A European Humus Forms Reference Base

NASA Astrophysics Data System (ADS)

Zanella, A.; Englisch, M.; Ponge, J.-F.; Jabiol, B.; Sartori, G.; Gardi, C.

2012-04-01

From 2003 on, a panel of experts in humus and humus dynamics (Humus group) has been working about a standardisation and improvement of existing national humus classifications. Some important goals have been reached, in order to share data and experiences: a) definition of specific terms; b) description of 15 types of diagnostic horizons; c) of 10 basic humus forms references; d) subdivision of each main reference in 2-4 sub-unities; e) elaboration of a general European Humus Form Reference Base (http://hal-agroparistech.archives-ouvertes.fr/docs/00/56/17/95/PDF/Humus_Forms_ERB_31_01_2011.pdf); f) publication of the scientific significance of this base of classification as an article [A European morpho-functional classification of humus forms. Geoderma, 164 (3-4), 138-145]. The classification will be updated every 2 years and presently the Humus group is assessing biological (general: soil, vegetation, biome; specific: fungi, bacteria, pedofauna), physical (air temperature, rainfall) and chemical (pH, mineral elements, organic matter, quality and quantity of humic components…) factors which characterize basic humus forms and their varieties. The content of the new version of the classification is planned to be more "practical", like an ecological manual which lists associated humus forms and environmental data in the aim to contribute to a more precise environmental diagnosis of every analysed terrestrial and semiterrestrial European ecosystem. The Humus group is also involved in an endeavour to include humus forms in the World Reference Base for Soils (WRB-FAO) according to nomenclatural principles erected for soil profiles. Thirty basic references have been defined, complemented by a set of qualifiers (prefixes and suffixes), allowing to classify European humus forms and probably a large majority of humus forms known worldwide. The principles of the classification, the diagnostic horizons and humus forms main references are presented at the General Assembly of the European Geosciences Union with the aim to stimulate members' curiosity. Interested people are invited to test the classification system in various field areas and to collaborate with the Humus group. Critical observations and field data/impressions are welcome as every other suggestions which can help in elaborating the 2013 version of the European humus forms classification.

The Reference Ability Neural Network Study: Life-time stability of reference-ability neural networks derived from task maps of young adults.

PubMed

Habeck, C; Gazes, Y; Razlighi, Q; Steffener, J; Brickman, A; Barulli, D; Salthouse, T; Stern, Y

2016-01-15

Analyses of large test batteries administered to individuals ranging from young to old have consistently yielded a set of latent variables representing reference abilities (RAs) that capture the majority of the variance in age-related cognitive change: Episodic Memory, Fluid Reasoning, Perceptual Processing Speed, and Vocabulary. In a previous paper (Stern et al., 2014), we introduced the Reference Ability Neural Network Study, which administers 12 cognitive neuroimaging tasks (3 for each RA) to healthy adults age 20-80 in order to derive unique neural networks underlying these 4 RAs and investigate how these networks may be affected by aging. We used a multivariate approach, linear indicator regression, to derive a unique covariance pattern or Reference Ability Neural Network (RANN) for each of the 4 RAs. The RANNs were derived from the neural task data of 64 younger adults of age 30 and below. We then prospectively applied the RANNs to fMRI data from the remaining sample of 227 adults of age 31 and above in order to classify each subject-task map into one of the 4 possible reference domains. Overall classification accuracy across subjects in the sample age 31 and above was 0.80±0.18. Classification accuracy by RA domain was also good, but variable; memory: 0.72±0.32; reasoning: 0.75±0.35; speed: 0.79±0.31; vocabulary: 0.94±0.16. Classification accuracy was not associated with cross-sectional age, suggesting that these networks, and their specificity to the respective reference domain, might remain intact throughout the age range. Higher mean brain volume was correlated with increased overall classification accuracy; better overall performance on the tasks in the scanner was also associated with classification accuracy. For the RANN network scores, we observed for each RANN that a higher score was associated with a higher corresponding classification accuracy for that reference ability. Despite the absence of behavioral performance information in the derivation of these networks, we also observed some brain-behavioral correlations, notably for the fluid-reasoning network whose network score correlated with performance on the memory and fluid-reasoning tasks. While age did not influence the expression of this RANN, the slope of the association between network score and fluid-reasoning performance was negatively associated with higher ages. These results provide support for the hypothesis that a set of specific, age-invariant neural networks underlies these four RAs, and that these networks maintain their cognitive specificity and level of intensity across age. Activation common to all 12 tasks was identified as another activation pattern resulting from a mean-contrast Partial-Least-Squares technique. This common pattern did show associations with age and some subject demographics for some of the reference domains, lending support to the overall conclusion that aspects of neural processing that are specific to any cognitive reference ability stay constant across age, while aspects that are common to all reference abilities differ across age. Copyright © 2015 Elsevier Inc. All rights reserved.

PROTAX-Sound: A probabilistic framework for automated animal sound identification

PubMed Central

Somervuo, Panu; Ovaskainen, Otso

2017-01-01

Autonomous audio recording is stimulating new field in bioacoustics, with a great promise for conducting cost-effective species surveys. One major current challenge is the lack of reliable classifiers capable of multi-species identification. We present PROTAX-Sound, a statistical framework to perform probabilistic classification of animal sounds. PROTAX-Sound is based on a multinomial regression model, and it can utilize as predictors any kind of sound features or classifications produced by other existing algorithms. PROTAX-Sound combines audio and image processing techniques to scan environmental audio files. It identifies regions of interest (a segment of the audio file that contains a vocalization to be classified), extracts acoustic features from them and compares with samples in a reference database. The output of PROTAX-Sound is the probabilistic classification of each vocalization, including the possibility that it represents species not present in the reference database. We demonstrate the performance of PROTAX-Sound by classifying audio from a species-rich case study of tropical birds. The best performing classifier achieved 68% classification accuracy for 200 bird species. PROTAX-Sound improves the classification power of current techniques by combining information from multiple classifiers in a manner that yields calibrated classification probabilities. PMID:28863178

PROTAX-Sound: A probabilistic framework for automated animal sound identification.

PubMed

de Camargo, Ulisses Moliterno; Somervuo, Panu; Ovaskainen, Otso

2017-01-01

Autonomous audio recording is stimulating new field in bioacoustics, with a great promise for conducting cost-effective species surveys. One major current challenge is the lack of reliable classifiers capable of multi-species identification. We present PROTAX-Sound, a statistical framework to perform probabilistic classification of animal sounds. PROTAX-Sound is based on a multinomial regression model, and it can utilize as predictors any kind of sound features or classifications produced by other existing algorithms. PROTAX-Sound combines audio and image processing techniques to scan environmental audio files. It identifies regions of interest (a segment of the audio file that contains a vocalization to be classified), extracts acoustic features from them and compares with samples in a reference database. The output of PROTAX-Sound is the probabilistic classification of each vocalization, including the possibility that it represents species not present in the reference database. We demonstrate the performance of PROTAX-Sound by classifying audio from a species-rich case study of tropical birds. The best performing classifier achieved 68% classification accuracy for 200 bird species. PROTAX-Sound improves the classification power of current techniques by combining information from multiple classifiers in a manner that yields calibrated classification probabilities.

76 FR 60388 - Revision of Cotton Futures Classification Procedures

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-29

...-005] RIN 0581-AD16 Revision of Cotton Futures Classification Procedures AGENCY: Agricultural Marketing... update the procedures for cotton futures quality classification services by using Smith-Doxey classification data in the cotton futures classification process. In addition, references to a separate and...

77 FR 5379 - Revision of Cotton Futures Classification Procedures

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-03

... 0581-AD16 Revision of Cotton Futures Classification Procedures AGENCY: Agricultural Marketing Service... for cotton futures quality classification services by using Smith-Doxey classification data in the cotton futures classification process. In addition, references to a separate and optional review of...

Strength Analysis on Ship Ladder Using Finite Element Method

NASA Astrophysics Data System (ADS)

Budianto; Wahyudi, M. T.; Dinata, U.; Ruddianto; Eko P., M. M.

2018-01-01

In designing the ship’s structure, it should refer to the rules in accordance with applicable classification standards. In this case, designing Ladder (Staircase) on a Ferry Ship which is set up, it must be reviewed based on the loads during ship operations, either during sailing or at port operations. The classification rules in ship design refer to the calculation of the structure components described in Classification calculation method and can be analysed using the Finite Element Method. Classification Regulations used in the design of Ferry Ships used BKI (Bureau of Classification Indonesia). So the rules for the provision of material composition in the mechanical properties of the material should refer to the classification of the used vessel. The analysis in this structure used program structure packages based on Finite Element Method. By using structural analysis on Ladder (Ladder), it obtained strength and simulation structure that can withstand load 140 kg both in static condition, dynamic, and impact. Therefore, the result of the analysis included values of safety factors in the ship is to keep the structure safe but the strength of the structure is not excessive.

20 CFR 410.418 - Irrebuttable presumption of total disability due to pneumoconiosis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... Classification of Radiographs of Pneumoconioses, 1971, or (2) The International Classification of the Radiographs of the Pneumoconioses of the International Labour Office, Extended Classification (1968) (which may be referred to as the “ILO Classification (1968)”), or (3) The Classification of the Pneumoconiosis...

NANDA Diagnoses, NIC Interventions, and NOC Outcomes Used in an Electronic Health Record with Elementary School Children

ERIC Educational Resources Information Center

Lunney, Margaret

2006-01-01

This is a report of a secondary analysis of data from a published quasi-experimental feasibility study of the effects of implementing diagnoses from North American Nursing Diagnosis Association International, interventions from the Nursing Interventions Classification, and outcomes from the Nursing Outcomes Classification (referred to as NNN) on…

Indoor transformer stations and ELF magnetic field exposure: use of transformer structural characteristics to improve exposure assessment.

PubMed

Okokon, Enembe Oku; Roivainen, Päivi; Kheifets, Leeka; Mezei, Gabor; Juutilainen, Jukka

2014-01-01

Previous studies have shown that populations of multiapartment buildings with indoor transformer stations may serve as a basis for improved epidemiological studies on the relationship between childhood leukaemia and extremely-low-frequency (ELF) magnetic fields (MFs). This study investigated whether classification based on structural characteristics of the transformer stations would improve ELF MF exposure assessment. The data included MF measurements in apartments directly above transformer stations ("exposed" apartments) in 30 buildings in Finland, and reference apartments in the same buildings. Transformer structural characteristics (type and location of low-voltage conductors) were used to classify exposed apartments into high-exposure (HE) and intermediate-exposure (IE) categories. An exposure gradient was observed: both the time-average MF and time above a threshold (0.4 μT) were highest in the HE apartments and lowest in the reference apartments, showing a statistically significant trend. The differences between HE and IE apartments, however, were not statistically significant. A simulation exercise showed that the three-category classification did not perform better than a two-category classification (exposed and reference apartments) in detecting the existence of an increased risk. However, data on the structural characteristics of transformers is potentially useful for evaluating exposure-response relationship.

Validation assessment of shoreline extraction on medium resolution satellite image

NASA Astrophysics Data System (ADS)

Manaf, Syaifulnizam Abd; Mustapha, Norwati; Sulaiman, Md Nasir; Husin, Nor Azura; Shafri, Helmi Zulhaidi Mohd

2017-10-01

Monitoring coastal zones helps provide information about the conditions of the coastal zones, such as erosion or accretion. Moreover, monitoring the shorelines can help measure the severity of such conditions. Such measurement can be performed accurately by using Earth observation satellite images rather than by using traditional ground survey. To date, shorelines can be extracted from satellite images with a high degree of accuracy by using satellite image classification techniques based on machine learning to identify the land and water classes of the shorelines. In this study, the researchers validated the results of extracted shorelines of 11 classifiers using a reference shoreline provided by the local authority. Specifically, the validation assessment was performed to examine the difference between the extracted shorelines and the reference shorelines. The research findings showed that the SVM Linear was the most effective image classification technique, as evidenced from the lowest mean distance between the extracted shoreline and the reference shoreline. Furthermore, the findings showed that the accuracy of the extracted shoreline was not directly proportional to the accuracy of the image classification.

Impact of training sets on classification of high-throughput bacterial 16s rRNA gene surveys

PubMed Central

Werner, Jeffrey J; Koren, Omry; Hugenholtz, Philip; DeSantis, Todd Z; Walters, William A; Caporaso, J Gregory; Angenent, Largus T; Knight, Rob; Ley, Ruth E

2012-01-01

Taxonomic classification of the thousands–millions of 16S rRNA gene sequences generated in microbiome studies is often achieved using a naïve Bayesian classifier (for example, the Ribosomal Database Project II (RDP) classifier), due to favorable trade-offs among automation, speed and accuracy. The resulting classification depends on the reference sequences and taxonomic hierarchy used to train the model; although the influence of primer sets and classification algorithms have been explored in detail, the influence of training set has not been characterized. We compared classification results obtained using three different publicly available databases as training sets, applied to five different bacterial 16S rRNA gene pyrosequencing data sets generated (from human body, mouse gut, python gut, soil and anaerobic digester samples). We observed numerous advantages to using the largest, most diverse training set available, that we constructed from the Greengenes (GG) bacterial/archaeal 16S rRNA gene sequence database and the latest GG taxonomy. Phylogenetic clusters of previously unclassified experimental sequences were identified with notable improvements (for example, 50% reduction in reads unclassified at the phylum level in mouse gut, soil and anaerobic digester samples), especially for phylotypes belonging to specific phyla (Tenericutes, Chloroflexi, Synergistetes and Candidate phyla TM6, TM7). Trimming the reference sequences to the primer region resulted in systematic improvements in classification depth, and greatest gains at higher confidence thresholds. Phylotypes unclassified at the genus level represented a greater proportion of the total community variation than classified operational taxonomic units in mouse gut and anaerobic digester samples, underscoring the need for greater diversity in existing reference databases. PMID:21716311

The Ex Vivo Eye Irritation Test as an alternative test method for serious eye damage/eye irritation.

PubMed

Spöler, Felix; Kray, Oya; Kray, Stefan; Panfil, Claudia; Schrage, Norbert F

2015-07-01

Ocular irritation testing is a common requirement for the classification, labelling and packaging of chemicals (substances and mixtures). The in vivo Draize rabbit eye test (OECD Test Guideline 405) is considered to be the regulatory reference method for the classification of chemicals according to their potential to induce eye injury. In the Draize test, chemicals are applied to rabbit eyes in vivo, and changes are monitored over time. If no damage is observed, the chemical is not categorised. Otherwise, the classification depends on the severity and reversibility of the damage. Alternative test methods have to be designed to match the classifications from the in vivo reference method. However, observation of damage reversibility is usually not possible in vitro. Within the present study, a new organotypic method based on rabbit corneas obtained from food production is demonstrated to close this gap. The Ex Vivo Eye Irritation Test (EVEIT) retains the full biochemical activity of the corneal epithelium, epithelial stem cells and endothelium. This permits the in-depth analysis of ocular chemical trauma beyond that achievable by using established in vitro methods. In particular, the EVEIT is the first test to permit the direct monitoring of recovery of all corneal layers after damage. To develop a prediction model for the EVEIT that is comparable to the GHS system, 37 reference chemicals were analysed. The experimental data were used to derive a three-level potency ranking of eye irritation and corrosion that best fits the GHS categorisation. In vivo data available in the literature were used for comparison. When compared with GHS classification predictions, the overall accuracy of the three-level potency ranking was 78%. The classification of chemicals as irritating versus non-irritating resulted in 96% sensitivity, 91% specificity and 95% accuracy. 2015 FRAME.

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

Code of Federal Regulations, 2011 CFR

2011-04-01

... classification categories are defined as follows: (1) Top Secret. Top Secret refers to national security... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Classification of... REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification § 3a...

Hypothesis-driven classification of materials using nuclear magnetic resonance relaxometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Espy, Michelle A.; Matlashov, Andrei N.; Schultz, Larry J.

Technologies related to identification of a substance in an optimized manner are provided. A reference group of known materials is identified. Each known material has known values for several classification parameters. The classification parameters comprise at least one of T.sub.1, T.sub.2, T.sub.1.rho., a relative nuclear susceptibility (RNS) of the substance, and an x-ray linear attenuation coefficient (LAC) of the substance. A measurement sequence is optimized based on at least one of a measurement cost of each of the classification parameters and an initial probability of each of the known materials in the reference group.

7 CFR 201.51 - Inert matter.

Code of Federal Regulations, 2010 CFR

2010-01-01

... stated under pure seed. Refer to § 201.48 (g) and (h) for pure seed classification. (5) Seed units with... the seed unit. Refer to § 201.48(h) for pure seed classification. (6) Broken seed units of... to be within the following categories: (1) Damaged seed (other than grasses) with over one-half of...

7 CFR 201.51 - Inert matter.

Code of Federal Regulations, 2011 CFR

2011-01-01

... stated under pure seed. Refer to § 201.48 (g) and (h) for pure seed classification. (5) Seed units with... the seed unit. Refer to § 201.48(h) for pure seed classification. (6) Broken seed units of... to be within the following categories: (1) Damaged seed (other than grasses) with over one-half of...

A risk-based classification scheme for genetically modified foods. III: Evaluation using a panel of reference foods.

PubMed

Chao, Eunice; Krewski, Daniel

2008-12-01

This paper presents an exploratory evaluation of four functional components of a proposed risk-based classification scheme (RBCS) for crop-derived genetically modified (GM) foods in a concordance study. Two independent raters assigned concern levels to 20 reference GM foods using a rating form based on the proposed RBCS. The four components of evaluation were: (1) degree of concordance, (2) distribution across concern levels, (3) discriminating ability of the scheme, and (4) ease of use. At least one of the 20 reference foods was assigned to each of the possible concern levels, demonstrating the ability of the scheme to identify GM foods of different concern with respect to potential health risk. There was reasonably good concordance between the two raters for the three separate parts of the RBCS. The raters agreed that the criteria in the scheme were sufficiently clear in discriminating reference foods into different concern levels, and that with some experience, the scheme was reasonably easy to use. Specific issues and suggestions for improvements identified in the concordance study are discussed.

Variance approximations for assessments of classification accuracy

Treesearch

R. L. Czaplewski

1994-01-01

Variance approximations are derived for the weighted and unweighted kappa statistics, the conditional kappa statistic, and conditional probabilities. These statistics are useful to assess classification accuracy, such as accuracy of remotely sensed classifications in thematic maps when compared to a sample of reference classifications made in the field. Published...

20 CFR 718.304 - Irrebuttable presumption of total disability or death due to pneumoconiosis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... International Classification of Radiographs of the Pneumoconioses, 1971, or subsequent revisions thereto; or (2) The International Classification of the Radiographs of the Pneumoconioses of the International Labour Office, Extended Classification (1968) (which may be referred to as the “ILO Classification (1968)”); or...

Determination of Classification Accuracy for Land Use/cover Types Using Landsat-Tm Spot-Mss and Multipolarized and Multi-Channel Synthetic Aperture Radar

NASA Astrophysics Data System (ADS)

Dondurur, Mehmet

The primary objective of this study was to determine the degree to which modern SAR systems can be used to obtain information about the Earth's vegetative resources. Information obtainable from microwave synthetic aperture radar (SAR) data was compared with that obtainable from LANDSAT-TM and SPOT data. Three hypotheses were tested: (a) Classification of land cover/use from SAR data can be accomplished on a pixel-by-pixel basis with the same overall accuracy as from LANDSAT-TM and SPOT data. (b) Classification accuracy for individual land cover/use classes will differ between sensors. (c) Combining information derived from optical and SAR data into an integrated monitoring system will improve overall and individual land cover/use class accuracies. The study was conducted with three data sets for the Sleeping Bear Dunes test site in the northwestern part of Michigan's lower peninsula, including an October 1982 LANDSAT-TM scene, a June 1989 SPOT scene and C-, L- and P-Band radar data from the Jet Propulsion Laboratory AIRSAR. Reference data were derived from the Michigan Resource Information System (MIRIS) and available color infrared aerial photos. Classification and rectification of data sets were done using ERDAS Image Processing Programs. Classification algorithms included Maximum Likelihood, Mahalanobis Distance, Minimum Spectral Distance, ISODATA, Parallelepiped, and Sequential Cluster Analysis. Classified images were rectified as necessary so that all were at the same scale and oriented north-up. Results were analyzed with contingency tables and percent correctly classified (PCC) and Cohen's Kappa (CK) as accuracy indices using CSLANT and ImagePro programs developed for this study. Accuracy analyses were based upon a 1.4 by 6.5 km area with its long axis east-west. Reference data for this subscene total 55,770 15 by 15 m pixels with sixteen cover types, including seven level III forest classes, three level III urban classes, two level II range classes, two water classes, one wetland class and one agriculture class. An initial analysis was made without correcting the 1978 MIRIS reference data to the different dates of the TM, SPOT and SAR data sets. In this analysis, highest overall classification accuracy (PCC) was 87% with the TM data set, with both SPOT and C-Band SAR at 85%, a difference statistically significant at the 0.05 level. When the reference data were corrected for land cover change between 1978 and 1991, classification accuracy with the C-Band SAR data increased to 87%. Classification accuracy differed from sensor to sensor for individual land cover classes, Combining sensors into hypothetical multi-sensor systems resulted in higher accuracies than for any single sensor. Combining LANDSAT -TM and C-Band SAR yielded an overall classification accuracy (PCC) of 92%. The results of this study indicate that C-Band SAR data provide an acceptable substitute for LANDSAT-TM or SPOT data when land cover information is desired of areas where cloud cover obscures the terrain. Even better results can be obtained by integrating TM and C-Band SAR data into a multi-sensor system.

How the Use of the International Classification of Functioning, Disability and Health for Children and Youth Changed the Individualized Education Programs in Portugal

ERIC Educational Resources Information Center

Silveira-Maia, Mónica; Lopes-dos-Santos, Pedro; Sanches-Ferreira, Manuela

2017-01-01

Current Portuguese Public Law No. 3/2008 requires the use of the International Classification of Functioning, Health and Disability for Children and Youth (ICF-CY) as a reference framework to guide assessment and intervention procedures for students with additional support needs. This study explores whether the ICF-CY use fostered multidimensional…

Delineation of marsh types from Corpus Christi Bay, Texas, to Perdido Bay, Alabama, in 2010

USGS Publications Warehouse

Enwright, Nicholas M.; Hartley, Stephen B.; Couvillion, Brady R.; Michael G. Brasher,; Jenneke M. Visser,; Michael K. Mitchell,; Bart M. Ballard,; Mark W. Parr,; Barry C. Wilson,

2015-07-23

This study incorporates about 9,800 ground reference locations collected via helicopter surveys in coastal wetland areas. Decision-tree analyses were used to classify emergent marsh vegetation types by using ground reference data from helicopter vegetation surveys and independent variables such as multitemporal satellite-based multispectral imagery from 2009 to 2011, bare-earth digital elevation models based on airborne light detection and ranging (lidar), alternative contemporary land cover classifications, and other spatially explicit variables. Image objects were created from 2010 National Agriculture Imagery Program color-infrared aerial photography. The final classification is a 10-meter raster dataset that was produced by using a majority filter to classify image objects according to the marsh vegetation type covering the majority of each image object. The classification is dated 2010 because the year is both the midpoint of the classified multitemporal satellite-based imagery (2009–11) and the date of the high-resolution airborne imagery that was used to develop image objects. The seamless classification produced through this work can be used to help develop and refine conservation efforts for priority natural resources.

Accuracy of automatic syndromic classification of coded emergency department diagnoses in identifying mental health-related presentations for public health surveillance.

PubMed

Liljeqvist, Henning T G; Muscatello, David; Sara, Grant; Dinh, Michael; Lawrence, Glenda L

2014-09-23

Syndromic surveillance in emergency departments (EDs) may be used to deliver early warnings of increases in disease activity, to provide situational awareness during events of public health significance, to supplement other information on trends in acute disease and injury, and to support the development and monitoring of prevention or response strategies. Changes in mental health related ED presentations may be relevant to these goals, provided they can be identified accurately and efficiently. This study aimed to measure the accuracy of using diagnostic codes in electronic ED presentation records to identify mental health-related visits. We selected a random sample of 500 records from a total of 1,815,588 ED electronic presentation records from 59 NSW public hospitals during 2010. ED diagnoses were recorded using any of ICD-9, ICD-10 or SNOMED CT classifications. Three clinicians, blinded to the automatically generated syndromic grouping and each other's classification, reviewed the triage notes and classified each of the 500 visits as mental health-related or not. A "mental health problem presentation" for the purposes of this study was defined as any ED presentation where either a mental disorder or a mental health problem was the reason for the ED visit. The combined clinicians' assessment of the records was used as reference standard to measure the sensitivity, specificity, and positive and negative predictive values of the automatic classification of coded emergency department diagnoses. Agreement between the reference standard and the automated coded classification was estimated using the Kappa statistic. Agreement between clinician's classification and automated coded classification was substantial (Kappa = 0.73. 95% CI: 0.58 - 0.87). The automatic syndromic grouping of coded ED diagnoses for mental health-related visits was found to be moderately sensitive (68% 95% CI: 46%-84%) and highly specific at 99% (95% CI: 98%-99.7%) when compared with the reference standard in identifying mental health related ED visits. Positive predictive value was 81% (95% CI: 0.57 - 0.94) and negative predictive value was 98% (95% CI: 0.97-0.99). Mental health presentations identified using diagnoses coded with various classifications in electronic ED presentation records offers sufficient accuracy for application in near real-time syndromic surveillance.

Change classification in SAR time series: a functional approach

NASA Astrophysics Data System (ADS)

Boldt, Markus; Thiele, Antje; Schulz, Karsten; Hinz, Stefan

2017-10-01

Change detection represents a broad field of research in SAR remote sensing, consisting of many different approaches. Besides the simple recognition of change areas, the analysis of type, category or class of the change areas is at least as important for creating a comprehensive result. Conventional strategies for change classification are based on supervised or unsupervised landuse / landcover classifications. The main drawback of such approaches is that the quality of the classification result directly depends on the selection of training and reference data. Additionally, supervised processing methods require an experienced operator who capably selects the training samples. This training step is not necessary when using unsupervised strategies, but nevertheless meaningful reference data must be available for identifying the resulting classes. Consequently, an experienced operator is indispensable. In this study, an innovative concept for the classification of changes in SAR time series data is proposed. Regarding the drawbacks of traditional strategies given above, it copes without using any training data. Moreover, the method can be applied by an operator, who does not have detailed knowledge about the available scenery yet. This knowledge is provided by the algorithm. The final step of the procedure, which main aspect is given by the iterative optimization of an initial class scheme with respect to the categorized change objects, is represented by the classification of these objects to the finally resulting classes. This assignment step is subject of this paper.

Diagnosis and classification of mastocytosis in non-specialized versus reference centres: a Spanish Network on Mastocytosis (REMA) study on 122 patients.

PubMed

Sánchez-Muñoz, Laura; Morgado, Jose M; Álvarez-Twose, Ivan; Matito, Almudena; Garcia-Montero, Andrés C; Teodosio, Cristina; Jara-Acevedo, Maria; Mayado, Andrea; Mollejo, Manuela; Caldas, Carolina; González de Olano, David; Escribano, Luis; Orfao, Alberto

2016-01-01

The diagnosis of 'rare diseases', such as mastocytosis, remains a challenge. Despite this, the precise benefits of referral of mastocytosis patients to highly specialized reference centres are poorly defined and whether patients should be managed at non-specialized versus reference centres remains a matter of debate. To evaluate the quality and efficiency of diagnostic procedures performed at the reference centres for mastocytosis in Spain (REMA) versus other non-reference centres, we retrospectively analysed a series of 122 patients, for the overall degree of agreement obtained for the World Health Organization (WHO) diagnostic and classification criteria betwen the referring and REMA centres. Our results showed that not all WHO diagnostic criteria were frequently investigated at the referring centres. Among the five WHO diagnostic criteria, the highest degree of agreement was obtained for serum tryptase levels [median 90% (95% confidence interval 84-96%)]; in turn, the overall agreement was significantly lower for the major histopathological criterion [80% (72-89%)], and the other three minor criteria: cytomorphology [68% (56-80%)] immunophenotyping of BM mast cells [75% (62-87%)] and detection of the KIT mutation [34% (8-60%)]. Referral of patients with diagnostic suspicion of mastocytosis to a multidisciplinary reference centre improves diagnostic efficiency and quality. © 2015 John Wiley & Sons Ltd.

Body mass index and childhood obesity classification systems: A comparison of the French, International Obesity Task Force (IOTF) and World Health Organization (WHO) references.

PubMed

Kêkê, L M; Samouda, H; Jacobs, J; di Pompeo, C; Lemdani, M; Hubert, H; Zitouni, D; Guinhouya, B C

2015-06-01

This study aims to compare three body mass index (BMI)-based classification systems of childhood obesity: the French, the International Obesity Task Force (IOTF) and the World Health Organization (WHO) references. The study involved 1382 schoolchildren, recruited from the Lille Academic District in France in May 2009 aged 8.4±1.7 years (4.0-12.0 years). Their mean height and body mass were 131.5±10.9cm and 30.7±9.2kg, respectively, resulting in a BMI of 17.4±3.2kg/m(2). The weight status was defined according to the three systems considered in this study. The agreement between these references was tested using the Cohen's kappa coefficient. The prevalence of overweight was higher with the WHO references (20.0%) in comparison with the French references (13.8%; P<0.0001) and the IOTF (16.2%; P≤0.01). A similar result was found with obesity (WHO: 11.6% vs. IOTF: 6.7%; or French references: 6.7%; P<0.0001). Agreement between the three references ranged from "moderate" to "perfect" (0.43≤κ≤1.00; P<0.0001). Kappa coefficients were higher when the three references were used to classify children as obese (0.63≤κ≤1.00; P<0.0001) as compared to classification in the overweight (obesity excluded) category (0.43≤κ≤0.94; P<0.0001). When sex and age categories (4-6 years vs. 7-12 years) were considered to define the overweight status, the lowest kappa coefficient was found between the French and WHO references in boys aged 7-12 years (κ=0.28; P<0.0001), and the highest one in girls aged 7-12 years between the French references and IOTF (κ=0.97; P<0.0001). As for obesity, agreement between the three references ranged from 0.60 to 1.00 (P<0.0001), with the lowest values obtained in the comparison of the WHO references against French references or IOTF among boys aged 7-12 years (κ=0.60; P<0.0001). Overall, the WHO references yield an overestimation in overweight and/or obesity within this sample of schoolchildren as compared to the French references and the IOTF. The magnitude of agreement coefficients between the three references depends on of both sex and age categories. The French references seem to be in rather close agreement with the IOTF in defining overweight, especially in 7-12-year-old children. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Study on Biopharmaceutics Classification and Oral Bioavailability of a Novel Multikinase Inhibitor NCE for Cancer Therapy

PubMed Central

Yang, Yang; Fan, Chun-Mei; He, Xuan; Ren, Ke; Zhang, Jin-Kun; He, Ying-Ju; Yu, Luo-Ting; Zhao, Ying-Lan; Gong, Chang-Yang; Zheng, Yu; Song, Xiang-Rong; Zeng, Jun

2014-01-01

Specific biopharmaceutics classification investigation and study on phamacokinetic profile of a novel drug candidate (2-methylcarbamoyl-4-{4-[3- (trifluoromethyl) benzamido] phenoxy} pyridinium 4-methylbenzenesulfonate monohydrate, NCE) were carried out. Equilibrium solubility and intrinsic dissolution rate (IDR) of NCE were estimated in different phosphate buffers. Effective intestinal permeability (Peff) of NCE was determined using single-pass intestinal perfusion technique in rat duodenum, jejunum and ileum at three concentrations. Theophylline (high permeability) and ranitidine (low permeability) were also applied to access the permeability of NCE as reference compounds. The bioavailability after intragastrical and intravenous administration was measured in beagle dogs. The solubility of NCE in tested phosphate buffers was quite low with the maximum solubility of 81.73 μg/mL at pH 1.0. The intrinsic dissolution ratio of NCE was 1 × 10−4 mg·min−1·cm−2. The Peff value of NCE in all intestinal segments was more proximate to the high-permeability reference theophylline. Therefore, NCE was classified as class II drug according to Biopharmaceutics Classification System due to its low solubility and high intestinal permeability. In addition, concentration-dependent permeability was not observed in all the segments, indicating that there might be passive transportation for NCE. The absolute oral bioavailability of NCE in beagle dogs was 26.75%. Therefore, dissolution promotion will be crucial for oral formulation development and intravenous administration route will also be suggested for further NCE formulation development. All the data would provide a reference for biopharmaceutics classification research of other novel drug candidates. PMID:24776763

Study on biopharmaceutics classification and oral bioavailability of a novel multikinase inhibitor NCE for cancer therapy.

PubMed

Yang, Yang; Fan, Chun-Mei; He, Xuan; Ren, Ke; Zhang, Jin-Kun; He, Ying-Ju; Yu, Luo-Ting; Zhao, Ying-Lan; Gong, Chang-Yang; Zheng, Yu; Song, Xiang-Rong; Zeng, Jun

2014-04-25

Specific biopharmaceutics classification investigation and study on phamacokinetic profile of a novel drug candidate (2-methylcarbamoyl-4-{4-[3- (trifluoromethyl) benzamido] phenoxy} pyridinium 4-methylbenzenesulfonate monohydrate, NCE) were carried out. Equilibrium solubility and intrinsic dissolution rate (IDR) of NCE were estimated in different phosphate buffers. Effective intestinal permeability (P(eff)) of NCE was determined using single-pass intestinal perfusion technique in rat duodenum, jejunum and ileum at three concentrations. Theophylline (high permeability) and ranitidine (low permeability) were also applied to access the permeability of NCE as reference compounds. The bioavailability after intragastrical and intravenous administration was measured in beagle dogs. The solubility of NCE in tested phosphate buffers was quite low with the maximum solubility of 81.73 μg/mL at pH 1.0. The intrinsic dissolution ratio of NCE was 1 × 10⁻⁴ mg·min⁻¹·cm⁻². The P(eff) value of NCE in all intestinal segments was more proximate to the high-permeability reference theophylline. Therefore, NCE was classified as class II drug according to Biopharmaceutics Classification System due to its low solubility and high intestinal permeability. In addition, concentration-dependent permeability was not observed in all the segments, indicating that there might be passive transportation for NCE. The absolute oral bioavailability of NCE in beagle dogs was 26.75%. Therefore, dissolution promotion will be crucial for oral formulation development and intravenous administration route will also be suggested for further NCE formulation development. All the data would provide a reference for biopharmaceutics classification research of other novel drug candidates.

Automatic adventitious respiratory sound analysis: A systematic review

PubMed Central

Bowyer, Stuart; Rodriguez-Villegas, Esther

2017-01-01

Background Automatic detection or classification of adventitious sounds is useful to assist physicians in diagnosing or monitoring diseases such as asthma, Chronic Obstructive Pulmonary Disease (COPD), and pneumonia. While computerised respiratory sound analysis, specifically for the detection or classification of adventitious sounds, has recently been the focus of an increasing number of studies, a standardised approach and comparison has not been well established. Objective To provide a review of existing algorithms for the detection or classification of adventitious respiratory sounds. This systematic review provides a complete summary of methods used in the literature to give a baseline for future works. Data sources A systematic review of English articles published between 1938 and 2016, searched using the Scopus (1938-2016) and IEEExplore (1984-2016) databases. Additional articles were further obtained by references listed in the articles found. Search terms included adventitious sound detection, adventitious sound classification, abnormal respiratory sound detection, abnormal respiratory sound classification, wheeze detection, wheeze classification, crackle detection, crackle classification, rhonchi detection, rhonchi classification, stridor detection, stridor classification, pleural rub detection, pleural rub classification, squawk detection, and squawk classification. Study selection Only articles were included that focused on adventitious sound detection or classification, based on respiratory sounds, with performance reported and sufficient information provided to be approximately repeated. Data extraction Investigators extracted data about the adventitious sound type analysed, approach and level of analysis, instrumentation or data source, location of sensor, amount of data obtained, data management, features, methods, and performance achieved. Data synthesis A total of 77 reports from the literature were included in this review. 55 (71.43%) of the studies focused on wheeze, 40 (51.95%) on crackle, 9 (11.69%) on stridor, 9 (11.69%) on rhonchi, and 18 (23.38%) on other sounds such as pleural rub, squawk, as well as the pathology. Instrumentation used to collect data included microphones, stethoscopes, and accelerometers. Several references obtained data from online repositories or book audio CD companions. Detection or classification methods used varied from empirically determined thresholds to more complex machine learning techniques. Performance reported in the surveyed works were converted to accuracy measures for data synthesis. Limitations Direct comparison of the performance of surveyed works cannot be performed as the input data used by each was different. A standard validation method has not been established, resulting in different works using different methods and performance measure definitions. Conclusion A review of the literature was performed to summarise different analysis approaches, features, and methods used for the analysis. The performance of recent studies showed a high agreement with conventional non-automatic identification. This suggests that automated adventitious sound detection or classification is a promising solution to overcome the limitations of conventional auscultation and to assist in the monitoring of relevant diseases. PMID:28552969

Ensemble of sparse classifiers for high-dimensional biological data.

PubMed

Kim, Sunghan; Scalzo, Fabien; Telesca, Donatello; Hu, Xiao

2015-01-01

Biological data are often high in dimension while the number of samples is small. In such cases, the performance of classification can be improved by reducing the dimension of data, which is referred to as feature selection. Recently, a novel feature selection method has been proposed utilising the sparsity of high-dimensional biological data where a small subset of features accounts for most variance of the dataset. In this study we propose a new classification method for high-dimensional biological data, which performs both feature selection and classification within a single framework. Our proposed method utilises a sparse linear solution technique and the bootstrap aggregating algorithm. We tested its performance on four public mass spectrometry cancer datasets along with two other conventional classification techniques such as Support Vector Machines and Adaptive Boosting. The results demonstrate that our proposed method performs more accurate classification across various cancer datasets than those conventional classification techniques.

46 CFR 126.235 - Alternate compliance.

Code of Federal Regulations, 2010 CFR

2010-10-01

... purposes of this section, a list of authorized classification societies, including information for ordering copies of approved classification society rules and supplements, is available from Commandant (CG-5212.... Approved classification society rules and supplements are incorporated by reference into 46 CFR 8.110(b...

46 CFR 126.235 - Alternate compliance.

Code of Federal Regulations, 2011 CFR

2011-10-01

... purposes of this section, a list of authorized classification societies, including information for ordering copies of approved classification society rules and supplements, is available from Commandant (CG-5212.... Approved classification society rules and supplements are incorporated by reference into 46 CFR 8.110(b...

46 CFR 91.15-5 - Alternate compliance.

Code of Federal Regulations, 2010 CFR

2010-10-01

... this section, a list of authorized classification societies, including information for ordering copies of approved classification society rules and supplements, is available from Commandant (CG-521), 2100.... Approved classification society rules and supplements are incorporated by reference into 46 CFR 8.110(b...

46 CFR 91.15-5 - Alternate compliance.

Code of Federal Regulations, 2011 CFR

2011-10-01

... this section, a list of authorized classification societies, including information for ordering copies of approved classification society rules and supplements, is available from Commandant (CG-521), 2100.... Approved classification society rules and supplements are incorporated by reference into 46 CFR 8.110(b...

A classification of ecological boundaries

USGS Publications Warehouse

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.

Mapping ecological states in a complex environment

NASA Astrophysics Data System (ADS)

Steele, C. M.; Bestelmeyer, B.; Burkett, L. M.; Ayers, E.; Romig, K.; Slaughter, A.

2013-12-01

The vegetation of northern Chihuahuan Desert rangelands is sparse, heterogeneous and for most of the year, consists of a large proportion of non-photosynthetic material. The soils in this area are spectrally bright and variable in their reflectance properties. Both factors provide challenges to the application of remote sensing for estimating canopy variables (e.g., leaf area index, biomass, percentage canopy cover, primary production). Additionally, with reference to current paradigms of rangeland health assessment, remotely-sensed estimates of canopy variables have limited practical use to the rangeland manager if they are not placed in the context of ecological site and ecological state. To address these challenges, we created a multifactor classification system based on the USDA-NRCS ecological site schema and associated state-and-transition models to map ecological states on desert rangelands in southern New Mexico. Applying this system using per-pixel image processing techniques and multispectral, remotely sensed imagery raised other challenges. Per-pixel image classification relies upon the spectral information in each pixel alone, there is no reference to the spatial context of the pixel and its relationship with its neighbors. Ecological state classes may have direct relevance to managers but the non-unique spectral properties of different ecological state classes in our study area means that per-pixel classification of multispectral data performs poorly in discriminating between different ecological states. We found that image interpreters who are familiar with the landscape and its associated ecological site descriptions perform better than per-pixel classification techniques in assigning ecological states. However, two important issues affect manual classification methods: subjectivity of interpretation and reproducibility of results. An alternative to per-pixel classification and manual interpretation is object-based image analysis. Object-based image analysis provides a platform for classification that more closely resembles human recognition of objects within a remotely sensed image. The analysis presented here compares multiple thematic maps created for test locations on the USDA-ARS Jornada Experimental Range ranch. Three study sites in different pastures, each 300 ha in size, were selected for comparison on the basis of their ecological site type (';Clayey', ';Sandy' and a combination of both) and the degree of complexity of vegetation cover. Thematic maps were produced for each study site using (i) manual interpretation of digital aerial photography (by five independent interpreters); (ii) object-oriented, decision-tree classification of fine and moderate spatial resolution imagery (Quickbird; Landsat Thematic Mapper) and (iii) ground survey. To identify areas of uncertainty, we compared agreement in location, areal extent and class assignation between 5 independently produced, manually-digitized ecological state maps and with the map created from ground survey. Location, areal extent and class assignation of the map produced by object-oriented classification was also assessed with reference to the ground survey map.

Assessing the impact of adjusting for maturity in weight status classification in a cross-sectional sample of UK children.

PubMed

Gillison, Fiona; Cumming, Sean; Standage, Martyn; Barnaby, Catherine; Katzmarzyk, Peter

2017-06-26

To compare the weight categorisation of a cohort of UK children using standard procedures (ie, comparing body mass index (BMI) centiles to age-matched UK reference data) versus an approach adjusted for maturation status (ie, matching relative to biological age). Analysis of data collected from an observational study of UK primary school children. Schools in South West England. Four hundred and seven 9-11 year-old children (98% white British). Weight status was classified using BMI centiles using (1) sex and chronological age-matched referents and (2) sex and biological age-matched referents (based on % of predicted adult stature) relative to UK 1990 reference growth charts. For both approaches, children were classified as a normal weight if >2nd centile and <85thcentile, overweight if 85th and <95thcentiles, and obese if ≥95thcentile. Fifty-one children (12.5%) were overweight, and a further 51 obese (12.5%) according to standard chronological age-matched classifications. Adjustment for maturity resulted in 32% of overweight girls, and 15% of overweight boys being reclassified as a normal weight, and 11% and 8% of obese girls and boys, respectively, being reclassified as overweight. Early maturing children were 4.9 times more likely to be reclassified from overweight to normal weight than 'on-time' maturers (OR 95% CI 1.3 to 19). Incorporating assessments of maturational status into weight classification resulted in significant changes to the classification of early-maturing adolescents. Further research exploring the implications for objective health risk and well-being is needed. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A Comparative Study of Different EEG Reference Choices for Diagnosing Unipolar Depression.

PubMed

Mumtaz, Wajid; Malik, Aamir Saeed

2018-06-02

The choice of an electroencephalogram (EEG) reference has fundamental importance and could be critical during clinical decision-making because an impure EEG reference could falsify the clinical measurements and subsequent inferences. In this research, the suitability of three EEG references was compared while classifying depressed and healthy brains using a machine-learning (ML)-based validation method. In this research, the EEG data of 30 unipolar depressed subjects and 30 age-matched healthy controls were recorded. The EEG data were analyzed in three different EEG references, the link-ear reference (LE), average reference (AR), and reference electrode standardization technique (REST). The EEG-based functional connectivity (FC) was computed. Also, the graph-based measures, such as the distances between nodes, minimum spanning tree, and maximum flow between the nodes for each channel pair, were calculated. An ML scheme provided a mechanism to compare the performances of the extracted features that involved a general framework such as the feature extraction (graph-based theoretic measures), feature selection, classification, and validation. For comparison purposes, the performance metrics such as the classification accuracies, sensitivities, specificities, and F scores were computed. When comparing the three references, the diagnostic accuracy showed better performances during the REST, while the LE and AR showed less discrimination between the two groups. Based on the results, it can be concluded that the choice of appropriate reference is critical during the clinical scenario. The REST reference is recommended for future applications of EEG-based diagnosis of mental illnesses.

A Review of Major Nursing Vocabularies and the Extent to Which They Have the Characteristics Required for Implementation in Computer-based Systems

PubMed Central

Henry, Suzanne Bakken; Warren, Judith J.; Lange, Linda; Button, Patricia

1998-01-01

Building on the work of previous authors, the Computer-based Patient Record Institute (CPRI) Work Group on Codes and Structures has described features of a classification scheme for implementation within a computer-based patient record. The authors of the current study reviewed the evaluation literature related to six major nursing vocabularies (the North American Nursing Diagnosis Association Taxonomy 1, the Nursing Interventions Classification, the Nursing Outcomes Classification, the Home Health Care Classification, the Omaha System, and the International Classification for Nursing Practice) to determine the extent to which the vocabularies include the CPRI features. None of the vocabularies met all criteria. The Omaha System, Home Health Care Classification, and International Classification for Nursing Practice each included five features. Criteria not fully met by any systems were clear and non-redundant representation of concepts, administrative cross-references, syntax and grammar, synonyms, uncertainty, context-free identifiers, and language independence. PMID:9670127

Rapid identification of oral Actinomyces species cultivated from subgingival biofilm by MALDI-TOF-MS

PubMed Central

Stingu, Catalina S.; Borgmann, Toralf; Rodloff, Arne C.; Vielkind, Paul; Jentsch, Holger; Schellenberger, Wolfgang; Eschrich, Klaus

2015-01-01

Background Actinomyces are a common part of the residential flora of the human intestinal tract, genitourinary system and skin. Isolation and identification of Actinomyces by conventional methods is often difficult and time consuming. In recent years, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) has become a rapid and simple method to identify bacteria. Objective The present study evaluated a new in-house algorithm using MALDI-TOF-MS for rapid identification of different species of oral Actinomyces cultivated from subgingival biofilm. Design Eleven reference strains and 674 clinical strains were used in this study. All the strains were preliminarily identified using biochemical methods and then subjected to MALDI-TOF-MS analysis using both similarity-based analysis and classification methods (support vector machine [SVM]). The genotype of the reference strains and of 232 clinical strains was identified by sequence analysis of the 16S ribosomal RNA (rRNA). Results The sequence analysis of the 16S rRNA gene of all references strains confirmed their previous identification. The MALDI-TOF-MS spectra obtained from the reference strains and the other clinical strains undoubtedly identified as Actinomyces by 16S rRNA sequencing were used to create the mass spectra reference database. Already a visual inspection of the mass spectra of different species reveals both similarities and differences. However, the differences between them are not large enough to allow a reliable differentiation by similarity analysis. Therefore, classification methods were applied as an alternative approach for differentiation and identification of Actinomyces at the species level. A cross-validation of the reference database representing 14 Actinomyces species yielded correct results for all species which were represented by more than two strains in the database. Conclusions Our results suggest that a combination of MALDI-TOF-MS with powerful classification algorithms, such as SVMs, provide a useful tool for the differentiation and identification of oral Actinomyces. PMID:25597306

(GTG)5-PCR reference framework for acetic acid bacteria.

PubMed

Papalexandratou, Zoi; Cleenwerck, Ilse; De Vos, Paul; De Vuyst, Luc

2009-11-01

One hundred and fifty-eight strains of acetic acid bacteria (AAB) were subjected to (GTG)(5)-PCR fingerprinting to construct a reference framework for their rapid classification and identification. Most of them clustered according to their respective taxonomic designation; others had to be reclassified based on polyphasic data. This study shows the usefulness of the method to determine the taxonomic and phylogenetic relationships among AAB and to study the AAB diversity of complex ecosystems.

Analysis of the Local Lymph Node Assay (LLNA) variability for assessing the prediction of skin sensitisation potential and potency of chemicals with non-animal approaches.

PubMed

Dumont, Coralie; Barroso, João; Matys, Izabela; Worth, Andrew; Casati, Silvia

2016-08-01

The knowledge of the biological mechanisms leading to the induction of skin sensitisation has favoured in recent years the development of alternative non-animal methods. During the formal validation process, results from the Local Lymph Node Assay (LLNA) are generally used as reference data to assess the predictive capacity of the non-animal tests. This study reports an analysis of the variability of the LLNA for a set of chemicals for which multiple studies are available and considers three hazard classification schemes: POS/NEG, GHS/CLP and ECETOC. As the type of vehicle used in a LLNA study is known to influence to some extent the results, two analyses were performed: considering the solvent used to test the chemicals and without considering the solvent. The results show that the number of discordant classifications increases when a chemical is tested in more than one solvent. Moreover, it can be concluded that study results leading to classification in the strongest classes (1A and EXT) seem to be more reliable than those in the weakest classes. This study highlights the importance of considering the variability of the reference data when evaluating non-animal tests. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Automatic adventitious respiratory sound analysis: A systematic review.

PubMed

Pramono, Renard Xaviero Adhi; Bowyer, Stuart; Rodriguez-Villegas, Esther

2017-01-01

Automatic detection or classification of adventitious sounds is useful to assist physicians in diagnosing or monitoring diseases such as asthma, Chronic Obstructive Pulmonary Disease (COPD), and pneumonia. While computerised respiratory sound analysis, specifically for the detection or classification of adventitious sounds, has recently been the focus of an increasing number of studies, a standardised approach and comparison has not been well established. To provide a review of existing algorithms for the detection or classification of adventitious respiratory sounds. This systematic review provides a complete summary of methods used in the literature to give a baseline for future works. A systematic review of English articles published between 1938 and 2016, searched using the Scopus (1938-2016) and IEEExplore (1984-2016) databases. Additional articles were further obtained by references listed in the articles found. Search terms included adventitious sound detection, adventitious sound classification, abnormal respiratory sound detection, abnormal respiratory sound classification, wheeze detection, wheeze classification, crackle detection, crackle classification, rhonchi detection, rhonchi classification, stridor detection, stridor classification, pleural rub detection, pleural rub classification, squawk detection, and squawk classification. Only articles were included that focused on adventitious sound detection or classification, based on respiratory sounds, with performance reported and sufficient information provided to be approximately repeated. Investigators extracted data about the adventitious sound type analysed, approach and level of analysis, instrumentation or data source, location of sensor, amount of data obtained, data management, features, methods, and performance achieved. A total of 77 reports from the literature were included in this review. 55 (71.43%) of the studies focused on wheeze, 40 (51.95%) on crackle, 9 (11.69%) on stridor, 9 (11.69%) on rhonchi, and 18 (23.38%) on other sounds such as pleural rub, squawk, as well as the pathology. Instrumentation used to collect data included microphones, stethoscopes, and accelerometers. Several references obtained data from online repositories or book audio CD companions. Detection or classification methods used varied from empirically determined thresholds to more complex machine learning techniques. Performance reported in the surveyed works were converted to accuracy measures for data synthesis. Direct comparison of the performance of surveyed works cannot be performed as the input data used by each was different. A standard validation method has not been established, resulting in different works using different methods and performance measure definitions. A review of the literature was performed to summarise different analysis approaches, features, and methods used for the analysis. The performance of recent studies showed a high agreement with conventional non-automatic identification. This suggests that automated adventitious sound detection or classification is a promising solution to overcome the limitations of conventional auscultation and to assist in the monitoring of relevant diseases.

A scheme for the classification of explosions in the chemical process industry.

PubMed

Abbasi, Tasneem; Pasman, H J; Abbasi, S A

2010-02-15

All process industry accidents fall under three broad categories-fire, explosion, and toxic release. Of these fire is the most common, followed by explosions. Within these broad categories occur a large number of sub-categories, each depicting a specific sub-type of a fire/explosion/toxic release. But whereas clear and self-consistent sub-classifications exist for fires and toxic releases, the situation is not as clear vis a vis explosions. In this paper the inconsistencies and/or shortcomings associated with the classification of different types of explosions, which are seen even in otherwise highly authentic and useful reference books on process safety, are reviewed. In its context a new classification is attempted which may, hopefully, provide a frame-of-reference for the future.

How can Smartphone-Based Internet Data Support Animal Ecology Fieldtrip?

NASA Astrophysics Data System (ADS)

Kurniawan, I. S.; Tapilow, F. S.; Hidayat, T.

2017-09-01

Identification and classification skills must be owned by the students. In animal ecology course, the identification and classification skills are necessary to study animals. This experimental study aims to describe the identification and classification skills of students on animal ecology field trip to studying various bird species using smartphone-based internet data. Using Involving 63 students divided into 7 groups for each observation station. Data of birds were sampled using line transect method (5000 meters/station). The results showed the identification and classification skills of students are in sufficient categories. Most students have difficulties because of the limitations of data on the internet about birds. In general, students support the use of smartphones in field trip activities. The results of this study can be used as a reference for the development of learning using smartphones in the future by developing application about birds. The outline, smartphones can be used as a method of alternative learning but needs to be developed for some special purposes.

Map Classification: A Comparison of Schemes with Special Reference to the Continent of Africa. Occasional Papers, Number 154.

ERIC Educational Resources Information Center

Merrett, Christopher E.

This guide to the theory and practice of map classification begins with a discussion of the filing of maps and the function of map classification based on area and theme as illustrated by four maps of Africa. The description of the various classification systems which follows is divided into book schemes with provision for maps (including Dewey…

Unbiased Taxonomic Annotation of Metagenomic Samples

PubMed Central

Fosso, Bruno; Pesole, Graziano; Rosselló, Francesc

2018-01-01

Abstract The classification of reads from a metagenomic sample using a reference taxonomy is usually based on first mapping the reads to the reference sequences and then classifying each read at a node under the lowest common ancestor of the candidate sequences in the reference taxonomy with the least classification error. However, this taxonomic annotation can be biased by an imbalanced taxonomy and also by the presence of multiple nodes in the taxonomy with the least classification error for a given read. In this article, we show that the Rand index is a better indicator of classification error than the often used area under the receiver operating characteristic (ROC) curve and F-measure for both balanced and imbalanced reference taxonomies, and we also address the second source of bias by reducing the taxonomic annotation problem for a whole metagenomic sample to a set cover problem, for which a logarithmic approximation can be obtained in linear time and an exact solution can be obtained by integer linear programming. Experimental results with a proof-of-concept implementation of the set cover approach to taxonomic annotation in a next release of the TANGO software show that the set cover approach further reduces ambiguity in the taxonomic annotation obtained with TANGO without distorting the relative abundance profile of the metagenomic sample. PMID:29028181

Study of sensor spectral responses and data processing algorithms and architectures for onboard feature identification

NASA Technical Reports Server (NTRS)

Huck, F. O.; Davis, R. E.; Fales, C. L.; Aherron, R. M.

1982-01-01

A computational model of the deterministic and stochastic processes involved in remote sensing is used to study spectral feature identification techniques for real-time onboard processing of data acquired with advanced earth-resources sensors. Preliminary results indicate that: Narrow spectral responses are advantageous; signal normalization improves mean-square distance (MSD) classification accuracy but tends to degrade maximum-likelihood (MLH) classification accuracy; and MSD classification of normalized signals performs better than the computationally more complex MLH classification when imaging conditions change appreciably from those conditions during which reference data were acquired. The results also indicate that autonomous categorization of TM signals into vegetation, bare land, water, snow and clouds can be accomplished with adequate reliability for many applications over a reasonably wide range of imaging conditions. However, further analysis is required to develop computationally efficient boundary approximation algorithms for such categorization.

Studies of Millimeter-Wave Diffraction Devices and Materials

DTIC Science & Technology

1984-12-28

7.0 REFERENCES 1. Andrenko, S . d., Devyatkov, Acad. N. D., and Shestopalov, V. P., "Millimeter Field Band Antenna Arrays", Dokl. Akad. 4auk SSSR, Vol... S UNCLASSTFIED I* .RIT.Y CL.ASSIFICATION OF THIS PAGE REPORT DOCUMENTATION PAGE :kFPOO- SEURITY CLASSIFICATION 1-b. RESTRICTIVE MARKINGS .EM...State and ZIP Code) 10. SOURCE OF FUNDIN.G NOS. ______ C)c \\~ S PROGRAM PROJECT TASK WORK UNIT 2~~V \\~ ~(~ELEMENT NO. NO. No. NO. ATEinciude Security

[The Goldthorpe Social Class Classification: reference framework for a proposal for the measurement of social class by the Working Group of the Spanish Society of Epidemiology].

PubMed

Regidor, E

2001-01-01

Two of the most important theory-based social class classifications are that of the neo-Weberian Goldthorpe and that of the neo-Marxist Wright. The social class classification proposal of the SES Working Group employed the Goldthorpe schema as a reference due to the empirical and mainly pragmatic aspects involved. In this article, these aspects are discussed and it is also discussed the problem of the validation of the measurements of social class and the problem of the use of the social class as an independent variable.

Revisiting the taxonomical classification of Porcine Circovirus type 2 (PCV2): still a real challenge.

PubMed

Franzo, Giovanni; Cortey, Martí; Olvera, Alex; Novosel, Dinko; Castro, Alessandra Marnie Martins Gomes De; Biagini, Philippe; Segalés, Joaquim; Drigo, Michele

2015-08-28

PCV2 has emerged as one of the most devastating viral infections of swine farming, causing a relevant economic impact due to direct losses and control strategies expenses. Epidemiological and experimental studies have evidenced that genetic diversity is potentially affecting the virulence of PVC2. The growing number of PCV2 complete genomes and partial sequences available at GenBank questioned the accepted PCV2 classification. Nine hundred seventy five PCV2 complete genomes and 1,270 ORF2 sequences available from GenBank were subjected to recombination, PASC and phylogenetic analyses and results were used for comparison with previous classification scheme. The outcome of these analyses favors the recognition of four genotypes on the basis of ORF2 sequences, namely PCV2a, PCV2b, PCV2c and PCV2d-mPCV2b. To deal with the difficulty of founding an unambiguous classification and accounting the impossibility to define a p-distance cut-off, a set of reference sequences that could be used in further phylogenetic studies for PCV2 genotyping was established. Being aware that extensive phylogenetic analyses are time-consuming and often impracticable during routine diagnostic activity, ORF2 nucleotide positions adequately conserved in the reference sequences were identified and reported to allow a quick genotype differentiation. Globally, the present work provides an updated scenario of PCV2 genotypes distribution and, based on the limits of the previous classification criteria, proposes new rapid and effective schemes for differentiating the four defined PCV2 genotypes.

Classifications of Acute Scaphoid Fractures: A Systematic Literature Review.

PubMed

Ten Berg, Paul W; Drijkoningen, Tessa; Strackee, Simon D; Buijze, Geert A

2016-05-01

Background In the lack of consensus, surgeon-based preference determines how acute scaphoid fractures are classified. There is a great variety of classification systems with considerable controversies. Purposes The purpose of this study was to provide an overview of the different classification systems, clarifying their subgroups and analyzing their popularity by comparing citation indexes. The intention was to improve data comparison between studies using heterogeneous fracture descriptions. Methods We performed a systematic review of the literature based on a search of medical literature from 1950 to 2015, and a manual search using the reference lists in relevant book chapters. Only original descriptions of classifications of acute scaphoid fractures in adults were included. Popularity was based on citation index as reported in the databases of Web of Science (WoS) and Google Scholar. Articles that were cited <10 times in WoS were excluded. Results Our literature search resulted in 308 potentially eligible descriptive reports of which 12 reports met the inclusion criteria. We distinguished 13 different (sub) classification systems based on (1) fracture location, (2) fracture plane orientation, and (3) fracture stability/displacement. Based on citations numbers, the Herbert classification was most popular, followed by the Russe and Mayo classifications. All classification systems were based on plain radiography. Conclusions Most classification systems were based on fracture location, displacement, or stability. Based on the controversy and limited reliability of current classification systems, suggested research areas for an updated classification include three-dimensional fracture pattern etiology and fracture fragment mobility assessed by dynamic imaging.

Rapid automated classification of anesthetic depth levels using GPU based parallelization of neural networks.

PubMed

Peker, Musa; Şen, Baha; Gürüler, Hüseyin

2015-02-01

The effect of anesthesia on the patient is referred to as depth of anesthesia. Rapid classification of appropriate depth level of anesthesia is a matter of great importance in surgical operations. Similarly, accelerating classification algorithms is important for the rapid solution of problems in the field of biomedical signal processing. However numerous, time-consuming mathematical operations are required when training and testing stages of the classification algorithms, especially in neural networks. In this study, to accelerate the process, parallel programming and computing platform (Nvidia CUDA) facilitates dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU) was utilized. The system was employed to detect anesthetic depth level on related electroencephalogram (EEG) data set. This dataset is rather complex and large. Moreover, the achieving more anesthetic levels with rapid response is critical in anesthesia. The proposed parallelization method yielded high accurate classification results in a faster time.

Sunspot Pattern Classification using PCA and Neural Networks (Poster)

NASA Technical Reports Server (NTRS)

Rajkumar, T.; Thompson, D. E.; Slater, G. L.

2005-01-01

The sunspot classification scheme presented in this paper is considered as a 2-D classification problem on archived datasets, and is not a real-time system. As a first step, it mirrors the Zuerich/McIntosh historical classification system and reproduces classification of sunspot patterns based on preprocessing and neural net training datasets. Ultimately, the project intends to move from more rudimentary schemes, to develop spatial-temporal-spectral classes derived by correlating spatial and temporal variations in various wavelengths to the brightness fluctuation spectrum of the sun in those wavelengths. Once the approach is generalized, then the focus will naturally move from a 2-D to an n-D classification, where "n" includes time and frequency. Here, the 2-D perspective refers both to the actual SOH0 Michelson Doppler Imager (MDI) images that are processed, but also refers to the fact that a 2-D matrix is created from each image during preprocessing. The 2-D matrix is the result of running Principal Component Analysis (PCA) over the selected dataset images, and the resulting matrices and their eigenvalues are the objects that are stored in a database, classified, and compared. These matrices are indexed according to the standard McIntosh classification scheme.

75 FR 53339 - Notice of Realty Action; Recreation and Public Purposes Act Classification for Conveyance of...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-31

... existing landfill. DATES: Interested parties may submit written comments regarding this classification for... . Please reference ``Conveyance of Federal Land to Emery County for Expansion of an Existing Landfill'' on... suitability of the land for the expansion of the existing county landfill. Comments on the classification are...

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery.

PubMed

Belgiu, Mariana; Dr Guţ, Lucian; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery

PubMed Central

Belgiu, Mariana; Drǎguţ, Lucian; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules. PMID:24623959

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery

NASA Astrophysics Data System (ADS)

Belgiu, Mariana; ǎguţ, Lucian, , Dr; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.

Validation of a systems-actuarial computer process for multidimensional classification of child psychopathology.

PubMed

McDermott, P A; Hale, R L

1982-07-01

Tested diagnostic classifications of child psychopathology produced by a computerized technique known as multidimensional actuarial classification (MAC) against the criterion of expert psychological opinion. The MAC program applies series of statistical decision rules to assess the importance of and relationships among several dimensions of classification, i.e., intellectual functioning, academic achievement, adaptive behavior, and social and behavioral adjustment, to perform differential diagnosis of children's mental retardation, specific learning disabilities, behavioral and emotional disturbance, possible communication or perceptual-motor impairment, and academic under- and overachievement in reading and mathematics. Classifications rendered by MAC are compared to those offered by two expert child psychologists for cases of 73 children referred for psychological services. Experts' agreement with MAC was significant for all classification areas, as was MAC's agreement with the experts held as a conjoint reference standard. Whereas the experts' agreement with MAC averaged 86.0% above chance, their agreement with one another averaged 76.5% above chance. Implications of the findings are explored and potential advantages of the systems-actuarial approach are discussed.

Indirect determination of particle shape of fine aggregate.

DOT National Transportation Integrated Search

1973-01-01

Three methods developed by various agencies for measuring indirectly the particle shapes of fine aggregates were used along with a visual classification procedure to study aggregates from eight commercial sources along with a reference sand. The meth...

(GTG)5-PCR fingerprinting for the classification and identification of coagulase-negative Staphylococcus species from bovine milk and teat apices: a comparison of type strains and field isolates.

