CrossLink: a novel method for cross-condition classification of cancer subtypes.

Science.gov (United States)

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.

Traffic Flow Condition Classification for Short Sections Using Single Microwave Sensor

Directory of Open Access Journals (Sweden)

Memiş Kemal

2010-01-01

Full Text Available Daily observed traffic flow can show different characteristics varying with the times of the day. They are caused by traffic incidents such as accidents, disabled cars, construction activities and other unusual events. Three different major traffic conditions can be occurred: "Flow," "Dense" and "Congested". Objective of this research is to identify the current traffic condition by examining the traffic measurement parameters. The earlier researches have dealt only with speed and volume by ignoring occupancy. In our study, the occupancy is another important parameter of classification. The previous works have used multiple sensors to classify traffic condition whereas our work uses only single microwave sensor. We have extended Multiple Linear Regression classification with our new approach of Estimating with Error Prediction. We present novel algorithms of Multiclassification with One-Against-All Method and Multiclassification with Binary Comparison for multiple SVM architecture. Finaly, a non-linear model of backpropagation neural network is introduced for classification. This combination has not been reported on previous studies. Training data are obtained from the Corsim based microscopic traffic simulator TSIS 5.1. All performances are compared using this data set. Our methods are currently installed and running at traffic management center of 2.Ring Road in Istanbul.

CargoCBM – Feature Generation and Classification for a Condition Monitoring System for Freight Wagons

International Nuclear Information System (INIS)

Gericke, C; Hecht, M

2012-01-01

Despite the fact that rail freight transport is one of the most environmentally friendly matters of transport, its growth has been far behind the growth of freight transport in general. Studies showed that a competitive disadvantage is caused by a low availability of rolling stock, especially freight wagons. Changing from a time based to a condition based maintenance strategy is believed to decrease down times by at least one third. To make condition based maintenance for freight wagons possible the TU Berlin and five industry partners started the research project CargoCBM. One task in this project is to develop algorithms for the automatic on-board diagnosis of wheel flats. The focus of the work is on the process of feature generation and feature selection as well as the application of different classifiers to automatically evaluate the data. Based on the results of measured data, features were selected and tested with different classifiers. Thought advanced classifiers such as neural networks have been analysed in accordance to their classification accuracy. It can be shown that with carefully constructed and selected features comparatively simple classifiers can lead to excellent results.

Securing classification and regulatory approval for deepwater projects: management challenges in a global environment

Energy Technology Data Exchange (ETDEWEB)

Feijo, Luiz P.; Burton, Gareth C. [American Bureau of Shipping (ABS), Rio de Janeiro, RJ (Brazil)

2008-07-01

As the offshore industry continues to develop and move into increasingly deeper waters, technological boundaries are being pushed to new limits. Along with these advances, the design, fabrication and installation of deepwater oil and gas projects has become an increasingly global endeavor. After providing an overview of the history and role of Classification Societies, this paper reviews the challenges of securing classification and regulatory approval in a global environment. Operational, procedural and technological changes which one Classification Society; the American Bureau of Shipping, known as ABS, has implemented to address these challenges are presented. The result of the changes has been a more customized service aiming at faster and more streamlined classification approval process. (author)

MULTITEMPORAL CROP TYPE CLASSIFICATION USING CONDITIONAL RANDOM FIELDS AND RAPIDEYE DATA

Directory of Open Access Journals (Sweden)

T. Hoberg

2012-09-01

Full Text Available The task of crop type classification with multitemporal imagery is nowadays often done applying classifiers that are originally developed for single images like support vector machines (SVM. These approaches do not model temporal dependencies in an explicit way. Existing approaches that make use of temporal dependencies are in most cases quite simple and based on rules. Approaches that integrate temporal dependencies to statistical models are very rare and at an early stage of development. Here our approach CRFmulti, based on conditional random fields (CRF, should make a contribution. Conditional random fields consider context knowledge among neighboring primitives in the same way as Markov random fields (MRF do. Furthermore conditional random fields handle the feature vectors of the neighboring primitives and not only the class labels. Additional to taking spatial context into account, we present an approach for multitemporal data processing where a temporal association potential has been integrated to the common CRF approach to model temporal dependencies. The classification works on pixel ‐level using spectral image features, whereas all available single images are taken separately. For our experiments a high resolution RapidEye satellite data set of 2010 consisting of 4 images made during the whole vegetation period from April to October is taken. Six crop type categories are distinguished, namely grassland, corn, winter crop, rapeseed, root crops and other crops. To evaluate the potential of the new conditional random field approach the classification result is compared to a manual reference on pixel‐ and on object‐level. Additional a SVM approach is applied under the same conditions and should serve as a benchmark.

Classifications for Coastal Wetlands Planning, Protection and Restoration Act site-specific projects: 2008 and 2009

Science.gov (United States)

Jones, William R.; Garber, Adrienne

2012-01-01

The Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) funds over 100 wetland restoration projects across Louisiana. Integral to the success of CWPPRA is its long-term monitoring program, which enables State and Federal agencies to determine the effectiveness of each restoration effort. One component of this monitoring program is the analysis of high-resolution, color-infrared aerial photography at the U.S. Geological Survey's National Wetlands Research Center in Lafayette, Louisiana. Color-infrared aerial photography (9- by 9-inch) is obtained before project construction and several times after construction. Each frame is scanned on a photogrametric scanner that produces a high-resolution image in Tagged Image File Format (TIFF). By using image-processing software, these TIFF files are then orthorectified and mosaicked to produce a seamless image of a project area and its associated reference area (a control site near the project that has common environmental features, such as marsh type, soil types, and water salinities.) The project and reference areas are then classified according to pixel value into two distinct classes, land and water. After initial land and water ratios have been established by using photography obtained before and after project construction, subsequent comparisons can be made over time to determine land-water change. Several challenges are associated with the land-water interpretation process. Primarily, land-water classifications are often complicated by the presence of floating aquatic vegetation that occurs throughout the freshwater systems of coastal Louisiana and that is sometimes difficult to differentiate from emergent marsh. Other challenges include tidal fluctuations and water movement from strong winds, which may result in flooding and inundation of emergent marsh during certain conditions. Compensating for these events is difficult but possible by using other sources of imagery to verify marsh conditions for other

Discriminative illumination: per-pixel classification of raw materials based on optimal projections of spectral BRDF.

Science.gov (United States)

Liu, Chao; Gu, Jinwei

2014-01-01

Classifying raw, unpainted materials--metal, plastic, ceramic, fabric, and so on--is an important yet challenging task for computer vision. Previous works measure subsets of surface spectral reflectance as features for classification. However, acquiring the full spectral reflectance is time consuming and error-prone. In this paper, we propose to use coded illumination to directly measure discriminative features for material classification. Optimal illumination patterns--which we call "discriminative illumination"--are learned from training samples, after projecting to which the spectral reflectance of different materials are maximally separated. This projection is automatically realized by the integration of incident light for surface reflection. While a single discriminative illumination is capable of linear, two-class classification, we show that multiple discriminative illuminations can be used for nonlinear and multiclass classification. We also show theoretically that the proposed method has higher signal-to-noise ratio than previous methods due to light multiplexing. Finally, we construct an LED-based multispectral dome and use the discriminative illumination method for classifying a variety of raw materials, including metal (aluminum, alloy, steel, stainless steel, brass, and copper), plastic, ceramic, fabric, and wood. Experimental results demonstrate its effectiveness.

Ecological land classification and terrestrial environment effects assessment for the Port Hope and Port Granby projects

International Nuclear Information System (INIS)

Taylor, M.; Wittkugel, U.; Kleb, H.

2006-01-01

The Ecological Land Classification system was developed to provide a standardized methodology for describing plant communities and wildlife habitat in southern Ontario. The method employs a hierarchical classification system. It can be applied at different levels of accuracy, i.e., at regional, sub-regional, and local scales with an increasing differentiation of vegetation communities. The standardization of the approach permits a comparison of vegetation communities from different sites and an evaluation of the rarity of these communities within the province. Further, the approach facilitates the monitoring of changes in terrestrial communities with time. These characteristics make Ecological Land Classification mapping a useful tool for environmental assessment such as the ones undertaken for the Port Hope and Port Granby Long-Term Waste Management Projects, which were conducted pursuant to the Canadian Environmental Assessment Act 1992. In the context of the Environmental Assessment for the Port Hope and Port Granby Projects, an Ecological Land Classification study was undertaken to characterize the terrestrial environment at regional, local and site levels. Vegetation patches (polygons) were delineated on the basis of air photo interpretation. The individual polygons were then visited for detailed inventory and classified to the most detailed level; that is to the vegetation type. Plant communities were then compared with those listed in the Ontario Natural Heritage Information Centre database to determine their rarity and to determine where they rank as Valued Ecosystem Components. Ecological Land Classification mapping results were used in the assessment of effects to Valued Ecosystem Components. A spatial analysis of the digitized vegetation maps showed the geographic extent of habitat losses and impairments due to various project works and activities. Landscape rehabilitation strategies and concepts were subsequently developed based on Ecological Land

Land cover's refined classification based on multi source of remote sensing information fusion: a case study of national geographic conditions census in China

Science.gov (United States)

Cheng, Tao; Zhang, Jialong; Zheng, Xinyan; Yuan, Rujin

2018-03-01

The project of The First National Geographic Conditions Census developed by Chinese government has designed the data acquisition content and indexes, and has built corresponding classification system mainly based on the natural property of material. However, the unified standard for land cover classification system has not been formed; the production always needs converting to meet the actual needs. Therefore, it proposed a refined classification method based on multi source of remote sensing information fusion. It takes the third-level classes of forest land and grassland for example, and has collected the thematic data of Vegetation Map of China (1:1,000,000), attempts to develop refined classification utilizing raster spatial analysis model. Study area is selected, and refined classification is achieved by using the proposed method. The results show that land cover within study area is divided principally among 20 classes, from subtropical broad-leaved forest (31131) to grass-forb community type of low coverage grassland (41192); what's more, after 30 years in the study area, climatic factors, developmental rhythm characteristics and vegetation ecological geographical characteristics have not changed fundamentally, only part of the original vegetation types have changed in spatial distribution range or land cover types. Research shows that refined classification for the third-level classes of forest land and grassland could make the results take on both the natural attributes of the original and plant community ecology characteristics, which could meet the needs of some industry application, and has certain practical significance for promoting the product of The First National Geographic Conditions Census.

Crown-condition classification: a guide to data collection and analysis

Science.gov (United States)

Michael E. Schomaker; Stanley J. Zarnoch; William A. Bechtold; David J. Latelle; William G. Burkman; Susan M. Cox

2007-01-01

The Forest Inventory and Analysis (FIA) Program of the Forest Service, U.S. Department of Agriculture, conducts a national inventory of forests across the United States. A systematic subset of permanent inventory plots in 38 States is currently sampled every year for numerous forest health indicators. One of these indicators, crown-condition classification, is designed...

Rock Mass Classification of Karstic Terrain in the Reservoir Slopes of Tekeze Hydropower Project

Science.gov (United States)

Hailemariam Gugsa, Trufat; Schneider, Jean Friedrich

2010-05-01

Hydropower reservoirs in deep gorges usually experience slope failures and mass movements. History also showed that some of these projects suffered severe landslides, which left lots of victims and enormous economic loss. Thus, it became vital to make substantial slope stability studies in such reservoirs to ensure safe project development. This study also presents a regional scale instability assessment of the Tekeze Hydropower reservoir slopes. Tekeze hydropower project is a newly constructed double arch dam that completed in August 2009. It is developed on Tekeze River, tributary of Blue Nile River that runs across the northern highlands of Ethiopia. It cuts a savage gorge 2000m deep, the deepest canyon in Africa. The dam is the highest dam in Ethiopia at 188m, 10 m higher than China's Three Gorges Dam. It is being developed by Chinese company at a cost of US350M. The reservoir is designed at 1140 m elevation, as retention level to store more than 9000 million m3 volume of water that covers an area of 150 km2, mainly in channel filling form. In this study, generation of digital elevation model from ASTER satellite imagery and surface field investigation is initially considered for further image processing and terrain parameters' analyses. Digitally processed multi spectral ASTER ortho-images drape over the DEM are used to have different three dimensional perspective views in interpreting lithological, structural and geomorphological features, which are later verified by field mapping. Terrain slopes are also delineated from the relief scene. A GIS database is ultimately developed to facilitate the delineation of geotechnical units for slope rock mass classification. Accordingly, 83 geotechnical units are delineated and, within them, 240 measurement points are established to quantify in-situ geotechnical parameters. Due to geotechnical uncertainties, four classification systems; namely geomorphic rock mass strength classification (RMS), slope mass rating (SMR

Stellar Spectral Classification with Locality Preserving Projections ...

Indian Academy of Sciences (India)

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

Global Stress Classification System for Materials Used in Solar Energy Applications

Science.gov (United States)

Slamova, Karolina; Schill, Christian; Herrmann, Jan; Datta, Pawan; Chih Wang, Chien

2016-08-01

Depending on the geographical location, the individual or combined impact of environmental stress factors and corresponding performance losses for solar applications varies significantly. Therefore, as a strategy to reduce investment risks and operating and maintenance costs, it is necessary to adapt the materials and components of solar energy systems specifically to regional environmental conditions. The project «GloBe Solar» supports this strategy by focusing on the development of a global stress classification system for materials in solar energy applications. The aim of this classification system is to assist in the identification of the individual stress conditions for every location on the earth's surface. The stress classification system could serve as a decision support tool for the industry (manufacturers, investors, lenders and project developers) and help to improve knowledge and services that can provide higher confidence to solar power systems.

Classification of heart valve condition using acoustic measurements

Energy Technology Data Exchange (ETDEWEB)

Clark, G. [Lawrence Livermore National Lab., CA (United States)

1994-11-15

Prosthetic heart valves and the many great strides in valve design have been responsible for extending the life spans of many people with serious heart conditions. Even though the prosthetic valves are extremely reliable, they are eventually susceptible to long-term fatigue and structural failure effects expected from mechanical devices operating over long periods of time. The purpose of our work is to classify the condition of in vivo Bjork-Shiley Convexo-Concave (BSCC) heart valves by processing acoustic measurements of heart valve sounds. The structural failures of interest for Bscc valves is called single leg separation (SLS). SLS can occur if the outlet strut cracks and separates from the main structure of the valve. We measure acoustic opening and closing sounds (waveforms) using high sensitivity contact microphones on the patient`s thorax. For our analysis, we focus our processing and classification efforts on the opening sounds because they yield direct information about outlet strut condition with minimal distortion caused by energy radiated from the valve disc.

Final hazard classification for the 183-C D ampersand D project

International Nuclear Information System (INIS)

Zimmer, J.J.

1995-01-01

The intent of this document is to provide a final Hazard Classification for the Decontamination and Decommissioning (D ampersand D) activities associated with the 183-C Filter Plant/Pump Room facility. The Hazard Classification was determined based upon DOE-EM-STD-5502-94, ''DOE Limited Standard, Hazard Baseline Documentation,'' issued by the US Department of Energy. The 183-C Filter Plant/Pump Room facility was constructed to support operations of the 105-B and 105-C Reactors at the Hanford Site. Since shutdown of the 105-C Reactor in April 1969, the 183-C facility has been kept in a safe storage condition

7 CFR 1794.31 - Classification.

Science.gov (United States)

2010-01-01

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

[Application of risk grading and classification for occupational hazards in risk management for a shipbuilding project].

Science.gov (United States)

Zeng, Wenfeng; Tan, Qiang; Wu, Shihua; Deng, Yingcong; Liu, Lifen; Wang, Zhi; Liu, Yimin

2015-12-01

To investigate the application of risk grading and classification for occupational hazards in risk management for a shipbuilding project. The risk management for this shipbuilding project was performed by a comprehensive application of MES evaluation, quality assessment of occupational health management, and risk grading and classification for occupational hazards, through the methods of occupational health survey, occupational health testing, and occupational health examinations. The results of MES evaluation showed that the risk of occupational hazards in this project was grade 3, which was considered as significant risk; Q value calculated by quality assessment of occupational health management was 0.52, which was considered to be unqualified; the comprehensive evaluation with these two methods showed that the integrated risk rating for this shipbuilding project was class D, and follow- up and rectification were needed with a focus on the improvement in health management. The application of MES evaluation and quality assessment of occupational health management in risk management for occupational hazards can achieve objective and reasonable conclusions and has good applicability.

Hydrological Classification, a Practical Tool for Mangrove Restoration.

Science.gov (United States)

Van Loon, Anne F; Te Brake, Bram; Van Huijgevoort, Marjolein H J; Dijksma, Roel

2016-01-01

Mangrove restoration projects, aimed at restoring important values of mangrove forests after degradation, often fail because hydrological conditions are disregarded. We present a simple, but robust methodology to determine hydrological suitability for mangrove species, which can guide restoration practice. In 15 natural and 8 disturbed sites (i.e. disused shrimp ponds) in three case study regions in south-east Asia, water levels were measured and vegetation species composition was determined. Using an existing hydrological classification for mangroves, sites were classified into hydrological classes, based on duration of inundation, and vegetation classes, based on occurrence of mangrove species. For the natural sites hydrological and vegetation classes were similar, showing clear distribution of mangrove species from wet to dry sites. Application of the classification to disturbed sites showed that in some locations hydrological conditions had been restored enough for mangrove vegetation to establish, in some locations hydrological conditions were suitable for various mangrove species but vegetation had not established naturally, and in some locations hydrological conditions were too wet for any mangrove species (natural or planted) to grow. We quantified the effect that removal of obstructions such as dams would have on the hydrology and found that failure of planting at one site could have been prevented. The hydrological classification needs relatively little data, i.e. water levels for a period of only one lunar tidal cycle without additional measurements, and uncertainties in the measurements and analysis are relatively small. For the study locations, the application of the hydrological classification gave important information about how to restore the hydrology to suitable conditions to improve natural regeneration or to plant mangrove species, which could not have been obtained by estimating elevation only. Based on this research a number of recommendations

Hydrological Classification, a Practical Tool for Mangrove Restoration.

Directory of Open Access Journals (Sweden)

Anne F Van Loon

Full Text Available Mangrove restoration projects, aimed at restoring important values of mangrove forests after degradation, often fail because hydrological conditions are disregarded. We present a simple, but robust methodology to determine hydrological suitability for mangrove species, which can guide restoration practice. In 15 natural and 8 disturbed sites (i.e. disused shrimp ponds in three case study regions in south-east Asia, water levels were measured and vegetation species composition was determined. Using an existing hydrological classification for mangroves, sites were classified into hydrological classes, based on duration of inundation, and vegetation classes, based on occurrence of mangrove species. For the natural sites hydrological and vegetation classes were similar, showing clear distribution of mangrove species from wet to dry sites. Application of the classification to disturbed sites showed that in some locations hydrological conditions had been restored enough for mangrove vegetation to establish, in some locations hydrological conditions were suitable for various mangrove species but vegetation had not established naturally, and in some locations hydrological conditions were too wet for any mangrove species (natural or planted to grow. We quantified the effect that removal of obstructions such as dams would have on the hydrology and found that failure of planting at one site could have been prevented. The hydrological classification needs relatively little data, i.e. water levels for a period of only one lunar tidal cycle without additional measurements, and uncertainties in the measurements and analysis are relatively small. For the study locations, the application of the hydrological classification gave important information about how to restore the hydrology to suitable conditions to improve natural regeneration or to plant mangrove species, which could not have been obtained by estimating elevation only. Based on this research a number

Naïve and Robust: Class-Conditional Independence in Human Classification Learning

Science.gov (United States)

Jarecki, Jana B.; Meder, Björn; Nelson, Jonathan D.

2018-01-01

Humans excel in categorization. Yet from a computational standpoint, learning a novel probabilistic classification task involves severe computational challenges. The present paper investigates one way to address these challenges: assuming class-conditional independence of features. This feature independence assumption simplifies the inference…

Causes of death and associated conditions (Codac): a utilitarian approach to the classification of perinatal deaths.

Science.gov (United States)

Frøen, J Frederik; Pinar, Halit; Flenady, Vicki; Bahrin, Safiah; Charles, Adrian; Chauke, Lawrence; Day, Katie; Duke, Charles W; Facchinetti, Fabio; Fretts, Ruth C; Gardener, Glenn; Gilshenan, Kristen; Gordijn, Sanne J; Gordon, Adrienne; Guyon, Grace; Harrison, Catherine; Koshy, Rachel; Pattinson, Robert C; Petersson, Karin; Russell, Laurie; Saastad, Eli; Smith, Gordon C S; Torabi, Rozbeh

2009-06-10

A carefully classified dataset of perinatal mortality will retain the most significant information on the causes of death. Such information is needed for health care policy development, surveillance and international comparisons, clinical services and research. For comparability purposes, we propose a classification system that could serve all these needs, and be applicable in both developing and developed countries. It is developed to adhere to basic concepts of underlying cause in the International Classification of Diseases (ICD), although gaps in ICD prevent classification of perinatal deaths solely on existing ICD codes.We tested the Causes of Death and Associated Conditions (Codac) classification for perinatal deaths in seven populations, including two developing country settings. We identified areas of potential improvements in the ability to retain existing information, ease of use and inter-rater agreement. After revisions to address these issues we propose Version II of Codac with detailed coding instructions.The ten main categories of Codac consist of three key contributors to global perinatal mortality (intrapartum events, infections and congenital anomalies), two crucial aspects of perinatal mortality (unknown causes of death and termination of pregnancy), a clear distinction of conditions relevant only to the neonatal period and the remaining conditions are arranged in the four anatomical compartments (fetal, cord, placental and maternal).For more detail there are 94 subcategories, further specified in 577 categories in the full version. Codac is designed to accommodate both the main cause of death as well as two associated conditions. We suggest reporting not only the main cause of death, but also the associated relevant conditions so that scenarios of combined conditions and events are captured.The appropriately applied Codac system promises to better manage information on causes of perinatal deaths, the conditions associated with them, and the most

Evaluation of low-level radioactive waste characterization and classification programs of the West Valley Demonstration Project

International Nuclear Information System (INIS)

Taie, K.R.

1994-01-01

The West Valley Demonstration Project (WVDP) is preparing to upgrade their low-level radioactive waste (LLW) characterization and classification program. This thesis describes a survey study of three other DOE sites conducted in support of this effort. The LLW characterization/classification programs of Oak Ridge National Laboratory, Savannah River Site, and Idaho National Engineering Laboratory were critically evaluated. The evaluation was accomplished through tours of each site facility and personnel interviews. Comparative evaluation of the individual characterization/classification programs suggests the WVDP should purchase a real-time radiography unit and a passive/active neutron detection system, make additional mechanical modifications to the segmented gamma spectroscopy assay system, provide a separate building to house characterization equipment and perform assays away from waste storage, develop and document a new LLW characterization/classification methodology, and make use of the supercompactor owned by WVDP

Criteria for classification of competitive housing projects in terms of their environmental friendliness

Science.gov (United States)

Nezhnikova, Ekaterina

2017-10-01

This article deals with social and economic essence of strategy of the housing industry development, both complex system of economic relations in field of production and consumption, which is regulated through the mechanism of prices and implemented through formation and realization of priority directions. Developed criteria for classification of housing construction projects as environmentally friendly and the quality criteria of variables for assessment of the environmental friendliness of residential buildings allowed to determine the ways of development of the industry on the basis of creation of competitive projects in interrelation with quality, environmental friendliness and price of consumption.

Classification of high resolution remote sensing image based on geo-ontology and conditional random fields

Science.gov (United States)

Hong, Liang

2013-10-01

The availability of high spatial resolution remote sensing data provides new opportunities for urban land-cover classification. More geometric details can be observed in the high resolution remote sensing image, Also Ground objects in the high resolution remote sensing image have displayed rich texture, structure, shape and hierarchical semantic characters. More landscape elements are represented by a small group of pixels. Recently years, the an object-based remote sensing analysis methodology is widely accepted and applied in high resolution remote sensing image processing. The classification method based on Geo-ontology and conditional random fields is presented in this paper. The proposed method is made up of four blocks: (1) the hierarchical ground objects semantic framework is constructed based on geoontology; (2) segmentation by mean-shift algorithm, which image objects are generated. And the mean-shift method is to get boundary preserved and spectrally homogeneous over-segmentation regions ;(3) the relations between the hierarchical ground objects semantic and over-segmentation regions are defined based on conditional random fields framework ;(4) the hierarchical classification results are obtained based on geo-ontology and conditional random fields. Finally, high-resolution remote sensed image data -GeoEye, is used to testify the performance of the presented method. And the experimental results have shown the superiority of this method to the eCognition method both on the effectively and accuracy, which implies it is suitable for the classification of high resolution remote sensing image.

VT Biodiversity Project - Bedrock Classification

Data.gov (United States)

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

FMCW radar system for detection and classification of small vessels in high sea state conditions

NARCIS (Netherlands)

Wasselin, J.-P.; Mazuel, S.; Itcia, E.; Huizing, A.G.; Theil, A.

2012-01-01

The ROCKWELL COLLINS France radar department is currently developing a FMCW radar system for the detection and the classification of small maritime targets in the frame of the SISMARIS, SARGOS & I2C projects. Several test campaigns have been conducted since 2009 to develop a sensor as well as an

A project on groundwater research inventory and classification to make groundwater visible

Science.gov (United States)

Cseko, Adrienn; Petitta, Marco; van der Keur, Peter; Fernandez, Isabel; Garcia Alibrandi, Clint; Hinsby, Klaus; Hartai, Eva; Garcia Padilla, Mercedes; Szucs, Peter; Mikita, Viktoria; Bisevac, Vanja; Bodo, Balazs

2017-04-01

Hydrogeology related research activities cover a wide spectrum of research areas at EU and national levels. The European knowledge base on this important topic is widespread and fragmented into broader programs generally related to waterresources, environment or ecology. In order to achieve a comprehensive understanding on the groundwater theme, the KINDRA project (Knowledge Inventory for Hydrogeology Research - www.kindraproject.eu) seeks to carry out an accurate assessment of the state of the art in hydrogeology research and to create a critical mass for scientific knowledge exchange of hydrogeology research, to ensure wide accessibility and applicability of research results, including support of innovation and development, and to reduce unnecessary duplication of efforts. The first two years of the project have focused its efforts in developing the concept of a Harmonized Terminology and Methodology for Classification and Reporting Hydrogeology related Research in Europe (HRCSYS) as well as its implementation in the European Inventory of Groundwater Research (EIGR). For developing the common terminology, keywords characterizing research on groundwater have been identified from two main sources: the most important EU directives and policy documents and from groundwater related scientific literature. To assess the importance and pertinence of the keywords, these have been ranked by performing searches via the Web of Science, Scopus and Google Scholar search engines. The complete merged list of keywords consisting of more than 200 terms has been organized in a tree hierarchy, identifying three main categories: Societal Challenges (SC), Operational Actions (OA) and Research Topics (RT). The relationships among these main categories expressed by a 3D approach, identifying single intersections among 5 main overarching groups for each category. The EIGR itself contains metadata (about 1800 records at the moment) of research efforts and topic related knowledge

Causes of death and associated conditions (Codac – a utilitarian approach to the classification of perinatal deaths

Directory of Open Access Journals (Sweden)

Harrison Catherine

2009-06-01

Full Text Available Abstract A carefully classified dataset of perinatal mortality will retain the most significant information on the causes of death. Such information is needed for health care policy development, surveillance and international comparisons, clinical services and research. For comparability purposes, we propose a classification system that could serve all these needs, and be applicable in both developing and developed countries. It is developed to adhere to basic concepts of underlying cause in the International Classification of Diseases (ICD, although gaps in ICD prevent classification of perinatal deaths solely on existing ICD codes. We tested the Causes of Death and Associated Conditions (Codac classification for perinatal deaths in seven populations, including two developing country settings. We identified areas of potential improvements in the ability to retain existing information, ease of use and inter-rater agreement. After revisions to address these issues we propose Version II of Codac with detailed coding instructions. The ten main categories of Codac consist of three key contributors to global perinatal mortality (intrapartum events, infections and congenital anomalies, two crucial aspects of perinatal mortality (unknown causes of death and termination of pregnancy, a clear distinction of conditions relevant only to the neonatal period and the remaining conditions are arranged in the four anatomical compartments (fetal, cord, placental and maternal. For more detail there are 94 subcategories, further specified in 577 categories in the full version. Codac is designed to accommodate both the main cause of death as well as two associated conditions. We suggest reporting not only the main cause of death, but also the associated relevant conditions so that scenarios of combined conditions and events are captured. The appropriately applied Codac system promises to better manage information on causes of perinatal deaths, the conditions

Causes of death and associated conditions (Codac) – a utilitarian approach to the classification of perinatal deaths

Science.gov (United States)

Frøen, J Frederik; Pinar, Halit; Flenady, Vicki; Bahrin, Safiah; Charles, Adrian; Chauke, Lawrence; Day, Katie; Duke, Charles W; Facchinetti, Fabio; Fretts, Ruth C; Gardener, Glenn; Gilshenan, Kristen; Gordijn, Sanne J; Gordon, Adrienne; Guyon, Grace; Harrison, Catherine; Koshy, Rachel; Pattinson, Robert C; Petersson, Karin; Russell, Laurie; Saastad, Eli; Smith, Gordon CS; Torabi, Rozbeh

2009-01-01

A carefully classified dataset of perinatal mortality will retain the most significant information on the causes of death. Such information is needed for health care policy development, surveillance and international comparisons, clinical services and research. For comparability purposes, we propose a classification system that could serve all these needs, and be applicable in both developing and developed countries. It is developed to adhere to basic concepts of underlying cause in the International Classification of Diseases (ICD), although gaps in ICD prevent classification of perinatal deaths solely on existing ICD codes. We tested the Causes of Death and Associated Conditions (Codac) classification for perinatal deaths in seven populations, including two developing country settings. We identified areas of potential improvements in the ability to retain existing information, ease of use and inter-rater agreement. After revisions to address these issues we propose Version II of Codac with detailed coding instructions. The ten main categories of Codac consist of three key contributors to global perinatal mortality (intrapartum events, infections and congenital anomalies), two crucial aspects of perinatal mortality (unknown causes of death and termination of pregnancy), a clear distinction of conditions relevant only to the neonatal period and the remaining conditions are arranged in the four anatomical compartments (fetal, cord, placental and maternal). For more detail there are 94 subcategories, further specified in 577 categories in the full version. Codac is designed to accommodate both the main cause of death as well as two associated conditions. We suggest reporting not only the main cause of death, but also the associated relevant conditions so that scenarios of combined conditions and events are captured. The appropriately applied Codac system promises to better manage information on causes of perinatal deaths, the conditions associated with them, and the

The US Forest Service Watershed Condition Classification: Status and Path Forward

Science.gov (United States)

Levinson, D. H.; Carlson, C. P.; Eberle, M. B.

