- Hodgkin lymphoma (NHL). Where as HD has had a fairly stable classification scheme over the years since Rye classification into being, NHL has had the most unstable classification schemes. First to come into being were Gall ...

  15. 75 FR 21212 - Approval of Classification Societies

    Science.gov (United States)

    2010-04-23

    ... acknowledges that classification societies often act as recognized organizations (ROs) under powers delegated... the ship is entitled to fly. Classification society means an organization that, at a minimum, verifies... organization that meets the definition of a classification society provided in Sec. 2.45-1 of this subpart. Sec...

  16. 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-...

  17. 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...

  18. 32 CFR 2001.22 - Derivative classification.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Derivative classification. 2001.22 Section 2001... Identification and Markings § 2001.22 Derivative classification. (a) General. Information classified derivatively... guide. (b) Identity of persons who apply derivative classification markings. Derivative classifiers...

  19. 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) ...

  20. 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 345.20 Judicial Administration FEDERAL PRISON INDUSTRIES, INC., DEPARTMENT OF JUSTICE FEDERAL PRISON INDUSTRIES (FPI) INMATE WORK PROGRAMS Position Classification § 345.20 Position classification. (a) Inmate...

  1. 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.

  2. 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.

  3. Classification of Health Related Applications.

    Science.gov (United States)

    Höhn, Matthias; von Jan, Ute; Framke, Theodor; Albrecht, Urs-Vito

    2016-01-01

    Although there is a large number of health related apps available in the stores of the major mobile platforms, the stores do not really offer clear definitions of what health related apps are and how they can be categorized. A similar picture is found in literature. Here, many proposals covering different app related aspects have been published, but often, these only cover a narrow field. There is no common terminology describing what health apps are and neither is there a common classification. In order to alleviate the situation, we developed a proposal for categorization that can be used as a basis for discussing aspects related to health applications and for describing the unclear situation on the market. In this paper, the function related aspects are covered, although the scheme itself covers many other aspects related to users of health apps, technical aspects and so on. This initial classification was applied to a sample of health apps available for iOS and Android.

  4. 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

  5. Human error analysis of commercial aviation accidents using the human factors analysis and classification system (HFACS)

    Science.gov (United States)

    2001-02-01

    The Human Factors Analysis and Classification System (HFACS) is a general human error framework : originally developed and tested within the U.S. military as a tool for investigating and analyzing the human : causes of aviation accidents. Based upon ...

  6. Perspectives on next steps in classification of oro-facial pain - part 1: role of ontology.

    Science.gov (United States)

    Ceusters, W; Michelotti, A; Raphael, K G; Durham, J; Ohrbach, R

    2015-12-01

    The purpose of this study was to review existing principles of oro-facial pain classifications and to specify design recommendations for a new system that would reflect recent insights in biomedical classification systems, terminologies and ontologies. The study was initiated by a symposium organised by the International RDC/TMD Consortium Network in March 2013, to which the present authors contributed. The following areas are addressed: problems with current classification approaches, status of the ontological basis of pain disorders, insufficient diagnostic aids and biomarkers for pain disorders, exploratory nature of current pain terminology and classification systems, and problems with prevailing classification methods from an ontological perspective. Four recommendations for addressing these problems are as follows: (i) develop a hypothesis-driven classification structure built on principles that ensure to our best understanding an accurate description of the relations among all entities involved in oro-facial pain disorders; (ii) take into account the physiology and phenomenology of oro-facial pain disorders to adequately represent both domains including psychosocial entities in a classification system; (iii) plan at the beginning for field-testing at strategic development stages; and (iv) consider how the classification system will be implemented. Implications in relation to the specific domains of psychosocial factors and biomarkers for inclusion into an oro-facial pain classification system are described in two separate papers. © 2015 John Wiley & Sons Ltd.

  7. COMPRESSIVE CLASSIFICATION FOR FACE RECOGNITION

    OpenAIRE

    Majumdar, Angshul; Ward, Rabab K.

    2010-01-01

    This chapter reviews an alternate face recognition method than those provided by traditional machine learning tools. Conventional machine learning solutions to dimensionality reduction and classification require all the data to be present beforehand, i.e. whenever new data is added, the system cannot be updated in online fashion, rather all the calculations need to be re-done from scratch. This creates a computational bottleneck for large scale implementation of face recognition systems.

  8. Biogeography based Satellite Image Classification

    OpenAIRE

    Harish Kundra; Parminder Singh; Navdeep Kaur; V.K. Panchal

    2009-01-01

    Biogeography is the study of the geographical distribution of biological organisms. The mindset of the engineer is that we can learn from nature. Biogeography Based Optimization is a burgeoning nature inspired technique to find the optimal solution of the problem. Satellite image classification is an important task because it is the only way we can know about the land cover map of inaccessible areas. Though satellite images have been classified in past by using various techniques, the researc...

  9. A New Classification of Technologies

    OpenAIRE

    Coccia, Mario

    2017-01-01

    This study here suggests a classification of technologies based on taxonomic characteristics of interaction between technologies in complex systems that is not a studied research field in economics of technical change. The proposed taxonomy here categorizes technologies in four typologies, in a broad analogy with the ecology: 1) technological parasitism is a relationship between two technologies T1 and T2 in a complex system S where one technology T1 benefits from the interaction with T2, whe...

  10. 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.)

  11. Memory Constraint Online Multitask Classification

    OpenAIRE

    Cavallanti, Giovanni; Cesa-Bianchi, Nicolò

    2012-01-01

    We investigate online kernel algorithms which simultaneously process multiple classification tasks while a fixed constraint is imposed on the size of their active sets. We focus in particular on the design of algorithms that can efficiently deal with problems where the number of tasks is extremely high and the task data are large scale. Two new projection-based algorithms are introduced to efficiently tackle those issues while presenting different trade offs on how the available memory is man...