PubMed

Braem, G; De Vliegher, S; Supré, K; Haesebrouck, F; Leroy, F; De Vuyst, L

2011-01-10

Due to significant financial losses in the dairy cattle farming industry caused by mastitis and the possible influence of coagulase-negative staphylococci (CNS) in the development of this disease, accurate identification methods are needed that untangle the different species of the diverse CNS group. In this study, 39 Staphylococcus type strains and 253 field isolates were subjected to (GTG)(5)-PCR fingerprinting to construct a reference framework for the classification and identification of different CNS from (sub)clinical milk samples and teat apices swabs. Validation of the reference framework was performed by dividing the field isolates in two separate groups and testing whether one group of field isolates, in combination with type strains, could be used for a correct classification and identification of a second group of field isolates. (GTG)(5)-PCR fingerprinting achieved a typeability of 94.7% and an accuracy of 94.3% compared to identifications based on gene sequencing. The study shows the usefulness of the method to determine the identity of bovine Staphylococcus species, provided an identification framework updated with field isolates is available. Copyright © 2010 Elsevier B.V. All rights reserved.

Reflecting on the structure of soil classification systems: insights from a proposal for integrating subsoil data into soil information systems

NASA Astrophysics Data System (ADS)

Dondeyne, Stefaan; Juilleret, Jérôme; Vancampenhout, Karen; Deckers, Jozef; Hissler, Christophe

2017-04-01

Classification of soils in both World Reference Base for soil resources (WRB) and Soil Taxonomy hinges on the identification of diagnostic horizons and characteristics. However as these features often occur within the first 100 cm, these classification systems convey little information on subsoil characteristics. An integrated knowledge of the soil, soil-to-substratum and deeper substratum continuum is required when dealing with environmental issues such as vegetation ecology, water quality or the Critical Zone in general. Therefore, we recently proposed a classification system of the subsolum complementing current soil classification systems. By reflecting on the structure of the subsoil classification system which is inspired by WRB, we aim at fostering a discussion on some potential future developments of WRB. For classifying the subsolum we define Regolite, Saprolite, Saprock and Bedrock as four Subsolum Reference Groups each corresponding to different weathering stages of the subsoil. Principal qualifiers can be used to categorize intergrades of these Subsoil Reference Groups while morphologic and lithologic characteristics can be presented with supplementary qualifiers. We argue that adopting a low hierarchical structure - akin to WRB and in contrast to a strong hierarchical structure as in Soil Taxonomy - offers the advantage of having an open classification system avoiding the need for a priori knowledge of all possible combinations which may be encountered in the field. Just as in WRB we also propose to use principal and supplementary qualifiers as a second level of classification. However, in contrast to WRB we propose to reserve the principal qualifiers for intergrades and to regroup the supplementary qualifiers into thematic categories (morphologic or lithologic). Structuring the qualifiers in this manner should facilitate the integration and handling of both soil and subsoil classification units into soil information systems and calls for paying attention to these structural issues in future developments of WRB.

Real-Time Food Authentication Using a Miniature Mass Spectrometer.

PubMed

Gerbig, Stefanie; Neese, Stephan; Penner, Alexander; Spengler, Bernhard; Schulz, Sabine

2017-10-17

Food adulteration is a threat to public health and the economy. In order to determine food adulteration efficiently, rapid and easy-to-use on-site analytical methods are needed. In this study, a miniaturized mass spectrometer in combination with three ambient ionization methods was used for food authentication. The chemical fingerprints of three milk types, five fish species, and two coffee types were measured using electrospray ionization, desorption electrospray ionization, and low temperature plasma ionization. Minimum sample preparation was needed for the analysis of liquid and solid food samples. Mass spectrometric data was processed using the laboratory-built software MS food classifier, which allows for the definition of specific food profiles from reference data sets using multivariate statistical methods and the subsequent classification of unknown data. Applicability of the obtained mass spectrometric fingerprints for food authentication was evaluated using different data processing methods, leave-10%-out cross-validation, and real-time classification of new data. Classification accuracy of 100% was achieved for the differentiation of milk types and fish species, and a classification accuracy of 96.4% was achieved for coffee types in cross-validation experiments. Measurement of two milk mixtures yielded correct classification of >94%. For real-time classification, the accuracies were comparable. Functionality of the software program and its performance is described. Processing time for a reference data set and a newly acquired spectrum was found to be 12 s and 2 s, respectively. These proof-of-principle experiments show that the combination of a miniaturized mass spectrometer, ambient ionization, and statistical analysis is suitable for on-site real-time food authentication.

Classification of HCV and HIV-1 Sequences with the Branching Index

PubMed Central

Hraber, Peter; Kuiken, Carla; Waugh, Mark; Geer, Shaun; Bruno, William J.; Leitner, Thomas

2009-01-01

SUMMARY Classification of viral sequences should be fast, objective, accurate, and reproducible. Most methods that classify sequences use either pairwise distances or phylogenetic relations, but cannot discern when a sequence is unclassifiable. The branching index (BI) combines distance and phylogeny methods to compute a ratio that quantifies how closely a query sequence clusters with a subtype clade. In the hypothesis-testing framework of statistical inference, the BI is compared with a threshold to test whether sufficient evidence exists for the query sequence to be classified among known sequences. If above the threshold, the null hypothesis of no support for the subtype relation is rejected and the sequence is taken as belonging to the subtype clade with which it clusters on the tree. This study evaluates statistical properties of the branching index for subtype classification in HCV and HIV-1. Pairs of BI values with known positive and negative test results were computed from 10,000 random fragments of reference alignments. Sampled fragments were of sufficient length to contain phylogenetic signal that groups reference sequences together properly into subtype clades. For HCV, a threshold BI of 0.71 yields 95.1% agreement with reference subtypes, with equal false positive and false negative rates. For HIV-1, a threshold of 0.66 yields 93.5% agreement. Higher thresholds can be used where lower false positive rates are required. In synthetic recombinants, regions without breakpoints are recognized accurately; regions with breakpoints do not uniquely represent any known subtype. Web-based services for viral subtype classification with the branching index are available online. PMID:18753218

Derivative spectra matching for wetland vegetation identification and classification by hyperspectral image

NASA Astrophysics Data System (ADS)

Wang, Jinnian; Zheng, Lanfen; Tong, Qingxi

1998-08-01

In this paper, we reported some research result in applying hyperspectral remote sensing data in identification and classification of wetland plant species and associations. Hyperspectral data were acquired by Modular Airborne Imaging Spectrometer (MAIS) over Poyang Lake wetland, China. A derivative spectral matching algorithm was used in hyperspectral vegetation analysis. The field measurement spectra were as reference for derivative spectral matching. In the study area, seven wetland plant associations were identified and classified with overall average accuracy is 84.03%.

Classification of Horn of Africa School Children: Is It Appropriate for the Educational Authorities in England to Refer to Them as Refugees?

ERIC Educational Resources Information Center

Kuyok, Kuyok Abol

2010-01-01

Drawing on evidence from a PhD study, this paper raises questions about the appropriateness of English educational authorities to continue to refer to the Horn of Africa children, most of them born in the UK, as refugees. The word refugee, in its broad definition, seemingly masks fundamental differences and may reinforce stereotypical perceptions…

Reference intervals and diagnostic ranges for serum free κ and free λ immunoglobulin light chains vary by instrument platform: Implications for classification of patient results in a multi-center study.

PubMed

Cotten, Steven W; Shajani-Yi, Zahra; Cervinski, Mark A; Voorhees, Timothy; Tuchman, Sascha A; Korpi-Steiner, Nichole

2018-06-06

Serum free light chain (FLC) immunoglobulins are key biomarkers that aid in the diagnosis, prognosis and assessment of treatment response in patients with plasma cell disorders (PCD). Here we investigated the transference of manufacturer's reported κFLC, λFLC and κ to λ FLC reference intervals (RI) and established de novo FLC RI and diagnostic ranges on four instruments at three academic medical centers. In addition, we also compared the classification of patient FLC results using manufacturer's versus established RIs and diagnostic ranges. CLSI EP28-A3C protocol was applied to investigate transference and establishment of FLC reference intervals on the cobas (Roche), Immage (Beckman), Optilite and SPA Plus (Binding Site). Serum κ FLC and λ FLC were measured in reference sera (N = 126) with estimation of central 95% RIs and FLC ratio diagnostic range (total range). Frequencies (%) in patient FLC results (N > 380 per institution) classified above, below or within manufacturer's versus established FLC RI were compared. Three of four instrument platforms did not exhibit acceptable transference of manufacturer's reported κFLC RI. The manufacturer's reported FLC total diagnostic range did not encompass all values observed in reference sera for any of the four platforms evaluated. Established FLC ratio diagnostic ranges reduced the frequency of patient results classified above range for three of four platforms evaluated. Transference of manufacturer's reported FLC RIs may be inappropriate for select instrument platforms. De novo establishment of FLC RIs specific to instrument platform is highly recommended in order to assure correct patient result classification. Copyright © 2017. Published by Elsevier Inc.

Classification of Chemicals Based On Structured Toxicity Information

EPA Science Inventory

Thirty years and millions of dollars worth of pesticide registration toxicity studies, historically stored as hardcopy and scanned documents, have been digitized into highly standardized and structured toxicity data within the Toxicity Reference Database (ToxRefDB). Toxicity-bas...

Sub-pixel image classification for forest types in East Texas

NASA Astrophysics Data System (ADS)

Westbrook, Joey

Sub-pixel classification is the extraction of information about the proportion of individual materials of interest within a pixel. Landcover classification at the sub-pixel scale provides more discrimination than traditional per-pixel multispectral classifiers for pixels where the material of interest is mixed with other materials. It allows for the un-mixing of pixels to show the proportion of each material of interest. The materials of interest for this study are pine, hardwood, mixed forest and non-forest. The goal of this project was to perform a sub-pixel classification, which allows a pixel to have multiple labels, and compare the result to a traditional supervised classification, which allows a pixel to have only one label. The satellite image used was a Landsat 5 Thematic Mapper (TM) scene of the Stephen F. Austin Experimental Forest in Nacogdoches County, Texas and the four cover type classes are pine, hardwood, mixed forest and non-forest. Once classified, a multi-layer raster datasets was created that comprised four raster layers where each layer showed the percentage of that cover type within the pixel area. Percentage cover type maps were then produced and the accuracy of each was assessed using a fuzzy error matrix for the sub-pixel classifications, and the results were compared to the supervised classification in which a traditional error matrix was used. The overall accuracy of the sub-pixel classification using the aerial photo for both training and reference data had the highest (65% overall) out of the three sub-pixel classifications. This was understandable because the analyst can visually observe the cover types actually on the ground for training data and reference data, whereas using the FIA (Forest Inventory and Analysis) plot data, the analyst must assume that an entire pixel contains the exact percentage of a cover type found in a plot. An increase in accuracy was found after reclassifying each sub-pixel classification from nine classes with 10 percent interval each to five classes with 20 percent interval each. When compared to the supervised classification which has a satisfactory overall accuracy of 90%, none of the sub-pixel classification achieved the same level. However, since traditional per-pixel classifiers assign only one label to pixels throughout the landscape while sub-pixel classifications assign multiple labels to each pixel, the traditional 85% accuracy of acceptance for pixel-based classifications should not apply to sub-pixel classifications. More research is needed in order to define the level of accuracy that is deemed acceptable for sub-pixel classifications.

Rapid corn and soybean mapping in US Corn Belt and neighboring areas

PubMed Central

Zhong, Liheng; Yu, Le; Li, Xuecao; Hu, Lina; Gong, Peng

2016-01-01

The goal of this study was to promptly map the extent of corn and soybeans early in the growing season. A classification experiment was conducted for the US Corn Belt and neighboring states, which is the most important production area of corn and soybeans in the world. To improve the timeliness of the classification algorithm, training was completely based on reference data and images from other years, circumventing the need to finish reference data collection in the current season. To account for interannual variability in crop development in the cross-year classification scenario, several innovative strategies were used. A random forest classifier was used in all tests, and MODIS surface reflectance products from the years 2008–2014 were used for training and cross-year validation. It is concluded that the fuzzy classification approach is necessary to achieve satisfactory results with R-squared ~0.9 (compared with the USDA Cropland Data Layer). The year of training data is an important factor, and it is recommended to select a year with similar crop phenology as the mapping year. With this phenology-based and cross-year-training method, in 2015 we mapped the cropping proportion of corn and soybeans around mid-August, when the two crops just reached peak growth. PMID:27811989

Rapid corn and soybean mapping in US Corn Belt and neighboring areas

NASA Astrophysics Data System (ADS)

Zhong, Liheng; Yu, Le; Li, Xuecao; Hu, Lina; Gong, Peng

2016-11-01

The goal of this study was to promptly map the extent of corn and soybeans early in the growing season. A classification experiment was conducted for the US Corn Belt and neighboring states, which is the most important production area of corn and soybeans in the world. To improve the timeliness of the classification algorithm, training was completely based on reference data and images from other years, circumventing the need to finish reference data collection in the current season. To account for interannual variability in crop development in the cross-year classification scenario, several innovative strategies were used. A random forest classifier was used in all tests, and MODIS surface reflectance products from the years 2008-2014 were used for training and cross-year validation. It is concluded that the fuzzy classification approach is necessary to achieve satisfactory results with R-squared ~0.9 (compared with the USDA Cropland Data Layer). The year of training data is an important factor, and it is recommended to select a year with similar crop phenology as the mapping year. With this phenology-based and cross-year-training method, in 2015 we mapped the cropping proportion of corn and soybeans around mid-August, when the two crops just reached peak growth.

Water quality of least-impaired lakes in eastern and southern Arkansas.

PubMed

Justus, Billy

2010-09-01

A three-phased study identified one least-impaired (reference) lake for each of four Arkansas lake classifications: three classifications in the Mississippi Alluvial Plain (MAP) ecoregion and a fourth classification in the South Central Plains (SCP) ecoregion. Water quality at three of the least-impaired lakes generally was comparable and also was comparable to water quality from Kansas and Missouri reference lakes and Texas least-impaired lakes. Water quality of one least-impaired lake in the MAP ecoregion was not as good as water quality in other least-impaired lakes in Arkansas or in the three other states: a probable consequence of all lakes in that classification having a designated use as a source of irrigation water. Chemical and physical conditions for all four lake classifications were at times naturally harsh as limnological characteristics changed temporally. As a consequence of allochthonous organic material, oxbow lakes isolated within watersheds comprised of swamps were susceptible to low dissolved oxygen concentrations to the extent that conditions would be limiting to some aquatic biota. Also, pH in lakes in the SCP ecoregion was <6.0, a level exceeding current Arkansas water-quality standards but typical of black water systems. Water quality of the deepest lakes exceeded that of shallow lakes. N/P ratios and trophic state indices may be less effective for assessing water quality for shallow lakes (<2 m) than for deep lakes because there is an increased exposure of sediment (and associated phosphorus) to disturbance and light in the former.

A recursive field-normalized bibliometric performance indicator: an application to the field of library and information science.

PubMed

Waltman, Ludo; Yan, Erjia; van Eck, Nees Jan

2011-10-01

Two commonly used ideas in the development of citation-based research performance indicators are the idea of normalizing citation counts based on a field classification scheme and the idea of recursive citation weighing (like in PageRank-inspired indicators). We combine these two ideas in a single indicator, referred to as the recursive mean normalized citation score indicator, and we study the validity of this indicator. Our empirical analysis shows that the proposed indicator is highly sensitive to the field classification scheme that is used. The indicator also has a strong tendency to reinforce biases caused by the classification scheme. Based on these observations, we advise against the use of indicators in which the idea of normalization based on a field classification scheme and the idea of recursive citation weighing are combined.

Something's Fishy in Paxton Lake: A Case on Speciation in Sticklebacks.

ERIC Educational Resources Information Center

Sharp, Joan

2002-01-01

Introduces a case study on speciation and evolutionary mechanisms. Teaches science process skills as well as natural selection, biological species concepts, basic genetic terminology, and classification. Includes teaching notes and classroom management strategies. (Contains 14 references.) (YDS)

The Design of Archives Buildings.

ERIC Educational Resources Information Center

Faye, Bernard

1982-01-01

Studies specific problems arising from design of archives buildings and examines three main purposes of this type of building, namely conservation, classification and restoration of archives, and the provision of access to them by administrators and research workers. Three references are listed. (Author/EJS)

An AERONET-Based Aerosol Classification Using the Mahalanobis Distance

NASA Technical Reports Server (NTRS)

Hamill, Patrick; Giordano, Marco; Ward, Carolyne; Giles, David; Holben, Brent

2016-01-01

We present an aerosol classification based on AERONET aerosol data from 1993 to 2012. We used the AERONET Level 2.0 almucantar aerosol retrieval products to define several reference aerosol clusters which are characteristic of the following general aerosol types: Urban-Industrial, Biomass Burning, Mixed Aerosol, Dust, and Maritime. The classification of a particular aerosol observation as one of these aerosol types is determined by its five-dimensional Mahalanobis distance to each reference cluster. We have calculated the fractional aerosol type distribution at 190 AERONET sites, as well as the monthly variation in aerosol type at those locations. The results are presented on a global map and individually in the supplementary material. Our aerosol typing is based on recognizing that different geographic regions exhibit characteristic aerosol types. To generate reference clusters we only keep data points that lie within a Mahalanobis distance of 2 from the centroid. Our aerosol characterization is based on the AERONET retrieved quantities, therefore it does not include low optical depth values. The analysis is based on point sources (the AERONET sites) rather than globally distributed values. The classifications obtained will be useful in interpreting aerosol retrievals from satellite borne instruments.

Applying aerial digital photography as a spectral remote sensing technique for macrophytic cover assessment in small rural streams

NASA Astrophysics Data System (ADS)

Anker, Y.; Hershkovitz, Y.; Gasith, A.; Ben-Dor, E.

2011-12-01

Although remote sensing of fluvial ecosystems is well developed, the tradeoff between spectral and spatial resolutions prevents its application in small streams (<3m width). In the current study, a remote sensing approach for monitoring and research of small ecosystem was developed. The method is based on differentiation between two indicative vegetation species out of the ecosystem flora. Since when studied, the channel was covered mostly by a filamentous green alga (Cladophora glomerata) and watercress (Nasturtium officinale), these species were chosen as indicative; nonetheless, common reed (Phragmites australis) was also classified in order to exclude it from the stream ROI. The procedure included: A. For both section and habitat scales classifications, acquisition of aerial digital RGB datasets. B. For section scale classification, hyperspectral (HSR) dataset acquisition. C. For calibration, HSR reflectance measurements of specific ground targets, in close proximity to each dataset acquisition swath. D. For habitat scale classification, manual, in-stream flora grid transects classification. The digital RGB datasets were converted to reflectance units by spectral calibration against colored reference plates. These red, green, blue, white, and black EVA foam reference plates were measured by an ASD field spectrometer and each was given a spectral value. Each spectral value was later applied to the spectral calibration and radiometric correction of spectral RGB (SRGB) cube. Spectral calibration of the HSR dataset was done using the empirical line method, based on reference values of progressive grey scale targets. Differentiation between the vegetation species was done by supervised classification both for the HSR and for the SRGB datasets. This procedure was done using the Spectral Angle Mapper function with the spectral pattern of each vegetation species as a spectral end member. Comparison between the two remote sensing techniques and between the SRGB classification and the in-situ transects indicates that: A. Stream vegetation classification resolution is about 4 cm by the SRGB method compared to about 1 m by HSR. Moreover, this resolution is also higher than of the manual grid transect classification. B. The SRGB method is by far the most cost-efficient. The combination of spectral information (rather than the cognitive color) and high spatial resolution of aerial photography provides noise filtration and better sub-water detection capabilities than the HSR technique. C. Only the SRGB method applies for habitat and section scales; hence, its application together with in-situ grid transects for validation, may be optimal for use in similar scenarios.
The HSR dataset was first degraded to 17 bands with the same spectral range as the RGB dataset and also to a dataset with 3 equivalent bands

Psychiatric diagnoses in patients with burning mouth syndrome and atypical odontalgia referred from psychiatric to dental facilities

PubMed Central

Takenoshita, Miho; Sato, Tomoko; Kato, Yuichi; Katagiri, Ayano; Yoshikawa, Tatsuya; Sato, Yusuke; Matsushima, Eisuke; Sasaki, Yoshiyuki; Toyofuku, Akira

2010-01-01

Background Burning mouth syndrome (BMS) and atypical odontalgia (AO) are two conditions involving chronic oral pain in the absence of any organic cause. Psychiatrically they can both be considered as “somatoform disorder”. From the dental point of view, however, the two disorders are quite distinct. BMS is a burning or stinging sensation in the mouth in association with a normal mucosa whereas AO is most frequently associated with a continuous pain in the teeth or in a tooth socket after extraction in the absence of any identifiable cause. Because of the absence of organic causes, BMS and AO are often regarded as psychogenic conditions, although the relationship between oral pain and psychologic factors is still unclear. Some studies have analyzed the psychiatric diagnoses of patients with chronic oral pain who have been referred from dental facilities to psychiatric facilities. No study to date has investigated patients referred from psychiatric facilities to dental facilities. Objective To analyze the psychiatric diagnoses of chronic oral pain patients, diagnosed with BMS and AO, and referred from psychiatric facilities to dental facilities. Study design Psychiatric diagnoses and disease conditions of BMS or AO were investigated in 162 patients by reviewing patients’ medical records and referral forms. Psychiatric diagnoses were categorized according to the International Statistical Classification of Disease and Related Health Problems, Tenth Revision. Results The proportion of F4 classification (neurotic, stress-related, and somatoform disorders) in AO patients was significantly higher than in BMS patients. BMS patients were more frequently given a F3 classification (mood/affective disorders). However, 50.8% of BMS patients and 33.3% of AO patients had no specific psychiatric diagnoses. Conclusion Although BMS and AO are both chronic pain disorders occurring in the absence of any organic cause, the psychiatric diagnoses of patients with BMS and AO differ substantially. PMID:21127687

A Real-Time Infrared Ultra-Spectral Signature Classification Method via Spatial Pyramid Matching

PubMed Central

Mei, Xiaoguang; Ma, Yong; Li, Chang; Fan, Fan; Huang, Jun; Ma, Jiayi

2015-01-01

The state-of-the-art ultra-spectral sensor technology brings new hope for high precision applications due to its high spectral resolution. However, it also comes with new challenges, such as the high data dimension and noise problems. In this paper, we propose a real-time method for infrared ultra-spectral signature classification via spatial pyramid matching (SPM), which includes two aspects. First, we introduce an infrared ultra-spectral signature similarity measure method via SPM, which is the foundation of the matching-based classification method. Second, we propose the classification method with reference spectral libraries, which utilizes the SPM-based similarity for the real-time infrared ultra-spectral signature classification with robustness performance. Specifically, instead of matching with each spectrum in the spectral library, our method is based on feature matching, which includes a feature library-generating phase. We calculate the SPM-based similarity between the feature of the spectrum and that of each spectrum of the reference feature library, then take the class index of the corresponding spectrum having the maximum similarity as the final result. Experimental comparisons on two publicly-available datasets demonstrate that the proposed method effectively improves the real-time classification performance and robustness to noise. PMID:26205263

15 CFR 748.3 - Classification requests, advisory opinions, and encryption review requests.

Code of Federal Regulations, 2010 CFR

2010-01-01

... to the EAR and, if applicable, the appropriate ECCN. This type of request is commonly referred to as... the appropriate ECCN in Block 24. If you are unable to determine a recommended classification for your...

Scanning electron microscope automatic defect classification of process induced defects

NASA Astrophysics Data System (ADS)

Wolfe, Scott; McGarvey, Steve

2017-03-01

With the integration of high speed Scanning Electron Microscope (SEM) based Automated Defect Redetection (ADR) in both high volume semiconductor manufacturing and Research and Development (R and D), the need for reliable SEM Automated Defect Classification (ADC) has grown tremendously in the past few years. In many high volume manufacturing facilities and R and D operations, defect inspection is performed on EBeam (EB), Bright Field (BF) or Dark Field (DF) defect inspection equipment. A comma separated value (CSV) file is created by both the patterned and non-patterned defect inspection tools. The defect inspection result file contains a list of the inspection anomalies detected during the inspection tools' examination of each structure, or the examination of an entire wafers surface for non-patterned applications. This file is imported into the Defect Review Scanning Electron Microscope (DRSEM). Following the defect inspection result file import, the DRSEM automatically moves the wafer to each defect coordinate and performs ADR. During ADR the DRSEM operates in a reference mode, capturing a SEM image at the exact position of the anomalies coordinates and capturing a SEM image of a reference location in the center of the wafer. A Defect reference image is created based on the Reference image minus the Defect image. The exact coordinates of the defect is calculated based on the calculated defect position and the anomalies stage coordinate calculated when the high magnification SEM defect image is captured. The captured SEM image is processed through either DRSEM ADC binning, exporting to a Yield Analysis System (YAS), or a combination of both. Process Engineers, Yield Analysis Engineers or Failure Analysis Engineers will manually review the captured images to insure that either the YAS defect binning is accurately classifying the defects or that the DRSEM defect binning is accurately classifying the defects. This paper is an exploration of the feasibility of the utilization of a Hitachi RS4000 Defect Review SEM to perform Automatic Defect Classification with the objective of the total automated classification accuracy being greater than human based defect classification binning when the defects do not require multiple process step knowledge for accurate classification. The implementation of DRSEM ADC has the potential to improve the response time between defect detection and defect classification. Faster defect classification will allow for rapid response to yield anomalies that will ultimately reduce the wafer and/or the die yield.

Classification problems of Mount Kenya soils

NASA Astrophysics Data System (ADS)

Mutuma, Evans; Csorba, Ádám; Wawire, Amos; Dobos, Endre; Michéli, Erika

2017-04-01

Soil sampling on the agricultural lands covering 1200 square kilometers in the Eastern part of Mount Kenya was carried out to assess the status of soil organic carbon (SOC) as a soil fertility indicator, and to create an up-to-date soil classification map. The geology of the area consists of volcanic rocks and recent superficial deposits. The volcanic rocks are related to the Pliocene time; mainly: lahars, phonolites, tuffs, basalt and ashes. A total of 28 open profiles and 49 augered profiles with 269 samples were collected. The samples were analyzed for total carbon, organic carbon, particle size distribution, percent bases, cation exchange capacity and pH among other parameters. The objective of the study was to evaluate the variability of SOC in different Reference Soil Groups (RGS) and to compare the determined classification units with the KENSOTER database. Soil classification was performed based on the World Reference Base (WRB) for Soil Resources 2014. Based on the earlier surveys, geological and environmental setting, Nitisols were expected to be the dominant soils of the sampled area. However, this was not the case. The major differences to earlier survey data (KENSOTER database) are the presence of high activity clays (CEC value range 27.6 cmol/kg - 70 cmol/kg), high silt content (range 32.6 % - 52.4 %) and silt/clay ratio (range of 0.6 - 1.4) keeping these soils out of the Nitisols RSG. There was good accordance in the morphological features with the earlier survey but failed the silt/clay ratio criteria for Nitisols. This observation calls attention to set new classification criteria for Nitisols and other soils of warm, humid regions with variable rate of weathering to avoid difficulties in interpretation. To address the classification problem, this paper further discusses the taxonomic relationships between the studied soils. On the contrary most of the diagnostic elements (like the presence Umbric horizon, Vitric and Andic properties) and the some qualifiers (Humic, Dystric, Clayic, Skeletic, Leptic, etc) represent useful information for land use and management in the area.

Auditory Warnings, Signal-Referent Relations, and Natural Indicators: Re-Thinking Theory and Application

ERIC Educational Resources Information Center

Petocz, Agnes; Keller, Peter E.; Stevens, Catherine J.

2008-01-01

In auditory warning design the idea of the strength of the association between sound and referent has been pivotal. Research has proceeded via constructing classification systems of signal-referent associations and then testing predictions about ease of learning of different levels of signal-referent relation strength across and within different…

46 CFR 2.45-5 - Incorporation by reference.

Code of Federal Regulations, 2012 CFR

2012-10-01

... INSPECTIONS Classification Society Activities § 2.45-5 Incorporation by reference. (a) Certain material is incorporated by reference into this part with the approval of the Director of the Federal Register under 5 U.S... 46 Shipping 1 2012-10-01 2012-10-01 false Incorporation by reference. 2.45-5 Section 2.45-5...

46 CFR 2.45-5 - Incorporation by reference.

Code of Federal Regulations, 2014 CFR

2014-10-01

... INSPECTIONS Classification Society Activities § 2.45-5 Incorporation by reference. (a) Certain material is incorporated by reference into this part with the approval of the Director of the Federal Register under 5 U.S... 46 Shipping 1 2014-10-01 2014-10-01 false Incorporation by reference. 2.45-5 Section 2.45-5...

46 CFR 2.45-5 - Incorporation by reference.

Code of Federal Regulations, 2013 CFR

2013-10-01

... INSPECTIONS Classification Society Activities § 2.45-5 Incorporation by reference. (a) Certain material is incorporated by reference into this part with the approval of the Director of the Federal Register under 5 U.S... 46 Shipping 1 2013-10-01 2013-10-01 false Incorporation by reference. 2.45-5 Section 2.45-5...

SLO blind data set inversion and classification using physically complete models

NASA Astrophysics Data System (ADS)

Shamatava, I.; Shubitidze, F.; Fernández, J. P.; Barrowes, B. E.; O'Neill, K.; Grzegorczyk, T. M.; Bijamov, A.

2010-04-01

Discrimination studies carried out on TEMTADS and Metal Mapper blind data sets collected at the San Luis Obispo UXO site are presented. The data sets included four types of targets of interest: 2.36" rockets, 60-mm mortar shells, 81-mm projectiles, and 4.2" mortar items. The total parameterized normalized magnetic source (NSMS) amplitudes were used to discriminate TOI from metallic clutter and among the different hazardous UXO. First, in object's frame coordinate, the total NSMS were determined for each TOI along three orthogonal axes from the training data provided by the Strategic Environmental Research and Development Program (SERDP) along with the referred blind data sets. Then the inverted total NSMS were used to extract the time-decay classification features. Once our inversion and classification algorithms were tested on the calibration data sets then we applied the same procedure to all blind data sets. The combined NSMS and differential evolution algorithm is utilized for determine the NSMS strengths for each cell. The obtained total NSMS time-decay curves were used to extract the discrimination features and perform classification using the training data as reference. In addition, for cross validation, the inverted locations and orientations from NSMS-DE algorithm were compared against the inverted data that obtained via the magnetic field, vector and scalar potentials (HAP) method and the combined dipole and Gauss-Newton approach technique. We examined the entire time decay history of the total NSMS case-by-case for classification purposes. Also, we use different multi-class statistical classification algorithms for separating the dangerous objects from non hazardous items. The inverted targets were ranked by target ID and submitted to SERDP for independent scoring. The independent scoring results are presented.

Characteristics of Children with Phonologic Disorders of Unknown Origin.

ERIC Educational Resources Information Center

Shriberg, Lawrence D.; And Others

1986-01-01

Descriptive data are presented from three studies of children referred for assessment of developmental speech disorders. Group findings indicate involvements in mechanism, cognitive, and psychosocial areas. The reliability, learnability, and efficiency of a diagnostic classification system is also considered. (Author/CL)

Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain-computer interface.

PubMed

Siuly; Li, Yan; Paul Wen, Peng

2014-03-01

Motor imagery (MI) tasks classification provides an important basis for designing brain-computer interface (BCI) systems. If the MI tasks are reliably distinguished through identifying typical patterns in electroencephalography (EEG) data, a motor disabled people could communicate with a device by composing sequences of these mental states. In our earlier study, we developed a cross-correlation based logistic regression (CC-LR) algorithm for the classification of MI tasks for BCI applications, but its performance was not satisfactory. This study develops a modified version of the CC-LR algorithm exploring a suitable feature set that can improve the performance. The modified CC-LR algorithm uses the C3 electrode channel (in the international 10-20 system) as a reference channel for the cross-correlation (CC) technique and applies three diverse feature sets separately, as the input to the logistic regression (LR) classifier. The present algorithm investigates which feature set is the best to characterize the distribution of MI tasks based EEG data. This study also provides an insight into how to select a reference channel for the CC technique with EEG signals considering the anatomical structure of the human brain. The proposed algorithm is compared with eight of the most recently reported well-known methods including the BCI III Winner algorithm. The findings of this study indicate that the modified CC-LR algorithm has potential to improve the identification performance of MI tasks in BCI systems. The results demonstrate that the proposed technique provides a classification improvement over the existing methods tested. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Open Dataset for the Automatic Recognition of Sedentary Behaviors.

PubMed

Possos, William; Cruz, Robinson; Cerón, Jesús D; López, Diego M; Sierra-Torres, Carlos H

2017-01-01

Sedentarism is associated with the development of noncommunicable diseases (NCD) such as cardiovascular diseases (CVD), type 2 diabetes, and cancer. Therefore, the identification of specific sedentary behaviors (TV viewing, sitting at work, driving, relaxing, etc.) is especially relevant for planning personalized prevention programs. To build and evaluate a public a dataset for the automatic recognition (classification) of sedentary behaviors. The dataset included data from 30 subjects, who performed 23 sedentary behaviors while wearing a commercial wearable on the wrist, a smartphone on the hip and another in the thigh. Bluetooth Low Energy (BLE) beacons were used in order to improve the automatic classification of different sedentary behaviors. The study also compared six well know data mining classification techniques in order to identify the more precise method of solving the classification problem of the 23 defined behaviors. A better classification accuracy was obtained using the Random Forest algorithm and when data were collected from the phone on the hip. Furthermore, the use of beacons as a reference for obtaining the symbolic location of the individual improved the precision of the classification.

Clinical Application of Six Current Classification Systems for Iatrogenic Bile Duct Injuries after Cholecystectomy.

PubMed

Velidedeoglu, Mehmet; Arikan, Akif Enes; Uludag, Sezgin Server; Olgun, Deniz Cebi; Kilic, Fahrettin; Kapan, Metin

2015-05-01

Due to being a severe complication, iatrogenic bile duct injury is still a challenging issue for surgeons in gallbladder surgery. However, a commonly accepted classification describing the type of injury has not been available yet. This study aims to evaluate ability of six current classification systems to discriminate bile duct injury patterns. Twelve patients, who were referred to our clinic because of iatrogenic bile duct injury after laparoscopic cholecystectomy were reviewed retrospectively. We described type of injury for each patient according to current six different classifications. 9 patients underwent definitive biliary reconstruction. Bismuth, Strasberg-Bismuth, Stewart-Way and Neuhaus classifications do not consider vascular involvement, Siewert system does, but only for the tangential lesions without structural loss of duct and lesion with a structural defect of hepatic or common bile duct. Siewert, Neuhaus and Stewart-Way systems do not discriminate between lesions at or above bifurcation of the hepatic duct. The Hannover classification may resolve the missing aspects of other systems by describing additional vascular involvement and location of the lesion at or above bifurcation.

Lung texture classification using bag of visual words

NASA Astrophysics Data System (ADS)

Asherov, Marina; Diamant, Idit; Greenspan, Hayit

2014-03-01

Interstitial lung diseases (ILD) refer to a group of more than 150 parenchymal lung disorders. High-Resolution Computed Tomography (HRCT) is the most essential imaging modality of ILD diagnosis. Nonetheless, classification of various lung tissue patterns caused by ILD is still regarded as a challenging task. The current study focuses on the classification of five most common categories of lung tissues of ILD in HRCT images: normal, emphysema, ground glass, fibrosis and micronodules. The objective of the research is to classify an expert-given annotated region of interest (AROI) using a bag of visual words (BoVW) framework. The images are divided into small patches and a collection of representative patches are defined as visual words. This procedure, termed dictionary construction, is performed for each individual lung texture category. The assumption is that different lung textures are represented by a different visual word distribution. The classification is performed using an SVM classifier with histogram intersection kernel. In the experiments, we use a dataset of 1018 AROIs from 95 patients. Classification using a leave-one-patient-out cross validation (LOPO CV) is used. Current classification accuracy obtained is close to 80%.

A PIXEL COMPOSITION-BASED REFERENCE DATA SET FOR THEMATIC ACCURACY ASSESSMENT

EPA Science Inventory

Developing reference data sets for accuracy assessment of land-cover classifications derived from coarse spatial resolution sensors such as MODIS can be difficult due to the large resolution differences between the image data and available reference data sources. Ideally, the spa...

[Classifications in forensic medicine and their logical basis].

PubMed

Kovalev, A V; Shmarov, L A; Ten'kov, A A

2014-01-01

The objective of the present study was to characterize the main requirements for the correct construction of classifications used in forensic medicine, with special reference to the errors that occur in the relevant text-books, guidelines, and manuals and the ways to avoid them. This publication continues the series of thematic articles of the authors devoted to the logical errors in the expert conclusions. The preparation of further publications is underway to report the results of the in-depth analysis of the logical errors encountered in expert conclusions, text-books, guidelines, and manuals.

Classification and Dose-Response Characterization of ...

EPA Pesticide Factsheets

Thirty years and over a billion of today’s dollars worth of pesticide registration toxicity studies, historically stored as hardcopy and scanned documents, have been digitized into highly standardized and structured toxicity data, within the U.S. Environmental Protection Agency’s (EPA) Toxicity Reference Database (ToxRefDB). The source toxicity data in ToxRefDB covers multiple study types, including subchronic, developmental, reproductive, chronic, and cancer studies, resulting in a diverse set of endpoints and toxicities. Novel approaches to chemical classification are performed as a model application of ToxRefDB and as an essential need for highly detailed chemical classifications within the EPA’s ToxCast™ research program. In order to develop predictive models and biological signatures utilizing high-throughput screening (HTS) and in vitro genomic data, endpoints and toxicities must first be identified and globally characterized for ToxCast Phase I chemicals. Secondarily, dose-response characterization within and across toxicity endpoints provide insight into key precursor toxicity events and overall endpoint relevance. Toxicity-based chemical classification and dose-response characterization utilizing ToxRefDB prioritized toxicity endpoints and differentiated toxicity outcomes across a large chemical set.

Evaluation of various mental task combinations for near-infrared spectroscopy-based brain-computer interfaces

NASA Astrophysics Data System (ADS)

Hwang, Han-Jeong; Lim, Jeong-Hwan; Kim, Do-Won; Im, Chang-Hwan

2014-07-01

A number of recent studies have demonstrated that near-infrared spectroscopy (NIRS) is a promising neuroimaging modality for brain-computer interfaces (BCIs). So far, most NIRS-based BCI studies have focused on enhancing the accuracy of the classification of different mental tasks. In the present study, we evaluated the performances of a variety of mental task combinations in order to determine the mental task pairs that are best suited for customized NIRS-based BCIs. To this end, we recorded event-related hemodynamic responses while seven participants performed eight different mental tasks. Classification accuracies were then estimated for all possible pairs of the eight mental tasks (C=28). Based on this analysis, mental task combinations with relatively high classification accuracies frequently included the following three mental tasks: "mental multiplication," "mental rotation," and "right-hand motor imagery." Specifically, mental task combinations consisting of two of these three mental tasks showed the highest mean classification accuracies. It is expected that our results will be a useful reference to reduce the time needed for preliminary tests when discovering individual-specific mental task combinations.

Case Studies of Actual and Alleged Overflights, 1930-1953. Supplement

DTIC Science & Technology

1955-08-15

the SECRET volume than would have been possible if all the case studies had been presented in the same volume, regardless of classification. The character of the intelligence mission of United States reconnaissance aircraft referred to in case studies Nos. 115-118, 120-123, and 129-131 is not precisely identified in the discussion of those

Terrain classification and land hazard mapping in Kalsi-Chakrata area (Garhwal Himalaya), India

NASA Astrophysics Data System (ADS)

Choubey, Vishnu D.; Litoria, Pradeep K.

Terrain classification and land system mapping of a part of the Garhwal Himalaya (India) have been used to provide a base map for land hazard evaluation, with special reference to landslides and other mass movements. The study was based on MSS images, aerial photographs and 1:50,000 scale maps, followed by detailed field-work. The area is composed of two groups of rocks: well exposed sedimentary Precambrian formations in the Himalayan Main Boundary Thrust Belt and the Tertiary molasse deposits of the Siwaliks. Major tectonic boundaries were taken as the natural boundaries of land systems. A physiographic terrain classification included slope category, forest cover, occurrence of landslides, seismicity and tectonic activity in the area.

Noninvasive Classification of Hepatic Fibrosis Based on Texture Parameters From Double Contrast-Enhanced Magnetic Resonance Images

PubMed Central

Bahl, Gautam; Cruite, Irene; Wolfson, Tanya; Gamst, Anthony C.; Collins, Julie M.; Chavez, Alyssa D.; Barakat, Fatma; Hassanein, Tarek; Sirlin, Claude B.

2016-01-01

Purpose To demonstrate a proof of concept that quantitative texture feature analysis of double contrast-enhanced magnetic resonance imaging (MRI) can classify fibrosis noninvasively, using histology as a reference standard. Materials and Methods A Health Insurance Portability and Accountability Act (HIPAA)-compliant Institutional Review Board (IRB)-approved retrospective study of 68 patients with diffuse liver disease was performed at a tertiary liver center. All patients underwent double contrast-enhanced MRI, with histopathology-based staging of fibrosis obtained within 12 months of imaging. The MaZda software program was used to compute 279 texture parameters for each image. A statistical regularization technique, generalized linear model (GLM)-path, was used to develop a model based on texture features for dichotomous classification of fibrosis category (F ≤2 vs. F ≥3) of the 68 patients, with histology as the reference standard. The model's performance was assessed and cross-validated. There was no additional validation performed on an independent cohort. Results Cross-validated sensitivity, specificity, and total accuracy of the texture feature model in classifying fibrosis were 91.9%, 83.9%, and 88.2%, respectively. Conclusion This study shows proof of concept that accurate, noninvasive classification of liver fibrosis is possible by applying quantitative texture analysis to double contrast-enhanced MRI. Further studies are needed in independent cohorts of subjects. PMID:22851409

40 CFR 152.97 - Rights and obligations regarding the Data Submitters List.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., the type(s) of study he has previously submitted (identified by reference to data/information... Data Submitters List. 152.97 Section 152.97 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Satisfaction of Data...

48 CFR 204.7101 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Definitions. Accounting classification reference number (ACRN) means any combination of a two position alpha/numeric code used as a method of relating the accounting classification citation to detailed line item... 48 Federal Acquisition Regulations System 3 2010-10-01 2010-10-01 false Definitions. 204.7101...

Image classification at low light levels

NASA Astrophysics Data System (ADS)

Wernick, Miles N.; Morris, G. Michael

1986-12-01

An imaging photon-counting detector is used to achieve automatic sorting of two image classes. The classification decision is formed on the basis of the cross correlation between a photon-limited input image and a reference function stored in computer memory. Expressions for the statistical parameters of the low-light-level correlation signal are given and are verified experimentally. To obtain a correlation-based system for two-class sorting, it is necessary to construct a reference function that produces useful information for class discrimination. An expression for such a reference function is derived using maximum-likelihood decision theory. Theoretically predicted results are used to compare on the basis of performance the maximum-likelihood reference function with Fukunaga-Koontz basis vectors and average filters. For each method, good class discrimination is found to result in milliseconds from a sparse sampling of the input image.

Pathological Bases for a Robust Application of Cancer Molecular Classification

PubMed Central

Diaz-Cano, Salvador J.

2015-01-01

Any robust classification system depends on its purpose and must refer to accepted standards, its strength relying on predictive values and a careful consideration of known factors that can affect its reliability. In this context, a molecular classification of human cancer must refer to the current gold standard (histological classification) and try to improve it with key prognosticators for metastatic potential, staging and grading. Although organ-specific examples have been published based on proteomics, transcriptomics and genomics evaluations, the most popular approach uses gene expression analysis as a direct correlate of cellular differentiation, which represents the key feature of the histological classification. RNA is a labile molecule that varies significantly according with the preservation protocol, its transcription reflect the adaptation of the tumor cells to the microenvironment, it can be passed through mechanisms of intercellular transference of genetic information (exosomes), and it is exposed to epigenetic modifications. More robust classifications should be based on stable molecules, at the genetic level represented by DNA to improve reliability, and its analysis must deal with the concept of intratumoral heterogeneity, which is at the origin of tumor progression and is the byproduct of the selection process during the clonal expansion and progression of neoplasms. The simultaneous analysis of multiple DNA targets and next generation sequencing offer the best practical approach for an analytical genomic classification of tumors. PMID:25898411

Water quality of least-impaired lakes in eastern and southern Arkansas

USGS Publications Warehouse

Justus, B.

2010-01-01

A three-phased study identified one least-impaired (reference) lake for each of four Arkansas lake classifications: three classifications in the Mississippi Alluvial Plain (MAP) ecoregion and a fourth classification in the South Central Plains (SCP) ecoregion. Water quality at three of the least-impaired lakes generally was comparable and also was comparable to water quality from Kansas and Missouri reference lakes and Texas least-impaired lakes. Water quality of one least-impaired lake in the MAP ecoregion was not as good as water quality in other least-impaired lakes in Arkansas or in the three other states: a probable consequence of all lakes in that classification having a designated use as a source of irrigation water. Chemical and physical conditions for all four lake classifications were at times naturally harsh as limnological characteristics changed temporally. As a consequence of allochthonous organic material, oxbow lakes isolated within watersheds comprised of swamps were susceptible to low dissolved oxygen concentrations to the extent that conditions would be limiting to some aquatic biota. Also, pH in lakes in the SCP ecoregion was <6.0, a level exceeding current Arkansas water-quality standards but typical of black water systems. Water quality of the deepest lakes exceeded that of shallow lakes. N/P ratios and trophic state indices may be less effective for assessing water quality for shallow lakes (<2 m) than for deep lakes because there is an increased exposure of sediment (and associated phosphorus) to disturbance and light in the former. ?? 2009 Springer Science+Business Media B.V.

Stable prevalence of obesity in Swedish schoolchildren from 2008 to 2013 but widening socio-economic gap in girls.

PubMed

Moraeus, Lotta; Lissner, Lauren; Sjöberg, Agneta

2014-12-01

The aim of this study was to follow the 5-year prevalence of overweight, obesity and thinness in 7- to 9-year-old children in West Sweden and to investigate whether trends differed according to gender and socio-economic status. Cross-sectional anthropometric measurements of three cohorts in grades one and two were performed in 3492 7- to 9-year-old children in 2008, 2010 and 2013. For body mass index classification, the IOTF/Cole and WHO 2007 references were used. Percentage of inhabitants with high education in the school area was used for socio-economic classification. Between 2008, 2010 and 2013, the overall time-trends in overweight 17.7%, 19.3% and 18.8%, obesity 3.2%, 3.3% and 3.1%, and thinness 6.5%, 4.7% and 6.9%, respectively, were fairly stable using the IOTF/Cole references. Thinness defined by the Cole reference increased in girls. The socio-economic gradient for overweight and obesity was clear by both references, but using the IOTF reference, the gap increased for obesity among girls (p = 0.024). No significant trends were observed with the WHO reference. The overall prevalence of overweight and obesity was stable over 5 years, but we detected growing inequality in obesity and increasing prevalence of thinness in girls. With these regionally representative data, we can draw conclusions about West Sweden, despite an absence of continued national surveillance. ©2014 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

A new Fourier transform based CBIR scheme for mammographic mass classification: a preliminary invariance assessment

NASA Astrophysics Data System (ADS)

Gundreddy, Rohith Reddy; Tan, Maxine; Qui, Yuchen; Zheng, Bin

2015-03-01

The purpose of this study is to develop and test a new content-based image retrieval (CBIR) scheme that enables to achieve higher reproducibility when it is implemented in an interactive computer-aided diagnosis (CAD) system without significantly reducing lesion classification performance. This is a new Fourier transform based CBIR algorithm that determines image similarity of two regions of interest (ROI) based on the difference of average regional image pixel value distribution in two Fourier transform mapped images under comparison. A reference image database involving 227 ROIs depicting the verified soft-tissue breast lesions was used. For each testing ROI, the queried lesion center was systematically shifted from 10 to 50 pixels to simulate inter-user variation of querying suspicious lesion center when using an interactive CAD system. The lesion classification performance and reproducibility as the queried lesion center shift were assessed and compared among the three CBIR schemes based on Fourier transform, mutual information and Pearson correlation. Each CBIR scheme retrieved 10 most similar reference ROIs and computed a likelihood score of the queried ROI depicting a malignant lesion. The experimental results shown that three CBIR schemes yielded very comparable lesion classification performance as measured by the areas under ROC curves with the p-value greater than 0.498. However, the CBIR scheme using Fourier transform yielded the highest invariance to both queried lesion center shift and lesion size change. This study demonstrated the feasibility of improving robustness of the interactive CAD systems by adding a new Fourier transform based image feature to CBIR schemes.

Realistic Expectations for Rock Identification.

ERIC Educational Resources Information Center

Westerback, Mary Elizabeth; Azer, Nazmy

1991-01-01

Presents a rock classification scheme for use by beginning students. The scheme is based on rock textures (glassy, crystalline, clastic, and organic framework) and observable structures (vesicles and graded bedding). Discusses problems in other rock classification schemes which may produce confusion, misidentification, and anxiety. (10 references)…

Spectroscopic parallaxes of MAP region stars from UBVRI, DDO, and uvbyH-beta photometry. [Multichannel Astrometric Photometer for astronomical observation

NASA Technical Reports Server (NTRS)

Persinger, Tim; Castelaz, Michael W.

1990-01-01

This paper presents the results of spectral type and luminosity classification of reference stars in the Allegheny Observatory MAP parallax program, using broadband and intermediate-band photometry. In addition to the use of UBVRI and DDO photometric systems, the uvbyH-beta photometric system was included for classification of blue (B - V less than 0.6) reference stars. The stellar classifications made from the photometry are used to determine spectroscopic parallaxes. The spectroscopic parallaxes are used in turn to adjust the relative parallaxes measured with the MAP to absolute parallaxes. A new method for dereddening stars using more than one photometric system is presented. In the process of dereddening, visual extinctions, spectral types, and luminosity classes are determined, as well as a measure of the goodness of fit. The measure of goodness of fit quantifies confidence in the stellar classifications. It is found that the spectral types are reliable to within 2.5 spectral subclasses.

Welcoming with risk classification in teaching hospitals: assessment of structure, process and result.

PubMed

Vituri, Dagmar Willamowius; Inoue, Kelly Cristina; Bellucci Júnior, José Aparecido; de Oliveira, Carlos Aparecido; Rossi, Robson Marcelo; Matsuda, Laura Misue

2013-01-01

To assess, from the worker's viewpoint, the structure, the process and the results of the Emergency Hospital Services that have taken up the guideline of "Welcoming with Risk Classification" in two teaching hospitals of the state of Paraná. Quantitative and descriptive research, exploratory and prospective, using random sampling stratified by professional category, comprising a universe of 216 professional people. They found some points of agreement regarding the promotion of a welcoming and humane environment; privacy and security; welcome and shelter of the companion and also the sheltering and classification of all patients; however, there was disagreement about the comfort of the environment, reference system and counter-reference, prioritisation of seriously ill patients in post-classification service, communication between the members of the multi-professional team and reassessment of the guideline. The workers assess the development of the guideline as being precarious, due mainly to the lack of physical structure, due to the lack of physical structure and shortcomings in the service process.

METHODS MODULE

EPA Science Inventory

The ultimate goal of classification is to reduce variation within classes to enable detection of differences between reference and impacted condition within classes as cost-effectively as possible, while minimizing the number of classes for which reference conditions must be defi...

Metabolic syndrome in children and adolescents from Mérida city, Venezuela: Comparison of results using local and international reference values (CREDEFAR study).

PubMed

Villalobos Reyes, Marjorie; Mederico, Maracelly; Paoli de Valeri, Mariela; Briceño, Yajaira; Zerpa, Yajaira; Gómez-Pérez, Roald; Camacho, Nolis; Martínez, José Luis; Valeri, Lenín; Arata-Bellabarba, Gabriela

2014-11-01

To obtain local reference values for blood lipids and blood pressure (BP), and to determine the prevalence of metabolic syndrome (MS) in children and adolescents from Mérida, Venezuela, and to compare results using local and international cut-off values. The study enrolled 916 participants of both sexes aged 9-18 years of age from educational institutions. Demographic, anthropometric, and BP data were collected. Fasting blood glucose and lipid profile were measured. Percentile distribution of lipid and BP values was done by age group and sex. Prevalence of MS was estimated based on the NCEP-ATPIII classification (as modified by Cook et al.) and the classification of the International Diabetes Federation, using percentiles of Mérida and the USA as cut-off points. Agreement between both classifications was estimated using the kappa test (κ). Prevalence of MS was 2.2% by Cook-Merida percentiles, as compared to 1.8% by Cook-USA percentiles, a moderate agreement (κ=0.54). Agreement between Cook et al. and IDF using Merida percentiles was weak (κ=0.28). There was a higher frequency of abdominal obesity, hypertriglyceridemia and hypertension, and a lower frequency of low HDL-C using Mérida percentiles. The risk (odds ratio) of having MS is greater if abdominal obesity exists (OR: 98.63, CI: 22.45-433.35, p=0.0001). MS was significantly more common in obese subjects (18.3%, p=0.0001). Prevalence of MS in this sample of children and adolescents was 2.2%. Lipid and BP values were lower in Venezuelan as compared to US, European, and Asian children and adolescents, and similar to those in Latin-American references. Own reference values are required for accurate diagnosis of MS, as well as a worldwide consensus on its diagnostic criteria. Copyright © 2014 SEEN. Published by Elsevier Espana. All rights reserved.

Lava Morphology Classification of a Fast-Spreading Ridge Using Deep-Towed Sonar Data: East Pacific Rise

NASA Astrophysics Data System (ADS)

Meyer, J.; White, S.

2005-05-01

Classification of lava morphology on a regional scale contributes to the understanding of the distribution and extent of lava flows at a mid-ocean ridge. Seafloor classification is essential to understand the regional undersea environment at midocean ridges. In this study, the development of a classification scheme is found to identify and extract textural patterns of different lava morphologies along the East Pacific Rise using DSL-120 side-scan and ARGO camera imagery. Application of an accurate image classification technique to side-scan sonar allows us to expand upon the locally available visual ground reference data to make the first comprehensive regional maps of small-scale lava morphology present at a mid-ocean ridge. The submarine lava morphologies focused upon in this study; sheet flows, lobate flows, and pillow flows; have unique textures. Several algorithms were applied to the sonar backscatter intensity images to produce multiple textural image layers useful in distinguishing the different lava morphologies. The intensity and spatially enhanced images were then combined and applied to a hybrid classification technique. The hybrid classification involves two integrated classifiers, a rule-based expert system classifier and a machine learning classifier. The complementary capabilities of the two integrated classifiers provided a higher accuracy of regional seafloor classification compared to using either classifier alone. Once trained, the hybrid classifier can then be applied to classify neighboring images with relative ease. This classification technique has been used to map the lava morphology distribution and infer spatial variability of lava effusion rates along two segments of the East Pacific Rise, 17 deg S and 9 deg N. Future use of this technique may also be useful for attaining temporal information. Repeated documentation of morphology classification in this dynamic environment can be compared to detect regional seafloor change.

Network-based high level data classification.

PubMed

Silva, Thiago Christiano; Zhao, Liang

2012-06-01

Traditional supervised data classification considers only physical features (e.g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

30 CFR 250.802 - Design, installation, and operation of surface production-safety systems.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Production Platform Piping Systems (as incorporated by reference in § 250.198). (4) Electrical system... classified according to API RP 500, Recommended Practice for Classification of Locations for Electrical..., Recommended Practice for Classification of Locations for Electrical Installations at Petroleum Facilities...

30 CFR 250.802 - Design, installation, and operation of surface production-safety systems.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Production Platform Piping Systems (as incorporated by reference in § 250.198). (4) Electrical system... classified according to API RP 500, Recommended Practice for Classification of Locations for Electrical..., Recommended Practice for Classification of Locations for Electrical Installations at Petroleum Facilities...

30 CFR 250.802 - Design, installation, and operation of surface production-safety systems.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Production Platform Piping Systems (as incorporated by reference in § 250.198). (4) Electrical system... classified according to API RP 500, Recommended Practice for Classification of Locations for Electrical..., Recommended Practice for Classification of Locations for Electrical Installations at Petroleum Facilities...

Single-particle cryo-EM using alignment by classification (ABC): the structure of Lumbricus terrestris haemoglobin.

PubMed

Afanasyev, Pavel; Seer-Linnemayr, Charlotte; Ravelli, Raimond B G; Matadeen, Rishi; De Carlo, Sacha; Alewijnse, Bart; Portugal, Rodrigo V; Pannu, Navraj S; Schatz, Michael; van Heel, Marin

2017-09-01

Single-particle cryogenic electron microscopy (cryo-EM) can now yield near-atomic resolution structures of biological complexes. However, the reference-based alignment algorithms commonly used in cryo-EM suffer from reference bias, limiting their applicability (also known as the 'Einstein from random noise' problem). Low-dose cryo-EM therefore requires robust and objective approaches to reveal the structural information contained in the extremely noisy data, especially when dealing with small structures. A reference-free pipeline is presented for obtaining near-atomic resolution three-dimensional reconstructions from heterogeneous ('four-dimensional') cryo-EM data sets. The methodologies integrated in this pipeline include a posteriori camera correction, movie-based full-data-set contrast transfer function determination, movie-alignment algorithms, (Fourier-space) multivariate statistical data compression and unsupervised classification, 'random-startup' three-dimensional reconstructions, four-dimensional structural refinements and Fourier shell correlation criteria for evaluating anisotropic resolution. The procedures exclusively use information emerging from the data set itself, without external 'starting models'. Euler-angle assignments are performed by angular reconstitution rather than by the inherently slower projection-matching approaches. The comprehensive 'ABC-4D' pipeline is based on the two-dimensional reference-free 'alignment by classification' (ABC) approach, where similar images in similar orientations are grouped by unsupervised classification. Some fundamental differences between X-ray crystallography versus single-particle cryo-EM data collection and data processing are discussed. The structure of the giant haemoglobin from Lumbricus terrestris at a global resolution of ∼3.8 Å is presented as an example of the use of the ABC-4D procedure.

Fatty acid methyl ester analysis to identify sources of soil in surface water.

PubMed

Banowetz, Gary M; Whittaker, Gerald W; Dierksen, Karen P; Azevedo, Mark D; Kennedy, Ann C; Griffith, Stephen M; Steiner, Jeffrey J

2006-01-01

Efforts to improve land-use practices to prevent contamination of surface waters with soil are limited by an inability to identify the primary sources of soil present in these waters. We evaluated the utility of fatty acid methyl ester (FAME) profiles of dry reference soils for multivariate statistical classification of soils collected from surface waters adjacent to agricultural production fields and a wooded riparian zone. Trials that compared approaches to concentrate soil from surface water showed that aluminum sulfate precipitation provided comparable yields to that obtained by vacuum filtration and was more suitable for handling large numbers of samples. Fatty acid methyl ester profiles were developed from reference soils collected from contrasting land uses in different seasons to determine whether specific fatty acids would consistently serve as variables in multivariate statistical analyses to permit reliable classification of soils. We used a Bayesian method and an independent iterative process to select appropriate fatty acids and found that variable selection was strongly impacted by the season during which soil was collected. The apparent seasonal variation in the occurrence of marker fatty acids in FAME profiles from reference soils prevented preparation of a standardized set of variables. Nevertheless, accurate classification of soil in surface water was achieved utilizing fatty acid variables identified in seasonally matched reference soils. Correlation analysis of entire chromatograms and subsequent discriminant analyses utilizing a restricted number of fatty acid variables showed that FAME profiles of soils exposed to the aquatic environment still had utility for classification at least 1 wk after submersion.

The Operational Commander’s Role in Planning and Executing a Successful Campaign

DTIC Science & Technology

1992-04-20

44 IS. PRICE CODE RIDGWAY IN KOREAN WAR AS CDR 8th ARMY ________ It. SECURITY CLASSIFICATION 10. SECURITY CLASSIFICATION 13. SECURITY CLASSIFICATION...Field-Marshal Slim as the 14th Army commander in Burma; General MacArthur in the World War II Cartwheel Operation and General Ridgway as the 8th Army...64 :. Introduction In his book, Command in War , Martin Van Creveld referred to the period of strategic

Application of Sensor Fusion to Improve Uav Image Classification

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Novelty and Foreseeing Research Trends: The Case of Astrophysics and Astronomy

NASA Astrophysics Data System (ADS)

Varga, Attila

2018-05-01

Metrics based on reference lists of research articles or on keywords have been used to predict citation impact. The concept behind such metrics is that original ideas stem from the reconfiguration of the structure of past knowledge, and therefore atypical combinations in the reference lists, keywords, or classification codes indicate future high-impact research. The current paper serves as an introduction to this line of research for astronomers and also addresses some of the methodological questions in this field of innovation studies. It is still not clear if the choice of particular indexes, such as references to journals, articles, or specific bibliometric classification codes affects the relationship between atypical combinations and citation impact. To understand more aspects of the innovation process, a new metric has been devised to measure to what extent researchers are able to anticipate the changing combinatorial trends of the future. Results show that the variant of the latter anticipation scores that is based on paper combinations is a good predictor of the future citation impact of scholarly works. The study also shows that the effects of tested indexes vary with the aggregation levels that were used to construct them. A detailed analysis of combinatorial novelty in the field reveals that certain sub-fields of astronomy and astrophysics have different roles in the reconfiguration of past knowledge.

Video Games: Instructional Potential and Classification.

ERIC Educational Resources Information Center

Nawrocki, Leon H.; Winner, Janet L.

1983-01-01

Intended to provide a framework and impetus for future investigations of video games, this paper summarizes activities investigating the instructional use of such games, observations by the authors, and a proposed classification scheme and a paradigm to assist in the preliminary selection of instructional video games. Nine references are listed.…

5 CFR 531.203 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Schedule or GS means the classification and pay system established under 5 U.S.C. chapter 51 and subchapter... officers (LEOs) receiving LEO special base rates are covered by the GS classification and pay system but... a break in service of more than 3 days. (See § 531.241.) Any reference to employees, grades...

5 CFR 531.203 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Schedule or GS means the classification and pay system established under 5 U.S.C. chapter 51 and subchapter... officers (LEOs) receiving LEO special base rates are covered by the GS classification and pay system but... a break in service of more than 3 days. (See § 531.241.) Any reference to employees, grades...

5 CFR 531.203 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Schedule or GS means the classification and pay system established under 5 U.S.C. chapter 51 and subchapter... officers (LEOs) receiving LEO special base rates are covered by the GS classification and pay system but... a break in service of more than 3 days. (See § 531.241.) Any reference to employees, grades...

5 CFR 531.203 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Schedule or GS means the classification and pay system established under 5 U.S.C. chapter 51 and subchapter... officers (LEOs) receiving LEO special base rates are covered by the GS classification and pay system but... a break in service of more than 3 days. (See § 531.241.) Any reference to employees, grades...

[Quantitative classification in catering trade and countermeasures of supervision and management in Hunan Province].

PubMed

Liu, Xiulan; Chen, Lizhang; He, Xiang

2012-02-01

To analyze the status quo of quantitative classification in Hunan Province catering industry, and to discuss the countermeasures in-depth. According to relevant laws and regulations, and after referring to Daily supervision and quantitative scoring sheet and consulting experts, a checklist of key supervision indicators was made. The implementation of quantitative classification in 10 cities in Hunan Province was studied, and the status quo was analyzed. All the 390 catering units implemented quantitative classified management. The larger the catering enterprise, the higher level of quantitative classification. In addition to cafeterias, the smaller the catering units, the higher point of deduction, and snack bars and beverage stores were the highest. For those quantified and classified as C and D, the point of deduction was higher in the procurement and storage of raw materials, operation processing and other aspects. The quantitative classification of Hunan Province has relatively wide coverage. There are hidden risks in food security in small catering units, snack bars, and beverage stores. The food hygienic condition of Hunan Province needs to be improved.

The Screening Accuracy of the Parent and Teacher-Reported Social Responsiveness Scale (SRS): Comparison with the 3Di and ADOS.

PubMed

Duvekot, Jorieke; van der Ende, Jan; Verhulst, Frank C; Greaves-Lord, Kirstin

2015-06-01

The screening accuracy of the parent and teacher-reported Social Responsiveness Scale (SRS) was compared with an autism spectrum disorder (ASD) classification according to (1) the Developmental, Dimensional, and Diagnostic Interview (3 Di), (2) the Autism Diagnostic Observation Schedule (ADOS), (3) both the 3 Di and ADOS, in 186 children referred to six mental health centers. The parent report showed excellent correspondence to an ASD classification according to the 3 Di and both the 3 Di and ADOS. The teacher report added significantly to the screening accuracy over and above the parent report when compared with the ADOS classification. Findings support the screening utility of the parent-reported SRS among clinically referred children and indicate that different informants may provide unique information relevant for ASD assessment.

The Influence of Tactile Perception on Classification of Bone Tissue at Dental Implant Insertion.