2017-12-01

The US Forest Service Watershed Condition Classification (WCC) was developed as a tool to characterize the condition or health of watersheds on National Forests and Grasslands and assist the Agency in prioritizing actions to restore or maintain the condition of specified watersheds. After a number of years of exploring alternative approaches to assessing the health or condition of watersheds, the WCC and the associated Watershed Condition Framework were developed in response to concerns raised by the US Office of Management and Budget that the Forest Service was not able to demonstrate success in restoring watersheds on a national scale. The WCC was initially applied in 2011 to the roughly 15,000 HUC12 watersheds with an area of Forest Service management of 5% or greater. This initial watershed classification found that 52% (or 7,882) were Functioning Properly (Class 1), 45% (or 6,751) were Functioning at Risk (Class 2), and 3% (or 431) had Impaired Function (Class 3). The basic model used in the WCC was intended to provide a reconnaissance-level evaluation of watershed condition through the use of a systematic, flexible means of classifying and comparing watersheds based on a core set of national watershed condition indicators. The WCC consists of 12 indicators in four major process categories: (1) aquatic physical, (2) aquatic biological, (3) terrestrial physical, and (4) terrestrial biological. Each of the indicators is informed by one or more attributes. The attributes fall into three primary categories: numeric, descriptive, and map-derived, each of which is to be interpreted by an interdisciplinary team at the unit level. The descriptive and map-derived attributes are considered to be semi-quantitative or based on professional judgement of the team. The original description of the attributes anticipated that many of them would be improved as better data and information become available. With the advances in geographic information systems and remote sensing

Safety analysis and hazard classification for the 100-B/C Site Remediation Project, Phase 1. Revision 1

International Nuclear Information System (INIS)

Adam, W.J.; Lehrschall, R.R.; Oestreich, D.K.

1996-07-01

The purpose of this report is to document the preliminary hazard classification (PHC) for the initial group of sites to be remediated by the 100-B/C Site Remediation Project. The project is targeted at excavation of contaminated solid from seven waste sites, and the transportation and disposal of these wastes at the Environmental Restoration Disposal Facility. The PHC for these remediation activities is rated as radiological

NNP-LANL Utilities - Condition Assessment and Project Approach

Energy Technology Data Exchange (ETDEWEB)

Stewart, Grant Lorenz [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-11-21

This report is a presentation on LANL Utilities & Transportation Asset Management; Utility Assets Overview; Condition Assessment; Utilities Project Nominations & Ranking; and Utilities Project Execution.

An intelligent condition monitoring system for on-line classification of machine tool wear

Energy Technology Data Exchange (ETDEWEB)

Pan, Fu; Hope, A D; Javed, M [Systems Engineering Faculty, Southampton Institute (United Kingdom)

1998-12-31

The development of intelligent tool condition monitoring systems is a necessary requirement for successful automation of manufacturing processes. This presentation introduces a tool wear monitoring system for milling operations. The system utilizes power, force, acoustic emission and vibration sensors to monitor tool condition comprehensively. Features relevant to tool wear are drawn from time and frequency domain signals and a fuzzy pattern recognition technique is applied to combine the multisensor information and provide reliable classification results of tool wear states. (orig.) 10 refs.

An intelligent condition monitoring system for on-line classification of machine tool wear

Energy Technology Data Exchange (ETDEWEB)

Fu Pan; Hope, A.D.; Javed, M. [Systems Engineering Faculty, Southampton Institute (United Kingdom)

1997-12-31

The development of intelligent tool condition monitoring systems is a necessary requirement for successful automation of manufacturing processes. This presentation introduces a tool wear monitoring system for milling operations. The system utilizes power, force, acoustic emission and vibration sensors to monitor tool condition comprehensively. Features relevant to tool wear are drawn from time and frequency domain signals and a fuzzy pattern recognition technique is applied to combine the multisensor information and provide reliable classification results of tool wear states. (orig.) 10 refs.

New guidelines for dam safety classification

International Nuclear Information System (INIS)

Dascal, O.

1999-01-01

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

2013-07-26

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

Dewey Decimal Classification Online Project: Interim Reports to the Council on Library Resources, April 1984, September 1984, and February 1985.

Science.gov (United States)

Markey, Karen; Demeyer, Anh N.

This research project focuses on the implementation and testing of the Dewey Decimal Classification (DDC) system as an online searcher's tool for subject access, browsing, and display in an online catalog. The research project comprises 12 activities. The three interim reports in this document cover the first seven of these activities: (1) obtain…

Condition based maintenance pilot projects at Pickering ND

International Nuclear Information System (INIS)

Zemdegs, R.T.

1995-01-01

Ontario Hydro has recognized that the approaches to maintenance have undergone significant changes to the past decades. The traditional break down maintenance approach has been replaced by preventative maintenance and more recently, by condition based maintenance. The nuclear plants of Ontario Hydro have evaluated on a number of alternative programs to improve their maintenance effectiveness and to reduce costs, including Reliability Centred Maintenance (RCM), call-up review, component-based PM programs, analysis of failure history and so on. Pickering ND (nuclear division) and Ontario Hydro's Nuclear Technologies Services Division, have embarked on a Condition Based Maintenance pilot project to address the above issues as a breakthrough solution for smarter maintenance. The Condition Based Maintenance pilot project will demonstrate an end-to-end process utilizing a Reliability Centred Maintenance structured approach to re-engineer and redefine the existing maintenance programs. The project emphasizes on-condition maintenance where justified, and utilizes an information management tool to provide the required records keeping and analysis infrastructure. This paper briefly describes the planned maintenance model at Pickering ND used to guide the CBM pilot, and an overview of the methodology used to develop on-condition equipment indicators as part of a re-engineered maintenance plan

Assessment of Smolt Condition for Travel Time Analysis Project, 1987-1997 Project Review.

Energy Technology Data Exchange (ETDEWEB)

Schrock, Robin M.; Hans, Karen M.; Beeman, John W. [US Geological Survey, Western Fisheries Research Center, Columbia River Research Laboratory, Cook, WA

1997-12-01

The assessment of Smolt Condition for Travel Time Analysis Project (Bonneville Power Administration Project 87-401) monitored attributes of salmonid smolt physiology in the Columbia and Snake River basins from 1987 to 1997, under the Northwest Power Planning Council Fish and Wildlife Program, in cooperation with the Smolt Monitoring Program of the Fish Passage Center. The primary goal of the project was to investigate the physiological development of juvenile salmonids related to migration rates. The assumption was made that the level of smolt development, interacting with environmental factos such as flow, would be reflected in travel times. The Fish Passage Center applied the physiological measurements of smolt condition to Water Budget management, to regulate flows so as to decrease travel time and increase survival.

Graph-based semi-supervised learning with genomic data integration using condition-responsive genes applied to phenotype classification.

Science.gov (United States)

Doostparast Torshizi, Abolfazl; Petzold, Linda R

2018-01-01

Data integration methods that combine data from different molecular levels such as genome, epigenome, transcriptome, etc., have received a great deal of interest in the past few years. It has been demonstrated that the synergistic effects of different biological data types can boost learning capabilities and lead to a better understanding of the underlying interactions among molecular levels. In this paper we present a graph-based semi-supervised classification algorithm that incorporates latent biological knowledge in the form of biological pathways with gene expression and DNA methylation data. The process of graph construction from biological pathways is based on detecting condition-responsive genes, where 3 sets of genes are finally extracted: all condition responsive genes, high-frequency condition-responsive genes, and P-value-filtered genes. The proposed approach is applied to ovarian cancer data downloaded from the Human Genome Atlas. Extensive numerical experiments demonstrate superior performance of the proposed approach compared to other state-of-the-art algorithms, including the latest graph-based classification techniques. Simulation results demonstrate that integrating various data types enhances classification performance and leads to a better understanding of interrelations between diverse omics data types. The proposed approach outperforms many of the state-of-the-art data integration algorithms. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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

NARCIS (Netherlands)

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

2013-01-01

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

Think Big! The Human Condition Project

Science.gov (United States)

Metcalfe, Gareth

2014-01-01

How can educators provide children with a genuine experience of carrying out an extended scientific investigation? And can teachers change the perception of what it means to be a scientist? These were key questions that lay behind "The Human Condition" project, an initiative funded by the Primary Science Teaching Trust to explore a new…

Projected estimators for robust semi-supervised classification

DEFF Research Database (Denmark)

Krijthe, Jesse H.; Loog, Marco

2017-01-01

For semi-supervised techniques to be applied safely in practice we at least want methods to outperform their supervised counterparts. We study this question for classification using the well-known quadratic surrogate loss function. Unlike other approaches to semi-supervised learning, the procedure...... specifically, we prove that, measured on the labeled and unlabeled training data, this semi-supervised procedure never gives a lower quadratic loss than the supervised alternative. To our knowledge this is the first approach that offers such strong, albeit conservative, guarantees for improvement over...... the supervised solution. The characteristics of our approach are explicated using benchmark datasets to further understand the similarities and differences between the quadratic loss criterion used in the theoretical results and the classification accuracy typically considered in practice....

A multi-tier higher order Conditional Random Field for land cover classification of multi-temporal multi-spectral Landsat imagery

CSIR Research Space (South Africa)

Salmon, BP

2015-07-01

Full Text Available In this paper the authors present a 2-tier higher order Conditional Random Field which is used for land cover classification. The Conditional Random Field is based on probabilistic messages being passed along a graph to compute efficiently...

Full data consistency conditions for cone-beam projections with sources on a plane

International Nuclear Information System (INIS)

Clackdoyle, Rolf; Desbat, Laurent

2013-01-01

Cone-beam consistency conditions (also known as range conditions) are mathematical relationships between different cone-beam projections, and they therefore describe the redundancy or overlap of information between projections. These redundancies have often been exploited for applications in image reconstruction. In this work we describe new consistency conditions for cone-beam projections whose source positions lie on a plane. A further restriction is that the target object must not intersect this plane. The conditions require that moments of the cone-beam projections be polynomial functions of the source positions, with some additional constraints on the coefficients of the polynomials. A precise description of the consistency conditions is that the four parameters of the cone-beam projections (two for the detector, two for the source position) can be expressed with just three variables, using a certain formulation involving homogeneous polynomials. The main contribution of this work is our demonstration that these conditions are not only necessary, but also sufficient. Thus the consistency conditions completely characterize all redundancies, so no other independent conditions are possible and in this sense the conditions are full. The idea of the proof is to use the known consistency conditions for 3D parallel projections, and to then apply a 1996 theorem of Edholm and Danielsson that links parallel to cone-beam projections. The consistency conditions are illustrated with a simulation example. (paper)

Final hazard classification and auditable safety analysis for the 105-C Reactor Interim Safe Storage Project

International Nuclear Information System (INIS)

Rodovsky, T.J.; Larson, A.R.; Dexheimer, D.

1996-12-01

This document summarizes the inventories of radioactive and hazardous materials present in the 105-C Reactor Facility and the operations associated with the Interim Safe Storage Project which includes decontamination and demolition and interim safe storage of the remaining facility. This document also establishes a final hazard classification and verifies that appropriate and adequate safety functions and controls are in place to reduce or mitigate the risk associated with those operations

A European classification of services for long-term care—the EU-project eDESDE-LTC

Science.gov (United States)

Weber, Germain; Brehmer, Barbara; Zeilinger, Elisabeth; Salvador-Carulla, Luis

2009-01-01

Purpose and theory The eDESDE-LTC project aims at developing an operational system for coding, mapping and comparing services for long-term care (LTC) across EU. The projects strategy is to improve EU listing and access to relevant sources of healthcare information via development of SEMANTIC INTER-OPERABILITY in eHEALTH (coding and listing of services for LTC); to increase access to relevant sources of information on LTC services, and to improve linkages between national and regional websites; to foster cooperation with international organizations (OECD). Methods This operational system will include a standard classification of main types of care for persons with LTC needs and an instrument for mapping and standard description of services. These instruments are based on previous classification systems for mental health services (ESMS), disabilities services (DESDE) and ageing services (DESDAE). A Delphi panel made by seven partners developed a DESDE-LTC beta version, which was translated into six languages. The feasibility of DESDE-LTC is tested in six countries using national focal groups. Then the final version will be developed by the Delphi panel, a webpage, training material and course will be carried out. Results and conclusions The eDESDE-LTC system will be piloted in two EU countries (Spain and Bulgaria). Evaluation will focus primarily on usability and impact analysis. Discussion The added value of this project is related to the right of “having access to high-quality healthcare when and where it is needed” by EU citizens. Due to semantic variability and service complexity, existing national listings of services do not provide an adequate framework for patient mobility.

Project Based Learning on Students' Performance in the Concept of Classification of Organisms among Secondary Schools in Kenya

Science.gov (United States)

Wekesa, Noah Wafula; Ongunya, Raphael Odhiambo

2016-01-01

The concept of classification of organisms in Biology seems to pose a problem to Secondary School students in Kenya. Though, the topic is important for understanding of the basic elements of the subject. The Examinations Council in Kenya has identified teacher centred pedagogical techniques as one of the main causes for this. Project based…

Soil classification using CPTu in Fort McMurray

Energy Technology Data Exchange (ETDEWEB)

Elbanna, M. [AMEC Earth and Environmental, Nanaimo, BC (Canada); El Sabbagh, M. [AMEC Earth and Environmental, Burnaby, BC (Canada); Sharp, J. [ConeTec Investigations Ltd., Richmond, BC (Canada)

2009-07-01

This paper evaluated 4 piezocone penetration testing (CPTu) classification methods using data from 3 different sites near Fort McMurray in northern Alberta. For comparative purposes, other in-situ tests, field observations, and laboratory tests were performed at all sites in close proximity to the CPTu soundings. The study evaluated pleistocene sand and sand till deposits with low fines content. Profiling these deposits is necessary because they are often used as filler material for earth retaining structures in many oilsands projects. The study also evaluated pleistocene clay and clay tills that are often used as low permeability material for seepage control. In thick layers, pleistocene clay is known to cause foundation problems. CPTu with dissipation data was shown to be a useful tool in geotechnical engineering practice to provide near continuous soil profiling and material properties. CPTu tip resistance and sleeve friction combined with pore pressure measurement provided useful evaluation of subsurface soil types. It was concluded that although all of the CPTu classification charts provided reasonable soil classification in typical soil conditions, local experience and understanding of soil behaviour is needed to make an appropriate selection of the most applicable charts in a given geological condition. 7 refs., 11 figs.

Cerebral cortex classification by conditional random fields applied to intraoperative thermal imaging

Directory of Open Access Journals (Sweden)

Hoffmann Nico

2016-09-01

Full Text Available Intraoperative thermal neuroimaging is a novel intraoperative imaging technique for the characterization of perfusion disorders, neural activity and other pathological changes of the brain. It bases on the correlation of (sub-cortical metabolism and perfusion with the emitted heat of the cortical surface. In order to minimize required computational resources and prevent unwanted artefacts in subsequent data analysis workflows foreground detection is a important preprocessing technique to differentiate pixels representing the cerebral cortex from background objects. We propose an efficient classification framework that integrates characteristic dynamic thermal behaviour into this classification task to include additional discriminative features. The first stage of our framework consists of learning this representation of characteristic thermal time-frequency behaviour. This representation models latent interconnections in the time-frequency domain that cover specific, yet a priori unknown, thermal properties of the cortex. In a second stage these features are then used to classify each pixel’s state with conditional random fields. We quantitatively evaluate several approaches to learning high-level features and their impact to the overall prediction accuracy. The introduction of high-level features leads to a significant accuracy improvement compared to a baseline classifier.

Projected estimators for robust semi-supervised classification

NARCIS (Netherlands)

Krijthe, J.H.; Loog, M.

2017-01-01

For semi-supervised techniques to be applied safely in practice we at least want methods to outperform their supervised counterparts. We study this question for classification using the well-known quadratic surrogate loss function. Unlike other approaches to semi-supervised learning, the

Proposed Terminology and Classification of Pre-Malignant Neoplastic Conditions: A Consensus Proposal

Directory of Open Access Journals (Sweden)

Peter Valent

2017-12-01

Full Text Available Cancer evolution is a step-wise non-linear process that may start early in life or later in adulthood, and includes pre-malignant (indolent and malignant phases. Early somatic changes may not be detectable or are found by chance in apparently healthy individuals. The same lesions may be detected in pre-malignant clonal conditions. In some patients, these lesions may never become relevant clinically whereas in others, they act together with additional pro-oncogenic hits and thereby contribute to the formation of an overt malignancy. Although some pre-malignant stages of a malignancy have been characterized, no global system to define and to classify these conditions is available. To discuss open issues related to pre-malignant phases of neoplastic disorders, a working conference was organized in Vienna in August 2015. The outcomes of this conference are summarized herein and include a basic proposal for a nomenclature and classification of pre-malignant conditions. This proposal should assist in the communication among patients, physicians and scientists, which is critical as genome-sequencing will soon be offered widely for early cancer-detection.

Classification of functional interactions from multi-electrodes data using conditional modularity analysis

Science.gov (United States)

Makhtar, Siti Noormiza; Senik, Mohd Harizal

2018-02-01

The availability of massive amount of neuronal signals are attracting widespread interest in functional connectivity analysis. Functional interactions estimated by multivariate partial coherence analysis in the frequency domain represent the connectivity strength in this study. Modularity is a network measure for the detection of community structure in network analysis. The discovery of community structure for the functional neuronal network was implemented on multi-electrode array (MEA) signals recorded from hippocampal regions in isoflurane-anaesthetized Lister-hooded rats. The analysis is expected to show modularity changes before and after local unilateral kainic acid (KA)-induced epileptiform activity. The result is presented using color-coded graphic of conditional modularity measure for 19 MEA nodes. This network is separated into four sub-regions to show the community detection within each sub-region. The results show that classification of neuronal signals into the inter- and intra-modular nodes is feasible using conditional modularity analysis. Estimation of segregation properties using conditional modularity analysis may provide further information about functional connectivity from MEA data.

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

Science.gov (United States)

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

2018-01-01

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

Real time automatic scene classification

NARCIS (Netherlands)

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

2004-01-01

This work has been done as part of the EU VICAR (IST) project and the EU SCOFI project (IAP). The aim of the first project was to develop a real time video indexing classification annotation and retrieval system. For our systems, we have adapted the approach of Picard and Minka [3], who categorized

Event Classification using Concepts

NARCIS (Netherlands)

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

2013-01-01

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

Classification of flipped SU(5) heterotic-string vacua

Energy Technology Data Exchange (ETDEWEB)

Faraggi, Alon E., E-mail: alon.faraggi@liv.ac.uk [Department of Mathematical Sciences, University of Liverpool, Liverpool L69 7ZL (United Kingdom); Rizos, John, E-mail: irizos@uoi.gr [Department of Physics, University of Ioannina, GR45110 Ioannina (Greece); Sonmez, Hasan, E-mail: Hasan.Sonmez@liv.ac.uk [Department of Mathematical Sciences, University of Liverpool, Liverpool L69 7ZL (United Kingdom)

2014-09-15

We extend the classification of free fermionic heterotic-string vacua to models in which the SO(10) GUT symmetry is reduced at the string level to the flipped SU(5) subgroup. In our classification method the set of boundary condition basis vectors is fixed and the enumeration of string vacua is obtained in terms of the Generalised GSO (GGSO) projection coefficients entering the one-loop partition function. We derive algebraic expressions for the GGSO projections for all the physical states appearing in the sectors generated by the set of basis vectors. This enables the programming of the entire spectrum analysis in a computer code. For that purpose we developed two independent codes, based on FORTRAN95 and JAVA, and all results presented are confirmed by the two independent routines. We perform a statistical sampling in the space of 2{sup 44}∼10{sup 13} flipped SU(5) vacua, and scan up to 10{sup 12} GGSO configurations. Contrary to the corresponding Pati–Salam classification results, we do not find exophobic flipped SU(5) vacua with an odd number of generations. We study the structure of exotic states appearing in the three generation models, that additionally contain a viable Higgs spectrum, and demonstrate the existence of models in which all the exotic states are confined by a hidden sector non-Abelian gauge symmetry, as well as models that may admit the racetrack mechanism.

Proposed Terminology and Classification of Pre-Malignant Neoplastic Conditions: A Consensus Proposal.

Science.gov (United States)

Valent, Peter; Akin, Cem; Arock, Michel; Bock, Christoph; George, Tracy I; Galli, Stephen J; Gotlib, Jason; Haferlach, Torsten; Hoermann, Gregor; Hermine, Olivier; Jäger, Ulrich; Kenner, Lukas; Kreipe, Hans; Majeti, Ravindra; Metcalfe, Dean D; Orfao, Alberto; Reiter, Andreas; Sperr, Wolfgang R; Staber, Philipp B; Sotlar, Karl; Schiffer, Charles; Superti-Furga, Giulio; Horny, Hans-Peter

2017-12-01

Cancer evolution is a step-wise non-linear process that may start early in life or later in adulthood, and includes pre-malignant (indolent) and malignant phases. Early somatic changes may not be detectable or are found by chance in apparently healthy individuals. The same lesions may be detected in pre-malignant clonal conditions. In some patients, these lesions may never become relevant clinically whereas in others, they act together with additional pro-oncogenic hits and thereby contribute to the formation of an overt malignancy. Although some pre-malignant stages of a malignancy have been characterized, no global system to define and to classify these conditions is available. To discuss open issues related to pre-malignant phases of neoplastic disorders, a working conference was organized in Vienna in August 2015. The outcomes of this conference are summarized herein and include a basic proposal for a nomenclature and classification of pre-malignant conditions. This proposal should assist in the communication among patients, physicians and scientists, which is critical as genome-sequencing will soon be offered widely for early cancer-detection. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Integrating human and machine intelligence in galaxy morphology classification tasks

Science.gov (United States)

Beck, Melanie R.; Scarlata, Claudia; Fortson, Lucy F.; Lintott, Chris J.; Simmons, B. D.; Galloway, Melanie A.; Willett, Kyle W.; Dickinson, Hugh; Masters, Karen L.; Marshall, Philip J.; Wright, Darryl

2018-06-01

Quantifying galaxy morphology is a challenging yet scientifically rewarding task. As the scale of data continues to increase with upcoming surveys, traditional classification methods will struggle to handle the load. We present a solution through an integration of visual and automated classifications, preserving the best features of both human and machine. We demonstrate the effectiveness of such a system through a re-analysis of visual galaxy morphology classifications collected during the Galaxy Zoo 2 (GZ2) project. We reprocess the top-level question of the GZ2 decision tree with a Bayesian classification aggregation algorithm dubbed SWAP, originally developed for the Space Warps gravitational lens project. Through a simple binary classification scheme, we increase the classification rate nearly 5-fold classifying 226 124 galaxies in 92 d of GZ2 project time while reproducing labels derived from GZ2 classification data with 95.7 per cent accuracy. We next combine this with a Random Forest machine learning algorithm that learns on a suite of non-parametric morphology indicators widely used for automated morphologies. We develop a decision engine that delegates tasks between human and machine and demonstrate that the combined system provides at least a factor of 8 increase in the classification rate, classifying 210 803 galaxies in just 32 d of GZ2 project time with 93.1 per cent accuracy. As the Random Forest algorithm requires a minimal amount of computational cost, this result has important implications for galaxy morphology identification tasks in the era of Euclid and other large-scale surveys.

Feature Subset Selection and Instance Filtering for Cross-project Defect Prediction - Classification and Ranking

Directory of Open Access Journals (Sweden)

Faimison Porto

2016-12-01

Full Text Available The defect prediction models can be a good tool on organizing the project's test resources. The models can be constructed with two main goals: 1 to classify the software parts - defective or not; or 2 to rank the most defective parts in a decreasing order. However, not all companies maintain an appropriate set of historical defect data. In this case, a company can build an appropriate dataset from known external projects - called Cross-project Defect Prediction (CPDP. The CPDP models, however, present low prediction performances due to the heterogeneity of data. Recently, Instance Filtering methods were proposed in order to reduce this heterogeneity by selecting the most similar instances from the training dataset. Originally, the similarity is calculated based on all the available dataset features (or independent variables. We propose that using only the most relevant features on the similarity calculation can result in more accurate filtered datasets and better prediction performances. In this study we extend our previous work. We analyse both prediction goals - Classification and Ranking. We present an empirical evaluation of 41 different methods by associating Instance Filtering methods with Feature Selection methods. We used 36 versions of 11 open source projects on experiments. The results show similar evidences for both prediction goals. First, the defect prediction performance of CPDP models can be improved by associating Feature Selection and Instance Filtering. Second, no evaluated method presented general better performances. Indeed, the most appropriate method can vary according to the characteristics of the project being predicted.

AOSpine subaxial cervical spine injury classification system

NARCIS (Netherlands)

Vaccaro, Alexander R.; Koerner, John D.; Radcliff, Kris E.; Oner, F. Cumhur; Reinhold, Maximilian; Schnake, Klaus J.; Kandziora, Frank; Fehlings, Michael G.; Dvorak, Marcel F.; Aarabi, Bizhan; Rajasekaran, Shanmuganathan; Schroeder, Gregory D.; Kepler, Christopher K.; Vialle, Luiz R.

2016-01-01

Purpose: This project describes a morphology-based subaxial cervical spine traumatic injury classification system. Using the same approach as the thoracolumbar system, the goal was to develop a comprehensive yet simple classification system with high intra- and interobserver reliability to be used

VALUES-ORIENTED PROJECT MANAGEMENT OF RENEWABLE ENERGY

Directory of Open Access Journals (Sweden)

Олександр Михайлович ВОЗНИЙ

2017-03-01

Full Text Available The value-oriented approach to project management of renewable energy based on classification stage of the life cycle of products of the projects, adapted to the goals and objectives of information modeling, which allowed to formulate stricter requirements information models used at different stages of the power plant is proposed. A classification of the alternative energy projects, which highlighting areas for activities is proposed. The list of stakeholders that have an impact on alternative energy projects and presented their classification is defined. The value of alternative energy projects considered from the standpoint of a utilitarian approach, using the concept of utility and on the basis of this concept proposed classification values of alternative energy projects. Criteria values as indicators for assessing the value of alternative energy projects and their weights determined by pairwise comparison. To take into account the changes of the value criteria over time proposed to use the key control points value, assessed value criteria in various key points of control, defined indicator of the total value of alternative energy projects. The classification of risks and tools for value-oriented risk management in alternative energy projects is proposed. Further study authors plan to link the development of mechanisms for harmonization value alternative energy projects for their stakeholders.

Spatial conditions - the 3. supervisor in project organized teaching?

DEFF Research Database (Denmark)

Bering Keiding, Tina

through reflection of its own border: is this new issue inside or outside the project. Individual rooms make it easier for the project to stabilize around its eigenvalues, but also enhance the risk of cognitive jog-trot. The challenge in this case becomes to seek out disturbances which can initiate new......The contribution presents a pilot study on project work situated in different spatial contexts. The main question for the study is if and how spatial conditions influence the interaction within and between projects. Possible answers to the question are sought through observations, informal...... interviews and questionnaires. The empirical findings are reflected in a Luhmann-based re-description of project organized group based teaching (Keiding 2008). Preliminary conclusions indicate that one big difference between open-space studio and individual group rooms is related to the immediate public...

Twisted injectivity in projected entangled pair states and the classification of quantum phases

Energy Technology Data Exchange (ETDEWEB)

Buerschaper, Oliver, E-mail: obuerschaper@perimeterinstitute.ca

2014-12-15

We introduce a class of projected entangled pair states (PEPS) which is based on a group symmetry twisted by a 3-cocycle of the group. This twisted symmetry is expressed as a matrix product operator (MPO) with bond dimension greater than 1 and acts on the virtual boundary of a PEPS tensor. We show that it gives rise to a new standard form for PEPS from which we construct a family of local Hamiltonians which are gapped, frustration-free and include fixed points of the renormalization group flow. Based on this insight, we advance the classification of 2D gapped quantum spin systems by showing how this new standard form for PEPS determines the emergent topological order of these local Hamiltonians. Specifically, we identify their universality class as DIJKGRAAF–WITTEN topological quantum field theory (TQFT). - Highlights: • We introduce a new standard form for projected entangled pair states via a twisted group symmetry which is given by nontrivial matrix product operators. • We construct a large family of gapped, frustration-free Hamiltonians in two dimensions from this new standard form. • We rigorously show how this new standard form for low energy states determines the emergent topological order.

DOE LLW classification rationale

International Nuclear Information System (INIS)

Flores, A.Y.

1991-01-01

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

For a conditional financing of low carbon risky projects

International Nuclear Information System (INIS)

Meunier, Guy; Ponssard, Jean-Pierre

2016-09-01

Subsidies are extensively used for promoting the deployment of green technologies (renewables, clean development mechanism, electric vehicles...). Such policies may generate high windfall profits: some of the projects that benefited from the subsidies would have been undertaken anyway. The paper formalizes this situation using a simple principal agent framework under adverse selection. The agent may invest or not and obtain some private benefit in case of success. The principal observes both the investment and the eventual success, which generates a social benefit. Under some conditions it is shown that a subsidy paid conditional on failure (and not on success) limits the windfall profit while encouraging a large portfolio of projects to be invested. The relevance of this policy is discussed in the context of facilitating investment for infrastructure for fuel cell electric vehicles. (authors)

Classification of hydrocephalus: critical analysis of classification categories and advantages of "Multi-categorical Hydrocephalus Classification" (Mc HC).