  12. Enhancement classification of galaxy images

    Science.gov (United States)

    Jenkinson, John

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

  13. 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.

  14. Improving classification in protein structure databases using text mining

    Directory of Open Access Journals (Sweden)

    Jones David T

    2009-05-01

    Full Text Available Abstract Background The classification of protein domains in the CATH resource is primarily based on structural comparisons, sequence similarity and manual analysis. One of the main bottlenecks in the processing of new entries is the evaluation of 'borderline' cases by human curators with reference to the literature, and better tools for helping both expert and non-expert users quickly identify relevant functional information from text are urgently needed. A text based method for protein classification is presented, which complements the existing sequence and structure-based approaches, especially in cases exhibiting low similarity to existing members and requiring manual intervention. The method is based on the assumption that textual similarity between sets of documents relating to proteins reflects biological function similarities and can be exploited to make classification decisions. Results An optimal strategy for the text comparisons was identified by using an established gold standard enzyme dataset. Filtering of the abstracts using a machine learning approach to discriminate sentences containing functional, structural and classification information that are relevant to the protein classification task improved performance. Testing this classification scheme on a dataset of 'borderline' protein domains that lack significant sequence or structure similarity to classified proteins showed that although, as expected, the structural similarity classifiers perform better on average, there is a significant benefit in incorporating text similarity in logistic regression models, indicating significant orthogonality in this additional information. Coverage was significantly increased especially at low error rates, which is important for routine classification tasks: 15.3% for the combined structure and text classifier compared to 10% for the structural classifier alone, at 10-3 error rate. Finally when only the highest scoring predictions were used

  15. Classification and recognition in artificial grammar learning: Analysis of receiver operating characteristics.

    Science.gov (United States)

    Lotz, Anja; Kinder, Annette

    2006-04-01

    In two experiments we investigated recognition and classification judgements using an artificial grammar learning paradigm. In Experiment 1, when only new test items had to be judged, analysis of z-transformed receiver operating characteristics (z-ROCs) revealed no differences between classification and recognition. In Experiment 2, where we included old test items, z-ROCs in the two tasks differed, suggesting that judgements relied on different types of information. The results are interpreted in terms of heuristics that people use when making classification and recognition judgements.

  16. Classification of electroencephalograph signals using time-frequency decomposition and linear discriminant analysis

    Science.gov (United States)

    Szuflitowska, B.; Orlowski, P.

    2017-08-01

    Automated detection system consists of two key steps: extraction of features from EEG signals and classification for detection of pathology activity. The EEG sequences were analyzed using Short-Time Fourier Transform and the classification was performed using Linear Discriminant Analysis. The accuracy of the technique was tested on three sets of EEG signals: epilepsy, healthy and Alzheimer's Disease. The classification error below 10% has been considered a success. The higher accuracy are obtained for new data of unknown classes than testing data. The methodology can be helpful in differentiation epilepsy seizure and disturbances in the EEG signal in Alzheimer's Disease.

  17. Applying wavelet entropy principle in fault classification

    Energy Technology Data Exchange (ETDEWEB)

    El Safty, S.; El-Zonkoly, A. [Arab Academy for Science and Technology, Miami, Alexandria, P.O.1029 (Egypt)

    2009-11-15

    The ability to detect and classify the type of fault plays a great role in the protection of power system. This procedure is required to be precise with no time consumption. In this paper detection of fault type has been implemented using wavelet analysis together with wavelet entropy principle. The simulation of power system is carried out using PSCAD/EMTDC. Different types of faults were studied obtaining various current waveforms. These current waveforms were decomposed using wavelet analysis into different approximation and details. The wavelet entropies of such decompositions are analyzed reaching a successful methodology for fault classification. The suggested approach is tested using different fault types and proven successful identification for the type of fault. (author)

  18. Drug solubility classification in the bovine.

    Science.gov (United States)

    Martinez, M N; Apley, M D

    2012-04-01

    Currently, the basis for solubility test conditions and the corresponding solubility criteria is derived from the tremendous wealth of information developed to support human pharmaceutical product development and regulation. However, there are several critical differences between the gastrointestinal tract of ruminants and monogastric species that can affect the conditions and criteria to be applied to the classification of drug solubility in cattle. These include the pH of the stomach, the volume of the stomach, the types of oral formulations, and the definition of 'highest dose'. These points are discussed below and alternative perspectives for consideration with regard to possible modification of solubility criteria for ruminants are presented. © Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

  19. Comparison research on iot oriented image classification algorithms

    Directory of Open Access Journals (Sweden)

    Du Ke

    2016-01-01

    Full Text Available Image classification belongs to the machine learning and computer vision fields, it aims to recognize and classify objects in the image contents. How to apply image classification algorithms to large-scale data in the IoT framework is the focus of current research. Based on Anaconda, this article implement sk-NN, SVM, Softmax and Neural Network algorithms by Python, performs data normalization, random search, HOG and colour histogram feature extraction to enhance the algorithms, experiments on them in CIFAR-10 datasets, then conducts comparison from three aspects of training time, test time and classification accuracy. The experimental results show that: the vectorized implementation of the algorithms is more efficient than the loop implementation; The training time of k-NN is the shortest, SVM and Softmax spend more time, and the training time of Neural Network is the longest; The test time of SVM, Softmax and Neural Network are much shorter than of k-NN; Neural Network gets the highest classification accuracy, SVM and Softmax get lower and approximate accuracies, and k-NN gets the lowest accuracy. The effects of three algorithm improvement methods are obvious.

  20. 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.