PubMed

Linck, Gláucia Kelly Silva Barbosa; Ferreira, Geovane Miranda; De Oliveira, Rubelisa Cândido Gomes; Lindh, Christina; Leles, Cláudio Rodrigues; Ribeiro-Rotta, Rejane Faria

2016-06-01

Various ways of using the Lekholm and Zarb (L&Z) classification have added to the lack of scientific evidence of the effectiveness of this clinical method in the evaluation of implant treatment. The study aims to assess subjective jawbone classifications in patients referred for implant treatment, using L&Z classification with and without surgeon's hand perception at implant insertion. The association between bone type classifications and quantitative parameters of primary implant stability was also assessed. One hundred thirty-five implants were inserted using conventional loading protocol. Three surgeons classified bone quality at implant sites using two methods: one based on periapical and panoramic images (modified L&Z) and one based on the same images associated with the surgeon's tactile perception during drilling (original L&Z). Peak insertion torque and implant stability quotient (ISQ) were recorded. The modified and original L&Z were strongly correlated (rho = 0.79; p < .001); Wilcoxon signed-rank test showed no significant difference in the distribution of bone type classification between pairs using the two methods (p = .538). Spearman correlation tested the association between primary stability parameters and bone type classifications (-0.34 to -0.57 [p < .001]). Tactile surgical perception has a minor influence on rating of subjective bone type for dental implant treatment using the L&Z classification. © 2015 Wiley Periodicals, Inc.

Assessment of Classification Accuracies of SENTINEL-2 and LANDSAT-8 Data for Land Cover / Use Mapping

NASA Astrophysics Data System (ADS)

Hale Topaloğlu, Raziye; Sertel, Elif; Musaoğlu, Nebiye

2016-06-01

This study aims to compare classification accuracies of land cover/use maps created from Sentinel-2 and Landsat-8 data. Istanbul metropolitan city of Turkey, with a population of around 14 million, having different landscape characteristics was selected as study area. Water, forest, agricultural areas, grasslands, transport network, urban, airport- industrial units and barren land- mine land cover/use classes adapted from CORINE nomenclature were used as main land cover/use classes to identify. To fulfil the aims of this research, recently acquired dated 08/02/2016 Sentinel-2 and dated 22/02/2016 Landsat-8 images of Istanbul were obtained and image pre-processing steps like atmospheric and geometric correction were employed. Both Sentinel-2 and Landsat-8 images were resampled to 30m pixel size after geometric correction and similar spectral bands for both satellites were selected to create a similar base for these multi-sensor data. Maximum Likelihood (MLC) and Support Vector Machine (SVM) supervised classification methods were applied to both data sets to accurately identify eight different land cover/ use classes. Error matrix was created using same reference points for Sentinel-2 and Landsat-8 classifications. After the classification accuracy, results were compared to find out the best approach to create current land cover/use map of the region. The results of MLC and SVM classification methods were compared for both images.

Feature Selection for Chemical Sensor Arrays Using Mutual Information

PubMed Central

Wang, X. Rosalind; Lizier, Joseph T.; Nowotny, Thomas; Berna, Amalia Z.; Prokopenko, Mikhail; Trowell, Stephen C.

2014-01-01

We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays. PMID:24595058

Spectral Band Selection for Urban Material Classification Using Hyperspectral Libraries

NASA Astrophysics Data System (ADS)

Le Bris, A.; Chehata, N.; Briottet, X.; Paparoditis, N.

2016-06-01

In urban areas, information concerning very high resolution land cover and especially material maps are necessary for several city modelling or monitoring applications. That is to say, knowledge concerning the roofing materials or the different kinds of ground areas is required. Airborne remote sensing techniques appear to be convenient for providing such information at a large scale. However, results obtained using most traditional processing methods based on usual red-green-blue-near infrared multispectral images remain limited for such applications. A possible way to improve classification results is to enhance the imagery spectral resolution using superspectral or hyperspectral sensors. In this study, it is intended to design a superspectral sensor dedicated to urban materials classification and this work particularly focused on the selection of the optimal spectral band subsets for such sensor. First, reflectance spectral signatures of urban materials were collected from 7 spectral libraires. Then, spectral optimization was performed using this data set. The band selection workflow included two steps, optimising first the number of spectral bands using an incremental method and then examining several possible optimised band subsets using a stochastic algorithm. The same wrapper relevance criterion relying on a confidence measure of Random Forests classifier was used at both steps. To cope with the limited number of available spectra for several classes, additional synthetic spectra were generated from the collection of reference spectra: intra-class variability was simulated by multiplying reference spectra by a random coefficient. At the end, selected band subsets were evaluated considering the classification quality reached using a rbf svm classifier. It was confirmed that a limited band subset was sufficient to classify common urban materials. The important contribution of bands from the Short Wave Infra-Red (SWIR) spectral domain (1000-2400 nm) to material classification was also shown.

Quality assurance of chemical ingredient classification for the National Drug File - Reference Terminology.

PubMed

Zheng, Ling; Yumak, Hasan; Chen, Ling; Ochs, Christopher; Geller, James; Kapusnik-Uner, Joan; Perl, Yehoshua

2017-09-01

The National Drug File - Reference Terminology (NDF-RT) is a large and complex drug terminology consisting of several classification hierarchies on top of an extensive collection of drug concepts. These hierarchies provide important information about clinical drugs, e.g., their chemical ingredients, mechanisms of action, dosage form and physiological effects. Within NDF-RT such information is represented using tens of thousands of roles connecting drugs to classifications. In previous studies, we have introduced various kinds of Abstraction Networks to summarize the content and structure of terminologies in order to facilitate their visual comprehension, and support quality assurance of terminologies. However, these previous kinds of Abstraction Networks are not appropriate for summarizing the NDF-RT classification hierarchies, due to its unique structure. In this paper, we present the novel Ingredient Abstraction Network (IAbN) to summarize, visualize and support the audit of NDF-RT's Chemical Ingredients hierarchy and its associated drugs. A common theme in our quality assurance framework is to use characterizations of sets of concepts, revealed by the Abstraction Network structure, to capture concepts, the modeling of which is more complex than for other concepts. For the IAbN, we characterize drug ingredient concepts as more complex if they belong to IAbN groups with multiple parent groups. We show that such concepts have a statistically significantly higher rate of errors than a control sample and identify two especially common patterns of errors. Copyright © 2017 Elsevier Inc. All rights reserved.

Robust Averaging of Covariances for EEG Recordings Classification in Motor Imagery Brain-Computer Interfaces.

PubMed

Uehara, Takashi; Sartori, Matteo; Tanaka, Toshihisa; Fiori, Simone

2017-06-01

The estimation of covariance matrices is of prime importance to analyze the distribution of multivariate signals. In motor imagery-based brain-computer interfaces (MI-BCI), covariance matrices play a central role in the extraction of features from recorded electroencephalograms (EEGs); therefore, correctly estimating covariance is crucial for EEG classification. This letter discusses algorithms to average sample covariance matrices (SCMs) for the selection of the reference matrix in tangent space mapping (TSM)-based MI-BCI. Tangent space mapping is a powerful method of feature extraction and strongly depends on the selection of a reference covariance matrix. In general, the observed signals may include outliers; therefore, taking the geometric mean of SCMs as the reference matrix may not be the best choice. In order to deal with the effects of outliers, robust estimators have to be used. In particular, we discuss and test the use of geometric medians and trimmed averages (defined on the basis of several metrics) as robust estimators. The main idea behind trimmed averages is to eliminate data that exhibit the largest distance from the average covariance calculated on the basis of all available data. The results of the experiments show that while the geometric medians show little differences from conventional methods in terms of classification accuracy in the classification of electroencephalographic recordings, the trimmed averages show significant improvement for all subjects.

Minimum Requirements for the CUS (Common User Subsystem) Workstation

DTIC Science & Technology

1987-04-20

PAGE -2- / ’ " I& REPORT SECURITY CLASSIFICATION lb RESTRICTIVE MARKINGS Unclassified 2a SECURITY CLASSIFICATION AUTHORITY 3 DISTRMBUTION...CLASSIFICATION UNCLASSIID/UNLIMITED r" SAME AS RPT. [ 3 DTIC USERS Unclassified tNM F RESPONSIBLE INDIVIDUAL 22b TELEPHONE (Include area codi) 22c OFFICE...Summary 1 1. Introduction 3 1.1 Purpose 3 1.2 Scope 3 1.3 Reference 4 2. Background 5 3 . Minimal WIS Workstation Requirements 8 3.1 Overview 8 4. Overview

The Effects of Evaluation and Production Blocking on the Performance of Brainstorming Groups

DTIC Science & Technology

1992-08-01

NUMBER OF PAGES 701 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LMIITATION OF ABSTRACT OF...special interest group. Once again, the people in the above examples share many things in common such as a sense of civil duty, an employer, a love for a...people respond differently in the presence of others, a phenomenon Zajonc refers to as compresence . In group settings, social facilitation can be

R-parametrization and its role in classification of linear multivariable feedback systems

NASA Technical Reports Server (NTRS)

Chen, Robert T. N.

1988-01-01

A classification of all the compensators that stabilize a given general plant in a linear, time-invariant multi-input, multi-output feedback system is developed. This classification, along with the associated necessary and sufficient conditions for stability of the feedback system, is achieved through the introduction of a new parameterization, referred to as R-Parameterization, which is a dual of the familiar Q-Parameterization. The classification is made to the stability conditions of the compensators and the plant by themselves; and necessary and sufficient conditions are based on the stability of Q and R themselves.

Comparison of SAM and OBIA as Tools for Lava Morphology Classification - A Case Study in Krafla, NE Iceland

NASA Astrophysics Data System (ADS)

Aufaristama, Muhammad; Hölbling, Daniel; Höskuldsson, Ármann; Jónsdóttir, Ingibjörg

2017-04-01

The Krafla volcanic system is part of the Icelandic North Volcanic Zone (NVZ). During Holocene, two eruptive events occurred in Krafla, 1724-1729 and 1975-1984. The last eruptive episode (1975-1984), known as the "Krafla Fires", resulted in nine volcanic eruption episodes. The total area covered by the lavas from this eruptive episode is 36 km2 and the volume is about 0.25-0.3 km3. Lava morphology is related to the characteristics of the surface morphology of a lava flow after solidification. The typical morphology of lava can be used as primary basis for the classification of lava flows when rheological properties cannot be directly observed during emplacement, and also for better understanding the behavior of lava flow models. Although mapping of lava flows in the field is relatively accurate such traditional methods are time consuming, especially when the lava covers large areas such as it is the case in Krafla. Semi-automatic mapping methods that make use of satellite remote sensing data allow for an efficient and fast mapping of lava morphology. In this study, two semi-automatic methods for lava morphology classification are presented and compared using Landsat 8 (30 m spatial resolution) and SPOT-5 (10 m spatial resolution) satellite images. For assessing the classification accuracy, the results from semi-automatic mapping were compared to the respective results from visual interpretation. On the one hand, the Spectral Angle Mapper (SAM) classification method was used. With this method an image is classified according to the spectral similarity between the image reflectance spectrums and the reference reflectance spectra. SAM successfully produced detailed lava surface morphology maps. However, the pixel-based approach partly leads to a salt-and-pepper effect. On the other hand, we applied the Random Forest (RF) classification method within an object-based image analysis (OBIA) framework. This statistical classifier uses a randomly selected subset of training samples to produce multiple decision trees. For final classification of pixels or - in the present case - image objects, the average of the class assignments probability predicted by the different decision trees is used. While the resulting OBIA classification of lava morphology types shows a high coincidence with the reference data, the approach is sensitive to the segmentation-derived image objects that constitute the base units for classification. Both semi-automatic methods produce reasonable results in the Krafla lava field, even if the identification of different pahoehoe and aa types of lava appeared to be difficult. The use of satellite remote sensing data shows a high potential for fast and efficient classification of lava morphology, particularly over large and inaccessible areas.

[On establishing comparative reference system for syndrome classification study from the thinking characteristics of syndrome differentiation dependent therapy].

PubMed

Liu, Ping; Hu, Yi-yang; Ni, Li-qiang

2006-05-01

To create a comparative referential system for syndrome classification study by viewing from the thinking characteristics of TCM on syndrome differentiation dependent therapy (SDDT), through analyzing the thinking process of SDDT, and the basic features of disease, syndrome and prescription, combining the basic principles of modern evidence-based medicine and feasibility of establishing integrative disease-syndrome animal model. The practice of creating a comparative referential system based on clinical efficacy of prescription was discussed around syndrome pathogenesis and its relationship with disease and prescription, which was one of the important scientific problems in TCM syndrome study. The authors hold that, it may be one of the available approaches for the present study on integration of disease with syndrome by way of insisting on the thinking pathway of stressing the characteristics of TCM and intermerging with modern scientific design; on taking the efficacy of prescription as the comparative reference system to accumulate and improve unceasingly according to the TCM method of syndrome diagnosis inferred from effect of prescription with reverse thought (i.e., to differentiate syndrome from the effect of prescription), and thus build up the syndrome diagnostic standard on the solid clinical and scientific base.

A land classification protocol for pollinator ecology research: An urbanization case study.

PubMed

Samuelson, Ash E; Leadbeater, Ellouise

2018-06-01

Land-use change is one of the most important drivers of widespread declines in pollinator populations. Comprehensive quantitative methods for land classification are critical to understanding these effects, but co-option of existing human-focussed land classifications is often inappropriate for pollinator research. Here, we present a flexible GIS-based land classification protocol for pollinator research using a bottom-up approach driven by reference to pollinator ecology, with urbanization as a case study. Our multistep method involves manually generating land cover maps at multiple biologically relevant radii surrounding study sites using GIS, with a focus on identifying land cover types that have a specific relevance to pollinators. This is followed by a three-step refinement process using statistical tools: (i) definition of land-use categories, (ii) principal components analysis on the categories, and (iii) cluster analysis to generate a categorical land-use variable for use in subsequent analysis. Model selection is then used to determine the appropriate spatial scale for analysis. We demonstrate an application of our protocol using a case study of 38 sites across a gradient of urbanization in South-East England. In our case study, the land classification generated a categorical land-use variable at each of four radii based on the clustering of sites with different degrees of urbanization, open land, and flower-rich habitat. Studies of land-use effects on pollinators have historically employed a wide array of land classification techniques from descriptive and qualitative to complex and quantitative. We suggest that land-use studies in pollinator ecology should broadly adopt GIS-based multistep land classification techniques to enable robust analysis and aid comparative research. Our protocol offers a customizable approach that combines specific relevance to pollinator research with the potential for application to a wide range of ecological questions, including agroecological studies of pest control.

[Correlation of size and age in Colombian indigenous children based on WHO and NCHS references].

PubMed

Benjumea-Rincón, María V; Parra-Sánchez, José H; Ocampo-Téllez, Paul R

2016-08-01

Objective To evaluate the correlation of size, according to age, of the anthropometric growth references of Colombian indigenous children studied in Encuesta Nacional de la Situación Nutricional de Colombia 2010 -ENSIN 2010 (National Survey of Nutrition in Colombia - 2010). Method A secondary analysis of 2598 data of indigenous Colombian children under five years of age, evaluated by ENSIN in 2010, was performed. The considered variables were size according to age, gender, height, place of residence, department and socioeconomic position. The classification of the deficit in size, based on the references of the National Center for Health Statistics (NCHS) and the World Health Organization (WHO), was made by using the Z <-2 score and the Anthro software. The Kappa coefficient was estimated to assess the correlation between anthropometric categories and was classified taking into account the proposal of Altman DG. Results One in four children had a deficit in size in the light of both anthropometric references. The prevalence of the deficit was higher when using the WHO standard, increased with age and was higher in children who resided in low altitude (m). The correlation between the two references was good (kappa ≥0,688, p=0,000) for children of both genders and all ages; the exception corresponded to children of age two, since it was moderate (kappa=0,601, p=0,000). The greatest disagreement in the classification was observed in the category "tall". Conclusion According to the statistical correlation found between the two anthropometric references (WHO vs. NCHS), any reference could be used for assessment of size according to for age.

Neuroimaging classification of progression patterns in glioblastoma: a systematic review.

PubMed

Piper, Rory J; Senthil, Keerthi K; Yan, Jiun-Lin; Price, Stephen J

2018-03-30

Our primary objective was to report the current neuroimaging classification systems of spatial patterns of progression in glioblastoma. In addition, we aimed to report the terminology used to describe 'progression' and to assess the compliance with the Response Assessment in Neuro-Oncology (RANO) Criteria. We conducted a systematic review to identify all neuroimaging studies of glioblastoma that have employed a categorical classification system of spatial progression patterns. Our review was registered with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) registry. From the included 157 results, we identified 129 studies that used labels of spatial progression patterns that were not based on radiation volumes (Group 1) and 50 studies that used labels that were based on radiation volumes (Group 2). In Group 1, we found 113 individual labels and the most frequent were: local/localised (58%), distant/distal (51%), diffuse (20%), multifocal (15%) and subependymal/subventricular zone (15%). We identified 13 different labels used to refer to 'progression', of which the most frequent were 'recurrence' (99%) and 'progression' (92%). We identified that 37% (n = 33/90) of the studies published following the release of the RANO classification were adherent compliant with the RANO criteria. Our review reports significant heterogeneity in the published systems used to classify glioblastoma spatial progression patterns. Standardization of terminology and classification systems used in studying progression would increase the efficiency of our research in our attempts to more successfully treat glioblastoma.

Fire severity classification: Uses and abuses

Treesearch

Theresa B. Jain; Russell T. Graham

2003-01-01

Burn severity (also referred to as fire severity) is not a single definition, but rather a concept and its classification is a function of the measured units unique to the system of interest. The systems include: flora and fauna, soil microbiology and hydrologic processes, atmospheric inputs, fire management, and society. Depending on the particular system of interest...

Data Science for Imbalanced Data: Methods and Applications

ERIC Educational Resources Information Center

Johnson, Reid A.

2016-01-01

Data science is a broad, interdisciplinary field concerned with the extraction of knowledge or insights from data, with the classification of data as a core, fundamental task. One of the most persistent challenges faced when performing classification is the class imbalance problem. Class imbalance refers to when the frequency with which each class…

5 CFR 2634.202 - Public filer defined.

Code of Federal Regulations, 2014 CFR

2014-01-01

... the Office of Government Ethics to be of equal classification; (d) Each employee who is an... competitive service by reason of being of a confidential or policy-making character, unless excluded by virtue...: References in this section and in §§ 2634.203 and 2634.904 to position classifications have been adjusted to...

5 CFR 2634.202 - Public filer defined.

Code of Federal Regulations, 2012 CFR

2012-01-01

... the Office of Government Ethics to be of equal classification; (d) Each employee who is an... competitive service by reason of being of a confidential or policy-making character, unless excluded by virtue...: References in this section and in §§ 2634.203 and 2634.904 to position classifications have been adjusted to...

5 CFR 2634.202 - Public filer defined.

Code of Federal Regulations, 2013 CFR

2013-01-01

... the Office of Government Ethics to be of equal classification; (d) Each employee who is an... competitive service by reason of being of a confidential or policy-making character, unless excluded by virtue...: References in this section and in §§ 2634.203 and 2634.904 to position classifications have been adjusted to...

Evaluating Intervention Effects in a Diagnostic Classification Model Framework

ERIC Educational Resources Information Center

Madison, Matthew J.; Bradshaw, Laine

2018-01-01

The evaluation of intervention effects is an important objective of educational research. One way to evaluate the effectiveness of an intervention is to conduct an experiment that assigns individuals to control and treatment groups. In the context of pretest/posttest designed studies, this is referred to as a control-group pretest/posttest design.…

Program of Studies: Trade and Industrial: Grades 9-12.

ERIC Educational Resources Information Center

Fairfax County Schools, VA.

Part 1 of the trade and industrial education curriculum guide for grades 9-12 contains a brief program overview and Vocational Industrial Clubs of America (VICA) description, more detailed descriptions of in-school and out-of-school programs and program classification methods, a list of references, and charts of various programs and training…

Scaffolding Young Children: The Utility of Mediation in a Classification Test

ERIC Educational Resources Information Center

Mata, Sara; van Geert, Paul; van der Aalsvoort, Geerdina

2017-01-01

Introduction: Studies of Dynamic Assessment of cognitive abilities reveal that young children profit from assistance while carrying out tasks that elicit cognitive effort. Dynamic assessment refers to a test format of a pretest-mediation-posttest in which the mediation phase includes scaffolding to assist the child to grasp the purpose of the…

Measures of Linguistic Accuracy in Second Language Writing Research.

ERIC Educational Resources Information Center

Polio, Charlene G.

1997-01-01

Investigates the reliability of measures of linguistic accuracy in second language writing. The study uses a holistic scale, error-free T-units, and an error classification system on the essays of English-as-a-Second-Language students and discusses why disagreements arise within a rater and between raters. (24 references) (Author/CK)

Diagnostic classification scheme in Iranian breast cancer patients using a decision tree.

PubMed

Malehi, Amal Saki

2014-01-01

The objective of this study was to determine a diagnostic classification scheme using a decision tree based model. The study was conducted as a retrospective case-control study in Imam Khomeini hospital in Tehran during 2001 to 2009. Data, including demographic and clinical-pathological characteristics, were uniformly collected from 624 females, 312 of them were referred with positive diagnosis of breast cancer (cases) and 312 healthy women (controls). The decision tree was implemented to develop a diagnostic classification scheme using CART 6.0 Software. The AUC (area under curve), was measured as the overall performance of diagnostic classification of the decision tree. Five variables as main risk factors of breast cancer and six subgroups as high risk were identified. The results indicated that increasing age, low age at menarche, single and divorced statues, irregular menarche pattern and family history of breast cancer are the important diagnostic factors in Iranian breast cancer patients. The sensitivity and specificity of the analysis were 66% and 86.9% respectively. The high AUC (0.82) also showed an excellent classification and diagnostic performance of the model. Decision tree based model appears to be suitable for identifying risk factors and high or low risk subgroups. It can also assists clinicians in making a decision, since it can identify underlying prognostic relationships and understanding the model is very explicit.

Convex formulation of multiple instance learning from positive and unlabeled bags.

PubMed

Bao, Han; Sakai, Tomoya; Sato, Issei; Sugiyama, Masashi

2018-05-24

Multiple instance learning (MIL) is a variation of traditional supervised learning problems where data (referred to as bags) are composed of sub-elements (referred to as instances) and only bag labels are available. MIL has a variety of applications such as content-based image retrieval, text categorization, and medical diagnosis. Most of the previous work for MIL assume that training bags are fully labeled. However, it is often difficult to obtain an enough number of labeled bags in practical situations, while many unlabeled bags are available. A learning framework called PU classification (positive and unlabeled classification) can address this problem. In this paper, we propose a convex PU classification method to solve an MIL problem. We experimentally show that the proposed method achieves better performance with significantly lower computation costs than an existing method for PU-MIL. Copyright © 2018 Elsevier Ltd. All rights reserved.

State-and-transition models for heterogeneous landscapes: A strategy for development and application

USDA-ARS?s Scientific Manuscript database

Interpretation of assessment and monitoring data requires information about reference conditions and ecological resilience. Reference conditions used as benchmarks can be specified via potential-based land classifications (e.g., ecological sites) that describe the plant communities potentially obser...

CON4EI: Selection of the reference chemicals for hazard identification and labelling of eye irritating chemicals.

PubMed

Adriaens, E; Alépée, N; Kandarova, H; Drzewieckac, A; Gruszka, K; Guest, R; Willoughby, J A; Verstraelen, S; Van Rompay, A R

2017-10-01

Assessment of the acute eye irritation potential is part of the international regulatory requirements for testing of chemicals. In the past, several prospective and retrospective validation studies have taken place in the area of serious eye damage/eye irritation testing. Success in terms of complete replacement of the regulatory in vivo Draize rabbit eye test has not yet been achieved. A very important aspect to ensure development of successful alternative test methods and/or strategies for serious eye damage/eye irritation testing is the selection of appropriate reference chemicals. A set of 80 reference chemicals was selected for the CEFIC-LRI-AIMT6-VITO CON4EI (CONsortium for in vitro Eye Irritation testing strategy) project, in collaboration with Cosmetics Europe, from the Draize Reference Database published by Cosmetics Europe based on key criteria that were set in their paper (e.g. balanced by important driver of classification and physical state). The most important goals of the CON4EI project were to identify the performance of eight in vitro alternative tests in terms of driver of classification and to identify similarities/differences between the methods in order the build a successful testing strategy that can discriminate between all UN GHS categories. This paper provides background on selection of the test chemicals. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reprint of "CON4EI: Selection of the reference chemicals for hazard identification and labelling of eye irritating chemicals".

PubMed

Adriaens, E; Alépée, N; Kandarova, H; Drzewieckac, A; Gruszka, K; Guest, R; Willoughby, J A; Verstraelen, S; Van Rompay, A R

2018-06-01

Assessment of the acute eye irritation potential is part of the international regulatory requirements for testing of chemicals. In the past, several prospective and retrospective validation studies have taken place in the area of serious eye damage/eye irritation testing. Success in terms of complete replacement of the regulatory in vivo Draize rabbit eye test has not yet been achieved. A very important aspect to ensure development of successful alternative test methods and/or strategies for serious eye damage/eye irritation testing is the selection of appropriate reference chemicals. A set of 80 reference chemicals was selected for the CEFIC-LRI-AIMT6-VITO CON4EI (CONsortium for in vitro Eye Irritation testing strategy) project, in collaboration with Cosmetics Europe, from the Draize Reference Database published by Cosmetics Europe based on key criteria that were set in their paper (e.g. balanced by important driver of classification and physical state). The most important goals of the CON4EI project were to identify the performance of eight in vitro alternative tests in terms of driver of classification and to identify similarities/differences between the methods in order the build a successful testing strategy that can discriminate between all UN GHS categories. This paper provides background on selection of the test chemicals. Copyright © 2018. Published by Elsevier Ltd.

Comparison of ambulatory blood pressure reference standards in children evaluated for hypertension.

PubMed

Jones, Deborah P; Richey, Phyllis A; Alpert, Bruce S

2009-06-01

The purpose of this study was to systematically compare methods for standardization of blood pressure levels obtained by ambulatory blood pressure monitoring (ABPM) in a group of 111 children studied at our institution. Blood pressure indices, blood pressure loads and standard deviation scores were calculated using the original ABPM and the modified reference standards. Bland-Altman plots and kappa statistics for the level of agreement were generated. Overall, the agreement between the two methods was excellent; however, approximately 5% of children were classified differently by one as compared with the other method. Depending on which version of the German Working Group's reference standards is used for interpretation of ABPM data, the classification of the individual as having hypertension or normal blood pressure may vary.

Comparison of ambulatory blood pressure reference standards in children evaluated for hypertension

PubMed Central

Jones, Deborah P.; Richey, Phyllis A.; Alpert, Bruce S.

2009-01-01

Objective The purpose of this study was to systematically compare methods for standardization of blood pressure levels obtained by ambulatory blood pressure monitoring (ABPM) in a group of 111 children studied at our institution. Methods Blood pressure indices, blood pressure loads and standard deviation scores were calculated using he original ABPM and the modified reference standards. Bland—Altman plots and kappa statistics for the level of agreement were generated. Results Overall, the agreement between the two methods was excellent; however, approximately 5% of children were classified differently by one as compared with the other method. Conclusion Depending on which version of the German Working Group’s reference standards is used for interpretation of ABPM data, the classification of the individual as having hypertension or normal blood pressure may vary. PMID:19433980

A global reference database from very high resolution commercial satellite data and methodology for application to Landsat derived 30 m continuous field tree cover data

USGS Publications Warehouse

Pengra, Bruce; Long, Jordan; Dahal, Devendra; Stehman, Stephen V.; Loveland, Thomas R.

2015-01-01

The methodology for selection, creation, and application of a global remote sensing validation dataset using high resolution commercial satellite data is presented. High resolution data are obtained for a stratified random sample of 500 primary sampling units (5 km  ×  5 km sample blocks), where the stratification based on Köppen climate classes is used to distribute the sample globally among biomes. The high resolution data are classified to categorical land cover maps using an analyst mediated classification workflow. Our initial application of these data is to evaluate a global 30 m Landsat-derived, continuous field tree cover product. For this application, the categorical reference classification produced at 2 m resolution is converted to percent tree cover per 30 m pixel (secondary sampling unit)for comparison to Landsat-derived estimates of tree cover. We provide example results (based on a subsample of 25 sample blocks in South America) illustrating basic analyses of agreement that can be produced from these reference data. Commercial high resolution data availability and data quality are shown to provide a viable means of validating continuous field tree cover. When completed, the reference classifications for the full sample of 500 blocks will be released for public use.

Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study.

PubMed

Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa

2018-07-01

Automatic text classification techniques are useful for classifying plaintext medical documents. This study aims to automatically predict the cause of death from free text forensic autopsy reports by comparing various schemes for feature extraction, term weighing or feature value representation, text classification, and feature reduction. For experiments, the autopsy reports belonging to eight different causes of death were collected, preprocessed and converted into 43 master feature vectors using various schemes for feature extraction, representation, and reduction. The six different text classification techniques were applied on these 43 master feature vectors to construct a classification model that can predict the cause of death. Finally, classification model performance was evaluated using four performance measures i.e. overall accuracy, macro precision, macro-F-measure, and macro recall. From experiments, it was found that that unigram features obtained the highest performance compared to bigram, trigram, and hybrid-gram features. Furthermore, in feature representation schemes, term frequency, and term frequency with inverse document frequency obtained similar and better results when compared with binary frequency, and normalized term frequency with inverse document frequency. Furthermore, the chi-square feature reduction approach outperformed Pearson correlation, and information gain approaches. Finally, in text classification algorithms, support vector machine classifier outperforms random forest, Naive Bayes, k-nearest neighbor, decision tree, and ensemble-voted classifier. Our results and comparisons hold practical importance and serve as references for future works. Moreover, the comparison outputs will act as state-of-art techniques to compare future proposals with existing automated text classification techniques. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Comparison of locus-specific databases for BRCA1 and BRCA2 variants reveals disparity in variant classification within and among databases.

PubMed

Vail, Paris J; Morris, Brian; van Kan, Aric; Burdett, Brianna C; Moyes, Kelsey; Theisen, Aaron; Kerr, Iain D; Wenstrup, Richard J; Eggington, Julie M

2015-10-01

Genetic variants of uncertain clinical significance (VUSs) are a common outcome of clinical genetic testing. Locus-specific variant databases (LSDBs) have been established for numerous disease-associated genes as a research tool for the interpretation of genetic sequence variants to facilitate variant interpretation via aggregated data. If LSDBs are to be used for clinical practice, consistent and transparent criteria regarding the deposition and interpretation of variants are vital, as variant classifications are often used to make important and irreversible clinical decisions. In this study, we performed a retrospective analysis of 2017 consecutive BRCA1 and BRCA2 genetic variants identified from 24,650 consecutive patient samples referred to our laboratory to establish an unbiased dataset representative of the types of variants seen in the US patient population, submitted by clinicians and researchers for BRCA1 and BRCA2 testing. We compared the clinical classifications of these variants among five publicly accessible BRCA1 and BRCA2 variant databases: BIC, ClinVar, HGMD (paid version), LOVD, and the UMD databases. Our results show substantial disparity of variant classifications among publicly accessible databases. Furthermore, it appears that discrepant classifications are not the result of a single outlier but widespread disagreement among databases. This study also shows that databases sometimes favor a clinical classification when current best practice guidelines (ACMG/AMP/CAP) would suggest an uncertain classification. Although LSDBs have been well established for research applications, our results suggest several challenges preclude their wider use in clinical practice.

Automating document classification for the Immune Epitope Database

PubMed Central

Wang, Peng; Morgan, Alexander A; Zhang, Qing; Sette, Alessandro; Peters, Bjoern

2007-01-01

Background The Immune Epitope Database contains information on immune epitopes curated manually from the scientific literature. Like similar projects in other knowledge domains, significant effort is spent on identifying which articles are relevant for this purpose. Results We here report our experience in automating this process using Naïve Bayes classifiers trained on 20,910 abstracts classified by domain experts. Improvements on the basic classifier performance were made by a) utilizing information stored in PubMed beyond the abstract itself b) applying standard feature selection criteria and c) extracting domain specific feature patterns that e.g. identify peptides sequences. We have implemented the classifier into the curation process determining if abstracts are clearly relevant, clearly irrelevant, or if no certain classification can be made, in which case the abstracts are manually classified. Testing this classification scheme on an independent dataset, we achieve 95% sensitivity and specificity in the 51.1% of abstracts that were automatically classified. Conclusion By implementing text classification, we have sped up the reference selection process without sacrificing sensitivity or specificity of the human expert classification. This study provides both practical recommendations for users of text classification tools, as well as a large dataset which can serve as a benchmark for tool developers. PMID:17655769

A survey on the geographic scope of textual documents

NASA Astrophysics Data System (ADS)

Monteiro, Bruno R.; Davis, Clodoveu A.; Fonseca, Fred

2016-11-01

Recognizing references to places in texts is needed in many applications, such as search engines, location-based social media and document classification. In this paper we present a survey of methods and techniques for the recognition and identification of places referenced in texts. We discuss concepts and terminology, and propose a classification of the solutions given in the literature. We introduce a definition of the Geographic Scope Resolution (GSR) problem, dividing it in three steps: geoparsing, reference resolution, and grounding references. Solutions to the first two steps are organized according to the method used, and solutions to the third step are organized according to the type of output produced. We found that it is difficult to compare existing solutions directly to one another, because they often create their own benchmarking data, targeted to their own problem.

A Study of MX Environmental Management Information System (MXEMIS) Needs.

DTIC Science & Technology

1983-12-01

ENVIRONMENTAL MANAGEMENT INFORMATION SYSTEM (MXEMIS) NEEDS by Ronald Webster Ralph Mitchell Valorie Young -J : 2 34 LA--. Approved for public release...System (SAIFS) The MX Management Information System (MX MIS) The Mobilization Early Warning System (MEWS) The Computer-Aided Environmental Baseline...26 REFERENCES DISTRIBUTION I5 S’ t A STUDY OF MX ENVIRONMENTAL 2 EXISTING SYSTEMS CLASSIFICATION MANAGEMENT INFORMATION SYSTEM (MXEMIS

Selecting reusable components using algebraic specifications

NASA Technical Reports Server (NTRS)

Eichmann, David A.

1992-01-01

A significant hurdle confronts the software reuser attempting to select candidate components from a software repository - discriminating between those components without resorting to inspection of the implementation(s). We outline a mixed classification/axiomatic approach to this problem based upon our lattice-based faceted classification technique and Guttag and Horning's algebraic specification techniques. This approach selects candidates by natural language-derived classification, by their interfaces, using signatures, and by their behavior, using axioms. We briefly outline our problem domain and related work. Lattice-based faceted classifications are described; the reader is referred to surveys of the extensive literature for algebraic specification techniques. Behavioral support for reuse queries is presented, followed by the conclusions.

Review of the literature on benzene exposure and leukemia subtypes.

PubMed

Schnatter, A Robert; Rosamilia, Kim; Wojcik, Nancy C

2005-05-30

The epidemiologic literature on benzene exposure and leukemia in the MEDLINE and TOXNET databases was examined through October 2004 using the keywords "benzene", "leukemia" and "adverse health effects". This search was complemented by reviewing the reference lists from extant literature reviews and criteria documents on benzene. Published studies were characterized according to the type of industry studied and design, exposure assessment, disease classification, and control for confounding variables. Study design consisted of either cohort studies or case-control studies, which were further categorized into population-based and nested case-control studies. Disease classification considered the source of diagnostic information, whether there was clinical confirmation from medical records or histopathological, morphological and/or cytogenetic reviews, and as to whether the International Classification of Diseases (ICD) or the French-American-British (FAB) schemes were used (no studies used the Revised European-American Lymphoma (REAL) classification scheme). Nine cohort and 13 case-control studies met inclusion criteria for this review. High and significant acute myeloid leukemia risks with positive dose response relationships were identified across study designs, particularly in the "well-conducted" cohort studies and especially in more highly exposed workers in rubber, shoe, and paint industries. Risks for chronic lymphocytic leukemia (CLL) tended to show elevations in nested case-control studies, with possible dose response relationships in at least two of the three studies. However, cohort studies on CLL show no such risks. Data for chronic myeloid leukemia and acute lymphocytic leukemia are sparse and inconclusive.

The additional benefit of the ML Flow test to classify leprosy patients.

PubMed

Bührer-Sékula, Samira; Illarramendi, Ximena; Teles, Rose B; Penna, Maria Lucia F; Nery, José Augusto C; Sales, Anna Maria; Oskam, Linda; Sampaio, Elizabeth P; Sarno, Euzenir N

2009-08-01

The use of the skin lesion counting classification leads to both under and over diagnosis of leprosy in many instances. Thus, there is a need to complement this classification with another simple and robust test for use in the field. Data of 202 untreated leprosy patients diagnosed at FIOCRUZ, Rio de Janeiro, Brazil, was analyzed. There were 90 patients classified as PB and 112 classified as MB according to the reference standard. The BI was positive in 111 (55%) patients and the ML Flow test in 116 (57.4%) patients. The ML Flow test was positive in 95 (86%) of the patients with a positive BI. The lesion counting classification was confirmed by both BI and ML Flow tests in 65% of the 92 patients with 5 or fewer lesions, and in 76% of the 110 patients with 6 or more lesions. The combination of skin lesion counting and the ML Flow test results yielded a sensitivity of 85% and a specificity of 87% for MB classification, and correctly classified 86% of the patients when compared to the standard reference. A considerable proportion of the patients (43.5%) with discordant test results in relation to standard classification was in reaction. The use of any classification system has limitations, especially those that oversimplify a complex disease such as leprosy. In the absence of an experienced dermatologist and slit skin smear, the ML Flow test could be used to improve treatment decisions in field conditions.

Evaluation of normalization methods for cDNA microarray data by k-NN classification

PubMed Central

Wu, Wei; Xing, Eric P; Myers, Connie; Mian, I Saira; Bissell, Mina J

2005-01-01

Background Non-biological factors give rise to unwanted variations in cDNA microarray data. There are many normalization methods designed to remove such variations. However, to date there have been few published systematic evaluations of these techniques for removing variations arising from dye biases in the context of downstream, higher-order analytical tasks such as classification. Results Ten location normalization methods that adjust spatial- and/or intensity-dependent dye biases, and three scale methods that adjust scale differences were applied, individually and in combination, to five distinct, published, cancer biology-related cDNA microarray data sets. Leave-one-out cross-validation (LOOCV) classification error was employed as the quantitative end-point for assessing the effectiveness of a normalization method. In particular, a known classifier, k-nearest neighbor (k-NN), was estimated from data normalized using a given technique, and the LOOCV error rate of the ensuing model was computed. We found that k-NN classifiers are sensitive to dye biases in the data. Using NONRM and GMEDIAN as baseline methods, our results show that single-bias-removal techniques which remove either spatial-dependent dye bias (referred later as spatial effect) or intensity-dependent dye bias (referred later as intensity effect) moderately reduce LOOCV classification errors; whereas double-bias-removal techniques which remove both spatial- and intensity effect reduce LOOCV classification errors even further. Of the 41 different strategies examined, three two-step processes, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, all of which removed intensity effect globally and spatial effect locally, appear to reduce LOOCV classification errors most consistently and effectively across all data sets. We also found that the investigated scale normalization methods do not reduce LOOCV classification error. Conclusion Using LOOCV error of k-NNs as the evaluation criterion, three double-bias-removal normalization strategies, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, outperform other strategies for removing spatial effect, intensity effect and scale differences from cDNA microarray data. The apparent sensitivity of k-NN LOOCV classification error to dye biases suggests that this criterion provides an informative measure for evaluating normalization methods. All the computational tools used in this study were implemented using the R language for statistical computing and graphics. PMID:16045803

Evaluation of normalization methods for cDNA microarray data by k-NN classification.

PubMed

Wu, Wei; Xing, Eric P; Myers, Connie; Mian, I Saira; Bissell, Mina J

2005-07-26

Non-biological factors give rise to unwanted variations in cDNA microarray data. There are many normalization methods designed to remove such variations. However, to date there have been few published systematic evaluations of these techniques for removing variations arising from dye biases in the context of downstream, higher-order analytical tasks such as classification. Ten location normalization methods that adjust spatial- and/or intensity-dependent dye biases, and three scale methods that adjust scale differences were applied, individually and in combination, to five distinct, published, cancer biology-related cDNA microarray data sets. Leave-one-out cross-validation (LOOCV) classification error was employed as the quantitative end-point for assessing the effectiveness of a normalization method. In particular, a known classifier, k-nearest neighbor (k-NN), was estimated from data normalized using a given technique, and the LOOCV error rate of the ensuing model was computed. We found that k-NN classifiers are sensitive to dye biases in the data. Using NONRM and GMEDIAN as baseline methods, our results show that single-bias-removal techniques which remove either spatial-dependent dye bias (referred later as spatial effect) or intensity-dependent dye bias (referred later as intensity effect) moderately reduce LOOCV classification errors; whereas double-bias-removal techniques which remove both spatial- and intensity effect reduce LOOCV classification errors even further. Of the 41 different strategies examined, three two-step processes, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, all of which removed intensity effect globally and spatial effect locally, appear to reduce LOOCV classification errors most consistently and effectively across all data sets. We also found that the investigated scale normalization methods do not reduce LOOCV classification error. Using LOOCV error of k-NNs as the evaluation criterion, three double-bias-removal normalization strategies, IGLOESS-SLFILTERW7, ISTSPLINE-SLLOESS and IGLOESS-SLLOESS, outperform other strategies for removing spatial effect, intensity effect and scale differences from cDNA microarray data. The apparent sensitivity of k-NN LOOCV classification error to dye biases suggests that this criterion provides an informative measure for evaluating normalization methods. All the computational tools used in this study were implemented using the R language for statistical computing and graphics.

Starmind: A Fuzzy Logic Knowledge-Based System for the Automated Classification of Stars in the MK System

NASA Astrophysics Data System (ADS)

Manteiga, M.; Carricajo, I.; Rodríguez, A.; Dafonte, C.; Arcay, B.

2009-02-01

Astrophysics is evolving toward a more rational use of costly observational data by intelligently exploiting the large terrestrial and spatial astronomical databases. In this paper, we present a study showing the suitability of an expert system to perform the classification of stellar spectra in the Morgan and Keenan (MK) system. Using the formalism of artificial intelligence for the development of such a system, we propose a rules' base that contains classification criteria and confidence grades, all integrated in an inference engine that emulates human reasoning by means of a hierarchical decision rules tree that also considers the uncertainty factors associated with rules. Our main objective is to illustrate the formulation and development of such a system for an astrophysical classification problem. An extensive spectral database of MK standard spectra has been collected and used as a reference to determine the spectral indexes that are suitable for classification in the MK system. It is shown that by considering 30 spectral indexes and associating them with uncertainty factors, we can find an accurate diagnose in MK types of a particular spectrum. The system was evaluated against the NOAO-INDO-US spectral catalog.

Classifying the bacterial gut microbiota of termites and cockroaches: A curated phylogenetic reference database (DictDb).

PubMed

Mikaelyan, Aram; Köhler, Tim; Lampert, Niclas; Rohland, Jeffrey; Boga, Hamadi; Meuser, Katja; Brune, Andreas

2015-10-01

Recent developments in sequencing technology have given rise to a large number of studies that assess bacterial diversity and community structure in termite and cockroach guts based on large amplicon libraries of 16S rRNA genes. Although these studies have revealed important ecological and evolutionary patterns in the gut microbiota, classification of the short sequence reads is limited by the taxonomic depth and resolution of the reference databases used in the respective studies. Here, we present a curated reference database for accurate taxonomic analysis of the bacterial gut microbiota of dictyopteran insects. The Dictyopteran gut microbiota reference Database (DictDb) is based on the Silva database but was significantly expanded by the addition of clones from 11 mostly unexplored termite and cockroach groups, which increased the inventory of bacterial sequences from dictyopteran guts by 26%. The taxonomic depth and resolution of DictDb was significantly improved by a general revision of the taxonomic guide tree for all important lineages, including a detailed phylogenetic analysis of the Treponema and Alistipes complexes, the Fibrobacteres, and the TG3 phylum. The performance of this first documented version of DictDb (v. 3.0) using the revised taxonomic guide tree in the classification of short-read libraries obtained from termites and cockroaches was highly superior to that of the current Silva and RDP databases. DictDb uses an informative nomenclature that is consistent with the literature also for clades of uncultured bacteria and provides an invaluable tool for anyone exploring the gut community structure of termites and cockroaches. Copyright © 2015 Elsevier GmbH. All rights reserved.

State-Level School Competitive Food and Beverage Laws Are Associated with Children's Weight Status

ERIC Educational Resources Information Center

Hennessy, Erin; Oh, April; Agurs-Collins, Tanya; Chriqui, Jamie F.; Mâsse, Louise C.; Moser, Richard P.; Perna, Frank

2014-01-01

Background: This study attempted to determine whether state laws regulating low nutrient, high energy-dense foods and beverages sold outside of the reimbursable school meals program (referred to as "competitive foods") are associated with children's weight status. Methods: We use the Classification of Laws Associated with School…

Monitoring of Qualifications and Employment in Austria: An Empirical Approach Based on the Labour Force Survey

ERIC Educational Resources Information Center

Lassnigg, Lorenz; Vogtenhuber, Stefan

2011-01-01

The empirical approach referred to in this article describes the relationship between education and training (ET) supply and employment in Austria; the use of the new ISCED (International Standard Classification of Education) fields of study variable makes this approach applicable abroad. The purpose is to explore a system that produces timely…

Stages of Change for Physical Activity in a Community Sample of Adolescents

ERIC Educational Resources Information Center

De Bourdeaudhuij, Ilse; Philippaerts, Renaat; Crombez, Geert; Matton, Lynn; Wijndaele, Katrien; Balduck, Anne-Line; Lefevre, Johan

2005-01-01

The aims of the present study were to investigate (1) the proportion of adolescents in each of the stages of change, (2) the differences in psychosocial factors and in physical activity between the stages, and (3) the classification accuracy using several reference criteria. A random sample of 38 schools from the Flemish community in Belgium…

Medical Record Clerk Training Program, Course of Study; Student Manual: For Medical Record Personnel in Small Rural Hospitals in Colorado.

ERIC Educational Resources Information Center

Community Health Service (DHEW/PHS), Arlington, VA. Div. of Health Resources.

The manual provides major topics, objectives, activities and, procedures, references and materials, and assignments for the training program. The topics covered are hospital organization and community role, organization and management of a medical records department, international classification of diseases and operations, medical terminology,…

Methods of classification for women undergoing induction of labour: a systematic review and novel classification system.

PubMed

Nippita, T A; Khambalia, A Z; Seeho, S K; Trevena, J A; Patterson, J A; Ford, J B; Morris, J M; Roberts, C L

2015-09-01

A lack of reproducible methods for classifying women having an induction of labour (IOL) has led to controversies regarding IOL and related maternal and perinatal health outcomes. To evaluate articles that classify IOL and to develop a novel IOL classification system. Electronic searches using CINAHL, EMBASE, WEB of KNOWLEDGE, and reference lists. Two reviewers independently assessed studies that classified women having an IOL. For the systematic review, data were extracted on study characteristics, quality, and results. Pre-specified criteria were used for evaluation. A multidisciplinary collaboration developed a new classification system using a clinically logical model and stakeholder feedback, demonstrating applicability in a population cohort of 909 702 maternities in New South Wales, Australia, over the period 2002-2011. All seven studies included in the systematic review categorised women according to the presence or absence of varying medical indications for IOL. Evaluation identified uncertainties or deficiencies across all studies, related to the criteria of total inclusivity, reproducibility, clinical utility, implementability, and data availability. A classification system of ten groups was developed based on parity, previous caesarean, gestational age, number, and presentation of the fetus. Nulliparous and parous women at full term were the largest groups (21.2 and 24.5%, respectively), and accounted for the highest proportion of all IOL (20.7 and 21.5%, respectively). Current methods of classifying women undertaking IOL based on medical indications are inadequate. We propose a classification system that has the attributes of simplicity and clarity, uses information that is readily and reliably collected, and enables the standard characterisation of populations of women having an IOL across and within jurisdictions. © 2015 Royal College of Obstetricians and Gynaecologists.

Chemical-Help Application for Classification and Identification of Stormwater Constituents

USGS Publications Warehouse

Granato, Gregory E.; Driskell, Timothy R.; Nunes, Catherine

2000-01-01

A computer application called Chemical Help was developed to facilitate review of reports for the National Highway Runoff Water-Quality Data and Methodology Synthesis (NDAMS). The application provides a tool to quickly find a proper classification for any constituent in the NDAMS review sheets. Chemical Help contents include the name of each water-quality property, constituent, or parameter, the section number within the NDAMS review sheet, the organizational levels within a classification hierarchy, the database number, and where appropriate, the chemical formula, the Chemical Abstract Service number, and a list of synonyms (for the organic chemicals). Therefore, Chemical Help provides information necessary to research available reference data for the water-quality properties and constituents of potential interest in stormwater studies. Chemical Help is implemented in the Microsoft help-system interface. (Computer files for the use and documentation of Chemical Help are included on an accompanying diskette.)

[Hand eczema. The clinical classification of the roles of exogenous and endogenous factors in each type].

PubMed

Tamiya, Y

1994-08-01

Hand eczema is one of the most common dermatological disorders. Although it is a general term referring to eczematous dermatitis of the hands, it actually covers a wide range of diseases. The classification of hand eczema is controversial even now, as definitions of individual diseases have not yet been established. It is well-known that exogenous factors, such as chemicals or water, are associated with the occurrence of hand eczema. In this study, we focused on endogenous factors, especially personal or family history of atopy as a causative factor in hand eczema. According to exogenous and endogenous factors, we classified hand eczema into three types: atopic dermatitis, contact dermatitis and dysidrosis. This classification is useful because it makes the definition of each disease clear. Skin-humidity and sebum measurement are simple and rapid methods of determining personal atopy, skin condition and the effect of treatment on hand eczema patients.

[Preoperative risk assessment with the ASA classification. A prospective study of morbidity and mortality in various ASA classes in 2,937 patients in general surgery].

PubMed

Menke, H; John, K D; Klein, A; Lorenz, W; Junginger, T

1992-12-01

The value of ASA classification in assessment of perioperative risk, i.e. especially postoperative morbidity, was analyzed prospectively using the data of 2937 patients. The analysis took into account the criteria validity, reliability, and sensitivity. The incidence of post-operative morbidity after elective surgery rose from 3.9% in ASA class I to 36% in ASA class IV. Mortality was 0.6% in ASA class II, whereas 9.3% died in ASA class IV. Morbidity, mortality respectively, after emergency surgery was 10.2% in ASA class II compared to 69% in class IV, mortality 1.4% compared to 21.5%. Differences between the ASA classes were confirmed (p-value < 0.05) considering separate kinds of complications and different periods. Furthermore, ASA classification was a valuable reference to length of stay and severity of necessary therapy at the ICU.

Object-Based Random Forest Classification of Land Cover from Remotely Sensed Imagery for Industrial and Mining Reclamation

NASA Astrophysics Data System (ADS)

Chen, Y.; Luo, M.; Xu, L.; Zhou, X.; Ren, J.; Zhou, J.

2018-04-01

The RF method based on grid-search parameter optimization could achieve a classification accuracy of 88.16 % in the classification of images with multiple feature variables. This classification accuracy was higher than that of SVM and ANN under the same feature variables. In terms of efficiency, the RF classification method performs better than SVM and ANN, it is more capable of handling multidimensional feature variables. The RF method combined with object-based analysis approach could highlight the classification accuracy further. The multiresolution segmentation approach on the basis of ESP scale parameter optimization was used for obtaining six scales to execute image segmentation, when the segmentation scale was 49, the classification accuracy reached the highest value of 89.58 %. The classification accuracy of object-based RF classification was 1.42 % higher than that of pixel-based classification (88.16 %), and the classification accuracy was further improved. Therefore, the RF classification method combined with object-based analysis approach could achieve relatively high accuracy in the classification and extraction of land use information for industrial and mining reclamation areas. Moreover, the interpretation of remotely sensed imagery using the proposed method could provide technical support and theoretical reference for remotely sensed monitoring land reclamation.

A regional classification scheme for estimating reference water quality in streams using land-use-adjusted spatial regression-tree analysis

USGS Publications Warehouse

Robertson, Dale M.; Saad, D.A.; Heisey, D.M.

2006-01-01

Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States. ?? 2006 Springer Science+Business Media, Inc.

20 CFR 702.504 - Vocational rehabilitation; referrals to State Employment Agencies.

Code of Federal Regulations, 2010 CFR

2010-04-01

... former private employers did not result in a job reassignment or in a job retention, shall be referred... counseling, job classification, and selective placement assistance. Referrals shall be made to State... shall be advised of available job counseling services and informed that he is being referred for...

Automated Coastal Engineering System: Technical Reference

DTIC Science & Technology

1992-09-01

of Contents ACES Technical Reference Wave Transmission Through Permeable Structures ..................................... 5-4 Littoral Processes...A-2 Table A-4: Grain-Size Scales ( Soil Classification) ..................................... A-3 Table A-5: Major Tidal Constituents... Permeable Structures Lonphore Sediment Tranaport Littoral Numerical Si~ulation of Time-Dependent Beach and Dune Erosion Processes Calculation of Composite

20 CFR 654.5 - Classification of labor surplus areas.

Code of Federal Regulations, 2010 CFR

2010-04-01

... unemployment rate for all civilian workers in the civil jurisdiction for the reference period is (1) 120 percent of the national average unemployment rate for civilian workers or higher for the reference period... shall be classified as a labor surplus area if the average unemployment rate for all civilian workers...

42 CFR 412.503 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... through September 30. LTC-DRG stands for the diagnosis-related group used to classify patient discharges... on or after October 1, 2007, are classified by a severity-adjusted patient classification system, the MS-LTC-DRGs. Any reference to the term “LTC-DRG” shall be considered a reference to the term “MS-LTC...

Two Approaches to Estimation of Classification Accuracy Rate under Item Response Theory

ERIC Educational Resources Information Center

Lathrop, Quinn N.; Cheng, Ying

2013-01-01

Within the framework of item response theory (IRT), there are two recent lines of work on the estimation of classification accuracy (CA) rate. One approach estimates CA when decisions are made based on total sum scores, the other based on latent trait estimates. The former is referred to as the Lee approach, and the latter, the Rudner approach,…

[Management of chemical products and European standards: new classification criteria according to the 1272/2008 (CLP) regulation].

PubMed

Fanghella, Paola Di Prospero; Aliberti, Ludovica Malaguti

2013-01-01

The European Union adopted regulations (EC) 1907/2006 REACH e (EC)1272/2008 CLP, to manage chemicals. REACH requires for evaluation and management of risks connected to the use of chemical substances, while o CLP provides for the classification, labelling and packagings of dangerous substances and mixtures by implementing in the EU the UN Globally Harmonised System of Classification and Labelling applying the building block approach, that is taking on board the hazard classes and categories which are close to the existing EU system in order to maintain the level of protection of human health and environment. This regulation provides also for the notification of the classification and labelling of substances to the Classification & Labelling Inventory established by the European Chemicals Agency (ECHA). Some european downstream regulations making reference to the classification criteria, as the health and safety laws at workplace, need to be adapted to these regulations.

Quantification of urban structure on building block level utilizing multisensoral remote sensing data

NASA Astrophysics Data System (ADS)

Wurm, Michael; Taubenböck, Hannes; Dech, Stefan

2010-10-01

Dynamics of urban environments are a challenge to a sustainable development. Urban areas promise wealth, realization of individual dreams and power. Hence, many cities are characterized by a population growth as well as physical development. Traditional, visual mapping and updating of urban structure information of cities is a very laborious and cost-intensive task, especially for large urban areas. For this purpose, we developed a workflow for the extraction of the relevant information by means of object-based image classification. In this manner, multisensoral remote sensing data has been analyzed in terms of very high resolution optical satellite imagery together with height information by a digital surface model to retrieve a detailed 3D city model with the relevant land-use / land-cover information. This information has been aggregated on the level of the building block to describe the urban structure by physical indicators. A comparison between the indicators derived by the classification and a reference classification has been accomplished to show the correlation between the individual indicators and a reference classification of urban structure types. The indicators have been used to apply a cluster analysis to group the individual blocks into similar clusters.

hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine.

PubMed

Falgreen, Steffen; Ellern Bilgrau, Anders; Brøndum, Rasmus Froberg; Hjort Jakobsen, Lasse; Have, Jonas; Lindblad Nielsen, Kasper; El-Galaly, Tarec Christoffer; Bødker, Julie Støve; Schmitz, Alexander; H Young, Ken; Johnsen, Hans Erik; Dybkær, Karen; Bøgsted, Martin

2016-01-01

Dozens of omics based cancer classification systems have been introduced with prognostic, diagnostic, and predictive capabilities. However, they often employ complex algorithms and are only applicable on whole cohorts of patients, making them difficult to apply in a personalized clinical setting. This prompted us to create hemaClass.org, an online web application providing an easy interface to one-by-one RMA normalization of microarrays and subsequent risk classifications of diffuse large B-cell lymphoma (DLBCL) into cell-of-origin and chemotherapeutic sensitivity classes. Classification results for one-by-one array pre-processing with and without a laboratory specific RMA reference dataset were compared to cohort based classifiers in 4 publicly available datasets. Classifications showed high agreement between one-by-one and whole cohort pre-processsed data when a laboratory specific reference set was supplied. The website is essentially the R-package hemaClass accompanied by a Shiny web application. The well-documented package can be used to run the website locally or to use the developed methods programmatically. The website and R-package is relevant for biological and clinical lymphoma researchers using affymetrix U-133 Plus 2 arrays, as it provides reliable and swift methods for calculation of disease subclasses. The proposed one-by-one pre-processing method is relevant for all researchers using microarrays.

Automatic parquet block sorting using real-time spectral classification

NASA Astrophysics Data System (ADS)

Astrom, Anders; Astrand, Erik; Johansson, Magnus

1999-03-01

This paper presents a real-time spectral classification system based on the PGP spectrograph and a smart image sensor. The PGP is a spectrograph which extracts the spectral information from a scene and projects the information on an image sensor, which is a method often referred to as Imaging Spectroscopy. The classification is based on linear models and categorizes a number of pixels along a line. Previous systems adopting this method have used standard sensors, which often resulted in poor performance. The new system, however, is based on a patented near-sensor classification method, which exploits analogue features on the smart image sensor. The method reduces the enormous amount of data to be processed at an early stage, thus making true real-time spectral classification possible. The system has been evaluated on hardwood parquet boards showing very good results. The color defects considered in the experiments were blue stain, white sapwood, yellow decay and red decay. In addition to these four defect classes, a reference class was used to indicate correct surface color. The system calculates a statistical measure for each parquet block, giving the pixel defect percentage. The patented method makes it possible to run at very high speeds with a high spectral discrimination ability. Using a powerful illuminator, the system can run with a line frequency exceeding 2000 line/s. This opens up the possibility to maintain high production speed and still measure with good resolution.

Remote sensing based detection of forested wetlands: An evaluation of LiDAR, aerial imagery, and their data fusion

NASA Astrophysics Data System (ADS)

Suiter, Ashley Elizabeth

Multi-spectral imagery provides a robust and low-cost dataset for assessing wetland extent and quality over broad regions and is frequently used for wetland inventories. However in forested wetlands, hydrology is obscured by tree canopy making it difficult to detect with multi-spectral imagery alone. Because of this, classification of forested wetlands often includes greater errors than that of other wetlands types. Elevation and terrain derivatives have been shown to be useful for modelling wetland hydrology. But, few studies have addressed the use of LiDAR intensity data detecting hydrology in forested wetlands. Due the tendency of LiDAR signal to be attenuated by water, this research proposed the fusion of LiDAR intensity data with LiDAR elevation, terrain data, and aerial imagery, for the detection of forested wetland hydrology. We examined the utility of LiDAR intensity data and determined whether the fusion of Lidar derived data with multispectral imagery increased the accuracy of forested wetland classification compared with a classification performed with only multi-spectral image. Four classifications were performed: Classification A -- All Imagery, Classification B -- All LiDAR, Classification C -- LiDAR without Intensity, and Classification D -- Fusion of All Data. These classifications were performed using random forest and each resulted in a 3-foot resolution thematic raster of forested upland and forested wetland locations in Vermilion County, Illinois. The accuracies of these classifications were compared using Kappa Coefficient of Agreement. Importance statistics produced within the random forest classifier were evaluated in order to understand the contribution of individual datasets. Classification D, which used the fusion of LiDAR and multi-spectral imagery as input variables, had moderate to strong agreement between reference data and classification results. It was found that Classification A performed using all the LiDAR data and its derivatives (intensity, elevation, slope, aspect, curvatures, and Topographic Wetness Index) was the most accurate classification with Kappa: 78.04%, indicating moderate to strong agreement. However, Classification C, performed with LiDAR derivative without intensity data had less agreement than would be expected by chance, indicating that LiDAR contributed significantly to the accuracy of Classification B.

Emotion recognition from multichannel EEG signals using K-nearest neighbor classification.

PubMed

Li, Mi; Xu, Hongpei; Liu, Xingwang; Lu, Shengfu

2018-04-27

Many studies have been done on the emotion recognition based on multi-channel electroencephalogram (EEG) signals. This paper explores the influence of the emotion recognition accuracy of EEG signals in different frequency bands and different number of channels. We classified the emotional states in the valence and arousal dimensions using different combinations of EEG channels. Firstly, DEAP default preprocessed data were normalized. Next, EEG signals were divided into four frequency bands using discrete wavelet transform, and entropy and energy were calculated as features of K-nearest neighbor Classifier. The classification accuracies of the 10, 14, 18 and 32 EEG channels based on the Gamma frequency band were 89.54%, 92.28%, 93.72% and 95.70% in the valence dimension and 89.81%, 92.24%, 93.69% and 95.69% in the arousal dimension. As the number of channels increases, the classification accuracy of emotional states also increases, the classification accuracy of the gamma frequency band is greater than that of the beta frequency band followed by the alpha and theta frequency bands. This paper provided better frequency bands and channels reference for emotion recognition based on EEG.

Texture classification of lung computed tomography images

NASA Astrophysics Data System (ADS)

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.

The macromorphoscopic databank.

PubMed

Hefner, Joseph T

2018-04-20

The development of identification standards in forensic anthropology requires large and appropriate reference samples comprising individuals with modern birth years. Recent advances in macromorphoscopic trait data collection and analysis have created a need for reference data for classification models and biological distance analyses. The Macromorphoscopic Databank (N ∼ 7,397) serves that function, making publicly available trait scores for a large sample (n = 2,363) of modern American populations and world-wide groups of various geographic origins (n = 1,790). In addition, the MaMD stores reference data for a large sample (n = 3,244) of pre-, proto- and historic Amerindian data, useful for biodistance studies and finer-levels of analysis during NAGPRA-related investigations and repatriations. In developing this database, particular attention was given to the level of classification needed during the estimation of ancestry in a forensic context. To fill the knowledge gap that currently exists in the analysis of these data, the following overview outlines many of the issues and their potential solutions. Developing valuable tools that are useful to other practitioners is the purpose of growing a databank. As the Macromorphoscopic Databank develops through data collection efforts and contributions from the field, its utility as a research and teaching tool will also mature, in turn creating a vital resource for forensic anthropologists for future generations. © 2018 Wiley Periodicals, Inc.

Range Reference Atmosphere 0-70 Km Altitude. Kwajalein Missile Range, Kwajalein, Marshall Islands

DTIC Science & Technology

1982-01-01

DOCUMENT 360-82 KWAJALEIN MISSILE RANGE KWAJALEIN, MARSHALL ISLANDS RANGE REFERENCE ATMOSPHERE 0-70 KM ALTITUDE, C00 L’’I METEOROLOGY GROUP .RANGE...34Reference Atmosphere (Part 1), Kwajale 4n Missile Range, Kwajalein, Marshall Islands ," ADA002664. * 19. KEY WORDS (Continue on revorsae d. If necoeewy...CLASSIFICATION OF TIlS PAGE (Whe~n Data EnterecD -v DOCUMENT 360-82 Vo- KWAJALEIN MISSILE RANGE KWAJALEIN, MARSHALL ISLANDS RANGE REFERENCE ATMOSPHERE 0-70 km

Empirical research on Kano’s model and customer satisfaction

PubMed Central

Lin, Feng-Han; Tsai, Sang-Bing; Lee, Yu-Cheng; Hsiao, Cheng-Fu; Zhou, Jie; Wang, Jiangtao; Shang, Zhiwen

2017-01-01

Products are now developed based on what customers desire, and thus attractive quality creation has become crucial. In studies on customer satisfaction, methods for analyzing quality attributes and enhancing customer satisfaction have been proposed to facilitate product development. Although substantial studies have performed to assess the impact of the attributes on customer satisfaction, little research has been conducted that quantitatively calculate the odds of customer satisfaction for the Kano classification, fitting a nonlinear relationship between attribute-level performance and customer satisfaction. In the present study, the odds of customer satisfaction were determined to identify the classification of quality attributes, and took customer psychology into account to suggest how decision-makers should prioritize the allocation of resources. A novel method for quantitatively assessing quality attributes was proposed to determine classification criteria and fit the nonlinear relationship between quality attributes and customer satisfaction. Subsequently, a case study was conducted on bicycle user satisfaction to verify the novel method. The concept of customer satisfaction odds was integrated with the value function from prospect theory to understand quality attributes. The results of this study can serve as a reference for product designers to create attractive quality attributes in their products and thus enhance customer satisfaction. PMID:28873418

Empirical research on Kano's model and customer satisfaction.