Science.gov (United States)

Oi, Shizuo

2011-10-01

Hydrocephalus is a complex pathophysiology with disturbed cerebrospinal fluid (CSF) circulation. There are numerous numbers of classification trials published focusing on various criteria, such as associated anomalies/underlying lesions, CSF circulation/intracranial pressure patterns, clinical features, and other categories. However, no definitive classification exists comprehensively to cover the variety of these aspects. The new classification of hydrocephalus, "Multi-categorical Hydrocephalus Classification" (Mc HC), was invented and developed to cover the entire aspects of hydrocephalus with all considerable classification items and categories. Ten categories include "Mc HC" category I: onset (age, phase), II: cause, III: underlying lesion, IV: symptomatology, V: pathophysiology 1-CSF circulation, VI: pathophysiology 2-ICP dynamics, VII: chronology, VII: post-shunt, VIII: post-endoscopic third ventriculostomy, and X: others. From a 100-year search of publication related to the classification of hydrocephalus, 14 representative publications were reviewed and divided into the 10 categories. The Baumkuchen classification graph made from the round o'clock classification demonstrated the historical tendency of deviation to the categories in pathophysiology, either CSF or ICP dynamics. In the preliminary clinical application, it was concluded that "Mc HC" is extremely effective in expressing the individual state with various categories in the past and present condition or among the compatible cases of hydrocephalus along with the possible chronological change in the future.

Classification of Magnetic Nanoparticle Systems—Synthesis, Standardization and Analysis Methods in the NanoMag Project

Directory of Open Access Journals (Sweden)

Sara Bogren

2015-08-01

Full Text Available This study presents classification of different magnetic single- and multi-core particle systems using their measured dynamic magnetic properties together with their nanocrystal and particle sizes. The dynamic magnetic properties are measured with AC (dynamical susceptometry and magnetorelaxometry and the size parameters are determined from electron microscopy and dynamic light scattering. Using these methods, we also show that the nanocrystal size and particle morphology determines the dynamic magnetic properties for both single- and multi-core particles. The presented results are obtained from the four year EU NMP FP7 project, NanoMag, which is focused on standardization of analysis methods for magnetic nanoparticles.

Power and contexts – some societal conditions for participatory projects

DEFF Research Database (Denmark)

Bloch-Poulsen, Jørgen; Kristiansen, Marianne

2014-01-01

Based on action research co-operation with a team of teachers at a Social and Healthcare College in Denmark 2012-2013, the article raises the question: What are the conditions for organisational action research projects in a neoliberal context? The article has three purposes. Firstly, we want...... to show that mapping and delimitating relevant contexts are critical in an organisational AR project, because it is always arbitrary what you delimit as your field of inquiry, initially. The consequences of ignoring this in the project described were fatal. Secondly, the article draws attention to clashes...... with immediate and additional stakeholders questioning, among others, if the action research project is practicable at all....

Text document classification

Czech Academy of Sciences Publication Activity Database

Novovičová, Jana

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

Evaluation of Effectiveness of Wavelet Based Denoising Schemes Using ANN and SVM for Bearing Condition Classification

Directory of Open Access Journals (Sweden)

Vijay G. S.

2012-01-01

Full Text Available The wavelet based denoising has proven its ability to denoise the bearing vibration signals by improving the signal-to-noise ratio (SNR and reducing the root-mean-square error (RMSE. In this paper seven wavelet based denoising schemes have been evaluated based on the performance of the Artificial Neural Network (ANN and the Support Vector Machine (SVM, for the bearing condition classification. The work consists of two parts, the first part in which a synthetic signal simulating the defective bearing vibration signal with Gaussian noise was subjected to these denoising schemes. The best scheme based on the SNR and the RMSE was identified. In the second part, the vibration signals collected from a customized Rolling Element Bearing (REB test rig for four bearing conditions were subjected to these denoising schemes. Several time and frequency domain features were extracted from the denoised signals, out of which a few sensitive features were selected using the Fisher’s Criterion (FC. Extracted features were used to train and test the ANN and the SVM. The best denoising scheme identified, based on the classification performances of the ANN and the SVM, was found to be the same as the one obtained using the synthetic signal.

Estimating population extinction thresholds with categorical classification trees for Louisiana black bears.

Science.gov (United States)

Laufenberg, Jared S; Clark, Joseph D; Chandler, Richard B

2018-01-01

Monitoring vulnerable species is critical for their conservation. Thresholds or tipping points are commonly used to indicate when populations become vulnerable to extinction and to trigger changes in conservation actions. However, quantitative methods to determine such thresholds have not been well explored. The Louisiana black bear (Ursus americanus luteolus) was removed from the list of threatened and endangered species under the U.S. Endangered Species Act in 2016 and our objectives were to determine the most appropriate parameters and thresholds for monitoring and management action. Capture mark recapture (CMR) data from 2006 to 2012 were used to estimate population parameters and variances. We used stochastic population simulations and conditional classification trees to identify demographic rates for monitoring that would be most indicative of heighted extinction risk. We then identified thresholds that would be reliable predictors of population viability. Conditional classification trees indicated that annual apparent survival rates for adult females averaged over 5 years ([Formula: see text]) was the best predictor of population persistence. Specifically, population persistence was estimated to be ≥95% over 100 years when [Formula: see text], suggesting that this statistic can be used as threshold to trigger management intervention. Our evaluation produced monitoring protocols that reliably predicted population persistence and was cost-effective. We conclude that population projections and conditional classification trees can be valuable tools for identifying extinction thresholds used in monitoring programs.

Estimating population extinction thresholds with categorical classification trees for Louisiana black bears.

Directory of Open Access Journals (Sweden)

Jared S Laufenberg

Full Text Available Monitoring vulnerable species is critical for their conservation. Thresholds or tipping points are commonly used to indicate when populations become vulnerable to extinction and to trigger changes in conservation actions. However, quantitative methods to determine such thresholds have not been well explored. The Louisiana black bear (Ursus americanus luteolus was removed from the list of threatened and endangered species under the U.S. Endangered Species Act in 2016 and our objectives were to determine the most appropriate parameters and thresholds for monitoring and management action. Capture mark recapture (CMR data from 2006 to 2012 were used to estimate population parameters and variances. We used stochastic population simulations and conditional classification trees to identify demographic rates for monitoring that would be most indicative of heighted extinction risk. We then identified thresholds that would be reliable predictors of population viability. Conditional classification trees indicated that annual apparent survival rates for adult females averaged over 5 years ([Formula: see text] was the best predictor of population persistence. Specifically, population persistence was estimated to be ≥95% over 100 years when [Formula: see text], suggesting that this statistic can be used as threshold to trigger management intervention. Our evaluation produced monitoring protocols that reliably predicted population persistence and was cost-effective. We conclude that population projections and conditional classification trees can be valuable tools for identifying extinction thresholds used in monitoring programs.

Estimating population extinction thresholds with categorical classification trees for Louisiana black bears

Science.gov (United States)

Laufenberg, Jared S.; Clark, Joseph D.; Chandler, Richard B.

2018-01-01

Monitoring vulnerable species is critical for their conservation. Thresholds or tipping points are commonly used to indicate when populations become vulnerable to extinction and to trigger changes in conservation actions. However, quantitative methods to determine such thresholds have not been well explored. The Louisiana black bear (Ursus americanus luteolus) was removed from the list of threatened and endangered species under the U.S. Endangered Species Act in 2016 and our objectives were to determine the most appropriate parameters and thresholds for monitoring and management action. Capture mark recapture (CMR) data from 2006 to 2012 were used to estimate population parameters and variances. We used stochastic population simulations and conditional classification trees to identify demographic rates for monitoring that would be most indicative of heighted extinction risk. We then identified thresholds that would be reliable predictors of population viability. Conditional classification trees indicated that annual apparent survival rates for adult females averaged over 5 years () was the best predictor of population persistence. Specifically, population persistence was estimated to be ≥95% over 100 years when , suggesting that this statistic can be used as threshold to trigger management intervention. Our evaluation produced monitoring protocols that reliably predicted population persistence and was cost-effective. We conclude that population projections and conditional classification trees can be valuable tools for identifying extinction thresholds used in monitoring programs.

Rule-guided human classification of Volunteered Geographic Information

Science.gov (United States)

Ali, Ahmed Loai; Falomir, Zoe; Schmid, Falko; Freksa, Christian

2017-05-01

During the last decade, web technologies and location sensing devices have evolved generating a form of crowdsourcing known as Volunteered Geographic Information (VGI). VGI acted as a platform of spatial data collection, in particular, when a group of public participants are involved in collaborative mapping activities: they work together to collect, share, and use information about geographic features. VGI exploits participants' local knowledge to produce rich data sources. However, the resulting data inherits problematic data classification. In VGI projects, the challenges of data classification are due to the following: (i) data is likely prone to subjective classification, (ii) remote contributions and flexible contribution mechanisms in most projects, and (iii) the uncertainty of spatial data and non-strict definitions of geographic features. These factors lead to various forms of problematic classification: inconsistent, incomplete, and imprecise data classification. This research addresses classification appropriateness. Whether the classification of an entity is appropriate or inappropriate is related to quantitative and/or qualitative observations. Small differences between observations may be not recognizable particularly for non-expert participants. Hence, in this paper, the problem is tackled by developing a rule-guided classification approach. This approach exploits data mining techniques of Association Classification (AC) to extract descriptive (qualitative) rules of specific geographic features. The rules are extracted based on the investigation of qualitative topological relations between target features and their context. Afterwards, the extracted rules are used to develop a recommendation system able to guide participants to the most appropriate classification. The approach proposes two scenarios to guide participants towards enhancing the quality of data classification. An empirical study is conducted to investigate the classification of grass

Classification of movement disorders.

Science.gov (United States)

Fahn, Stanley

2011-05-01

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

Final Hazard Classification and Auditable Safety Analysis for the 105-F Building Interim Safe Storage Project

International Nuclear Information System (INIS)

Rodovsky, T.J.; Bond, S.L.

1998-07-01

The auditable safety analysis (ASA) documents the authorization basis for the partial decommissioning and facility modifications to place the 105-F Building into interim safe storage (ISS). Placement into the ISS is consistent with the preferred alternative identified in the Record of Decision (58 FR). Modifications will reduce the potential for release and worker exposure to hazardous and radioactive materials, as well as lower surveillance and maintenance (S ampersand M) costs. This analysis includes the following: A description of the activities to be performed in the course of the 105-F Building ISS Project. An assessment of the inventory of radioactive and other hazardous materials within the 105-F Building. Identification of the hazards associated with the activities of the 105-F Building ISS Project. Identification of internally and externally initiated accident scenarios with the potential to produce significant local or offsite consequences during the 105-F Building ISS Project. Bounding evaluation of the consequences of the potentially significant accident scenarios. Hazard classification based on the bounding consequence evaluation. Associated safety function and controls, including commitments. Radiological and other employee safety and health considerations

ACCUWIND - Methods for classification of cup anemometers

Energy Technology Data Exchange (ETDEWEB)

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

2006-05-15

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

Risk Classification and Risk-based Safety and Mission Assurance

Science.gov (United States)

Leitner, Jesse A.

2014-01-01

Recent activities to revamp and emphasize the need to streamline processes and activities for Class D missions across the agency have led to various interpretations of Class D, including the lumping of a variety of low-cost projects into Class D. Sometimes terms such as Class D minus are used. In this presentation, mission risk classifications will be traced to official requirements and definitions as a measure to ensure that projects and programs align with the guidance and requirements that are commensurate for their defined risk posture. As part of this, the full suite of risk classifications, formal and informal will be defined, followed by an introduction to the new GPR 8705.4 that is currently under review.GPR 8705.4 lays out guidance for the mission success activities performed at the Classes A-D for NPR 7120.5 projects as well as for projects not under NPR 7120.5. Furthermore, the trends in stepping from Class A into higher risk posture classifications will be discussed. The talk will conclude with a discussion about risk-based safety and mission assuranceat GSFC.

Construction of a knowledge classification scheme for sharing and usage of knowledge

International Nuclear Information System (INIS)

Yoo, Jae Bok; Oh, Jeong Hoon; Lee, Ji Ho; Ko, Young Chul

2003-12-01

To efficiently share knowledge among our members on the basis of knowledge management system, first of all, we need to systematically design the knowledge classification scheme that we can classify these knowledge well. The objective of this project is to construct the most suitable knowledge classification scheme that all of us can share them in Korea Atomic Energy Research Institute(KAERI). To construct the knowledge classification scheme all over the our organization, we established a few principles to design it and examined related many classification schemes. And we carried out 3 steps to complete the best desirable KAERI's knowledge classification scheme, that is, 1) the step to design a draft of the knowledge classification scheme, 2) the step to revise a draft of the knowledge classification scheme, 3) the step to verify the revised scheme and to decide its scheme. The scheme completed as a results of this project is consisted of total 218 items, that is, sections of 8 items, classes of 43 items and sub-classes of 167 items. We expect that the knowledge classification scheme designed as the results of this project can be played an important role as the frame to share knowledge among our members when we introduce knowledge management system in our organization. In addition, we expect that methods to design its scheme as well as this scheme itself can be applied when design a knowledge classification scheme at the other R and D institutes and enterprises

Classification of the emergency conditions in the uranium industry

International Nuclear Information System (INIS)

Jonchev, L.

1999-01-01

The exploration, production and treatment of uranium ores in Bulgaria have a half century history. The end was its shutdown in 1992 by a Decree of the Council of Ministers. The technological processes as well as the shutdown procedures lead to emergency situations. As a result a technogenic increase of the natural background radiation takes place. The assessment of already happened or possible emergency situations reveals their reiteration which determines the limits of a phenomenon. Thus a classification of all its elements into a binding system becomes possible, also a definition of the notion 'emergency' for the uranium sub sector of the mining industry. There are two main groups: radiation emergencies and geo-technological ones with subsequent radiological contamination, both of them in determined interrelation. The radiation emergencies could be a result of geological ones or to occur independently. They have no catastrophic character but a chronic effect on the adjacent population. The proposed classification gives a possibility to predict an emergency situation

The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification

Science.gov (United States)

Reddy, T.B.K.; Thomas, Alex D.; Stamatis, Dimitri; Bertsch, Jon; Isbandi, Michelle; Jansson, Jakob; Mallajosyula, Jyothi; Pagani, Ioanna; Lobos, Elizabeth A.; Kyrpides, Nikos C.

2015-01-01

The Genomes OnLine Database (GOLD; http://www.genomesonline.org) is a comprehensive online resource to catalog and monitor genetic studies worldwide. GOLD provides up-to-date status on complete and ongoing sequencing projects along with a broad array of curated metadata. Here we report version 5 (v.5) of the database. The newly designed database schema and web user interface supports several new features including the implementation of a four level (meta)genome project classification system and a simplified intuitive web interface to access reports and launch search tools. The database currently hosts information for about 19 200 studies, 56 000 Biosamples, 56 000 sequencing projects and 39 400 analysis projects. More than just a catalog of worldwide genome projects, GOLD is a manually curated, quality-controlled metadata warehouse. The problems encountered in integrating disparate and varying quality data into GOLD are briefly highlighted. GOLD fully supports and follows the Genomic Standards Consortium (GSC) Minimum Information standards. PMID:25348402

The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification

Energy Technology Data Exchange (ETDEWEB)

Reddy, Tatiparthi B. K. [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Thomas, Alex D. [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Stamatis, Dimitri [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Bertsch, Jon [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Isbandi, Michelle [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Jansson, Jakob [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Mallajosyula, Jyothi [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Pagani, Ioanna [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Lobos, Elizabeth A. [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Kyrpides, Nikos C. [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); King Abdulaziz Univ., Jeddah (Saudi Arabia)

2014-10-27

The Genomes OnLine Database (GOLD; http://www.genomesonline.org) is a comprehensive online resource to catalog and monitor genetic studies worldwide. GOLD provides up-to-date status on complete and ongoing sequencing projects along with a broad array of curated metadata. Within this paper, we report version 5 (v.5) of the database. The newly designed database schema and web user interface supports several new features including the implementation of a four level (meta)genome project classification system and a simplified intuitive web interface to access reports and launch search tools. The database currently hosts information for about 19 200 studies, 56 000 Biosamples, 56 000 sequencing projects and 39 400 analysis projects. More than just a catalog of worldwide genome projects, GOLD is a manually curated, quality-controlled metadata warehouse. The problems encountered in integrating disparate and varying quality data into GOLD are briefly highlighted. Lastly, GOLD fully supports and follows the Genomic Standards Consortium (GSC) Minimum Information standards.

Light-water reactors reference system classification for the European reliability data system (ERDS)

International Nuclear Information System (INIS)

Melis, M.; Mancini, G.

1982-01-01

The reference system classification represents a basic stage in the organization of the European reliability data system (ERDS) for light-water reactors, a project actually in development at the Joint Research Centre, Ispra. This project is concerned with operational reliability data collection from the various ''national'' data banks, and centralization in a European reliability data system, so improving the significance of the resulting reliability evaluations. In the framework of the ERDS project, the reference system classification provides a LWR functional break-down and represents a plant-unique identification in the process of homogenization of event-data coming from the various ''national'' organizations. The report, after a brief description of the main objectives of the ERDS project, reviews the criteria followed in the elaboration of the reference system classification; then the detailed classification is presented. The nuclear power station is subdivided in about 180 systems. To each system a sheet is associated, containing: a comprehensive description of system-functions and boundaries; a descritpion of the plant operating mode, linked to the various system functions; a list of the main interface system; and finally, a list of the main components, including type and safety classification

The Influence of Weather Conditions on Joint Pain in Older People with Osteoarthritis: Results from the European Project on OSteoArthritis.

Science.gov (United States)

Timmermans, Erik J; Schaap, Laura A; Herbolsheimer, Florian; Dennison, Elaine M; Maggi, Stefania; Pedersen, Nancy L; Castell, Maria Victoria; Denkinger, Michael D; Edwards, Mark H; Limongi, Federica; Sánchez-Martínez, Mercedes; Siviero, Paola; Queipo, Rocio; Peter, Richard; van der Pas, Suzan; Deeg, Dorly J H

2015-10-01

This study examined whether daily weather conditions, 3-day average weather conditions, and changes in weather conditions influence joint pain in older people with osteoarthritis (OA) in 6 European countries. Data from the population-based European Project on OSteoArthritis were used. The American College of Rheumatology classification criteria were used to diagnose OA in older people (65-85 yrs). After the baseline interview, at 6 months, and after the 12-18 months followup interview, joint pain was assessed using 2-week pain calendars. Daily values for temperature, precipitation, atmospheric pressure, relative humidity, and wind speed were obtained from local weather stations. Multilevel regression modelling was used to examine the pain-weather associations, adjusted for several confounders. The study included 810 participants with OA in the knee, hand, and/or hip. After adjustment, there were significant associations of joint pain with daily average humidity (B = 0.004, p weather conditions. Changes in weather variables between 2 consecutive days were not significantly associated with reported joint pain. The associations between pain and daily average weather conditions suggest that a causal relationship exist between joint pain and weather variables, but the associations between day-to-day weather changes and pain do not confirm causation. Knowledge about the relationship between joint pain in OA and weather may help individuals with OA, physicians, and therapists to better understand and manage fluctuations in pain.

Gynecomastia Classification for Surgical Management: A Systematic Review and Novel Classification System.

Science.gov (United States)

Waltho, Daniel; Hatchell, Alexandra; Thoma, Achilleas

2017-03-01

Gynecomastia is a common deformity of the male breast, where certain cases warrant surgical management. There are several surgical options, which vary depending on the breast characteristics. To guide surgical management, several classification systems for gynecomastia have been proposed. A systematic review was performed to (1) identify all classification systems for the surgical management of gynecomastia, and (2) determine the adequacy of these classification systems to appropriately categorize the condition for surgical decision-making. The search yielded 1012 articles, and 11 articles were included in the review. Eleven classification systems in total were ascertained, and a total of 10 unique features were identified: (1) breast size, (2) skin redundancy, (3) breast ptosis, (4) tissue predominance, (5) upper abdominal laxity, (6) breast tuberosity, (7) nipple malposition, (8) chest shape, (9) absence of sternal notch, and (10) breast skin elasticity. On average, classification systems included two or three of these features. Breast size and ptosis were the most commonly included features. Based on their review of the current classification systems, the authors believe the ideal classification system should be universal and cater to all causes of gynecomastia; be surgically useful and easy to use; and should include a comprehensive set of clinically appropriate patient-related features, such as breast size, breast ptosis, tissue predominance, and skin redundancy. None of the current classification systems appears to fulfill these criteria.

CONDITIONS OF SUSTAINABILITY OF INVESTMENT BUILDING PROJECTS BASED ON THE RISK MANAGEMENT CONCEPT

Directory of Open Access Journals (Sweden)

Morozenko Andrey Aleksandrovich

2012-10-01

minimization of risky situations requires reduction of the project implementation period; development of domestic methodologies and standards of project risk management tailored to the conditions of our construction industry is a relevant assignment.

Integrating Human and Machine Intelligence in Galaxy Morphology Classification Tasks

Science.gov (United States)

Beck, Melanie Renee

The large flood of data flowing from observatories presents significant challenges to astronomy and cosmology--challenges that will only be magnified by projects currently under development. Growth in both volume and velocity of astrophysics data is accelerating: whereas the Sloan Digital Sky Survey (SDSS) has produced 60 terabytes of data in the last decade, the upcoming Large Synoptic Survey Telescope (LSST) plans to register 30 terabytes per night starting in the year 2020. Additionally, the Euclid Mission will acquire imaging for 5 x 107 resolvable galaxies. The field of galaxy evolution faces a particularly challenging future as complete understanding often cannot be reached without analysis of detailed morphological galaxy features. Historically, morphological analysis has relied on visual classification by astronomers, accessing the human brains capacity for advanced pattern recognition. However, this accurate but inefficient method falters when confronted with many thousands (or millions) of images. In the SDSS era, efforts to automate morphological classifications of galaxies (e.g., Conselice et al., 2000; Lotz et al., 2004) are reasonably successful and can distinguish between elliptical and disk-dominated galaxies with accuracies of 80%. While this is statistically very useful, a key problem with these methods is that they often cannot say which 80% of their samples are accurate. Furthermore, when confronted with the more complex task of identifying key substructure within galaxies, automated classification algorithms begin to fail. The Galaxy Zoo project uses a highly innovative approach to solving the scalability problem of visual classification. Displaying images of SDSS galaxies to volunteers via a simple and engaging web interface, www.galaxyzoo.org asks people to classify images by eye. Within the first year hundreds of thousands of members of the general public had classified each of the 1 million SDSS galaxies an average of 40 times. Galaxy Zoo

Project Management Plan to Maintain Safe and Compliant Conditions at the Plutonium Finishing Plant

International Nuclear Information System (INIS)

COX, G.J.

1999-01-01

This Project Management Plan presents the overall plan, description, mission, and workscope for the Plutonium Finishing Plant (PFP) maintain safe and compliant conditions project at PFP. This plan presents the overall description, mission, work scope, and planning for the Plutonium Finishing Plant (PFP) Maintain Safe and Compliant Conditions Project at PFP. This project includes all tasks required to maintain the safety boundary for the PFP Complex, except for the 2736-2 Vault Complex and the 234-52 vaults and vault-type rooms. The intent of this plan is to describe how this project will be managed and integrated with the stabilization, and deactivation activities. This plan supplements the overall integrated plan presented in the Plutonium Finishing Plant Integrated Project Management Plan (IPMP), HNF-3617, Rev. 0. This is the top-level definitive project management document that specifies the technical (work scope), schedule, and cost baselines that will manage the execution of this project. It describes the organizational approach and roles/responsibilities implemented to execute the project. This plan is under configuration management and any deviations must be authorized by appropriate change control action

Effective Exchange Rate Classifications and Growth

OpenAIRE

Justin M. Dubas; Byung-Joo Lee; Nelson C. Mark

2005-01-01

We propose an econometric procedure for obtaining de facto exchange rate regime classifications which we apply to study the relationship between exchange rate regimes and economic growth. Our classification method models the de jure regimes as outcomes of a multinomial logit choice problem conditional on the volatility of a country's effective exchange rate, a bilateral exchange rate and international reserves. An `effective' de facto exchange rate regime classification is then obtained by as...

Automotive System for Remote Surface Classification.

Science.gov (United States)

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

2017-04-01

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

Partitioning uncertainty in streamflow projections under nonstationary model conditions

Science.gov (United States)

Chawla, Ila; Mujumdar, P. P.

2018-02-01

Assessing the impacts of Land Use (LU) and climate change on future streamflow projections is necessary for efficient management of water resources. However, model projections are burdened with significant uncertainty arising from various sources. Most of the previous studies have considered climate models and scenarios as major sources of uncertainty, but uncertainties introduced by land use change and hydrologic model assumptions are rarely investigated. In this paper an attempt is made to segregate the contribution from (i) general circulation models (GCMs), (ii) emission scenarios, (iii) land use scenarios, (iv) stationarity assumption of the hydrologic model, and (v) internal variability of the processes, to overall uncertainty in streamflow projections using analysis of variance (ANOVA) approach. Generally, most of the impact assessment studies are carried out with unchanging hydrologic model parameters in future. It is, however, necessary to address the nonstationarity in model parameters with changing land use and climate. In this paper, a regression based methodology is presented to obtain the hydrologic model parameters with changing land use and climate scenarios in future. The Upper Ganga Basin (UGB) in India is used as a case study to demonstrate the methodology. The semi-distributed Variable Infiltration Capacity (VIC) model is set-up over the basin, under nonstationary conditions. Results indicate that model parameters vary with time, thereby invalidating the often-used assumption of model stationarity. The streamflow in UGB under the nonstationary model condition is found to reduce in future. The flows are also found to be sensitive to changes in land use. Segregation results suggest that model stationarity assumption and GCMs along with their interactions with emission scenarios, act as dominant sources of uncertainty. This paper provides a generalized framework for hydrologists to examine stationarity assumption of models before considering them

Correlation Dimension Estimation for Classification

Czech Academy of Sciences Publication Activity Database

Jiřina, Marcel; Jiřina jr., M.

2006-01-01

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

Galaxy Zoo 1: data release of morphological classifications for nearly 900 000 galaxies

Energy Technology Data Exchange (ETDEWEB)

Linott, C.; Slosar, A.; Lintott, C.; Schawinski, K.; Bamford, S.; Slosar, A.; Land, K.; Thomas, D.; Edmondson, E.; Masters, K.; Nichol, R.C.; Raddick, M.J.; Szalay, A.; Andreescu, D.; Murray, P.; Vandenberg, J.

2011-01-01

Morphology is a powerful indicator of a galaxy's dynamical and merger history. It is strongly correlated with many physical parameters, including mass, star formation history and the distribution of mass. The Galaxy Zoo project collected simple morphological classifications of nearly 900,000 galaxies drawn from the Sloan Digital Sky Survey, contributed by hundreds of thousands of volunteers. This large number of classifications allows us to exclude classifier error, and measure the influence of subtle biases inherent in morphological classification. This paper presents the data collected by the project, alongside measures of classification accuracy and bias. The data are now publicly available and full catalogues can be downloaded in electronic format from http://data.galaxyzoo.org.

Dewey Decimal Classification Online Project: Evaluation of a Library Schedule and Index Integrated into the Subject Searching Capabilities of an Online Catalog. Final Report.

Science.gov (United States)

Markey, Karen; Demeyer, Anh N.

In this research project, subject terms from the Dewey Decimal Classification (DDC) Schedules and Relative Index were incorporated into an online catalog as searcher's tools for subject access, browsing, and display. Four features of the DDC were employed to help searchers browse for and match their own subject terms with the online catalog's…

River reach classification for the Greater Mekong Region at high spatial resolution

Science.gov (United States)

Ouellet Dallaire, C.; Lehner, B.

2014-12-01

River classifications have been used in river health and ecological assessments as coarse proxies to represent aquatic biodiversity when comprehensive biological and/or species data is unavailable. Currently there are no river classifications or biological data available in a consistent format for the extent of the Greater Mekong Region (GMR; including the Irrawaddy, the Salween, the Chao Praya, the Mekong and the Red River basins). The current project proposes a new river habitat classification for the region, facilitated by the HydroSHEDS (HYDROlogical SHuttle Elevation Derivatives at multiple Scales) database at 500m pixel resolution. The classification project is based on the Global River Classification framework relying on the creation of multiple sub-classifications based on different disciplines. The resulting classes from the sub-classification are later combined into final classes to create a holistic river reach classification. For the GMR, a final habitat classification was created based on three sub-classifications: a hydrological sub-classification based only on discharge indices (river size and flow variability); a physio-climatic sub-classification based on large scale indices of climate and elevation (biomes, ecoregions and elevation); and a geomorphological sub-classification based on local morphology (presence of floodplains, reach gradient and sand transport). Key variables and thresholds were identified in collaboration with local experts to ensure that regional knowledge was included. The final classification is composed 54 unique final classes based on 3 sub-classifications with less than 15 classes each. The resulting classifications are driven by abiotic variables and do not include biological data, but they represent a state-of-the art product based on best available data (mostly global data). The most common river habitat type is the "dry broadleaf, low gradient, very small river". These classifications could be applied in a wide range of

Evaluation of rock classifications at B. C. Rail tumbler ridge tunnels

Science.gov (United States)

Kaiser, Peter K.; Mackay, C.; Gale, A. D.

1986-10-01

Construction of four single track railway tunnels through sedimentary rocks in central British Columbia, Canada, provided an excellent opportunity to compare various rock mass classification systems and to evaluate their applicability to the local geology. The tunnels were excavated by conventional drilling and blasting techniques and supported primarily with rock bolts and shotcrete, and with steel sets in some sections. After a brief project description including tunnel construction techniques, local geology and groundwater conditions, the data collection and filed mapping procedure is reviewed. Four rock mass classification systems ( RQD, RSR, RMR, Q) for empirical tunnel design are reviewed and relevant factors for the data interpretation are discussed. In comparing and evaluating the performance of these classification systems three aspects received special attention. The tunnel support predicted by the various systems was compared to the support installed, a unique correlation between the two most useful and most frequently applied classifications, the RMR and Q systems, was established and assessed, and finally, the non-support limit and size effect were evaluated. It is concluded that the Q-system best predicted the required tunnel support and that the RMR was only adequate after adjustment for the influence of opening size. Correction equations for opening size effects are presented for the RMR system. The RSR and RQD systems are not recommended for empirical tunnel design.

Analysis of a Bibliographic Database Enhanced with a Library Classification.

Science.gov (United States)

Drabenstott, Karen Markey; And Others

1990-01-01

Describes a project that examined the effects of incorporating subject terms from the Dewey Decimal Classification (DDC) into a bibliographic database. It is concluded that the incorporation of DDC and possibly other library classifications into online catalogs can enhance subject access and provide additional subject searching strategies. (11…

[Definition and classification of pulmonary arterial hypertension].

Science.gov (United States)

Nakanishi, Norifumi

2008-11-01

Pulmonary hypertension(PH) is a disorder that may occur either in the setting of a variety of underlying medical conditions or as a disease that uniquely affects the pulmonary vasculature. Because an accurate diagnosis of PH in a patient is essential to establish an effective treatment, a classification of PH has been helpful. The first classification, established at WHO Symposium in 1973, classified PH into groups based on the known cause and defined primary pulmonary hypertension (PPH) as a separate entity of unknown cause. In 1998, the second World Symposium on PPH was held in Evian. Evian classification introduced the concept of conditions that directly affected the pulmonary vasculature (i.e., PAH), which included PPH. In 2003, the third World Symposium on PAH convened in Venice. In Venice classification, the term 'PPH' was abandoned in favor of 'idiopathic' within the group of disease known as 'PAH'.

Titulus Scuola: the new file classification schema for Italian schools

Directory of Open Access Journals (Sweden)

Gianni Penzo Doria

2017-05-01

Full Text Available This article presents the new file classification schema national for Italian schools, produced by the Italian Directorate General of Archives of the Ministry for Cultural Heritage, within the project Titulus Scuola. This classification schema represents the starting point for a standard documental system, aimed at the digital administration.

Locality-preserving sparse representation-based classification in hyperspectral imagery

Science.gov (United States)

Gao, Lianru; Yu, Haoyang; Zhang, Bing; Li, Qingting

2016-10-01

This paper proposes to combine locality-preserving projections (LPP) and sparse representation (SR) for hyperspectral image classification. The LPP is first used to reduce the dimensionality of all the training and testing data by finding the optimal linear approximations to the eigenfunctions of the Laplace Beltrami operator on the manifold, where the high-dimensional data lies. Then, SR codes the projected testing pixels as sparse linear combinations of all the training samples to classify the testing pixels by evaluating which class leads to the minimum approximation error. The integration of LPP and SR represents an innovative contribution to the literature. The proposed approach, called locality-preserving SR-based classification, addresses the imbalance between high dimensionality of hyperspectral data and the limited number of training samples. Experimental results on three real hyperspectral data sets demonstrate that the proposed approach outperforms the original counterpart, i.e., SR-based classification.

International proposal for an acoustic classification scheme for dwellings

DEFF Research Database (Denmark)

Rasmussen, Birgit

2014-01-01

Acoustic classification schemes specify different quality levels for acoustic conditions. Regulations and classification schemes for dwellings typically include criteria for airborne and impact sound insulation, façade sound insulation and service equipment noise. However, although important...... classes, implying also trade barriers. Thus, a harmonized classification scheme would be useful, and the European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions", running 2009-2013 with members from 32 countries, including three overseas...... for quality of life, information about acoustic conditions is rarely available, neither for new or existing housing. Regulatory acoustic requirements will, if enforced, ensure a corresponding quality for new dwellings, but satisfactory conditions for occupants are not guaranteed. Consequently, several...

Definition and classification of epilepsy. Classification of epileptic seizures 2016

Directory of Open Access Journals (Sweden)

K. Yu. Mukhin

2017-01-01

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

Accurate classification of brain gliomas by discriminate dictionary learning based on projective dictionary pair learning of proton magnetic resonance spectra.

Science.gov (United States)

Adebileje, Sikiru Afolabi; Ghasemi, Keyvan; Aiyelabegan, Hammed Tanimowo; Saligheh Rad, Hamidreza

2017-04-01

Proton magnetic resonance spectroscopy is a powerful noninvasive technique that complements the structural images of cMRI, which aids biomedical and clinical researches, by identifying and visualizing the compositions of various metabolites within the tissues of interest. However, accurate classification of proton magnetic resonance spectroscopy is still a challenging issue in clinics due to low signal-to-noise ratio, overlapping peaks of metabolites, and the presence of background macromolecules. This paper evaluates the performance of a discriminate dictionary learning classifiers based on projective dictionary pair learning method for brain gliomas proton magnetic resonance spectroscopy spectra classification task, and the result were compared with the sub-dictionary learning methods. The proton magnetic resonance spectroscopy data contain a total of 150 spectra (74 healthy, 23 grade II, 23 grade III, and 30 grade IV) from two databases. The datasets from both databases were first coupled together, followed by column normalization. The Kennard-Stone algorithm was used to split the datasets into its training and test sets. Performance comparison based on the overall accuracy, sensitivity, specificity, and precision was conducted. Based on the overall accuracy of our classification scheme, the dictionary pair learning method was found to outperform the sub-dictionary learning methods 97.78% compared with 68.89%, respectively. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Stream Classification Tool User Manual: For Use in Applications in Hydropower-Related Evironmental Mitigation

Energy Technology Data Exchange (ETDEWEB)

McManamay, Ryan A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Troia, Matthew J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); DeRolph, Christopher R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Samu, Nicole M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2016-01-01

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 level 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.

Controlled cooling of an electronic system based on projected conditions

Science.gov (United States)

David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.

2015-08-18

Energy efficient control of a cooling system cooling an electronic system is provided based, in part, on projected conditions. The control includes automatically determining an adjusted control setting(s) for an adjustable cooling component(s) of the cooling system. The automatically determining is based, at least in part, on projected power consumed by the electronic system at a future time and projected temperature at the future time of a heat sink to which heat extracted is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the cooling system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on an experimentally obtained model(s) relating the targeted temperature and power consumption of the adjustable cooling component(s) of the cooling system.

Projections of meteorological and snow conditions in the Pyrenees using adjusted EURO-CORDEX climate projections

Science.gov (United States)

Verfaillie, Deborah; Déqué, Michel; Morin, Samuel; Soubeyroux, Jean-Michel; Lafaysse, Matthieu

2017-04-01

Current and future availability of seasonal snow is a recurring topic in mountain regions such as the Pyrenees, where winter tourism and hydropower production are large contributors to the regional revenues in France, Spain and Andorra. Associated changes in river discharges, their consequences on water storage management, the future vulnerability of Pyrenean ecosystems as well as the occurrence of climate-related hazards such as debris flows and avalanches are also under consideration. However, to generate projections of snow conditions, a traditional dynamical downscaling approach featuring spatial resolutions typically between 10 and 50 km is not sufficient to capture the fine-scale processes and thresholds at play. Indeed, the altitudinal resolution matters, since the phase of precipitation is mainly controlled by the temperature which is altitude-dependent. Moreover, simulations from general circulation models (GCMs) and regional climate models (RCMs) suffer from biases compared to local observations, and often provide outputs at too coarse time resolution to drive impact models. RCM simulations must therefore be adjusted before they can be used to drive specific models such as land surface models. In this study, time series of hourly temperature, precipitation, wind speed, humidity, and short- and longwave radiation were generated over the Pyrenees for the period 1950-2100, by using a new approach (named ADAMONT for ADjustment of RCM outputs to MOuNTain regions) based on quantile mapping applied to daily data, followed by time disaggregation accounting for weather patterns selection. Meteorological observations used for the quantile mapping consist of the regional scale reanalysis SAFRAN, which operates at the scale of homogeneous areas on the order of 1000 km2 within which meteorological conditions vary only with elevation. SAFRAN combines large-scale NWP reanalysis (ERA40, ARPEGE) with in-situ meteorological observations. The SAFRAN reanalysis is available

Ice Water Classification Using Statistical Distribution Based Conditional Random Fields in RADARSAT-2 Dual Polarization Imagery

Science.gov (United States)

Zhang, Y.; Li, F.; Zhang, S.; Hao, W.; Zhu, T.; Yuan, L.; Xiao, F.

2017-09-01

In this paper, Statistical Distribution based Conditional Random Fields (STA-CRF) algorithm is exploited for improving marginal ice-water classification. Pixel level ice concentration is presented as the comparison of methods based on CRF. Furthermore, in order to explore the effective statistical distribution model to be integrated into STA-CRF, five statistical distribution models are investigated. The STA-CRF methods are tested on 2 scenes around Prydz Bay and Adélie Depression, where contain a variety of ice types during melt season. Experimental results indicate that the proposed method can resolve sea ice edge well in Marginal Ice Zone (MIZ) and show a robust distinction of ice and water.

Atmospheric circulation classification comparison based on wildfires in Portugal

Science.gov (United States)

Pereira, M. G.; Trigo, R. M.

2009-04-01

Atmospheric circulation classifications are not a simple description of atmospheric states but a tool to understand and interpret the atmospheric processes and to model the relation between atmospheric circulation and surface climate and other related variables (Radan Huth et al., 2008). Classifications were initially developed with weather forecasting purposes, however with the progress in computer processing capability, new and more robust objective methods were developed and applied to large datasets prompting atmospheric circulation classification methods to one of the most important fields in synoptic and statistical climatology. Classification studies have been extensively used in climate change studies (e.g. reconstructed past climates, recent observed changes and future climates), in bioclimatological research (e.g. relating human mortality to climatic factors) and in a wide variety of synoptic climatological applications (e.g. comparison between datasets, air pollution, snow avalanches, wine quality, fish captures and forest fires). Likewise, atmospheric circulation classifications are important for the study of the role of weather in wildfire occurrence in Portugal because the daily synoptic variability is the most important driver of local weather conditions (Pereira et al., 2005). In particular, the objective classification scheme developed by Trigo and DaCamara (2000) to classify the atmospheric circulation affecting Portugal have proved to be quite useful in discriminating the occurrence and development of wildfires as well as the distribution over Portugal of surface climatic variables with impact in wildfire activity such as maximum and minimum temperature and precipitation. This work aims to present: (i) an overview the existing circulation classification for the Iberian Peninsula, and (ii) the results of a comparison study between these atmospheric circulation classifications based on its relation with wildfires and relevant meteorological

Local soil classification and crop suitability: Implications for the historical land use and soil management in Monti di Trapani (Sicily)

Science.gov (United States)

Garcia-Vila, Margarita; Corselli, Rocco; Bonet, María Teresa; Lopapa, Giuseppe; Pillitteri, Valentina; Fereres, Elias

2017-04-01

In the past, the lack of technologies (e.g. synthetic fertilizers) to overcome biophysical limitations has played a central role in land use planning. Thus, landscape management and agronomic practices are reactions to local knowledge and perceptions on natural resources, particularly soil. In the framework of the European research project MEMOLA (FP7), the role of local farmers knowledge and perceptions on soil for the historical land use through the spatial distribution of crops and the various management practices have been assessed in three different areas of Monti di Trapani region (Sicily). The identification of the soil classification systems of farmers and the criteria on which it is based, linked to the evaluation of the farmers' ability to identify and map the different soil types, was a key step. Nevertheless, beyond the comparison of the ethnopedological classification approach versus standard soil classification systems, the study also aims at understanding local soil management and land use decisions. The applied methodology was based on an interdisciplinary approach, combining soil science methods and participatory appraisal tools, particularly: i) semi-structured interviews; ii) soil sampling and analysis; iii) discussion groups; and iv) a workshop with local edafologists and agronomists. A rich local glossary of terms associated with the soil conditions and an own soil classification system have been identified in the region. Also, a detailed soil map, including process of soil degradation and soil capability, has been generated. This traditional soil knowledge has conditioned the management and the spatial distribution of the crops, and therefore the configuration of the landscape, until the 1990s. Acknowledgements This work has been funded by the European Union project MEMOLA (Grant agreement no: 613265).

Evaluation of nuclear power plant operating procedures classifications and interfaces: Problems and techniques for improvement

International Nuclear Information System (INIS)

Barnes, V.E.; Radford, L.R.

1987-02-01

This report presents activities and findings of a project designed to evaluate current practices and problems related to procedure classification schemes and procedure interfaces in commercial nuclear power plants. The phrase ''procedure classification scheme'' refers to how plant operating procedures are categorized and indexed (e.g., normal, abnormal, emergency operating procedures). The term ''procedure interface'' refers to how reactor operators are instructed to transition within and between procedures. The project consisted of four key tasks, including (1) a survey of literature regarding problems associated with procedure classifications and interfaces, as well as techniques for overcoming them; (2) interviews with experts in the nuclear industry to discuss the appropriate scope of different classes of operating procedures and techniques for managing interfaces between them; (3) a reanalysis of data gathered about nuclear power plant normal operating and off-normal operating procedures in a related project, ''Program Plan for Assessing and Upgrading Operating Procedures for Nuclear Power Plants''; and (4) solicitation of the comments and expert opinions of a peer review group on the draft project report and on proposed techniques for resolving classification and interface issues. In addition to describing these activities and their results, recommendations for NRC and utility actions to address procedure classification and interface problems are offered

Diagnosis of periodontal diseases using different classification ...

African Journals Online (AJOL)

The codes created for risk factors, periodontal data, and radiographically bone loss were formed as a matrix structure and regarded as inputs for the classification unit. A total of six periodontal conditions was the outputs of the classification unit. The accuracy of the suggested methods was compared according to their ...

Pavement type and wear condition classification from tire cavity acoustic measurements with artificial neural networks.

Science.gov (United States)

Masino, Johannes; Foitzik, Michael-Jan; Frey, Michael; Gauterin, Frank

2017-06-01

Tire road noise is the major contributor to traffic noise, which leads to general annoyance, speech interference, and sleep disturbances. Standardized methods to measure tire road noise are expensive, sophisticated to use, and they cannot be applied comprehensively. This paper presents a method to automatically classify different types of pavement and the wear condition to identify noisy road surfaces. The methods are based on spectra of time series data of the tire cavity sound, acquired under normal vehicle operation. The classifier, an artificial neural network, correctly predicts three pavement types, whereas there are few bidirectional mis-classifications for two pavements, which have similar physical characteristics. The performance measures of the classifier to predict a new or worn out condition are over 94.6%. One could create a digital map with the output of the presented method. On the basis of these digital maps, road segments with a strong impact on tire road noise could be automatically identified. Furthermore, the method can estimate the road macro-texture, which has an impact on the tire road friction especially on wet conditions. Overall, this digital map would have a great benefit for civil engineering departments, road infrastructure operators, and for advanced driver assistance systems.

Tropical Warm Semi-Arid Regions Expanding Over Temperate Latitudes In The Projected 21st Century

Science.gov (United States)

Rajaud, A.; de Noblet, N. I.

2015-12-01

Two billion people today live in drylands, where extreme climatic conditions prevail, and natural resources are limited. Drylands are expected to expand under several scenarios of climatic change. However, relevant adaptation strategies need to account for the aridity level: it conditions the equilibrium tree-cover density, ranging from deserts (hyper-arid) to dense savannas (sub-humid). Here we focus on the evolution of climatically defined warm semi-arid areas, where low-tree density covers can be maintained. We study the global repartition of these regions in the future and the bioclimatic shifts involved. We adopted a bioclimatological approach based on the Köppen climate classification. The warm semi-arid class is characterized by mean annual temperatures over 18°C and a rainfall-limitation criterion. A multi-model ensemble of CMIP5 projections for three representative concentration pathways was selected to analyze future conditions. The classification was first applied to the start, middle and end of the 20th and 21st centuries, in order to localize past and future warm semi-arid regions. Then, time-series for the classification were built to characterize trends and variability in the evolution of those regions. According to the CRU datasets, global expansion of the warm semi-arid area has already started (~+13%), following the global warming trend since the 1900s. This will continue according to all projections, most significantly so outside the tropical belt. Under the "business as usual" scenario, the global warm semi-arid area will increase by 30% and expand 12° poleward in the Northern Hemisphere, according to the multi-model mean. Drying drives the conversion from equatorial sub-humid conditions. Beyond 30° of latitude, cold semi-arid conditions become warm semi-arid through warming, and temperate conditions through combined warming and drying processes. Those various transitions may have drastic but also very distinct ecological and sociological

Topobathymetric LiDAR point cloud processing and landform classification in a tidal environment

Science.gov (United States)

Skovgaard Andersen, Mikkel; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Brandbyge Ernstsen, Verner

2017-04-01

Historically it has been difficult to create high resolution Digital Elevation Models (DEMs) in land-water transition zones due to shallow water depth and often challenging environmental conditions. This gap of information has been reflected as a "white ribbon" with no data in the land-water transition zone. In recent years, the technology of airborne topobathymetric Light Detection and Ranging (LiDAR) has proven capable of filling out the gap by simultaneously capturing topographic and bathymetric elevation information, using only a single green laser. We collected green LiDAR point cloud data in the Knudedyb tidal inlet system in the Danish Wadden Sea in spring 2014. Creating a DEM from a point cloud requires the general processing steps of data filtering, water surface detection and refraction correction. However, there is no transparent and reproducible method for processing green LiDAR data into a DEM, specifically regarding the procedure of water surface detection and modelling. We developed a step-by-step procedure for creating a DEM from raw green LiDAR point cloud data, including a procedure for making a Digital Water Surface Model (DWSM) (see Andersen et al., 2017). Two different classification analyses were applied to the high resolution DEM: A geomorphometric and a morphological classification, respectively. The classification methods were originally developed for a small test area; but in this work, we have used the classification methods to classify the complete Knudedyb tidal inlet system. References Andersen MS, Gergely Á, Al-Hamdani Z, Steinbacher F, Larsen LR, Ernstsen VB (2017). Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment. Hydrol. Earth Syst. Sci., 21: 43-63, doi:10.5194/hess-21-43-2017. Acknowledgements This work was funded by the Danish Council for Independent Research | Natural Sciences through the project "Process-based understanding and

A proposal for a classification of product-related dependencies in development of mechatronic products

DEFF Research Database (Denmark)

Torry-Smith, Jonas; Mortensen, Niels Henrik; Achiche, Sofiane

2014-01-01

to the classification of product-related dependencies. Traditionally these dependencies have been described as appearing between the following product attributes: function, properties and structure. By analysing three mechatronic projects from industry we identified and classified 13 types of product......-related dependencies. Each product-related dependency is described and illustrated using the practical examples from the industrial projects. The value of the classification is evaluated by applying it to an industrial development setting not used for the analysis. The evaluation shows that delays in the project...

Rock suitability classification RSC 2012

Energy Technology Data Exchange (ETDEWEB)

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

2012-12-15

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

Rock suitability classification RSC 2012

International Nuclear Information System (INIS)

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

2012-12-01

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

Employing the International Classification of Functioning, Disability and Health to enhance services for children and youth with chronic physical health conditions and disabilities.

Science.gov (United States)

McDougall, Janette; Horgan, Karen; Baldwin, Patricia; Tucker, Mary Ann; Frid, Pamela

2008-03-01

In 2001, the World Health Organization published the International Classification of Functioning, Disability and Health (ICF). The ICF is just beginning to be used in a variety of clinical and research settings in Canada and worldwide. The purpose of the present article is to describe the initial use of the ICF at an Ontario children's rehabilitation centre, and to consider further uses both within and outside the centre for enhancing services for children and youth with chronic physical health conditions and disabilities, as well as for their families. A description is provided on how the ICF has been used at the centre to guide clinical thinking and practice, and to justify and steer research directions. Plans underway to use the ICF to collect and record functional data at the centre are also described. Finally, recommendations for the use of the ICF to enhance communication among child health professionals across service settings are provided. Used in conjunction with the International Classification of Diseases - Tenth Revision, the ICF's conceptual framework and classification system shows great promise for enhancing the quality of services for children with chronic conditions and their families. This information may assist paediatric specialists, other child health professionals, researchers and administrators to use the ICF in similar settings. It may also stimulate exploration of the use of the ICF for general paediatricians and other service providers in the larger community.

CLASSIFICATION BY USING MULTISPECTRAL POINT CLOUD DATA

Directory of Open Access Journals (Sweden)

C. T. Liao

2012-07-01

Full Text Available Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

Classification by Using Multispectral Point Cloud Data

Science.gov (United States)

Liao, C. T.; Huang, H. H.

2012-07-01

Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

Fiscal 2000 survey report. High-efficiency energy system introduction promotion project for houses and structures - Houses (Technical classification tables prepared by analysis of proposed systems, and comments on the same); 2000 nendo jutaku kenchikubutsu kokoritsu energy system donyu sokushin jigyo (jutaku ni kakawaru mono) teian system no bunseki ni yoru gijutsu bunruihyo oyobi dokaisetsu

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-03-01

As an energy conservation promotion measure, a project is under development for introducing and subsidizing high-efficiency energy systems and for letting their effect known publicly and widely. The number of proposed energy systems has increased greatly and technical divisions to follow in classifying them have become vague, from which problems are now arising over the execution of follow-up checks and the maintenance of fair treatment. In the effort to solve this problem, 376 propositions are analyzed and classified, a technical classification method is proposed, and an instruction manual on the method is compiled. The classification involves (1) proposed classification, (2) variation, (3) energy reduction rate, and (4) tentatively calculated cost. Item (1) deals with the basic classification (air-conditioning, ventilation, and hot water supply, and, to be considered in combination with them, options which are cooking, illumination, and others) and, item (2) covers eight items such as new/old construction, structure, and structural frame. In Chapter 1 of the report, the 376 propositions are put in order according to common classification items and an original classification table is prepared. In Chapter 2, the goals are clarified and the classification principles are defined. In Chapter 3, the classification is checked for its validity and some realistic ways of grouping are described. In Chapter 4, a classification implementation flow chart is shown. (NEDO)

Assessment of an extended version of the Jenkinson-Collison classification on CMIP5 models over Europe

Science.gov (United States)

Otero, Noelia; Sillmann, Jana; Butler, Tim

2018-03-01

A gridded, geographically extended weather type classification has been developed based on the Jenkinson-Collison (JC) classification system and used to evaluate the representation of weather types over Europe in a suite of climate model simulations. To this aim, a set of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) is compared with the circulation from two reanalysis products. Furthermore, we examine seasonal changes between simulated frequencies of weather types at present and future climate conditions. The models are in reasonably good agreement with the reanalyses, but some discrepancies occur in cyclonic days being overestimated over North, and underestimated over South Europe, while anticyclonic situations were overestimated over South, and underestimated over North Europe. Low flow conditions were generally underestimated, especially in summer over South Europe, and Westerly conditions were generally overestimated. The projected frequencies of weather types in the late twenty-first century suggest an increase of Anticyclonic days over South Europe in all seasons except summer, while Westerly days increase over North and Central Europe, particularly in winter. We find significant changes in the frequency of Low flow conditions and the Easterly type that become more frequent during the warmer seasons over Southeast and Southwest Europe, respectively. Our results indicate that in winter the Westerly type has significant impacts on positive anomalies of maximum and minimum temperature over most of Europe. Except in winter, the warmer temperatures are linked to Easterlies, Anticyclonic and Low Flow conditions, especially over the Mediterranean area. Furthermore, we show that changes in the frequency of weather types represent a minor contribution of the total change of European temperatures, which would be mainly driven by changes in the temperature anomalies associated with the weather types themselves.

Effects of baseline conditions on the simulated hydrologic response to projected climate change

Science.gov (United States)

Koczot, Kathryn M.; Markstrom, Steven L.; Hay, Lauren E.

2011-01-01

Changes in temperature and precipitation projected from five general circulation models, using one late-twentieth-century and three twenty-first-century emission scenarios, were downscaled to three different baseline conditions. Baseline conditions are periods of measured temperature and precipitation data selected to represent twentieth-century climate. The hydrologic effects of the climate projections are evaluated using the Precipitation-Runoff Modeling System (PRMS), which is a watershed hydrology simulation model. The Almanor Catchment in the North Fork of the Feather River basin, California, is used as a case study. Differences and similarities between PRMS simulations of hydrologic components (i.e., snowpack formation and melt, evapotranspiration, and streamflow) are examined, and results indicate that the selection of a specific time period used for baseline conditions has a substantial effect on some, but not all, hydrologic variables. This effect seems to be amplified in hydrologic variables, which accumulate over time, such as soil-moisture content. Results also indicate that uncertainty related to the selection of baseline conditions should be evaluated using a range of different baseline conditions. This is particularly important for studies in basins with highly variable climate, such as the Almanor Catchment.

75 FR 65615 - Conditional Commitment for a Federal Loan Guarantee for Project Financing for Southwest Intertie...

Science.gov (United States)

2010-10-26

... DEPARTMENT OF ENERGY Conditional Commitment for a Federal Loan Guarantee for Project Financing for... based on the analysis in the Final Environmental Impact Statement for Project Financing for Southwest... support of debt financing for transmission infrastructure investment projects located in the United States...

[Changes introduced into the recent International Classification of Headache Disorders: ICHD-III beta classification].

Science.gov (United States)

Belvis, Robert; Mas, Natàlia; Roig, Carles

2015-01-16

The International Headache Society (IHS) has published the third edition of the International Classification of Headache Disorders (ICHD-III beta), the most commonly used guide to diagnosing headaches in the world. To review the recent additions to the guide, to explain the new entities that appear in it and to compare the conditions that have had their criteria further clarified against the criteria in the previous edition. We have recorded a large number of clarifications in the criteria in practically all the headaches and neuralgias in the classification, but the conditions that have undergone the most significant clarifications are chronic migraine, primary headache associated with sexual activity, short-lasting unilateral neuralgiform headache attacks, new daily persistent headache, medication-overuse headache, syndrome of transient headache and neurological deficits with cerebrospinal fluid lymphocytosis. The most notable new entities that have been incorporated are external-compression headache, cold-stimulus headache, nummular headache, headache attributed to aeroplane travel and headache attributed to autonomic dysreflexia. Another point to be highlighted is the case of the new headaches (still not considered entities in their own right) included in the appendix, some of the most noteworthy being epicrania fugax, vestibular migraine and infantile colic. The IHS recommends no longer using the previous classification and changing over to the new classification (ICHD-III beta) in healthcare, teaching and research, in addition to making this new guide as widely known as possible.

Maximum entropy PDF projection: A review

Science.gov (United States)

Baggenstoss, Paul M.

2017-06-01

We review maximum entropy (MaxEnt) PDF projection, a method with wide potential applications in statistical inference. The method constructs a sampling distribution for a high-dimensional vector x based on knowing the sampling distribution p(z) of a lower-dimensional feature z = T (x). Under mild conditions, the distribution p(x) having highest possible entropy among all distributions consistent with p(z) may be readily found. Furthermore, the MaxEnt p(x) may be sampled, making the approach useful in Monte Carlo methods. We review the theorem and present a case study in model order selection and classification for handwritten character recognition.

Supervised Cross-Modal Factor Analysis for Multiple Modal Data Classification

KAUST Repository

Wang, Jingbin

2015-10-09

In this paper we study the problem of learning from multiple modal data for purpose of document classification. In this problem, each document is composed two different modals of data, i.e., An image and a text. Cross-modal factor analysis (CFA) has been proposed to project the two different modals of data to a shared data space, so that the classification of a image or a text can be performed directly in this space. A disadvantage of CFA is that it has ignored the supervision information. In this paper, we improve CFA by incorporating the supervision information to represent and classify both image and text modals of documents. We project both image and text data to a shared data space by factor analysis, and then train a class label predictor in the shared space to use the class label information. The factor analysis parameter and the predictor parameter are learned jointly by solving one single objective function. With this objective function, we minimize the distance between the projections of image and text of the same document, and the classification error of the projection measured by hinge loss function. The objective function is optimized by an alternate optimization strategy in an iterative algorithm. Experiments in two different multiple modal document data sets show the advantage of the proposed algorithm over other CFA methods.

Typology of local government’s projects and it’s using for methodological support of the project’s ground

OpenAIRE

Y. P. Sharov; D. H. Bezugliy

2016-01-01

Taking into account diversity of local government’s projects, traditional project’s technologies of business management can be use for it with some constraints. Present project’s classifications are imperfect, inadequate for modern conditions of local government, have week applied orientation. The approach for systematization of project’s diversity in local government, which realized as typology of local government’s projects, is decrypted in the article. Use of the typology for forming recom...

On music genre classification via compressive sampling

DEFF Research Database (Denmark)

Sturm, Bob L.

2013-01-01

Recent work \\cite{Chang2010} combines low-level acoustic features and random projection (referred to as ``compressed sensing'' in \\cite{Chang2010}) to create a music genre classification system showing an accuracy among the highest reported for a benchmark dataset. This not only contradicts previ...

Periodontal manifestations of systemic diseases and developmental and acquired conditions: Consensus report of workgroup 3 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions.

Science.gov (United States)

Jepsen, Søren; Caton, Jack G; Albandar, Jasim M; Bissada, Nabil F; Bouchard, Philippe; Cortellini, Pierpaolo; Demirel, Korkud; de Sanctis, Massimo; Ercoli, Carlo; Fan, Jingyuan; Geurs, Nicolaas C; Hughes, Francis J; Jin, Lijian; Kantarci, Alpdogan; Lalla, Evanthia; Madianos, Phoebus N; Matthews, Debora; McGuire, Michael K; Mills, Michael P; Preshaw, Philip M; Reynolds, Mark A; Sculean, Anton; Susin, Cristiano; West, Nicola X; Yamazaki, Kazuhisa

2018-06-01

A variety of systemic diseases and conditions can affect the course of periodontitis or have a negative impact on the periodontal attachment apparatus. Gingival recessions are highly prevalent and often associated with hypersensitivity, the development of caries and non-carious cervical lesions on the exposed root surface and impaired esthetics. Occlusal forces can result in injury of teeth and periodontal attachment apparatus. Several developmental or acquired conditions associated with teeth or prostheses may predispose to diseases of the periodontium. The aim of this working group was to review and update the 1999 classification with regard to these diseases and conditions, and to develop case definitions and diagnostic considerations. Discussions were informed by four reviews on 1) periodontal manifestions of systemic diseases and conditions; 2) mucogingival conditions around natural teeth; 3) traumatic occlusal forces and occlusal trauma; and 4) dental prostheses and tooth related factors. This consensus report is based on the results of these reviews and on expert opinion of the participants. Key findings included the following: 1) there are mainly rare systemic conditions (such as Papillon-Lefevre Syndrome, leucocyte adhesion deficiency, and others) with a major effect on the course of periodontitis and more common conditions (such as diabetes mellitus) with variable effects, as well as conditions affecting the periodontal apparatus independently of dental plaque biofilm-induced inflammation (such as neoplastic diseases); 2) diabetes-associated periodontitis should not be regarded as a distinct diagnosis, but diabetes should be recognized as an important modifying factor and included in a clinical diagnosis of periodontitis as a descriptor; 3) likewise, tobacco smoking - now considered a dependence to nicotine and a chronic relapsing medical disorder with major adverse effects on the periodontal supporting tissues - is an important modifier to be included in

Defect detection and classification of galvanized stamping parts based on fully convolution neural network

Science.gov (United States)

Xiao, Zhitao; Leng, Yanyi; Geng, Lei; Xi, Jiangtao

2018-04-01

In this paper, a new convolution neural network method is proposed for the inspection and classification of galvanized stamping parts. Firstly, all workpieces are divided into normal and defective by image processing, and then the defective workpieces extracted from the region of interest (ROI) area are input to the trained fully convolutional networks (FCN). The network utilizes an end-to-end and pixel-to-pixel training convolution network that is currently the most advanced technology in semantic segmentation, predicts result of each pixel. Secondly, we mark the different pixel values of the workpiece, defect and background for the training image, and use the pixel value and the number of pixels to realize the recognition of the defects of the output picture. Finally, the defect area's threshold depended on the needs of the project is set to achieve the specific classification of the workpiece. The experiment results show that the proposed method can successfully achieve defect detection and classification of galvanized stamping parts under ordinary camera and illumination conditions, and its accuracy can reach 99.6%. Moreover, it overcomes the problem of complex image preprocessing and difficult feature extraction and performs better adaptability.