PubMed

Lin, Feng-Han; Tsai, Sang-Bing; Lee, Yu-Cheng; Hsiao, Cheng-Fu; Zhou, Jie; Wang, Jiangtao; Shang, Zhiwen

2017-01-01

Products are now developed based on what customers desire, and thus attractive quality creation has become crucial. In studies on customer satisfaction, methods for analyzing quality attributes and enhancing customer satisfaction have been proposed to facilitate product development. Although substantial studies have performed to assess the impact of the attributes on customer satisfaction, little research has been conducted that quantitatively calculate the odds of customer satisfaction for the Kano classification, fitting a nonlinear relationship between attribute-level performance and customer satisfaction. In the present study, the odds of customer satisfaction were determined to identify the classification of quality attributes, and took customer psychology into account to suggest how decision-makers should prioritize the allocation of resources. A novel method for quantitatively assessing quality attributes was proposed to determine classification criteria and fit the nonlinear relationship between quality attributes and customer satisfaction. Subsequently, a case study was conducted on bicycle user satisfaction to verify the novel method. The concept of customer satisfaction odds was integrated with the value function from prospect theory to understand quality attributes. The results of this study can serve as a reference for product designers to create attractive quality attributes in their products and thus enhance customer satisfaction.

Disability, human rights, and the International Classification of Functioning, Disability, and Health: systematic review.

PubMed

Aluas, Maria; Colombetti, Elena; Osimani, Barbara; Musio, Alessio; Pessina, Adriano

2012-02-01

This literature review focuses on the literature on disability from the ethical and human rights perspective in the light of the International Classification of Functioning, Disability, and Health in the period from January 1, 2008, to June 30, 2010. This article identifies and examines studies that deal with the subject of disability with reference to rights, ethical issues, and justice. A total of 42 articles and 33 books were selected. The subject most frequently dealt with in studies on disability is that of human rights (76% of the articles and 79% of the books examined), followed by topics relating to welfare (52% of articles and 64% of books), International Classification of Functioning, Disability, and Health (38% of articles and 45% of books), justice (24% of articles and 48% of books), education (21% of articles and 61% of books), and work (19% of articles and 39% of books). The subject of disability is dealt with in various fields of study and various disciplines. Most of the studies are based on the legal approach. It is to be hoped that there will be an increase in the philosophical and ethical study of disability, which has only recently entered the European debate.

Molecular phylogeny and systematics of the banana family (Musaceae) inferred from multiple nuclear and chloroplast DNA fragments, with a special reference to the genus Musa.

PubMed

Li, Lin-Feng; Häkkinen, Markku; Yuan, Yong-Ming; Hao, Gang; Ge, Xue-Jun

2010-10-01

Musaceae is a small paleotropical family. Three genera have been recognised within this family although the generic delimitations remain controversial. Most species of the family (around 65 species) have been placed under the genus Musa and its infrageneric classification has long been disputed. In this study, we obtained nuclear ribosomal ITS and chloroplast (atpB-rbcL, rps16, and trnL-F) DNA sequences of 36 species (42 accessions of ingroups representing three genera) together with 10 accessions of ingroups retrieved from GenBank database and 4 accessions of outgroups, to construct the phylogeny of the family, with a special reference to the infrageneric classification of the genus Musa. Our phylogenetic analyses elaborated previous results in supporting the monophyly of the family and suggested that Musella and Ensete may be congeneric or at least closely related, but refuted the previous infrageneric classification of Musa. None of the five sections of Musa previously defined based on morphology was recovered as monophyletic group in the molecular phylogeny. Two infrageneric clades were identified, which corresponded well to the basic chromosome numbers of x=11 and 10/9/7, respectively: the former clade comprises species from the sections Musa and Rhodochlamys while the latter contains sections of Callimusa, Australimusa, and Ingentimusa. Copyright 2010 Elsevier Inc. All rights reserved.

Issues in the classification of disease instances with ontologies.

PubMed

Burgun, Anita; Bodenreider, Olivier; Jacquelinet, Christian

2005-01-01

Ontologies define classes of entities and their interrelations. They are used to organize data according to a theory of the domain. Towards that end, ontologies provide class definitions (i.e., the necessary and sufficient conditions for defining class membership). In medical ontologies, it is often difficult to establish such definitions for diseases. We use three examples (anemia, leukemia and schizophrenia) to illustrate the limitations of ontologies as classification resources. We show that eligibility criteria are often more useful than the Aristotelian definitions traditionally used in ontologies. Examples of eligibility criteria for diseases include complex predicates such as ' x is an instance of the class C when at least n criteria among m are verified' and 'symptoms must last at least one month if not treated, but less than one month, if effectively treated'. References to normality and abnormality are often found in disease definitions, but the operational definition of these references (i.e., the statistical and contextual information necessary to define them) is rarely provided. We conclude that knowledge bases that include probabilistic and statistical knowledge as well as rule-based criteria are more useful than Aristotelian definitions for representing the predicates defined by necessary and sufficient conditions. Rich knowledge bases are needed to clarify the relations between individuals and classes in various studies and applications. However, as ontologies represent relations among classes, they can play a supporting role in disease classification services built primarily on knowledge bases.

Crowd-sourced data collection to support automatic classification of building footprint data

NASA Astrophysics Data System (ADS)

Hecht, Robert; Kalla, Matthias; Krüger, Tobias

2018-05-01

Human settlements are mainly formed by buildings with their different characteristics and usage. Despite the importance of buildings for the economy and society, complete regional or even national figures of the entire building stock and its spatial distribution are still hardly available. Available digital topographic data sets created by National Mapping Agencies or mapped voluntarily through a crowd via Volunteered Geographic Information (VGI) platforms (e.g. OpenStreetMap) contain building footprint information but often lack additional information on building type, usage, age or number of floors. For this reason, predictive modeling is becoming increasingly important in this context. The capabilities of machine learning allow for the prediction of building types and other building characteristics and thus, the efficient classification and description of the entire building stock of cities and regions. However, such data-driven approaches always require a sufficient amount of ground truth (reference) information for training and validation. The collection of reference data is usually cost-intensive and time-consuming. Experiences from other disciplines have shown that crowdsourcing offers the possibility to support the process of obtaining ground truth data. Therefore, this paper presents the results of an experimental study aiming at assessing the accuracy of non-expert annotations on street view images collected from an internet crowd. The findings provide the basis for a future integration of a crowdsourcing component into the process of land use mapping, particularly the automatic building classification.

Sociometric-Status-Group Classification of Mainstreamed Children Who Have Moderate Learning Difficulties: An Investigation of Personal and Environmental Factors.

ERIC Educational Resources Information Center

Frederickson, Norah L.; Furnham, Adrian F.

1998-01-01

Study examines the classes of variables identified in D. L. MacMillan and G. M. Morrison's (1984) multicomponent model for research on sociometric status in special education. Results are discussed with reference to social-exchange theory, as an integrative basis for research on children's sociometric status. Implications for mainstreaming…

Progress toward the determination of correct classification rates in fire debris analysis.

PubMed

Waddell, Erin E; Song, Emma T; Rinke, Caitlin N; Williams, Mary R; Sigman, Michael E

2013-07-01

Principal components analysis (PCA), linear discriminant analysis (LDA), and quadratic discriminant analysis (QDA) were used to develop a multistep classification procedure for determining the presence of ignitable liquid residue in fire debris and assigning any ignitable liquid residue present into the classes defined under the American Society for Testing and Materials (ASTM) E 1618-10 standard method. A multistep classification procedure was tested by cross-validation based on model data sets comprised of the time-averaged mass spectra (also referred to as total ion spectra) of commercial ignitable liquids and pyrolysis products from common building materials and household furnishings (referred to simply as substrates). Fire debris samples from laboratory-scale and field test burns were also used to test the model. The optimal model's true-positive rate was 81.3% for cross-validation samples and 70.9% for fire debris samples. The false-positive rate was 9.9% for cross-validation samples and 8.9% for fire debris samples. © 2013 American Academy of Forensic Sciences.

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

PubMed Central

Plenis, Alina; Rekowska, Natalia; Bączek, Tomasz

2016-01-01

This article focuses on correlating the column classification obtained from the method created at the Katholieke Universiteit Leuven (KUL), with the chromatographic resolution attained in biomedical separation. In the KUL system, each column is described with four parameters, which enables estimation of the FKUL value characterising similarity of those parameters to the selected reference stationary phase. Thus, a ranking list based on the FKUL value can be calculated for the chosen reference column, then correlated with the results of the column performance test. In this study, the column performance test was based on analysis of moclobemide and its two metabolites in human plasma by liquid chromatography (LC), using 18 columns. The comparative study was performed using traditional correlation of the FKUL values with the retention parameters of the analytes describing the column performance test. In order to deepen the comparative assessment of both data sets, factor analysis (FA) was also used. The obtained results indicated that the stationary phase classes, closely related according to the KUL method, yielded comparable separation for the target substances. Therefore, the column ranking system based on the FKUL-values could be considered supportive in the choice of the appropriate column for biomedical analysis. PMID:26805819

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

PubMed

Plenis, Alina; Rekowska, Natalia; Bączek, Tomasz

2016-01-21

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

A phylogenomic approach to bacterial subspecies classification: proof of concept in Mycobacterium abscessus.

PubMed

Tan, Joon Liang; Khang, Tsung Fei; Ngeow, Yun Fong; Choo, Siew Woh

2013-12-13

Mycobacterium abscessus is a rapidly growing mycobacterium that is often associated with human infections. The taxonomy of this species has undergone several revisions and is still being debated. In this study, we sequenced the genomes of 12 M. abscessus strains and used phylogenomic analysis to perform subspecies classification. A data mining approach was used to rank and select informative genes based on the relative entropy metric for the construction of a phylogenetic tree. The resulting tree topology was similar to that generated using the concatenation of five classical housekeeping genes: rpoB, hsp65, secA, recA and sodA. Additional support for the reliability of the subspecies classification came from the analysis of erm41 and ITS gene sequences, single nucleotide polymorphisms (SNPs)-based classification and strain clustering demonstrated by a variable number tandem repeat (VNTR) assay and a multilocus sequence analysis (MLSA). We subsequently found that the concatenation of a minimal set of three median-ranked genes: DNA polymerase III subunit alpha (polC), 4-hydroxy-2-ketovalerate aldolase (Hoa) and cell division protein FtsZ (ftsZ), is sufficient to recover the same tree topology. PCR assays designed specifically for these genes showed that all three genes could be amplified in the reference strain of M. abscessus ATCC 19977T. This study provides proof of concept that whole-genome sequence-based data mining approach can provide confirmatory evidence of the phylogenetic informativeness of existing markers, as well as lead to the discovery of a more economical and informative set of markers that produces similar subspecies classification in M. abscessus. The systematic procedure used in this study to choose the informative minimal set of gene markers can potentially be applied to species or subspecies classification of other bacteria.

[Difficulties in learning mathematics].

PubMed

Rebollo, M A; Rodríguez, A L

2006-02-13

To discuss our concern for some aspects of mathematics learning disorders related to the nomenclature employed and their diagnosis; these aspects refer to the term 'dyscalculia' and to its diagnosis (especially syndromatic diagnosis). We also intend to propose a classification that could help to define the terminology. Lastly we are going to consider the different aspects of diagnosis and to determine which of them are indispensable in the diagnosis of primary and secondary disorders. As far as the nomenclature is concerned, we refer to the term 'dyscalculia'. The origins of the term are analysed along with the reasons why it should not be used in children with difficulties in learning mathematics. We propose a classification and denominations for the different types that should undoubtedly be discussed. With respect to the diagnosis, several problems related to the syndromatic diagnosis are considered, since in our country there are no standardised tests with which to study performance in arithmetic and geometry. This means that criterion reference tests are conducted to try to establish current and potential performance. At this stage of the diagnosis pedagogical and psychological studies must be conducted. The important factors with regard to the topographical and aetiological diagnoses are prior knowledge, results from the studies that have been carried out and findings from imaging studies. The importance of a genetic study must be defined in the aetiological diagnosis. We propose a nomenclature to replace the term 'dyscalculia'. Standardised tests are needed for the diagnosis. The need to establish current and potential performance is hierarchized. With regard to the topographical diagnosis, we highlight the need for more information about geometry, and in aetiological studies the analyses must be conducted with greater numbers of children.

Searching bioremediation patents through Cooperative Patent Classification (CPC).

PubMed

Prasad, Rajendra

2016-03-01

Patent classification systems have traditionally evolved independently at each patent jurisdiction to classify patents handled by their examiners to be able to search previous patents while dealing with new patent applications. As patent databases maintained by them went online for free access to public as also for global search of prior art by examiners, the need arose for a common platform and uniform structure of patent databases. The diversity of different classification, however, posed problems of integrating and searching relevant patents across patent jurisdictions. To address this problem of comparability of data from different sources and searching patents, WIPO in the recent past developed what is known as International Patent Classification (IPC) system which most countries readily adopted to code their patents with IPC codes along with their own codes. The Cooperative Patent Classification (CPC) is the latest patent classification system based on IPC/European Classification (ECLA) system, developed by the European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) which is likely to become a global standard. This paper discusses this new classification system with reference to patents on bioremediation.

Program for Critical Technologies in Breast Oncology

DTIC Science & Technology

1999-07-01

the tissues, and in a ethical manner that respects the patients’ rights . The Program for Critical Technologies in Breast Oncology helps address all of...diagnosis, database 15. NUMBER OF PAGES 148 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF THIS...closer to clinical utility. Page 17 References Adida C. Crotty PL. McGrath J. Berrebi D. Diebold J. Altieri DC. Developmentally regulated

Evaluation of the Retrieval of Nuclear Science Document References Using the Universal Decimal Classification as the Indexing Language for a Computer-Based System

ERIC Educational Resources Information Center

Atherton, Pauline; And Others

A single issue of Nuclear Science Abstracts, containing about 2,300 abstracts, was indexed by Universal Decimal Classification (UDC) using the Special Subject Edition of UDC for Nuclear Science and Technology. The descriptive cataloging and UDC-indexing records formed a computer-stored data base. A systematic random sample of 500 additional…

The Characteristics of Learning Disabled and Other Handicapped Students Referred for Evaluation in the State of Iowa.

ERIC Educational Resources Information Center

Wilson, Lonny; And Others

1986-01-01

Demographic data, IQ, achievement, perceptual-motor, behavior ratings, and diagnostic classification (learning, mental, emotional disability or no handicap) were analyzed for all children (N=2002) referred for complete psychological evaluation during one school year in Iowa. Learning disabled children showed a distinct pattern different from…

Tests: A Comprehensive Reference for Assessments in Psychology, Education, and Business. Fourth Edition.

ERIC Educational Resources Information Center

Maddox, Taddy, Ed.

The fourth edition of this reference guide contains information on thousands of assessment instruments published by 221 publishers and available for use by psychologists, educators, and human resources personnel. The assessments described are organized according to a system of primary classification and cross referencing intended to make the…

Metacognitive judgments of repetition and variability effects in natural concept learning: evidence for variability neglect.

PubMed

Wahlheim, Christopher N; Finn, Bridgid; Jacoby, Larry L

2012-07-01

In four experiments, we examined the effects of repetitions and variability on the learning of bird families and metacognitive awareness of such effects. Of particular interest was the accuracy of, and bases for, predictions regarding classification of novel bird species, referred to as category learning judgments (CLJs). Participants studied birds in high repetitions and high variability conditions. These conditions differed in the number of presentations of each bird (repetitions) and the number of unique species from each family (variability). After study, participants made CLJs for each family and were then tested. Results from a classification test revealed repetition benefits for studied species and variability benefits for novel species. In contrast with performance, CLJs did not reflect the benefits of variability. Results showed that CLJs were susceptible to accessibility-based metacognitive illusions produced by additional repetitions of studied items.

False alarm reduction by the And-ing of multiple multivariate Gaussian classifiers

NASA Astrophysics Data System (ADS)

Dobeck, Gerald J.; Cobb, J. Tory

2003-09-01

The high-resolution sonar is one of the principal sensors used by the Navy to detect and classify sea mines in minehunting operations. For such sonar systems, substantial effort has been devoted to the development of automated detection and classification (D/C) algorithms. These have been spurred by several factors including (1) aids for operators to reduce work overload, (2) more optimal use of all available data, and (3) the introduction of unmanned minehunting systems. The environments where sea mines are typically laid (harbor areas, shipping lanes, and the littorals) give rise to many false alarms caused by natural, biologic, and man-made clutter. The objective of the automated D/C algorithms is to eliminate most of these false alarms while still maintaining a very high probability of mine detection and classification (PdPc). In recent years, the benefits of fusing the outputs of multiple D/C algorithms have been studied. We refer to this as Algorithm Fusion. The results have been remarkable, including reliable robustness to new environments. This paper describes a method for training several multivariate Gaussian classifiers such that their And-ing dramatically reduces false alarms while maintaining a high probability of classification. This training approach is referred to as the Focused- Training method. This work extends our 2001-2002 work where the Focused-Training method was used with three other types of classifiers: the Attractor-based K-Nearest Neighbor Neural Network (a type of radial-basis, probabilistic neural network), the Optimal Discrimination Filter Classifier (based linear discrimination theory), and the Quadratic Penalty Function Support Vector Machine (QPFSVM). Although our experience has been gained in the area of sea mine detection and classification, the principles described herein are general and can be applied to a wide range of pattern recognition and automatic target recognition (ATR) problems.

What is new in genetics and osteogenesis imperfecta classification?

PubMed

Valadares, Eugênia R; Carneiro, Túlio B; Santos, Paula M; Oliveira, Ana Cristina; Zabel, Bernhard

2014-01-01

Literature review of new genes related to osteogenesis imperfecta (OI) and update of its classification. Literature review in the PubMed and OMIM databases, followed by selection of relevant references. In 1979, Sillence et al. developed a classification of OI subtypes based on clinical features and disease severity: OI type I, mild, common, with blue sclera; OI type II, perinatal lethal form; OI type III, severe and progressively deforming, with normal sclera; and OI type IV, moderate severity with normal sclera. Approximately 90% of individuals with OI are heterozygous for mutations in the COL1A1 and COL1A2 genes, with dominant pattern of inheritance or sporadic mutations. After 2006, mutations were identified in the CRTAP, FKBP10, LEPRE1, PLOD2, PPIB, SERPINF1, SERPINH1, SP7, WNT1, BMP1, and TMEM38B genes, associated with recessive OI and mutation in the IFITM5 gene associated with dominant OI. Mutations in PLS3 were recently identified in families with osteoporosis and fractures, with X-linked inheritance pattern. In addition to the genetic complexity of the molecular basis of OI, extensive phenotypic variability resulting from individual loci has also been documented. Considering the discovery of new genes and limited genotype-phenotype correlation, the use of next-generation sequencing tools has become useful in molecular studies of OI cases. The recommendation of the Nosology Group of the International Society of Skeletal Dysplasias is to maintain the classification of Sillence as the prototypical form, universally accepted to classify the degree of severity in OI, while maintaining it free from direct molecular reference. Copyright © 2014 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Utilizing a Value of Information Framework to Improve Ore Collection and Classification Procedures

DTIC Science & Technology

2006-05-01

account for uncertainty in revenues or costs. Studies that utilize this type of deterministic modeling are: Boshkov & Wright (1973); Laubscher (1981... Disney & Peters, 2003). Disney & Peters (2003) reference a number of applications in both the veterinary and agricultural sectors. Agricultural studies...covered by revenue made from selling the end product. Because the cost data are aggregated for the BI and D3 mills at Kiruna, we have to allocate the

CT imaging-based determination and classification of anatomic variations of left gastric vein.

PubMed

Wu, Yongyou; Chen, Guangqiang; Wu, Pengfei; Zhu, Jianbin; Peng, Wei; Xing, Chungen

2017-03-01

Precise determination and classification of left gastric vein (LGV) anatomy are helpful in planning for gastric surgery, in particular, for resection of gastric cancer. However, the anatomy of LGV is highly variable. A systematic classification of its variations is still to be proposed. We aimed to investigate the anatomical variations in LGV using CT imaging and develop a new nomenclature system. We reviewed CT images and tracked the course of LGV in 825 adults. The frequencies of common and variable LGV anatomical courses were recorded. Anatomic variations of LGV were proposed and classified into different types mainly based on its courses. The inflow sites of LGV into the portal system were also considered if common hepatic artery (CHA) or splenic artery (SA) could not be used as a frame of reference due to variations. Detailed anatomy and courses of LGV were depicted on CT images. Using CHA and SA as the frames of reference, the routes of LGV were divided into six types (i.e., PreS, RetroS, Mid, PreCH, RetroCH, and Supra). The inflow sites were classified into four types (i.e., PV, SV, PSV, and LPV). The new classification was mainly based on the courses of LGV, which was validated with MDCT in the 805 cases with an identifiable LGV, namely type I, RetroCH, 49.8 % (401/805); type II, PreS, 20.6 % (166/805); type III, Mid, 20.0 % (161/805); type IV, RetroS, 7.3 % (59/805); type V, Supra, 1.5 % (12/805); and type VI, PreCH, 0.7 % (6/805). Type VII, designated to the cases in which SA and CHA could not be used as frames of reference, was not observed in this series. Detailed depiction of the anatomy and courses of LGV on CT images allowed us to evaluate and develop a new classification and nomenclature system for the anatomical variations of LGV.

Classification of orbital morphology for decompression surgery in Graves' orbitopathy: two-dimensional versus three-dimensional orbital parameters.

PubMed

Borumandi, Farzad; Hammer, Beat; Noser, Hansrudi; Kamer, Lukas

2013-05-01

Three-dimensional (3D) CT reconstruction of the bony orbit for accurate measurement and classification of the complex orbital morphology may not be suitable for daily practice. We present an easily measurable two-dimensional (2D) reference dataset of the bony orbit for study of individual orbital morphology prior to decompression surgery in Graves' orbitopathy. CT images of 70 European adults (140 orbits) with unaffected orbits were included. On axial views, the following orbital dimensions were assessed: orbital length (OL), globe length (GL), GL/OL ratio and cone angle. Postprocessed CT data were required to measure the corresponding 3D orbital parameters. The 2D and 3D orbital parameters were correlated. The 2D orbital parameters were significantly correlated to the corresponding 3D parameters (significant at the 0.01 level). The average GL was 25 mm (SD±1.0), the average OL was 42 mm (SD±2.0) and the average GL/OL ratio was 0.6 (SD±0.03). The posterior cone angle was, on average, 50.2° (SD±4.1). Three orbital sizes were classified: short (OL≤40 mm), medium (OL>40 to <45 mm) and large (OL≥45 mm). We present easily measurable reference data for the orbit that can be used for preoperative study and classification of individual orbital morphology. A short and shallow orbit may require a different decompression technique than a large and deep orbit. Prospective clinical trials are needed to demonstrate how individual orbital morphology affects the outcome of decompression surgery.

Energy-efficiency based classification of the manufacturing workstation

NASA Astrophysics Data System (ADS)

Frumuşanu, G.; Afteni, C.; Badea, N.; Epureanu, A.

2017-08-01

EU Directive 92/75/EC established for the first time an energy consumption labelling scheme, further implemented by several other directives. As consequence, nowadays many products (e.g. home appliances, tyres, light bulbs, houses) have an EU Energy Label when offered for sale or rent. Several energy consumption models of manufacturing equipments have been also developed. This paper proposes an energy efficiency - based classification of the manufacturing workstation, aiming to characterize its energetic behaviour. The concept of energy efficiency of the manufacturing workstation is defined. On this base, a classification methodology has been developed. It refers to specific criteria and their evaluation modalities, together to the definition & delimitation of energy efficiency classes. The energy class position is defined after the amount of energy needed by the workstation in the middle point of its operating domain, while its extension is determined by the value of the first coefficient from the Taylor series that approximates the dependence between the energy consume and the chosen parameter of the working regime. The main domain of interest for this classification looks to be the optimization of the manufacturing activities planning and programming. A case-study regarding an actual lathe classification from energy efficiency point of view, based on two different approaches (analytical and numerical) is also included.

Classification of Microarray Data Using Kernel Fuzzy Inference System

PubMed Central

Kumar Rath, Santanu

2014-01-01

The DNA microarray classification technique has gained more popularity in both research and practice. In real data analysis, such as microarray data, the dataset contains a huge number of insignificant and irrelevant features that tend to lose useful information. Classes with high relevance and feature sets with high significance are generally referred for the selected features, which determine the samples classification into their respective classes. In this paper, kernel fuzzy inference system (K-FIS) algorithm is applied to classify the microarray data (leukemia) using t-test as a feature selection method. Kernel functions are used to map original data points into a higher-dimensional (possibly infinite-dimensional) feature space defined by a (usually nonlinear) function ϕ through a mathematical process called the kernel trick. This paper also presents a comparative study for classification using K-FIS along with support vector machine (SVM) for different set of features (genes). Performance parameters available in the literature such as precision, recall, specificity, F-measure, ROC curve, and accuracy are considered to analyze the efficiency of the classification model. From the proposed approach, it is apparent that K-FIS model obtains similar results when compared with SVM model. This is an indication that the proposed approach relies on kernel function. PMID:27433543

A Ternary Hybrid EEG-NIRS Brain-Computer Interface for the Classification of Brain Activation Patterns during Mental Arithmetic, Motor Imagery, and Idle State.

PubMed

Shin, Jaeyoung; Kwon, Jinuk; Im, Chang-Hwan

2018-01-01

The performance of a brain-computer interface (BCI) can be enhanced by simultaneously using two or more modalities to record brain activity, which is generally referred to as a hybrid BCI. To date, many BCI researchers have tried to implement a hybrid BCI system by combining electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS) to improve the overall accuracy of binary classification. However, since hybrid EEG-NIRS BCI, which will be denoted by hBCI in this paper, has not been applied to ternary classification problems, paradigms and classification strategies appropriate for ternary classification using hBCI are not well investigated. Here we propose the use of an hBCI for the classification of three brain activation patterns elicited by mental arithmetic, motor imagery, and idle state, with the aim to elevate the information transfer rate (ITR) of hBCI by increasing the number of classes while minimizing the loss of accuracy. EEG electrodes were placed over the prefrontal cortex and the central cortex, and NIRS optodes were placed only on the forehead. The ternary classification problem was decomposed into three binary classification problems using the "one-versus-one" (OVO) classification strategy to apply the filter-bank common spatial patterns filter to EEG data. A 10 × 10-fold cross validation was performed using shrinkage linear discriminant analysis (sLDA) to evaluate the average classification accuracies for EEG-BCI, NIRS-BCI, and hBCI when the meta-classification method was adopted to enhance classification accuracy. The ternary classification accuracies for EEG-BCI, NIRS-BCI, and hBCI were 76.1 ± 12.8, 64.1 ± 9.7, and 82.2 ± 10.2%, respectively. The classification accuracy of the proposed hBCI was thus significantly higher than those of the other BCIs ( p < 0.005). The average ITR for the proposed hBCI was calculated to be 4.70 ± 1.92 bits/minute, which was 34.3% higher than that reported for a previous binary hBCI study.

Importance of Adopting BMI Classifications Using Public Health Action Points to Delineate Obstetric Risk Factors Resulting in Worsening Obstetric Outcomes Among Asian Population.

PubMed

Ganeshan, Muniswaran; Bujang, Mohamad Adam; Soelar, Shahrul Aiman; Karalasingam, Shamala Devi; Suharjono, Harris; Jeganathan, Ravichandran

2018-06-01

The aim of this study is to compare obstetric outcomes between overweight and class 1 obesity among pregnant women in their first pregnancy based on WHO's BMI cut-offs and the potential public health action points identified by WHO expert consultations specific for high-risk population such as Asians. This is a retrospective cohort review of data obtained from the Malaysian National Obstetrics and Gynaecology Registry between the year 2010 and year 2012. All women in their first pregnancy with a booking BMI in their first trimester were included in this study. The association between BMI classifications as defined by the WHO cut-offs and the potential public health action points identified by WHO expert consultations towards adverse obstetric outcomes was compared. A total of 88,837 pregnant women were included in this study. We noted that the risk of adverse obstetric outcomes was significantly higher using the public health action points identified by WHO expert consultations even among the overweight group as the risk of stillbirths was (OR 1.2; 95% CI 1.0,1.4), shoulder dystocia (OR 1.9; 95% CI 1.2,2.9), foetal macrosomia (OR 1.8; 95% CI 1.6,2.0), caesarean section (OR 1.9; 95% CI 1.8,2.0) and assisted conception (OR 1.9; 95% CI 1.6,2.1). A specifically lower BMI references based on the potential public health action points for BMI classifications were a more sensitive predictor of adverse obstetric outcomes, and we recommend the use of these references in pregnancy especially among Asian population.

Enhancing the Resolution of Rumen Microbial Classification from Metatranscriptomic Data Using Kraken and Mothur

PubMed Central

Neves, Andre L. A.; Li, Fuyong; Ghoshal, Bibaswan; McAllister, Tim; Guan, Le L.

2017-01-01

The advent of next generation sequencing and bioinformatics tools have greatly advanced our knowledge about the phylogenetic diversity and ecological role of microbes inhabiting the mammalian gut. However, there is a lack of information on the evaluation of these computational tools in the context of the rumen microbiome as these programs have mostly been benchmarked on real or simulated datasets generated from human studies. In this study, we compared the outcomes of two methods, Kraken (mRNA based) and a pipeline developed in-house based on Mothur (16S rRNA based), to assess the taxonomic profiles (bacteria and archaea) of rumen microbial communities using total RNA sequencing of rumen fluid collected from 12 cattle with differing feed conversion ratios (FCR). Both approaches revealed a similar phyla distribution of the most abundant taxa, with Bacteroidetes, Firmicutes, and Proteobacteria accounting for approximately 80% of total bacterial abundance. For bacterial taxa, although 69 genera were commonly detected by both methods, an additional 159 genera were exclusively identified by Kraken. Kraken detected 423 species, while Mothur was not able to assign bacterial sequences to the species level. For archaea, both methods generated similar results only for the abundance of Methanomassiliicoccaceae (previously referred as RCC), which comprised more than 65% of the total archaeal families. Taxon R4-41B was exclusively identified by Mothur in the rumen of feed efficient bulls, whereas Kraken uniquely identified Methanococcaceae in inefficient bulls. Although Kraken enhanced the microbial classification at the species level, identification of bacteria or archaea in the rumen is limited due to a lack of reference genomes for the rumen microbiome. The findings from this study suggest that the development of the combined pipelines using Mothur and Kraken is needed for a more inclusive and representative classification of microbiomes. PMID:29270165

Development of an autofluorescence spectral database for the identification and classification of microbial extremophiles

NASA Astrophysics Data System (ADS)

Davis, Justin; Howard, Hillari; Hoover, Richard B.; Sabanayagam, Chandran R.

2010-09-01

Extremophiles are microorganisms that have adapted to severe conditions that were once considered devoid of life. The extreme settings in which these organisms flourish on Earth resemble many extraterrestrial environments. Identification and classification of extremophiles in situ (without the requirement for excessive handling and processing) can provide a basis for designing remotely operated instruments for extraterrestrial life exploration. An important consideration when designing such experiments is to prevent contamination of the environments. We are developing a reference spectral database of autofluorescence from microbial extremophiles using long-UV excitation (408 nm). Aromatic compounds are essential components of living systems, and biological molecules such as aromatic amino acids, nucleotides, porphyrins and vitamins can also exhibit fluorescence under long-UV excitation conditions. Autofluorescence spectra were obtained from a light microscope that additionally allowed observations of microbial geometry and motility. It was observed that all extremophiles studied displayed an autofluorescence peak at around 470 nm, followed by a long decay that was species specific. The autofluorescence database can potentially be used as a reference to identify and classify past or present microbial life in our solar system.

Development of an Autofluorescence Spectral Database for the Identification and Classification of Microbial Extremophiles

NASA Technical Reports Server (NTRS)

Sabanayagam, Chandran; Howard, Hillari; Hoover, Richard B.

2010-01-01

Extremophiles are microorganisms that have adapted to severe conditions that were once considered devoid of life. The extreme settings in which these organisms flourish on earth resemble many extraterrestrial environments. Identification and classification of extremophiles in situ (without the requirement for excessive handling and processing) can provide a basis for designing remotely operated instruments for extraterrestrial life exploration. An important consideration when designing such experiments is to prevent contamination of the environments. We are developing a reference spectral database of autofluorescence from microbial extremophiles using long-UV excitation (405 nm). Aromatic compounds are essential components of living systems, and biological molecules such as aromatic amino acids, nucleotides, porphyrins and vitamins can also exhibit fluorescence under long-UV excitation conditions. Autofluorescence spectra were obtained from a confocal microscope that additionally allowed observations of microbial geometry and motility. It was observed that all extremophiles studied displayed an autofluorescence peak at around 470 nm, followed by a long decay that was species specific. The autofluorescence database can potentially be used as a reference to identify and classify past or present microbial life in our solar system.

Effects of Admission and Treatment Strategies of DWI Courts on Offender Outcomes

PubMed Central

Sloan, Frank A.; Chepke, Lindsey M.; Davis, Dontrell V.; Acquah, Kofi; Zold-Kilbourne, Phyllis

2013-01-01

Purpose The purpose of this study is to classify DWI courts on the basis of the mix of difficult cases participating in the court (casemix severity) and the amount of involvement between the court and participant (service intensity). Using our classification typology, we assess how casemix severity and service intensity are associated with program outcomes. We expected that holding other factors constant, greater service intensity would improve program outcomes while a relatively severe casemix would result in worse program outcomes. Methods The study used data from 8 DWI courts, 7 from Michigan and 1 from North Carolina. Using a 2-way classification system based on court casemix severity and program intensity, we selected participants in 1 of the courts, and alternatively 2 courts as reference groups. Reference group courts had relatively severe casemixes and high service intensity. We used propensity score matching to match participants in the other courts to participants in the reference group court programs. Program outcome measures were the probabilities of participants’: failing to complete the court’s program; increasing educational attainment; participants improving employment from time of program enrollment; and re-arrest. Results For most outcomes, our main finding was that higher service intensity is associated with better outcomes for court participants, as anticipated, but a court’s casemix severity was unrelated to study outcomes. Conclusions Our results imply that devoting more resources to increasing duration of treatment is productive in terms of better outcomes, irrespective of the mix of participants in the court’s program PMID:23416679

Outcome measures in older persons with acquired joint contractures: a systematic review and content analysis using the ICF (International Classification of Functioning, Disability and Health) as a reference.

PubMed

Bartoszek, Gabriele; Fischer, Uli; Müller, Martin; Strobl, Ralf; Grill, Eva; Nadolny, Stephan; Meyer, Gabriele

2016-02-09

Joint contractures are a common health problem in older persons with significant impact on activities of daily living. We aimed to retrieve outcome measures applied in studies on older persons with joint contractures and to identify and categorise the concepts contained in these outcome measures using the ICF (International Classification of Functioning, Disability and Health) as a reference. Electronic searches of Medline, EMBASE, CINAHL, Pedro and the Cochrane Library were conducted (1/2002-8/2012). We included studies in the geriatric rehabilitation and nursing home settings with participants aged ≥ 65 years and with acquired joint contractures. Two independent reviewers extracted the outcome measures and transferred them to concepts using predefined conceptual frameworks. Concepts were subsequently linked to the ICF categories. From the 1057 abstracts retrieved, 60 studies met the inclusion criteria. We identified 52 single outcome measures and 24 standardised assessment instruments. A total of 1353 concepts were revealed from the outcome measures; 96.2% could be linked to 50 ICF categories in the 2nd level; 3.8% were not categorised. Fourteen of the 50 categories (28%) belonged to the component Body Functions, 4 (8%) to the component Body Structures, 26 (52%) to the component Activities and Participation, and 6 (12%) to the component Environmental Factors. The ICF is a valuable reference for identifying and quantifying the concepts of outcome measures on joint contractures in older people. The revealed ICF categories remain to be validated in populations with joint contractures in terms of clinical relevance and personal impact.

CD4 Enumeration Technologies: A Systematic Review of Test Performance for Determining Eligibility for Antiretroviral Therapy

PubMed Central

Peeling, Rosanna W.; Sollis, Kimberly A.; Glover, Sarah; Crowe, Suzanne M.; Landay, Alan L.; Cheng, Ben; Barnett, David; Denny, Thomas N.; Spira, Thomas J.; Stevens, Wendy S.; Crowley, Siobhan; Essajee, Shaffiq; Vitoria, Marco; Ford, Nathan

2015-01-01

Background Measurement of CD4+ T-lymphocytes (CD4) is a crucial parameter in the management of HIV patients, particularly in determining eligibility to initiate antiretroviral treatment (ART). A number of technologies exist for CD4 enumeration, with considerable variation in cost, complexity, and operational requirements. We conducted a systematic review of the performance of technologies for CD4 enumeration. Methods and Findings Studies were identified by searching electronic databases MEDLINE and EMBASE using a pre-defined search strategy. Data on test accuracy and precision included bias and limits of agreement with a reference standard, and misclassification probabilities around CD4 thresholds of 200 and 350 cells/μl over a clinically relevant range. The secondary outcome measure was test imprecision, expressed as % coefficient of variation. Thirty-two studies evaluating 15 CD4 technologies were included, of which less than half presented data on bias and misclassification compared to the same reference technology. At CD4 counts <350 cells/μl, bias ranged from -35.2 to +13.1 cells/μl while at counts >350 cells/μl, bias ranged from -70.7 to +47 cells/μl, compared to the BD FACSCount as a reference technology. Misclassification around the threshold of 350 cells/μl ranged from 1-29% for upward classification, resulting in under-treatment, and 7-68% for downward classification resulting in overtreatment. Less than half of these studies reported within laboratory precision or reproducibility of the CD4 values obtained. Conclusions A wide range of bias and percent misclassification around treatment thresholds were reported on the CD4 enumeration technologies included in this review, with few studies reporting assay precision. The lack of standardised methodology on test evaluation, including the use of different reference standards, is a barrier to assessing relative assay performance and could hinder the introduction of new point-of-care assays in countries where they are most needed. PMID:25790185

[Burning sensation in oral cavity--burning mouth syndrome in everyday medical practice].

PubMed

Gerlinger, Imre

2012-09-30

Burning mouth syndrome (BMS) refers to chronic orofacial pain, unaccompanied by mucosal lesions or other evident clinical signs. It is observed principally in middle-aged patients and postmenopausal women. BMS is characterized by an intense burning or stinging sensation, typically on the tongue or in other areas of the oral mucosa. It can be accompanied by other sensory disorders such as dry mouth or taste alterations. Probably of multifactorial origin, and often idiopathic, with a still unknown etiopathogenesis in which local, systemic and psychological factors are implicated. Currently there is no consensus on the diagnosis and classification of BMS. This study reviews the literature on this syndrome, with special reference to the etiological factors that may be involved and the clinical aspects they present. The diagnostic criteria that should be followed and the therapeutic management are discussed with reference to the most recent studies.

The International Classification of Functioning, Disability and Health and the version for children and youth as a tool in child habilitation/early childhood intervention--feasibility and usefulness as a common language and frame of reference for practice.

PubMed

Björck-Åkesson, Eva; Wilder, Jenny; Granlund, Mats; Pless, Mia; Simeonsson, Rune; Adolfsson, Margareta; Almqvist, Lena; Augustine, Lilly; Klang, Nina; Lillvist, Anne

2010-01-01

Early childhood intervention and habilitation services for children with disabilities operate on an interdisciplinary basis. It requires a common language between professionals, and a shared framework for intervention goals and intervention implementation. The International Classification of Functioning, Disability and Health (ICF) and the version for children and youth (ICF-CY) may serve as this common framework and language. This overview of studies implemented by our research group is based on three research questions: Do the ICF-CY conceptual model have a valid content and is it logically coherent when investigated empirically? Is the ICF-CY classification useful for documenting child characteristics in services? What difficulties and benefits are related to using ICF-CY model as a basis for intervention when it is implemented in services? A series of studies, undertaken by the CHILD researchers are analysed. The analysis is based on data sets from published studies or master theses. Results and conclusion show that the ICF-CY has a useful content and is logically coherent on model level. Professionals find it useful for documenting children's body functions and activities. Guidelines for separating activity and participation are needed. ICF-CY is a complex classification, implementing it in services is a long-term project.

Reference set for performance testing of pediatric vaccine safety signal detection methods and systems.

PubMed

Brauchli Pernus, Yolanda; Nan, Cassandra; Verstraeten, Thomas; Pedenko, Mariia; Osokogu, Osemeke U; Weibel, Daniel; Sturkenboom, Miriam; Bonhoeffer, Jan

2016-12-12

Safety signal detection in spontaneous reporting system databases and electronic healthcare records is key to detection of previously unknown adverse events following immunization. Various statistical methods for signal detection in these different datasources have been developed, however none are geared to the pediatric population and none specifically to vaccines. A reference set comprising pediatric vaccine-adverse event pairs is required for reliable performance testing of statistical methods within and across data sources. The study was conducted within the context of the Global Research in Paediatrics (GRiP) project, as part of the seventh framework programme (FP7) of the European Commission. Criteria for the selection of vaccines considered in the reference set were routine and global use in the pediatric population. Adverse events were primarily selected based on importance. Outcome based systematic literature searches were performed for all identified vaccine-adverse event pairs and complemented by expert committee reports, evidence based decision support systems (e.g. Micromedex), and summaries of product characteristics. Classification into positive (PC) and negative control (NC) pairs was performed by two independent reviewers according to a pre-defined algorithm and discussed for consensus in case of disagreement. We selected 13 vaccines and 14 adverse events to be included in the reference set. From a total of 182 vaccine-adverse event pairs, we classified 18 as PC, 113 as NC and 51 as unclassifiable. Most classifications (91) were based on literature review, 45 were based on expert committee reports, and for 46 vaccine-adverse event pairs, an underlying pathomechanism was not plausible classifying the association as NC. A reference set of vaccine-adverse event pairs was developed. We propose its use for comparing signal detection methods and systems in the pediatric population. Published by Elsevier Ltd.

A targeted change-detection procedure by combining change vector analysis and post-classification approach

NASA Astrophysics Data System (ADS)

Ye, Su; Chen, Dongmei; Yu, Jie

2016-04-01

In remote sensing, conventional supervised change-detection methods usually require effective training data for multiple change types. This paper introduces a more flexible and efficient procedure that seeks to identify only the changes that users are interested in, here after referred to as "targeted change detection". Based on a one-class classifier "Support Vector Domain Description (SVDD)", a novel algorithm named "Three-layer SVDD Fusion (TLSF)" is developed specially for targeted change detection. The proposed algorithm combines one-class classification generated from change vector maps, as well as before- and after-change images in order to get a more reliable detecting result. In addition, this paper introduces a detailed workflow for implementing this algorithm. This workflow has been applied to two case studies with different practical monitoring objectives: urban expansion and forest fire assessment. The experiment results of these two case studies show that the overall accuracy of our proposed algorithm is superior (Kappa statistics are 86.3% and 87.8% for Case 1 and 2, respectively), compared to applying SVDD to change vector analysis and post-classification comparison.

Geomorphology Classification of Shandong Province Based on Digital Elevation Model in the 1 Arc-second Format of Shuttle Radar Topography Mission Data

NASA Astrophysics Data System (ADS)

Fu, Jundong; Zhang, Guangcheng; Wang, Lei; Xia, Nuan

2018-01-01

Based on gigital elevation model in the 1 arc-second format of shuttle radar topography mission data, using the window analysis and mean change point analysis of geographic information system (GIS) technology, programmed with python modules this, automatically extracted and calculated geomorphic elements of Shandong province. The best access to quantitatively study area relief amplitude of statistical area. According to Chinese landscape classification standard, the landscape type in Shandong province was divided into 8 types: low altitude plain, medium altitude plain, low altitude platform, medium altitude platform, low altitude hills, medium altitude hills, low relief mountain, medium relief mountain and the percentages of Shandong province’s total area are as follows: 12.72%, 0.01%, 36.38%, 0.24%, 17.26%, 15.64%, 11.1%, 6.65%. The results of landforms are basically the same as the overall terrain of Shandong Province, Shandong province’s total area, and the study can quantitatively and scientifically provide reference for the classification of landforms in Shandong province.

[Forensic medical characteristic of the damages to the skin and clothes by plastic knives].

PubMed

Finkel'shtein, V T

2016-01-01

The present study was designed to characterize the group and individual properties of plastic knives with special reference to the classification of the damages inflicted to the human skin and textile fabric by these weapons including multiblade ones. It was shown in experiment that repeated impacts through a barrier (textile fabric) lead to a partial destruction of the blade.

Extending a field-based Sonoran desert vegetation classification to a regional scale using optical and microwave satellite imagery

NASA Astrophysics Data System (ADS)

Shupe, Scott Marshall

2000-10-01

Vegetation mapping in and regions facilitates ecological studies, land management, and provides a record to which future land changes can be compared. Accurate and representative mapping of desert vegetation requires a sound field sampling program and a methodology to transform the data collected into a representative classification system. Time and cost constraints require that a remote sensing approach be used if such a classification system is to be applied on a regional scale. However, desert vegetation may be sparse and thus difficult to sense at typical satellite resolutions, especially given the problem of soil reflectance. This study was designed to address these concerns by conducting vegetation mapping research using field and satellite data from the US Army Yuma Proving Ground (USYPG) in Southwest Arizona. Line and belt transect data from the Army's Land Condition Trend Analysis (LCTA) Program were transformed into relative cover and relative density classification schemes using cluster analysis. Ordination analysis of the same data produced two and three-dimensional graphs on which the homogeneity of each vegetation class could be examined. It was found that the use of correspondence analysis (CA), detrended correspondence analysis (DCA), and non-metric multidimensional scaling (NMS) ordination methods was superior to the use of any single ordination method for helping to clarify between-class and within-class relationships in vegetation composition. Analysis of these between-class and within-class relationships were of key importance in examining how well relative cover and relative density schemes characterize the USYPG vegetation. Using these two classification schemes as reference data, maximum likelihood and artificial neural net classifications were then performed on a coregistered dataset consisting of a summer Landsat Thematic Mapper (TM) image, one spring and one summer ERS-1 microwave image, and elevation, slope, and aspect layers. Classifications using a combination of ERS-1 imagery and elevation, slope, and aspect data were superior to classifications carried out using Landsat TM data alone. In all classification iterations it was consistently found that the highest classification accuracy was obtained by using a combination of Landsat TM, ERS-1, and elevation, slope, and aspect data. Maximum likelihood classification accuracy was found to be higher than artificial neural net classification in all cases.

Classification and overview of research in real-time imaging

NASA Astrophysics Data System (ADS)

Sinha, Purnendu; Gorinsky, Sergey V.; Laplante, Phillip A.; Stoyenko, Alexander D.; Marlowe, Thomas J.

1996-10-01

Real-time imaging has application in areas such as multimedia, virtual reality, medical imaging, and remote sensing and control. Recently, the imaging community has witnessed a tremendous growth in research and new ideas in these areas. To lend structure to this growth, we outline a classification scheme and provide an overview of current research in real-time imaging. For convenience, we have categorized references by research area and application.

Computer Center Reference Manual. Volume 1

DTIC Science & Technology

1990-09-30

Unlimited o- 0 0 91o1 UNCLASSI FI ED SECURITY CLASSIFICATION OF THIS PAGE REPORT DOCUMENTATION PAGE la . REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE...with connection to INTERNET ) (host tables allow transfer to some other networks) OASYS - the DTRC Office Automation System The following can be reached...and buffers, two windows, and some word processing commands. Advanced editing commands are entered through the use of a command line. EVE las its own

Spirituality and the International Classification of Functioning, Disability and Health: content comparison of questionnaires measuring mindfulness based on the International Classification of Functioning.

PubMed

Offenbächer, Martin; Sauer, Sebastian; Hieblinger, Robin; Hufford, David J; Walach, Harald; Kohls, Niko

2011-01-01

To identify and compare the concepts contained in questionnaires measuring mindfulness using the International Classification of Functioning (ICF) as external reference. Questionnaires which are published in peer-reviewed journals and listed in Pubmed or PsycInfo were included. The questionnaires were analysed and, using a content-analytical approach, the respective items were categorised and linked to the ICF. Ten questionnaires were included. Ninety-four per cent (N = 341) of the concepts could be linked to 37 different ICF categories. One hundred and seventy-one (50.1%) concepts were linked to ICF categories of the component Body Function, 74 (21.7%) to categories of the component Activity and Participation and none to categories of the component Environmental Factors. In total, 28.2% of the linked concepts belonged to Personal factors, which are not yet classified in the ICF. The questionnaires exhibited considerable differences regarding content density (i.e. the average number of concepts per item) and content diversity (i.e. the number of ICF categories per concept). The ICF provides an useful external reference to identify and compare the concepts contained in mindfulness questionnaires. Also, mindfulness questionnaire concepts suggest potentially useful factors for classification within the ICF.

Introduction to Grassland Management. Instructor Guide, Student Reference [and] Crop and Grassland Plant Identification Manual.

ERIC Educational Resources Information Center

Suits, Susie

This packet contains an Instructor guide and student reference for a course in introduction to grassland management, as well as a crop and grassland plant identification manual. The three-unit curriculum contains the following 11 lessons: (unit I, grasslands and grassland plants): (1) an introduction to grasslands; (2) plant classification; (3)…

Plant Science. Instructor Guide [and] Student Reference. Volume 24, Numbers 3 and 4.

ERIC Educational Resources Information Center

Humphrey, John Kevin

This document consists of two separately published guides for a course on plant science: an instructor's guide and a student's reference manual. Each part consists of eight lessons and cover the following topics: (1) importance of plants; (2) classification of plants; (3) plant growth factors; (4) weeds, diseases, insects; (5) germination; (6)…

A Guide to the Principal Marine Fouling Organisms, with Particular Reference to Cockburn Sound, W.A.,

DTIC Science & Technology

1982-07-01

4. HYDROIDS (Phylum Cnidaria , Class Hydrozoa) 7 4.1 General 7 4.2 Common Species 7 4.3 Other Species 8 4.4 References 8 5. TUBEWORMS (Phylum Annelida...Classification of the Calcareous Sponges, British Museum (National History), London, England. 693 pp. 4. HYDROIDS (Phylum Cnidaria , Class Hydrozoa) 4.1

Kmeans-ICA based automatic method for ocular artifacts removal in a motorimagery classification.

PubMed

Bou Assi, Elie; Rihana, Sandy; Sawan, Mohamad

2014-01-01

Electroencephalogram (EEG) recordings aroused as inputs of a motor imagery based BCI system. Eye blinks contaminate the spectral frequency of the EEG signals. Independent Component Analysis (ICA) has been already proved for removing these artifacts whose frequency band overlap with the EEG of interest. However, already ICA developed methods, use a reference lead such as the ElectroOculoGram (EOG) to identify the ocular artifact components. In this study, artifactual components were identified using an adaptive thresholding by means of Kmeans clustering. The denoised EEG signals have been fed into a feature extraction algorithm extracting the band power, the coherence and the phase locking value and inserted into a linear discriminant analysis classifier for a motor imagery classification.

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

PubMed

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

2011-11-30

Non-invasive tests have been constructed and evaluated mainly for binary diagnoses such as significant fibrosis. Recently, detailed fibrosis classifications for several non-invasive tests have been developed, but their accuracy has not been thoroughly evaluated in comparison to liver biopsy, especially in clinical practice and for Fibroscan. Therefore, the main aim of the present study was to evaluate the accuracy of detailed fibrosis classifications available for non-invasive tests and liver biopsy. The secondary aim was to validate these accuracies in independent populations. Four HCV populations provided 2,068 patients with liver biopsy, four different pathologist skill-levels and non-invasive tests. Results were expressed as percentages of correctly classified patients. In population #1 including 205 patients and comparing liver biopsy (reference: consensus reading by two experts) and blood tests, Metavir fibrosis (FM) stage accuracy was 64.4% in local pathologists vs. 82.2% (p < 10-3) in single expert pathologist. Significant discrepancy (≥ 2FM vs reference histological result) rates were: Fibrotest: 17.2%, FibroMeter2G: 5.6%, local pathologists: 4.9%, FibroMeter3G: 0.5%, expert pathologist: 0% (p < 10-3). In population #2 including 1,056 patients and comparing blood tests, the discrepancy scores, taking into account the error magnitude, of detailed fibrosis classification were significantly different between FibroMeter2G (0.30 ± 0.55) and FibroMeter3G (0.14 ± 0.37, p < 10-3) or Fibrotest (0.84 ± 0.80, p < 10-3). In population #3 (and #4) including 458 (359) patients and comparing blood tests and Fibroscan, accuracies of detailed fibrosis classification were, respectively: Fibrotest: 42.5% (33.5%), Fibroscan: 64.9% (50.7%), FibroMeter2G: 68.7% (68.2%), FibroMeter3G: 77.1% (83.4%), p < 10-3 (p < 10-3). Significant discrepancy (≥ 2 FM) rates were, respectively: Fibrotest: 21.3% (22.2%), Fibroscan: 12.9% (12.3%), FibroMeter2G: 5.7% (6.0%), FibroMeter3G: 0.9% (0.9%), p < 10-3 (p < 10-3). The accuracy in detailed fibrosis classification of the best-performing blood test outperforms liver biopsy read by a local pathologist, i.e., in clinical practice; however, the classification precision is apparently lesser. This detailed classification accuracy is much lower than that of significant fibrosis with Fibroscan and even Fibrotest but higher with FibroMeter3G. FibroMeter classification accuracy was significantly higher than those of other non-invasive tests. Finally, for hepatitis C evaluation in clinical practice, fibrosis degree can be evaluated using an accurate blood test.

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

PubMed Central

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 < 10-3) in single expert pathologist. Significant discrepancy (≥ 2FM vs reference histological result) rates were: Fibrotest: 17.2%, FibroMeter2G: 5.6%, local pathologists: 4.9%, FibroMeter3G: 0.5%, expert pathologist: 0% (p < 10-3). In population #2 including 1,056 patients and comparing blood tests, the discrepancy scores, taking into account the error magnitude, of detailed fibrosis classification were significantly different between FibroMeter2G (0.30 ± 0.55) and FibroMeter3G (0.14 ± 0.37, p < 10-3) or Fibrotest (0.84 ± 0.80, p < 10-3). In population #3 (and #4) including 458 (359) patients and comparing blood tests and Fibroscan, accuracies of detailed fibrosis classification were, respectively: Fibrotest: 42.5% (33.5%), Fibroscan: 64.9% (50.7%), FibroMeter2G: 68.7% (68.2%), FibroMeter3G: 77.1% (83.4%), p < 10-3 (p < 10-3). Significant discrepancy (≥ 2 FM) rates were, respectively: Fibrotest: 21.3% (22.2%), Fibroscan: 12.9% (12.3%), FibroMeter2G: 5.7% (6.0%), FibroMeter3G: 0.9% (0.9%), p < 10-3 (p < 10-3). Conclusions The accuracy in detailed fibrosis classification of the best-performing blood test outperforms liver biopsy read by a local pathologist, i.e., in clinical practice; however, the classification precision is apparently lesser. This detailed classification accuracy is much lower than that of significant fibrosis with Fibroscan and even Fibrotest but higher with FibroMeter3G. FibroMeter classification accuracy was significantly higher than those of other non-invasive tests. Finally, for hepatitis C evaluation in clinical practice, fibrosis degree can be evaluated using an accurate blood test. PMID:22129438

Exploring different strategies for imbalanced ADME data problem: case study on Caco-2 permeability modeling.

PubMed

Pham-The, Hai; Casañola-Martin, Gerardo; Garrigues, Teresa; Bermejo, Marival; González-Álvarez, Isabel; Nguyen-Hai, Nam; Cabrera-Pérez, Miguel Ángel; Le-Thi-Thu, Huong

2016-02-01

In many absorption, distribution, metabolism, and excretion (ADME) modeling problems, imbalanced data could negatively affect classification performance of machine learning algorithms. Solutions for handling imbalanced dataset have been proposed, but their application for ADME modeling tasks is underexplored. In this paper, various strategies including cost-sensitive learning and resampling methods were studied to tackle the moderate imbalance problem of a large Caco-2 cell permeability database. Simple physicochemical molecular descriptors were utilized for data modeling. Support vector machine classifiers were constructed and compared using multiple comparison tests. Results showed that the models developed on the basis of resampling strategies displayed better performance than the cost-sensitive classification models, especially in the case of oversampling data where misclassification rates for minority class have values of 0.11 and 0.14 for training and test set, respectively. A consensus model with enhanced applicability domain was subsequently constructed and showed improved performance. This model was used to predict a set of randomly selected high-permeability reference drugs according to the biopharmaceutics classification system. Overall, this study provides a comparison of numerous rebalancing strategies and displays the effectiveness of oversampling methods to deal with imbalanced permeability data problems.

Classification deficits in Alzheimer's disease with special reference to living and nonliving things.

PubMed

Montanes, P; Goldblum, M C; Boller, F

1996-08-01

The present study was conducted to assess the hypothesis that visual similarity between exemplars within a semantic category may affect differentially the recognition process of living and nonliving things, according to task demands, in patients with semantic memory disorders. Thirty-nine Alzheimer's patients and 39 normal elderly subjects were presented with a task in which they had to classify pictures and words, depicting either living or nonliving things, at two levels of classification: subordinate (e.g., mammals versus birds or tools versus vehicles) and attribute (e.g., wild versus domestic animals or fast versus slow vehicles). Contrary to previous results (Montañes, Goldblum, & Boller, 1995) in a naming task, but as expected, living things were better classified than nonliving ones by both controls and patients. As expected, classifications at the subordinate level also gave rise to better performance than classifications at the attribute level. Although (and somewhat unexpectedly) no advantage of picture over word classification emerged, some effects consistent with the hypothesis that visual similarity affects picture classification emerged, in particular within a subgroup of patients with predominant verbal deficits and the most severe semantic memory disorders. This subgroup obtained a better score on classification of pictures than of words depicting living items (that share many visual features) when classification is at the subordinate level (for which visual similarity is a reliable clue to classification), but met with major difficulties when classifying those pictures at the attribute level (for which shared visual features are not reliable clues to classification). These results emphasize the fact that some "normal" effects specific to items in living and nonliving categories have to be considered among the factors causing selective category-specific deficits in patients, as well as their relevance in achieving tasks which require either differentiation between competing exemplars in the same semantic category (naming) or detection of resemblance between those exemplars (categorization).

Identifying predictive features in drug response using machine learning: opportunities and challenges.

PubMed

Vidyasagar, Mathukumalli

2015-01-01

This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

Application of Bayes' to the prediction of referral decisions made by specialist optometrists in relation to chronic open angle glaucoma.

PubMed

Gurney, J C; Ansari, E; Harle, D; O'Kane, N; Sagar, R V; Dunne, M C M

2018-02-09

To determine the accuracy of a Bayesian learning scheme (Bayes') applied to the prediction of clinical decisions made by specialist optometrists in relation to the referral refinement of chronic open angle glaucoma. This cross-sectional observational study involved collection of data from the worst affected or right eyes of a consecutive sample of cases (n = 1,006) referred into the West Kent Clinical Commissioning Group Community Ophthalmology Team (COT) by high street optometrists. Multilevel classification of each case was based on race, sex, age, family history of chronic open angle glaucoma, reason for referral, Goldmann Applanation Tonometry (intraocular pressure and interocular asymmetry), optic nerve head assessment (vertical size, cup disc ratio and interocular asymmetry), central corneal thickness and visual field analysis (Hodapp-Parrish-Anderson classification). Randomised stratified tenfold cross-validation was applied to determine the accuracy of Bayes' by comparing its output to the clinical decisions of three COT specialist optometrists; namely, the decision to discharge, follow-up or refer each case. Outcomes of cross-validation, expressed as means and standard deviations, showed that the accuracy of Bayes' was high (95%, 2.0%) but that it falsely discharged (3.4%, 1.6%) or referred (3.1%, 1.5%) some cases. The results indicate that Bayes' has the potential to augment the decisions of specialist optometrists.

Estimation of the Age and Amount of Brown Rice Plant Hoppers Based on Bionic Electronic Nose Use

PubMed Central

Xu, Sai; Zhou, Zhiyan; Lu, Huazhong; Luo, Xiwen; Lan, Yubin; Zhang, Yang; Li, Yanfang

2014-01-01

The brown rice plant hopper (BRPH), Nilaparvata lugens (Stal), is one of the most important insect pests affecting rice and causes serious damage to the yield and quality of rice plants in Asia. This study used bionic electronic nose technology to sample BRPH volatiles, which vary in age and amount. Principal component analysis (PCA), linear discrimination analysis (LDA), probabilistic neural network (PNN), BP neural network (BPNN) and loading analysis (Loadings) techniques were used to analyze the sampling data. The results indicate that the PCA and LDA classification ability is poor, but the LDA classification displays superior performance relative to PCA. When a PNN was used to evaluate the BRPH age and amount, the classification rates of the training set were 100% and 96.67%, respectively, and the classification rates of the test set were 90.67% and 64.67%, respectively. When BPNN was used for the evaluation of the BRPH age and amount, the classification accuracies of the training set were 100% and 48.93%, respectively, and the classification accuracies of the test set were 96.67% and 47.33%, respectively. Loadings for BRPH volatiles indicate that the main elements of BRPHs' volatiles are sulfur-containing organics, aromatics, sulfur- and chlorine-containing organics and nitrogen oxides, which provide a reference for sensors chosen when exploited in specialized BRPH identification devices. This research proves the feasibility and broad application prospects of bionic electronic noses for BRPH recognition. PMID:25268913

Mixed-phenotype acute leukemia: state-of-the-art of the diagnosis, classification and treatment.

PubMed

Cernan, Martin; Szotkowski, Tomas; Pikalova, Zuzana

2017-09-01

Mixed-phenotype acute leukemia (MPAL) is a heterogeneous group of hematopoietic malignancies in which blasts show markers of multiple developmental lineages and cannot be clearly classified as acute myeloid or lymphoblastic leukemias. Historically, various names and classifications were used for this rare entity accounting for 2-5% of all acute leukemias depending on the diagnostic criterias used. The currently valid classification of myeloid neoplasms and acute leukemia published by the World Health Organization (WHO) in 2016 refers to this group of diseases as MPAL. Because adverse cytogenetic abnormalities are frequently present, MPAL is generally considered a disease with a poor prognosis. Knowledge of its treatment is limited to retrospective analyses of small patient cohorts. So far, no treatment recommendations verified by prospective studies have been published. The reported data suggest that induction therapy for acute lymphoblastic leukemia followed by allogeneic hematopoietic cell transplantation is more effective than induction therapy for acute myeloid leukemia or consolidation chemotherapy. The establishment of cooperative groups and international registries based on the recent WHO criterias are required to ensure further progress in understanding and treatment of MPAL. This review summarizes current knowledge on the diagnosis, classification, prognosis and treatment of MPAL patients.

An Evaluation of Feature Learning Methods for High Resolution Image Classification

NASA Astrophysics Data System (ADS)

Tokarczyk, P.; Montoya, J.; Schindler, K.

2012-07-01

Automatic image classification is one of the fundamental problems of remote sensing research. The classification problem is even more challenging in high-resolution images of urban areas, where the objects are small and heterogeneous. Two questions arise, namely which features to extract from the raw sensor data to capture the local radiometry and image structure at each pixel or segment, and which classification method to apply to the feature vectors. While classifiers are nowadays well understood, selecting the right features remains a largely empirical process. Here we concentrate on the features. Several methods are evaluated which allow one to learn suitable features from unlabelled image data by analysing the image statistics. In a comparative study, we evaluate unsupervised feature learning with different linear and non-linear learning methods, including principal component analysis (PCA) and deep belief networks (DBN). We also compare these automatically learned features with popular choices of ad-hoc features including raw intensity values, standard combinations like the NDVI, a few PCA channels, and texture filters. The comparison is done in a unified framework using the same images, the target classes, reference data and a Random Forest classifier.

Comparison and critical appraisal of dengue clinical guidelines and their use in Asia and Latin America.