Comparison of four classification methods for brain-computer interface

Czech Academy of Sciences Publication Activity Database

Frolov, A.; Húsek, Dušan; Bobrov, P.

2011-01-01

Roč. 21, č. 2 (2011), s. 101-115 ISSN 1210-0552 R&D Projects: GA MŠk(CZ) 1M0567; GA ČR GA201/05/0079; GA ČR GAP202/10/0262 Institutional research plan: CEZ:AV0Z10300504 Keywords : brain computer interface * motor imagery * visual imagery * EEG pattern classification * Bayesian classification * Common Spatial Patterns * Common Tensor Discriminant Analysis Subject RIV: IN - Informatics, Computer Science Impact factor: 0.646, year: 2011

Projection operators and supplementary conditions for superfields with an arbitrary spin

International Nuclear Information System (INIS)

Sokatchev, E.

1975-01-01

It is shown that a superfield with an external spin j and a nonzero mass contains four non reducible representations of supersymmetry algebra. A general method is proposed for the evolution the representations out of the superfield by using projection operators, derived from Casimir operators. This expansion is also expressed in terms of additional differential conditions

Early classification of pathological heartbeats on wireless body sensor nodes.

Science.gov (United States)

Braojos, Rubén; Beretta, Ivan; Ansaloni, Giovanni; Atienza, David

2014-11-27

Smart Wireless Body Sensor Nodes (WBSNs) are a novel class of unobtrusive, battery-powered devices allowing the continuous monitoring and real-time interpretation of a subject's bio-signals, such as the electrocardiogram (ECG). These low-power platforms, while able to perform advanced signal processing to extract information on heart conditions, are usually constrained in terms of computational power and transmission bandwidth. It is therefore essential to identify in the early stages which parts of an ECG are critical for the diagnosis and, only in these cases, activate on demand more detailed and computationally intensive analysis algorithms. In this work, we present a comprehensive framework for real-time automatic classification of normal and abnormal heartbeats, targeting embedded and resource-constrained WBSNs. In particular, we provide a comparative analysis of different strategies to reduce the heartbeat representation dimensionality, and therefore the required computational effort. We then combine these techniques with a neuro-fuzzy classification strategy, which effectively discerns normal and pathological heartbeats with a minimal run time and memory overhead. We prove that, by performing a detailed analysis only on the heartbeats that our classifier identifies as abnormal, a WBSN system can drastically reduce its overall energy consumption. Finally, we assess the choice of neuro-fuzzy classification by comparing its performance and workload with respect to other state-of-the-art strategies. Experimental results using the MIT-BIH Arrhythmia database show energy savings of as much as 60% in the signal processing stage, and 63% in the subsequent wireless transmission, when a neuro-fuzzy classification structure is employed, coupled with a dimensionality reduction technique based on random projections.

Classifying Classifications

DEFF Research Database (Denmark)

Debus, Michael S.

2017-01-01

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

Language of Czech Medical Reports and Classification Systems in Medicine

Czech Academy of Sciences Publication Activity Database

Přečková, Petra

2010-01-01

Roč. 6, č. 1 (2010), s. 58-65 ISSN 1801-5603 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : terminology, * synonyms * classification systems * thesaurus * nomenclature * electronic health record * interoperability * semantic interoperability * cardiology * atherosclerosis Subject RIV: IN - Informatics, Computer Science http://www.ejbi.org/en/ejbi/article/53-en-language-of-czech-medical-reports- and -classification-systems-in-medicine.html

The last classification of vasculitis

NARCIS (Netherlands)

Kallenberg, Cees G. M.

2008-01-01

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

Enterprise Potential: Essence, Classification and Types

Directory of Open Access Journals (Sweden)

Turylo Anatolii M.

2014-02-01

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

Development of streamflow projections under changing climate conditions over Colorado River basin headwaters

Directory of Open Access Journals (Sweden)

W. P. Miller

2011-07-01

Full Text Available The current drought over the Colorado River Basin has raised concerns that the US Department of the Interior, Bureau of Reclamation (Reclamation may impose water shortages over the lower portion of the basin for the first time in history. The guidelines that determine levels of shortage are affected by relatively short-term (3 to 7 month forecasts determined by the Colorado Basin River Forecast Center (CBRFC using the National Weather Service (NWS River Forecasting System (RFS hydrologic model. While these forecasts by the CBRFC are useful, water managers within the basin are interested in long-term projections of streamflow, particularly under changing climate conditions. In this study, a bias-corrected, statistically downscaled dataset of projected climate is used to force the NWS RFS utilized by the CBRFC to derive projections of streamflow over the Green, Gunnison, and San Juan River headwater basins located within the Colorado River Basin. This study evaluates the impact of changing climate to evapotranspiration rates and contributes to a better understanding of how hydrologic processes change under varying climate conditions. The impact to evapotranspiration rates is taken into consideration and incorporated into the development of streamflow projections over Colorado River headwater basins in this study. Additionally, the NWS RFS is modified to account for impacts to evapotranspiration due to changing temperature over the basin. Adjusting evapotranspiration demands resulted in a 6 % to 13 % average decrease in runoff over the Gunnison River Basin when compared to static evapotranspiration rates. Streamflow projections derived using projections of future climate and the NWS RFS provided by the CBRFC resulted in decreased runoff in 2 of the 3 basins considered. Over the Gunnison and San Juan River basins, a 10 % to 15 % average decrease in basin runoff is projected through the year 2099. However, over the Green River basin, a 5 % to 8

Fuzzy C-means classification for corrosion evolution of steel images

Science.gov (United States)

Trujillo, Maite; Sadki, Mustapha

2004-05-01

An unavoidable problem of metal structures is their exposure to rust degradation during their operational life. Thus, the surfaces need to be assessed in order to avoid potential catastrophes. There is considerable interest in the use of patch repair strategies which minimize the project costs. However, to operate such strategies with confidence in the long useful life of the repair, it is essential that the condition of the existing coatings and the steel substrate can be accurately quantified and classified. This paper describes the application of fuzzy set theory for steel surfaces classification according to the steel rust time. We propose a semi-automatic technique to obtain image clustering using the Fuzzy C-means (FCM) algorithm and we analyze two kinds of data to study the classification performance. Firstly, we investigate the use of raw images" pixels without any pre-processing methods and neighborhood pixels. Secondly, we apply Gaussian noise to the images with different standard deviation to study the FCM method tolerance to Gaussian noise. The noisy images simulate the possible perturbations of the images due to the weather or rust deposits in the steel surfaces during typical on-site acquisition procedures

Comparison and analysis for item classifications between AP1000 and traditional PWR

International Nuclear Information System (INIS)

Luo Shuiyun; Liu Xiaoyan

2012-01-01

The comparison and analysis for the safety classification, seismic category, code classification and QA classification between AP1000 and traditional PWR were presented. The safety could be guaranteed and the construction and manufacture costs could be cut down since all sorts of AP1000 classifications. It is suggested that the QA classification and the QA requirements correspond to the national conditions should be drafted in the process of AP1000 domestication. (authors)

Towards a unified classification of the ectodermal dysplasias: opportunities outweigh challenges.

LENUS (Irish Health Repository)

Irvine, Alan D

2012-02-01

The ectodermal dysplasias include a complex and highly diverse group of heritable disorders that share in common developmental abnormalities of ectodermal derivatives. The broader definition of ectodermal dysplasias (as heritable disorders involving at least two of the ectodermal derivatives nails, teeth, hair, and eccrine sweat glands) encompasses 170-200 conditions. Some conditions included by this definition are relatively common; others are rare and, in some cases, family-specific. Classification of the ectodermal dysplasias has largely been approached by categorizing patterns of clinical findings (phenotypic grouping). In the last 2 decades great progress has been made in understanding the molecular pathogenesis and inter-relatedness of some of these conditions and a new consensus approach to classification that incorporates this new information is needed. A comprehensive and definitive classification of these disorders would be highly valuable for the many stakeholders in ED. As disease-specific molecular treatments are developed, accurate classification will assume greater importance in designing registries to enable rapid identification of those with rare disorders who may wish to participate in clinical trials. Ideally a working classification of such a disparate collection of conditions would have a design and architecture that would facilitate easy accessibility by each of the key stakeholder groups and would encourage enhanced interaction between these parties. Attaining this objective is a major challenge but is achievable. This article reviews the historical-clinical perspective and the impact of recent developments in molecular biology in the field. Reflections are offered as to the future direction of classification systems in these disorders.

Conditions for monograph projectsʼ by preservice teachers: lessons from the long and winding route

Directory of Open Access Journals (Sweden)

Melba Libia Cárdenas

2011-04-01

Full Text Available This paper is based on the analysis of the nature of monograph projects undertaken by pre-service teachers at the Universidad Nacional de Colombia. It will examine the main factors that, according to the participants of a case-study, favour or limit the development of those projects. On the basis of our findings, we highlight the conditions associated with the successful fulfilment of what students are required to do in monograph projects.

Cirse Quality Assurance Document and Standards for Classification of Complications: The Cirse Classification System.

Science.gov (United States)

Filippiadis, D K; Binkert, C; Pellerin, O; Hoffmann, R T; Krajina, A; Pereira, P L

2017-08-01

Interventional radiology provides a wide variety of vascular, nonvascular, musculoskeletal, and oncologic minimally invasive techniques aimed at therapy or palliation of a broad spectrum of pathologic conditions. Outcome data for these techniques are globally evaluated by hospitals, insurance companies, and government agencies targeting in a high-quality health care policy, including reimbursement strategies. To analyze effectively the outcome of a technique, accurate reporting of complications is necessary. Throughout the literature, numerous classification systems for complications grading and classification have been reported. Until now, there has been no method for uniform reporting of complications both in terms of definition and grading. The purpose of this CIRSE guideline is to provide a classification system of complications based on combining outcome and severity of sequelae. The ultimate challenge will be the adoption of this system by practitioners in different countries and health economies within the European Union and beyond.

Updated United Nations Framework Classification for reserves and resources of extractive industries

Science.gov (United States)

Ahlbrandt, T.S.; Blaise, J.R.; Blystad, P.; Kelter, D.; Gabrielyants, G.; Heiberg, S.; Martinez, A.; Ross, J.G.; Slavov, S.; Subelj, A.; Young, E.D.

2004-01-01

The United Nations have studied how the oil and gas resource classification developed jointly by the SPE, the World Petroleum Congress (WPC) and the American Association of Petroleum Geologists (AAPG) could be harmonized with the United Nations Framework Classification (UNFC) for Solid Fuel and Mineral Resources (1). The United Nations has continued to build on this and other works, with support from many relevant international organizations, with the objective of updating the UNFC to apply to the extractive industries. The result is the United Nations Framework Classification for Energy and Mineral Resources (2) that this paper will present. Reserves and resources are categorized with respect to three sets of criteria: ??? Economic and commercial viability ??? Field project status and feasibility ??? The level of geologic knowledge The field project status criteria are readily recognized as the ones highlighted in the SPE/WPC/AAPG classification system of 2000. The geologic criteria absorb the rich traditions that form the primary basis for the Russian classification system, and the ones used to delimit, in part, proved reserves. Economic and commercial criteria facilitate the use of the classification in general, and reflect the commercial considerations used to delimit proved reserves in particular. The classification system will help to develop a common understanding of reserves and resources for all the extractive industries and will assist: ??? International and national resources management to secure supplies; ??? Industries' management of business processes to achieve efficiency in exploration and production; and ??? An appropriate basis for documenting the value of reserves and resources in financial statements.

Convergence rates in constrained Tikhonov regularization: equivalence of projected source conditions and variational inequalities

International Nuclear Information System (INIS)

Flemming, Jens; Hofmann, Bernd

2011-01-01

In this paper, we enlighten the role of variational inequalities for obtaining convergence rates in Tikhonov regularization of nonlinear ill-posed problems with convex penalty functionals under convexity constraints in Banach spaces. Variational inequalities are able to cover solution smoothness and the structure of nonlinearity in a uniform manner, not only for unconstrained but, as we indicate, also for constrained Tikhonov regularization. In this context, we extend the concept of projected source conditions already known in Hilbert spaces to Banach spaces, and we show in the main theorem that such projected source conditions are to some extent equivalent to certain variational inequalities. The derived variational inequalities immediately yield convergence rates measured by Bregman distances

Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios

Science.gov (United States)

Erikson, Li H.; Hegermiller, Christie; Barnard, Patrick; Ruggiero, Peter; van Ormondt, Martin

2015-01-01

Hindcast and 21st century winds, simulated by General Circulation Models (GCMs), were used to drive global- and regional-scale spectral wind-wave generation models in the Pacific Ocean Basin to assess future wave conditions along the margins of the North American west coast and Hawaiian Islands. Three-hourly winds simulated by four separate GCMs were used to generate an ensemble of wave conditions for a recent historical time-period (1976–2005) and projections for the mid and latter parts of the 21st century under two radiative forcing scenarios (RCP 4.5 and RCP 8.5), as defined by the fifth phase of the Coupled Model Inter-comparison Project (CMIP5) experiments. Comparisons of results from historical simulations with wave buoy and ERA-Interim wave reanalysis data indicate acceptable model performance of wave heights, periods, and directions, giving credence to generating projections. Mean and extreme wave heights are projected to decrease along much of the North American west coast. Extreme wave heights are projected to decrease south of ∼50°N and increase to the north, whereas extreme wave periods are projected to mostly increase. Incident wave directions associated with extreme wave heights are projected to rotate clockwise at the eastern end of the Aleutian Islands and counterclockwise offshore of Southern California. Local spatial patterns of the changing wave climate are similar under the RCP 4.5 and RCP 8.5 scenarios, but stronger magnitudes of change are projected under RCP 8.5. Findings of this study are similar to previous work using CMIP3 GCMs that indicates decreasing mean and extreme wave conditions in the Eastern North Pacific, but differ from other studies with respect to magnitude and local patterns of change. This study contributes toward a larger ensemble of global and regional climate projections needed to better assess uncertainty of potential future wave climate change, and provides model boundary conditions for assessing the impacts of

The Ecohydrological Context of Drought and Classification of Plant Responses

Science.gov (United States)

Feng, X.; Ackerly, D.; Dawson, T. E.; Manzoni, S.; Skelton, R. P.; Vico, G.; Thompson, S. E.

2017-12-01

Many recent studies on drought-induced vegetation mortality have explored how plant functional traits, and classifications of such traits along axes of, e.g., isohydry - anisohydry, might contribute to predicting drought survival and recovery. As these studies proliferate, concerns are growing about the consistency and predictive value of such classifications. Here, we outline the basis for a systematic classification of drought strategies that accounts for both environmental conditions and functional traits. We (1) identify drawbacks of exiting isohydricity and trait-based metrics, (2) identify major axes of trait and environmental variation that determine drought mortality pathways (hydraulic failure and carbon starvation) using non-dimensional trait groups, and (3) demonstrate that these trait groupings predict physiological drought outcomes using both measured and synthetic data. In doing so we untangle some confounding effects of environment and trait variations that undermine current classification schemes, outline a pathway to progress towards a general classification of drought vulnerability, and advocate for more careful treatment of the environmental conditions within which plant drought responses occur.

Experimental conditions and monitoring items of the prototype repository project (PRP). Research document

International Nuclear Information System (INIS)

Sugita, Yutaka; Ito, Akira; Kawakami, Susumu

2003-03-01

Various experiments are ongoing in the underground research facility 'the Hard Rock Laboratory (HRL)' of SKB in Sweden for the geological disposal of the high-level radioactive waste. International joint project Prototype Repository Project (PRP) is one of the experiments in the HRL which has some engineered barrier systems and to study the coupled behavior happening in and around the engineered barrier system. JNC has joined this international joint project PRP to obtain the information of the coupled behavior on such systematic engineered barrier system and to apply the JNC's coupled THMC analytical code to the prediction and back analysis of the PRP. The analytical code will be verified through these analyses in this project. JNC can apply the verified analytical code to assess the coupled behavior in Japan. This report summarizes the experimental conditions and monitoring items of the PRP. (author)

WE-AB-207A-02: John’s Equation Based Consistency Condition and Incomplete Projection Restoration Upon Circular Orbit CBCT

International Nuclear Information System (INIS)

Ma, J; Qi, H; Wu, S; Xu, Y; Zhou, L; Yan, H

2016-01-01

Purpose: In transmitted X-ray tomography imaging, projections are sometimes incomplete due to a variety of reasons, such as geometry inaccuracy, defective detector cells, etc. To address this issue, we have derived a direct consistency condition based on John’s Equation, and proposed a method to effectively restore incomplete projections based on this consistency condition. Methods: Through parameter substitutions, we have derived a direct consistency condition equation from John’s equation, in which the left side is only projection derivative of view and the right side is projection derivative of other geometrical parameters. Based on this consistency condition, a projection restoration method is proposed, which includes five steps: 1) Forward projecting reconstructed image and using linear interpolation to estimate the incomplete projections as the initial result; 2) Performing Fourier transform on the projections; 3) Restoring the incomplete frequency data using the consistency condition equation; 4) Performing inverse Fourier transform; 5) Repeat step 2)∼4) until our criteria is met to terminate the iteration. Results: A beam-blocking-based scatter correction case and a bad-pixel correction case were used to demonstrate the efficacy and robustness of our restoration method. The mean absolute error (MAE), signal noise ratio (SNR) and mean square error (MSE) were employed as our evaluation metrics of the reconstructed images. For the scatter correction case, the MAE is reduced from 63.3% to 71.7% with 4 iterations. Compared with the existing Patch’s method, the MAE of our method is further reduced by 8.72%. For the bad-pixel case, the SNR of the reconstructed image by our method is increased from 13.49% to 21.48%, with the MSE being decreased by 45.95%, compared with linear interpolation method. Conclusion: Our studies have demonstrated that our restoration method based on the new consistency condition could effectively restore the incomplete projections

Genome-Wide Comparative Gene Family Classification

Science.gov (United States)

Frech, Christian; Chen, Nansheng

2010-01-01

Correct classification of genes into gene families is important for understanding gene function and evolution. Although gene families of many species have been resolved both computationally and experimentally with high accuracy, gene family classification in most newly sequenced genomes has not been done with the same high standard. This project has been designed to develop a strategy to effectively and accurately classify gene families across genomes. We first examine and compare the performance of computer programs developed for automated gene family classification. We demonstrate that some programs, including the hierarchical average-linkage clustering algorithm MC-UPGMA and the popular Markov clustering algorithm TRIBE-MCL, can reconstruct manual curation of gene families accurately. However, their performance is highly sensitive to parameter setting, i.e. different gene families require different program parameters for correct resolution. To circumvent the problem of parameterization, we have developed a comparative strategy for gene family classification. This strategy takes advantage of existing curated gene families of reference species to find suitable parameters for classifying genes in related genomes. To demonstrate the effectiveness of this novel strategy, we use TRIBE-MCL to classify chemosensory and ABC transporter gene families in C. elegans and its four sister species. We conclude that fully automated programs can establish biologically accurate gene families if parameterized accordingly. Comparative gene family classification finds optimal parameters automatically, thus allowing rapid insights into gene families of newly sequenced species. PMID:20976221

Classification of Ship Routing and Scheduling Problems in Liner Shipping

DEFF Research Database (Denmark)

Kjeldsen, Karina Hjortshøj

2011-01-01

This article provides a classification scheme for ship routing and scheduling problems in liner shipping in line with the current and future operational conditions of the liner shipping industry. Based on the classification, the literature is divided into groups whose main characteristics...

Compas project stress analysis of HLW containers: behaviour under realistic disposal conditions

International Nuclear Information System (INIS)

Ove Arup and Partners, London

1990-01-01

The Compas project is concerned with the structural performance of metal overpacks which may be used to encapsulate vitrified high-level waste (HLW) forms before disposal in deep geological repositories. In this final stage of the project, analysis of an HLW overpack of realistic design is performed to predict its behaviour when subjected to likely repository loads. This analysis work is undertaken with the benefit of experience gained in previous phases of the project in which the ability to accurately predict overpack behaviour, when subjected to a uniform external pressure, was demonstrated. Burial in clay, granite and salt environments has been considered and two distinct loading arrangements identified, in an attempt to represent the worst conditions that could be imposed by such media. The analysis successfully demonstrates the ability of the containers to withstand extreme, yet credible, repository loads

Knowledge-based sea ice classification by polarimetric SAR

DEFF Research Database (Denmark)

Skriver, Henning; Dierking, Wolfgang

2004-01-01

Polarimetric SAR images acquired at C- and L-band over sea ice in the Greenland Sea, Baltic Sea, and Beaufort Sea have been analysed with respect to their potential for ice type classification. The polarimetric data were gathered by the Danish EMISAR and the US AIRSAR which both are airborne...... systems. A hierarchical classification scheme was chosen for sea ice because our knowledge about magnitudes, variations, and dependences of sea ice signatures can be directly considered. The optimal sequence of classification rules and the rules themselves depend on the ice conditions/regimes. The use...... of the polarimetric phase information improves the classification only in the case of thin ice types but is not necessary for thicker ice (above about 30 cm thickness)...

Application of United Nations Framework Classification – 2009 (UNFC-2009) to nuclear fuel resources

International Nuclear Information System (INIS)

Tulsidas, Harikrishnan; Li Shengxiang; Van Gosen, Bradley

2014-01-01

United Nations Framework Classification for Fossil Fuel and Mineral Reserves and Resources 2009: • Generic, principles-based system: – Applicable to both solid minerals and fluids; • Applications in: – International energy studies; – National resource reporting; – Company project management; – Financial reporting; • 3-D classification of resources on the basis of: – Socio-economic criteria (E); – Project maturity (technical feasibility) (F); – Geological knowledge (G); • A key goal of UNFC-2009 is to provide a tool to facilitate global communications: – Uses a numerical coding system; – Language independent reporting

Map of the portfolio of projects of energy efficiency and of renewable energies by the AFD group and the FFEM

International Nuclear Information System (INIS)

Guillaumie, Koulm; Briand, Claude; Ries, Alain

2007-09-01

The AFD (the French Agency for Development) and the FFEM (French Fund for World Environment) are involved in cooperation and partnership projects for the development of energy efficiency, notably, but not only, in developing and emerging countries. This report first proposes a classification of these projects according to a typology which comprises the concerned sectors (urban planning and housing, fuels, hydroelectricity and wind energy, electricity distribution, industries and services, transports and mobility, capacity building, multi-sector), the intervener (AFD, FFEM, and Proparco, an AFD's subsidy), the project evolution in time (number of projects, evolution of funding), the funding type (loan types, subsidy, credit line), and the geographical area. The second part discusses the conditions to start projects in energy management: legal framework, economic conditions, funding, social and environmental factors, and technical factors. Appendices propose a set of ten technical sheets which indicate and discuss conditions of success as well as obstacles for different types of projects: big dams, mini hydroelectric projects, wind energy, biomass/biogas co-generation, bio-fuels, decentralised rural electrification based on renewable energy projects, collective transports and energy efficiency in transports, development of partnerships and institutional support, multi-sector tools of investment, and carbon market

Authorization Basis Safety Classification of Transfer Bay Bridge Crane at the 105-K Basins

International Nuclear Information System (INIS)

CHAFFEE, G.A.

2000-01-01

This supporting document provides the bases for the safety classification for the K Basin transfer bay bridge crane and the bases for the Structures, Systems, and Components (SSC) safety classification. A table is presented that delineates the safety significant components. This safety classification is based on a review of the Authorization Basis (AB). This Authorization Basis review was performed regarding AB and design baseline issues. The primary issues are: (1) What is the AB for the safety classification of the transfer bay bridge crane? (2) What does the SSC safety classification ''Safety Significant'' or ''Safety Significant for Design Only'' mean for design requirements and quality requirements for procurement, installation and maintenance (including replacement of parts) activities for the crane during its expected life time? The AB information on the crane was identified based on review of Department of Energy--Richland Office (RL) and Spent Nuclear Fuel (SNF) Project correspondence, K Basin Safety Analysis Report (SAR) and RL Safety Evaluation Reports (SERs) of SNF Project SAR submittals. The relevant correspondence, actions and activities taken and substantive directions or conclusions of these documents are provided in Appendix A

Project Evaluation under Inflation Condition

International Nuclear Information System (INIS)

Hindy, M.; El Missiry, P.

2004-01-01

This paper analyzes the role of inflation in capital budgeting and attempts to introduce solutions to such implication in order to make the appropriate decision for the firm' stockholders under these circumstances. Inflation leads to biasness in evaluating the investment projects, due to its impact on the cash flow, the discount rate, the initial investment cost, and the depreciation. This paper has shown that the capital budgeting process is not neutral with respect to inflation, as the output prices will raise as well as the operating and capital expenditures will also be adjusted due to inflation. In addition, it has shown that it is reasonable to expect that the cost of capital will increase as a result of an increase in the real interest rate, the inflation premium, and the cost of equity. Of critical importance is the basis used in calculating the annual depreciation which may lead to the transfer of wealth from the investment projects to the government and will result in underestimating the net present value of the investment projects, if these depreciation charges is calculated based upon the historical values and not on the replacement cost of the fixed assets

Advances in the classification and treatment of mastocytosis

DEFF Research Database (Denmark)

Valent, Peter; Akin, Cem; Hartmann, Karin

2017-01-01

Mastocytosis is a term used to denote a heterogeneous group of conditions defined by the expansion and accumulation of clonal (neoplastic) tissue mast cells in various organs. The classification of the World Health Organization (WHO) divides the disease into cutaneous mastocytosis, systemic...... leukemia. The clinical impact and prognostic value of this classification has been confirmed in numerous studies, and its basic concept remains valid. However, refinements have recently been proposed by the consensus group, the WHO, and the European Competence Network on Mastocytosis. In addition, new...... of mastocytosis, with emphasis on classification, prognostication, and emerging new treatment options in advanced systemic mastocytosis....

CIN classification and prediction using machine learning methods

Science.gov (United States)

Chirkina, Anastasia; Medvedeva, Marina; Komotskiy, Evgeny

2017-06-01

The aim of this paper is a comparison of the existing classification algorithms with different parameters, and selection those ones, which allows solving the problem of primary diagnosis of cervical intraepithelial neoplasia (CIN), as it characterizes the condition of the body in the precancerous stage. The paper describes a feature selection process, as well as selection of the best models for a multiclass classification.

Extending an emergency classification expert system to the real-time environment

International Nuclear Information System (INIS)

Greene, K.R.; Robinson, A.H.

1990-01-01

The process of determining emergency action level (EAL) during real or simulated emergencies at the Trojan nuclear power plant was automated in 1988 with development of the EM-CLASS expert system. This system serves to replace the manual flip-chart method of determining the EAL. While the task of performing the classification is more reliable when using EM-CLASS, it still takes as long to determine the appropriate EAL with EM-CLASS as it does with the flowchart tracing method currently in use. During a plant emergency, an environment will exist where there are not enough resources to complete all of the desired tasks. To change this condition, some tasks must be accomplished with greater efficiency. The EM-CLASS application may be improved by taking advantage of the fact that most of the responses to the questions in the emergency classification procedure, EP-001, are available directly from plant measurements. This information could be passed to the expert system electronically. A prototype demonstration of a real-time emergency classification expert system has been developed. It repetitively performs the consultation, acquiring the necessary data electronically when possible and from the user when electronic data are unavailable. The expert system is being tested with scenarios from the drills and graded exercises that have taken place at the Trojan nuclear power plant. The goal of this project is to install the system on the plant simulator and/or the plant computer

High Dimensional Classification Using Features Annealed Independence Rules.

Science.gov (United States)

Fan, Jianqing; Fan, Yingying

2008-01-01

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

Field sampling and data analysis methods for development of ecological land classifications: an application on the Manistee National Forest.

Science.gov (United States)

George E. Host; Carl W. Ramm; Eunice A. Padley; Kurt S. Pregitzer; James B. Hart; David T. Cleland

1992-01-01

Presents technical documentation for development of an Ecological Classification System for the Manistee National Forest in northwest Lower Michigan, and suggests procedures applicable to other ecological land classification projects. Includes discussion of sampling design, field data collection, data summarization and analyses, development of classification units,...

Stakeholder Salience in ERP Projects

OpenAIRE

Salhotra, Eashan

2014-01-01

The aim of this study is to examine stakeholder involvement in an Enterprise Resource Planning (ERP) System project that involves implementation and improvement of the implemented system. The study targets stakeholders, their classification, and their degree of importance during different phases of an ERP project life cycle, i.e. planning, implementation, stabilisation and improvement. The study shows that stakeholder involvement and their salience vary along the ERP project life cycle a...