PubMed

Santamaria, R; Martinez, E; Kratochwill, S; Soria, C; Tan, L H; Nuñez, A; Dimaano, E; Villegas, E; Bendezú, H; Kroeger, A; Castelobranco, I; Siqueira, J B; Jaenisch, T; Horstick, O; Lum, L C S

2009-12-01

The World Health Organization (WHO) dengue classification scheme for dengue fever (DF) and dengue haemorrhagic fever (DHF)/dengue shock syndrome (DSS) has been adopted as the standard for diagnosis, clinical management and reporting. In recent years, difficulties in applying the WHO case classification have been reported in several countries. A multicenter study was carried out in Asia and Latin America to analyze the variation and utility of dengue clinical guidelines (DCGs) taking as reference the WHO/PAHO guidelines (1994) and the WHO/SEARO guidelines (1998). A document analysis of 13 dengue guidelines was followed by a questionnaire and Focus Group discussions (FGDs) with 858 health care providers in seven countries. Differences in DCGs of the 13 countries were identified including the concept of warning signs, case classification, use of treatment algorithms and grading into levels of severity. The questionnaires and FGDs revealed (1) inaccessibility of DCGs, (2) lack of training, (3) insufficient number of staff to correctly apply the DCGs at the frontline and (4) the unavailability of diagnostic tests. The differences of the DCGs and the inconsistency in their application suggest a need to re-evaluate and standardise DCGs. This applies especially to case classification and case management.

HPMCD: the database of human microbial communities from metagenomic datasets and microbial reference genomes.

PubMed

Forster, Samuel C; Browne, Hilary P; Kumar, Nitin; Hunt, Martin; Denise, Hubert; Mitchell, Alex; Finn, Robert D; Lawley, Trevor D

2016-01-04

The Human Pan-Microbe Communities (HPMC) database (http://www.hpmcd.org/) provides a manually curated, searchable, metagenomic resource to facilitate investigation of human gastrointestinal microbiota. Over the past decade, the application of metagenome sequencing to elucidate the microbial composition and functional capacity present in the human microbiome has revolutionized many concepts in our basic biology. When sufficient high quality reference genomes are available, whole genome metagenomic sequencing can provide direct biological insights and high-resolution classification. The HPMC database provides species level, standardized phylogenetic classification of over 1800 human gastrointestinal metagenomic samples. This is achieved by combining a manually curated list of bacterial genomes from human faecal samples with over 21000 additional reference genomes representing bacteria, viruses, archaea and fungi with manually curated species classification and enhanced sample metadata annotation. A user-friendly, web-based interface provides the ability to search for (i) microbial groups associated with health or disease state, (ii) health or disease states and community structure associated with a microbial group, (iii) the enrichment of a microbial gene or sequence and (iv) enrichment of a functional annotation. The HPMC database enables detailed analysis of human microbial communities and supports research from basic microbiology and immunology to therapeutic development in human health and disease. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Invited commentary: the incremental value of customization in defining abnormal fetal growth status.

PubMed

Zhang, Jun; Sun, Kun

2013-10-15

Reference tools based on birth weight percentiles at a given gestational week have long been used to define fetuses or infants that are small or large for their gestational ages. However, important deficiencies of the birth weight reference are being increasingly recognized. Overwhelming evidence indicates that an ultrasonography-based fetal weight reference should be used to classify fetal and newborn sizes during pregnancy and at birth, respectively. Questions have been raised as to whether further adjustments for race/ethnicity, parity, sex, and maternal height and weight are helpful to improve the accuracy of the classification. In this issue of the Journal, Carberry et al. (Am J Epidemiol. 2013;178(8):1301-1308) show that adjustment for race/ethnicity is useful, but that additional fine tuning for other factors (i.e., full customization) in the classification may not further improve the ability to predict infant morbidity, mortality, and other fetal growth indicators. Thus, the theoretical advantage of full customization may have limited incremental value for pediatric outcomes, particularly in term births. Literature on the prediction of short-term maternal outcomes and very long-term outcomes (adult diseases) is too scarce to draw any conclusions. Given that each additional variable being incorporated in the classification scheme increases complexity and costs in practice, the clinical utility of full customization in obstetric practice requires further testing.

Issues in the Classification of Disease Instances with Ontologies

PubMed Central

Burgun, Anita; Bodenreider, Olivier; Jacquelinet, Christian

2006-01-01

Ontologies define classes of entities and their interrelations. They are used to organize data according to a theory of the domain. Towards that end, ontologies provide class definitions (i.e., the necessary and sufficient conditions for defining class membership). In medical ontologies, it is often difficult to establish such definitions for diseases. We use three examples (anemia, leukemia and schizophrenia) to illustrate the limitations of ontologies as classification resources. We show that eligibility criteria are often more useful than the Aristotelian definitions traditionally used in ontologies. Examples of eligibility criteria for diseases include complex predicates such as ‘ x is an instance of the class C when at least n criteria among m are verified’ and ‘symptoms must last at least one month if not treated, but less than one month, if effectively treated’. References to normality and abnormality are often found in disease definitions, but the operational definition of these references (i.e., the statistical and contextual information necessary to define them) is rarely provided. We conclude that knowledge bases that include probabilistic and statistical knowledge as well as rule-based criteria are more useful than Aristotelian definitions for representing the predicates defined by necessary and sufficient conditions. Rich knowledge bases are needed to clarify the relations between individuals and classes in various studies and applications. However, as ontologies represent relations among classes, they can play a supporting role in disease classification services built primarily on knowledge bases. PMID:16160339

Comparison of Naive Bayes and Decision Tree on Feature Selection Using Genetic Algorithm for Classification Problem

NASA Astrophysics Data System (ADS)

Rahmadani, S.; Dongoran, A.; Zarlis, M.; Zakarias

2018-03-01

This paper discusses the problem of feature selection using genetic algorithms on a dataset for classification problems. The classification model used is the decicion tree (DT), and Naive Bayes. In this paper we will discuss how the Naive Bayes and Decision Tree models to overcome the classification problem in the dataset, where the dataset feature is selectively selected using GA. Then both models compared their performance, whether there is an increase in accuracy or not. From the results obtained shows an increase in accuracy if the feature selection using GA. The proposed model is referred to as GADT (GA-Decision Tree) and GANB (GA-Naive Bayes). The data sets tested in this paper are taken from the UCI Machine Learning repository.

Application of Piedmont Landscape Ecosystem Classification as a Reference For A Vegetation and Herpetofaunal Survey on Lake Thurmond, SC

Treesearch

Victor B. Shelburne; Lawrence R. Gering; J. Drew Lanham; Gregory P. Smith; Thomas M. Floyd; Eran S. Kilpatrick

2002-01-01

Application of a Piedmont landscape ecosystem classification methodology was used as a basis for a survey of vegetation and herpetofaunal communities on a 343 hectare (846 acre) tract on Lake Thurmond near Plum Branch, SC. The site is located in the Carolina Slate Belt of the Midlands Plateau Region of the Piedmont province. A total of 160 plots were established and 30...

VizieR Online Data Catalog: Diffuse ionized gas database DIGEDA (Flores-Fajardo+ 2009)

NASA Astrophysics Data System (ADS)

Flores-Fajardo, N.; Morisset, C.; Binette, L.

2009-09-01

DIGEDA is a comprehensive database comprising 1061 DIG and HII region spectroscopic observations of 29 different galaxies (25 spiral galaxies and 4 irregulars) from 18 bibliographic references. This survey contains galaxies with significant spread in star formation rates, Halpha luminosities, distances, disk inclinations, slit positions and slit orientations. The 1061 observations obtained from these references were extracted by digitalization of published figures or tables. The data were subsequently normalized and incorporated in DIGEDA. This resulted in a table of 26 columns containing 1061 data lines or records (DIGEDA.dat file). We have not performed any reddening by dust correction or for the presence of underlying absorption lines, although we did use the reddening corrected ratios when made available by the authors. Missing entries are represented by (-1) in the corresponding data field. In DIGEDA the observed areas are classificated in three possible emission region types: HII region, transition zones or DIG. When this classification was not reported (no matter the criterion) for the authors, we introduce our own classification taking into account the value of |z| as described in the paper. (4 data files).

A Methodology for Benchmarking Relational Database Machines,

DTIC Science & Technology

1984-01-01

user benchmarks is to compare the multiple users to the best-case performance The data for each query classification coll and the performance...called a benchmark. The term benchmark originates from the markers used by sur - veyors in establishing common reference points for their measure...formatted databases. In order to further simplify the problem, we restrict our study to those DBMs which support the relational model. A sur - vey

24 CFR 3285.4 - Incorporation by reference (IBR).

Code of Federal Regulations, 2010 CFR

2010-04-01

... purchase from the Structural Engineering Institute/American Society of Civil Engineers (SEI/ASCE), 1801... for Engineering Purposes (Unified Soil Classification System), 2000, IBR approved for the table at...

Object-oriented feature extraction approach for mapping supraglacial debris in Schirmacher Oasis using very high-resolution satellite data

NASA Astrophysics Data System (ADS)

Jawak, Shridhar D.; Jadhav, Ajay; Luis, Alvarinho J.

2016-05-01

Supraglacial debris was mapped in the Schirmacher Oasis, east Antarctica, by using WorldView-2 (WV-2) high resolution optical remote sensing data consisting of 8-band calibrated Gram Schmidt (GS)-sharpened and atmospherically corrected WV-2 imagery. This study is a preliminary attempt to develop an object-oriented rule set to extract supraglacial debris for Antarctic region using 8-spectral band imagery. Supraglacial debris was manually digitized from the satellite imagery to generate the ground reference data. Several trials were performed using few existing traditional pixel-based classification techniques and color-texture based object-oriented classification methods to extract supraglacial debris over a small domain of the study area. Multi-level segmentation and attributes such as scale, shape, size, compactness along with spectral information from the data were used for developing the rule set. The quantitative analysis of error was carried out against the manually digitized reference data to test the practicability of our approach over the traditional pixel-based methods. Our results indicate that OBIA-based approach (overall accuracy: 93%) for extracting supraglacial debris performed better than all the traditional pixel-based methods (overall accuracy: 80-85%). The present attempt provides a comprehensive improved method for semiautomatic feature extraction in supraglacial environment and a new direction in the cryospheric research.

36 CFR § 1238.14 - What are the microfilming requirements for permanent and unscheduled records?

Code of Federal Regulations, 2013 CFR

2013-07-01

... processing procedures in ANSI/AIIM MS1 and ANSI/AIIM MS23 (both incorporated by reference, see § 1238.5). (d... reference, see § 1238.5). (2) Background density of images. Agencies must use the background ISO standard... densities for images of documents are as follows: Classification Description of document Background density...

Evaluation of the Retrieval of Metallurgical Document References using the Universal Decimal Classification in a Computer-Based System.

ERIC Educational Resources Information Center

Freeman, Robert R.

A set of twenty five questions was processed against a computer-stored file of 9159 document references in the field of ferrous metallurgy, representing the 1965 coverage of the Iron and Steel Institute (London) information service. A basis for evaluation of system performance characteristics and analysis of system failures was provided by using…

Nondestructive evaluation technique guide

NASA Technical Reports Server (NTRS)

Vary, A.

1973-01-01

A total of 70 individual nondestructive evaluation (NDE) techniques are described. Information is presented that permits ease of comparison of the merits and limitations of each technique with respect to various NDE problems. An NDE technique classification system is presented. It is based on the system that was adopted by the National Materials Advisory Board (NMAB). The classification system presented follows the NMAB system closely with the exception of additional categories that have been added to cover more advanced techniques presently in use. The rationale of the technique is explained. The format provides for a concise description of each technique, the physical principles involved, objectives of interrogation, example applications, limitations of each technique, a schematic illustration, and key reference material. Cross-index tabulations are also provided so that particular NDE problems can be referred to appropriate techniques.

Origins and challenges of viral dark matter.

PubMed

Krishnamurthy, Siddharth R; Wang, David

2017-07-15

The accurate classification of viral dark matter - metagenomic sequences that originate from viruses but do not align to any reference virus sequences - is one of the major obstacles in comprehensively defining the virome. Depending on the sample, viral dark matter can make up from anywhere between 40 and 90% of sequences. This review focuses on the specific nature of dark matter as it relates to viral sequences. We identify three factors that contribute to the existence of viral dark matter: the divergence and length of virus sequences, the limitations of alignment based classification, and limited representation of viruses in reference sequence databases. We then discuss current methods that have been developed to at least partially circumvent these limitations and thereby reduce the extent of viral dark matter. Copyright © 2017 Elsevier B.V. All rights reserved.

Defining traumatic brain injury in children and youth using international classification of diseases version 10 codes: a systematic review protocol.

PubMed

Chan, Vincy; Thurairajah, Pravheen; Colantonio, Angela

2013-11-13

Although healthcare administrative data are commonly used for traumatic brain injury research, there is currently no consensus or consistency on using the International Classification of Diseases version 10 codes to define traumatic brain injury among children and youth. This protocol is for a systematic review of the literature to explore the range of International Classification of Diseases version 10 codes that are used to define traumatic brain injury in this population. The databases MEDLINE, MEDLINE In-Process, Embase, PsychINFO, CINAHL, SPORTDiscus, and Cochrane Database of Systematic Reviews will be systematically searched. Grey literature will be searched using Grey Matters and Google. Reference lists of included articles will also be searched. Articles will be screened using predefined inclusion and exclusion criteria and all full-text articles that meet the predefined inclusion criteria will be included for analysis. The study selection process and reasons for exclusion at the full-text level will be presented using a PRISMA study flow diagram. Information on the data source of included studies, year and location of study, age of study population, range of incidence, and study purpose will be abstracted into a separate table and synthesized for analysis. All International Classification of Diseases version 10 codes will be listed in tables and the codes that are used to define concussion, acquired traumatic brain injury, head injury, or head trauma will be identified. The identification of the optimal International Classification of Diseases version 10 codes to define this population in administrative data is crucial, as it has implications for policy, resource allocation, planning of healthcare services, and prevention strategies. It also allows for comparisons across countries and studies. This protocol is for a review that identifies the range and most common diagnoses used to conduct surveillance for traumatic brain injury in children and youth. This is an important first step in reaching an appropriate definition using International Classification of Diseases version 10 codes and can inform future work on reaching consensus on the codes to define traumatic brain injury for this vulnerable population.

Assessment of habitat representation across a network of marine protected areas with implications for the spatial design of monitoring.

PubMed

Young, Mary; Carr, Mark

2015-01-01

Networks of marine protected areas (MPAs) are being adopted globally to protect ecosystems and supplement fisheries management. The state of California recently implemented a coast-wide network of MPAs, a statewide seafloor mapping program, and ecological characterizations of species and ecosystems targeted for protection by the network. The main goals of this study were to use these data to evaluate how well seafloor features, as proxies for habitats, are represented and replicated across an MPA network and how well ecological surveys representatively sampled fish habitats inside MPAs and adjacent reference sites. Seafloor data were classified into broad substrate categories (rock and sediment) and finer scale geomorphic classifications standard to marine classification schemes using surface analyses (slope, ruggedness, etc.) done on the digital elevation model derived from multibeam bathymetry data. These classifications were then used to evaluate the representation and replication of seafloor structure within the MPAs and across the ecological surveys. Both the broad substrate categories and the finer scale geomorphic features were proportionately represented for many of the classes with deviations of 1-6% and 0-7%, respectively. Within MPAs, however, representation of seafloor features differed markedly from original estimates, with differences ranging up to 28%. Seafloor structure in the biological monitoring design had mismatches between sampling in the MPAs and their corresponding reference sites and some seafloor structure classes were missed entirely. The geomorphic variables derived from multibeam bathymetry data for these analyses are known determinants of the distribution and abundance of marine species and for coastal marine biodiversity. Thus, analyses like those performed in this study can be a valuable initial method of evaluating and predicting the conservation value of MPAs across a regional network.

Assessment of Habitat Representation across a Network of Marine Protected Areas with Implications for the Spatial Design of Monitoring

PubMed Central

Young, Mary; Carr, Mark

2015-01-01

Networks of marine protected areas (MPAs) are being adopted globally to protect ecosystems and supplement fisheries management. The state of California recently implemented a coast-wide network of MPAs, a statewide seafloor mapping program, and ecological characterizations of species and ecosystems targeted for protection by the network. The main goals of this study were to use these data to evaluate how well seafloor features, as proxies for habitats, are represented and replicated across an MPA network and how well ecological surveys representatively sampled fish habitats inside MPAs and adjacent reference sites. Seafloor data were classified into broad substrate categories (rock and sediment) and finer scale geomorphic classifications standard to marine classification schemes using surface analyses (slope, ruggedness, etc.) done on the digital elevation model derived from multibeam bathymetry data. These classifications were then used to evaluate the representation and replication of seafloor structure within the MPAs and across the ecological surveys. Both the broad substrate categories and the finer scale geomorphic features were proportionately represented for many of the classes with deviations of 1-6% and 0-7%, respectively. Within MPAs, however, representation of seafloor features differed markedly from original estimates, with differences ranging up to 28%. Seafloor structure in the biological monitoring design had mismatches between sampling in the MPAs and their corresponding reference sites and some seafloor structure classes were missed entirely. The geomorphic variables derived from multibeam bathymetry data for these analyses are known determinants of the distribution and abundance of marine species and for coastal marine biodiversity. Thus, analyses like those performed in this study can be a valuable initial method of evaluating and predicting the conservation value of MPAs across a regional network. PMID:25760858

Dutch population specific sex estimation formulae using the proximal femur.

PubMed

Colman, K L; Janssen, M C L; Stull, K E; van Rijn, R R; Oostra, R J; de Boer, H H; van der Merwe, A E

2018-05-01

Sex estimation techniques are frequently applied in forensic anthropological analyses of unidentified human skeletal remains. While morphological sex estimation methods are able to endure population differences, the classification accuracy of metric sex estimation methods are population-specific. No metric sex estimation method currently exists for the Dutch population. The purpose of this study is to create Dutch population specific sex estimation formulae by means of osteometric analyses of the proximal femur. Since the Netherlands lacks a representative contemporary skeletal reference population, 2D plane reconstructions, derived from clinical computed tomography (CT) data, were used as an alternative source for a representative reference sample. The first part of this study assesses the intra- and inter-observer error, or reliability, of twelve measurements of the proximal femur. The technical error of measurement (TEM) and relative TEM (%TEM) were calculated using 26 dry adult femora. In addition, the agreement, or accuracy, between the dry bone and CT-based measurements was determined by percent agreement. Only reliable and accurate measurements were retained for the logistic regression sex estimation formulae; a training set (n=86) was used to create the models while an independent testing set (n=28) was used to validate the models. Due to high levels of multicollinearity, only single variable models were created. Cross-validated classification accuracies ranged from 86% to 92%. The high cross-validated classification accuracies indicate that the developed formulae can contribute to the biological profile and specifically in sex estimation of unidentified human skeletal remains in the Netherlands. Furthermore, the results indicate that clinical CT data can be a valuable alternative source of data when representative skeletal collections are unavailable. Copyright © 2017 Elsevier B.V. All rights reserved.

Transparent Tube Studies of Burning to Detonation Transition in Granular Explosives 1: Preliminary Framing Camera Studies

DTIC Science & Technology

1980-10-27

Reference 13. The 94/6 RDX/ wax (X893) and 97/3 RDX/ wax (X758) were mechanical mixtures prepared from Class A RDX (X597) and carnauba wax (N134). The...UKLAS9*TE SE,’CRITY CLASSIFICATION OF THIS PAGE (When Data Entered) ionization probes in previous steel tube studies. In charges of 94/6 RDX/ wax ...explosives (picric acid, tetryl, and RDX/ wax ) were among those materials in previous steel tube studies at NSWC which achieved deflagration to

Resilience in Utility Technologies

NASA Astrophysics Data System (ADS)

Seaton, Roger

The following sections are included: * Scope of paper * Preamble * Background to the case-study projects * Source projects * Resilience * Case study 1: Electricity generation * Context * Model * Case study 2: Water recycling * Context * Model * Case study 3: Ecotechnology and water treatment * Context * The problem of classification: Finding a classificatory solution * Application of the new taxonomy to water treatment * Concluding comments and questions * Conclusions * Questions and issues * Purposive or Purposeful? * Resilience: Flexibility and adaptivity? * Resilience: With respect of what? * Risk, uncertainty, surprise, emergence - What sort of shock, and who says so? * Co-evolutionary friction * References

[Object-oriented segmentation and classification of forest gap based on QuickBird remote sensing image.

PubMed

Mao, Xue Gang; Du, Zi Han; Liu, Jia Qian; Chen, Shu Xin; Hou, Ji Yu

2018-01-01

Traditional field investigation and artificial interpretation could not satisfy the need of forest gaps extraction at regional scale. High spatial resolution remote sensing image provides the possibility for regional forest gaps extraction. In this study, we used object-oriented classification method to segment and classify forest gaps based on QuickBird high resolution optical remote sensing image in Jiangle National Forestry Farm of Fujian Province. In the process of object-oriented classification, 10 scales (10-100, with a step length of 10) were adopted to segment QuickBird remote sensing image; and the intersection area of reference object (RA or ) and intersection area of segmented object (RA os ) were adopted to evaluate the segmentation result at each scale. For segmentation result at each scale, 16 spectral characteristics and support vector machine classifier (SVM) were further used to classify forest gaps, non-forest gaps and others. The results showed that the optimal segmentation scale was 40 when RA or was equal to RA os . The accuracy difference between the maximum and minimum at different segmentation scales was 22%. At optimal scale, the overall classification accuracy was 88% (Kappa=0.82) based on SVM classifier. Combining high resolution remote sensing image data with object-oriented classification method could replace the traditional field investigation and artificial interpretation method to identify and classify forest gaps at regional scale.

Subintentional Suicide among Youth.

ERIC Educational Resources Information Center

Smith, D. F.

1980-01-01

Subintentional suicide is a classification that refers to ill-defined deaths and practices that lead toward death. Types of subintentional suicide among adolescents include drug abuse and risk taking when driving automobiles. (JN)

Low back related leg pain: an investigation of construct validity of a new classification system.

PubMed

Schäfer, Axel G M; Hall, Toby M; Rolke, Roman; Treede, Rolf-Detlef; Lüdtke, Kerstin; Mallwitz, Joachim; Briffa, Kathryn N

2014-01-01

Leg pain is associated with back pain in 25-65% of all cases and classified as somatic referred pain or radicular pain. However, distinction between the two may be difficult as different pathomechanisms may cause similar patterns of pain. Therefore a pathomechanism based classification system was proposed, with four distinct hierarchical and mutually exclusive categories: Neuropathic Sensitization (NS) comprising major features of neuropathic pain with sensory sensitization; Denervation (D) arising from significant axonal compromise; Peripheral Nerve Sensitization (PNS) with marked nerve trunk mechanosensitivity; and Musculoskeletal (M) with pain referred from musculoskeletal structures. To investigate construct validity of the classification system. Construct validity was investigated by determining the relationship of nerve functioning with subgroups of patients and asymptomatic controls. Thus somatosensory profiles of subgroups of patients with low back related leg pain (LBRLP) and healthy controls were determined by a comprehensive quantitative sensory test (QST) protocol. It was hypothesized that subgroups of patients and healthy controls would show differences in QST profiles relating to underlying pathomechanisms. 77 subjects with LBRLP were recruited and classified in one of the four groups. Additionally, 18 age and gender matched asymptomatic controls were measured. QST revealed signs of pain hypersensitivity in group NS and sensory deficits in group D whereas Groups PNS and M showed no significant differences when compared to the asymptomatic group. These findings support construct validity for two of the categories of the new classification system, however further research is warranted to achieve construct validation of the classification system as a whole.

Advancement of High Resolution Radar Polarimetry in Target Verses Clutter Detection, Discrimination, Classification: A. Basic Theory and Modeling of Polarimetric Clutter Phenomenology.

DTIC Science & Technology

1988-07-15

the interim period, polarimetLic measurement data collected at other DOD/NATO/Industrial R/D/M facilities will be used. These basic studies will be...the polarization sphere and its spread can he related either to the coherency factor or the depolarization factor plus descriptive parameters of the...careful study of the concluding sections outlining the overall scenario of solved and unsolved problems. Here, we also refer to the recent report (Dec

Geospatial Method for Computing Supplemental Multi-Decadal U.S. Coastal Land-Use and Land-Cover Classification Products, Using Landsat Data and C-CAP Products

NASA Technical Reports Server (NTRS)

Spruce, J. P.; Smoot, James; Ellis, Jean; Hilbert, Kent; Swann, Roberta

2012-01-01

This paper discusses the development and implementation of a geospatial data processing method and multi-decadal Landsat time series for computing general coastal U.S. land-use and land-cover (LULC) classifications and change products consisting of seven classes (water, barren, upland herbaceous, non-woody wetland, woody upland, woody wetland, and urban). Use of this approach extends the observational period of the NOAA-generated Coastal Change and Analysis Program (C-CAP) products by almost two decades, assuming the availability of one cloud free Landsat scene from any season for each targeted year. The Mobile Bay region in Alabama was used as a study area to develop, demonstrate, and validate the method that was applied to derive LULC products for nine dates at approximate five year intervals across a 34-year time span, using single dates of data for each classification in which forests were either leaf-on, leaf-off, or mixed senescent conditions. Classifications were computed and refined using decision rules in conjunction with unsupervised classification of Landsat data and C-CAP value-added products. Each classification's overall accuracy was assessed by comparing stratified random locations to available reference data, including higher spatial resolution satellite and aerial imagery, field survey data, and raw Landsat RGBs. Overall classification accuracies ranged from 83 to 91% with overall Kappa statistics ranging from 0.78 to 0.89. The accuracies are comparable to those from similar, generalized LULC products derived from C-CAP data. The Landsat MSS-based LULC product accuracies are similar to those from Landsat TM or ETM+ data. Accurate classifications were computed for all nine dates, yielding effective results regardless of season. This classification method yielded products that were used to compute LULC change products via additive GIS overlay techniques.

Single-particle cryo-EM using alignment by classification (ABC): the structure of Lumbricus terrestris haemoglobin

PubMed Central

Seer-Linnemayr, Charlotte; Ravelli, Raimond B. G.; Matadeen, Rishi; De Carlo, Sacha; Alewijnse, Bart; Portugal, Rodrigo V.; Pannu, Navraj S.; Schatz, Michael; van Heel, Marin

2017-01-01

Single-particle cryogenic electron microscopy (cryo-EM) can now yield near-atomic resolution structures of biological complexes. However, the reference-based alignment algorithms commonly used in cryo-EM suffer from reference bias, limiting their applicability (also known as the ‘Einstein from random noise’ problem). Low-dose cryo-EM therefore requires robust and objective approaches to reveal the structural information contained in the extremely noisy data, especially when dealing with small structures. A reference-free pipeline is presented for obtaining near-atomic resolution three-dimensional reconstructions from heterogeneous (‘four-dimensional’) cryo-EM data sets. The methodologies integrated in this pipeline include a posteriori camera correction, movie-based full-data-set contrast transfer function determination, movie-alignment algorithms, (Fourier-space) multivariate statistical data compression and unsupervised classification, ‘random-startup’ three-dimensional reconstructions, four-dimensional structural refinements and Fourier shell correlation criteria for evaluating anisotropic resolution. The procedures exclusively use information emerging from the data set itself, without external ‘starting models’. Euler-angle assignments are performed by angular reconstitution rather than by the inherently slower projection-matching approaches. The comprehensive ‘ABC-4D’ pipeline is based on the two-dimensional reference-free ‘alignment by classification’ (ABC) approach, where similar images in similar orientations are grouped by unsupervised classification. Some fundamental differences between X-ray crystallography versus single-particle cryo-EM data collection and data processing are discussed. The structure of the giant haemoglobin from Lumbricus terrestris at a global resolution of ∼3.8 Å is presented as an example of the use of the ABC-4D procedure. PMID:28989723

Application of laser ablation multicollector inductively coupled plasma mass spectrometry for the measurement of calcium and lead isotope ratios in packaging for discriminatory purposes.

PubMed

Santamaria-Fernandez, Rebeca; Wolff, Jean-Claude

2010-07-30

The potential of high-precision calcium and lead isotope ratio measurements using laser ablation coupled to multicollector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS) to aid distinction between four genuine and five counterfeit pharmaceutical packaging samples and further classification of counterfeit packaging samples has been evaluated. We highlight the lack of reference materials for LA-MC-ICP-MS isotope ratio measurements in solids. In this case the problem is minimised by using National Institute of Standards and Technology Standard Reference Material (NIST SRM) 915a calcium carbonate (as solid pellets) and NIST SRM610 glass disc for sample bracketing external standardisation. In addition, a new reference material, NIST SRM915b calcium carbonate, has been characterised in-house for Ca isotope ratios and is used as a reference sample. Significant differences have been found between genuine and counterfeit samples; the method allows detection of counterfeits and aids further classification of packaging samples. Typical expanded uncertainties for measured-corrected Ca isotope ratio values ((43)Ca/(44)Ca and (42)Ca/(44)Ca) were found to be below 0.06% (k = 2, 95% confidence) and below 0.2% for measured-corrected Pb isotope ratios ((207)Pb/(206)Pb and (208)Pb/(206)Pb). This is the first time that Ca isotope ratios have been measured in packaging materials using LA coupled to a multicollector (MC)-ICP-MS instrument. The use of LA-MC-ICP-MS for direct measurement of Ca and Pb isotopic variations in cardboard/ink in packaging has definitive potential to aid counterfeit detection and classification. Copyright 2010 John Wiley & Sons, Ltd.

Further examination of embedded performance validity indicators for the Conners' Continuous Performance Test and Brief Test of Attention in a large outpatient clinical sample.

PubMed

Sharland, Michael J; Waring, Stephen C; Johnson, Brian P; Taran, Allise M; Rusin, Travis A; Pattock, Andrew M; Palcher, Jeanette A

2018-01-01

Assessing test performance validity is a standard clinical practice and although studies have examined the utility of cognitive/memory measures, few have examined attention measures as indicators of performance validity beyond the Reliable Digit Span. The current study further investigates the classification probability of embedded Performance Validity Tests (PVTs) within the Brief Test of Attention (BTA) and the Conners' Continuous Performance Test (CPT-II), in a large clinical sample. This was a retrospective study of 615 patients consecutively referred for comprehensive outpatient neuropsychological evaluation. Non-credible performance was defined two ways: failure on one or more PVTs and failure on two or more PVTs. Classification probability of the BTA and CPT-II into non-credible groups was assessed. Sensitivity, specificity, positive predictive value, and negative predictive value were derived to identify clinically relevant cut-off scores. When using failure on two or more PVTs as the indicator for non-credible responding compared to failure on one or more PVTs, highest classification probability, or area under the curve (AUC), was achieved by the BTA (AUC = .87 vs. .79). CPT-II Omission, Commission, and Total Errors exhibited higher classification probability as well. Overall, these findings corroborate previous findings, extending them to a large clinical sample. BTA and CPT-II are useful embedded performance validity indicators within a clinical battery but should not be used in isolation without other performance validity indicators.

Can Statistical Machine Learning Algorithms Help for Classification of Obstructive Sleep Apnea Severity to Optimal Utilization of Polysomnography Resources?

PubMed

Bozkurt, Selen; Bostanci, Asli; Turhan, Murat

2017-08-11

The goal of this study is to evaluate the results of machine learning methods for the classification of OSA severity of patients with suspected sleep disorder breathing as normal, mild, moderate and severe based on non-polysomnographic variables: 1) clinical data, 2) symptoms and 3) physical examination. In order to produce classification models for OSA severity, five different machine learning methods (Bayesian network, Decision Tree, Random Forest, Neural Networks and Logistic Regression) were trained while relevant variables and their relationships were derived empirically from observed data. Each model was trained and evaluated using 10-fold cross-validation and to evaluate classification performances of all methods, true positive rate (TPR), false positive rate (FPR), Positive Predictive Value (PPV), F measure and Area Under Receiver Operating Characteristics curve (ROC-AUC) were used. Results of 10-fold cross validated tests with different variable settings promisingly indicated that the OSA severity of suspected OSA patients can be classified, using non-polysomnographic features, with 0.71 true positive rate as the highest and, 0.15 false positive rate as the lowest, respectively. Moreover, the test results of different variables settings revealed that the accuracy of the classification models was significantly improved when physical examination variables were added to the model. Study results showed that machine learning methods can be used to estimate the probabilities of no, mild, moderate, and severe obstructive sleep apnea and such approaches may improve accurate initial OSA screening and help referring only the suspected moderate or severe OSA patients to sleep laboratories for the expensive tests.

An Example of Unsupervised Networks Kohonen's Self-Organizing Feature Map

NASA Technical Reports Server (NTRS)

Niebur, Dagmar

1995-01-01

Kohonen's self-organizing feature map belongs to a class of unsupervised artificial neural network commonly referred to as topographic maps. It serves two purposes, the quantization and dimensionality reduction of date. A short description of its history and its biological context is given. We show that the inherent classification properties of the feature map make it a suitable candidate for solving the classification task in power system areas like load forecasting, fault diagnosis and security assessment.

The Libraries of Rio.

ERIC Educational Resources Information Center

Foster, Barbara

1988-01-01

Describes aspects of several libraries in Rio de Janeiro. Topics covered include library policies, budgets, periodicals and books in the collections, classification schemes used, and literary areas of interest to patrons. (6 references) (CLB)

Toward genetics-based virus taxonomy: comparative analysis of a genetics-based classification and the taxonomy of picornaviruses.

PubMed

Lauber, Chris; Gorbalenya, Alexander E

2012-04-01

Virus taxonomy has received little attention from the research community despite its broad relevance. In an accompanying paper (C. Lauber and A. E. Gorbalenya, J. Virol. 86:3890-3904, 2012), we have introduced a quantitative approach to hierarchically classify viruses of a family using pairwise evolutionary distances (PEDs) as a measure of genetic divergence. When applied to the six most conserved proteins of the Picornaviridae, it clustered 1,234 genome sequences in groups at three hierarchical levels (to which we refer as the "GENETIC classification"). In this study, we compare the GENETIC classification with the expert-based picornavirus taxonomy and outline differences in the underlying frameworks regarding the relation of virus groups and genetic diversity that represent, respectively, the structure and content of a classification. To facilitate the analysis, we introduce two novel diagrams. The first connects the genetic diversity of taxa to both the PED distribution and the phylogeny of picornaviruses. The second depicts a classification and the accommodated genetic diversity in a standardized manner. Generally, we found striking agreement between the two classifications on species and genus taxa. A few disagreements concern the species Human rhinovirus A and Human rhinovirus C and the genus Aphthovirus, which were split in the GENETIC classification. Furthermore, we propose a new supergenus level and universal, level-specific PED thresholds, not reached yet by many taxa. Since the species threshold is approached mostly by taxa with large sampling sizes and those infecting multiple hosts, it may represent an upper limit on divergence, beyond which homologous recombination in the six most conserved genes between two picornaviruses might not give viable progeny.

Rotationally Invariant Image Representation for Viewing Direction Classification in Cryo-EM

PubMed Central

Zhao, Zhizhen; Singer, Amit

2014-01-01

We introduce a new rotationally invariant viewing angle classification method for identifying, among a large number of cryo-EM projection images, similar views without prior knowledge of the molecule. Our rotationally invariant features are based on the bispectrum. Each image is denoised and compressed using steerable principal component analysis (PCA) such that rotating an image is equivalent to phase shifting the expansion coefficients. Thus we are able to extend the theory of bispectrum of 1D periodic signals to 2D images. The randomized PCA algorithm is then used to efficiently reduce the dimensionality of the bispectrum coefficients, enabling fast computation of the similarity between any pair of images. The nearest neighbors provide an initial classification of similar viewing angles. In this way, rotational alignment is only performed for images with their nearest neighbors. The initial nearest neighbor classification and alignment are further improved by a new classification method called vector diffusion maps. Our pipeline for viewing angle classification and alignment is experimentally shown to be faster and more accurate than reference-free alignment with rotationally invariant K-means clustering, MSA/MRA 2D classification, and their modern approximations. PMID:24631969

A Review on Data Stream Classification

NASA Astrophysics Data System (ADS)

Haneen, A. A.; Noraziah, A.; Wahab, Mohd Helmy Abd

2018-05-01

At this present time, the significance of data streams cannot be denied as many researchers have placed their focus on the research areas of databases, statistics, and computer science. In fact, data streams refer to some data points sequences that are found in order with the potential to be non-binding, which is generated from the process of generating information in a manner that is not stationary. As such the typical tasks of searching data have been linked to streams of data that are inclusive of clustering, classification, and repeated mining of pattern. This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies.

A modular case-mix classification system for medical rehabilitation illustrated.

PubMed

Stineman, M G; Granger, C V

1997-01-01

The authors present a modular set of patient classification systems designed for medical rehabilitation that predict resource use and outcomes for clinically similar groups of individuals. The systems, based on the Functional Independence Measure, are referred to as Function-Related Groups (FIM-FRGs). Using data from 23,637 lower extremity fracture patients from 458 inpatient medical rehabilitation facilities, 1995 benchmarks are provided and illustrated for length of stay, functional outcome, and discharge to home and skilled nursing facilities (SNFs). The FIM-FRG modules may be used in parallel to study interactions between resource use and quality and could ultimately yield an integrated strategy for payment and outcomes measurement. This could position the rehabilitation community to take a pioneering role in the application of outcomes-based clinical indicators.

Scalable metagenomic taxonomy classification using a reference genome database

PubMed Central

Ames, Sasha K.; Hysom, David A.; Gardner, Shea N.; Lloyd, G. Scott; Gokhale, Maya B.; Allen, Jonathan E.

2013-01-01

Motivation: Deep metagenomic sequencing of biological samples has the potential to recover otherwise difficult-to-detect microorganisms and accurately characterize biological samples with limited prior knowledge of sample contents. Existing metagenomic taxonomic classification algorithms, however, do not scale well to analyze large metagenomic datasets, and balancing classification accuracy with computational efficiency presents a fundamental challenge. Results: A method is presented to shift computational costs to an off-line computation by creating a taxonomy/genome index that supports scalable metagenomic classification. Scalable performance is demonstrated on real and simulated data to show accurate classification in the presence of novel organisms on samples that include viruses, prokaryotes, fungi and protists. Taxonomic classification of the previously published 150 giga-base Tyrolean Iceman dataset was found to take <20 h on a single node 40 core large memory machine and provide new insights on the metagenomic contents of the sample. Availability: Software was implemented in C++ and is freely available at http://sourceforge.net/projects/lmat Contact: allen99@llnl.gov Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23828782

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification

PubMed Central

Liu, Fuxian

2018-01-01

One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs) as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM) classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references. PMID:29581722

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification.

PubMed

Yu, Yunlong; Liu, Fuxian

2018-01-01

One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs) as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM) classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references.

Application of Convolutional Neural Network in Classification of High Resolution Agricultural Remote Sensing Images

NASA Astrophysics Data System (ADS)

Yao, C.; Zhang, Y.; Zhang, Y.; Liu, H.

2017-09-01

With the rapid development of Precision Agriculture (PA) promoted by high-resolution remote sensing, it makes significant sense in management and estimation of agriculture through crop classification of high-resolution remote sensing image. Due to the complex and fragmentation of the features and the surroundings in the circumstance of high-resolution, the accuracy of the traditional classification methods has not been able to meet the standard of agricultural problems. In this case, this paper proposed a classification method for high-resolution agricultural remote sensing images based on convolution neural networks(CNN). For training, a large number of training samples were produced by panchromatic images of GF-1 high-resolution satellite of China. In the experiment, through training and testing on the CNN under the toolbox of deep learning by MATLAB, the crop classification finally got the correct rate of 99.66 % after the gradual optimization of adjusting parameter during training. Through improving the accuracy of image classification and image recognition, the applications of CNN provide a reference value for the field of remote sensing in PA.

Taxonaut: an application software for comparative display of multiple taxonomies with a use case of GBIF Species API.

PubMed

Ytow, Nozomi

2016-01-01

The Species API of the Global Biodiversity Information Facility (GBIF) provides public access to taxonomic data aggregated from multiple data sources. Each data source follows its own classification which can be inconsistent with classifications from other sources. Even with a reference classification e.g. the GBIF Backbone taxonomy, a comprehensive method to compare classifications in the data aggregation is essential, especially for non-expert users. A Java application was developed to compare multiple taxonomies graphically using classification data acquired from GBIF's ChecklistBank via the GBIF Species API. It uses a table to display taxonomies where each column represents a taxonomy under comparison, with an aligner column to organise taxa by name. Each cell contains the name of a taxon if the classification in that column contains the name. Each column also has a cell showing the hierarchy of the taxonomy by a folder metaphor where taxa are aligned and synchronised in the aligner column. A set of those comparative tables shows taxa categorised by relationship between taxonomies. The result set is also available as tables in an Excel format file.

NASA Scope and Subject Category Guide

NASA Technical Reports Server (NTRS)

2011-01-01

This guide provides a simple, effective tool to assist aerospace information analysts and database builders in the high-level subject classification of technical materials. Each of the 76 subject categories comprising the classification scheme is presented with a description of category scope, a listing of subtopics, cross references, and an indication of particular areas of NASA interest. The guide also includes an index of nearly 3,000 specific research topics cross referenced to the subject categories. The portable document format (PDF) version of the guide contains links in the index from each input subject to its corresponding categories. In addition to subject classification, the guide can serve as an aid to searching databases that use the classification scheme, and is also an excellent selection guide for those involved in the acquisition of aerospace literature. The CD-ROM contains both HTML and PDF versions.

The Structured Clinical Interview for DSM-IV Childhood Diagnoses (Kid-SCID): first psychometric evaluation in a Dutch sample of clinically referred youths.

PubMed

Roelofs, Jeffrey; Muris, Peter; Braet, Caroline; Arntz, Arnoud; Beelen, Imke

2015-06-01

The Structured Clinical Interview for DSM-IV Childhood Disorders (Kid-SCID) is a semi-structured interview for the classification of psychiatric disorders in children and adolescents. This study presents a first evaluation of the psychometric properties of the Kid-SCID in a Dutch sample of children and adolescents who had been referred to an outpatient treatment centre for mental health problems. Results indicated that the inter-rater reliability of the Kid-SCID classifications and the internal consistency of various (dimensional) criteria of the diagnoses were moderate to good. Further, for most Kid-SCID diagnoses, reasonable agreement between children and parents was found. Finally, the correspondence between the Kid-SCID and the final clinical diagnosis as established after the full intake procedure, which included the information as provided by the Kid-SCID, ranged from poor to good. Results are discussed in the light of methodological issues pertaining to the assessment of psychiatric disorders in youths. The Kid-SCID can generally be seen as a reliable and useful tool that can assist clinicians in carrying out clinical evaluations of children and adolescents.

Measurement properties of gingival biotype evaluation methods.

PubMed

Alves, Patrick Henry Machado; Alves, Thereza Cristina Lira Pacheco; Pegoraro, Thiago Amadei; Costa, Yuri Martins; Bonfante, Estevam Augusto; de Almeida, Ana Lúcia Pompéia Fraga

2018-06-01

There are numerous methods to measure the dimensions of the gingival tissue, but few have compared the effectiveness of one method over another. This study aimed to describe a new method and to estimate the validity of gingival biotype assessment with the aid of computed tomography scanning (CTS). In each patient different methods of evaluation of the gingival thickness were used: transparency of periodontal probe, transgingival, photography, and a new method of CTS). Intrarater and interrater reliability considering the categorical classification of the gingival biotype were estimated with Cohen's kappa coefficient, intraclass correlation coefficient (ICC), and ANOVA (P < .05). The criterion validity of the CTS was determined using the transgingival method as the reference standard. Sensitivity and specificity values were computed along with theirs 95% CI. Twelve patients were subjected to assessment of their gingival thickness. The highest agreement was found between transgingival and CTS (86.1%). The comparison between the categorical classifications of CTS and the transgingival method (reference standard) showed high specificity (94.92%) and low sensitivity (53.85%) for definition of a thin biotype. The new method of CTS assessment to classify gingival tissue thickness can be considered reliable and clinically useful to diagnose thick biotype. © 2018 Wiley Periodicals, Inc.

Reference Models for Multi-Layer Tissue Structures

DTIC Science & Technology

2016-09-01

simulation,  finite   element  analysis 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON USAMRMC...Physiologically realistic, fully specimen-specific, nonlinear reference models. Tasks. Finite element analysis of non-linear mechanics of cadaver...models. Tasks. Finite element analysis of non-linear mechanics of multi-layer tissue regions of human subjects. Deliverables. Partially subject- and

Age-specific MRI brain and head templates for healthy adults from 20 through 89 years of age

PubMed Central

Fillmore, Paul T.; Phillips-Meek, Michelle C.; Richards, John E.

2015-01-01

This study created and tested a database of adult, age-specific MRI brain and head templates. The participants included healthy adults from 20 through 89 years of age. The templates were done in five-year, 10-year, and multi-year intervals from 20 through 89 years, and consist of average T1W for the head and brain, and segmenting priors for gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). It was found that age-appropriate templates provided less biased tissue classification estimates than age-inappropriate reference data and reference data based on young adult templates. This database is available for use by other investigators and clinicians for their MRI studies, as well as other types of neuroimaging and electrophysiological research.1 PMID:25904864

A Review of Wetland Remote Sensing.

PubMed

Guo, Meng; Li, Jing; Sheng, Chunlei; Xu, Jiawei; Wu, Li

2017-04-05

Wetlands are some of the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water and also provide habitats for many plants and animals. Wetlands also interact with climate change. Over the past 50 years, wetlands have been polluted and declined dramatically as land cover has changed in some regions. Remote sensing has been the most useful tool to acquire spatial and temporal information about wetlands. In this paper, seven types of sensors were reviewed: aerial photos coarse-resolution, medium-resolution, high-resolution, hyperspectral imagery, radar, and Light Detection and Ranging (LiDAR) data. This study also discusses the advantage of each sensor for wetland research. Wetland research themes reviewed in this paper include wetland classification, habitat or biodiversity, biomass estimation, plant leaf chemistry, water quality, mangrove forest, and sea level rise. This study also gives an overview of the methods used in wetland research such as supervised and unsupervised classification and decision tree and object-based classification. Finally, this paper provides some advice on future wetland remote sensing. To our knowledge, this paper is the most comprehensive and detailed review of wetland remote sensing and it will be a good reference for wetland researchers.

A Review of Wetland Remote Sensing

PubMed Central

Guo, Meng; Li, Jing; Sheng, Chunlei; Xu, Jiawei; Wu, Li

2017-01-01

Wetlands are some of the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water and also provide habitats for many plants and animals. Wetlands also interact with climate change. Over the past 50 years, wetlands have been polluted and declined dramatically as land cover has changed in some regions. Remote sensing has been the most useful tool to acquire spatial and temporal information about wetlands. In this paper, seven types of sensors were reviewed: aerial photos coarse-resolution, medium-resolution, high-resolution, hyperspectral imagery, radar, and Light Detection and Ranging (LiDAR) data. This study also discusses the advantage of each sensor for wetland research. Wetland research themes reviewed in this paper include wetland classification, habitat or biodiversity, biomass estimation, plant leaf chemistry, water quality, mangrove forest, and sea level rise. This study also gives an overview of the methods used in wetland research such as supervised and unsupervised classification and decision tree and object-based classification. Finally, this paper provides some advice on future wetland remote sensing. To our knowledge, this paper is the most comprehensive and detailed review of wetland remote sensing and it will be a good reference for wetland researchers. PMID:28379174

Applying ethnic-specific bone mineral density T-scores to Chinese women in the USA.

PubMed

Lo, J C; Kim, S; Chandra, M; Ettinger, B

2016-12-01

Caucasian reference data are used to classify bone mineral density in US women of all races. However, use of Chinese American reference data yields lower osteoporosis prevalence in Chinese women. The reduction in osteoporosis labeling may be relevant for younger Chinese women at low fracture risk. Caucasian reference data are used for osteoporosis classification in US postmenopausal women regardless of race, including Asians who tend to have lower bone mineral density (BMD) than women of white race. This study examines BMD classification by ethnic T-scores for Chinese women. Using BMD data in a Northern California healthcare population, Chinese women aged 50-79 years were compared to age-matched white women (1:5 ratio), with femoral neck (FN), total hip (TH), and lumbar spine (LS) T-scores calculated using Caucasian versus Chinese American reference data. Comparing 4039 Chinese and 20,195 white women (44.8 % age 50-59 years, 37.5 % age 60-69 years, 17.7 % age 70-79 years), Chinese women had lower BMD T-scores at the FN, TH, and LS (median T-score 0.29-0.72 units lower across age groups, p < 0.001) using Caucasian reference data. Using Chinese American BMD reference data resulted in an average +0.47, +0.36, and +0.48 units higher FN, TH, and LS T-scores, respectively, reducing the prevalence of osteoporosis (T-score ≤ -2.5) in Chinese women at the FN (16.7 to 6.6 %), TH (9.8 to 3.2 %), and LS (23.2 to 8.9 %); osteoporosis prevalence at any one of three sites fell from 29.6 to 12.6 % (22.4 to 8.1 % for age 50-64 years and 43.2 to 21.0 % for age 65-79 years). Use of Chinese American BMD reference data yields higher (ethnic) T-scores by 0.4-0.5 units, with a large proportion of Chinese women reclassified from osteoporosis to osteopenia. The reduction in osteoporosis labeling with ethnic T-scores may be relevant for younger Chinese women at low fracture risk.

17 CFR 140.21 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-04-01

... classified information. (d) Classification levels. Refers to Top Secret “(TS)”, Secret “(S)”, and Confidential “(C)” levels used to identify national security information. Markings “For Official Use Only,” and...

Classification of urban features using airborne hyperspectral data

NASA Astrophysics Data System (ADS)

Ganesh Babu, Bharath

Accurate mapping and modeling of urban environments are critical for their efficient and successful management. Superior understanding of complex urban environments is made possible by using modern geospatial technologies. This research focuses on thematic classification of urban land use and land cover (LULC) using 248 bands of 2.0 meter resolution hyperspectral data acquired from an airborne imaging spectrometer (AISA+) on 24th July 2006 in and near Terre Haute, Indiana. Three distinct study areas including two commercial classes, two residential classes, and two urban parks/recreational classes were selected for classification and analysis. Four commonly used classification methods -- maximum likelihood (ML), extraction and classification of homogeneous objects (ECHO), spectral angle mapper (SAM), and iterative self organizing data analysis (ISODATA) - were applied to each data set. Accuracy assessment was conducted and overall accuracies were compared between the twenty four resulting thematic maps. With the exception of SAM and ISODATA in a complex commercial area, all methods employed classified the designated urban features with more than 80% accuracy. The thematic classification from ECHO showed the best agreement with ground reference samples. The residential area with relatively homogeneous composition was classified consistently with highest accuracy by all four of the classification methods used. The average accuracy amongst the classifiers was 93.60% for this area. When individually observed, the complex recreational area (Deming Park) was classified with the highest accuracy by ECHO, with an accuracy of 96.80% and 96.10% Kappa. The average accuracy amongst all the classifiers was 92.07%. The commercial area with relatively high complexity was classified with the least accuracy by all classifiers. The lowest accuracy was achieved by SAM at 63.90% with 59.20% Kappa. This was also the lowest accuracy in the entire analysis. This study demonstrates the potential for using the visible and near infrared (VNIR) bands from AISA+ hyperspectral data in urban LULC classification. Based on their performance, the need for further research using ECHO and SAM is underscored. The importance incorporating imaging spectrometer data in high resolution urban feature mapping is emphasized.

A Preliminary Statistical Investigation into the Impace of an N-Gram Analysis Approach Based on World Syntactic Categories Toward Text Author Classification

DTIC Science & Technology

2000-06-01

of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources...words: N-gram, Shakespeare , Middleton, Wardigo, Funeral Elegy, Author Classification Introduction Literary experts refer to the style of the ...signed W. S. at the time of the investigation; the jury was still out as to the identity of its author. It has been noted as of late

Medical Parasitology Taxonomy Update: January 2012 to December 2015.

PubMed

Simner, P J

2017-01-01

Parasites of medical importance have long been classified taxonomically by morphological characteristics. However, molecular-based techniques have been increasingly used and relied on to determine evolutionary distances for the basis of rational hierarchal classifications. This has resulted in several different classification schemes for parasites and changes in parasite taxonomy. The purpose of this Minireview is to provide a single reference for diagnostic laboratories that summarizes new and revised clinically relevant parasite taxonomy from January 2012 through December 2015. Copyright © 2016 American Society for Microbiology.

Exploring the impact of wavelet-based denoising in the classification of remote sensing hyperspectral images

NASA Astrophysics Data System (ADS)

Quesada-Barriuso, Pablo; Heras, Dora B.; Argüello, Francisco

2016-10-01

The classification of remote sensing hyperspectral images for land cover applications is a very intensive topic. In the case of supervised classification, Support Vector Machines (SVMs) play a dominant role. Recently, the Extreme Learning Machine algorithm (ELM) has been extensively used. The classification scheme previously published by the authors, and called WT-EMP, introduces spatial information in the classification process by means of an Extended Morphological Profile (EMP) that is created from features extracted by wavelets. In addition, the hyperspectral image is denoised in the 2-D spatial domain, also using wavelets and it is joined to the EMP via a stacked vector. In this paper, the scheme is improved achieving two goals. The first one is to reduce the classification time while preserving the accuracy of the classification by using ELM instead of SVM. The second one is to improve the accuracy results by performing not only a 2-D denoising for every spectral band, but also a previous additional 1-D spectral signature denoising applied to each pixel vector of the image. For each denoising the image is transformed by applying a 1-D or 2-D wavelet transform, and then a NeighShrink thresholding is applied. Improvements in terms of classification accuracy are obtained, especially for images with close regions in the classification reference map, because in these cases the accuracy of the classification in the edges between classes is more relevant.

The 2016 update of the International Study Group (ISGPS) definition and grading of postoperative pancreatic fistula: 11 Years After.

PubMed

Bassi, Claudio; Marchegiani, Giovanni; Dervenis, Christos; Sarr, Micheal; Abu Hilal, Mohammad; Adham, Mustapha; Allen, Peter; Andersson, Roland; Asbun, Horacio J; Besselink, Marc G; Conlon, Kevin; Del Chiaro, Marco; Falconi, Massimo; Fernandez-Cruz, Laureano; Fernandez-Del Castillo, Carlos; Fingerhut, Abe; Friess, Helmut; Gouma, Dirk J; Hackert, Thilo; Izbicki, Jakob; Lillemoe, Keith D; Neoptolemos, John P; Olah, Attila; Schulick, Richard; Shrikhande, Shailesh V; Takada, Tadahiro; Takaori, Kyoichi; Traverso, William; Vollmer, Charles R; Wolfgang, Christopher L; Yeo, Charles J; Salvia, Roberto; Buchler, Marcus

2017-03-01

In 2005, the International Study Group of Pancreatic Fistula developed a definition and grading of postoperative pancreatic fistula that has been accepted universally. Eleven years later, because postoperative pancreatic fistula remains one of the most relevant and harmful complications of pancreatic operation, the International Study Group of Pancreatic Fistula classification has become the gold standard in defining postoperative pancreatic fistula in clinical practice. The aim of the present report is to verify the value of the International Study Group of Pancreatic Fistula definition and grading of postoperative pancreatic fistula and to update the International Study Group of Pancreatic Fistula classification in light of recent evidence that has emerged, as well as to address the lingering controversies about the original definition and grading of postoperative pancreatic fistula. The International Study Group of Pancreatic Fistula reconvened as the International Study Group in Pancreatic Surgery in order to perform a review of the recent literature and consequently to update and revise the grading system of postoperative pancreatic fistula. Based on the literature since 2005 investigating the validity and clinical use of the original International Study Group of Pancreatic Fistula classification, a clinically relevant postoperative pancreatic fistula is now redefined as a drain output of any measurable volume of fluid with an amylase level >3 times the upper limit of institutional normal serum amylase activity, associated with a clinically relevant development/condition related directly to the postoperative pancreatic fistula. Consequently, the former "grade A postoperative pancreatic fistula" is now redefined and called a "biochemical leak," because it has no clinical importance and is no longer referred to a true pancreatic fistula. Postoperative pancreatic fistula grades B and C are confirmed but defined more strictly. In particular, grade B requires a change in the postoperative management; drains are either left in place >3 weeks or repositioned through endoscopic or percutaneous procedures. Grade C postoperative pancreatic fistula refers to those postoperative pancreatic fistula that require reoperation or lead to single or multiple organ failure and/or mortality attributable to the pancreatic fistula. This new definition and grading system of postoperative pancreatic fistula should lead to a more universally consistent evaluation of operative outcomes after pancreatic operation and will allow for a better comparison of techniques used to mitigate the rate and clinical impact of a pancreatic fistula. Use of this updated classification will also allow for more precise comparisons of surgical quality between surgeons and units who perform pancreatic surgery. Copyright © 2016 Elsevier Inc. All rights reserved.

A new climatic classification of afforestation in Three-North regions of China with multi-source remote sensing data

NASA Astrophysics Data System (ADS)

Zheng, Xiao; Zhu, Jiaojun

2017-01-01

Afforestation and reforestation activities achieve high attention at the policy agenda as measures for carbon sequestration in order to mitigate climate change. The Three-North Shelter Forest Program, the largest ecological afforestation program worldwide, was launched in 1978 and will last until 2050 in the Three-North regions (accounting for 42.4 % of China's territory). Shelter forests of the Three-North Shelter Forest Program have exhibited severe decline after planting in 1978 due to lack of detailed climatic classification. Besides, a comprehensive assessment of climate adaptation for the current shelter forests was lacking. In this study, the aridity index determined by precipitation and reference evapotranspiration was employed to classify climatic zones for the afforestation program. The precipitation and reference evapotranspiration with 1-km resolution were estimated based on data from the tropical rainfall measuring mission and moderate resolution imaging spectroradiometer, respectively. Then, the detailed climatic classification for the afforestation program was obtained based on the relationship between the different vegetation types and the aridity index. The shelter forests in 2008 were derived from Landsat TM in the Three-North regions. In addition, climatic zones and shelter forests were corrected by comparing with natural vegetation map and field surveys. By overlaying the shelter forests on the climatic zones, we found that 16.30 % coniferous forests, 8.21 % broadleaved forests, 2.03 % mixed conifer-broadleaved forests, and 10.86 % shrubs were not in strict accordance with the climate conditions. These results open new perspectives for potential use of remote sensing techniques for afforestation management.

ASTM clustering for improving coal analysis by near-infrared spectroscopy.

PubMed

Andrés, J M; Bona, M T

2006-11-15

Multivariate analysis techniques have been applied to near-infrared (NIR) spectra coals to investigate the relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding predictor variables. In this work, a whole set of coal samples was grouped into six more homogeneous clusters following the ASTM reference method for classification prior to the application of calibration methods to each coal set. The results obtained showed a considerable improvement of the error determination compared with the calibration for the whole sample set. For some groups, the established calibrations approached the quality required by the ASTM/ISO norms for laboratory analysis. To predict property values for a new coal sample it is necessary the assignation of that sample to its respective group. Thus, the discrimination and classification ability of coal samples by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) in the NIR range was also studied by applying Soft Independent Modelling of Class Analogy (SIMCA) and Linear Discriminant Analysis (LDA) techniques. Modelling of the groups by SIMCA led to overlapping models that cannot discriminate for unique classification. On the other hand, the application of Linear Discriminant Analysis improved the classification of the samples but not enough to be satisfactory for every group considered.

Objective classification of ecological status in marine water bodies using ecotoxicological information and multivariate analysis.

PubMed

Beiras, Ricardo; Durán, Iria

2014-12-01

Some relevant shortcomings have been identified in the current approach for the classification of ecological status in marine water bodies, leading to delays in the fulfillment of the Water Framework Directive objectives. Natural variability makes difficult to settle fixed reference values and boundary values for the Ecological Quality Ratios (EQR) for the biological quality elements. Biological responses to environmental degradation are frequently of nonmonotonic nature, hampering the EQR approach. Community structure traits respond only once ecological damage has already been done and do not provide early warning signals. An alternative methodology for the classification of ecological status integrating chemical measurements, ecotoxicological bioassays and community structure traits (species richness and diversity), and using multivariate analyses (multidimensional scaling and cluster analysis), is proposed. This approach does not depend on the arbitrary definition of fixed reference values and EQR boundary values, and it is suitable to integrate nonlinear, sensitive signals of ecological degradation. As a disadvantage, this approach demands the inclusion of sampling sites representing the full range of ecological status in each monitoring campaign. National or international agencies in charge of coastal pollution monitoring have comprehensive data sets available to overcome this limitation.

Duane retraction syndrome on the Arabian Peninsula.

PubMed

Khan, Arif O; Oystreck, Darren T; Wilken, Keith; Akbar, Fatima

2007-01-01

To describe the clinical features of patients from the Arabian Peninsula with Duane retraction syndrome (DRS). Retrospective chart review of patients referred to the King Khaled Eye Specialist Hospital in Riyadh, Saudi Arabia from 1982 to 2003 with a diagnosis of DRS. Patients having had prior strabismus surgery were excluded. Of 404 DRS patients, 347 (86%) were unilateral, 57 (14%) were bilateral, and 111 (27%) had amblyopia. There were 221 (55%) females and 182 (45%) males. The Huber classification was as follows: 315 (78%) Type I, 16 (4%) Type II, and 77 (19%) Type III. Of the 57 bilateral cases, 25 (44%) were female and 32 (56%) were male. Overall, the clinical features of DRS patients referred to a Riyadh eye hospital are similar to those reported in series throughout the world. However, our referred bilateral DRS patients are more commonly male. The clinical features of bilateral DRS deserve further worldwide study.

EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES

PubMed Central

Liu, Jingyu; Xu, Lai; Caprihan, Arvind; Calhoun, Vince D.

2009-01-01

This paper presents an approach for selecting optimal components for discriminant analysis. Such an approach is useful when further detailed analyses for discrimination or characterization requires dimensionality reduction. Our approach can accommodate a categorical variable such as diagnosis (e.g. schizophrenic patient or healthy control), or a continuous variable like severity of the disorder. This information is utilized as a reference for measuring a component’s discriminant power after principle component decomposition. After sorting each component according to its discriminant power, we extract the best components for discriminant analysis. An application of our reference selection approach is shown using a functional magnetic resonance imaging data set in which the sample size is much less than the dimensionality. The results show that the reference selection approach provides an improved discriminant component set as compared to other approaches. Our approach is general and provides a solid foundation for further discrimination and classification studies. PMID:20582334

EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES.

PubMed

Liu, Jingyu; Xu, Lai; Caprihan, Arvind; Calhoun, Vince D

2008-05-12

This paper presents an approach for selecting optimal components for discriminant analysis. Such an approach is useful when further detailed analyses for discrimination or characterization requires dimensionality reduction. Our approach can accommodate a categorical variable such as diagnosis (e.g. schizophrenic patient or healthy control), or a continuous variable like severity of the disorder. This information is utilized as a reference for measuring a component's discriminant power after principle component decomposition. After sorting each component according to its discriminant power, we extract the best components for discriminant analysis. An application of our reference selection approach is shown using a functional magnetic resonance imaging data set in which the sample size is much less than the dimensionality. The results show that the reference selection approach provides an improved discriminant component set as compared to other approaches. Our approach is general and provides a solid foundation for further discrimination and classification studies.

Metrological aspects of enzyme production

NASA Astrophysics Data System (ADS)

Kerber, T. M.; Dellamora-Ortiz, G. M.; Pereira-Meirelles, F. V.

2010-05-01

Enzymes are frequently used in biotechnology to carry out specific biological reactions, either in industrial processes or for the production of bioproducts and drugs. Microbial lipases are an important group of biotechnologically valuable enzymes that present widely diversified applications. Lipase production by microorganisms is described in several published papers; however, none of them refer to metrological evaluation and the estimation of the uncertainty in measurement. Moreover, few of them refer to process optimization through experimental design. The objectives of this work were to enhance lipase production in shaken-flasks with Yarrowia lipolytica cells employing experimental design and to evaluate the uncertainty in measurement of lipase activity. The highest lipolytic activity obtained was about three- and fivefold higher than the reported activities of CRMs BCR-693 and BCR-694, respectively. Lipase production by Y. lipolytica cells aiming the classification as certified reference material is recommended after further purification and stability studies.

A curated database of cyanobacterial strains relevant for modern taxonomy and phylogenetic studies.

PubMed

Ramos, Vitor; Morais, João; Vasconcelos, Vitor M

2017-04-25

The dataset herein described lays the groundwork for an online database of relevant cyanobacterial strains, named CyanoType (http://lege.ciimar.up.pt/cyanotype). It is a database that includes categorized cyanobacterial strains useful for taxonomic, phylogenetic or genomic purposes, with associated information obtained by means of a literature-based curation. The dataset lists 371 strains and represents the first version of the database (CyanoType v.1). Information for each strain includes strain synonymy and/or co-identity, strain categorization, habitat, accession numbers for molecular data, taxonomy and nomenclature notes according to three different classification schemes, hierarchical automatic classification, phylogenetic placement according to a selection of relevant studies (including this), and important bibliographic references. The database will be updated periodically, namely by adding new strains meeting the criteria for inclusion and by revising and adding up-to-date metadata for strains already listed. A global 16S rDNA-based phylogeny is provided in order to assist users when choosing the appropriate strains for their studies.

A curated database of cyanobacterial strains relevant for modern taxonomy and phylogenetic studies

PubMed Central

Ramos, Vitor; Morais, João; Vasconcelos, Vitor M.

2017-01-01

The dataset herein described lays the groundwork for an online database of relevant cyanobacterial strains, named CyanoType (http://lege.ciimar.up.pt/cyanotype). It is a database that includes categorized cyanobacterial strains useful for taxonomic, phylogenetic or genomic purposes, with associated information obtained by means of a literature-based curation. The dataset lists 371 strains and represents the first version of the database (CyanoType v.1). Information for each strain includes strain synonymy and/or co-identity, strain categorization, habitat, accession numbers for molecular data, taxonomy and nomenclature notes according to three different classification schemes, hierarchical automatic classification, phylogenetic placement according to a selection of relevant studies (including this), and important bibliographic references. The database will be updated periodically, namely by adding new strains meeting the criteria for inclusion and by revising and adding up-to-date metadata for strains already listed. A global 16S rDNA-based phylogeny is provided in order to assist users when choosing the appropriate strains for their studies. PMID:28440791

PrionHome: a database of prions and other sequences relevant to prion phenomena.

PubMed

Harbi, Djamel; Parthiban, Marimuthu; Gendoo, Deena M A; Ehsani, Sepehr; Kumar, Manish; Schmitt-Ulms, Gerold; Sowdhamini, Ramanathan; Harrison, Paul M

2012-01-01

Prions are units of propagation of an altered state of a protein or proteins; prions can propagate from organism to organism, through cooption of other protein copies. Prions contain no necessary nucleic acids, and are important both as both pathogenic agents, and as a potential force in epigenetic phenomena. The original prions were derived from a misfolded form of the mammalian Prion Protein PrP. Infection by these prions causes neurodegenerative diseases. Other prions cause non-Mendelian inheritance in budding yeast, and sometimes act as diseases of yeast. We report the bioinformatic construction of the PrionHome, a database of >2000 prion-related sequences. The data was collated from various public and private resources and filtered for redundancy. The data was then processed according to a transparent classification system of prionogenic sequences (i.e., sequences that can make prions), prionoids (i.e., proteins that propagate like prions between individual cells), and other prion-related phenomena. There are eight PrionHome classifications for sequences. The first four classifications are derived from experimental observations: prionogenic sequences, prionoids, other prion-related phenomena, and prion interactors. The second four classifications are derived from sequence analysis: orthologs, paralogs, pseudogenes, and candidate-prionogenic sequences. Database entries list: supporting information for PrionHome classifications, prion-determinant areas (where relevant), and disordered and compositionally-biased regions. Also included are literature references for the PrionHome classifications, transcripts and genomic coordinates, and structural data (including comparative models made for the PrionHome from manually curated alignments). We provide database usage examples for both vertebrate and fungal prion contexts. Using the database data, we have performed a detailed analysis of the compositional biases in known budding-yeast prionogenic sequences, showing that the only abundant bias pattern is for asparagine bias with subsidiary serine bias. We anticipate that this database will be a useful experimental aid and reference resource. It is freely available at: http://libaio.biol.mcgill.ca/prion.

PrionHome: A Database of Prions and Other Sequences Relevant to Prion Phenomena

PubMed Central

Harbi, Djamel; Parthiban, Marimuthu; Gendoo, Deena M. A.; Ehsani, Sepehr; Kumar, Manish; Schmitt-Ulms, Gerold; Sowdhamini, Ramanathan; Harrison, Paul M.

2012-01-01

Prions are units of propagation of an altered state of a protein or proteins; prions can propagate from organism to organism, through cooption of other protein copies. Prions contain no necessary nucleic acids, and are important both as both pathogenic agents, and as a potential force in epigenetic phenomena. The original prions were derived from a misfolded form of the mammalian Prion Protein PrP. Infection by these prions causes neurodegenerative diseases. Other prions cause non-Mendelian inheritance in budding yeast, and sometimes act as diseases of yeast. We report the bioinformatic construction of the PrionHome, a database of >2000 prion-related sequences. The data was collated from various public and private resources and filtered for redundancy. The data was then processed according to a transparent classification system of prionogenic sequences (i.e., sequences that can make prions), prionoids (i.e., proteins that propagate like prions between individual cells), and other prion-related phenomena. There are eight PrionHome classifications for sequences. The first four classifications are derived from experimental observations: prionogenic sequences, prionoids, other prion-related phenomena, and prion interactors. The second four classifications are derived from sequence analysis: orthologs, paralogs, pseudogenes, and candidate-prionogenic sequences. Database entries list: supporting information for PrionHome classifications, prion-determinant areas (where relevant), and disordered and compositionally-biased regions. Also included are literature references for the PrionHome classifications, transcripts and genomic coordinates, and structural data (including comparative models made for the PrionHome from manually curated alignments). We provide database usage examples for both vertebrate and fungal prion contexts. Using the database data, we have performed a detailed analysis of the compositional biases in known budding-yeast prionogenic sequences, showing that the only abundant bias pattern is for asparagine bias with subsidiary serine bias. We anticipate that this database will be a useful experimental aid and reference resource. It is freely available at: http://libaio.biol.mcgill.ca/prion. PMID:22363733

Application of the International Classification of Functioning, Disability and Health system to symptoms of the Duchenne and Becker muscular dystrophies.

PubMed

Conway, Kristin M; Ciafaloni, Emma; Matthews, Dennis; Westfield, Chris; James, Kathy; Paramsothy, Pangaja; Romitti, Paul A

2018-07-01

Duchenne and Becker muscular dystrophies, collectively referred to as dystrophinopathies, are X-linked recessive diseases that affect dystrophin production resulting in compromised muscle function across multiple systems. The International Classification of Functioning, Disability and Health provides a systematic classification scheme from which body functions affected by a dystrophinopathy can be identified and used to examine functional health. The infrastructure of the Muscular Dystrophy Surveillance, Tracking, and Research Network was used to identify commonly affected body functions and link selected functions to clinical surveillance data collected through medical record abstraction. Seventy-one (24 second-, 41 third- and 7 fourth-level) body function categories were selected via clinician review and consensus. Of these, 15 of 24 retained second-level categories were linked to data elements from the Muscular Dystrophy Surveillance, Tracking, and Research Network surveillance database. Our findings support continued development of a core set of body functions from the International Classification of Functioning, Disability and Health system that are representative of disease progression in dystrophinopathies and the incorporation of these functions in standardized evaluations of functional health and implementation of individualized rehabilitation care plans. Implications for Rehabilitation Duchenne and Becker muscular dystrophies, collectively referred to as dystrophinopathies, are X-linked recessive disorders that affect the production of dystrophin resulting in compromised muscle function across multiple systems. The severity and progressive nature of dystrophinopathies can have considerable impact on a patient's participation in activities across multiple life domains. Our findings support continued development of an International Classification of Functioning, Disability and Health core set for childhood-onset dystrophinopathies. A standardized dystrophinopathy International Classification of Functioning, Disability and Health documentation form can be used as a screening tool by rehabilitation professionals and for patient goal setting when developing rehabilitation plans. Patient reports of perceived functional health should be incorporated into the rehabilitation plan and therapeutic progress monitored by a standardized form.

Effects of eye artifact removal methods on single trial P300 detection, a comparative study.

PubMed

Ghaderi, Foad; Kim, Su Kyoung; Kirchner, Elsa Andrea

2014-01-15

Electroencephalographic signals are commonly contaminated by eye artifacts, even if recorded under controlled conditions. The objective of this work was to quantitatively compare standard artifact removal methods (regression, filtered regression, Infomax, and second order blind identification (SOBI)) and two artifact identification approaches for independent component analysis (ICA) methods, i.e. ADJUST and correlation. To this end, eye artifacts were removed and the cleaned datasets were used for single trial classification of P300 (a type of event related potentials elicited using the oddball paradigm). Statistical analysis of the results confirms that the combination of Infomax and ADJUST provides a relatively better performance (0.6% improvement on average of all subject) while the combination of SOBI and correlation performs the worst. Low-pass filtering the data at lower cutoffs (here 4 Hz) can also improve the classification accuracy. Without requiring any artifact reference channel, the combination of Infomax and ADJUST improves the classification performance more than the other methods for both examined filtering cutoffs, i.e., 4 Hz and 25 Hz. Copyright © 2013 Elsevier B.V. All rights reserved.

Evaluation of SLAR and simulated thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M.; Dean, M. E.; Knowlton, D. J.; Latty, R. S.

1982-01-01

Kershaw County, South Carolina was selected as the study site for analyzing simulated thematic mapper MSS data and dual-polarized X-band synthetic aperture radar (SAR) data. The impact of the improved spatial and spectral characteristics of the LANDSAT D thematic mapper data on computer aided analysis for forest cover type mapping was examined as well as the value of synthetic aperture radar data for differentiating forest and other cover types. The utility of pattern recognition techniques for analyzing SAR data was assessed. Topics covered include: (1) collection and of TMS and reference data; (2) reformatting, geometric and radiometric rectification, and spatial resolution degradation of TMS data; (3) development of training statistics and test data sets; (4) evaluation of different numbers and combinations of wavelength bands on classification performance; (5) comparison among three classification algorithms; and (6) the effectiveness of the principal component transformation in data analysis. The collection, digitization, reformatting, and geometric adjustment of SAR data are also discussed. Image interpretation results and classification results are presented.

Automated color classification of urine dipstick image in urine examination

NASA Astrophysics Data System (ADS)

Rahmat, R. F.; Royananda; Muchtar, M. A.; Taqiuddin, R.; Adnan, S.; Anugrahwaty, R.; Budiarto, R.

2018-03-01

Urine examination using urine dipstick has long been used to determine the health status of a person. The economical and convenient use of urine dipstick is one of the reasons urine dipstick is still used to check people health status. The real-life implementation of urine dipstick is done manually, in general, that is by comparing it with the reference color visually. This resulted perception differences in the color reading of the examination results. In this research, authors used a scanner to obtain the urine dipstick color image. The use of scanner can be one of the solutions in reading the result of urine dipstick because the light produced is consistent. A method is required to overcome the problems of urine dipstick color matching and the test reference color that have been conducted manually. The method proposed by authors is Euclidean Distance, Otsu along with RGB color feature extraction method to match the colors on the urine dipstick with the standard reference color of urine examination. The result shows that the proposed approach was able to classify the colors on a urine dipstick with an accuracy of 95.45%. The accuracy of color classification on urine dipstick against the standard reference color is influenced by the level of scanner resolution used, the higher the scanner resolution level, the higher the accuracy.

Bacterial reference genes for gene expression studies by RT-qPCR: survey and analysis.

PubMed

Rocha, Danilo J P; Santos, Carolina S; Pacheco, Luis G C

2015-09-01

The appropriate choice of reference genes is essential for accurate normalization of gene expression data obtained by the method of reverse transcription quantitative real-time PCR (RT-qPCR). In 2009, a guideline called the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) highlighted the importance of the selection and validation of more than one suitable reference gene for obtaining reliable RT-qPCR results. Herein, we searched the recent literature in order to identify the bacterial reference genes that have been most commonly validated in gene expression studies by RT-qPCR (in the first 5 years following publication of the MIQE guidelines). Through a combination of different search parameters with the text mining tool MedlineRanker, we identified 145 unique bacterial genes that were recently tested as candidate reference genes. Of these, 45 genes were experimentally validated and, in most of the cases, their expression stabilities were verified using the software tools geNorm and NormFinder. It is noteworthy that only 10 of these reference genes had been validated in two or more of the studies evaluated. An enrichment analysis using Gene Ontology classifications demonstrated that genes belonging to the functional categories of DNA Replication (GO: 0006260) and Transcription (GO: 0006351) rendered a proportionally higher number of validated reference genes. Three genes in the former functional class were also among the top five most stable genes identified through an analysis of gene expression data obtained from the Pathosystems Resource Integration Center. These results may provide a guideline for the initial selection of candidate reference genes for RT-qPCR studies in several different bacterial species.

Object Based Image Analysis Combining High Spatial Resolution Imagery and Laser Point Clouds for Urban Land Cover

NASA Astrophysics Data System (ADS)

Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

2016-06-01

With the rapid developments of the sensor technology, high spatial resolution imagery and airborne Lidar point clouds can be captured nowadays, which make classification, extraction, evaluation and analysis of a broad range of object features available. High resolution imagery, Lidar dataset and parcel map can be widely used for classification as information carriers. Therefore, refinement of objects classification is made possible for the urban land cover. The paper presents an approach to object based image analysis (OBIA) combing high spatial resolution imagery and airborne Lidar point clouds. The advanced workflow for urban land cover is designed with four components. Firstly, colour-infrared TrueOrtho photo and laser point clouds were pre-processed to derive the parcel map of water bodies and nDSM respectively. Secondly, image objects are created via multi-resolution image segmentation integrating scale parameter, the colour and shape properties with compactness criterion. Image can be subdivided into separate object regions. Thirdly, image objects classification is performed on the basis of segmentation and a rule set of knowledge decision tree. These objects imagery are classified into six classes such as water bodies, low vegetation/grass, tree, low building, high building and road. Finally, in order to assess the validity of the classification results for six classes, accuracy assessment is performed through comparing randomly distributed reference points of TrueOrtho imagery with the classification results, forming the confusion matrix and calculating overall accuracy and Kappa coefficient. The study area focuses on test site Vaihingen/Enz and a patch of test datasets comes from the benchmark of ISPRS WG III/4 test project. The classification results show higher overall accuracy for most types of urban land cover. Overall accuracy is 89.5% and Kappa coefficient equals to 0.865. The OBIA approach provides an effective and convenient way to combine high resolution imagery and Lidar ancillary data for classification of urban land cover.

An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs

NASA Astrophysics Data System (ADS)

Haaf, Ezra; Barthel, Roland

2016-04-01

When assessing hydrogeological conditions at the regional scale, the analyst is often confronted with uncertainty of structures, inputs and processes while having to base inference on scarce and patchy data. Haaf and Barthel (2015) proposed a concept for handling this predicament by developing a groundwater systems classification framework, where information is transferred from similar, but well-explored and better understood to poorly described systems. The concept is based on the central hypothesis that similar systems react similarly to the same inputs and vice versa. It is conceptually related to PUB (Prediction in ungauged basins) where organization of systems and processes by quantitative methods is intended and used to improve understanding and prediction. Furthermore, using the framework it is expected that regional conceptual and numerical models can be checked or enriched by ensemble generated data from neighborhood-based estimators. In a first step, groundwater hydrographs from a large dataset in Southern Germany are compared in an effort to identify structural similarity in groundwater dynamics. A number of approaches to group hydrographs, mostly based on a similarity measure - which have previously only been used in local-scale studies, can be found in the literature. These are tested alongside different global feature extraction techniques. The resulting classifications are then compared to a visual "expert assessment"-based classification which serves as a reference. A ranking of the classification methods is carried out and differences shown. Selected groups from the classifications are related to geological descriptors. Here we present the most promising results from a comparison of classifications based on series correlation, different series distances and series features, such as the coefficients of the discrete Fourier transform and the intrinsic mode functions of empirical mode decomposition. Additionally, we show examples of classes corresponding to geological descriptors. Haaf, E., Barthel, R., 2015. Methods for assessing hydrogeological similarity and for classification of groundwater systems on the regional scale, EGU General Assembly 2015, Vienna, Austria.

A comparison of the accuracy of pixel based and object based classifications of integrated optical and LiDAR data

NASA Astrophysics Data System (ADS)

Gajda, Agnieszka; Wójtowicz-Nowakowska, Anna

2013-04-01

A comparison of the accuracy of pixel based and object based classifications of integrated optical and LiDAR data Land cover maps are generally produced on the basis of high resolution imagery. Recently, LiDAR (Light Detection and Ranging) data have been brought into use in diverse applications including land cover mapping. In this study we attempted to assess the accuracy of land cover classification using both high resolution aerial imagery and LiDAR data (airborne laser scanning, ALS), testing two classification approaches: a pixel-based classification and object-oriented image analysis (OBIA). The study was conducted on three test areas (3 km2 each) in the administrative area of Kraków, Poland, along the course of the Vistula River. They represent three different dominating land cover types of the Vistula River valley. Test site 1 had a semi-natural vegetation, with riparian forests and shrubs, test site 2 represented a densely built-up area, and test site 3 was an industrial site. Point clouds from ALS and ortophotomaps were both captured in November 2007. Point cloud density was on average 16 pt/m2 and it contained additional information about intensity and encoded RGB values. Ortophotomaps had a spatial resolution of 10 cm. From point clouds two raster maps were generated: intensity (1) and (2) normalised Digital Surface Model (nDSM), both with the spatial resolution of 50 cm. To classify the aerial data, a supervised classification approach was selected. Pixel based classification was carried out in ERDAS Imagine software. Ortophotomaps and intensity and nDSM rasters were used in classification. 15 homogenous training areas representing each cover class were chosen. Classified pixels were clumped to avoid salt and pepper effect. Object oriented image object classification was carried out in eCognition software, which implements both the optical and ALS data. Elevation layers (intensity, firs/last reflection, etc.) were used at segmentation stage due to proper wages usage. Thus a more precise and unambiguous boundaries of segments (objects) were received. As a results of the classification 5 classes of land cover (buildings, water, high and low vegetation and others) were extracted. Both pixel-based image analysis and OBIA were conducted with a minimum mapping unit of 10m2. Results were validated on the basis on manual classification and random points (80 per test area), reference data set was manually interpreted using ortophotomaps and expert knowledge of the test site areas.

The Transporter Classification Database: recent advances.

PubMed

Saier, Milton H; Yen, Ming Ren; Noto, Keith; Tamang, Dorjee G; Elkan, Charles

2009-01-01

The Transporter Classification Database (TCDB), freely accessible at http://www.tcdb.org, is a relational database containing sequence, structural, functional and evolutionary information about transport systems from a variety of living organisms, based on the International Union of Biochemistry and Molecular Biology-approved transporter classification (TC) system. It is a curated repository for factual information compiled largely from published references. It uses a functional/phylogenetic system of classification, and currently encompasses about 5000 representative transporters and putative transporters in more than 500 families. We here describe novel software designed to support and extend the usefulness of TCDB. Our recent efforts render it more user friendly, incorporate machine learning to input novel data in a semiautomatic fashion, and allow analyses that are more accurate and less time consuming. The availability of these tools has resulted in recognition of distant phylogenetic relationships and tremendous expansion of the information available to TCDB users.

A scope classification of data quality requirements for food composition data.

PubMed

Presser, Karl; Hinterberger, Hans; Weber, David; Norrie, Moira

2016-02-15

Data quality is an important issue when managing food composition data since the usage of the data can have a significant influence on policy making and further research. Although several frameworks for data quality have been proposed, general tools and measures are still lacking. As a first step in this direction, we investigated data quality requirements for an information system to manage food composition data, called FoodCASE. The objective of our investigation was to find out if different requirements have different impacts on the intrinsic data quality that must be regarded during data quality assessment and how these impacts can be described. We refer to the resulting classification with its categories as the scope classification of data quality requirements. As proof of feasibility, the scope classification has been implemented in the FoodCASE system. Copyright © 2015 Elsevier Ltd. All rights reserved.

Alexnet Feature Extraction and Multi-Kernel Learning for Objectoriented Classification

NASA Astrophysics Data System (ADS)

Ding, L.; Li, H.; Hu, C.; Zhang, W.; Wang, S.

2018-04-01

In view of the fact that the deep convolutional neural network has stronger ability of feature learning and feature expression, an exploratory research is done on feature extraction and classification for high resolution remote sensing images. Taking the Google image with 0.3 meter spatial resolution in Ludian area of Yunnan Province as an example, the image segmentation object was taken as the basic unit, and the pre-trained AlexNet deep convolution neural network model was used for feature extraction. And the spectral features, AlexNet features and GLCM texture features are combined with multi-kernel learning and SVM classifier, finally the classification results were compared and analyzed. The results show that the deep convolution neural network can extract more accurate remote sensing image features, and significantly improve the overall accuracy of classification, and provide a reference value for earthquake disaster investigation and remote sensing disaster evaluation.

Stygoregions – a promising approach to a bioregional classification of groundwater systems

PubMed Central

Stein, Heide; Griebler, Christian; Berkhoff, Sven; Matzke, Dirk; Fuchs, Andreas; Hahn, Hans Jürgen

2012-01-01

Linked to diverse biological processes, groundwater ecosystems deliver essential services to mankind, the most important of which is the provision of drinking water. In contrast to surface waters, ecological aspects of groundwater systems are ignored by the current European Union and national legislation. Groundwater management and protection measures refer exclusively to its good physicochemical and quantitative status. Current initiatives in developing ecologically sound integrative assessment schemes by taking groundwater fauna into account depend on the initial classification of subsurface bioregions. In a large scale survey, the regional and biogeographical distribution patterns of groundwater dwelling invertebrates were examined for many parts of Germany. Following an exploratory approach, our results underline that the distribution patterns of invertebrates in groundwater are not in accordance with any existing bioregional classification system established for surface habitats. In consequence, we propose to develope a new classification scheme for groundwater ecosystems based on stygoregions. PMID:22993698

Robust tissue classification for reproducible wound assessment in telemedicine environments

NASA Astrophysics Data System (ADS)

Wannous, Hazem; Treuillet, Sylvie; Lucas, Yves

2010-04-01

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

Classification of comorbidity in trauma: the reliability of pre-injury ASA physical status classification.

PubMed

Ringdal, Kjetil G; Skaga, Nils Oddvar; Steen, Petter Andreas; Hestnes, Morten; Laake, Petter; Jones, J Mary; Lossius, Hans Morten

2013-01-01

Pre-injury comorbidities can influence the outcomes of severely injured patients. Pre-injury comorbidity status, graded according to the American Society of Anesthesiologists Physical Status (ASA-PS) classification system, is an independent predictor of survival in trauma patients and is recommended as a comorbidity score in the Utstein Trauma Template for Uniform Reporting of Data. Little is known about the reliability of pre-injury ASA-PS scores. The objective of this study was to examine whether the pre-injury ASA-PS system was a reliable scale for grading comorbidity in trauma patients. Nineteen Norwegian trauma registry coders were invited to participate in a reliability study in which 50 real but anonymised patient medical records were distributed. Reliability was analysed using quadratic weighted kappa (κ(w)) analysis with 95% CI as the primary outcome measure and unweighted kappa (κ) analysis, which included unknown values, as a secondary outcome measure. Fifteen of the invitees responded to the invitation, and ten participated. We found moderate (κ(w)=0.77 [95% CI: 0.64-0.87]) to substantial (κ(w)=0.95 [95% CI: 0.89-0.99]) rater-against-reference standard reliability using κ(w) and fair (κ=0.46 [95% CI: 0.29-0.64]) to substantial (κ=0.83 [95% CI: 0.68-0.94]) reliability using κ. The inter-rater reliability ranged from moderate (κ(w)=0.66 [95% CI: 0.45-0.81]) to substantial (κ(w)=0.96 [95% CI: 0.88-1.00]) for κ(w) and from slight (κ=0.36 [95% CI: 0.21-0.54]) to moderate (κ=0.75 [95% CI: 0.62-0.89]) for κ. The rater-against-reference standard reliability varied from moderate to substantial for the primary outcome measure and from fair to substantial for the secondary outcome measure. The study findings indicate that the pre-injury ASA-PS scale is a reliable score for classifying comorbidity in trauma patients. Copyright © 2012 Elsevier Ltd. All rights reserved.

Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

PubMed

Li, Zhixi; He, Yifan; Keel, Stuart; Meng, Wei; Chang, Robert T; He, Mingguang

2018-03-02

To assess the performance of a deep learning algorithm for detecting referable glaucomatous optic neuropathy (GON) based on color fundus photographs. A deep learning system for the classification of GON was developed for automated classification of GON on color fundus photographs. We retrospectively included 48 116 fundus photographs for the development and validation of a deep learning algorithm. This study recruited 21 trained ophthalmologists to classify the photographs. Referable GON was defined as vertical cup-to-disc ratio of 0.7 or more and other typical changes of GON. The reference standard was made until 3 graders achieved agreement. A separate validation dataset of 8000 fully gradable fundus photographs was used to assess the performance of this algorithm. The area under receiver operator characteristic curve (AUC) with sensitivity and specificity was applied to evaluate the efficacy of the deep learning algorithm detecting referable GON. In the validation dataset, this deep learning system achieved an AUC of 0.986 with sensitivity of 95.6% and specificity of 92.0%. The most common reasons for false-negative grading (n = 87) were GON with coexisting eye conditions (n = 44 [50.6%]), including pathologic or high myopia (n = 37 [42.6%]), diabetic retinopathy (n = 4 [4.6%]), and age-related macular degeneration (n = 3 [3.4%]). The leading reason for false-positive results (n = 480) was having other eye conditions (n = 458 [95.4%]), mainly including physiologic cupping (n = 267 [55.6%]). Misclassification as false-positive results amidst a normal-appearing fundus occurred in only 22 eyes (4.6%). A deep learning system can detect referable GON with high sensitivity and specificity. Coexistence of high or pathologic myopia is the most common cause resulting in false-negative results. Physiologic cupping and pathologic myopia were the most common reasons for false-positive results. Copyright © 2018 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Decision Tree Repository and Rule Set Based Mingjiang River Estuarine Wetlands Classifaction

NASA Astrophysics Data System (ADS)

Zhang, W.; Li, X.; Xiao, W.

2018-05-01

The increasing urbanization and industrialization have led to wetland losses in estuarine area of Mingjiang River over past three decades. There has been increasing attention given to produce wetland inventories using remote sensing and GIS technology. Due to inconsistency training site and training sample, traditionally pixel-based image classification methods can't achieve a comparable result within different organizations. Meanwhile, object-oriented image classification technique shows grate potential to solve this problem and Landsat moderate resolution remote sensing images are widely used to fulfill this requirement. Firstly, the standardized atmospheric correct, spectrally high fidelity texture feature enhancement was conducted before implementing the object-oriented wetland classification method in eCognition. Secondly, we performed the multi-scale segmentation procedure, taking the scale, hue, shape, compactness and smoothness of the image into account to get the appropriate parameters, using the top and down region merge algorithm from single pixel level, the optimal texture segmentation scale for different types of features is confirmed. Then, the segmented object is used as the classification unit to calculate the spectral information such as Mean value, Maximum value, Minimum value, Brightness value and the Normalized value. The Area, length, Tightness and the Shape rule of the image object Spatial features and texture features such as Mean, Variance and Entropy of image objects are used as classification features of training samples. Based on the reference images and the sampling points of on-the-spot investigation, typical training samples are selected uniformly and randomly for each type of ground objects. The spectral, texture and spatial characteristics of each type of feature in each feature layer corresponding to the range of values are used to create the decision tree repository. Finally, with the help of high resolution reference images, the random sampling method is used to conduct the field investigation, achieve an overall accuracy of 90.31 %, and the Kappa coefficient is 0.88. The classification method based on decision tree threshold values and rule set developed by the repository, outperforms the results obtained from the traditional methodology. Our decision tree repository and rule set based object-oriented classification technique was an effective method for producing comparable and consistency wetlands data set.

Study on Classification Accuracy Inspection of Land Cover Data Aided by Automatic Image Change Detection Technology

NASA Astrophysics Data System (ADS)

Xie, W.-J.; Zhang, L.; Chen, H.-P.; Zhou, J.; Mao, W.-J.

2018-04-01

The purpose of carrying out national geographic conditions monitoring is to obtain information of surface changes caused by human social and economic activities, so that the geographic information can be used to offer better services for the government, enterprise and public. Land cover data contains detailed geographic conditions information, thus has been listed as one of the important achievements in the national geographic conditions monitoring project. At present, the main issue of the production of the land cover data is about how to improve the classification accuracy. For the land cover data quality inspection and acceptance, classification accuracy is also an important check point. So far, the classification accuracy inspection is mainly based on human-computer interaction or manual inspection in the project, which are time consuming and laborious. By harnessing the automatic high-resolution remote sensing image change detection technology based on the ERDAS IMAGINE platform, this paper carried out the classification accuracy inspection test of land cover data in the project, and presented a corresponding technical route, which includes data pre-processing, change detection, result output and information extraction. The result of the quality inspection test shows the effectiveness of the technical route, which can meet the inspection needs for the two typical errors, that is, missing and incorrect update error, and effectively reduces the work intensity of human-computer interaction inspection for quality inspectors, and also provides a technical reference for the data production and quality control of the land cover data.

Mapping Mangrove Density from Rapideye Data in Central America

NASA Astrophysics Data System (ADS)

Son, Nguyen-Thanh; Chen, Chi-Farn; Chen, Cheng-Ru

2017-06-01

Mangrove forests provide a wide range of socioeconomic and ecological services for coastal communities. Extensive aquaculture development of mangrove waters in many developing countries has constantly ignored services of mangrove ecosystems, leading to unintended environmental consequences. Monitoring the current status and distribution of mangrove forests is deemed important for evaluating forest management strategies. This study aims to delineate the density distribution of mangrove forests in the Gulf of Fonseca, Central America with Rapideye data using the support vector machines (SVM). The data collected in 2012 for density classification of mangrove forests were processed based on four different band combination schemes: scheme-1 (bands 1-3, 5 excluding the red-edge band 4), scheme-2 (bands 1-5), scheme-3 (bands 1-3, 5 incorporating with the normalized difference vegetation index, NDVI), and scheme-4 (bands 1-3, 5 incorporating with the normalized difference red-edge index, NDRI). We also hypothesized if the obvious contribution of Rapideye red-edge band could improve the classification results. Three main steps of data processing were employed: (1), data pre-processing, (2) image classification, and (3) accuracy assessment to evaluate the contribution of red-edge band in terms of the accuracy of classification results across these four schemes. The classification maps compared with the ground reference data indicated the slightly higher accuracy level observed for schemes 2 and 4. The overall accuracies and Kappa coefficients were 97% and 0.95 for scheme-2 and 96.9% and 0.95 for scheme-4, respectively.

Biowaiver extension potential and IVIVC for BCS Class II drugs by formulation design: Case study for cyclosporine self-microemulsifying formulation.

PubMed

Yang, Su-Geun

2010-11-01

The objective of this work was to suggest the biowaiver potential of biopharmaceutical classification system (BCS) Class II drugs in self-microemulsifying drug delivery systems (SMEDDS) which are known to increase the solubility, dissolution and oral absorption of water-insoluble drugs. Cyclosporine was selected as a representative BCS Class II drug. New generic candidate of cyclosporine SMEDDS (test) was applied for the study with brand SMEDDS (reference I) and cyclosporine self-emulsifying drug delivery systems (SEDDS, reference II). Solubility and dissolution of cyclosporine from SMEDDS were critically enhanced, which were the similar behaviors with BCS class I drug. The test showed the identical dissolution rate and the equivalent bioavailability (0.34, 0.42 and 0.68 of p values for AUC₀(→)₂₄(h), C(max) and T(max), respectively) with the reference I. Based on the results, level A in vitro-in vivo correlation (IVIVC) was established from these two SMEDDS formulations. This study serves as a good example for speculating the biowaiver extension potential of BCS Class II drugs specifically in solubilizing formulation such as SMEDDS.

An interactive system for computer-aided diagnosis of breast masses.

PubMed

Wang, Xingwei; Li, Lihua; Liu, Wei; Xu, Weidong; Lederman, Dror; Zheng, Bin

2012-10-01

Although mammography is the only clinically accepted imaging modality for screening the general population to detect breast cancer, interpreting mammograms is difficult with lower sensitivity and specificity. To provide radiologists "a visual aid" in interpreting mammograms, we developed and tested an interactive system for computer-aided detection and diagnosis (CAD) of mass-like cancers. Using this system, an observer can view CAD-cued mass regions depicted on one image and then query any suspicious regions (either cued or not cued by CAD). CAD scheme automatically segments the suspicious region or accepts manually defined region and computes a set of image features. Using content-based image retrieval (CBIR) algorithm, CAD searches for a set of reference images depicting "abnormalities" similar to the queried region. Based on image retrieval results and a decision algorithm, a classification score is assigned to the queried region. In this study, a reference database with 1,800 malignant mass regions and 1,800 benign and CAD-generated false-positive regions was used. A modified CBIR algorithm with a new function of stretching the attributes in the multi-dimensional space and decision scheme was optimized using a genetic algorithm. Using a leave-one-out testing method to classify suspicious mass regions, we compared the classification performance using two CBIR algorithms with either equally weighted or optimally stretched attributes. Using the modified CBIR algorithm, the area under receiver operating characteristic curve was significantly increased from 0.865 ± 0.006 to 0.897 ± 0.005 (p < 0.001). This study demonstrated the feasibility of developing an interactive CAD system with a large reference database and achieving improved performance.

Devices for the Production of Reference Gas Mixtures.

PubMed

Fijało, Cyprian; Dymerski, Tomasz; Gębicki, Jacek; Namieśnik, Jacek

2016-09-02

For many years there has been growing demand for gaseous reference materials, which is connected with development in many fields of science and technology. As a result, new methodological and instrumental solutions appear that can be used for this purpose. Appropriate quality assurance/quality control (QA/QC) must be used to make sure that measurement data are a reliable source of information. Reference materials are a significant element of such systems. In the case of gas samples, such materials are generally called reference gas mixtures. This article presents the application and classification of reference gas mixtures, which are a specific type of reference materials, and the methods for obtaining them are described. Construction solutions of devices for the production of reference gas mixtures are detailed, and a description of a prototype device for dynamic production of reference gas mixtures containing aroma compounds is presented.

Spatio-spectral classification of hyperspectral images for brain cancer detection during surgical operations.

PubMed

Fabelo, Himar; Ortega, Samuel; Ravi, Daniele; Kiran, B Ravi; Sosa, Coralia; Bulters, Diederik; Callicó, Gustavo M; Bulstrode, Harry; Szolna, Adam; Piñeiro, Juan F; Kabwama, Silvester; Madroñal, Daniel; Lazcano, Raquel; J-O'Shanahan, Aruma; Bisshopp, Sara; Hernández, María; Báez, Abelardo; Yang, Guang-Zhong; Stanciulescu, Bogdan; Salvador, Rubén; Juárez, Eduardo; Sarmiento, Roberto

2018-01-01

Surgery for brain cancer is a major problem in neurosurgery. The diffuse infiltration into the surrounding normal brain by these tumors makes their accurate identification by the naked eye difficult. Since surgery is the common treatment for brain cancer, an accurate radical resection of the tumor leads to improved survival rates for patients. However, the identification of the tumor boundaries during surgery is challenging. Hyperspectral imaging is a non-contact, non-ionizing and non-invasive technique suitable for medical diagnosis. This study presents the development of a novel classification method taking into account the spatial and spectral characteristics of the hyperspectral images to help neurosurgeons to accurately determine the tumor boundaries in surgical-time during the resection, avoiding excessive excision of normal tissue or unintentionally leaving residual tumor. The algorithm proposed in this study to approach an efficient solution consists of a hybrid framework that combines both supervised and unsupervised machine learning methods. Firstly, a supervised pixel-wise classification using a Support Vector Machine classifier is performed. The generated classification map is spatially homogenized using a one-band representation of the HS cube, employing the Fixed Reference t-Stochastic Neighbors Embedding dimensional reduction algorithm, and performing a K-Nearest Neighbors filtering. The information generated by the supervised stage is combined with a segmentation map obtained via unsupervised clustering employing a Hierarchical K-Means algorithm. The fusion is performed using a majority voting approach that associates each cluster with a certain class. To evaluate the proposed approach, five hyperspectral images of surface of the brain affected by glioblastoma tumor in vivo from five different patients have been used. The final classification maps obtained have been analyzed and validated by specialists. These preliminary results are promising, obtaining an accurate delineation of the tumor area.

Spatio-spectral classification of hyperspectral images for brain cancer detection during surgical operations

PubMed Central

Kabwama, Silvester; Madroñal, Daniel; Lazcano, Raquel; J-O’Shanahan, Aruma; Bisshopp, Sara; Hernández, María; Báez, Abelardo; Yang, Guang-Zhong; Stanciulescu, Bogdan; Salvador, Rubén; Juárez, Eduardo; Sarmiento, Roberto

2018-01-01

Surgery for brain cancer is a major problem in neurosurgery. The diffuse infiltration into the surrounding normal brain by these tumors makes their accurate identification by the naked eye difficult. Since surgery is the common treatment for brain cancer, an accurate radical resection of the tumor leads to improved survival rates for patients. However, the identification of the tumor boundaries during surgery is challenging. Hyperspectral imaging is a non-contact, non-ionizing and non-invasive technique suitable for medical diagnosis. This study presents the development of a novel classification method taking into account the spatial and spectral characteristics of the hyperspectral images to help neurosurgeons to accurately determine the tumor boundaries in surgical-time during the resection, avoiding excessive excision of normal tissue or unintentionally leaving residual tumor. The algorithm proposed in this study to approach an efficient solution consists of a hybrid framework that combines both supervised and unsupervised machine learning methods. Firstly, a supervised pixel-wise classification using a Support Vector Machine classifier is performed. The generated classification map is spatially homogenized using a one-band representation of the HS cube, employing the Fixed Reference t-Stochastic Neighbors Embedding dimensional reduction algorithm, and performing a K-Nearest Neighbors filtering. The information generated by the supervised stage is combined with a segmentation map obtained via unsupervised clustering employing a Hierarchical K-Means algorithm. The fusion is performed using a majority voting approach that associates each cluster with a certain class. To evaluate the proposed approach, five hyperspectral images of surface of the brain affected by glioblastoma tumor in vivo from five different patients have been used. The final classification maps obtained have been analyzed and validated by specialists. These preliminary results are promising, obtaining an accurate delineation of the tumor area. PMID:29554126

A multitemporal (1979-2009) land-use/land-cover dataset of the binational Santa Cruz Watershed

USGS Publications Warehouse

2011-01-01

Trends derived from multitemporal land-cover data can be used to make informed land management decisions and to help managers model future change scenarios. We developed a multitemporal land-use/land-cover dataset for the binational Santa Cruz watershed of southern Arizona, United States, and northern Sonora, Mexico by creating a series of land-cover maps at decadal intervals (1979, 1989, 1999, and 2009) using Landsat Multispectral Scanner and Thematic Mapper data and a classification and regression tree classifier. The classification model exploited phenological changes of different land-cover spectral signatures through the use of biseasonal imagery collected during the (dry) early summer and (wet) late summer following rains from the North American monsoon. Landsat images were corrected to remove atmospheric influences, and the data were converted from raw digital numbers to surface reflectance values. The 14-class land-cover classification scheme is based on the 2001 National Land Cover Database with a focus on "Developed" land-use classes and riverine "Forest" and "Wetlands" cover classes required for specific watershed models. The classification procedure included the creation of several image-derived and topographic variables, including digital elevation model derivatives, image variance, and multitemporal Kauth-Thomas transformations. The accuracy of the land-cover maps was assessed using a random-stratified sampling design, reference aerial photography, and digital imagery. This showed high accuracy results, with kappa values (the statistical measure of agreement between map and reference data) ranging from 0.80 to 0.85.

Systematic review of autosomal recessive ataxias and proposal for a classification.

PubMed

Beaudin, Marie; Klein, Christopher J; Rouleau, Guy A; Dupré, Nicolas

2017-01-01

The classification of autosomal recessive ataxias represents a significant challenge because of high genetic heterogeneity and complex phenotypes. We conducted a comprehensive systematic review of the literature to examine all recessive ataxias in order to propose a new classification and properly circumscribe this field as new technologies are emerging for comprehensive targeted gene testing. We searched Pubmed and Embase to identify original articles on recessive forms of ataxia in humans for which a causative gene had been identified. Reference lists and public databases, including OMIM and GeneReviews, were also reviewed. We evaluated the clinical descriptions to determine if ataxia was a core feature of the phenotype and assessed the available evidence on the genotype-phenotype association. Included disorders were classified as primary recessive ataxias, as other complex movement or multisystem disorders with prominent ataxia, or as disorders that may occasionally present with ataxia. After removal of duplicates, 2354 references were reviewed and assessed for inclusion. A total of 130 articles were completely reviewed and included in this qualitative analysis. The proposed new list of autosomal recessive ataxias includes 45 gene-defined disorders for which ataxia is a core presenting feature. We propose a clinical algorithm based on the associated symptoms. We present a new classification for autosomal recessive ataxias that brings awareness to their complex phenotypes while providing a unified categorization of this group of disorders. This review should assist in the development of a consensus nomenclature useful in both clinical and research applications.

Teachers' opinion about learning continuum based on student's level of competence and specific pedagogical material in classification topics

NASA Astrophysics Data System (ADS)

Andriani, Aldina Eka; Subali, Bambang

2017-08-01

This research discusses learning continuum development for designing a curriculum. The objective of this study is to gather the opinion of public junior and senior high school teachers about learning continuum based on student's level of competence and specific pedagogical material in classification topics. This research was conducted in Yogyakarta province from October 2016 to January 2017. This research utilizes a descriptive survey method. Respondents in this study consist of 281 science teachers at junior and senior high school in Yogyakarta city and 4 regencies namely Sleman, Bantul, Kulonprogo, and Gunung Kidul. The sample were taken using a census. The collection of data used questionnaire that had been validated from the aspects of construct validity and experts judgements. Data were analyzed using a descriptive analysis technique. The results of the analysis show that the opinions of teachers regarding specific pedagogical material in classification topics of living things at the junior high school taught in grade VII to the ability level of C2 (Understanding). At senior high school level, it is taught in grade X with the ability level C2 (Understanding). Based on these results, it can be concluded that the opinions of teachers still refer to the current syllabus and curriculum so that the teachers do not have pure opinions about the student's competence level in classification topics that should be taught at the level of the grade in accordance with the level of corresponding competency.

Machine-based classification of ADHD and nonADHD participants using time/frequency features of event-related neuroelectric activity.

PubMed

Öztoprak, Hüseyin; Toycan, Mehmet; Alp, Yaşar Kemal; Arıkan, Orhan; Doğutepe, Elvin; Karakaş, Sirel

2017-12-01

Attention-deficit/hyperactivity disorder (ADHD) is the most frequent diagnosis among children who are referred to psychiatry departments. Although ADHD was discovered at the beginning of the 20th century, its diagnosis is still confronted with many problems. A novel classification approach that discriminates ADHD and nonADHD groups over the time-frequency domain features of event-related potential (ERP) recordings that are taken during Stroop task is presented. Time-Frequency Hermite-Atomizer (TFHA) technique is used for the extraction of high resolution time-frequency domain features that are highly localized in time-frequency domain. Based on an extensive investigation, Support Vector Machine-Recursive Feature Elimination (SVM-RFE) was used to obtain the best discriminating features. When the best three features were used, the classification accuracy for the training dataset reached 98%, and the use of five features further improved the accuracy to 99.5%. The accuracy was 100% for the testing dataset. Based on extensive experiments, the delta band emerged as the most contributing frequency band and statistical parameters emerged as the most contributing feature group. The classification performance of this study suggests that TFHA can be employed as an auxiliary component of the diagnostic and prognostic procedures for ADHD. The features obtained in this study can potentially contribute to the neuroelectrical understanding and clinical diagnosis of ADHD. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Classification of cancer cell lines using matrix-assisted laser desorption/ionization time‑of‑flight mass spectrometry and statistical analysis.

PubMed

Serafim, Vlad; Shah, Ajit; Puiu, Maria; Andreescu, Nicoleta; Coricovac, Dorina; Nosyrev, Alexander; Spandidos, Demetrios A; Tsatsakis, Aristides M; Dehelean, Cristina; Pinzaru, Iulia

2017-10-01

Over the past decade, matrix-assisted laser desorption/ionization time‑of‑flight mass spectrometry (MALDI‑TOF MS) has been established as a valuable platform for microbial identification, and it is also frequently applied in biology and clinical studies to identify new markers expressed in pathological conditions. The aim of the present study was to assess the potential of using this approach for the classification of cancer cell lines as a quantifiable method for the proteomic profiling of cellular organelles. Intact protein extracts isolated from different tumor cell lines (human and murine) were analyzed using MALDI‑TOF MS and the obtained mass lists were processed using principle component analysis (PCA) within Bruker Biotyper® software. Furthermore, reference spectra were created for each cell line and were used for classification. Based on the intact protein profiles, we were able to differentiate and classify six cancer cell lines: two murine melanoma (B16‑F0 and B164A5), one human melanoma (A375), two human breast carcinoma (MCF7 and MDA‑MB‑231) and one human liver carcinoma (HepG2). The cell lines were classified according to cancer type and the species they originated from, as well as by their metastatic potential, offering the possibility to differentiate non‑invasive from invasive cells. The obtained results pave the way for developing a broad‑based strategy for the identification and classification of cancer cells.

Advances in Patient Classification for Traditional Chinese Medicine: A Machine Learning Perspective

PubMed Central

Zhao, Changbo; Li, Guo-Zheng; Wang, Chengjun; Niu, Jinling

2015-01-01

As a complementary and alternative medicine in medical field, traditional Chinese medicine (TCM) has drawn great attention in the domestic field and overseas. In practice, TCM provides a quite distinct methodology to patient diagnosis and treatment compared to western medicine (WM). Syndrome (ZHENG or pattern) is differentiated by a set of symptoms and signs examined from an individual by four main diagnostic methods: inspection, auscultation and olfaction, interrogation, and palpation which reflects the pathological and physiological changes of disease occurrence and development. Patient classification is to divide patients into several classes based on different criteria. In this paper, from the machine learning perspective, a survey on patient classification issue will be summarized on three major aspects of TCM: sign classification, syndrome differentiation, and disease classification. With the consideration of different diagnostic data analyzed by different computational methods, we present the overview for four subfields of TCM diagnosis, respectively. For each subfield, we design a rectangular reference list with applications in the horizontal direction and machine learning algorithms in the longitudinal direction. According to the current development of objective TCM diagnosis for patient classification, a discussion of the research issues around machine learning techniques with applications to TCM diagnosis is given to facilitate the further research for TCM patient classification. PMID:26246834

A structural SVM approach for reference parsing.

PubMed

Zhang, Xiaoli; Zou, Jie; Le, Daniel X; Thoma, George R

2011-06-09

Automated extraction of bibliographic data, such as article titles, author names, abstracts, and references is essential to the affordable creation of large citation databases. References, typically appearing at the end of journal articles, can also provide valuable information for extracting other bibliographic data. Therefore, parsing individual reference to extract author, title, journal, year, etc. is sometimes a necessary preprocessing step in building citation-indexing systems. The regular structure in references enables us to consider reference parsing a sequence learning problem and to study structural Support Vector Machine (structural SVM), a newly developed structured learning algorithm on parsing references. In this study, we implemented structural SVM and used two types of contextual features to compare structural SVM with conventional SVM. Both methods achieve above 98% token classification accuracy and above 95% overall chunk-level accuracy for reference parsing. We also compared SVM and structural SVM to Conditional Random Field (CRF). The experimental results show that structural SVM and CRF achieve similar accuracies at token- and chunk-levels. When only basic observation features are used for each token, structural SVM achieves higher performance compared to SVM since it utilizes the contextual label features. However, when the contextual observation features from neighboring tokens are combined, SVM performance improves greatly, and is close to that of structural SVM after adding the second order contextual observation features. The comparison of these two methods with CRF using the same set of binary features show that both structural SVM and CRF perform better than SVM, indicating their stronger sequence learning ability in reference parsing.

Scoliosis: review of types of curves, etiological theories and conservative treatment.

PubMed

Shakil, Halima; Iqbal, Zaheen A; Al-Ghadir, Ahmad H

2014-01-01

Scoliosis is the deviation in the normal vertical spine. Although there are numerous studies available about treatment approaches for scoliosis, the numbers of studies that talk about its etiology and pathology are limited. Aim of this study was to discuss the different types of scoliosis; its curves and etiological theories; and to note their implication on its treatment. We examined various electronic databases including Pub MED, Medline, Cinhal, Cochrane library and Google scholar using key words "scoliosis", "etiology", "pathology" and "conservative treatment". References of obtained articles were also examined for cross references. The search was limited to articles in English language. A total of 145 papers, about Prevalence, History, Symptoms, classification, Biomechanics, Pathogenesis, Kinematics and Treatment of scoliosis were identified to be relevant. To choose the appropriate treatment approach for scoliosis we need to understand its etiology and pathogenesis first. Early intervention with conservative treatment like physiotherapy and bracing can prevent surgery.

Low-Altitude AVIRIS Data for Mapping Land Cover in Yellowstone National Park: Use of Isodata Clustering Techniques

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.

2001-01-01

Northeast Yellowstone National Park (YNP) has a diversity of forest, range, and wetland cover types. Several remote sensing studies have recently been done in this area, including the NASA Earth Observations Commercial Applications Program (EOCAP) hyperspectral project conducted by Yellowstone Ecosystems Studies (YES) on the use of hyperspectral imaging for assessing riparian and in-stream habitats. In 1999, YES and NASA's Commercial Remote Sensing Program Office began collaborative study of this area, assessing the potential of synergistic use of hyperspectral, synthetic aperture radar (SAR), and multiband thermal data for mapping forest, range, and wetland land cover. Since the beginning, a quality 'reference' land cover map has been desired as a tool for developing and validating other land cover maps produced during the project. This paper recounts an effort to produce such a reference land cover map using low-altitude Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data and unsupervised classification techniques. The main objective of this study is to assess ISODATA classification for mapping land cover in Northeast YNP using select bands of low-altitude AVIRIS data. A secondary, more long-term objective is to assess the potential for improving ISODATA-based classification of land cover through use of principal components analysis and minimum noise fraction (MNF) techniques. This paper will primarily report on work regarding the primary research objective. This study focuses on an AVIRIS cube acquired on July 23, 1999, by the confluence of Soda Butte Creek with the Lamar River. Range and wetland habitats dominate the image with forested habitats being a comparatively minor component of the scene. The scene generally tracks from southwest to northeast. Most of the scene is valley bottom with some lower side slopes occurring on the western portion. Elevations within the AVIRIS scene range from approximately 1998 to 2165 m above sea level, based on US Geological Survey (USGS) 30-m digital elevation model (DEM) data. Despain and the National Park Service (NPS) provide additional description of the study area.

A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.

PubMed

Randhawa, Vinay; Kumar Singh, Anil; Acharya, Vishal

2015-12-01

Systems-biology inspired identification of drug targets and machine learning-based screening of small molecules which modulate their activity have the potential to revolutionize modern drug discovery by complementing conventional methods. To utilize the effectiveness of such pipelines, we first analyzed the dysregulated gene pairs between control and tumor samples and then implemented an ensemble-based feature selection approach to prioritize targets in oral squamous cell carcinoma (OSCC) for therapeutic exploration. Based on the structural information of known inhibitors of CXCR4-one of the best targets identified in this study-a feature selection was implemented for the identification of optimal structural features (molecular descriptor) based on which a classification model was generated. Furthermore, the CXCR4-centered descriptor-based classification model was finally utilized to screen a repository of plant derived small-molecules to obtain potential inhibitors. The application of our methodology may assist effective selection of the best targets which may have previously been overlooked, that in turn will lead to the development of new oral cancer medications. The small molecules identified in this study can be ideal candidates for trials as potential novel anti-oral cancer agents. Importantly, distinct steps of this whole study may provide reference for the analysis of other complex human diseases.

Classification of wines according to their production regions with the contained trace elements using laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Tian, Ye; Yan, Chunhua; Zhang, Tianlong; Tang, Hongsheng; Li, Hua; Yu, Jialu; Bernard, Jérôme; Chen, Li; Martin, Serge; Delepine-Gilon, Nicole; Bocková, Jana; Veis, Pavel; Chen, Yanping; Yu, Jin

2017-09-01

Laser-induced breakdown spectroscopy (LIBS) has been applied to classify French wines according to their production regions. The use of the surface-assisted (or surface-enhanced) sample preparation method enabled a sub-ppm limit of detection (LOD), which led to the detection and identification of at least 22 metal and nonmetal elements in a typical wine sample including majors, minors and traces. An ensemble of 29 bottles of French wines, either red or white wines, from five production regions, Alsace, Bourgogne, Beaujolais, Bordeaux and Languedoc, was analyzed together with a wine from California, considered as an outlier. A non-supervised classification model based on principal component analysis (PCA) was first developed for the classification. The results showed a limited separation power of the model, which however allowed, in a step by step approach, to understand the physical reasons behind each step of sample separation and especially to observe the influence of the matrix effect in the sample classification. A supervised classification model was then developed based on random forest (RF), which is in addition a nonlinear algorithm. The obtained classification results were satisfactory with, when the parameters of the model were optimized, a classification accuracy of 100% for the tested samples. We especially discuss in the paper, the effect of spectrum normalization with an internal reference, the choice of input variables for the classification models and the optimization of parameters for the developed classification models.

Fixed Indexed Annuities and Insurance Products Classification Act of 2009

THOMAS, 111th Congress

Sen. Nelson, Ben [D-NE

2009-06-25

Senate - 06/25/2009 Read twice and referred to the Committee on Banking, Housing, and Urban Affairs. (All Actions) Tracker: This bill has the status IntroducedHere are the steps for Status of Legislation:

Microcomputers in Libraries.

ERIC Educational Resources Information Center

Ertel, Monica M.

1984-01-01

This discussion of current microcomputer technologies available to libraries focuses on software applications in four major classifications: communications (online database searching); word processing; administration; and database management systems. Specific examples of library applications are given and six references are cited. (EJS)

Taxonaut: an application software for comparative display of multiple taxonomies with a use case of GBIF Species API

PubMed Central

2016-01-01

Abstract Background The Species API of the Global Biodiversity Information Facility (GBIF) provides public access to taxonomic data aggregated from multiple data sources. Each data source follows its own classification which can be inconsistent with classifications from other sources. Even with a reference classification e.g. the GBIF Backbone taxonomy, a comprehensive method to compare classifications in the data aggregation is essential, especially for non-expert users. New information A Java application was developed to compare multiple taxonomies graphically using classification data acquired from GBIF’s ChecklistBank via the GBIF Species API. It uses a table to display taxonomies where each column represents a taxonomy under comparison, with an aligner column to organise taxa by name. Each cell contains the name of a taxon if the classification in that column contains the name. Each column also has a cell showing the hierarchy of the taxonomy by a folder metaphor where taxa are aligned and synchronised in the aligner column. A set of those comparative tables shows taxa categorised by relationship between taxonomies. The result set is also available as tables in an Excel format file. PMID:27932916

Muscle Injuries in Sports: A New Evidence-Informed and Expert Consensus-Based Classification with Clinical Application.

PubMed

Valle, Xavier; Alentorn-Geli, Eduard; Tol, Johannes L; Hamilton, Bruce; Garrett, William E; Pruna, Ricard; Til, Lluís; Gutierrez, Josep Antoni; Alomar, Xavier; Balius, Ramón; Malliaropoulos, Nikos; Monllau, Joan Carles; Whiteley, Rodney; Witvrouw, Erik; Samuelsson, Kristian; Rodas, Gil

2017-07-01

Muscle injuries are among the most common injuries in sport and continue to be a major concern because of training and competition time loss, challenging decision making regarding treatment and return to sport, and a relatively high recurrence rate. An adequate classification of muscle injury is essential for a full understanding of the injury and to optimize its management and return-to-play process. The ongoing failure to establish a classification system with broad acceptance has resulted from factors such as limited clinical applicability, and the inclusion of subjective findings and ambiguous terminology. The purpose of this article was to describe a classification system for muscle injuries with easy clinical application, adequate grouping of injuries with similar functional impairment, and potential prognostic value. This evidence-informed and expert consensus-based classification system for muscle injuries is based on a four-letter initialism system: MLG-R, respectively referring to the mechanism of injury (M), location of injury (L), grading of severity (G), and number of muscle re-injuries (R). The goal of the classification is to enhance communication between healthcare and sports-related professionals and facilitate rehabilitation and return-to-play decision making.

The Surgical Nosology In Primary-care Settings (SNIPS): a simple bridging classification for the interface between primary and specialist care

PubMed Central

Gruen, Russell L; Knox, Stephanie; Britt, Helena; Bailie, Ross S

2004-01-01

Background The interface between primary care and specialist medical services is an important domain for health services research and policy. Of particular concern is optimising specialist services and the organisation of the specialist workforce to meet the needs and demands for specialist care, particularly those generated by referral from primary care. However, differences in the disease classification and reporting of the work of primary and specialist surgical sectors hamper such research. This paper describes the development of a bridging classification for use in the study of potential surgical problems in primary care settings, and for classifying referrals to surgical specialties. Methods A three stage process was undertaken, which involved: (1) defining the categories of surgical disorders from a specialist perspective that were relevant to the specialist-primary care interface; (2) classifying the 'terms' in the International Classification of Primary Care Version 2-Plus (ICPC-2 Plus) to the surgical categories; and (3) using referral data from 303,000 patient encounters in the BEACH study of general practice activity in Australia to define a core set of surgical conditions. Inclusion of terms was based on the probability of specialist referral of patients with such problems, and specialists' perception that they constitute part of normal surgical practice. Results A four-level hierarchy was developed, containing 8, 27 and 79 categories in the first, second and third levels, respectively. These categories classified 2050 ICPC-2 Plus terms that constituted the fourth level, and which covered the spectrum of problems that were managed in primary care and referred to surgical specialists. Conclusion Our method of classifying terms from a primary care classification system to categories delineated by specialists should be applicable to research addressing the interface between primary and specialist care. By describing the process and putting the bridging classification system in the public domain, we invite comment and application in other settings where similar problems might be faced. PMID:15142280

Classification of Nortes in the Gulf of Mexico derived from wave energy maps

NASA Astrophysics Data System (ADS)

Appendini, C. M.; Hernández-Lasheras, J.

2016-02-01

Extreme wave climate in the Gulf of Mexico is determined by tropical cyclones and winds from the Central American Cold Surges, locally referred to as Nortes. While hurricanes can have catastrophic effects, extreme waves and storm surge from Nortes occur several times a year, and thus have greater impacts on human activities along the Mexican coast of the Gulf of Mexico. Despite the constant impacts from Nortes, there is no available classification that relates their characteristics (e.g. pressure gradients, wind speed), to the associated coastal impacts. This work presents a first approximation to characterize and classify Nortes, which is based on the assumption that the derived wave energy synthetizes information (i.e. wind intensity, direction and duration) of individual Norte events as they pass through the Gulf of Mexico. First, we developed an index to identify Nortes based on surface pressure differences of two locations. To validate the methodology we compared the events identified with other studies and available Nortes logs. Afterwards, we detected Nortes from the 1986/1987, 2008/2009 and 2009/2010 seasons and used their corresponding wind fields to derive the wave energy maps using a numerical wave model. We used the energy maps to classify the events into groups using manual (visual) and automatic classifications (principal component analysis and k-means). The manual classification identified 3 types of Nortes and the automatic classification identified 5, although 3 of them had a high degree of similarity. The principal component analysis indicated that all events have similar characteristics, as few components are necessary to explain almost all of the variance. The classification from the k-means indicated that 81% of analyzed Nortes affect the southeastern Gulf of Mexico, while a smaller percentage affects the northern Gulf of Mexico and even less affect the western Caribbean.

Toward Genetics-Based Virus Taxonomy: Comparative Analysis of a Genetics-Based Classification and the Taxonomy of Picornaviruses

PubMed Central

Lauber, Chris

2012-01-01

Virus taxonomy has received little attention from the research community despite its broad relevance. In an accompanying paper (C. Lauber and A. E. Gorbalenya, J. Virol. 86:3890–3904, 2012), we have introduced a quantitative approach to hierarchically classify viruses of a family using pairwise evolutionary distances (PEDs) as a measure of genetic divergence. When applied to the six most conserved proteins of the Picornaviridae, it clustered 1,234 genome sequences in groups at three hierarchical levels (to which we refer as the “GENETIC classification”). In this study, we compare the GENETIC classification with the expert-based picornavirus taxonomy and outline differences in the underlying frameworks regarding the relation of virus groups and genetic diversity that represent, respectively, the structure and content of a classification. To facilitate the analysis, we introduce two novel diagrams. The first connects the genetic diversity of taxa to both the PED distribution and the phylogeny of picornaviruses. The second depicts a classification and the accommodated genetic diversity in a standardized manner. Generally, we found striking agreement between the two classifications on species and genus taxa. A few disagreements concern the species Human rhinovirus A and Human rhinovirus C and the genus Aphthovirus, which were split in the GENETIC classification. Furthermore, we propose a new supergenus level and universal, level-specific PED thresholds, not reached yet by many taxa. Since the species threshold is approached mostly by taxa with large sampling sizes and those infecting multiple hosts, it may represent an upper limit on divergence, beyond which homologous recombination in the six most conserved genes between two picornaviruses might not give viable progeny. PMID:22278238

Multiple Sparse Representations Classification

PubMed Central

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

2015-01-01

Sparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In this empirical study we propose to further leverage the redundancy of the learned dictionaries to achieve a more accurate classifier. In conventional SRC, each image pixel is associated with a small patch surrounding it. Using these patches, a dictionary is trained for each class in a supervised fashion. Commonly, redundant/overcomplete dictionaries are trained and image patches are sparsely represented by a linear combination of only a few of the dictionary elements. Given a set of trained dictionaries, a new patch is sparse coded using each of them, and subsequently assigned to the class whose dictionary yields the minimum residual energy. We propose a generalization of this scheme. The method, which we call multiple sparse representations classification (mSRC), is based on the observation that an overcomplete, class specific dictionary is capable of generating multiple accurate and independent estimates of a patch belonging to the class. So instead of finding a single sparse representation of a patch for each dictionary, we find multiple, and the corresponding residual energies provides an enhanced statistic which is used to improve classification. We demonstrate the efficacy of mSRC for three example applications: pixelwise classification of texture images, lumen segmentation in carotid artery magnetic resonance imaging (MRI), and bifurcation point detection in carotid artery MRI. We compare our method with conventional SRC, K-nearest neighbor, and support vector machine classifiers. The results show that mSRC outperforms SRC and the other reference methods. In addition, we present an extensive evaluation of the effect of the main mSRC parameters: patch size, dictionary size, and sparsity level. PMID:26177106

Fusion of multiple quadratic penalty function support vector machines (QPFSVM) for automated sea mine detection and classification

NASA Astrophysics Data System (ADS)

Dobeck, Gerald J.; Cobb, J. Tory

2002-08-01

The high-resolution sonar is one of the principal sensors used by the Navy to detect and classify sea mines in minehunting operations. For such sonar systems, substantial effort has been devoted to the development of automated detection and classification (D/C) algorithms. These have been spurred by several factors including (1) aids for operators to reduce work overload, (2) more optimal use of all available data, and (3) the introduction of unmanned minehunting systems. The environments where sea mines are typically laid (harbor areas, shipping lanes, and the littorals) give rise to many false alarms caused by natural, biologic, and man-made clutter. The objective of the automated D/C algorithms is to eliminate most of these false alarms while still maintaining a very high probability of mine detection and classification (PdPc). In recent years, the benefits of fusing the outputs of multiple D/C algorithms have been studied. We refer to this as Algorithm Fusion. The results have been remarkable, including reliable robustness to new environments. The Quadratic Penalty Function Support Vector Machine (QPFSVM) algorithm to aid in the automated detection and classification of sea mines is introduced in this paper. The QPFSVM algorithm is easy to train, simple to implement, and robust to feature space dimension. Outputs of successive SVM algorithms are cascaded in stages (fused) to improve the Probability of Classification (Pc) and reduce the number of false alarms. Even though our experience has been gained in the area of sea mine detection and classification, the principles described herein are general and can be applied to fusion of any D/C problem (e.g., automated medical diagnosis or automatic target recognition for ballistic missile defense).

How reliable and accurate is the AO/OTA comprehensive classification for adult long-bone fractures?

PubMed

Meling, Terje; Harboe, Knut; Enoksen, Cathrine H; Aarflot, Morten; Arthursson, Astvaldur J; Søreide, Kjetil

2012-07-01

Reliable classification of fractures is important for treatment allocation and study comparisons. The overall accuracy of scoring applied to a general population of fractures is little known. This study aimed to investigate the accuracy and reliability of the comprehensive Arbeitsgemeinschaft für Osteosynthesefragen/Orthopedic Trauma Association classification for adult long-bone fractures and identify factors associated with poor coding agreement. Adults (>16 years) with long-bone fractures coded in a Fracture and Dislocation Registry at the Stavanger University Hospital during the fiscal year 2008 were included. An unblinded reference code dataset was generated for the overall accuracy assessment by two experienced orthopedic trauma surgeons. Blinded analysis of intrarater reliability was performed by rescoring and of interrater reliability by recoding of a randomly selected fracture sample. Proportion of agreement (PA) and kappa (κ) statistics are presented. Uni- and multivariate logistic regression analyses of factors predicting accuracy were performed. During the study period, 949 fractures were included and coded by 26 surgeons. For the intrarater analysis, overall agreements were κ = 0.67 (95% confidence interval [CI]: 0.64-0.70) and PA 69%. For interrater assessment, κ = 0.67 (95% CI: 0.62-0.72) and PA 69%. The accuracy of surgeons' blinded recoding was κ = 0.68 (95% CI: 0.65- 0.71) and PA 68%. Fracture type, frequency of the fracture, and segment fractured significantly influenced accuracy whereas the coder's experience did not. Both the reliability and accuracy of the comprehensive Arbeitsgemeinschaft für Osteosynthesefragen/Orthopedic Trauma Association classification for long-bone fractures ranged from substantial to excellent. Variations in coding accuracy seem to be related more to the fracture itself than the surgeon. Diagnostic study, level I.