Assessing the social sustainability contribution of an infrastructure project under conditions of uncertainty

International Nuclear Information System (INIS)

Sierra, Leonardo A.; Yepes, Víctor; Pellicer, Eugenio

2017-01-01

Assessing the viability of a public infrastructure includes economic, technical and environmental aspects; however, on many occasions, the social aspects are not always adequately considered. This article proposes a procedure to estimate the social sustainability of infrastructure projects under conditions of uncertainty, based on a multicriteria deterministic method. The variability of the method inputs is contributed by the decision-makers. Uncertain inputs are treated through uniform and beta PERT distributions. The Monte Carlo method is used to propagate uncertainty in the method. A case study of a road infrastructure improvement in El Salvador is used to illustrate this treatment. The main results determine the variability of the short and long-term social improvement indices by infrastructure and the probability of the position in the prioritization of the alternatives. The proposed mechanism improves the reliability of the decision making early in infrastructure projects, taking their social contribution into account. The results can complement environmental and economic sustainability assessments. - Highlights: •Estimate the social sustainability of infrastructure projects under conditions of uncertainty •The method uses multicriteria and Monte Carlo techniques and beta PERT distributions •Determines variability of the short and long term social improvement •Determines probability in the prioritization of alternatives •Improves reliability of decision making considering the social contribution

Use of topographic and climatological models in a geographical data base to improve Landsat MSS classification for Olympic National Park

Science.gov (United States)

Cibula, William G.; Nyquist, Maurice O.

1987-01-01

An unsupervised computer classification of vegetation/landcover of Olympic National Park and surrounding environs was initially carried out using four bands of Landsat MSS data. The primary objective of the project was to derive a level of landcover classifications useful for park management applications while maintaining an acceptably high level of classification accuracy. Initially, nine generalized vegetation/landcover classes were derived. Overall classification accuracy was 91.7 percent. In an attempt to refine the level of classification, a geographic information system (GIS) approach was employed. Topographic data and watershed boundaries (inferred precipitation/temperature) data were registered with the Landsat MSS data. The resultant boolean operations yielded 21 vegetation/landcover classes while maintaining the same level of classification accuracy. The final classification provided much better identification and location of the major forest types within the park at the same high level of accuracy, and these met the project objective. This classification could now become inputs into a GIS system to help provide answers to park management coupled with other ancillary data programs such as fire management.

A transient search using combined human and machine classifications

Science.gov (United States)

Wright, Darryl E.; Lintott, Chris J.; Smartt, Stephen J.; Smith, Ken W.; Fortson, Lucy; Trouille, Laura; Allen, Campbell R.; Beck, Melanie; Bouslog, Mark C.; Boyer, Amy; Chambers, K. C.; Flewelling, Heather; Granger, Will; Magnier, Eugene A.; McMaster, Adam; Miller, Grant R. M.; O'Donnell, James E.; Simmons, Brooke; Spiers, Helen; Tonry, John L.; Veldthuis, Marten; Wainscoat, Richard J.; Waters, Chris; Willman, Mark; Wolfenbarger, Zach; Young, Dave R.

2017-12-01

Large modern surveys require efficient review of data in order to find transient sources such as supernovae, and to distinguish such sources from artefacts and noise. Much effort has been put into the development of automatic algorithms, but surveys still rely on human review of targets. This paper presents an integrated system for the identification of supernovae in data from Pan-STARRS1, combining classifications from volunteers participating in a citizen science project with those from a convolutional neural network. The unique aspect of this work is the deployment, in combination, of both human and machine classifications for near real-time discovery in an astronomical project. We show that the combination of the two methods outperforms either one used individually. This result has important implications for the future development of transient searches, especially in the era of Large Synoptic Survey Telescope and other large-throughput surveys.

Ventilation and air conditioning systems in maritime productions units; Panorama dos sistemas de VAC em unidades maritimas de producao

Energy Technology Data Exchange (ETDEWEB)

Guedes, Fernando Pedrosa; Sztajnbok, Ernani Luis [PETROBRAS, Rio de Janeiro, RJ (Brazil); Padua, Carlos Eduardo Dantas de; Passos, Alfredo Silveira [DUOVAC Engenharia Ltda. (Brazil)

2004-07-01

In an Offshore Stationary Production Unit (SPU), the adequate project of the Ventilation and Air Conditioning (VAC) System is not only a thermal comfort requirement but part of the essential safety services of the installation and complement for area classification requirements associated with electrical equipment. The VAC installations are sometimes the object of complaints by onboard team. Problems such as unsatisfactory system performance, high noise levels in the accommodation quarters, offices and other areas and the discomfort caused by unbalanced ventilation and air conditioning systems, are some of the most frequent complaints. Air Conditioning systems are classified as Direct and Indirect Expansion. Decentralized systems with Indirect Expansion has been adopted in PETROBRAS projects. This conception is not used in VAC Systems for platforms installed in North Sea, where the use of Centralized Systems with Direct Expansion are more common. The objective of this work is to compare the VAC conception projects, analyzing their advantages and disadvantages . The evaluation of VAC System in PETROBRAS project, and their steps in SPU development, is also scope of this paper. (author)

A NEW HABITAT CLASSIFICATION AND MANUAL FOR STANDARDIZED HABITAT MAPPING

Directory of Open Access Journals (Sweden)

A. KUN

2007-01-01

Full Text Available Today the documentation of natural heritage with scientific methods but for conservation practice – like mapping of actual vegetation – becomes more and more important. For this purpose mapping guides containing only the names and descriptions of vegetation types are not sufficient. Instead, new, mapping-oriented vegetation classification systems and handbooks are needed. There are different standardised systems fitted to the characteristics of a region already published and used successfully for surveying large territories. However, detailed documentation of the aims and steps of their elaboration is still missing. Here we present a habitat-classification method developed specifically for mapping and the steps of its development. Habitat categories and descriptions reflect site conditions, physiognomy and species composition as well. However, for species composition much lower role was given deliberately than in the phytosociological systems. Recognition and mapping of vegetation types in the field is highly supported by a definition, list of subtypes and list of ‘types not belonging to this habitat category’. Our system is two-dimensional: the first dimension is habitat type, the other is naturalness based habitat quality. The development of the system was conducted in two steps, over 200 mappers already tested it over 7000 field days in different projects.

APPLICATION OF AHP METHOD IN THE IDENTIFICATION AND CLASSIFICATION OF PROJECT SELECTION CRITERIA: AN ENERGY SECTOR CASE STUDY

Directory of Open Access Journals (Sweden)

Silvério, Adriano Augusto

2015-07-01

Full Text Available Choosing from several alternative investment projects in hydropower to build a portfolio of projects is a complex matter. The most commonly used selection model for building the portfolio is the financial method, however it constraints options investments to the economic and financial parameters, which are limiting in nature. Alternatively, this paper proposes the use of multicriterial method Analytic Hierarchy Process – AHP, which incorporates measures to evaluate both quantitative and qualitative data. This method is based on criteria or parameters of operational processes that hinder or facilitate the execution of projects. In order to get the definition of the set of criteria, the Delphi technique was applied to a group of seven experts in managing hydropower projects. Main results show that essential criteria for selection of project investment portfolio, are not limited to financial aspects, but it involves criteria of bureaucratic, organizational, and political environment and technological characters. The conclusion is that the financial potential of hydropower projects are not the only determinants for investments on hydropower projects and, at large, these project are conditioned to other criteria such as, those of bureaucratic and technological nature.

Hygienic aspects of the classification of works with ionizing radiation sources

International Nuclear Information System (INIS)

Poplavskij, K.K.

1978-01-01

Classification is presented of ionizing radiation sources (IRS) the underlying principle of which is the effect of radiation on living organisms. The ways of improving the classification and expanding it by identifying more groups of IRS and defining the terminology more precisely are suggested. On this basis, a classification of IRS-handling activities has been developed and recommendations on conditions of work with each group have been given

A New Classification Approach Based on Multiple Classification Rules

OpenAIRE

Zhongmei Zhou

2014-01-01

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

Classification theorem for principal fibre bundles, Berry's phase, and exact cycle evolution

International Nuclear Information System (INIS)

Bohm, A.; Boya, L.J.; Mostafazadeh, A.; Rudolph, G.

1993-03-01

The relation between the two mathematical interpretations of the geometric (Berry) phase is discussed, using either the fibre bundle over parameter space or over projective Hilbert space. It turns out that these two geometric constructions are linked by the classification theorem for vector bundles. The classification theorem provides the means to classify the parameter space bundles for adiabatic evolution and for non-adiabatic cyclic evolution of the statevectors

Gene selection for microarray data classification via subspace learning and manifold regularization.

Science.gov (United States)

Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

2017-12-19

With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

78 FR 68983 - Cotton Futures Classification: Optional Classification Procedure

Science.gov (United States)

2013-11-18

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

Probabilistic topic modeling for the analysis and classification of genomic sequences

Science.gov (United States)

2015-01-01

Background Studies on genomic sequences for classification and taxonomic identification have a leading role in the biomedical field and in the analysis of biodiversity. These studies are focusing on the so-called barcode genes, representing a well defined region of the whole genome. Recently, alignment-free techniques are gaining more importance because they are able to overcome the drawbacks of sequence alignment techniques. In this paper a new alignment-free method for DNA sequences clustering and classification is proposed. The method is based on k-mers representation and text mining techniques. Methods The presented method is based on Probabilistic Topic Modeling, a statistical technique originally proposed for text documents. Probabilistic topic models are able to find in a document corpus the topics (recurrent themes) characterizing classes of documents. This technique, applied on DNA sequences representing the documents, exploits the frequency of fixed-length k-mers and builds a generative model for a training group of sequences. This generative model, obtained through the Latent Dirichlet Allocation (LDA) algorithm, is then used to classify a large set of genomic sequences. Results and conclusions We performed classification of over 7000 16S DNA barcode sequences taken from Ribosomal Database Project (RDP) repository, training probabilistic topic models. The proposed method is compared to the RDP tool and Support Vector Machine (SVM) classification algorithm in a extensive set of trials using both complete sequences and short sequence snippets (from 400 bp to 25 bp). Our method reaches very similar results to RDP classifier and SVM for complete sequences. The most interesting results are obtained when short sequence snippets are considered. In these conditions the proposed method outperforms RDP and SVM with ultra short sequences and it exhibits a smooth decrease of performance, at every taxonomic level, when the sequence length is decreased. PMID:25916734

Dense Iterative Contextual Pixel Classification using Kriging

DEFF Research Database (Denmark)

Ganz, Melanie; Loog, Marco; Brandt, Sami

2009-01-01

have been proposed to this end, e.g., iterative contextual pixel classification, iterated conditional modes, and other approaches related to Markov random fields. A problem of these methods, however, is their computational complexity, especially when dealing with high-resolution images in which......In medical applications, segmentation has become an ever more important task. One of the competitive schemes to perform such segmentation is by means of pixel classification. Simple pixel-based classification schemes can be improved by incorporating contextual label information. Various methods...... relatively long range interactions may play a role. We propose a new method based on Kriging that makes it possible to include such long range interactions, while keeping the computations manageable when dealing with large medical images....

Text document classification based on mixture models

Czech Academy of Sciences Publication Activity Database

Novovičová, Jana; Malík, Antonín

2004-01-01

Roč. 40, č. 3 (2004), s. 293-304 ISSN 0023-5954 R&D Projects: GA AV ČR IAA2075302; GA ČR GA102/03/0049; GA AV ČR KSK1019101 Institutional research plan: CEZ:AV0Z1075907 Keywords : text classification * text categorization * multinomial mixture model Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.224, year: 2004

New proposals for the international classification of diseases-11 revision of pain diagnoses

DEFF Research Database (Denmark)

Rief, Winfried; Kaasa, Stein; Jensen, Rigmor

2012-01-01

The representation of pain diagnoses in current classification systems like International Classification of Diseases (ICD)-10 and Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV does not adequately reflect the state of the art of pain research, and does not sufficiently support...... the clinical management and research programs for pain conditions. Moreover, there is an urgent need to harmonize classification of pain syndromes of special expert groups (eg, International Classification of Headache Disorders) and general classification systems (eg, ICD-11, DSM-V). Therefore, this paper...

Strategically oriented management and controlling of resource intensive projects

International Nuclear Information System (INIS)

Kemmeter, Sascha

2015-01-01

The book on strategically oriented management and controlling of resource intensive projects covers the following issues: frame of project management and project controlling, classification of the decommissioning of nuclear facilities as resource intensive projects, research design for case studies, results of the study of project management specific characteristics of decommissioning, reference model for the project management of nuclear facility decommissioning.

Classifications of track structures

International Nuclear Information System (INIS)

Paretzke, H.G.

1984-01-01

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

Performance of classification confidence measures in dynamic classifier systems

Czech Academy of Sciences Publication Activity Database

Štefka, D.; Holeňa, Martin

2013-01-01

Roč. 23, č. 4 (2013), s. 299-319 ISSN 1210-0552 R&D Projects: GA ČR GA13-17187S Institutional support: RVO:67985807 Keywords : classifier combining * dynamic classifier systems * classification confidence Subject RIV: IN - Informatics, Computer Science Impact factor: 0.412, year: 2013

Object-Based Land Use Classification of Agricultural Land by Coupling Multi-Temporal Spectral Characteristics and Phenological Events in Germany

Science.gov (United States)

Knoefel, Patrick; Loew, Fabian; Conrad, Christopher

2015-04-01

Crop maps based on classification of remotely sensed data are of increased attendance in agricultural management. This induces a more detailed knowledge about the reliability of such spatial information. However, classification of agricultural land use is often limited by high spectral similarities of the studied crop types. More, spatially and temporally varying agro-ecological conditions can introduce confusion in crop mapping. Classification errors in crop maps in turn may have influence on model outputs, like agricultural production monitoring. One major goal of the PhenoS project ("Phenological structuring to determine optimal acquisition dates for Sentinel-2 data for field crop classification"), is the detection of optimal phenological time windows for land cover classification purposes. Since many crop species are spectrally highly similar, accurate classification requires the right selection of satellite images for a certain classification task. In the course of one growing season, phenological phases exist where crops are separable with higher accuracies. For this purpose, coupling of multi-temporal spectral characteristics and phenological events is promising. The focus of this study is set on the separation of spectrally similar cereal crops like winter wheat, barley, and rye of two test sites in Germany called "Harz/Central German Lowland" and "Demmin". However, this study uses object based random forest (RF) classification to investigate the impact of image acquisition frequency and timing on crop classification uncertainty by permuting all possible combinations of available RapidEye time series recorded on the test sites between 2010 and 2014. The permutations were applied to different segmentation parameters. Then, classification uncertainty was assessed and analysed, based on the probabilistic soft-output from the RF algorithm at the per-field basis. From this soft output, entropy was calculated as a spatial measure of classification uncertainty

Dynamic species classification of microorganisms across time, abiotic and biotic environments-A sliding window approach.

Directory of Open Access Journals (Sweden)

Frank Pennekamp

Full Text Available The development of video-based monitoring methods allows for rapid, dynamic and accurate monitoring of individuals or communities, compared to slower traditional methods, with far reaching ecological and evolutionary applications. Large amounts of data are generated using video-based methods, which can be effectively processed using machine learning (ML algorithms into meaningful ecological information. ML uses user defined classes (e.g. species, derived from a subset (i.e. training data of video-observed quantitative features (e.g. phenotypic variation, to infer classes in subsequent observations. However, phenotypic variation often changes due to environmental conditions, which may lead to poor classification, if environmentally induced variation in phenotypes is not accounted for. Here we describe a framework for classifying species under changing environmental conditions based on the random forest classification. A sliding window approach was developed that restricts temporal and environmentally conditions to improve the classification. We tested our approach by applying the classification framework to experimental data. The experiment used a set of six ciliate species to monitor changes in community structure and behavior over hundreds of generations, in dozens of species combinations and across a temperature gradient. Differences in biotic and abiotic conditions caused simplistic classification approaches to be unsuccessful. In contrast, the sliding window approach allowed classification to be highly successful, as phenotypic differences driven by environmental change, could be captured by the classifier. Importantly, classification using the random forest algorithm showed comparable success when validated against traditional, slower, manual identification. Our framework allows for reliable classification in dynamic environments, and may help to improve strategies for long-term monitoring of species in changing environments. Our

Exploratory study on classification and individualisation of earprints.

Science.gov (United States)

Meijerman, Lynn; Sholl, Sarah; De Conti, Francesca; Giacon, Marta; van der Lugt, Cor; Drusini, Andrea; Vanezis, Peter; Maat, George

2004-02-10

The FearID research project is aimed at the individualisation of earprints for the purpose of forensic research. The study presented here was carried out within the framework of this project. It intends to combine a review of what is known from literature on the classification and individualisation of earprints with results from a preliminary study of earprints. Possibilities for, and limitations to, the use of earprints in forensic investigation are addressed. Differences between eliminating a suspect, placing a suspect at a crime scene, and linking crimes by prints left at different scenes are considered.

Brake fault diagnosis using Clonal Selection Classification Algorithm (CSCA – A statistical learning approach

Directory of Open Access Journals (Sweden)

R. Jegadeeshwaran

2015-03-01

Full Text Available In automobile, brake system is an essential part responsible for control of the vehicle. Any failure in the brake system impacts the vehicle's motion. It will generate frequent catastrophic effects on the vehicle cum passenger's safety. Thus the brake system plays a vital role in an automobile and hence condition monitoring of the brake system is essential. Vibration based condition monitoring using machine learning techniques are gaining momentum. This study is one such attempt to perform the condition monitoring of a hydraulic brake system through vibration analysis. In this research, the performance of a Clonal Selection Classification Algorithm (CSCA for brake fault diagnosis has been reported. A hydraulic brake system test rig was fabricated. Under good and faulty conditions of a brake system, the vibration signals were acquired using a piezoelectric transducer. The statistical parameters were extracted from the vibration signal. The best feature set was identified for classification using attribute evaluator. The selected features were then classified using CSCA. The classification accuracy of such artificial intelligence technique has been compared with other machine learning approaches and discussed. The Clonal Selection Classification Algorithm performs better and gives the maximum classification accuracy (96% for the fault diagnosis of a hydraulic brake system.

Classification of High Spatial Resolution, Hyperspectral ...

Science.gov (United States)

EPA announced the availability of the final report,Classification of High Spatial Resolution, Hyperspectral Remote Sensing Imagery of the Little Miami River Watershed in Southwest Ohio, USA . This report and associated land use/land cover (LULC) coverage is the result of a collaborative effort among an interdisciplinary team of scientists with the U.S. Environmental Protection Agency's (U.S. EPA's) Office of Research and Development in Cincinnati, Ohio. A primary goal of this project is to enhance the use of geography and spatial analytic tools in risk assessment, and to improve the scientific basis for risk management decisions affecting drinking water and water quality. The land use/land cover classification is derived from 82 flight lines of Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery acquired from July 24 through August 9, 2002 via fixed-wing aircraft.

Is overall similarity classification less effortful than single-dimension classification?

Science.gov (United States)

Wills, Andy J; Milton, Fraser; Longmore, Christopher A; Hester, Sarah; Robinson, Jo

2013-01-01

It is sometimes argued that the implementation of an overall similarity classification is less effortful than the implementation of a single-dimension classification. In the current article, we argue that the evidence securely in support of this view is limited, and report additional evidence in support of the opposite proposition--overall similarity classification is more effortful than single-dimension classification. Using a match-to-standards procedure, Experiments 1A, 1B and 2 demonstrate that concurrent load reduces the prevalence of overall similarity classification, and that this effect is robust to changes in the concurrent load task employed, the level of time pressure experienced, and the short-term memory requirements of the classification task. Experiment 3 demonstrates that participants who produced overall similarity classifications from the outset have larger working memory capacities than those who produced single-dimension classifications initially, and Experiment 4 demonstrates that instructions to respond meticulously increase the prevalence of overall similarity classification.

THE TRUST INSTITUTION ROLE IN THE MANAGEMENT OF COMMUNICATIONS IN SOCIAL PROJECT

Directory of Open Access Journals (Sweden)

Ирина Николаевна КАДЫКОВА

2015-05-01

Full Text Available The authors propose expansion of the social projects classification on the basis of the magnitude of the projects products impact on the society, focusing on their role in the development of the state. The authors accept Russell D. Archibald projects classification as a whole, and expand it. Two subcategory are allocated ("social applied projects" and "socio-forming projects". Comparison was conducted on a number of indicators (project volume, project complexity, level of project risk and so on.. The innovativeness of innovative social-forming projects is identified. They are innovative in that aim formation / change of public opinion. The role of the institute of trust in building of effective system of social project communication is defined. The trust has a significant impact on the timing of the socio-forming projects. Identify priority communication channel for innovative projects of the social spectrum - online social network.

MULTI-TEMPORAL CLASSIFICATION AND CHANGE DETECTION USING UAV IMAGES

Directory of Open Access Journals (Sweden)

S. Makuti

2018-05-01

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

Projects management in organization on the selected example

OpenAIRE

A. Kania; M. Spilka; S. Griner

2013-01-01

Purpose: In this paper stages of project management taking into consideration many useful tools and methods were presented. The quality management in the project, the risk estimation, costs of the project realization and many others were discussed. The analysis of project management of an element using in an automotive industry was carried out.Design/methodology/approach: In this article classification of the projects was presented. The stages of project management and relations among them we...

Trace Fear Conditioning Differentially Modulates Intrinsic Excitability of Medial Prefrontal Cortex-Basolateral Complex of Amygdala Projection Neurons in Infralimbic and Prelimbic Cortices.

Science.gov (United States)

Song, Chenghui; Ehlers, Vanessa L; Moyer, James R

2015-09-30

Neuronal activity in medial prefrontal cortex (mPFC) is critical for the formation of trace fear memory, yet the cellular mechanisms underlying these memories remain unclear. One possibility involves the modulation of intrinsic excitability within mPFC neurons that project to the basolateral complex of amygdala (BLA). The current study used a combination of retrograde labeling and in vitro whole-cell patch-clamp recordings to examine the effect of trace fear conditioning on the intrinsic excitability of layer 5 mPFC-BLA projection neurons in adult rats. Trace fear conditioning significantly enhanced the intrinsic excitability of regular spiking infralimbic (IL) projection neurons, as evidenced by an increase in the number of action potentials after current injection. These changes were also associated with a reduction in spike threshold and an increase in h current. In contrast, trace fear conditioning reduced the excitability of regular spiking prelimbic (PL) projection neurons, through a learning-related decrease of input resistance. Interestingly, the amount of conditioned freezing was (1) positively correlated with excitability of IL-BLA projection neurons after conditioning and (2) negatively correlated with excitability of PL-BLA projection neurons after extinction. Trace fear conditioning also significantly enhanced the excitability of burst spiking PL-BLA projection neurons. In both regions, conditioning-induced plasticity was learning specific (observed in conditioned but not in pseudoconditioned rats), flexible (reversed by extinction), and transient (lasted extinction of trace fear conditioning. Significance statement: Frontal lobe-related function is vital for a variety of important behaviors, some of which decline during aging. This study involves a novel combination of electrophysiological recordings from fluorescently labeled mPFC-to-amygdala projection neurons in rats with acquisition and extinction of trace fear conditioning to determine how

A Procedure for Classification of Cup-Anemometers

DEFF Research Database (Denmark)

Friis Pedersen, Troels; Paulsen, Uwe Schmidt

1997-01-01

The paper proposes a classification procedure for cup-anemometers based on similar principles as for power converters. A range of operational parameters are established within which the response of the cup-anemometer is evaluated. The characteristics of real cup-anemometers are fitted...... to a realistic 3D cup-anemometer model. Afterwards, the model is used to calculate the response under the range of operational conditions which are set up for the classification. Responses are compared to the normal linear calibration relationship, derived from Wind tunnel calibrations. Results of the 3D cup...

Heuristic approach to the classification of postpartum endometritis and its forms

Directory of Open Access Journals (Sweden)

E. A. Balashova

2017-01-01

Full Text Available Тhe work is dedicated to the development of a method of automated medical diagnosis based on the description of biomedical systems using two parameters: energy, reflecting the interaction of its elements, and entropy characterizing the organization of the system. The violations of the energy-entropy cycle of biomedical systems is reflected in the symptoms of the disease. Statistical link between the symptoms of the condition of the body and the nature of excitation of its elements best expressed in the heuristic description of the system state. High accuracy classification of the patient's condition is achieved by using heuristic detection methods. In the proposed approach, allowing to estimate the probability of correct diagnosis increases the accuracy of the classification, and the estimated minimum amount of training samples and the capacity of its constituent signs. Classification technique consists in averaging the characteristic values in the selected classes, the preparation of the complex of symptoms of the most important signs of the disease, to conduct a "rough" diagnostic threshold rules that allow to distinguish severe forms of the disease, then differential diagnosis the severity of the disease. The proposed method was tested for classification of the forms of puerperal endometritis (mild, moderate, severe. The training sample contained 70 case histories. Syndrome to classify the patient's condition was composed of 17 characteristics. Threshold diagnosis has allowed to establish the presence of disease and to separate heavy. Differential diagnosis was used for classification of mild and moderate severity of postpartum endometritis. The accuracy of the classification of forms of postpartum endometritis amounted to 97.1%.

The Project Method in Agricultural Education: Then and Now

Science.gov (United States)

Roberts, T. Grady; Harlin, Julie F.

2007-01-01

The purpose of this philosophical paper was to synthesize theoretical and historical foundations of the project method and compare them to modern best-practices. A review of historical and contemporary literature related to the project method yielded six themes: 1) purpose of projects; 2) project classification; 3) the process; 4) the context; 5)…

Three approaches to the classification of inland wetlands. [Dismal Swamp, Tennessee, and Florida

Science.gov (United States)

Gammon, P. T.; Malone, D.; Brooks, P. D.; Carter, V.

1977-01-01

In the Dismal Swamp project, seasonal, color-infrared aerial photographs and LANDSAT digital data were interpreted for a detailed analysis of the vegetative communities in a large, highly altered wetland. In Western Tennessee, seasonal high altitude color-infrared aerial photographs provided the hydrologic and vegetative information needed to map inland wetlands, using a classification system developed for the Tennessee Valley Region. In Florida, color-infrared aerial photographs were analyzed to produce wetland maps using three existing classification systems to evaluate the information content and mappability of each system. The methods used in each of the three projects can be extended or modified for use in the mapping of inland wetlands in other parts of the United States.

APPLICATION OF SENSOR FUSION TO IMPROVE UAV IMAGE CLASSIFICATION

Directory of Open Access Journals (Sweden)

S. Jabari

2017-08-01

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

Application of Sensor Fusion to Improve Uav Image Classification

Science.gov (United States)

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

2017-08-01

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

The Competence for Project Team Members in the Conditions of Remote Working

Directory of Open Access Journals (Sweden)

Zdonek Iwona

2017-02-01

Full Text Available The article presents results of the qualitative research on competence of project team members in the conditions of remote working. These competences were considered in relation to different roles, which the members of such a team accept. The reference point to studied roles was the concept of Hansen and Allen authorships, and with regard to competence, the author's synthesis of deliberations above their models described in the literature.

Learning about the internal structure of categories through classification and feature inference.

Science.gov (United States)

Jee, Benjamin D; Wiley, Jennifer

2014-01-01

Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a "partial inference" condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.

Contributions for classification of platelet rich plasma - proposal of a new classification: MARSPILL.

Science.gov (United States)

Lana, Jose Fabio Santos Duarte; Purita, Joseph; Paulus, Christian; Huber, Stephany Cares; Rodrigues, Bruno Lima; Rodrigues, Ana Amélia; Santana, Maria Helena; Madureira, João Lopo; Malheiros Luzo, Ângela Cristina; Belangero, William Dias; Annichino-Bizzacchi, Joyce Maria

2017-07-01

Platelet-rich plasma (PRP) has emerged as a significant therapy used in medical conditions with heterogeneous results. There are some important classifications to try to standardize the PRP procedure. The aim of this report is to describe PRP contents studying celular and molecular components, and also propose a new classification for PRP. The main focus is on mononuclear cells, which comprise progenitor cells and monocytes. In addition, there are important variables related to PRP application incorporated in this study, which are the harvest method, activation, red blood cells, number of spins, image guidance, leukocytes number and light activation. The other focus is the discussion about progenitor cells presence on peripherial blood which are interesting due to neovasculogenesis and proliferation. The function of monocytes (in tissue-macrophages) are discussed here and also its plasticity, a potential property for regenerative medicine treatments.

SAW Classification Algorithm for Chinese Text Classification

OpenAIRE

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

2015-01-01

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

Understanding new product project performance : A meta-analysis

NARCIS (Netherlands)

Commandeur, H.R.; Pattikawa, L.H.; Verwaal, E.

2006-01-01

Purpose: The purpose of this paper is to summarize the accumulated body of knowledge on the performance of new product projects and provide directions for further research. Design/methodology/approach: Using a refined classification of antecedents of new product project performance the research

Vulnerable land ecosystems classification using spatial context and spectral indices

Science.gov (United States)

Ibarrola-Ulzurrun, Edurne; Gonzalo-Martín, Consuelo; Marcello, Javier

2017-10-01

Natural habitats are exposed to growing pressure due to intensification of land use and tourism development. Thus, obtaining information on the vegetation is necessary for conservation and management projects. In this context, remote sensing is an important tool for monitoring and managing habitats, being classification a crucial stage. The majority of image classifications techniques are based upon the pixel-based approach. An alternative is the object-based (OBIA) approach, in which a previous segmentation step merges image pixels to create objects that are then classified. Besides, improved results may be gained by incorporating additional spatial information and specific spectral indices into the classification process. The main goal of this work was to implement and assess object-based classification techniques on very-high resolution imagery incorporating spectral indices and contextual spatial information in the classification models. The study area was Teide National Park in Canary Islands (Spain) using Worldview-2 orthoready imagery. In the classification model, two common indices were selected Normalized Difference Vegetation Index (NDVI) and Optimized Soil Adjusted Vegetation Index (OSAVI), as well as two specific Worldview-2 sensor indices, Worldview Vegetation Index and Worldview Soil Index. To include the contextual information, Grey Level Co-occurrence Matrices (GLCM) were used. The classification was performed training a Support Vector Machine with sufficient and representative number of vegetation samples (Spartocytisus supranubius, Pterocephalus lasiospermus, Descurainia bourgaeana and Pinus canariensis) as well as urban, road and bare soil classes. Confusion Matrices were computed to evaluate the results from each classification model obtaining the highest overall accuracy (90.07%) combining both Worldview indices with the GLCM-dissimilarity.