Classification of California streams using combined deductive and inductive approaches: Setting the foundation for analysis of hydrologic alteration

USGS Publications Warehouse

Pyne, Matthew I.; Carlisle, Daren M.; Konrad, Christopher P.; Stein, Eric D.

2017-01-01

Regional classification of streams is an early step in the Ecological Limits of Hydrologic Alteration framework. Many stream classifications are based on an inductive approach using hydrologic data from minimally disturbed basins, but this approach may underrepresent streams from heavily disturbed basins or sparsely gaged arid regions. An alternative is a deductive approach, using watershed climate, land use, and geomorphology to classify streams, but this approach may miss important hydrological characteristics of streams. We classified all stream reaches in California using both approaches. First, we used Bayesian and hierarchical clustering to classify reaches according to watershed characteristics. Streams were clustered into seven classes according to elevation, sedimentary rock, and winter precipitation. Permutation-based analysis of variance and random forest analyses were used to determine which hydrologic variables best separate streams into their respective classes. Stream typology (i.e., the class that a stream reach is assigned to) is shaped mainly by patterns of high and mean flow behavior within the stream's landscape context. Additionally, random forest was used to determine which hydrologic variables best separate minimally disturbed reference streams from non-reference streams in each of the seven classes. In contrast to stream typology, deviation from reference conditions is more difficult to detect and is largely defined by changes in low-flow variables, average daily flow, and duration of flow. Our combined deductive/inductive approach allows us to estimate flow under minimally disturbed conditions based on the deductive analysis and compare to measured flow based on the inductive analysis in order to estimate hydrologic change.

Quantitative determination and classification of energy drinks using near-infrared spectroscopy.

PubMed

Rácz, Anita; Héberger, Károly; Fodor, Marietta

2016-09-01

Almost a hundred commercially available energy drink samples from Hungary, Slovakia, and Greece were collected for the quantitative determination of their caffeine and sugar content with FT-NIR spectroscopy and high-performance liquid chromatography (HPLC). Calibration models were built with partial least-squares regression (PLSR). An HPLC-UV method was used to measure the reference values for caffeine content, while sugar contents were measured with the Schoorl method. Both the nominal sugar content (as indicated on the cans) and the measured sugar concentration were used as references. Although the Schoorl method has larger error and bias, appropriate models could be developed using both references. The validation of the models was based on sevenfold cross-validation and external validation. FT-NIR analysis is a good candidate to replace the HPLC-UV method, because it is much cheaper than any chromatographic method, while it is also more time-efficient. The combination of FT-NIR with multidimensional chemometric techniques like PLSR can be a good option for the detection of low caffeine concentrations in energy drinks. Moreover, three types of energy drinks that contain (i) taurine, (ii) arginine, and (iii) none of these two components were classified correctly using principal component analysis and linear discriminant analysis. Such classifications are important for the detection of adulterated samples and for quality control, as well. In this case, more than a hundred samples were used for the evaluation. The classification was validated with cross-validation and several randomization tests (X-scrambling). Graphical Abstract The way of energy drinks from cans to appropriate chemometric models.

Application of a global reference for fetal-weight and birthweight percentiles in predicting infant mortality.

PubMed

Ding, G; Tian, Y; Zhang, Y; Pang, Y; Zhang, J S; Zhang, J

2013-12-01

To determine whether the recently published A global reference for fetal-weight and birthweight percentiles (Global Reference) improves small- (SGA), appropriate- (AGA), and large-for-gestational-age (LGA) definitions in predicting infant mortality. Population-based cohort study. The US Linked Livebirth and Infant Death records between 1995 and 2004. Singleton births with birthweight >500 g born at 24-41 weeks of gestation. We compared infant mortality rates of SGA, AGA, and LGA infants classified by three different references: the Global Reference; a commonly used birthweight reference; and Hadlock's ultrasound reference. Infant mortality rates. Among 33 997 719 eligible liveborn singleton births, 25% of preterm and 9% of term infants were classified differently for SGA, AGA, and LGA by the Global Reference and the birthweight reference. The Global Reference indicated higher mortality rates in preterm SGA and preterm LGA infants than the birthweight reference. The mortality rate was considerably higher in infants classified as preterm SGA by the Global Reference but not by the birthweight reference, compared with the corresponding infants classified by the birthweight reference but not by the Global Reference (105.7 versus 12.9 per 1000, RR 8.17, 95% CI 7.38-9.06). Yet, the differences in mortality rates were much smaller in term infants than in preterm infants. Black infants had a particularly higher mortality rate than other races in AGA and LGA preterm and term infants. In respect to the commonly used birthweight reference, the Global Reference increases the identification of infant deaths by improved classification of abnormal newborn size at birth, and these advantages were more obvious in preterm than in term infants. © 2013 RCOG.

A classification model of Hyperion image base on SAM combined decision tree

NASA Astrophysics Data System (ADS)

Wang, Zhenghai; Hu, Guangdao; Zhou, YongZhang; Liu, Xin

2009-10-01

Monitoring the Earth using imaging spectrometers has necessitated more accurate analyses and new applications to remote sensing. A very high dimensional input space requires an exponentially large amount of data to adequately and reliably represent the classes in that space. On the other hand, with increase in the input dimensionality the hypothesis space grows exponentially, which makes the classification performance highly unreliable. Traditional classification algorithms Classification of hyperspectral images is challenging. New algorithms have to be developed for hyperspectral data classification. The Spectral Angle Mapper (SAM) is a physically-based spectral classification that uses an ndimensional angle to match pixels to reference spectra. The algorithm determines the spectral similarity between two spectra by calculating the angle between the spectra, treating them as vectors in a space with dimensionality equal to the number of bands. The key and difficulty is that we should artificial defining the threshold of SAM. The classification precision depends on the rationality of the threshold of SAM. In order to resolve this problem, this paper proposes a new automatic classification model of remote sensing image using SAM combined with decision tree. It can automatic choose the appropriate threshold of SAM and improve the classify precision of SAM base on the analyze of field spectrum. The test area located in Heqing Yunnan was imaged by EO_1 Hyperion imaging spectrometer using 224 bands in visual and near infrared. The area included limestone areas, rock fields, soil and forests. The area was classified into four different vegetation and soil types. The results show that this method choose the appropriate threshold of SAM and eliminates the disturbance and influence of unwanted objects effectively, so as to improve the classification precision. Compared with the likelihood classification by field survey data, the classification precision of this model heightens 9.9%.

Choice of Reference Serum Creatinine in Defining AKI

PubMed Central

Siew, Edward D.; Matheny, Michael E.

2015-01-01

Background/Aims The study of acute kidney injury (AKI) has expanded with the increasing availability of electronic health records and the use of standardized definitions. Understanding the impact of AKI between settings is limited by heterogeneity in the selection of reference creatinine to anchor the definition of AKI. In this mini-review, we discuss different approaches used to select reference creatinine and their relative merits and limitations. Methods We reviewed the literature to obtain representative examples of published baseline creatinine definitions when pre-hospital data were not available, as well as literature evaluating estimation of baseline renal function, using Pubmed and reference back-tracing within known works. Results 1) Prehospital creatinine values are useful in determining reference creatinine, and in high-risk populations, the mean outpatient serum creatinine value 7-365 days before hospitalization closely approximates nephrology adjudication, 2) in patients without pre-hospital data, the eGFR 75 approach does not reliably estimate true AKI incidence in most at-risk populations 3) using the lowest inpatient serum creatinine may be reasonable, especially in those with preserved kidney function, but may generously estimate AKI incidence and severity and miss community-acquired AKI that does not fully resolve, 4) using more specific definitions of AKI (e.g. KIDGO Stage 2 and 3) may help to reduce the effects of misclassification when using surrogate values, and 5) leveraging available clinical data may help refine the estimate of reference creatinine. Conclusions Choosing reference creatinine for AKI calculation is important for AKI classification and study interpretation. We recommend obtaining data on pre-hospital kidney function, wherever possible. In studies where surrogate estimates are used, transparency in how they are applied and discussion that informs the reader of potential biases should be provided. Further work to refine the estimation of reference creatinine is needed. PMID:26332325

The Assignment of American Society of Anesthesiologists Physical Status Classification for Adult Polytrauma Patients: Results From a Survey and Future Considerations.

PubMed

Kuza, Catherine M; Hatzakis, George; Nahmias, Jeffry T

2017-12-01

The American Society of Anesthesiologists (ASA) physical status (PS) classification system assesses the preoperative health of patients. Previous studies demonstrated poor interrater reliability and variable ASA PS scores, especially in trauma scenarios. There are few studies that evaluated the assignment of ASA PS scores in trauma patients and no studies that evaluated ASA PS assignment in severely injured adult polytrauma patients. Our objective was to assess interrater reliability and identify sources of discrepancy among anesthesiologists and trauma surgeons in designating ASA PS scores to adult polytrauma patients. A link to an online survey containing questions assessing attitudes regarding ASA PS classification, demographic information, and 8 fictional trauma cases was e-mailed to anesthesiologists and trauma surgeons. The participants were asked to assign an ASA PS score to each scenario and explain their choice. Rater-versus-reference and interrater reliability, beyond that expected by chance, among respondents was analyzed using the Fleiss kappa analysis. A total of 349 participants completed the survey. All 8 cases had inconsistent ASA PS scores; several cases had scores ranging from I to VI and variable emergency (E) designations. Using weighted kappa (Kw) analysis for a subset of 201 respondents (101 trauma surgeons [S] and 100 anesthesiologists [A]), we found moderate (Kw = 0.63; SE = 0.024; 95% confidence interval, 0.594-0.666; P < .001) interrater-versus-reference reliability. The interrater reliability was fair (Kw = 0.43; SE = 0.037; 95% confidence interval, 0.360-0.491; P < .001). This study demonstrates fair interrater reliability beyond that expected by chance of the ASA PS scores among anesthesiologists and trauma surgeons when assessing adult polytrauma patients. Although the ASA PS is used in some trauma risk stratification models, discrepancies of ASA PS scores assigned to trauma cases exist. Future modifications of the ASA PS guidelines should aim to improve the interrater reliability of ASA PS scores in trauma patients. Further studies are warranted to determine the value of the ASA PS score as a trauma prognostic metric.

Inhibited attachment behaviour and disinhibited social engagement behaviour as relevant concepts in referred home reared children.

PubMed

Scheper, F Y; Abrahamse, M E; Jonkman, C S; Schuengel, C; Lindauer, R J L; de Vries, A L C; Doreleijers, T A H; Jansen, L M C

2016-07-01

Disorders of attachment and social engagement have mainly been studied in children, reared in institutions and foster care. There are few studies amongst home reared children living with biological parents. The aim of this study was to test the clinical significance of inhibited attachment behaviour and disinhibited social engagement behaviour in young home reared children, referred for treatment of emotional and behavioural problems, compared with young children in treatment foster care. The Disturbances of Attachment Interview, Maltreatment Classification System, the Child Behaviour Checklist and Parenting Stress Index were used in 141 referred home reared children and 59 referred foster children, aged 2.0-7.9 years (M = 4.7, SE = 1.3), 71% boys. Inhibited attachment behaviour was less prevalent in the referred home reared group (9%) than in the foster care group (27%). Disinhibited social engagement behaviour was found in 42% of the home reared group, similar to the foster care group. Inhibited attachment behaviour and disinhibited social engagement behaviour were not associated with child maltreatment. More inhibited attachment behaviour was associated with clinical levels of child internalizing and externalizing behaviour in the home reared group, not in the foster care group. In both groups, more disinhibited social engagement behaviour was associated with clinical levels of externalizing behaviour and with more parenting stress. Even without evident links to maltreatment, results of this study suggest clinical significance of inhibited attachment behaviour and disinhibited social engagement behaviour in young home reared children referred for treatment of emotional and behavioural problems. © 2016 John Wiley & Sons Ltd.

Uncertainties and Solutions Related to Use of WRB (2007) in the Boreo-nemoral zone, Case of Latvia

NASA Astrophysics Data System (ADS)

Kasparinskis, Raimonds; Nikodemus, Olgerts; Rolavs, Nauris

2014-05-01

Relatively high diversity of soils groups according to the WRB (2007) classification is observed in forest ecosystems in the boreo-nemoral zone in Latvia. This is due to the geological genesis of area and environmental conditions (Kasparinskis, Nikodemus, 2012), as well as historical land use and management (Nikodemus et al., 2013). Due to the relatively young soils, Albic, Spodic and Cambic horizons are relatively weakly expressed in many cases. Relatively well developed Albic horizons occur in sandy forest soils, but unusually well expressed Spodic features are observed. In some cases there is a Cambic horizon, however location of Cambisols in the WRB (2007) soil classification sequence does not provide an opportunity to classify these soils as Cambisols, but they are classified as Arenosols. This sequence does not reflect the logical sheme of soil development, and therefore raises the question about location of Podzols, Arenosols and Cambisols in the sequence of WRB (2007) soil classification. Soils with two parent materials (abrupt textural change) are relatively common in Latvia, where conceptually on the small scale mapping results in classification as the soil group Planosols, but in many cases there is occurrence of Fluvic materials, as parent material in the upper part of the soil profile is formed by Baltic Ice lake sandy sediments - this leads to question about the location of Fluvisols and Planosols in the sequence of the WRB (2007) soil classification. Soil research has found cases, where a relatively well developed Spodic horizon was established as the result of ground water table depth in areas of abrupt textural change. In this case the profile corresponds to the soil group of Podzols, however in some cases - Gleysols not Planosols due to a high ground water table. Therefore there is a need for discussion also about the location of Podzols and Planosols in the sequence of the WRB (2007) soil classification. The above mentioned questions raise problems related to unambiguous determination of soil groups. Soil classification must be very precise by reflecting relationships of soil forming processes. In the development of international soil classification it is advisable to pay more attention on ecological processes. This study was supported by the European Social Fund No. 2013/0020/1DP/1.1.1.2.0/13/APIA/VIAA/066. References: IUSS Working Group, 2007. World Reference Base for Soil Resources 2006, first update 2007. World Soil Resources Reports 103. FAO, Rome. 103-116. Kasparinskis R., Nikodemus O. 2012. Influence of environmental factors on the spatial distribution and diversity of forest soil in Latvia. Estonian Journal of Earth Sciences. 61(1): 48-64. Nikodemus O., Kasparinskis R., Kukuls I. 2013. Influence of Afforestation on Soil Genesis, Morphology and Properties in Glacial Till Deposits. Archives of Agronomy and Soil Science. 59(3): 449-465.

Rationale for classification of combustible gases, vapors and dusts with reference to the National Electrical Code

NASA Astrophysics Data System (ADS)

1982-07-01

Serious reservations about the entire classification procedure of chemical compounds present in electrical equipment environments and the precepts on which it is based are discussed. Although some tests were conducted on selected key compounds, the committee primarily considered the chemical similarity of compounds and other known flammability properties and relied heavily on the experience and intuition of its members. The committee also recommended that the NEC grouping of dusts be changed in some ways and has reclassified dusts according to the modified version of the code.

Anorexia Nervosa and Bulimia.

ERIC Educational Resources Information Center

Csapo, Marg

1987-01-01

The article reviews the literature on anorexia nervosa, with or without bulimia, and presents a comprehensive picture of this eating disorder, focusing on terminology, historical references, prevalence, prognosis, classification, diagnostic criteria, physical and psychological characteristics, evolution of the disability, etiology, treatment, and…

Aquatics, Flyers, Creepers and Terrestrials--Students' Conceptions of Animal Classification.

ERIC Educational Resources Information Center

Kattmann, Ulrich

2001-01-01

Students prefer to classify creatures along the criteria of habitat and locomotion (method of movement). Discusses the educational consequences for biology instruction, particularly with regard to biological taxonomy, biodiversity, and evolution. (Contains 33 references.) (Author/YDS)

29 CFR 1990.101 - Scope.

Code of Federal Regulations, 2014 CFR

2014-07-01

...) IDENTIFICATION, CLASSIFICATION, AND REGULATION OF POTENTIAL OCCUPATIONAL CARCINOGENS General § 1990.101 Scope... potential occupational carcinogens found in each workplace in the United States regulated by the... occupational carcinogens. This part may be referred to as “The OSHA Cancer Policy.” ...

29 CFR 1990.101 - Scope.

Code of Federal Regulations, 2012 CFR

2012-07-01

...) IDENTIFICATION, CLASSIFICATION, AND REGULATION OF POTENTIAL OCCUPATIONAL CARCINOGENS General § 1990.101 Scope... potential occupational carcinogens found in each workplace in the United States regulated by the... occupational carcinogens. This part may be referred to as “The OSHA Cancer Policy.” ...

29 CFR 1990.101 - Scope.

Code of Federal Regulations, 2013 CFR

2013-07-01

...) IDENTIFICATION, CLASSIFICATION, AND REGULATION OF POTENTIAL OCCUPATIONAL CARCINOGENS General § 1990.101 Scope... potential occupational carcinogens found in each workplace in the United States regulated by the... occupational carcinogens. This part may be referred to as “The OSHA Cancer Policy.” ...

Comment on "An Evaluation of Query Expansion by the Addition of Clustered Terms for a Document Retrieval System"

ERIC Educational Resources Information Center

Salton, G.

1972-01-01

The author emphasized that one cannot conclude from the experiments reported upon that term clusters (or equivalently, keyword classifications or thesauruses) are not useful in retrieval. (2 references) (Author)

Automated ancillary cancer history classification for mesothelioma patients from free-text clinical reports

PubMed Central

Wilson, Richard A.; Chapman, Wendy W.; DeFries, Shawn J.; Becich, Michael J.; Chapman, Brian E.

2010-01-01

Background: Clinical records are often unstructured, free-text documents that create information extraction challenges and costs. Healthcare delivery and research organizations, such as the National Mesothelioma Virtual Bank, require the aggregation of both structured and unstructured data types. Natural language processing offers techniques for automatically extracting information from unstructured, free-text documents. Methods: Five hundred and eight history and physical reports from mesothelioma patients were split into development (208) and test sets (300). A reference standard was developed and each report was annotated by experts with regard to the patient’s personal history of ancillary cancer and family history of any cancer. The Hx application was developed to process reports, extract relevant features, perform reference resolution and classify them with regard to cancer history. Two methods, Dynamic-Window and ConText, for extracting information were evaluated. Hx’s classification responses using each of the two methods were measured against the reference standard. The average Cohen’s weighted kappa served as the human benchmark in evaluating the system. Results: Hx had a high overall accuracy, with each method, scoring 96.2%. F-measures using the Dynamic-Window and ConText methods were 91.8% and 91.6%, which were comparable to the human benchmark of 92.8%. For the personal history classification, Dynamic-Window scored highest with 89.2% and for the family history classification, ConText scored highest with 97.6%, in which both methods were comparable to the human benchmark of 88.3% and 97.2%, respectively. Conclusion: We evaluated an automated application’s performance in classifying a mesothelioma patient’s personal and family history of cancer from clinical reports. To do so, the Hx application must process reports, identify cancer concepts, distinguish the known mesothelioma from ancillary cancers, recognize negation, perform reference resolution and determine the experiencer. Results indicated that both information extraction methods tested were dependant on the domain-specific lexicon and negation extraction. We showed that the more general method, ConText, performed as well as our task-specific method. Although Dynamic- Window could be modified to retrieve other concepts, ConText is more robust and performs better on inconclusive concepts. Hx could greatly improve and expedite the process of extracting data from free-text, clinical records for a variety of research or healthcare delivery organizations. PMID:21031012

Chemometric study of Andalusian extra virgin olive oils Raman spectra: Qualitative and quantitative information.

PubMed

Sánchez-López, E; Sánchez-Rodríguez, M I; Marinas, A; Marinas, J M; Urbano, F J; Caridad, J M; Moalem, M

2016-08-15

Authentication of extra virgin olive oil (EVOO) is an important topic for olive oil industry. The fraudulent practices in this sector are a major problem affecting both producers and consumers. This study analyzes the capability of FT-Raman combined with chemometric treatments of prediction of the fatty acid contents (quantitative information), using gas chromatography as the reference technique, and classification of diverse EVOOs as a function of the harvest year, olive variety, geographical origin and Andalusian PDO (qualitative information). The optimal number of PLS components that summarizes the spectral information was introduced progressively. For the estimation of the fatty acid composition, the lowest error (both in fitting and prediction) corresponded to MUFA, followed by SAFA and PUFA though such errors were close to zero in all cases. As regards the qualitative variables, discriminant analysis allowed a correct classification of 94.3%, 84.0%, 89.0% and 86.6% of samples for harvest year, olive variety, geographical origin and PDO, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Identifying Pediatric Severe Sepsis and Septic Shock: Accuracy of Diagnosis Codes.

PubMed

Balamuth, Fran; Weiss, Scott L; Hall, Matt; Neuman, Mark I; Scott, Halden; Brady, Patrick W; Paul, Raina; Farris, Reid W D; McClead, Richard; Centkowski, Sierra; Baumer-Mouradian, Shannon; Weiser, Jason; Hayes, Katie; Shah, Samir S; Alpern, Elizabeth R

2015-12-01

To evaluate accuracy of 2 established administrative methods of identifying children with sepsis using a medical record review reference standard. Multicenter retrospective study at 6 US children's hospitals. Subjects were children >60 days to <19 years of age and identified in 4 groups based on International Classification of Diseases, Ninth Revision, Clinical Modification codes: (1) severe sepsis/septic shock (sepsis codes); (2) infection plus organ dysfunction (combination codes); (3) subjects without codes for infection, organ dysfunction, or severe sepsis; and (4) infection but not severe sepsis or organ dysfunction. Combination codes were allowed, but not required within the sepsis codes group. We determined the presence of reference standard severe sepsis according to consensus criteria. Logistic regression was performed to determine whether addition of codes for sepsis therapies improved case identification. A total of 130 out of 432 subjects met reference SD of severe sepsis. Sepsis codes had sensitivity 73% (95% CI 70-86), specificity 92% (95% CI 87-95), and positive predictive value 79% (95% CI 70-86). Combination codes had sensitivity 15% (95% CI 9-22), specificity 71% (95% CI 65-76), and positive predictive value 18% (95% CI 11-27). Slight improvements in model characteristics were observed when codes for vasoactive medications and endotracheal intubation were added to sepsis codes (c-statistic 0.83 vs 0.87, P = .008). Sepsis specific International Classification of Diseases, Ninth Revision, Clinical Modification codes identify pediatric patients with severe sepsis in administrative data more accurately than a combination of codes for infection plus organ dysfunction. Copyright © 2015 Elsevier Inc. All rights reserved.

Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.

PubMed

Torkzaban, Bahareh; Kayvanjoo, Amir Hossein; Ardalan, Arman; Mousavi, Soraya; Mariotti, Roberto; Baldoni, Luciana; Ebrahimie, Esmaeil; Ebrahimi, Mansour; Hosseini-Mazinani, Mehdi

2015-01-01

Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biology. However, these methods have been less frequently used with empirical population genetics data. In this study, we developed a new combined approach of data analysis using microsatellite marker data from our previous studies of olive populations using machine learning algorithms. Herein, 267 olive accessions of various origins including 21 reference cultivars, 132 local ecotypes, and 37 wild olive specimens from the Iranian plateau, together with 77 of the most represented Mediterranean varieties were investigated using a finely selected panel of 11 microsatellite markers. We organized data in two '4-targeted' and '16-targeted' experiments. A strategy of assaying different machine based analyses (i.e. data cleaning, feature selection, and machine learning classification) was devised to identify the most informative loci and the most diagnostic alleles to represent the population and the geography of each olive accession. These analyses revealed microsatellite markers with the highest differentiating capacity and proved efficiency for our method of clustering olive accessions to reflect upon their regions of origin. A distinguished highlight of this study was the discovery of the best combination of markers for better differentiating of populations via machine learning models, which can be exploited to distinguish among other biological populations.

Development of terminology for mammographic techniques for radiological technologists.

PubMed

Yagahara, Ayako; Yokooka, Yuki; Tsuji, Shintaro; Nishimoto, Naoki; Uesugi, Masahito; Muto, Hiroshi; Ohba, Hisateru; Kurowarabi, Kunio; Ogasawara, Katsuhiko

2011-07-01

We are developing a mammographic ontology to share knowledge of the mammographic domain for radiologic technologists, with the aim of improving mammographic techniques. As a first step in constructing the ontology, we used mammography reference books to establish mammographic terminology for identifying currently available knowledge. This study proceeded in three steps: (1) determination of the domain and scope of the terminology, (2) lexical extraction, and (3) construction of hierarchical structures. We extracted terms mainly from three reference books and constructed the hierarchical structures manually. We compared features of the terms extracted from the three reference books. We constructed a terminology consisting of 440 subclasses grouped into 19 top-level classes: anatomic entity, image quality factor, findings, material, risk, breast, histological classification of breast tumors, role, foreign body, mammographic technique, physics, purpose of mammography examination, explanation of mammography examination, image development, abbreviation, quality control, equipment, interpretation, and evaluation of clinical imaging. The number of terms that occurred in the subclasses varied depending on which reference book was used. We developed a terminology of mammographic techniques for radiologic technologists consisting of 440 terms.

LTRsift: a graphical user interface for semi-automatic classification and postprocessing of de novo detected LTR retrotransposons

PubMed Central

2012-01-01

Background Long terminal repeat (LTR) retrotransposons are a class of eukaryotic mobile elements characterized by a distinctive sequence similarity-based structure. Hence they are well suited for computational identification. Current software allows for a comprehensive genome-wide de novo detection of such elements. The obvious next step is the classification of newly detected candidates resulting in (super-)families. Such a de novo classification approach based on sequence-based clustering of transposon features has been proposed before, resulting in a preliminary assignment of candidates to families as a basis for subsequent manual refinement. However, such a classification workflow is typically split across a heterogeneous set of glue scripts and generic software (for example, spreadsheets), making it tedious for a human expert to inspect, curate and export the putative families produced by the workflow. Results We have developed LTRsift, an interactive graphical software tool for semi-automatic postprocessing of de novo predicted LTR retrotransposon annotations. Its user-friendly interface offers customizable filtering and classification functionality, displaying the putative candidate groups, their members and their internal structure in a hierarchical fashion. To ease manual work, it also supports graphical user interface-driven reassignment, splitting and further annotation of candidates. Export of grouped candidate sets in standard formats is possible. In two case studies, we demonstrate how LTRsift can be employed in the context of a genome-wide LTR retrotransposon survey effort. Conclusions LTRsift is a useful and convenient tool for semi-automated classification of newly detected LTR retrotransposons based on their internal features. Its efficient implementation allows for convenient and seamless filtering and classification in an integrated environment. Developed for life scientists, it is helpful in postprocessing and refining the output of software for predicting LTR retrotransposons up to the stage of preparing full-length reference sequence libraries. The LTRsift software is freely available at http://www.zbh.uni-hamburg.de/LTRsift under an open-source license. PMID:23131050

LTRsift: a graphical user interface for semi-automatic classification and postprocessing of de novo detected LTR retrotransposons.

PubMed

Steinbiss, Sascha; Kastens, Sascha; Kurtz, Stefan

2012-11-07

Long terminal repeat (LTR) retrotransposons are a class of eukaryotic mobile elements characterized by a distinctive sequence similarity-based structure. Hence they are well suited for computational identification. Current software allows for a comprehensive genome-wide de novo detection of such elements. The obvious next step is the classification of newly detected candidates resulting in (super-)families. Such a de novo classification approach based on sequence-based clustering of transposon features has been proposed before, resulting in a preliminary assignment of candidates to families as a basis for subsequent manual refinement. However, such a classification workflow is typically split across a heterogeneous set of glue scripts and generic software (for example, spreadsheets), making it tedious for a human expert to inspect, curate and export the putative families produced by the workflow. We have developed LTRsift, an interactive graphical software tool for semi-automatic postprocessing of de novo predicted LTR retrotransposon annotations. Its user-friendly interface offers customizable filtering and classification functionality, displaying the putative candidate groups, their members and their internal structure in a hierarchical fashion. To ease manual work, it also supports graphical user interface-driven reassignment, splitting and further annotation of candidates. Export of grouped candidate sets in standard formats is possible. In two case studies, we demonstrate how LTRsift can be employed in the context of a genome-wide LTR retrotransposon survey effort. LTRsift is a useful and convenient tool for semi-automated classification of newly detected LTR retrotransposons based on their internal features. Its efficient implementation allows for convenient and seamless filtering and classification in an integrated environment. Developed for life scientists, it is helpful in postprocessing and refining the output of software for predicting LTR retrotransposons up to the stage of preparing full-length reference sequence libraries. The LTRsift software is freely available at http://www.zbh.uni-hamburg.de/LTRsift under an open-source license.

[New international classification of corneal dystrophies and clinical landmarks].

PubMed

Lisch, W; Seitz, B

2008-07-01

The International Committee on Classification of Corneal Dystrophies, briefly IC (3)D, was founded with the sponsorship of the American Cornea Society and the American Academy of Ophthalmology in July 2005. This committee consists of 17 corneal experts (1) from USA, Asia and Europe. The goal of this group was to develop a new, internationally accepted classification of corneal dystrophies (CD) based on modern clinical, histological and genetical knowledge. The aim of the new classification should be to avoid wrong interpretations and misnomers of the different forms of CD. The IC (3)D extensive manuscript is in press as Supplement publication in the journal "Cornea". The 25 different CD are divided in four categories by clinical and genetical knowledge. Additionally, templates for each type of CD are included. Finally, many typical color slit-lamp photos are presented in the publication together with essential references and current genetical results in tabular form. As members of IC (3)D the authors present a clinical landmark survey of the different corneal dystrophies. The ophthalmologist is the first to examine and to diagnose a new patient with a probable CD at the slit-lamp. Our elaborated table of landmarks is supposed to be a "bridge" for the ophthalmologist to precisely define the corneal opacities of a presumed CD. This "bridge" makes it easier for them to study the IC (3)D Supplement publication and to get more information including adequate differential diagnosis.

CON4EI: EpiOcular™ Eye Irritation Test (EpiOcular™ EIT) for hazard identification and labelling of eye irritating chemicals.

PubMed

Kandarova, H; Letasiova, S; Adriaens, E; Guest, R; Willoughby, J A; Drzewiecka, A; Gruszka, K; Alépée, Nathalie; Verstraelen, Sandra; Van Rompay, An R

2018-06-01

Assessment of the acute eye irritation potential is part of the international regulatory requirements for testing of chemicals. The objective of the CON4EI project was to develop tiered testing strategies for eye irritation assessment. A set of 80 reference chemicals (38 liquids and 42 solids) was tested with eight different methods. Here, the results obtained with the EpiOcular™ Eye Irritation Test (EIT), adopted as OECD TG 492, are shown. The primary aim of this study was to evaluate of the performance of the test method to discriminate between chemicals not requiring classification for serious eye damage/eye irritancy (No Category) and chemicals requiring classification and labelling. In addition, the predictive capacity in terms of in vivo drivers of classification (i.e. corneal opacity, conjunctival redness and persistence at day 21) was investigated. EpiOcular™ EIT achieved a sensitivity of 97%, a specificity of 87% and accuracy of 95% and also confirmed its excellent reproducibility (100%) from the original validation. The assay was applicable to all chemical categories tested in this project and its performance was not limited to the particular driver of the classification. In addition to the existing prediction model for dichotomous categorization, a new prediction model for Cat 1 is suggested. Copyright © 2017. Published by Elsevier Ltd.

LPT. Low power test (TAN640 and641) sections. Referent drawing is ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

LPT. Low power test (TAN-640 and-641) sections. Referent drawing is HAER ID-33-E-292. Section A shows cable tunnel between reactor cells and control room. Bridge crane, roof, ladder details. Ralph M. Parsons 1229-12 ANP/GE-7-640-A-3. November 1956. Approved by INEEL Classification Office for public release. INEEL index code no. 038-0640-00-693-107276 - Idaho National Engineering Laboratory, Test Area North, Scoville, Butte County, ID

NASIS data base management system - IBM 360/370 OS MVT implementation. 5: Retrieval command system reference manual

NASA Technical Reports Server (NTRS)

1973-01-01

The retrieval command subsystem reference manual for the NASA Aerospace Safety Information System (NASIS) is presented. The output oriented classification of retrieval commands provides the user with the ability to review a set of data items for verification or inspection as a typewriter or CRT terminal and to print a set of data on a remote printer. Predefined and user-definable data formatting are available for both output media.

Pressure-flow characteristics of normal and disordered esophageal motor patterns.

PubMed

Singendonk, Maartje M J; Kritas, Stamatiki; Cock, Charles; Ferris, Lara F; McCall, Lisa; Rommel, Nathalie; van Wijk, Michiel P; Benninga, Marc A; Moore, David; Omari, Taher I

2015-03-01

To perform pressure-flow analysis (PFA) in a cohort of pediatric patients who were referred for diagnostic manometric investigation. PFA was performed using purpose designed Matlab-based software. The pressure-flow index (PFI), a composite measure of bolus pressurization relative to flow and the impedance ratio, a measure of the extent of bolus clearance failure were calculated. Tracings of 76 pediatric patients (32 males; 9.1 ± 0.7 years) and 25 healthy adult controls (7 males; 36.1 ± 2.2 years) were analyzed. Patients mostly had normal motility (50%) or a category 4 disorder and usually weak peristalsis (31.5%) according to the Chicago Classification. PFA of healthy controls defined reference ranges for PFI ≤142 and impedance ratio ≤0.49. Pediatric patients with pressure-flow (PF) characteristics within these limits had normal motility (62%), most patients with PF characteristics outside these limits also had an abnormal Chicago Classification (61%). Patients with high PFI and disordered motor patterns all had esophagogastric junction outflow obstruction. Disordered PF characteristics are associated with disordered esophageal motor patterns. By defining the degree of over-pressurization and/or extent of clearance failure, PFA may be a useful adjunct to esophageal pressure topography-based classification. Copyright © 2015 Elsevier Inc. All rights reserved.

Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning

PubMed Central

Wu, Jiayi; Ma, Yong-Bei; Congdon, Charles; Brett, Bevin; Chen, Shuobing; Xu, Yaofang; Ouyang, Qi

2017-01-01

Structural heterogeneity in single-particle cryo-electron microscopy (cryo-EM) data represents a major challenge for high-resolution structure determination. Unsupervised classification may serve as the first step in the assessment of structural heterogeneity. However, traditional algorithms for unsupervised classification, such as K-means clustering and maximum likelihood optimization, may classify images into wrong classes with decreasing signal-to-noise-ratio (SNR) in the image data, yet demand increased computational costs. Overcoming these limitations requires further development of clustering algorithms for high-performance cryo-EM data processing. Here we introduce an unsupervised single-particle clustering algorithm derived from a statistical manifold learning framework called generative topographic mapping (GTM). We show that unsupervised GTM clustering improves classification accuracy by about 40% in the absence of input references for data with lower SNRs. Applications to several experimental datasets suggest that our algorithm can detect subtle structural differences among classes via a hierarchical clustering strategy. After code optimization over a high-performance computing (HPC) environment, our software implementation was able to generate thousands of reference-free class averages within hours in a massively parallel fashion, which allows a significant improvement on ab initio 3D reconstruction and assists in the computational purification of homogeneous datasets for high-resolution visualization. PMID:28786986

Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning.

PubMed

Wu, Jiayi; Ma, Yong-Bei; Congdon, Charles; Brett, Bevin; Chen, Shuobing; Xu, Yaofang; Ouyang, Qi; Mao, Youdong

2017-01-01

Structural heterogeneity in single-particle cryo-electron microscopy (cryo-EM) data represents a major challenge for high-resolution structure determination. Unsupervised classification may serve as the first step in the assessment of structural heterogeneity. However, traditional algorithms for unsupervised classification, such as K-means clustering and maximum likelihood optimization, may classify images into wrong classes with decreasing signal-to-noise-ratio (SNR) in the image data, yet demand increased computational costs. Overcoming these limitations requires further development of clustering algorithms for high-performance cryo-EM data processing. Here we introduce an unsupervised single-particle clustering algorithm derived from a statistical manifold learning framework called generative topographic mapping (GTM). We show that unsupervised GTM clustering improves classification accuracy by about 40% in the absence of input references for data with lower SNRs. Applications to several experimental datasets suggest that our algorithm can detect subtle structural differences among classes via a hierarchical clustering strategy. After code optimization over a high-performance computing (HPC) environment, our software implementation was able to generate thousands of reference-free class averages within hours in a massively parallel fashion, which allows a significant improvement on ab initio 3D reconstruction and assists in the computational purification of homogeneous datasets for high-resolution visualization.

The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013.

PubMed

Hastings, Janna; de Matos, Paula; Dekker, Adriano; Ennis, Marcus; Harsha, Bhavana; Kale, Namrata; Muthukrishnan, Venkatesh; Owen, Gareth; Turner, Steve; Williams, Mark; Steinbeck, Christoph

2013-01-01

ChEBI (http://www.ebi.ac.uk/chebi) is a database and ontology of chemical entities of biological interest. Over the past few years, ChEBI has continued to grow steadily in content, and has added several new features. In addition to incorporating all user-requested compounds, our annotation efforts have emphasized immunology, natural products and metabolites in many species. All database entries are now 'is_a' classified within the ontology, meaning that all of the chemicals are available to semantic reasoning tools that harness the classification hierarchy. We have completely aligned the ontology with the Open Biomedical Ontologies (OBO) Foundry-recommended upper level Basic Formal Ontology. Furthermore, we have aligned our chemical classification with the classification of chemical-involving processes in the Gene Ontology (GO), and as a result of this effort, the majority of chemical-involving processes in GO are now defined in terms of the ChEBI entities that participate in them. This effort necessitated incorporating many additional biologically relevant compounds. We have incorporated additional data types including reference citations, and the species and component for metabolites. Finally, our website and web services have had several enhancements, most notably the provision of a dynamic new interactive graph-based ontology visualization.

48 CFR 204.7101 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 48 Federal Acquisition Regulations System 3 2013-10-01 2013-10-01 false Definitions. 204.7101... OF DEFENSE GENERAL ADMINISTRATIVE MATTERS Uniform Contract Line Item Numbering System 204.7101 Definitions. Accounting classification reference number (ACRN) means any combination of a two position alpha...

48 CFR 204.7101 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 3 2011-10-01 2011-10-01 false Definitions. 204.7101... OF DEFENSE GENERAL ADMINISTRATIVE MATTERS Uniform Contract Line Item Numbering System 204.7101 Definitions. Accounting classification reference number (ACRN) means any combination of a two position alpha...

A NULL MODEL FOR THE EXPECTED MACROINVERTEBRATE ASSEMBLAGE IN STREAMS

EPA Science Inventory

Predictive models such as River InVertebrate Prediction And Classification System (RIVPACS) and AUStralian RIVer Assessment System (AUSRIVAS) model the natural variation across geographic regions in the occurrences of macroinvertebrate taxa in data from streams that are in refere...

40 CFR 11.4 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 1 2010-07-01 2010-07-01 false Definitions. 11.4 Section 11.4 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY GENERAL SECURITY CLASSIFICATION REGULATIONS.... Confidential refers to that national security information or material which requires protection. The test for...

5 CFR 9901.204 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Administrative Personnel DEPARTMENT OF DEFENSE HUMAN RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM... meaning given that term in § 9901.103. Classification, also referred to as job evaluation, means the...

[Vinyl chloride and 1,2-dichloroethane: classification and assessment of carcinogenicity, guidelines, threshold values, and standards developed by national and international entities, organizations, and agencies].

PubMed

Binetti, R; Costamagna, F M; Marcello, I

2001-01-01

International, national and regulatory classification, evaluation, guidelines and occupational exposure values regarding vinyl chloride and 1,2-dichloroethane, carried out by European Union (EU). Environmental Protection Agency (US EPA), International Agency for Research on Cancer (IARC), Italian National Advisory Toxicological Committee (CCTN), Occupational Safety and Health Administration (OSHA), World Health Organization (WHO), National Institute for Occupational Safety and Health (NIOSH), American Conference of Governmental Industrial Hygienists (ACGIH) and other institutions, have been considered with particular reference to the carcinogenic effects. Moreover information is reported in support of classification and evaluation and a short historical review since early 1970s, when first evidence that occupational exposure to VC could lead to angiosarcoma was published.

A multiple-point spatially weighted k-NN method for object-based classification

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Jing, Linhai; Li, Hui; Atkinson, Peter M.

2016-10-01

Object-based classification, commonly referred to as object-based image analysis (OBIA), is now commonly regarded as able to produce more appealing classification maps, often of greater accuracy, than pixel-based classification and its application is now widespread. Therefore, improvement of OBIA using spatial techniques is of great interest. In this paper, multiple-point statistics (MPS) is proposed for object-based classification enhancement in the form of a new multiple-point k-nearest neighbour (k-NN) classification method (MPk-NN). The proposed method first utilises a training image derived from a pre-classified map to characterise the spatial correlation between multiple points of land cover classes. The MPS borrows spatial structures from other parts of the training image, and then incorporates this spatial information, in the form of multiple-point probabilities, into the k-NN classifier. Two satellite sensor images with a fine spatial resolution were selected to evaluate the new method. One is an IKONOS image of the Beijing urban area and the other is a WorldView-2 image of the Wolong mountainous area, in China. The images were object-based classified using the MPk-NN method and several alternatives, including the k-NN, the geostatistically weighted k-NN, the Bayesian method, the decision tree classifier (DTC), and the support vector machine classifier (SVM). It was demonstrated that the new spatial weighting based on MPS can achieve greater classification accuracy relative to the alternatives and it is, thus, recommended as appropriate for object-based classification.

An enhanced forest classification scheme for modeling vegetation-climate interactions based on national forest inventory data

NASA Astrophysics Data System (ADS)

Majasalmi, Titta; Eisner, Stephanie; Astrup, Rasmus; Fridman, Jonas; Bright, Ryan M.

2018-01-01

Forest management affects the distribution of tree species and the age class of a forest, shaping its overall structure and functioning and in turn the surface-atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management, good accounts of forest structure are necessary. Here, using Fennoscandia as a case study, we make use of Fennoscandic National Forest Inventory (NFI) data to systematically classify forest cover into groups of similar aboveground forest structure. An enhanced forest classification scheme and related lookup table (LUT) of key forest structural attributes (i.e., maximum growing season leaf area index (LAImax), basal-area-weighted mean tree height, tree crown length, and total stem volume) was developed, and the classification was applied for multisource NFI (MS-NFI) maps from Norway, Sweden, and Finland. To provide a complete surface representation, our product was integrated with the European Space Agency Climate Change Initiative Land Cover (ESA CCI LC) map of present day land cover (v.2.0.7). Comparison of the ESA LC and our enhanced LC products (https://doi.org/10.21350/7zZEy5w3) showed that forest extent notably (κ = 0.55, accuracy 0.64) differed between the two products. To demonstrate the potential of our enhanced LC product to improve the description of the maximum growing season LAI (LAImax) of managed forests in Fennoscandia, we compared our LAImax map with reference LAImax maps created using the ESA LC product (and related cross-walking table) and PFT-dependent LAImax values used in three leading land models. Comparison of the LAImax maps showed that our product provides a spatially more realistic description of LAImax in managed Fennoscandian forests compared to reference maps. This study presents an approach to account for the transient nature of forest structural attributes due to human intervention in different land models.

Using the International Classification of Functioning, Disability and Health (ICF) to describe children referred to special care or paediatric dental services.

PubMed

Faulks, Denise; Norderyd, Johanna; Molina, Gustavo; Macgiolla Phadraig, Caoimhin; Scagnet, Gabriela; Eschevins, Caroline; Hennequin, Martine

2013-01-01

Children in dentistry are traditionally described in terms of medical diagnosis and prevalence of oral disease. This approach gives little information regarding a child's capacity to maintain oral health or regarding the social determinants of oral health. The biopsychosocial approach, embodied in the International Classification of Functioning, Disability and Health - Child and Youth version (ICF-CY) (WHO), provides a wider picture of a child's real-life experience, but practical tools for the application of this model are lacking. This article describes the preliminary empirical study necessary for development of such a tool - an ICF-CY Core Set for Oral Health. An ICF-CY questionnaire was used to identify the medical, functional, social and environmental context of 218 children and adolescents referred to special care or paediatric dental services in France, Sweden, Argentina and Ireland (mean age 8 years ± 3.6 yrs). International Classification of Disease (ICD-10) diagnoses included disorders of the nervous system (26.1%), Down syndrome (22.0%), mental retardation (17.0%), autistic disorders (16.1%), and dental anxiety alone (11.0%). The most frequently impaired items in the ICF Body functions domain were 'Intellectual functions', 'High-level cognitive functions', and 'Attention functions'. In the Activities and Participation domain, participation restriction was frequently reported for 25 items including 'Handling stress', 'Caring for body parts', 'Looking after one's health' and 'Speaking'. In the Environment domain, facilitating items included 'Support of friends', 'Attitude of friends' and 'Support of immediate family'. One item was reported as an environmental barrier - 'Societal attitudes'. The ICF-CY can be used to highlight common profiles of functioning, activities, participation and environment shared by children in relation to oral health, despite widely differing medical, social and geographical contexts. The results of this empirical study might be used to develop an ICF-CY Core Set for Oral Health - a holistic but practical tool for clinical and epidemiological use.

Survey on large scale system control methods

NASA Technical Reports Server (NTRS)

Mercadal, Mathieu

1987-01-01

The problem inherent to large scale systems such as power network, communication network and economic or ecological systems were studied. The increase in size and flexibility of future spacecraft has put those dynamical systems into the category of large scale systems, and tools specific to the class of large systems are being sought to design control systems that can guarantee more stability and better performance. Among several survey papers, reference was found to a thorough investigation on decentralized control methods. Especially helpful was the classification made of the different existing approaches to deal with large scale systems. A very similar classification is used, even though the papers surveyed are somehow different from the ones reviewed in other papers. Special attention is brought to the applicability of the existing methods to controlling large mechanical systems like large space structures. Some recent developments are added to this survey.

Object recognition through a multi-mode fiber

NASA Astrophysics Data System (ADS)

Takagi, Ryosuke; Horisaki, Ryoichi; Tanida, Jun

2017-04-01

We present a method of recognizing an object through a multi-mode fiber. A number of speckle patterns transmitted through a multi-mode fiber are provided to a classifier based on machine learning. We experimentally demonstrated binary classification of face and non-face targets based on the method. The measurement process of the experimental setup was random and nonlinear because a multi-mode fiber is a typical strongly scattering medium and any reference light was not used in our setup. Comparisons between three supervised learning methods, support vector machine, adaptive boosting, and neural network, are also provided. All of those learning methods achieved high accuracy rates at about 90% for the classification. The approach presented here can realize a compact and smart optical sensor. It is practically useful for medical applications, such as endoscopy. Also our study indicated a promising utilization of artificial intelligence, which has rapidly progressed, for reducing optical and computational costs in optical sensing systems.

Classification of Chemicals Based On Structured Toxicity ...

EPA Pesticide Factsheets

Thirty years and millions of dollars worth of pesticide registration toxicity studies, historically stored as hardcopy and scanned documents, have been digitized into highly standardized and structured toxicity data within the Toxicity Reference Database (ToxRefDB). Toxicity-based classifications of chemicals were performed as a model application of ToxRefDB. These endpoints will ultimately provide the anchoring toxicity information for the development of predictive models and biological signatures utilizing in vitro assay data. Utilizing query and structured data mining approaches, toxicity profiles were uniformly generated for greater than 300 chemicals. Based on observation rate, species concordance and regulatory relevance, individual and aggregated effects have been selected to classify the chemicals providing a set of predictable endpoints. ToxRefDB exhibits the utility of transforming unstructured toxicity data into structured data and, furthermore, into computable outputs, and serves as a model for applying such data to address modern toxicological problems.

Eye movement identification based on accumulated time feature

NASA Astrophysics Data System (ADS)

Guo, Baobao; Wu, Qiang; Sun, Jiande; Yan, Hua

2017-06-01

Eye movement is a new kind of feature for biometrical recognition, it has many advantages compared with other features such as fingerprint, face, and iris. It is not only a sort of static characteristics, but also a combination of brain activity and muscle behavior, which makes it effective to prevent spoofing attack. In addition, eye movements can be incorporated with faces, iris and other features recorded from the face region into multimode systems. In this paper, we do an exploring study on eye movement identification based on the eye movement datasets provided by Komogortsev et al. in 2011 with different classification methods. The time of saccade and fixation are extracted from the eye movement data as the eye movement features. Furthermore, the performance analysis was conducted on different classification methods such as the BP, RBF, ELMAN and SVM in order to provide a reference to the future research in this field.

Synopsis of Phyllosticta in China

PubMed Central

Zhang, Ke; Shivas, Roger G.; Cai, Lei

2015-01-01

The generic concept of Phyllosticta has undergone substantial changes since its establishment in 1818. The existence of conidia with a mucilaginous sheath and an apical appendage is synapomorphic for Phyllosticta species, which has been shown in recent molecular phylogenetic studies. Thus a natural classification of Phyllosticta species should emphasize above morphological characters. Many names in Phyllosticta, both published in the scientific literatures and in publically accessible databases, need updating. In China, more than 200 species names in Phyllosticta have been recorded, of which, 158 species names are reviewed here based on their morphological descriptions and molecular data. Only 20 species of Phyllosticta are accepted from China. Other records of Phyllosticta refer to Phoma (89 records), Asteromella (14 records), Boeremia (9 records), Phomopsis (7 records) and Microsphaeropsis (1 record), with 19 names of uncertain generic classification. This work demonstrates an urgent need for the re-assessment of records of Phyllosticta worldwide. PMID:26000199

Plant landscape design simulating natural community by using AHP method based on TWINSPAN classification

NASA Astrophysics Data System (ADS)

Wang, Li Han

2018-06-01

Taking the forest vegetation in Zijin Mountain (Purple Mountain) Area of Nanjing as the research object, based on the simulation natural and semi natural plant communities, the systematic research on the construction of Nanjing regional plant landscape is carried out by the method such as literature and theory, investigation and evaluation, discussion and reference. On the basis of TWINSPAN classification, the species composition (flora and geographical composition), community structure, species diversity, interspecific relationship and ecological niche of Zijin Mountain natural vegetation are studied and analyzed as a basis for simulation design and planting. Then, from the three levels of ornamental value, resource development and utilization potential and biological characteristics, a comprehensive evaluation system used for wild ornamental plant resources in Zijin Mountain is built. Finally, some suggestions on the planting species of deep forest vegetation in Zijin Mountain are put forward.

Feature Relevance Assessment of Multispectral Airborne LIDAR Data for Tree Species Classification

NASA Astrophysics Data System (ADS)

Amiri, N.; Heurich, M.; Krzystek, P.; Skidmore, A. K.

2018-04-01

The presented experiment investigates the potential of Multispectral Laser Scanning (MLS) point clouds for single tree species classification. The basic idea is to simulate a MLS sensor by combining two different Lidar sensors providing three different wavelngthes. The available data were acquired in the summer 2016 at the same date in a leaf-on condition with an average point density of 37 points/m2. For the purpose of classification, we segmented the combined 3D point clouds consisiting of three different spectral channels into 3D clusters using Normalized Cut segmentation approach. Then, we extracted four group of features from the 3D point cloud space. Once a varity of features has been extracted, we applied forward stepwise feature selection in order to reduce the number of irrelevant or redundant features. For the classification, we used multinomial logestic regression with L1 regularization. Our study is conducted using 586 ground measured single trees from 20 sample plots in the Bavarian Forest National Park, in Germany. Due to lack of reference data for some rare species, we focused on four classes of species. The results show an improvement between 4-10 pp for the tree species classification by using MLS data in comparison to a single wavelength based approach. A cross validated (15-fold) accuracy of 0.75 can be achieved when all feature sets from three different spectral channels are used. Our results cleary indicates that the use of MLS point clouds has great potential to improve detailed forest species mapping.

Use of field reflectance data for crop mapping using airborne hyperspectral image

NASA Astrophysics Data System (ADS)

Nidamanuri, Rama Rao; Zbell, Bernd

2011-09-01

Recent developments in hyperspectral remote sensing technologies enable acquisition of image with high spectral resolution, which is typical to the laboratory or in situ reflectance measurements. There has been an increasing interest in the utilization of in situ reference reflectance spectra for rapid and repeated mapping of various surface features. Here we examined the prospect of classifying airborne hyperspectral image using field reflectance spectra as the training data for crop mapping. Canopy level field reflectance measurements of some important agricultural crops, i.e. alfalfa, winter barley, winter rape, winter rye, and winter wheat collected during four consecutive growing seasons are used for the classification of a HyMAP image acquired for a separate location by (1) mixture tuned matched filtering (MTMF), (2) spectral feature fitting (SFF), and (3) spectral angle mapper (SAM) methods. In order to answer a general research question "what is the prospect of using independent reference reflectance spectra for image classification", while focussing on the crop classification, the results indicate distinct aspects. On the one hand, field reflectance spectra of winter rape and alfalfa demonstrate excellent crop discrimination and spectral matching with the image across the growing seasons. On the other hand, significant spectral confusion detected among the winter barley, winter rye, and winter wheat rule out the possibility of existence of a meaningful spectral matching between field reflectance spectra and image. While supporting the current notion of "non-existence of characteristic reflectance spectral signatures for vegetation", results indicate that there exist some crops whose spectral signatures are similar to characteristic spectral signatures with possibility of using them in image classification.

From comparison to classification: a cortical tool for boosting perception.

PubMed

Nahum, Mor; Daikhin, Luba; Lubin, Yedida; Cohen, Yamit; Ahissar, Merav

2010-01-20

Humans are much better in relative than in absolute judgments. This common assertion is based on findings that discrimination thresholds are much lower when measured with methods that allow interstimuli comparisons than when measured with methods that require classification of one stimulus at a time and are hence sensitive to memory load. We now challenged this notion by measuring discrimination thresholds and evoked potentials while listeners performed a two-tone frequency discrimination task. We tested various protocols that differed in the pattern of cross-trial tone repetition. We found that best performance was achieved only when listeners effectively used cross-trial repetition to avoid interstimulus comparisons with the repeated reference tone. Instead, they classified one tone, the nonreference tone, as either high or low by comparing it with a recently formed internal reference. Listeners were not aware of the switch from interstimulus comparison to classification. Its successful use was revealed by the conjunction of improved behavioral performance and an event-related potential component (P3), indicating an implicit perceptual decision, which followed the nonreference tone in each trial. Interestingly, tone repetition itself did not suffice for the switch, implying that the bottleneck to discrimination does not reside at the lower, sensory stage. Rather, the temporal consistency of repetition was important, suggesting the involvement of higher-level mechanisms with longer time constants. These findings suggest that classification is based on more automatic and accurate mechanisms than interstimulus comparisons and that the ability to effectively use them depends on a dynamic interplay between higher- and lower-level cortical mechanisms.

CrossLink: a novel method for cross-condition classification of cancer subtypes.

PubMed

Ma, Chifeng; Sastry, Konduru S; Flore, Mario; Gehani, Salah; Al-Bozom, Issam; Feng, Yusheng; Serpedin, Erchin; Chouchane, Lotfi; Chen, Yidong; Huang, Yufei

2016-08-22

We considered the prediction of cancer classes (e.g. subtypes) using patient gene expression profiles that contain both systematic and condition-specific biases when compared with the training reference dataset. The conventional normalization-based approaches cannot guarantee that the gene signatures in the reference and prediction datasets always have the same distribution for all different conditions as the class-specific gene signatures change with the condition. Therefore, the trained classifier would work well under one condition but not under another. To address the problem of current normalization approaches, we propose a novel algorithm called CrossLink (CL). CL recognizes that there is no universal, condition-independent normalization mapping of signatures. In contrast, it exploits the fact that the signature is unique to its associated class under any condition and thus employs an unsupervised clustering algorithm to discover this unique signature. We assessed the performance of CL for cross-condition predictions of PAM50 subtypes of breast cancer by using a simulated dataset modeled after TCGA BRCA tumor samples with a cross-validation scheme, and datasets with known and unknown PAM50 classification. CL achieved prediction accuracy >73 %, highest among other methods we evaluated. We also applied the algorithm to a set of breast cancer tumors derived from Arabic population to assign a PAM50 classification to each tumor based on their gene expression profiles. A novel algorithm CrossLink for cross-condition prediction of cancer classes was proposed. In all test datasets, CL showed robust and consistent improvement in prediction performance over other state-of-the-art normalization and classification algorithms.

Screening for problem gambling within mental health services: a comparison of the classification accuracy of brief instruments.

PubMed

Dowling, Nicki A; Merkouris, Stephanie S; Manning, Victorian; Volberg, Rachel; Lee, Stuart J; Rodda, Simone N; Lubman, Dan I

2018-06-01

Despite the over-representation of people with gambling problems in mental health populations, there is limited information available to guide the selection of brief screening instruments within mental health services. The primary aim was to compare the classification accuracy of nine brief problem gambling screening instruments (two to five items) with a reference standard among patients accessing mental health services. The classification accuracy of nine brief screening instruments was compared with multiple cut-off scores on a reference standard. Eight mental health services in Victoria, Australia. A total of 837 patients were recruited consecutively between June 2015 and January 2016. The brief screening instruments were the Lie/Bet Questionnaire, Brief Problem Gambling Screen (BPGS) (two- to five-item versions), NODS-CLiP, NODS-CLiP2, Brief Biosocial Gambling Screen (BBGS) and NODS-PERC. The Problem Gambling Severity Index (PGSI) was the reference standard. The five-item BPGS was the only instrument displaying satisfactory classification accuracy in detecting any level of gambling problem (low-risk, moderate-risk or problem gambling) (sensitivity = 0.803, specificity = 0.982, diagnostic efficiency = 0.943). Several shorter instruments adequately detected both problem and moderate-risk, but not low-risk, gambling: two three-item instruments (NODS-CLiP, three-item BPGS) and two four-item instruments (NODS-PERC, four-item BPGS) (sensitivity = 0.854-0.966, specificity = 0.901-0.954, diagnostic efficiency = 0.908-0.941). The four-item instruments, however, did not provide any considerable advantage over the three-item instruments. Similarly, the very brief (two-item) instruments (Lie/Bet and two-item BPGS) adequately detected problem gambling (sensitivity = 0.811-0.868, specificity = 0.938-0.943, diagnostic efficiency = 0.933-0.934), but not moderate-risk or low-risk gambling. The optimal brief screening instrument for mental health services wanting to screen for any level of gambling problem is the five-item Brief Problem Gambling Screen (BPGS). Services wanting to employ a shorter instrument or to screen only for more severe gambling problems (moderate-risk/problem gambling) can employ the NODS-CLiP or the three-item BPGS. Services that are only able to accommodate a very brief instrument can employ the Lie/Bet Questionnaire or the two-item BPGS. © 2017 Society for the Study of Addiction.

Detection of artifacts from high energy bursts in neonatal EEG.

PubMed

Bhattacharyya, Sourya; Biswas, Arunava; Mukherjee, Jayanta; Majumdar, Arun Kumar; Majumdar, Bandana; Mukherjee, Suchandra; Singh, Arun Kumar

2013-11-01

Detection of non-cerebral activities or artifacts, intermixed within the background EEG, is essential to discard them from subsequent pattern analysis. The problem is much harder in neonatal EEG, where the background EEG contains spikes, waves, and rapid fluctuations in amplitude and frequency. Existing artifact detection methods are mostly limited to detect only a subset of artifacts such as ocular, muscle or power line artifacts. Few methods integrate different modules, each for detection of one specific category of artifact. Furthermore, most of the reference approaches are implemented and tested on adult EEG recordings. Direct application of those methods on neonatal EEG causes performance deterioration, due to greater pattern variation and inherent complexity. A method for detection of a wide range of artifact categories in neonatal EEG is thus required. At the same time, the method should be specific enough to preserve the background EEG information. The current study describes a feature based classification approach to detect both repetitive (generated from ECG, EMG, pulse, respiration, etc.) and transient (generated from eye blinking, eye movement, patient movement, etc.) artifacts. It focuses on artifact detection within high energy burst patterns, instead of detecting artifacts within the complete background EEG with wide pattern variation. The objective is to find true burst patterns, which can later be used to identify the Burst-Suppression (BS) pattern, which is commonly observed during newborn seizure. Such selective artifact detection is proven to be more sensitive to artifacts and specific to bursts, compared to the existing artifact detection approaches applied on the complete background EEG. Several time domain, frequency domain, statistical features, and features generated by wavelet decomposition are analyzed to model the proposed bi-classification between burst and artifact segments. A feature selection method is also applied to select the feature subset producing highest classification accuracy. The suggested feature based classification method is executed using our recorded neonatal EEG dataset, consisting of burst and artifact segments. We obtain 78% sensitivity and 72% specificity as the accuracy measures. The accuracy obtained using the proposed method is found to be about 20% higher than that of the reference approaches. Joint use of the proposed method with our previous work on burst detection outperforms reference methods on simultaneous burst and artifact detection. As the proposed method supports detection of a wide range of artifact patterns, it can be improved to incorporate the detection of artifacts within other seizure patterns and background EEG information as well. © 2013 Elsevier Ltd. All rights reserved.

Assessing gross motor development of Brazilian infants.

PubMed

Gontijo, Ana Paula Bensemann; de Castro Magalhães, Lívia; Guerra, Miriam Queiroz Faria

2014-01-01

To determine whether the Alberta Infant Motor Scale (AIMS) requires reference values specific for Brazilian infants. A total of 660 (330 girls) healthy full-term infants from Belo Horizonte were assessed using the AIMS. Scores and percentile curves were compared with the Canadian reference values. Differences were found in the 5th percentile (9-<10 and 10-<11 months) and the 10th percentile (4-<5, 9-<10, and 10-<11 months) curves. No significant differences were found between sexes on the basis of the economic classification or the criteria of the Human Development Index. Primarily because of the corrections made to the 5th and 10th percentile curves, we recommend the use of the Brazilian infant data curves reported here for further studies conducted in Brazil. Because the Human Development Index of Belo Horizonte is similar to that for Brazil as a whole, the results of this study should be relevant for clinicians throughout Brazil.

Automatic Classification of Protein Structure Using the Maximum Contact Map Overlap Metric

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andonov, Rumen; Djidjev, Hristo Nikolov; Klau, Gunnar W.

In this paper, we propose a new distance measure for comparing two protein structures based on their contact map representations. We show that our novel measure, which we refer to as the maximum contact map overlap (max-CMO) metric, satisfies all properties of a metric on the space of protein representations. Having a metric in that space allows one to avoid pairwise comparisons on the entire database and, thus, to significantly accelerate exploring the protein space compared to no-metric spaces. We show on a gold standard superfamily classification benchmark set of 6759 proteins that our exact k-nearest neighbor (k-NN) scheme classifiesmore » up to 224 out of 236 queries correctly and on a larger, extended version of the benchmark with 60; 850 additional structures, up to 1361 out of 1369 queries. Finally, our k-NN classification thus provides a promising approach for the automatic classification of protein structures based on flexible contact map overlap alignments.« less

Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT

PubMed Central

Nelson, Scott D; Parker, Jaqui; Lario, Robert; Winnenburg, Rainer; Erlbaum, Mark S.; Lincoln, Michael J.; Bodenreider, Olivier

2018-01-01

Interoperability among medication classification systems is known to be limited. We investigated the mapping of the Established Pharmacologic Classes (EPCs) to SNOMED CT. We compared lexical and instance-based methods to an expert-reviewed reference standard to evaluate contributions of these methods. Of the 543 EPCs, 284 had an equivalent SNOMED CT class, 205 were more specific, and 54 could not be mapped. Precision, recall, and F1 score were 0.416, 0.620, and 0.498 for lexical mapping and 0.616, 0.504, and 0.554 for instance-based mapping. Each automatic method has strengths, weaknesses, and unique contributions in mapping between medication classification systems. In our experience, it was beneficial to consider the mapping provided by both automated methods for identifying potential matches, gaps, inconsistencies, and opportunities for quality improvement between classifications. However, manual review by subject matter experts is still needed to select the most relevant mappings. PMID:29295234

The use and abuse of standard stars

NASA Astrophysics Data System (ADS)

Garrison, R. F.

The 'mandate' of classification systems is examined with reference to spectral classification. In using a classification system, it is of the greatest importance to be aware of why it was created, how it was constructed, what its useful limits are, how it has evolved, and what credibility it has achieved in practice . . . all of which constitute the mandate of the system. In the particular case of the MK system of spectral classification, types are defined by the standard stars. They can be calibrated, and the calibration may evolve with time, but the types are relatively stable because they are defined by the standards. The autonomy of this powerful system is crucial to its success, but some astronomers do not understand the importance of this distinction. Recent suggestions to change the spectral type of the sun show an ignorance of the way the system works. The confrontation and complementary use of autonomous systems yield information which is not contained in any individual system.

Virus Database and Online Inquiry System Based on Natural Vectors.

PubMed

Dong, Rui; Zheng, Hui; Tian, Kun; Yau, Shek-Chung; Mao, Weiguang; Yu, Wenping; Yin, Changchuan; Yu, Chenglong; He, Rong Lucy; Yang, Jie; Yau, Stephen St

2017-01-01

We construct a virus database called VirusDB (http://yaulab.math.tsinghua.edu.cn/VirusDB/) and an online inquiry system to serve people who are interested in viral classification and prediction. The database stores all viral genomes, their corresponding natural vectors, and the classification information of the single/multiple-segmented viral reference sequences downloaded from National Center for Biotechnology Information. The online inquiry system serves the purpose of computing natural vectors and their distances based on submitted genomes, providing an online interface for accessing and using the database for viral classification and prediction, and back-end processes for automatic and manual updating of database content to synchronize with GenBank. Submitted genomes data in FASTA format will be carried out and the prediction results with 5 closest neighbors and their classifications will be returned by email. Considering the one-to-one correspondence between sequence and natural vector, time efficiency, and high accuracy, natural vector is a significant advance compared with alignment methods, which makes VirusDB a useful database in further research.

Automatic Classification of Protein Structure Using the Maximum Contact Map Overlap Metric

DOE PAGES

Andonov, Rumen; Djidjev, Hristo Nikolov; Klau, Gunnar W.; ...

2015-10-09

In this paper, we propose a new distance measure for comparing two protein structures based on their contact map representations. We show that our novel measure, which we refer to as the maximum contact map overlap (max-CMO) metric, satisfies all properties of a metric on the space of protein representations. Having a metric in that space allows one to avoid pairwise comparisons on the entire database and, thus, to significantly accelerate exploring the protein space compared to no-metric spaces. We show on a gold standard superfamily classification benchmark set of 6759 proteins that our exact k-nearest neighbor (k-NN) scheme classifiesmore » up to 224 out of 236 queries correctly and on a larger, extended version of the benchmark with 60; 850 additional structures, up to 1361 out of 1369 queries. Finally, our k-NN classification thus provides a promising approach for the automatic classification of protein structures based on flexible contact map overlap alignments.« less

Discriminative least squares regression for multiclass classification and feature selection.

PubMed

Xiang, Shiming; Nie, Feiping; Meng, Gaofeng; Pan, Chunhong; Zhang, Changshui

2012-11-01

This paper presents a framework of discriminative least squares regression (LSR) for multiclass classification and feature selection. The core idea is to enlarge the distance between different classes under the conceptual framework of LSR. First, a technique called ε-dragging is introduced to force the regression targets of different classes moving along opposite directions such that the distances between classes can be enlarged. Then, the ε-draggings are integrated into the LSR model for multiclass classification. Our learning framework, referred to as discriminative LSR, has a compact model form, where there is no need to train two-class machines that are independent of each other. With its compact form, this model can be naturally extended for feature selection. This goal is achieved in terms of L2,1 norm of matrix, generating a sparse learning model for feature selection. The model for multiclass classification and its extension for feature selection are finally solved elegantly and efficiently. Experimental evaluation over a range of benchmark datasets indicates the validity of our method.

A proposal for the annotation of recurrent colorectal cancer: the 'Sheffield classification'.

PubMed

Majeed, A W; Shorthouse, A J; Blakeborough, A; Bird, N C

2011-11-01

Current classification systems of large bowel cancer only refer to metastatic disease as M0, M1 or Mx. Recurrent colorectal cancer primarily occurs in the liver, lungs, nodes or peritoneum. The management of each of these sites of recurrence has made significant advances and each is a subspecialty in its own right. The aim of this paper was to devise a classification system which accurately describes the site and extent of metastatic spread. An amendment of the current system is proposed in which liver, lung and peritoneal metastases are annotated by 'Liv 0,1', 'Pul 0,1' and 'Per 0,1' in describing the primary presentation. These are then subclassified, taking into account the chronology, size, number and geographical distribution of metastatic disease or logoregional recurrence and its K-Ras status. This discussion document proposes a classification system which is logical and simple to use. We plan to validate it prospectively. © 2011 The Authors. Colorectal Disease © 2011 The Association of Coloproctology of Great Britain and Ireland.

Classification Algorithms for Big Data Analysis, a Map Reduce Approach

NASA Astrophysics Data System (ADS)

Ayma, V. A.; Ferreira, R. S.; Happ, P.; Oliveira, D.; Feitosa, R.; Costa, G.; Plaza, A.; Gamba, P.

2015-03-01

Since many years ago, the scientific community is concerned about how to increase the accuracy of different classification methods, and major achievements have been made so far. Besides this issue, the increasing amount of data that is being generated every day by remote sensors raises more challenges to be overcome. In this work, a tool within the scope of InterIMAGE Cloud Platform (ICP), which is an open-source, distributed framework for automatic image interpretation, is presented. The tool, named ICP: Data Mining Package, is able to perform supervised classification procedures on huge amounts of data, usually referred as big data, on a distributed infrastructure using Hadoop MapReduce. The tool has four classification algorithms implemented, taken from WEKA's machine learning library, namely: Decision Trees, Naïve Bayes, Random Forest and Support Vector Machines (SVM). The results of an experimental analysis using a SVM classifier on data sets of different sizes for different cluster configurations demonstrates the potential of the tool, as well as aspects that affect its performance.

Cardiovascular, diabetes, and cancer strips: evidences, mechanisms, and classifications

PubMed Central

Wu, Qing-Hua; Hu, Da-Yi

2014-01-01

Objectives To report and name firstly that there are cardiovascular disease (CVD), diabetes mellitus (DM) and cancers (CDC) strips; and disclose their mechanisms, classifications, and clinical significances. Study design Narrative and systematic review study and interpretive analysis. Methods Data sources and study selection: to collect and present related evidences on CDC strips from evidence-based, open-access, both Chinese- and English-language literatures in recent 10 years on clinical trials from PubMed according to keywords “CVD, DM and cancers” as well as authors’ extensive clinical experience with the treatment of more than fifty thousands of patients with CVD, diabetes and cancers over the past decades, and analyze their related mechanisms and categories which based on authors’ previous works. Data extraction: data were mainly extracted from 48 articles which are listed in the reference section of this review. Qualitative, quantitative and mixed data were included, narratively and systematically reviewed. Results With several conceptual and technical breakthrough, authors present related evidences on CDC strips, these are, CVD and DM, DM and cancers, cancers and CVD linked, respectively; And “Bad SEED” +/– “bad soil” theory or doctrine may explain this phenomenon due to “internal environmental injure, abnormal or unbalance” in human body resulting from the role of risk factors (RFs) related multi-pathways and multi-targets, which including organ & tissue (e.g., vascular-specific), cell and gene-based mechanisms. Their classifications include main strips/type B, and Branches/type A as showed by tables and figures in this article. Conclusions There are CDC strips and related mechanisms and classifications. CDC strips may help us to understand, prevent, and control related common non-communicable diseases (NCDs) as well as these high risk strips. PMID:25276377

Analysis of Draize Eye Irritation Testing and its Prediction by Mining Publicly Available 2008–2014 REACH Data

PubMed Central

Luechtefeld, Thomas; Maertens, Alexandra; Russo, Daniel P.; Rovida, Costanza; Zhu, Hao; Hartung, Thomas

2017-01-01

Summary Public data from ECHA online dossiers on 9,801 substances encompassing 326,749 experimental key studies and additional information on classification and labeling were made computable. Eye irritation hazard, for which the rabbit Draize eye test still represents the reference method, was analyzed. Dossiers contained 9,782 Draize eye studies on 3,420 unique substances, indicating frequent retesting of substances. This allowed assessment of the test’s reproducibility based on all substances tested more than once. There was a 10% chance of a non-irritant evaluation after a prior severe-irritant result according to UN GHS classification criteria. The most reproducible outcomes were the results negative (94% reproducible) and severe eye irritant (73% reproducible). To evaluate whether other GHS categorizations predict eye irritation, we built a dataset of 5,629 substances (1,931 “irritant” and 3,698 “non-irritant”). The two best decision trees with up to three other GHS classifications resulted in balanced accuracies of 68% and 73%, i.e., in the rank order of the Draize rabbit eye test itself, but both use inhalation toxicity data (“May cause respiratory irritation”), which is not typically available. Next, a dataset of 929 substances with at least one Draize study was mapped to PubChem to compute chemical similarity using 2D conformational fingerprints and Tanimoto similarity. Using a minimum similarity of 0.7 and simple classification by the closest chemical neighbor resulted in balanced accuracy from 73% over 737 substances to 100% at a threshold of 0.975 over 41 substances. This represents a strong support of read-across and (Q)SAR approaches in this area. PMID:26863293

Semi-supervised learning for ordinal Kernel Discriminant Analysis.

PubMed

Pérez-Ortiz, M; Gutiérrez, P A; Carbonero-Ruz, M; Hervás-Martínez, C

2016-12-01

Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels are given by a user or expert (e.g. in recommendation systems). Firstly, this paper develops a new strategy for ordinal classification where both labelled and unlabelled data are used in the model construction step (a scheme which is referred to as semi-supervised learning). More specifically, the ordinal version of kernel discriminant learning is extended for this setting considering the neighbourhood information of unlabelled data, which is proposed to be computed in the feature space induced by the kernel function. Secondly, a new method for semi-supervised kernel learning is devised in the context of ordinal classification, which is combined with our developed classification strategy to optimise the kernel parameters. The experiments conducted compare 6 different approaches for semi-supervised learning in the context of ordinal classification in a battery of 30 datasets, showing (1) the good synergy of the ordinal version of discriminant analysis and the use of unlabelled data and (2) the advantage of computing distances in the feature space induced by the kernel function. Copyright © 2016 Elsevier Ltd. All rights reserved.

Proposition of novel classification approach and features for improved real-time arrhythmia monitoring.

PubMed

Kim, Yoon Jae; Heo, Jeong; Park, Kwang Suk; Kim, Sungwan

2016-08-01

Arrhythmia refers to a group of conditions in which the heartbeat is irregular, fast, or slow due to abnormal electrical activity in the heart. Some types of arrhythmia such as ventricular fibrillation may result in cardiac arrest or death. Thus, arrhythmia detection becomes an important issue, and various studies have been conducted. Additionally, an arrhythmia detection algorithm for portable devices such as mobile phones has recently been developed because of increasing interest in e-health care. This paper proposes a novel classification approach and features, which are validated for improved real-time arrhythmia monitoring. The classification approach that was employed for arrhythmia detection is based on the concept of ensemble learning and the Taguchi method and has the advantage of being accurate and computationally efficient. The electrocardiography (ECG) data for arrhythmia detection was obtained from the MIT-BIH Arrhythmia Database (n=48). A novel feature, namely the heart rate variability calculated from 5s segments of ECG, which was not considered previously, was used. The novel classification approach and feature demonstrated arrhythmia detection accuracy of 89.13%. When the same data was classified using the conventional support vector machine (SVM), the obtained accuracy was 91.69%, 88.14%, and 88.74% for Gaussian, linear, and polynomial kernels, respectively. In terms of computation time, the proposed classifier was 5821.7 times faster than conventional SVM. In conclusion, the proposed classifier and feature showed performance comparable to those of previous studies, while the computational complexity and update interval were highly reduced. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of Snyder-Dolan classification scheme to the selection of "orthogonal" columns for fast screening of illicit drugs and impurity profiling of pharmaceuticals--I. Isocratic elution.

PubMed

Fan, Wenzhe; Zhang, Yu; Carr, Peter W; Rutan, Sarah C; Dumarey, Melanie; Schellinger, Adam P; Pritts, Wayne

2009-09-18

Fourteen judiciously selected reversed phase columns were tested with 18 cationic drug solutes under the isocratic elution conditions advised in the Snyder-Dolan (S-D) hydrophobic subtraction method of column classification. The standard errors (S.E.) of the least squares regressions of logk' vs. logk'(REF) were obtained for a given column against a reference column and used to compare and classify columns based on their selectivity. The results are consistent with those obtained with a study of the 16 test solutes recommended by Snyder and Dolan. To the extent these drugs are representative, these results show that the S-D classification scheme is also generally applicable to pharmaceuticals under isocratic conditions. That is, those columns judged to be similar based on the 16 S-D solutes were similar based on the 18 drugs; furthermore those columns judged to have significantly different selectivities based on the 16 S-D probes appeared to be quite different for the drugs as well. Given that the S-D method has been used to classify more than 400 different types of reversed phases the extension to cationic drugs is a significant finding.

[Etiologic classification of cerebral infarct. Experience from a prospective data register].

PubMed

Brainin, M

1990-12-01

Most classifications of stroke include clinically heterogeneous subgroups and therefore are of limited value for comparative studies or clinical protocols. The view is held that a classification according to stroke etiology is clinically more reasonable and more consistent for therapeutic strategies. In order to determine the frequency of various etiological subgroups in a series of stroke cases, the results of the Klosterneuburger Schlaganfall-Datenbank (KSDB) are reported. This stroke registry has prospectively recorded over 300 items on all stroke cases referred to one center since March 1988. Investigation rates include CT in almost 100% and the investigation of cerebral vessels in over 90% of all cases. By applying defined etiological categories (undetermined etiology, atherosclerosis of the large craniocervical vessels, cardiogenic embolism, lacunar, primary hemorrhage, and multiple and other causes) to the first 420 patients registered within the first two years it can be shown that even with CT and neurosonology in routine use, in 29% of all cases the cause of the stroke cannot be determined. To investigate this largest subgroup by means of additional new methods as well as by investigating the long-term natural course represents an important challenge for clinical stroke research.

10 CFR 4.122 - General prohibitions against employment discrimination.

Code of Federal Regulations, 2012 CFR

2012-01-01

... form of compensation and changes in compensation; (4) Job assignments, job classifications... participate in a contractual or other relationship that has the effect of subjecting qualified handicapped applicants or employees to discrimination prohibited by this subpart. The relationships referred to in this...

10 CFR 4.122 - General prohibitions against employment discrimination.

Code of Federal Regulations, 2011 CFR

2011-01-01

... form of compensation and changes in compensation; (4) Job assignments, job classifications... participate in a contractual or other relationship that has the effect of subjecting qualified handicapped applicants or employees to discrimination prohibited by this subpart. The relationships referred to in this...

National Plant Diagnostic Network, Taxonomic training videos: Introduction to Aphids - Part 1

USDA-ARS?s Scientific Manuscript database

Training is a critical part of aphid (Hemiptera: Aphididae) identification. This video provides visual instruction on important subject areas for aphid examination and identification. Aphid topics such as classification, morphology, plant disease transmission, and references are discussed. This dis...

23 CFR 750.703 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-04-01

... classifications. (b) Erect means to construct, build, raise, assemble, place, affix, attach, create, paint, draw... frontage roads, turning roadways, or parking areas. (i) Sign, display or device, hereinafter referred to as “sign,” means an outdoor advertising sign, light, display, device, figure, painting, drawing, message...

23 CFR 750.703 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... classifications. (b) Erect means to construct, build, raise, assemble, place, affix, attach, create, paint, draw... frontage roads, turning roadways, or parking areas. (i) Sign, display or device, hereinafter referred to as “sign,” means an outdoor advertising sign, light, display, device, figure, painting, drawing, message...

23 CFR 750.703 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... classifications. (b) Erect means to construct, build, raise, assemble, place, affix, attach, create, paint, draw... frontage roads, turning roadways, or parking areas. (i) Sign, display or device, hereinafter referred to as “sign,” means an outdoor advertising sign, light, display, device, figure, painting, drawing, message...

23 CFR 750.703 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-04-01

... classifications. (b) Erect means to construct, build, raise, assemble, place, affix, attach, create, paint, draw... frontage roads, turning roadways, or parking areas. (i) Sign, display or device, hereinafter referred to as “sign,” means an outdoor advertising sign, light, display, device, figure, painting, drawing, message...

23 CFR 750.703 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-04-01

... classifications. (b) Erect means to construct, build, raise, assemble, place, affix, attach, create, paint, draw... frontage roads, turning roadways, or parking areas. (i) Sign, display or device, hereinafter referred to as “sign,” means an outdoor advertising sign, light, display, device, figure, painting, drawing, message...

Short Course in Highway Lighting.

ERIC Educational Resources Information Center

Federal Highway Administration (DOT), Washington, DC.

This course guide in highway lighting includes an overview of trends in highway lighting, illustrated information on three light sources for today's luminaires, a reference guide to lamp classification, specifications for highway lighting equipment, and instructions for calculating appropriate use. Maintenance notes on highway illumination and…

Mapping the distribution of the main host for plague in a complex landscape in Kazakhstan: An object-based approach using SPOT-5 XS, Landsat 7 ETM+, SRTM and multiple Random Forests

NASA Astrophysics Data System (ADS)

Wilschut, L. I.; Addink, E. A.; Heesterbeek, J. A. P.; Dubyanskiy, V. M.; Davis, S. A.; Laudisoit, A.; Begon, M.; Burdelov, L. A.; Atshabar, B. B.; de Jong, S. M.

2013-08-01

Plague is a zoonotic infectious disease present in great gerbil populations in Kazakhstan. Infectious disease dynamics are influenced by the spatial distribution of the carriers (hosts) of the disease. The great gerbil, the main host in our study area, lives in burrows, which can be recognized on high resolution satellite imagery. In this study, using earth observation data at various spatial scales, we map the spatial distribution of burrows in a semi-desert landscape. The study area consists of various landscape types. To evaluate whether identification of burrows by classification is possible in these landscape types, the study area was subdivided into eight landscape units, on the basis of Landsat 7 ETM+ derived Tasselled Cap Greenness and Brightness, and SRTM derived standard deviation in elevation. In the field, 904 burrows were mapped. Using two segmented 2.5 m resolution SPOT-5 XS satellite scenes, reference object sets were created. Random Forests were built for both SPOT scenes and used to classify the images. Additionally, a stratified classification was carried out, by building separate Random Forests per landscape unit. Burrows were successfully classified in all landscape units. In the ‘steppe on floodplain’ areas, classification worked best: producer's and user's accuracy in those areas reached 88% and 100%, respectively. In the ‘floodplain’ areas with a more heterogeneous vegetation cover, classification worked least well; there, accuracies were 86 and 58% respectively. Stratified classification improved the results in all landscape units where comparison was possible (four), increasing kappa coefficients by 13, 10, 9 and 1%, respectively. In this study, an innovative stratification method using high- and medium resolution imagery was applied in order to map host distribution on a large spatial scale. The burrow maps we developed will help to detect changes in the distribution of great gerbil populations and, moreover, serve as a unique empirical data set which can be used as input for epidemiological plague models. This is an important step in understanding the dynamics of plague.

Classification of anthropogenic soils by new diagnostic criteria involved in the Slovak Soil Classification System (2014)

NASA Astrophysics Data System (ADS)

Sobocká, Jaroslava; Balkovič, Juraj; Bedrna, Zoltán

2017-04-01

Anthropogenic soils can be found mostly in SUITMA areas. The issue of adequate and correct description and classification of these soils occurs very often and can result in inconsistent even in contradictory opinions. In the new version of the anthropogenic soil classification system in Slovakia some new diagnostics criteria were involved and applied for better understanding the inherent nature of these soils. The group of the former anthropogenic soils was divided following scheme of soil reference groups in the WRB 2014 (Anthrozem and Technozem). According to the new version of the Slovak anthropogenic soils classification (2014) there have been distinguished 2 groups of anthropogenic soils: 1) cultivated soils group including 2 soil types (in Slovak terminology): Kultizem and Hortizem and 2) technogenic soils group having 2 soil types: Antrozem and Technozem. Cultivated soil group represents soils developing or forming "in-situ" with diagnostic horizons characterized by human deeply influenced cultivated processes. Technogenic soil group are soils developing like "ex-situ" soils. The key features recognizing technogenic soil group are human-transported and altered material (HTAM = ex-situ aspect), and artefacts content. Diagnostic horizons (top and subsoil) were described as various material affected by physical-mechanical excavation, transportation and spread, mixing, and containing artefacts (the new diagnostic feature). Kultizems are differentiated by cultivated horizon(s) and Technozems by anthropogenic horizon(s). Cultivated horizons are mostly well-known described horizon in many scientific references. Anthropogenic horizons for Technozem are developed from the human-induced transported and altered material which origin is from the other ecological locality that adjacent area. Materials (or substrates) can consist of various material (natural, technogenic or their mixing) with thickness ≥ 60 cm. Artefacts are the second diagnostic feature which presence authenticates the "artificial origin" of the soil. Natural material contains ≤ 10 % artefacts; natural-technogenic 10-40 % artefacts; and technogenic ≥ 40 %. In the soil survey anthropogenic transported or altered layer is very simply recognizable in soil profile if it is compared with adjacent natural horizons. The classification problem is to define and distinguish not only artefacts in soil profile but recognize the origin of the material. The completed manual for these issues is missing. In the contribution, there graphically individual basic soil types of Antrozems and Technozems with some subtypes will be illustrated. Also the basic schema of classification units in Slovakia will be depicted.

Study on Spatio-Temporal Change of Ecological Land in Yellow River Delta Based on RS&GIS

NASA Astrophysics Data System (ADS)

An, GuoQiang

2018-06-01

The temporal and spatial variation of ecological land use and its current distribution were studied to provide reference for the protection of original ecological land and ecological environment in the Yellow River Delta. Using RS colour synthesis, supervised classification, unsupervised classification, vegetation index and other methods to monitor the impact of human activities on the original ecological land in the past 30 years; using GIS technology to analyse the statistical data and construct the model of original ecological land area index to study the ecological land distribution status. The results show that the boundary of original ecological land in the Yellow River Delta had been pushed toward the coastline at an average speed of 0.8km per year due to human activities. In the past 20 years, a large amount of original ecological land gradually transformed into artificial ecological land. In view of the evolution and status of ecological land in the Yellow River Delta, related local departments should adopt differentiated and focused protection measures to protect the ecological land of the Yellow River Delta.

A historical approach to scorpion studies with special reference to the 20th and 21st centuries

PubMed Central

2014-01-01

This work provides historical context about scorpion studies from the end of the 19th century to the present day. The content is mainly addressed to non-zoologists, working in research fields that embrace scorpion biology, notably to those working with venoms and toxins. The historical aspects described include academic professional scholars who worked on scorpion classification and general distribution patterns; and to a lesser extent, on studies of ecology and natural history. The aim is not to provide an exhaustive description of all scholars who in one way or another became involved with scorpions, but rather of those who greatly contributed during a given period to the research of these organisms. No critical analysis of the work of previous researchers is undertaken, but some comments are proposed to bring clarification on ‘who’s who’. Since a global consensus in relation to classification and/or distribution patterns has not been reached among modern experts, these different approaches are also presented without judgment. Consequently, distinct approaches remain open for discussion. PMID:24618067

The effects of orthoses, footwear, and walking aids on the walking ability of children and adolescents with spina bifida: A systematic review using International Classification of Functioning, Disability and Health for Children and Youth (ICF-CY) as a reference framework.

PubMed

Ivanyi, Barbara; Schoenmakers, Marja; van Veen, Natasja; Maathuis, Karel; Nollet, Frans; Nederhand, Marc

2015-12-01

To date no review has been published that analyzes the efficacy of assistive devices on the walking ability of ambulant children and adolescents with spina bifida and, differentiates between the effects of treatment on gait parameters, walking capacity, and walking performance. To review the literature for evidence of the efficacy of orthotic management, footwear, and walking aids on gait and walking outcomes in ambulant children and adolescents with spina bifida. Systematic literature review. A systematic literature search was performed to identify studies that evaluated the effect of any type of lower limb orthoses, orthopedic footwear, or walking aids in ambulant children (≤18 years old) with spina bifida. Outcome measures and treatment results for gait parameters, walking capacity, and walking performance were identified using International Classification of Functioning, Disability and Health for Children and Youth (ICF-CY) as the reference framework. Six case-crossover studies met the criteria and were included in this systematic review. Four studies provided indications of the efficacy of the ankle-foot orthosis in improving a number of kinematic and kinetic properties of gait, stride characteristics, and the oxygen cost of walking. Two studies indicated that walking with forearm crutches may have a favorable effect on gait. The evidence level of these studies was low, and none of the studies assessed the efficacy of the intervention on walking capacity and walking performance. Some data support the efficacy of using ankle-foot orthosis and crutches for gait and walking outcomes at the body functions and structures level of the ICF-CY. Potential benefits at the activities and participation level have not been investigated. This is the first evidence-based systematic review of the efficacy of assistive devices for gait and walking outcomes for children with spina bifida. The ICF-CY is used as a reference framework to differentiate the effects of treatment on gait parameters, walking capacity, and walking performance. © The International Society for Prosthetics and Orthotics 2014.

A revisitation of TRIX for trophic status assessment in the light of the European Water Framework Directive: application to Italian coastal waters.

PubMed

Pettine, Maurizio; Casentini, Barbara; Fazi, Stefano; Giovanardi, Franco; Pagnotta, Romano

2007-09-01

The trophic status classification of coastal waters at the European scale requires the availability of harmonised indicators and procedures. The composite trophic status index (TRIX) provides useful metrics for the assessment of the trophic status of coastal waters. It was originally developed for Italian coastal waters and then applied in many European seas (Adriatic, Tyrrhenian, Baltic, Black and Northern seas). The TRIX index does not fulfil the classification procedure suggested by the WFD for two reasons: (a) it is based on an absolute trophic scale without any normalization to type-specific reference conditions; (b) it makes an ex ante aggregation of biological (Chl-a) and physico-chemical (oxygen, nutrients) quality elements, instead of an ex post integration of separate evaluations of biological and subsequent chemical quality elements. A revisitation of the TRIX index in the light of the European Water Framework Directive (WFD, 2000/60/EC) and new TRIX derived tools are presented in this paper. A number of Italian coastal sites were grouped into different types based on a thorough analysis of their hydro-morphological conditions, and type-specific reference sites were selected. Unscaled TRIX values (UNTRIX) for reference and impacted sites have been calculated and two alternative UNTRIX-based classification procedures are discussed. The proposed procedures, to be validated on a broader scale, provide users with simple tools that give an integrated view of nutrient enrichment and its effects on algal biomass (Chl-a) and on oxygen levels. This trophic evaluation along with phytoplankton indicator species and algal blooms contribute to the comprehensive assessment of phytoplankton, one of the biological quality elements in coastal waters.

Fluorescence-based classification of Caribbean coral reef organisms and substrates

USGS Publications Warehouse

Zawada, David G.; Mazel, Charles H.

2014-01-01

A diverse group of coral reef organisms, representing several phyla, possess fluorescent pigments. We investigated the potential of using the characteristic fluorescence emission spectra of these pigments to enable unsupervised, optical classification of coral reef habitats. We compiled a library of characteristic fluorescence spectra through in situ and laboratory measurements from a variety of specimens throughout the Caribbean. Because fluorescent pigments are not species-specific, the spectral library is organized in terms of 15 functional groups. We investigated the spectral separability of the functional groups in terms of the number of wavebands required to distinguish between them, using the similarity measures Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), SID-SAM mixed measure, and Mahalanobis distance. This set of measures represents geometric, stochastic, joint geometric-stochastic, and statistical approaches to classifying spectra. Our hyperspectral fluorescence data were used to generate sets of 4-, 6-, and 8-waveband spectra, including random variations in relative signal amplitude, spectral peak shifts, and water-column attenuation. Each set consisted of 2 different band definitions: ‘optimally-picked’ and ‘evenly-spaced.’ The optimally-picked wavebands were chosen to coincide with as many peaks as possible in the functional group spectra. Reference libraries were formed from half of the spectra in each set and used for training purposes. Average classification accuracies ranged from 76.3% for SAM with 4 evenly-spaced wavebands to 93.8% for Mahalanobis distance with 8 evenly-spaced wavebands. The Mahalanobis distance consistently outperformed the other measures. In a second test, empirically-measured spectra were classified using the same reference libraries and the Mahalanobis distance for just the 8 evenly-spaced waveband case. Average classification accuracies were 84% and 87%, corresponding to the extremes in modeled water-column attenuation. The classification results from both tests indicate that a high degree of separability among the 15 fluorescent-spectra functional groups is possible using only a modest number of spectral bands.

Design and update of a classification system: the UCSD map of science.

PubMed

Börner, Katy; Klavans, Richard; Patek, Michael; Zoss, Angela M; Biberstine, Joseph R; Light, Robert P; Larivière, Vincent; Boyack, Kevin W

2012-01-01

Global maps of science can be used as a reference system to chart career trajectories, the location of emerging research frontiers, or the expertise profiles of institutes or nations. This paper details data preparation, analysis, and layout performed when designing and subsequently updating the UCSD map of science and classification system. The original classification and map use 7.2 million papers and their references from Elsevier's Scopus (about 15,000 source titles, 2001-2005) and Thomson Reuters' Web of Science (WoS) Science, Social Science, Arts & Humanities Citation Indexes (about 9,000 source titles, 2001-2004)-about 16,000 unique source titles. The updated map and classification adds six years (2005-2010) of WoS data and three years (2006-2008) from Scopus to the existing category structure-increasing the number of source titles to about 25,000. To our knowledge, this is the first time that a widely used map of science was updated. A comparison of the original 5-year and the new 10-year maps and classification system show (i) an increase in the total number of journals that can be mapped by 9,409 journals (social sciences had a 80% increase, humanities a 119% increase, medical (32%) and natural science (74%)), (ii) a simplification of the map by assigning all but five highly interdisciplinary journals to exactly one discipline, (iii) a more even distribution of journals over the 554 subdisciplines and 13 disciplines when calculating the coefficient of variation, and (iv) a better reflection of journal clusters when compared with paper-level citation data. When evaluating the map with a listing of desirable features for maps of science, the updated map is shown to have higher mapping accuracy, easier understandability as fewer journals are multiply classified, and higher usability for the generation of data overlays, among others.

Design and Update of a Classification System: The UCSD Map of Science

PubMed Central

Börner, Katy; Klavans, Richard; Patek, Michael; Zoss, Angela M.; Biberstine, Joseph R.; Light, Robert P.; Larivière, Vincent; Boyack, Kevin W.

2012-01-01

Global maps of science can be used as a reference system to chart career trajectories, the location of emerging research frontiers, or the expertise profiles of institutes or nations. This paper details data preparation, analysis, and layout performed when designing and subsequently updating the UCSD map of science and classification system. The original classification and map use 7.2 million papers and their references from Elsevier’s Scopus (about 15,000 source titles, 2001–2005) and Thomson Reuters’ Web of Science (WoS) Science, Social Science, Arts & Humanities Citation Indexes (about 9,000 source titles, 2001–2004)–about 16,000 unique source titles. The updated map and classification adds six years (2005–2010) of WoS data and three years (2006–2008) from Scopus to the existing category structure–increasing the number of source titles to about 25,000. To our knowledge, this is the first time that a widely used map of science was updated. A comparison of the original 5-year and the new 10-year maps and classification system show (i) an increase in the total number of journals that can be mapped by 9,409 journals (social sciences had a 80% increase, humanities a 119% increase, medical (32%) and natural science (74%)), (ii) a simplification of the map by assigning all but five highly interdisciplinary journals to exactly one discipline, (iii) a more even distribution of journals over the 554 subdisciplines and 13 disciplines when calculating the coefficient of variation, and (iv) a better reflection of journal clusters when compared with paper-level citation data. When evaluating the map with a listing of desirable features for maps of science, the updated map is shown to have higher mapping accuracy, easier understandability as fewer journals are multiply classified, and higher usability for the generation of data overlays, among others. PMID:22808037

ICA-Based Imagined Conceptual Words Classification on EEG Signals.

PubMed

Imani, Ehsan; Pourmohammad, Ali; Bagheri, Mahsa; Mobasheri, Vida

2017-01-01

Independent component analysis (ICA) has been used for detecting and removing the eye artifacts conventionally. However, in this research, it was used not only for detecting the eye artifacts, but also for detecting the brain-produced signals of two conceptual danger and information category words. In this cross-sectional research, electroencephalography (EEG) signals were recorded using Micromed and 19-channel helmet devices in unipolar mode, wherein Cz electrode was selected as the reference electrode. In the first part of this research, the statistical community test case included four men and four women, who were 25-30 years old. In the designed task, three groups of traffic signs were considered, in which two groups referred to the concept of danger, and the third one referred to the concept of information. In the second part, the three volunteers, two men and one woman, who had the best results, were chosen from among eight participants. In the second designed task, direction arrows (up, down, left, and right) were used. For the 2/8 volunteers in the rest times, very high-power alpha waves were observed from the back of the head; however, in the thinking times, they were different. According to this result, alpha waves for changing the task from thinking to rest condition took at least 3 s for the two volunteers, and it was at most 5 s until they went to the absolute rest condition. For the 7/8 volunteers, the danger and information signals were well classified; these differences for the 5/8 volunteers were observed in the right hemisphere, and, for the other three volunteers, the differences were observed in the left hemisphere. For the second task, simulations showed that the best classification accuracies resulted when the time window was 2.5 s. In addition, it also showed that the features of the autoregressive (AR)-15 model coefficients were the best choices for extracting the features. For all the states of neural network except hardlim discriminator function, the classification accuracies were almost the same and not very different. Linear discriminant analysis (LDA) in comparison with the neural network yielded higher classification accuracies. ICA is a suitable algorithm for recognizing of the word's concept and its place in the brain. Achieved results from this experiment were the same compared with the results from other methods such as functional magnetic resonance imaging and methods based on the brain signals (EEG) in the vowel imagination and covert speech. Herein, the highest classification accuracy was obtained by extracting the target signal from the output of the ICA and extracting the features of coefficients AR model with time interval of 2.5 s. Finally, LDA resulted in the highest classification accuracy more than 60%.

Combined target factor analysis and Bayesian soft-classification of interference-contaminated samples: forensic fire debris analysis.

PubMed

Williams, Mary R; Sigman, Michael E; Lewis, Jennifer; Pitan, Kelly McHugh

2012-10-10

A bayesian soft classification method combined with target factor analysis (TFA) is described and tested for the analysis of fire debris data. The method relies on analysis of the average mass spectrum across the chromatographic profile (i.e., the total ion spectrum, TIS) from multiple samples taken from a single fire scene. A library of TIS from reference ignitable liquids with assigned ASTM classification is used as the target factors in TFA. The class-conditional distributions of correlations between the target and predicted factors for each ASTM class are represented by kernel functions and analyzed by bayesian decision theory. The soft classification approach assists in assessing the probability that ignitable liquid residue from a specific ASTM E1618 class, is present in a set of samples from a single fire scene, even in the presence of unspecified background contributions from pyrolysis products. The method is demonstrated with sample data sets and then tested on laboratory-scale burn data and large-scale field test burns. The overall performance achieved in laboratory and field test of the method is approximately 80% correct classification of fire debris samples. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Electroconvulsive therapy-induced brain functional connectivity predicts therapeutic efficacy in patients with schizophrenia: a multivariate pattern recognition study.

PubMed

Li, Peng; Jing, Ri-Xing; Zhao, Rong-Jiang; Ding, Zeng-Bo; Shi, Le; Sun, Hong-Qiang; Lin, Xiao; Fan, Teng-Teng; Dong, Wen-Tian; Fan, Yong; Lu, Lin

2017-05-11

Previous studies suggested that electroconvulsive therapy can influence regional metabolism and dopamine signaling, thereby alleviating symptoms of schizophrenia. It remains unclear what patients may benefit more from the treatment. The present study sought to identify biomarkers that predict the electroconvulsive therapy response in individual patients. Thirty-four schizophrenia patients and 34 controls were included in this study. Patients were scanned prior to treatment and after 6 weeks of treatment with antipsychotics only (n = 16) or a combination of antipsychotics and electroconvulsive therapy (n = 13). Subject-specific intrinsic connectivity networks were computed for each subject using a group information-guided independent component analysis technique. Classifiers were built to distinguish patients from controls and quantify brain states based on intrinsic connectivity networks. A general linear model was built on the classification scores of first scan (referred to as baseline classification scores) to predict treatment response. Classifiers built on the default mode network, the temporal lobe network, the language network, the corticostriatal network, the frontal-parietal network, and the cerebellum achieved a cross-validated classification accuracy of 83.82%, with specificity of 91.18% and sensitivity of 76.47%. After the electroconvulsive therapy, psychosis symptoms of the patients were relieved and classification scores of the patients were decreased. Moreover, the baseline classification scores were predictive for the treatment outcome. Schizophrenia patients exhibited functional deviations in multiple intrinsic connectivity networks which were able to distinguish patients from healthy controls at an individual level. Patients with lower classification scores prior to treatment had better treatment outcome, indicating that the baseline classification scores before treatment is a good predictor for treatment outcome. CONNECTIVITY NETWORKS REVEAL GOOD CANDIDATES FOR BRAIN STIMULATION: Connectivity patterns in the brain may help identify patients with schizophrenia most likely to benefit from electroconvulsive therapy. A team led by Lin Lu from Peking University, China, and Yong Fan from the University of Pennsylvania, USA, took functional magnetic resonance imaging (MRI) scans of 34 people with schizophrenia and 34 control individuals without mental illness. Those with schizophrenia were scanned before and after treatment; some received antipsychotics alone, others received medication plus electroconvulsive therapy. The researchers created organizational brain maps known as "intrinsic connectivity networks" for each individual, and showed that the neuroimaging pattern could discriminate between people with and without schizophrenia. For the schizophrenia patients, the connectivity networks taken prior to treatment also helped predict who would benefit from the brain-stimulation procedure. Such a biomarker could prove a useful diagnostic tool for clinicians.

Visual impairment from uveitis in a reference hospital of Southeast Brazil: a retrospective review over a twenty years period.

PubMed

Silva, Luci Meire Pereira da; Muccioli, Cristina; Oliveira, Filipe de; Arantes, Tiago Eugênio; Gonzaga, Lucas Renó; Nakanami, Célia Regina

2013-01-01

To identify the frequency and causes of uveitis leading to visual impairment in patients referred to the Low Vision Service - Department of Ophthalmology - UNIFESP, over a twenty years period. In a retrospective study, medical records of 5,461 patients were reviewed. Data from the first clinical evaluation at the Low Vision Service were collected, patient's age, gender and cause of visual impairment were analyzed. Patients with uveitis had their chart reviewed for anatomical classification and clinical diagnosis. The mean age of the patients referred to the Low Vision Service was 42.86 years and the mean age of patients with uveitis diagnosis was 25.51 years. Retinal disorders were the most common cause of visual impairment (N=2,835 patients; 51.9%) followed by uveitis (862 patients, 15.7%). Uveitis was posterior in 792 patients (91.9% of uveitis) and toxoplasmosis was the most common diagnosis (765 patients, 88.7%). In our study, uveitis represents the second cause of visual impairment in patients referred for visual rehabilitation and toxoplasmic retinochoroiditis was the most common clinical diagnosis. It affects a young working age population with a relevant social and economic impact, but the early diagnosis and treatment can improve the quality of life of these patients.

Evaluating Mixture Modeling for Clustering: Recommendations and Cautions

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2011-01-01

This article provides a large-scale investigation into several of the properties of mixture-model clustering techniques (also referred to as latent class cluster analysis, latent profile analysis, model-based clustering, probabilistic clustering, Bayesian classification, unsupervised learning, and finite mixture models; see Vermunt & Magdison,…

49 CFR 1245.6 - Cross reference to standard occupational classification manual.

Code of Federal Regulations, 2013 CFR

2013-10-01

...: Electrical Worker (lineman) 6433. Electrical Worker (groundsman) 6432. Communications Maintainer 6151... Maintainer Helper 8635. 320Camp Car Cooks: Camp Car Cook 5214. Camp Car Helper 5219. 400Maintenance of... Reclamations Plant 6318. Assist. General Foreman 6318. 403Equipment, Shop, Electrical Inspectors: Chief...

49 CFR 1245.6 - Cross reference to standard occupational classification manual.

Code of Federal Regulations, 2012 CFR

2012-10-01

...: Electrical Worker (lineman) 6433. Electrical Worker (groundsman) 6432. Communications Maintainer 6151... Maintainer Helper 8635. 320Camp Car Cooks: Camp Car Cook 5214. Camp Car Helper 5219. 400Maintenance of... Reclamations Plant 6318. Assist. General Foreman 6318. 403Equipment, Shop, Electrical Inspectors: Chief...

49 CFR 1245.6 - Cross reference to standard occupational classification manual.

Code of Federal Regulations, 2014 CFR

2014-10-01

...: Electrical Worker (lineman) 6433. Electrical Worker (groundsman) 6432. Communications Maintainer 6151... Maintainer Helper 8635. 320Camp Car Cooks: Camp Car Cook 5214. Camp Car Helper 5219. 400Maintenance of... Reclamations Plant 6318. Assist. General Foreman 6318. 403Equipment, Shop, Electrical Inspectors: Chief...

Application of Holland's Theory to a Nonprofessional Occupation.

ERIC Educational Resources Information Center

Miller, Mark J.; Bass, Connie

2003-01-01

The authors, using the recently developed Position Classification Inventory, examined male and female perceptions of a nonprofessional occupation. Results suggest that the PCI shows promise as a method of classifying occupations according to J. L. Holland's (1997) theory. (Contains 20 references and 2 tables.) (Author)

Measurement and classification methods using the ASAE S572-1 reference nozzles

USDA-ARS?s Scientific Manuscript database

An increasing number of spray nozzle and agrochemical manufacturers are incorporating droplet size measurements into both research and development with each laboratory invariably having their own sampling setup and procedures, particularly with regard to both measurement distance from the nozzle and...

21 CFR 892.1400 - Nuclear sealed calibration source.

Code of Federal Regulations, 2012 CFR

2012-04-01

... reference radionuclide intended for calibration of medical nuclear radiation detectors. (b) Classification... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Nuclear sealed calibration source. 892.1400... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1400 Nuclear sealed calibration source...

21 CFR 892.1400 - Nuclear sealed calibration source.

Code of Federal Regulations, 2011 CFR

2011-04-01

... reference radionuclide intended for calibration of medical nuclear radiation detectors. (b) Classification... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Nuclear sealed calibration source. 892.1400... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1400 Nuclear sealed calibration source...

21 CFR 892.1400 - Nuclear sealed calibration source.

Code of Federal Regulations, 2014 CFR

2014-04-01

... reference radionuclide intended for calibration of medical nuclear radiation detectors. (b) Classification... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Nuclear sealed calibration source. 892.1400... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1400 Nuclear sealed calibration source...

21 CFR 892.1400 - Nuclear sealed calibration source.

Code of Federal Regulations, 2010 CFR

2010-04-01

... reference radionuclide intended for calibration of medical nuclear radiation detectors. (b) Classification... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Nuclear sealed calibration source. 892.1400... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1400 Nuclear sealed calibration source...

21 CFR 892.1400 - Nuclear sealed calibration source.

Code of Federal Regulations, 2013 CFR

2013-04-01

... reference radionuclide intended for calibration of medical nuclear radiation detectors. (b) Classification... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Nuclear sealed calibration source. 892.1400... (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1400 Nuclear sealed calibration source...

Evolution & Diversity in Plants.

ERIC Educational Resources Information Center

Pearson, Lorentz C.

1988-01-01

Summarizes recent findings that help in understanding how evolution has brought about the diversity of plant life that presently exists. Discusses basic concepts of evolution, diversity and classification, the three-line hypothesis of plant evolution, the origin of fungi, and the geologic time table. Included are 31 references. (CW)

46 CFR 110.10-1 - Incorporation by reference.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Classing Mobile Offshore Drilling Units, Part 4 Machinery and Systems, 2001 (“ABS MODU Rules”), IBR... Hazardous (Classified) Locations: Type of Protection—Encapsulation “m”, approved July 31, 2009 (“ANSI/ISA... Practice for Classification of Locations for Electrical Installations at Petroleum Facilities Classified as...

24 CFR 3285.4 - Incorporation by reference (IBR).

Code of Federal Regulations, 2012 CFR

2012-04-01

...-6600, fax number (253) 565-7265. (1) PS1-95, Construction and Industrial Plywood (with typical APA... for Engineering Purposes (Unified Soil Classification System), 2000, IBR approved for the table at... purchase from the Structural Engineering Institute/American Society of Civil Engineers (SEI/ASCE), 1801...

24 CFR 3285.4 - Incorporation by reference (IBR).

Code of Federal Regulations, 2011 CFR

2011-04-01

...-6600, fax number (253) 565-7265. (1) PS1-95, Construction and Industrial Plywood (with typical APA... for Engineering Purposes (Unified Soil Classification System), 2000, IBR approved for the table at... purchase from the Structural Engineering Institute/American Society of Civil Engineers (SEI/ASCE), 1801...

37 CFR 1.76 - Application data sheet.

Code of Federal Regulations, 2010 CFR

2010-07-01

... includes the correspondence address, which may be indicated by reference to a customer number, to which... title of the invention, a suggested classification, by class and subclass, the Technology Center to... application, the type of application (e.g., utility, plant, design, reissue, provisional), whether the...

Spatial Patterns of NLCD Land Cover Change Thematic Accuracy (2001 - 2011)

EPA Science Inventory

Research on spatial non-stationarity of land cover classification accuracy has been ongoing for over two decades. We extend the understanding of thematic map accuracy spatial patterns by: 1) quantifying spatial patterns of map-reference agreement for class-specific land cover c...

Towards a Framework for Developing Semantic Relatedness Reference Standards

PubMed Central

Pakhomov, Serguei V.S.; Pedersen, Ted; McInnes, Bridget; Melton, Genevieve B.; Ruggieri, Alexander; Chute, Christopher G.

2010-01-01

Our objective is to develop a framework for creating reference standards for functional testing of computerized measures of semantic relatedness. Currently, research on computerized approaches to semantic relatedness between biomedical concepts relies on reference standards created for specific purposes using a variety of methods for their analysis. In most cases, these reference standards are not publicly available and the published information provided in manuscripts that evaluate computerized semantic relatedness measurement approaches is not sufficient to reproduce the results. Our proposed framework is based on the experiences of medical informatics and computational linguistics communities and addresses practical and theoretical issues with creating reference standards for semantic relatedness. We demonstrate the use of the framework on a pilot set of 101 medical term pairs rated for semantic relatedness by 13 medical coding experts. While the reliability of this particular reference standard is in the “moderate” range; we show that using clustering and factor analyses offers a data-driven approach to finding systematic differences among raters and identifying groups of potential outliers. We test two ontology-based measures of relatedness and provide both the reference standard containing individual ratings and the R program used to analyze the ratings as open-source. Currently, these resources are intended to be used to reproduce and compare results of studies involving computerized measures of semantic relatedness. Our framework may be extended to the development of reference standards in other research areas in medical informatics including automatic classification, information retrieval from medical records and vocabulary/ontology development. PMID:21044697

VizieR Online Data Catalog: 2007.5 to 2010.4 HST astrometry of HD 202206 (Benedict+, 2017)

NASA Astrophysics Data System (ADS)

Benedict, G. F.; Harrison, T. E.

2017-08-01

For this study astrometric measurements came from Fine Guidance Sensor 1r (FGS 1r), an upgraded FGS installed in 1997 during the second Hubble Space Telescope (HST) servicing mission. It provided superior fringes from which to obtain target and reference star positions (McArthur et al. 2003hstc.conf..373M). We utilized only the fringe tracking mode (POS mode) in this investigation. POS mode observations of a star have a typical duration of 60s, during which over 2000 individual position measures are collected. The astrometric centroid is estimated by choosing the median measure, after filtering large outliers (caused by cosmic-ray hits and particles trapped by the Earth's magnetic field). The standard deviation of the measures provides a measurement error. We refer to the aggregate of astrometric centroids of each star secured during one visibility period as an "orbit". Because one of the pillars of the scientific method involves reproducibility, we present a complete ensemble of time-tagged HD202206 and reference star astrometric measurements, Optical Field Angle Distortion (OFAD; McArthur et al. 2006hstc.conf..396M) and intra-orbit-drift-corrected, in Table2, along with calculated parallax factors in R.A. and decl. These data, collected from 2007.5 to 2010.4, in addition to providing material for confirmation of our results, might ultimately be combined with Gaia measures, significantly extending the time baseline of astrometry, thereby improving proper motion and perturbation characterization. Our band passes for reference star photometry include: BVRI photometry of the reference stars from the NMSU 1m telescope located at Apache Point Observatory and JHK (from 2MASS; see Cutri et al. 2003, Cat. II/246). Table4 lists the visible and infrared photometry for the HD202206 reference stars. To establish spectral type and luminosity class, the reference frame stars were observed on 2009 December 9 using the RCSPEC on the Blanco 4m telescope at Cerro Tololo Inter-American Observatory (CTIO). We used the KPGL1 grating to give a dispersion of 0.95Å/pix. Classifications used a combination of template matching and line ratios. We determine the spectral types for the higher S/N stars to within ±1 subclass. Classifications for the lower S/N stars have ±2 subclass uncertainty. Table5 lists the spectral types and luminosity classes for our reference stars. (6 data files).

The use of old and recent DSM definitions of premature ejaculation in observational studies: a contribution to the present debate for a new classification of PE in the DSM-V.

PubMed

Waldinger, Marcel D; Schweitzer, Dave H

2008-05-01

The DSM-III definition of premature ejaculation (PE) contains the criterion "control" but not that of "ejaculation time." In contrast, the Diagnostic and Statistical Manual of Mental Disorders (4th edition, Text Revision) (DSM-IV-TR) contains the criterion "short ejaculation time," while it lacks "control." To review the adequacy and consequent use of all criteria of the DSM-IV-TR definition in previously published PE Internet surveys. Reviewing all published cohort studies on PE from 2004 to 2007. MEDLINE and EMBASE computer bibliographies were used. Definitions of DSM-III, DSM-IV-TR, and International Classification of Diseases. Five papers, of which three are original studies, reported inclusion of men with PE according to DSM-IV-TR definition but omitted to apply the required "short ejaculation time" criterion. These studies, which have defined PE according to subjective criteria such as control, actually referred to the DSM-III definition. Using DSM-III-like definitions in three different studies revealed a highly variable prevalence of PE (32.5%, 27.6%, and 13.0%). In contrast, based on studies using a 1-minute cutoff point, being the time that is required to call ejaculation time "short" or using the criterion "persistent occurrence," PE revealed to be far less prevalent (5-6%). Unacceptable discrepancies of PE definitions according to DSM-III (abandoned but still used) and DSM-IV-TR argue strongly in favor of a multidimensional new classification of PE for the DSM-V.

UNMANNED AERIAL VEHICLE (UAV) HYPERSPECTRAL REMOTE SENSING FOR DRYLAND VEGETATION MONITORING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nancy F. Glenn; Jessica J. Mitchell; Matthew O. Anderson

2012-06-01

UAV-based hyperspectral remote sensing capabilities developed by the Idaho National Lab and Idaho State University, Boise Center Aerospace Lab, were recently tested via demonstration flights that explored the influence of altitude on geometric error, image mosaicking, and dryland vegetation classification. The test flights successfully acquired usable flightline data capable of supporting classifiable composite images. Unsupervised classification results support vegetation management objectives that rely on mapping shrub cover and distribution patterns. Overall, supervised classifications performed poorly despite spectral separability in the image-derived endmember pixels. Future mapping efforts that leverage ground reference data, ultra-high spatial resolution photos and time series analysis shouldmore » be able to effectively distinguish native grasses such as Sandberg bluegrass (Poa secunda), from invasives such as burr buttercup (Ranunculus testiculatus) and cheatgrass (Bromus tectorum).« less

Mapping regional distribution of a single tree species: Whitebark pine in the Greater Yellowstone Ecosystem

USGS Publications Warehouse

Landenburger, L.; Lawrence, R.L.; Podruzny, S.; Schwartz, C.C.

2008-01-01

Moderate resolution satellite imagery traditionally has been thought to be inadequate for mapping vegetation at the species level. This has made comprehensive mapping of regional distributions of sensitive species, such as whitebark pine, either impractical or extremely time consuming. We sought to determine whether using a combination of moderate resolution satellite imagery (Landsat Enhanced Thematic Mapper Plus), extensive stand data collected by land management agencies for other purposes, and modern statistical classification techniques (boosted classification trees) could result in successful mapping of whitebark pine. Overall classification accuracies exceeded 90%, with similar individual class accuracies. Accuracies on a localized basis varied based on elevation. Accuracies also varied among administrative units, although we were not able to determine whether these differences related to inherent spatial variations or differences in the quality of available reference data.

Stream Classification Tool User Manual: For Use in Applications in Hydropower-Related Evironmental Mitigation

DOE Office of Scientific and Technical Information (OSTI.GOV)

McManamay, Ryan A.; Troia, Matthew J.; DeRolph, Christopher R.

Stream classifications are an inventory of different types of streams. Classifications help us explore similarities and differences among different types of streams, make inferences regarding stream ecosystem behavior, and communicate the complexities of ecosystems. We developed a nested, layered, and spatially contiguous stream classification to characterize the biophysical settings of stream reaches within the Eastern United States (~ 900,000 reaches). The classification is composed of five natural characteristics (hydrology, temperature, size, confinement, and substrate) along with several disturbance regime layers, and each was selected because of their relevance to hydropower mitigation. We developed the classification at the stream reach levelmore » using the National Hydrography Dataset Plus Version 1 (1:100k scale). The stream classification is useful to environmental mitigation for hydropower dams in multiple ways. First, it creates efficiency in the regulatory process by creating an objective and data-rich means to address meaningful mitigation actions. Secondly, the SCT addresses data gaps as it quickly provides an inventory of hydrology, temperature, morphology, and ecological communities for the immediate project area, but also surrounding streams. This includes identifying potential reference streams as those that are proximate to the hydropower facility and fall within the same class. These streams can potentially be used to identify ideal environmental conditions or identify desired ecological communities. In doing so, the stream provides some context for how streams may function, respond to dam regulation, and an overview of specific mitigation needs. Herein, we describe the methodology in developing each stream classification layer and provide a tutorial to guide applications of the classification (and associated data) in regulatory settings, such as hydropower (re)licensing.« less

Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI.

PubMed

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R

2017-04-01

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels. The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (<35 Hz) frequency ranges. MBRLAF is computationally more demanding than RLAF, but highly effective in all EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best. In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We introduce new algorithms for reducing EEG artifacts due to simultaneous fMRI The algorithms combine a reference layer and adaptive filtering Several evaluation criteria suggest superior effectivity in terms of artifact reduction We demonstrate that physiological EEG components are preserved.

Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI

NASA Astrophysics Data System (ADS)

Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R.

2017-04-01

Objective. Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. Approach. To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels. Main results. The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (<35 Hz) frequency ranges. MBRLAF is computationally more demanding than RLAF, but highly effective in all EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best. Significance. In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We introduce new algorithms for reducing EEG artifacts due to simultaneous fMRI The algorithms combine a reference layer and adaptive filtering Several evaluation criteria suggest superior effectivity in terms of artifact reduction We demonstrate that physiological EEG components are preserved

North American Multicenter Volumetric CT Study for Clinical Staging of Malignant Pleural Mesothelioma: Feasibility and Logistics of Setting Up a Quantitative Imaging Study.

PubMed

Gill, Ritu R; Naidich, David P; Mitchell, Alan; Ginsberg, Michelle; Erasmus, Jeremy; Armato, Samuel G; Straus, Christopher; Katz, Sharyn; Patios, Demetrois; Richards, William G; Rusch, Valerie W

2016-08-01

Clinical tumor (T), node, and metastasis staging is based on a qualitative assessment of features defining T descriptors and has been found to be suboptimal for predicting the prognosis of patients with malignant pleural mesothelioma (MPM). Previous work suggests that volumetric computed tomography (VolCT) is prognostic and, if found practical and reproducible, could improve clinical MPM classification. Six North American institutions electronically submitted clinical, pathologic, and imaging data on patients with stages I to IV MPM to an established multicenter database and biostatistical center. Two reference radiologists blinded to clinical data independently reviewed the scans; calculated clinical T, node, and metastasis stage by standard criteria; performed semiautomated tumor volume calculations using commercially available software; and submitted the findings to the biostatistical center. Study end points included the feasibility of a multi-institutional VolCT network, concordance of independent VolCT assessments, and association of VolCT with pathological T classification. Of 164 submitted cases, 129 were evaluated by both reference radiologists. Discordant clinical staging of most cases confirmed the inadequacy of current criteria. The overall correlation between VolCT estimates was good (Spearman correlation 0.822), but some were significantly discordant. Root cause analysis of the most discordant estimates identified four common sources of variability. Despite these limitations, median tumor volume estimates were similar within subgroups of cases representing each pathological T descriptor and increased monotonically for each reference radiologist with increasing pathological T status. The good correlation between VolCT estimates obtained for most cases reviewed by two independent radiologists and qualitative association of VolCT with pathological T status combine to encourage further study. The identified sources of user error will inform design of a follow-up prospective trial to more formally assess interobserver variability of VolCT and its potential contribution to clinical MPM staging. Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

D Land Cover Classification Based on Multispectral LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

2016-06-01

Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable of collecting point clouds data from all three channels at 532nm visible (Green), at 1064 nm near infrared (NIR) and at 1550nm intermediate infrared (IR). It has become a new source of data for 3D land cover classification. The paper presents an Object Based Image Analysis (OBIA) approach to only use multispectral Lidar point clouds datasets for 3D land cover classification. The approach consists of three steps. Firstly, multispectral intensity images are segmented into image objects on the basis of multi-resolution segmentation integrating different scale parameters. Secondly, intensity objects are classified into nine categories by using the customized features of classification indexes and a combination the multispectral reflectance with the vertical distribution of object features. Finally, accuracy assessment is conducted via comparing random reference samples points from google imagery tiles with the classification results. The classification results show higher overall accuracy for most of the land cover types. Over 90% of overall accuracy is achieved via using multispectral Lidar point clouds for 3D land cover classification.

The process and utility of classification and regression tree methodology in nursing research

PubMed Central

Kuhn, Lisa; Page, Karen; Ward, John; Worrall-Carter, Linda

2014-01-01

Aim This paper presents a discussion of classification and regression tree analysis and its utility in nursing research. Background Classification and regression tree analysis is an exploratory research method used to illustrate associations between variables not suited to traditional regression analysis. Complex interactions are demonstrated between covariates and variables of interest in inverted tree diagrams. Design Discussion paper. Data sources English language literature was sourced from eBooks, Medline Complete and CINAHL Plus databases, Google and Google Scholar, hard copy research texts and retrieved reference lists for terms including classification and regression tree* and derivatives and recursive partitioning from 1984–2013. Discussion Classification and regression tree analysis is an important method used to identify previously unknown patterns amongst data. Whilst there are several reasons to embrace this method as a means of exploratory quantitative research, issues regarding quality of data as well as the usefulness and validity of the findings should be considered. Implications for Nursing Research Classification and regression tree analysis is a valuable tool to guide nurses to reduce gaps in the application of evidence to practice. With the ever-expanding availability of data, it is important that nurses understand the utility and limitations of the research method. Conclusion Classification and regression tree analysis is an easily interpreted method for modelling interactions between health-related variables that would otherwise remain obscured. Knowledge is presented graphically, providing insightful understanding of complex and hierarchical relationships in an accessible and useful way to nursing and other health professions. PMID:24237048

The process and utility of classification and regression tree methodology in nursing research.

PubMed

Kuhn, Lisa; Page, Karen; Ward, John; Worrall-Carter, Linda

2014-06-01

This paper presents a discussion of classification and regression tree analysis and its utility in nursing research. Classification and regression tree analysis is an exploratory research method used to illustrate associations between variables not suited to traditional regression analysis. Complex interactions are demonstrated between covariates and variables of interest in inverted tree diagrams. Discussion paper. English language literature was sourced from eBooks, Medline Complete and CINAHL Plus databases, Google and Google Scholar, hard copy research texts and retrieved reference lists for terms including classification and regression tree* and derivatives and recursive partitioning from 1984-2013. Classification and regression tree analysis is an important method used to identify previously unknown patterns amongst data. Whilst there are several reasons to embrace this method as a means of exploratory quantitative research, issues regarding quality of data as well as the usefulness and validity of the findings should be considered. Classification and regression tree analysis is a valuable tool to guide nurses to reduce gaps in the application of evidence to practice. With the ever-expanding availability of data, it is important that nurses understand the utility and limitations of the research method. Classification and regression tree analysis is an easily interpreted method for modelling interactions between health-related variables that would otherwise remain obscured. Knowledge is presented graphically, providing insightful understanding of complex and hierarchical relationships in an accessible and useful way to nursing and other health professions. © 2013 The Authors. Journal of Advanced Nursing Published by John Wiley & Sons Ltd.

Using EUNIS habitat classification for benthic mapping in European seas: present concerns and future needs.

PubMed

Galparsoro, Ibon; Connor, David W; Borja, Angel; Aish, Annabelle; Amorim, Patricia; Bajjouk, Touria; Chambers, Caroline; Coggan, Roger; Dirberg, Guillaume; Ellwood, Helen; Evans, Douglas; Goodin, Kathleen L; Grehan, Anthony; Haldin, Jannica; Howell, Kerry; Jenkins, Chris; Michez, Noëmie; Mo, Giulia; Buhl-Mortensen, Pål; Pearce, Bryony; Populus, Jacques; Salomidi, Maria; Sánchez, Francisco; Serrano, Alberto; Shumchenia, Emily; Tempera, Fernando; Vasquez, Mickaël

2012-12-01

The EUNIS (European Union Nature Information System) habitat classification system aims to provide a common European reference set of habitat types within a hierarchical classification, and to cover all terrestrial, freshwater and marine habitats of Europe. The classification facilitates reporting of habitat data in a comparable manner, for use in nature conservation (e.g. inventories, monitoring and assessments), habitat mapping and environmental management. For the marine environment the importance of a univocal habitat classification system is confirmed by the fact that many European initiatives, aimed at marine mapping, assessment and reporting, are increasingly using EUNIS habitat categories and respective codes. For this reason substantial efforts have been made to include information on marine benthic habitats from different regions, aiming to provide a comprehensive geographical coverage of European seas. However, there still remain many concerns on its applicability as only a small fraction of Europe's seas are fully mapped and increasing knowledge and application raise further issues to be resolved. This paper presents an overview of the main discussion and conclusions of a workshop, organised by the MeshAtlantic project, focusing upon the experience in using the EUNIS habitats classification across different countries and seas, together with case studies. The aims of the meeting were to: (i) bring together scientists with experience in the use of the EUNIS marine classification and representatives from the European Environment Agency (EEA); (ii) agree on enhancements to EUNIS that ensure an improved representation of the European marine habitats; and (iii) establish practices that make marine habitat maps produced by scientists more consistent with the needs of managers and decision-makers. During the workshop challenges for the future development of EUNIS were identified, which have been classified into five categories: (1) structure and hierarchy; (2) biology; (3) terminology; (4) mapping; and (5) future development. The workshop ended with a declaration from the attendees, with recommendations to the EEA and European Topic Centre on Biological Diversity, to take into account the outputs of the workshop, which identify weaknesses in the current classification and include proposals for its modification, and to devise a process to further develop the marine component of the EUNIS habitat classification. Copyright © 2012 Elsevier Ltd. All rights reserved.

Non-English speakers attend gastroenterology clinic appointments at higher rates than English speakers in a vulnerable patient population

PubMed Central

Sewell, Justin L.; Kushel, Margot B.; Inadomi, John M.; Yee, Hal F.

2009-01-01

Goals We sought to identify factors associated with gastroenterology clinic attendance in an urban safety net healthcare system. Background Missed clinic appointments reduce the efficiency and availability of healthcare, but subspecialty clinic attendance among patients with established healthcare access has not been studied. Study We performed an observational study using secondary data from administrative sources to study patients referred to, and scheduled for an appointment in, the adult gastroenterology clinic serving the safety net healthcare system of San Francisco, California. Our dependent variable was whether subjects attended or missed a scheduled appointment. Analysis included multivariable logistic regression and classification tree analysis. 1,833 patients were referred and scheduled for an appointment between 05/2005 and 08/2006. Prisoners were excluded. All patients had a primary care provider. Results 683 patients (37.3%) missed their appointment; 1,150 (62.7%) attended. Language was highly associated with attendance in the logistic regression; non-English speakers were less likely than English speakers to miss an appointment (adjusted odds ratio 0.42 [0.28,0.63] for Spanish, 0.56 [0.38,0.82] for Asian language, p < 0.001). Other factors were also associated with attendance, but classification tree analysis identified language to be the most highly associated variable. Conclusions In an urban safety net healthcare population, among patients with established healthcare access and a scheduled gastroenterology clinic appointment, not speaking English was most strongly associated with higher attendance rates. Patient related factors associated with not speaking English likely influence subspecialty clinic attendance rates, and these factors may differ from those affecting general healthcare access. PMID:19169147