Classification in context

DEFF Research Database (Denmark)

Mai, Jens Erik

2004-01-01

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

A Two-Level Sound Classification Platform for Environmental Monitoring

Directory of Open Access Journals (Sweden)

Stelios A. Mitilineos

2018-01-01

Full Text Available STORM is an ongoing European research project that aims at developing an integrated platform for monitoring, protecting, and managing cultural heritage sites through technical and organizational innovation. Part of the scheduled preventive actions for the protection of cultural heritage is the development of wireless acoustic sensor networks (WASNs that will be used for assessing the impact of human-generated activities as well as for monitoring potentially hazardous environmental phenomena. Collected sound samples will be forwarded to a central server where they will be automatically classified in a hierarchical manner; anthropogenic and environmental activity will be monitored, and stakeholders will be alarmed in the case of potential malevolent behavior or natural phenomena like excess rainfall, fire, gale, high tides, and waves. Herein, we present an integrated platform that includes sound sample denoising using wavelets, feature extraction from sound samples, Gaussian mixture modeling of these features, and a powerful two-layer neural network for automatic classification. We contribute to previous work by extending the proposed classification platform to perform low-level classification too, i.e., classify sounds to further subclasses that include airplane, car, and pistol sounds for the anthropogenic sound class; bird, dog, and snake sounds for the biophysical sound class; and fire, waterfall, and gale for the geophysical sound class. Classification results exhibit outstanding classification accuracy in both high-level and low-level classification thus demonstrating the feasibility of the proposed approach.

Classification

DEFF Research Database (Denmark)

Hjørland, Birger

2017-01-01

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

EnviroAtlas - Ecosystem Service Market and Project Enabling Conditions, U.S., 2016, Forest Trends' Ecosystem Marketplace

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset contains polygons depicting conditions enabling market-based programs, referred to herein as markets, and projects addressing ecosystem...

Vegetation classification and distribution mapping report Mesa Verde National Park

Science.gov (United States)

Thomas, Kathryn A.; McTeague, Monica L.; Ogden, Lindsay; Floyd, M. Lisa; Schulz, Keith; Friesen, Beverly A.; Fancher, Tammy; Waltermire, Robert G.; Cully, Anne

2009-01-01

The classification and distribution mapping of the vegetation of Mesa Verde National Park (MEVE) and surrounding environment was achieved through a multi-agency effort between 2004 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center, Fort Collins Research Center, and Rocky Mountain Geographic Science Center; Northern Arizona University; Prescott College; and NatureServe. The project team described 47 plant communities for MEVE, 34 of which were described from quantitative classification based on f eld-relevé data collected in 1993 and 2004. The team derived 13 additional plant communities from field observations during the photointerpretation phase of the project. The National Vegetation Classification Standard served as a framework for classifying these plant communities to the alliance and association level. Eleven of the 47 plant communities were classified as “park specials;” that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing MEVE, with three different map-class schemas: base, group, and management map classes. The base map classes represent the fi nest level of spatial detail. Initial polygons were developed using Definiens Professional (at the time of our use, this software was called eCognition), assisted by interpretation of 1:12,000 true-color digital orthophoto quarter quadrangles (DOQQs). These polygons (base map classes) were labeled using manual photo interpretation of the DOQQs and 1:12,000 true-color aerial photography. Field visits verified interpretation concepts. The vegetation map database includes 46 base map classes, which consist of associations, alliances, and park specials classified with quantitative analysis, additional associations and park specials noted

Notification: Follow-up Review of EPA’s Classification of National Security Information

Science.gov (United States)

Project #OPE-FY15-0057, July 20, 2015. The EPA OIG plans to begin preliminary research on the OARM actions taken to improve policies and procedures related to the classification of national security information.

Automatic workflow for the classification of local DNA conformations

Czech Academy of Sciences Publication Activity Database

Čech, P.; Kukal, J.; Černý, Jiří; Schneider, Bohdan; Svozil, D.

2013-01-01

Roč. 14, č. 205 (2013) ISSN 1471-2105 R&D Projects: GA ČR GAP305/12/1801 Institutional research plan: CEZ:AV0Z50520701 Keywords : DNA * Dinucleotide conformation * Classification * Machine learning * Neural network * k-NN * Cluster analysis Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.672, year: 2013

Refinements of the Weyl tensor classification in five dimensions

Czech Academy of Sciences Publication Activity Database

Coley, A.; Hervik, S.; Ortaggio, Marcello; Wylleman, L.

2012-01-01

Roč. 29, č. 15 (2012), s. 155016 ISSN 0264-9381 R&D Projects: GA ČR GAP203/10/0749 Institutional support: RVO:67985840 Keywords : black - holes * Petrov classification * space-times Subject RIV: BA - General Mathematics Impact factor: 3.562, year: 2012 http://iopscience.iop.org/0264-9381/29/15/155016/

An automated cirrus classification

Science.gov (United States)

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

2018-05-01

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

Aerodynamic Classification of Swept-Wing Ice Accretion

Science.gov (United States)

Diebold, Jeff M.; Broeren, Andy P.; Bragg, Michael B.

2013-01-01

The continued design, certification and safe operation of swept-wing airplanes in icing conditions rely on the advancement of computational and experimental simulation methods for higher fidelity results over an increasing range of aircraft configurations and performance, and icing conditions. The current stateof- the-art in icing aerodynamics is mainly built upon a comprehensive understanding of two-dimensional geometries that does not currently exist for fundamentally three-dimensional geometries such as swept wings. The purpose of this report is to describe what is known of iced-swept-wing aerodynamics and to identify the type of research that is required to improve the current understanding. Following the method used in a previous review of iced-airfoil aerodynamics, this report proposes a classification of swept-wing ice accretion into four groups based upon unique flowfield attributes. These four groups are: ice roughness, horn ice, streamwise ice and spanwise-ridge ice. In the case of horn ice it is shown that a further subclassification of "nominally 3D" or "highly 3D" horn ice may be necessary. For all of the proposed ice-shape classifications, relatively little is known about the three-dimensional flowfield and even less about the effect of Reynolds number and Mach number on these flowfields. The classifications and supporting data presented in this report can serve as a starting point as new research explores swept-wing aerodynamics with ice shapes. As further results are available, it is expected that these classifications will need to be updated and revised.

EDUCATIONAL PROJECTS STAKEHOLDER MANAGEMENT

Directory of Open Access Journals (Sweden)

Юлія Юріївна ГУСЄВА

2016-02-01

Full Text Available An approach based on an integration of requirements breakdown structure and work breakdown structure of the project is proposed. It can complement existing methods of project stakeholders classification with the indicator of resource input, which can be defined in monetary terms. A method of requirements monitoring is proposed, which allows you to track the requirements of project stakeholders over time according to the actual amount of resources spent by analogy with the earned value method. Proposed indexes are the basis not only for monitoring but for the forecast of the project. The need of creating of a mechanism for getting baseline data taking into account the existence of different types of requirements of project stakeholders is grounded.

Formalized classification of European fen vegetation at the alliance level

Czech Academy of Sciences Publication Activity Database

Peterka, T.; Hájek, M.; Jiroušek, M.; Jiménez-Alfaro, B.; Aunina, L.; Bergamini, A.; Dítě, D.; Felbaba-Klushyna, L.; Graf, U.; Hájková, Petra; Hettenbergerová, E.; Ivchenko, T. G.; Jansen, F.; Koroleva, N. E.; Lapshina, E. D.; Lazarević, P. M.; Moen, A.; Napreenko, M. G.; Pawlikowski, P.; Plesková, Z.; Sekulová, L.; Smagin, V. A.; Tahvanainen, T.; Thiele, A.; Bita-Nicolae, C.; Biurrun, I.; Brisse, H.; Ćušterevska, R.; De Bie, E.; Ewald, J.; FitzPatrick, U.; Font, X.; Jandt, U.; Kazcki, Z.; Kuzemko, A.; Landucci, F.; Moeslund, J. E.; Perez-Haase, A.; Rašomavičius, V.; Rodwell, J. S.; Schaminée, J.H.J.; Šilc, U.; Stančić, Z.; Chytrý, M.

2017-01-01

Roč. 20, č. 1 (2017), s. 124-142 ISSN 1402-2001 R&D Projects: GA ČR GB14-36079G Institutional support: RVO:67985939 Keywords : Scheuchzerio-Caricetea * vegetation classification * mires Subject RIV: EH - Ecology, Behaviour OBOR OECD: Ecology Impact factor: 2.474, year: 2016

Simple Fully Automated Group Classification on Brain fMRI

International Nuclear Information System (INIS)

Honorio, J.; Goldstein, R.; Samaras, D.; Tomasi, D.; Goldstein, R.Z.

2010-01-01

We propose a simple, well grounded classification technique which is suited for group classification on brain fMRI data sets that have high dimensionality, small number of subjects, high noise level, high subject variability, imperfect registration and capture subtle cognitive effects. We propose threshold-split region as a new feature selection method and majority voteas the classification technique. Our method does not require a predefined set of regions of interest. We use average acros ssessions, only one feature perexperimental condition, feature independence assumption, and simple classifiers. The seeming counter-intuitive approach of using a simple design is supported by signal processing and statistical theory. Experimental results in two block design data sets that capture brain function under distinct monetary rewards for cocaine addicted and control subjects, show that our method exhibits increased generalization accuracy compared to commonly used feature selection and classification techniques.

Simple Fully Automated Group Classification on Brain fMRI

Energy Technology Data Exchange (ETDEWEB)

Honorio, J.; Goldstein, R.; Honorio, J.; Samaras, D.; Tomasi, D.; Goldstein, R.Z.

2010-04-14

We propose a simple, well grounded classification technique which is suited for group classification on brain fMRI data sets that have high dimensionality, small number of subjects, high noise level, high subject variability, imperfect registration and capture subtle cognitive effects. We propose threshold-split region as a new feature selection method and majority voteas the classification technique. Our method does not require a predefined set of regions of interest. We use average acros ssessions, only one feature perexperimental condition, feature independence assumption, and simple classifiers. The seeming counter-intuitive approach of using a simple design is supported by signal processing and statistical theory. Experimental results in two block design data sets that capture brain function under distinct monetary rewards for cocaine addicted and control subjects, show that our method exhibits increased generalization accuracy compared to commonly used feature selection and classification techniques.

78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

Science.gov (United States)

2013-09-09

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

The classification of finite simple groups groups of characteristic 2 type

CERN Document Server

Aschbacher, Michael; Smith, Stephen D; Solomon, Ronald

2011-01-01

The book provides an outline and modern overview of the classification of the finite simple groups. It primarily covers the "even case", where the main groups arising are Lie-type (matrix) groups over a field of characteristic 2. The book thus completes a project begun by Daniel Gorenstein's 1983 book, which outlined the classification of groups of "noncharacteristic 2 type". However, this book provides much more. Chapter 0 is a modern overview of the logical structure of the entire classification. Chapter 1 is a concise but complete outline of the "odd case" with updated references, while Chapter 2 sets the stage for the remainder of the book with a similar outline of the "even case". The remaining six chapters describe in detail the fundamental results whose union completes the proof of the classification theorem. Several important subsidiary results are also discussed. In addition, there is a comprehensive listing of the large number of papers referenced from the literature. Appendices provide a brief but ...

An Automated Algorithm to Screen Massive Training Samples for a Global Impervious Surface Classification

Science.gov (United States)

Tan, Bin; Brown de Colstoun, Eric; Wolfe, Robert E.; Tilton, James C.; Huang, Chengquan; Smith, Sarah E.

2012-01-01

An algorithm is developed to automatically screen the outliers from massive training samples for Global Land Survey - Imperviousness Mapping Project (GLS-IMP). GLS-IMP is to produce a global 30 m spatial resolution impervious cover data set for years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. This unprecedented high resolution impervious cover data set is not only significant to the urbanization studies but also desired by the global carbon, hydrology, and energy balance researches. A supervised classification method, regression tree, is applied in this project. A set of accurate training samples is the key to the supervised classifications. Here we developed the global scale training samples from 1 m or so resolution fine resolution satellite data (Quickbird and Worldview2), and then aggregate the fine resolution impervious cover map to 30 m resolution. In order to improve the classification accuracy, the training samples should be screened before used to train the regression tree. It is impossible to manually screen 30 m resolution training samples collected globally. For example, in Europe only, there are 174 training sites. The size of the sites ranges from 4.5 km by 4.5 km to 8.1 km by 3.6 km. The amount training samples are over six millions. Therefore, we develop this automated statistic based algorithm to screen the training samples in two levels: site and scene level. At the site level, all the training samples are divided to 10 groups according to the percentage of the impervious surface within a sample pixel. The samples following in each 10% forms one group. For each group, both univariate and multivariate outliers are detected and removed. Then the screen process escalates to the scene level. A similar screen process but with a looser threshold is applied on the scene level considering the possible variance due to the site difference. We do not perform the screen process across the scenes because the scenes might vary due to

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

International Nuclear Information System (INIS)

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

1997-01-01

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

An innovative device for powders classification based on combined aerodynamic and electrostatic separation of particles

Science.gov (United States)

Piriou, Bruno; Mayer-Laigle, Claire; Maalel, Firas; Plissot, Jorys; Rouau, Xavier

2017-06-01

An innovative separator have been developed which aims at sorting out powders fractions according to aerodynamic and electrostatic properties of particles. The prototype is composed of a projection unit, a separation module and a classification/collection zone. The projection part is ensured by a pressurized gun. The separation module is conceived to disperse particles according to front and transverse directions. At the output of the gun, electrodes can be disposed to deviate the trajectory of charged particles. The classification part is made of a series of collecting bins. Starch, fine ash powders, and mixtures of these two materials were used to test the working of the separator. The efficiency of the separation was assessed by yields and particle sizes distribution of the collected fractions in the different bins. An aerodynamic classification was achieved along the main axis, with the finest particles crossing larger distances. With a blend of starch and ash, particles from both materials were unevenly distributed in the classifyier, opening the way to a possible separation based simply on aerodynamic properties. When an electric deviation was applied in addition to the projection of powders, the distribution of particles in the collecting part was modified.

An innovative device for powders classification based on combined aerodynamic and electrostatic separation of particles

Directory of Open Access Journals (Sweden)

Piriou Bruno

2017-01-01

Full Text Available An innovative separator have been developed which aims at sorting out powders fractions according to aerodynamic and electrostatic properties of particles. The prototype is composed of a projection unit, a separation module and a classification/collection zone. The projection part is ensured by a pressurized gun. The separation module is conceived to disperse particles according to front and transverse directions. At the output of the gun, electrodes can be disposed to deviate the trajectory of charged particles. The classification part is made of a series of collecting bins. Starch, fine ash powders, and mixtures of these two materials were used to test the working of the separator. The efficiency of the separation was assessed by yields and particle sizes distribution of the collected fractions in the different bins. An aerodynamic classification was achieved along the main axis, with the finest particles crossing larger distances. With a blend of starch and ash, particles from both materials were unevenly distributed in the classifyier, opening the way to a possible separation based simply on aerodynamic properties. When an electric deviation was applied in addition to the projection of powders, the distribution of particles in the collecting part was modified.

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

Science.gov (United States)

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

2014-05-01

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

Cheese Classification, Characterization, and Categorization: A Global Perspective.

Science.gov (United States)

Almena-Aliste, Montserrat; Mietton, Bernard

2014-02-01

Cheese is one of the most fascinating, complex, and diverse foods enjoyed today. Three elements constitute the cheese ecosystem: ripening agents, consisting of enzymes and microorganisms; the composition of the fresh cheese; and the environmental conditions during aging. These factors determine and define not only the sensory quality of the final cheese product but also the vast diversity of cheeses produced worldwide. How we define and categorize cheese is a complicated matter. There are various approaches to cheese classification, and a global approach for classification and characterization is needed. We review current cheese classification schemes and the limitations inherent in each of the schemes described. While some classification schemes are based on microbiological criteria, others rely on descriptions of the technologies used for cheese production. The goal of this review is to present an overview of comprehensive and practical integrative classification models in order to better describe cheese diversity and the fundamental differences within cheeses, as well as to connect fundamental technological, microbiological, chemical, and sensory characteristics to contribute to an overall characterization of the main families of cheese, including the expanding world of American artisanal cheeses.

Classification of inland Bolboschoenus-dominated vegetation in Central Europe

Czech Academy of Sciences Publication Activity Database

Hroudová, Zdenka; Hrivnák, R.; Chytrý, M.

2009-01-01

Roč. 39, č. 2 (2009), s. 205-215 ISSN 0340-269X R&D Projects: GA AV ČR IAA6005905; GA ČR GA521/04/0997 Institutional research plan: CEZ:AV0Z60050516 Keywords : vegetation classification * saline vegetation * freshwater inland communities Subject RIV: EF - Botanics Impact factor: 0.674, year: 2009

A simplified immunohistochemical classification of skeletal muscle fibres in mouse

Directory of Open Access Journals (Sweden)

M. Kammoun

2014-06-01

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

Spent fuel stability under repository conditions - final report of the european project

International Nuclear Information System (INIS)

Poinssot, Ch.; Ferry, C.; Kelm, M.; Cavedon, J.M.; Corbel, C.; Jegou, Ch.; Lovera, P.; Miserque, F.; Poulesquen, A.; Grambow, B.; Andriambololona, Z.; Martinez-Esparza, A.; Kelm, M.; Loida, A.; Rondinella, V.; Wegen, D.; Spahiu, K.; Johnson, L.; Cachoir, Ch.; Lemmens, K.; Quinones, J.; Bruno, J.; Christensen, H.; Grambow, B.; Pablo, J. de

2005-01-01

This report is the final report of the European Project 'Spent Fuel Stability under Repository Conditions' (FIKW-CT-2001-00192 SFS) funded by the European Commission from Nov.2000 to Oct.2004. Gathering the work performed by 13 partners from 6 countries, it aims to specifically focus on the spent nuclear fuel long term alteration in deep repository and the subsequent radionuclides release rate as a function of time. This report synthesised the wide experimental work performed within this project and enlightens the major outcomes, which can be summarised as follow: - A new model for defining the Instant Release Fraction was developed in order to consider the potential fuel evolution before the water penetrates the canister. Quantitative assessment has been produced and shows a significant contribution to the long term dose; - Based on new experimental data, kinetic radiolytic scheme have been upgraded and are used to determine the amount of oxidants produced at the fuel/water interface; - The existence of a dose threshold below which the water radiolysis does not influence the fuel alteration has been demonstrated and occurs between 3.5 and 33 MBq.g UO21. Above the threshold, the fuel alteration rates is directly related to the dose rate. - Hydrogen was experimentally demonstrated to be an efficient oxidants scavenger preventing therefore the fuel oxidation. Molecular mechanism still need to be understood. - Finally, a new Matrix Alteration Model integrating most of the SFS results (apart of the hydrogen effect) has been developed and used to assess the fuel long tern stability in representative conditions of deep repository in salt, clay-rock and granite. The breadth of the results and the significance of the conclusions testify of the success of the collaboration within the project. (authors)

Classification of refrigerants; Classification des fluides frigorigenes

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-07-01

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

Vegetation classification and biogeography of European floodplain forests and alder carrs

Czech Academy of Sciences Publication Activity Database

Douda, Jan; Boublík, K.; Slezák, M.; Biurrun, I.; Nociar, J.; Havrdová, Alena; Doudová, J.; Aćić, S.; Brisse, H.; Brunet, J.; Chytrý, M.; Claessens, H.; Csiky, J.; Didukh, Y. P.; Dimopoulos, P.; Dullinger, S.; FitzPatrick, U.; Guisan, A.; Horchler, P. J.; Hrivnák, R.; Jandt, U.; Kacki, Z.; Kevey, B.; Landucci, F.; Lecomte, H.; Lenoir, J.; Paal, J.; Paternoster, D.; Pauli, H.; Pielech, R.; Rodwell, J. S.; Roelandt, B.; Svenning, J.-C.; Šibík, J.; Šilc, U.; Škvorc, Ž.; Tsiripidis, I.; Tzonev, R.; Wohlgemuth, T.; Zimmermann, N. E.

2016-01-01

Roč. 19, č. 1 (2016), s. 147-163 ISSN 1402-2001 R&D Projects: GA ČR(CZ) GAP504/11/0402 Institutional support: RVO:67985939 Keywords : formalized classification * Iberian peninsula * diversity Subject RIV: EF - Botanics Impact factor: 2.474, year: 2016

The Optimization of the Time-Cost Tradeoff Problem in Projects with Conditional Activities Using of the Multi-Objective Charged System Search Algorithm (SMOCSS

Directory of Open Access Journals (Sweden)

M. K. Sharbatdar

2016-11-01

Full Text Available Abstract The appropriate planning and scheduling for reaching the project goals in the most economical way is the very basic issue of the project management. As in each project, the project manager must determine the required activities for the implementation of the project and select the best option in the implementation of each of the activities, in a way that the least final cost and time of the project is achieved. Considering the number of activities and selecting options for each of the activities, usually the selection has not one unique solution, but it consists of a set of solutions that are not preferred to each other and are known as Pareto solutions. On the other hand, in some actual projects, there are activities that their implementation options depend on the implementation of the prerequisite activity and are not applicable using all the implementation options, and even in some cases the implementation or the non-implementation of some activities are also dependent on the prerequisite activity implementation. These projects can be introduced as conditional projects. Much researchs have been conducted for acquiring Pareto solution set, using different methods and algorithms, but in all the done tasks the time-cost optimization of conditional projects is not considered. Thus, in the present study the concept of conditional network is defined along with some practical examples, then an appropriate way to illustrate these networks and suitable time-cost formulation of these are presented. Finally, for some instances of conditional activity networks, conditional project time-cost optimization conducted multi-objectively using known meta-heuristic algorithms such as multi-objective genetic algorithm, multi-objective particle swarm algorithm and multi-objective charged system search algorithm.

REMOTE SENSING IMAGE CLASSIFICATION APPLIED TO THE FIRST NATIONAL GEOGRAPHICAL INFORMATION CENSUS OF CHINA

Directory of Open Access Journals (Sweden)

X. Yu

2016-06-01

Full Text Available Image classification will still be a long way in the future, although it has gone almost half a century. In fact, researchers have gained many fruits in the image classification domain, but there is still a long distance between theory and practice. However, some new methods in the artificial intelligence domain will be absorbed into the image classification domain and draw on the strength of each to offset the weakness of the other, which will open up a new prospect. Usually, networks play the role of a high-level language, as is seen in Artificial Intelligence and statistics, because networks are used to build complex model from simple components. These years, Bayesian Networks, one of probabilistic networks, are a powerful data mining technique for handling uncertainty in complex domains. In this paper, we apply Tree Augmented Naive Bayesian Networks (TAN to texture classification of High-resolution remote sensing images and put up a new method to construct the network topology structure in terms of training accuracy based on the training samples. Since 2013, China government has started the first national geographical information census project, which mainly interprets geographical information based on high-resolution remote sensing images. Therefore, this paper tries to apply Bayesian network to remote sensing image classification, in order to improve image interpretation in the first national geographical information census project. In the experiment, we choose some remote sensing images in Beijing. Experimental results demonstrate TAN outperform than Naive Bayesian Classifier (NBC and Maximum Likelihood Classification Method (MLC in the overall classification accuracy. In addition, the proposed method can reduce the workload of field workers and improve the work efficiency. Although it is time consuming, it will be an attractive and effective method for assisting office operation of image interpretation.

Classification of uranium reserves/resources

International Nuclear Information System (INIS)

1998-08-01

Projections of future availability of uranium to meet present and future nuclear power requirements depend on the reliability of uranium resource estimates. Lack of harmony of the definition of the different classes of uranium reserves and resources between countries makes the compilation and analysis of such information difficult. The problem was accentuated in the early 1990s with the entry of uranium producing countries from the former Soviet Union, eastern Europe and China into the world uranium supply market. The need for an internationally acceptable reserve/resource classification system and terminology using market based criteria is therefore obvious. This publication was compiled from participant's contributions and findings of the Consultants Meetings on Harmonization of Uranium Resource Assessment Concepts held in Vienna from 22 to 25 June 1992, and two Consultants Meetings on the Development of a More Meaningful Classification of Uranium Resources held in Kiev, Ukraine on 24-26 April 1995 and 20-23 August 1996. This document includes 11 contributions, summary, list of participants of the Consultants Meetings. Each contribution has been indexed and provided with an abstract

Supervised machine learning and active learning in classification of radiology reports.

Science.gov (United States)

Nguyen, Dung H M; Patrick, Jon D

2014-01-01

This paper presents an automated system for classifying the results of imaging examinations (CT, MRI, positron emission tomography) into reportable and non-reportable cancer cases. This system is part of an industrial-strength processing pipeline built to extract content from radiology reports for use in the Victorian Cancer Registry. In addition to traditional supervised learning methods such as conditional random fields and support vector machines, active learning (AL) approaches were investigated to optimize training production and further improve classification performance. The project involved two pilot sites in Victoria, Australia (Lake Imaging (Ballarat) and Peter MacCallum Cancer Centre (Melbourne)) and, in collaboration with the NSW Central Registry, one pilot site at Westmead Hospital (Sydney). The reportability classifier performance achieved 98.25% sensitivity and 96.14% specificity on the cancer registry's held-out test set. Up to 92% of training data needed for supervised machine learning can be saved by AL. AL is a promising method for optimizing the supervised training production used in classification of radiology reports. When an AL strategy is applied during the data selection process, the cost of manual classification can be reduced significantly. The most important practical application of the reportability classifier is that it can dramatically reduce human effort in identifying relevant reports from the large imaging pool for further investigation of cancer. The classifier is built on a large real-world dataset and can achieve high performance in filtering relevant reports to support cancer registries. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Variational Infinite Hidden Conditional Random Fields

NARCIS (Netherlands)

Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja; Ghahramani, Zoubin

2015-01-01

Hidden conditional random fields (HCRFs) are discriminative latent variable models which have been shown to successfully learn the hidden structure of a given classification problem. An Infinite hidden conditional random field is a hidden conditional random field with a countably infinite number of

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function

Science.gov (United States)

Groenendyk, Derek G.; Ferré, Ty P.A.; Thorp, Kelly R.; Rice, Amy K.

2015-01-01

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth’s surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape

Approaches to Substance of Social Infrastructure and to Its Classification

Directory of Open Access Journals (Sweden)

Kyrychenko Sergiy О. –

2016-03-01

Full Text Available The article is concerned with studying and analyzing approaches to both substance and classification of social infrastructure objects as a specific constellation of subsystems and components. To address the purpose set, the following tasks have been formulated: analysis of existing methods for determining the classification of social infrastructure; classification of the branches of social infrastructure using functional-dedicated approach; formulation of author's own definition of substance of social infrastructure. It has been determined that to date most often a social infrastructure classification is carried out depending on its functional tasks, although there are other approaches to classification. The author's definition of substance of social infrastructure has been formulated as follows: social infrastructure is a body of economy branches (public utilities, management, public safety and environment, socio-economic services, the purpose of which is to impact on reproductive potential and overall conditions of human activity in the spheres of work, everyday living, family, social-political, spiritual and intellectual development as well as life activity.

The history of transdisciplinary race classification: methods, politics and institutions, 1840s-1940s.

Science.gov (United States)

McMahon, Richard

2018-03-01

A recently blossoming historiographical literature recognizes that physical anthropologists allied with scholars of diverse aspects of society and history to racially classify European peoples over a period of about a hundred years. They created three successive race classification coalitions - ethnology, from around 1840; anthropology, from the 1850s; and interwar raciology - each of which successively disintegrated. The present genealogical study argues that representing these coalitions as 'transdisciplinary' can enrich our understanding of challenges to disciplinary specialization. This is especially the case for the less well-studied nineteenth century, when disciplines and challenges to disciplinary specialization were both gradually emerging. Like Marxism or structuralism, race classification was a holistic interpretive framework, which, at its most ambitious, aimed to structure the human sciences as a whole. It resisted the organization of academia and knowledge into disciplines with separate organizational institutions and research practices. However, the 'transdisciplinarity' of this nationalistic project also bridged emerging borderlines between science and politics. I ascribe race classification's simultaneous longevity and instability to its complex and intricately entwined processes of political and interdisciplinary coalition building. Race classification's politically useful conclusions helped secure public support for institutionalizing the coalition's component disciplines. Institutionalization in turn stimulated disciplines to professionalize. They emphasized disciplinary boundaries and insisted on apolitical science, thus ultimately undermining the 'transdisciplinary' project.

[The International Classification of Functioning, Disability and Health (ICF) : The implementation of the ICF Core Sets for Hand Conditions in clinical routine as an example of application].

Science.gov (United States)

Coenen, Michaela; Rudolf, Klaus-Dieter; Kus, Sandra; Dereskewitz, Caroline

2018-05-24

The International Classification of Functioning, Disability and Health (ICF) provides a standardized language of almost 1500 ICF categories for coding information about functioning and contextual factors. Short lists (ICF Core Sets) are helpful tools to support the implementation of the ICF in clinical routine. In this paper we report on the implementation of ICF Core Sets in clinical routine using the "ICF Core Sets for Hand Conditions" and the "Lighthouse Project Hand" as an example. Based on the ICF categories of the "Brief ICF Core Set for Hand Conditions", the ICF-based assessment tool (ICF Hand A ) was developed aiming to guide the assessment and treatment of patients with injuries and diseases located at the hand. The ICF Hand A facilitates the standardized assessment of functioning - taking into consideration of a holistic view of the patients - along the continuum of care ranging from acute care to rehabilitation and return to work. Reference points for the assessment of the ICF Hand A are determined in treatment guidelines for selected injuries and diseases of the hand along with recommendations for acute treatment and care, procedures and interventions of subsequent treatment and rehabilitation. The assessment of the ICF Hand A according to the defined reference points can be done using electronic clinical assessment tools and allows for an automatic generation of a timely medical report of a patient's functioning. In the future, the ICF Hand A can be used to inform the coding of functioning in ICD-11.

Classification of human- and automated resource allocation approaches in multi-project management

NARCIS (Netherlands)

Ponsteen, A.; Kusters, R.J.; Pasian, B.; Storm, P.

2015-01-01

Managing a multi-project environment requires a different method than managing a single project. The main challenge of managing a multi-project environment is the allocation of scarce human resources over the projects in execution. As part of a broader research on this topic, the aim of this paper

Supervised Classification in the Presence of Misclassified Training Data: A Monte Carlo Simulation Study in the Three Group Case

Directory of Open Access Journals (Sweden)

Jocelyn E Bolin

2014-02-01

Full Text Available Statistical classification of phenomena into observed groups is very common in the social and behavioral sciences. Statistical classification methods, however, are affected by the characteristics of the data under study. Statistical classification can be further complicated by initial misclassification of the observed groups. The purpose of this study is to investigate the impact of initial training data misclassification on several statistical classification and data mining techniques. Misclassification conditions in the three-group case will be simulated and results will be presented in terms of overall as well as subgroup classification accuracy. Results show decreased classification accuracy as sample size, group separation and group size ratio decrease and as misclassification percentage increases with random forests demonstrating the highest accuracy across conditions.

2012 provisional classification criteria for polymyalgia rheumatica

DEFF Research Database (Denmark)

Dasgupta, Bhaskar; Cimmino, Marco A; Maradit-Kremers, Hilal

2012-01-01

The objective of this study was to develop EULAR/ACR classification criteria for polymyalgia rheumatica (PMR). Candidate criteria were evaluated in a 6-month prospective cohort study of 125 patients with new onset PMR and 169 non-PMR comparison subjects with conditions mimicking PMR. A scoring al...

Inter-Labeler and Intra-Labeler Variability of Condition Severity Classification Models Using Active and Passive Learning Methods

Science.gov (United States)

Nissim, Nir; Shahar, Yuval; Boland, Mary Regina; Tatonetti, Nicholas P; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

2018-01-01

Background and Objectives Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers’ learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. Methods We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by

Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods.

Science.gov (United States)

Nissim, Nir; Shahar, Yuval; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

2017-09-01

Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers' learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by using the labels provided by seven

Classification

Science.gov (United States)

Clary, Renee; Wandersee, James

2013-01-01

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

Classification of Magnetic Nanoparticle Systems

DEFF Research Database (Denmark)

Bogren, Sara; Fornara, Andrea; Ludwig, Frank

2015-01-01

and the size parameters are determined from electron microscopy and dynamic light scattering. Using these methods, we also show that the nanocrystal size and particle morphology determines the dynamic magnetic properties for both single- and multi-core particles. The presented results are obtained from...... the four year EU NMP FP7 project, NanoMag, which is focused on standardization of analysis methods for magnetic nanoparticles.......This study presents classification of different magnetic single- and multi-core particle systems using their measured dynamic magnetic properties together with their nanocrystal and particle sizes. The dynamic magnetic properties are measured with AC (dynamical) susceptometry and magnetorelaxometry...

Mobile communications – on standards, classifications and generations

DEFF Research Database (Denmark)

Tadayoni, Reza; Henten, Anders; Sørensen, Jannick Kirk

The research question addressed in this paper is concerned with the manners in which the general technological progress in mobile communications is presented and the reasons for the differences in these manners of presentation. The relevance of this research question is that the different....... In common parlance, progress in mobile technologies is mostly referred to as generations. In the International Telecommunication Union (ITU), the classification terminology is that of International Mobile Telecommunication (IMT) standards. In the specialized standards body with a central position...... in the standardization of core mobile technologies, namely 3GPP (3rd Generation Partnership Project), the terminology of ‘releases’ is used. In order to address the research question, the paper uses an analytical framework based on the differences and relationships between the concepts of standards, classifications...

Classification of domains of closed operators

International Nuclear Information System (INIS)

Lassner, G.; Timmermann, W.

1975-01-01

The structure of domains of determining closed operators in the Hilbert space by means of sequence spaces is investigated. The final classification provides three classes of these domains. Necessary and sufficient conditions of equivalence of these domains are obtained in the form of equivalency of corresponding sequences of natural numbers. Connection with the perturbation theory is mentioned [ru

Detection of explosives in traces by laser induced breakdown spectroscopy: Differences from organic interferents and conditions for a correct classification

International Nuclear Information System (INIS)

Lazic, V.; Palucci, A.; Jovicevic, S.; Carpanese, M.

2011-01-01

With the aim to study and to improve LIBS capability for detecting residues of energetic compounds in air surrounding, nine types of explosives and some potential interferents, placed in small quantities on a metallic support, were interrogated by a laser. Shot-to-shot behavior of the line intensities relative to the sample constituents was studied. The detected plasma was not stoichiometric and the line intensities, as well as their ratios, were changing even for an order of magnitude from one sampling point to another, particularly in the case of aromatic compounds. We explained some sources of such LIBS signal's behavior and this allowed us to establish a data processing procedure, which leads to a good linearization among the data sets. In this way, it was possible to determine some real differences between the LIBS spectra from explosives and interferents, and to correlate them with molecular formulas, with some known pathways for the molecule's decomposition and with successive chemical reactions in the plasma. Number spectral parameters, which distinguish the each studied explosive from other organic materials, were also determined and compared with previously published results relative to percentages of correct classifications for the same explosives. Experimental conditions for reliable recognition of the explosives by LIBS in air are also suggested, together with the parameters that should be considered or discarded from the classification procedure.

Classification of phosphogypsum as a waste material from the aspect of environmental protection

Directory of Open Access Journals (Sweden)

Rajković Miloš B.

2004-01-01

Full Text Available Phosphogypsum is primarily classified as a heavy waste. The classification of phosphogypsum as dangerous waste may be only maintained under the condition that phosphates with the highest content of radio nuclides are used in the production of H3PO4 by the so called "wet procedure" (Morocco, Florida, which, due to the great quantity of present radio nuclides, causes considerable environmental pollution by radon. The classification of phosphogypsum as a separate category of radioactive waste may be conditionally accepted, because phosphogypsum is not a radioactive waste. All the instructions about the collection, documentation and storage of phosphogypsum so far on disposal sites, and possible transport, also due to non-existing legal recommendations must comply with the classification of phosphogypsum as dangerous waste.

Classification of right-hand grasp movement based on EMOTIV Epoc+

Science.gov (United States)

Tobing, T. A. M. L.; Prawito, Wijaya, S. K.

2017-07-01

Combinations of BCT elements for right-hand grasp movement have been obtained, providing the average value of their classification accuracy. The aim of this study is to find a suitable combination for best classification accuracy of right-hand grasp movement based on EEG headset, EMOTIV Epoc+. There are three movement classifications: grasping hand, relax, and opening hand. These classifications take advantage of Event-Related Desynchronization (ERD) phenomenon that makes it possible to differ relaxation, imagery, and movement state from each other. The combinations of elements are the usage of Independent Component Analysis (ICA), spectrum analysis by Fast Fourier Transform (FFT), maximum mu and beta power with their frequency as features, and also classifier Probabilistic Neural Network (PNN) and Radial Basis Function (RBF). The average values of classification accuracy are ± 83% for training and ± 57% for testing. To have a better understanding of the signal quality recorded by EMOTIV Epoc+, the result of classification accuracy of left or right-hand grasping movement EEG signal (provided by Physionet) also be given, i.e.± 85% for training and ± 70% for testing. The comparison of accuracy value from each combination, experiment condition, and external EEG data are provided for the purpose of value analysis of classification accuracy.

How a national vegetation classification can help ecological research and management

Science.gov (United States)

Scott Franklin; Patrick Comer; Julie Evens; Exequiel Ezcurra; Don Faber-Langendoen; Janet Franklin; Michael Jennings; Carmen Josse; Chris Lea; Orie Loucks; Esteban Muldavin; Robert Peet; Serguei Ponomarenko; David Roberts; Ayzik Solomeshch; Todd Keeler-Wolf; James Van Kley; Alan Weakley; Alexa McKerrow; Marianne Burke; Carol. Spurrier

2015-01-01

The elegance of classification lies in its ability to compile and systematize various terminological conventions and masses of information that are unattainable during typical research projects. Imagine a discipline without standards for collection, analysis, and interpretation; unfortunately, that describes much of 20th-century vegetation ecology.

A New Feature Ensemble with a Multistage Classification Scheme for Breast Cancer Diagnosis

Directory of Open Access Journals (Sweden)

Idil Isikli Esener

2017-01-01

Full Text Available A new and effective feature ensemble with a multistage classification is proposed to be implemented in a computer-aided diagnosis (CAD system for breast cancer diagnosis. A publicly available mammogram image dataset collected during the Image Retrieval in Medical Applications (IRMA project is utilized to verify the suggested feature ensemble and multistage classification. In achieving the CAD system, feature extraction is performed on the mammogram region of interest (ROI images which are preprocessed by applying a histogram equalization followed by a nonlocal means filtering. The proposed feature ensemble is formed by concatenating the local configuration pattern-based, statistical, and frequency domain features. The classification process of these features is implemented in three cases: a one-stage study, a two-stage study, and a three-stage study. Eight well-known classifiers are used in all cases of this multistage classification scheme. Additionally, the results of the classifiers that provide the top three performances are combined via a majority voting technique to improve the recognition accuracy on both two- and three-stage studies. A maximum of 85.47%, 88.79%, and 93.52% classification accuracies are attained by the one-, two-, and three-stage studies, respectively. The proposed multistage classification scheme is more effective than the single-stage classification for breast cancer diagnosis.

Using genetically modified tomato crop plants with purple leaves for absolute weed/crop classification.

Science.gov (United States)

Lati, Ran N; Filin, Sagi; Aly, Radi; Lande, Tal; Levin, Ilan; Eizenberg, Hanan

2014-07-01

Weed/crop classification is considered the main problem in developing precise weed-management methodologies, because both crops and weeds share similar hues. Great effort has been invested in the development of classification models, most based on expensive sensors and complicated algorithms. However, satisfactory results are not consistently obtained due to imaging conditions in the field. We report on an innovative approach that combines advances in genetic engineering and robust image-processing methods to detect weeds and distinguish them from crop plants by manipulating the crop's leaf color. We demonstrate this on genetically modified tomato (germplasm AN-113) which expresses a purple leaf color. An autonomous weed/crop classification is performed using an invariant-hue transformation that is applied to images acquired by a standard consumer camera (visible wavelength) and handles variations in illumination intensities. The integration of these methodologies is simple and effective, and classification results were accurate and stable under a wide range of imaging conditions. Using this approach, we simplify the most complicated stage in image-based weed/crop classification models. © 2013 Society of Chemical Industry.

Conditions, factors and criteria for successful project implementation: generalization of experience of project management

Directory of Open Access Journals (Sweden)

Feraru Galina Sergeevna

2014-11-01

Full Text Available The article addresses issues characterizing features of project management contributing to their competitive advantage; shows the factors and criteria of success of projects and the main reasons for their failures, making the failed efforts of developers to create projects.

Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

Science.gov (United States)

Faye, Ibrahima; Samir, Brahim Belhaouari; Md Said, Abas

2014-01-01

Bioinformatics has been an emerging area of research for the last three decades. The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding. The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods. To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods. In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector. The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth. PMID:25045727

Classification of projection images of proteins with structural polymorphism by manifold: A simulation study for x-ray free-electron laser diffraction imaging

Science.gov (United States)

Yoshidome, Takashi; Oroguchi, Tomotaka; Nakasako, Masayoshi; Ikeguchi, Mitsunori

2015-09-01

Coherent x-ray diffraction imaging (CXDI) enables us to visualize noncrystalline sample particles with micrometer to submicrometer dimensions. Using x-ray free-electron laser (XFEL) sources, two-dimensional diffraction patterns are collected from fresh samples supplied to the irradiation area in the "diffraction-before-destruction" scheme. A recent significant increase in the intensity of the XFEL pulse is promising and will allow us to visualize the three-dimensional structures of proteins using XFEL-CXDI in the future. For the protocol proposed for molecular structure determination using future XFEL-CXDI [T. Oroguchi and M. Nakasako, Phys. Rev. E 87, 022712 (2013), 10.1103/PhysRevE.87.022712], we require an algorithm that can classify the data in accordance with the structural polymorphism of proteins arising from their conformational dynamics. However, most of the algorithms proposed primarily require the numbers of conformational classes, and then the results are biased by the numbers. To improve this point, here we examine whether a method based on the manifold concept can classify simulated XFEL-CXDI data with respect to the structural polymorphism of a protein that predominantly adopts two states. After random sampling of the conformations of the two states and in-between states from the trajectories of molecular dynamics simulations, a diffraction pattern is calculated from each conformation. Classification was performed by using our custom-made program suite named enma, in which the diffusion map (DM) method developed based on the manifold concept was implemented. We successfully classify most of the projection electron density maps phase retrieved from diffraction patterns into each of the two states and in-between conformations without the knowledge of the number of conformational classes. We also examined the classification of the projection electron density maps of each of the three states with respect to the Euler angle. The present results suggest

A Framework for Categorizing Important Project Variables

Science.gov (United States)

Parsons, Vickie S.

2003-01-01

While substantial research has led to theories concerning the variables that affect project success, no universal set of such variables has been acknowledged as the standard. The identification of a specific set of controllable variables is needed to minimize project failure. Much has been hypothesized about the need to match project controls and management processes to individual projects in order to increase the chance for success. However, an accepted taxonomy for facilitating this matching process does not exist. This paper surveyed existing literature on classification of project variables. After an analysis of those proposals, a simplified categorization is offered to encourage further research.

Hand eczema classification

DEFF Research Database (Denmark)

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

2008-01-01

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

Integrating Vegetation Classification, Mapping, and Strategic Inventory for Forest Management

Science.gov (United States)

C. K. Brewer; R. Bush; D. Berglund; J. A. Barber; S. R. Brown

2006-01-01

Many of the analyses needed to address multiple resource issues are focused on vegetation pattern and process relationships and most rely on the data models produced from vegetation classification, mapping, and/or inventory. The Northern Region Vegetation Mapping Project (R1-VMP) data models are based on these three integrally related, yet separate processes. This...

A model for scheduling projects under the condition of inflation and under penalty and reward arrangements

Directory of Open Access Journals (Sweden)

J.K. Jolayemi

2014-01-01

Full Text Available A zero-one mixed integer linear programming model is developed for the scheduling of projects under the condition of inflation and under penalty and reward arrangements. The effects of inflation on time-cost trade-off curves are illustrated and a modified approach to time-cost trade-off analysis presented. Numerical examples are given to illustrate the model and its properties. The examples show that misleading schedules and inaccurate project-cost estimates will be produced if the inflation factor is neglected in an environment of high inflation. They also show that award of penalty or bonus is a catalyst for early completion of a project, just as it can be expected.

Assessment and prevention of acute health effects of weather conditions in Europe, the PHEWE project: background, objectives, design

Directory of Open Access Journals (Sweden)

Anderson Hugh

2007-04-01

Full Text Available Abstract Background The project "Assessment and prevention of acute health effects of weather conditions in Europe" (PHEWE had the aim of assessing the association between weather conditions and acute health effects, during both warm and cold seasons in 16 European cities with widely differing climatic conditions and to provide information for public health policies. Methods The PHEWE project was a three-year pan-European collaboration between epidemiologists, meteorologists and experts in public health. Meteorological, air pollution and mortality data from 16 cities and hospital admission data from 12 cities were available from 1990 to 2000. The short-term effect on mortality/morbidity was evaluated through city-specific and pooled time series analysis. The interaction between weather and air pollutants was evaluated and health impact assessments were performed to quantify the effect on the different populations. A heat/health watch warning system to predict oppressive weather conditions and alert the population was developed in a subgroup of cities and information on existing prevention policies and of adaptive strategies was gathered. Results Main results were presented in a symposium at the conference of the International Society of Environmental Epidemiology in Paris on September 6th 2006 and will be published as scientific articles. The present article introduces the project and includes a description of the database and the framework of the applied methodology. Conclusion The PHEWE project offers the opportunity to investigate the relationship between temperature and mortality in 16 European cities, representing a wide range of climatic, socio-demographic and cultural characteristics; the use of a standardized methodology allows for direct comparison between cities.

Classification of the web

DEFF Research Database (Denmark)

Mai, Jens Erik

2004-01-01

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

Security classification of information

Energy Technology Data Exchange (ETDEWEB)

Quist, A.S.

1993-04-01

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

Data classification and MTBF prediction with a multivariate analysis approach

International Nuclear Information System (INIS)

Braglia, Marcello; Carmignani, Gionata; Frosolini, Marco; Zammori, Francesco

2012-01-01

The paper presents a multivariate statistical approach that supports the classification of mechanical components, subjected to specific operating conditions, in terms of the Mean Time Between Failure (MTBF). Assessing the influence of working conditions and/or environmental factors on the MTBF is a prerequisite for the development of an effective preventive maintenance plan. However, this task may be demanding and it is generally performed with ad-hoc experimental methods, lacking of statistical rigor. To solve this common problem, a step by step multivariate data classification technique is proposed. Specifically, a set of structured failure data are classified in a meaningful way by means of: (i) cluster analysis, (ii) multivariate analysis of variance, (iii) feature extraction and (iv) predictive discriminant analysis. This makes it possible not only to define the MTBF of the analyzed components, but also to identify the working parameters that explain most of the variability of the observed data. The approach is finally demonstrated on 126 centrifugal pumps installed in an oil refinery plant; obtained results demonstrate the quality of the final discrimination, in terms of data classification and failure prediction.

Hazard classification methodology

International Nuclear Information System (INIS)

Brereton, S.J.

1996-01-01

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

Revising the definition of the crustacean seta and setal classification systems based on examinations of the mouthpart setae of seven species of decapods

DEFF Research Database (Denmark)

Garm, Anders Lydik

2004-01-01

and problems in making a consistent classification system. Here, the cuticular projections on the mouthparts of seven species of decapods are examined by scanning and transmission electron microscopy. A new definition is given: a seta is an elongate projection with a more or less circular base and a continuous...... and not evolutionary history. This classification system is compared with earlier systems. (C) 2004 The Linnean Society of London....

Application of project management in technology improvement of Qinshan III

International Nuclear Information System (INIS)

Liu Xiaonian

2008-01-01

During the operation of Qinshan III, many engineering modifications and renovation projects are being carried out. Advanced international project management methodologies accustomed to the policy and organizational characteristics of TQNPC were applied to the management of these projects. After practical application and development of these methodologies, the company finally sets up its own classification of project management system. The project management system is introduced and discussed for its evolving direction in this paper. (authors)

Changing Histopathological Diagnostics by Genome-Based Tumor Classification

Directory of Open Access Journals (Sweden)

Michael Kloth

2014-05-01

Full Text Available Traditionally, tumors are classified by histopathological criteria, i.e., based on their specific morphological appearances. Consequently, current therapeutic decisions in oncology are strongly influenced by histology rather than underlying molecular or genomic aberrations. The increase of information on molecular changes however, enabled by the Human Genome Project and the International Cancer Genome Consortium as well as the manifold advances in molecular biology and high-throughput sequencing techniques, inaugurated the integration of genomic information into disease classification. Furthermore, in some cases it became evident that former classifications needed major revision and adaption. Such adaptations are often required by understanding the pathogenesis of a disease from a specific molecular alteration, using this molecular driver for targeted and highly effective therapies. Altogether, reclassifications should lead to higher information content of the underlying diagnoses, reflecting their molecular pathogenesis and resulting in optimized and individual therapeutic decisions. The objective of this article is to summarize some particularly important examples of genome-based classification approaches and associated therapeutic concepts. In addition to reviewing disease specific markers, we focus on potentially therapeutic or predictive markers and the relevance of molecular diagnostics in disease monitoring.

Innovations in redevelopment projects

Directory of Open Access Journals (Sweden)

Radushinsky Dmitry

2018-01-01

Full Text Available Some examples of redevelopment of industrial territories (lofting abroad and in Russia for the purpose of qualitative research and classification, identification of the main features of process innovations are considered in the article. The following main parameters were established, according to which the differences in the implementation of various types of redevelopment projects were determined: the composition of the consumers of the services (the result of the implemented project, the opportunities and the intensity of the flow of high-class specialists to the jobs created during the redevelopment of municipal and regional facilities, area, value (budget and terms of project implementation. A perspective project of RTOs (museum-entertainment complex for machine-building in Kolpino, as well as opportunities to expand the ecosystem of innovation Sochi Innovation Valley, was considered.

Definition and Classification of the Stakeholders in Land Consolidation Project

Institute of Scientific and Technical Information of China (English)

LIU Xiang-dong; GUO Bi-jun; GUO Mao-xuan

2012-01-01

Using the methods of questionnaire survey, statistical analysis and multidimensional rating, we define and classify the stakeholders in land consolidation project. 25 kinds of stakeholders are determined, divided into three categories: core stakeholders, including county-level government, county-level land departments, county-level land consolidation center, the rural collective economic organizations, farmers, township government, and the villagers’ committee; middle stakeholders, including central government, the Ministry of Land and Resources, the Ministry of Land and Resources Land Consolidation Center, the provincial land departments, the provincial land consolidation center, the county-level finance departments, the county-level water resources departments, the government supervisory departments, government audit departments, and the public; peripheral stakeholders, including the county-level environmental protection departments, the county-level agricultural departments, supervisory agencies, design agencies, project contractors, equipment suppliers, material suppliers, and the bidding agencies. The project managers should pay attention to the interest appeal of the stakeholders, and adopt different coping strategies.

Application of InterPro for the functional classification of the proteins ...

Indian Academy of Sciences (India)

InterPro (http://www.ebi.ac.uk/interpro/) is an integrated documentation resource for protein families, domains and sites, developed initially as a means of rationalizing the complementary efforts of the PROSITE, PRINTS, Pfam and ProDom database projects. It is a useful resource that aids the functional classification of ...

A Study of Major Projects and Contractual conditions: A Framework for Performance Improvement

OpenAIRE

Sangesland, Jon Sigbjørn

2016-01-01

Master's thesis in Industrial economics The oil price has experienced a significant decline since the second half of 2014. In combination with the high cost level, many field developments in the Norwegian petroleum sector entail marginable profit. As a counter measure to cope with the challenging market conditions, both oil companies and service suppliers are making various efforts such as substantial downsizing internal staff, as well as reducing costs in all phases of the project. Moreov...

Sound classification of dwellings in the Nordic countries

DEFF Research Database (Denmark)

Rindel, Jens Holger; Turunen-Rise, Iiris

1997-01-01

be met. The classification system is based on limit values for airborne sound insulation, impact sound pressure level, reverberation time and indoor and outdoor noise levels. The purpose of the standard is to offer a tool for specification of a standardised acoustic climate and to promote constructors......A draft standard INSTA 122:1997 on sound classification of dwellings is for voting as a common national standard in the Nordic countries (Denmark, Norway, Sweden, Finland, Iceland) and in Estonia. The draft standard specifies a sound classification system with four classes A, B, C and D, where...... class C is proposed as the future minimum requirements for new dwellings. The classes B and A define criteria for dwellings with improved or very good acoustic conditions, whereas class D may be used for older, renovated dwellings in which the acoustic quality level of a new dwelling cannot reasonably...

Contract-program evaluation: Impact of the DRG classification system on hospitals' outputs

OpenAIRE

Alves, Helder António Pereira Gomes

2010-01-01

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics The present work project aims at evaluating the impact of contract-program implementation in 2003 and of incentives created in 2007 on hospital output, under the DRG inpatient classification system. A sample of five Portuguese acute public district hospitals was chosen as sample, between 2002 and 2007. Results of hypothesis testing ...

Controlling a human-computer interface system with a novel classification method that uses electrooculography signals.

Science.gov (United States)

Wu, Shang-Lin; Liao, Lun-De; Lu, Shao-Wei; Jiang, Wei-Ling; Chen, Shi-An; Lin, Chin-Teng

2013-08-01

Electrooculography (EOG) signals can be used to control human-computer interface (HCI) systems, if properly classified. The ability to measure and process these signals may help HCI users to overcome many of the physical limitations and inconveniences in daily life. However, there are currently no effective multidirectional classification methods for monitoring eye movements. Here, we describe a classification method used in a wireless EOG-based HCI device for detecting eye movements in eight directions. This device includes wireless EOG signal acquisition components, wet electrodes and an EOG signal classification algorithm. The EOG classification algorithm is based on extracting features from the electrical signals corresponding to eight directions of eye movement (up, down, left, right, up-left, down-left, up-right, and down-right) and blinking. The recognition and processing of these eight different features were achieved in real-life conditions, demonstrating that this device can reliably measure the features of EOG signals. This system and its classification procedure provide an effective method for identifying eye movements. Additionally, it may be applied to study eye functions in real-life conditions in the near future.

Territorial pattern and classification of soils of Kryvyi Rih Iron-Ore Basin

Directory of Open Access Journals (Sweden)

О. О. Dolina

2014-10-01

Full Text Available The authors developed the classification of soils and adapted it to the conditions of Krivyi Rih industrial region. It became the basis for determining the degree of soil cover transformation in the iron-ore basin under technogenesis. The classification represents the system of hierarchical objects of different taxonomic levels. It allows determination of relationships between objects and their properties. Researched patterns of soil cover structures’ distribution were the basis for the relevant mapping and classification of soils. The classification is adapted to highly-influential industrial conditions of soils formation in the region. The adaptation measures were specific classification levels and units, which provided more detailed differentiation of soils. The authors proposed to separate the soils by the degree of soil formation potential realization for super-divisions. The potential determination allowed predicting the outcome of soil formation and identification of transformation degree of soil cover structures in the region. The results indicated that the main type of soil structures in the industrial region was represented by primitive soils (indicated as a separate type. These soils were determined as dynamic elements in the structure of industrial region soil cover. The article indicated that presence of soil cover structures with the domination of technogenic soils, particularly post-technogenic soils, was the marker of the soil cover in Krivyi Rih Iron-Ore Basin

Classification, disease, and diagnosis.

Science.gov (United States)

Jutel, Annemarie

2011-01-01

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

An optimum condition for attainment of a single currency project in West Africa

Directory of Open Access Journals (Sweden)

Moses Abanyam Chiawa

2014-01-01

Full Text Available The paper examines the primary and secondary convergence conditions for a monetary union in the second monetary zone for West Africa. The focus of the paper is on the primary conditions as they provide the basis for the secondary conditions. The annual panel data used for the research are obtained from the West African Monetary Agency website: www.wami.imao.org. The panel variables are first tested for unit root and stationarity. The panel unit root test results show that all the variables are integrated of order one. The stationarity test confirms the result, as the variables are non-stationarity in level but stationarity after first difference. The Long-run co integration equation is obtained using the pooled group mean estimator. Linear programming is then applied on the result of the long-run equationto obtain the optimal conditions for attainment of single currency project for West Africa. The result shows that the objective value of 0.0462 is obtained with inflation contributing more to the variation in the government external reserves. The Central Banks in West Africa should be cautious in implementing inflation targeting as a way of tackling their economic problem.

Conditions That Support the Implementation of E-Government through the Digital Towpath Project: An Exploratory Study

Science.gov (United States)

Tyksinski, Deborah J.

2009-01-01

This study examined the social environmental conditions perceived by local government representatives as relatively important for their implementation of e-government using the Digital Towpath Project (DTP) content management system, referred to as "websites". The survey population included individuals who administered the municipal websites for…

Overlapping Chronic Pain Conditions: Implications for Diagnosis and Classification.

Science.gov (United States)

Maixner, William; Fillingim, Roger B; Williams, David A; Smith, Shad B; Slade, Gary D

2016-09-01

There is increasing recognition that many if not most common chronic pain conditions are heterogeneous with a high degree of overlap or coprevalence of other common pain conditions along with influences from biopsychosocial factors. At present, very little attention is given to the high degree of overlap of many common pain conditions when recruiting for clinical trials. As such, many if not most patients enrolled into clinical studies are not representative of most chronic pain patients. The failure to account for the heterogeneous and overlapping nature of most common pain conditions may result in treatment responses of small effect size when these treatments are administered to patients with chronic overlapping pain conditions (COPCs) represented in the general population. In this brief review we describe the concept of COPCs and the putative mechanisms underlying COPCs. Finally, we present a series of recommendations that will advance our understanding of COPCs. This brief review describes the concept of COPCs. A mechanism-based heuristic model is presented and current knowledge and evidence for COPCs are presented. Finally, a set of recommendations is provided to advance our understanding of COPCs. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

Standard classification: Physics

International Nuclear Information System (INIS)

1977-01-01

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

Analysis and mapping of present and future drought conditions over Greek areas with different climate conditions

Science.gov (United States)

Paparrizos, Spyridon; Maris, Fotios; Weiler, Markus; Matzarakis, Andreas

2018-01-01

Estimation of drought in a certain temporal and spatial scale is crucial in climate change studies. The current study targets on three agricultural areas widespread in Greece, Ardas River Basin in Northeastern Greece, Sperchios River Basin in Central Greece, and Geropotamos River Basin in Crete Island in South Greece that are characterized by diverse climates as they are located in various regions. The objective is to assess the spatiotemporal variation of drought conditions prevailing in these areas. The Standardized Precipitation Index (SPI) was used to identify and assess the present and future drought conditions. Future simulated data were derived from a number of Regional Climatic Models (RCMs) from the ENSEMBLES European Project. The analysis was performed for the future periods of 2021-2050 and 2071-2100, implementing A1B and B1 scenarios. The spatial analysis of the drought conditions was performed using a combined downscaling technique and the Ordinary Kriging. The Mann-Kendall test was implemented for trend investigation. During both periods and scenarios, drought conditions will tend to be more severe in the upcoming years. The decrease of the SPI values in the Sperchios River Basin is expected to be the strongest, as it is the only study area that will show a negative balance (in SPI values), regarding the drought conditions. For the Ardas and the Geropotamos River Basins, a great increase of the drought conditions will occur during the 2021-2050 period, while for 2071-2100 period, the decrease will continue but it will be tempered. Nevertheless, the situation in all study areas according to the SPI classification is characterized as "Near-normal", in terms of drought conditions.

Framework for Probabilistic Projections of Energy-Relevant Streamflow Indicators under Climate Change Scenarios for the U.S.

Energy Technology Data Exchange (ETDEWEB)

Wagener, Thorsten [Univ. of Bristol (United Kingdom); Mann, Michael [Pennsylvania State Univ., State College, PA (United States); Crane, Robert [Pennsylvania State Univ., State College, PA (United States)

2014-04-29

This project focuses on uncertainty in streamflow forecasting under climate change conditions. The objective is to develop easy to use methodologies that can be applied across a range of river basins to estimate changes in water availability for realistic projections of climate change. There are three major components to the project: Empirical downscaling of regional climate change projections from a range of Global Climate Models; Developing a methodology to use present day information on the climate controls on the parameterizations in streamflow models to adjust the parameterizations under future climate conditions (a trading-space-for-time approach); and Demonstrating a bottom-up approach to establishing streamflow vulnerabilities to climate change. The results reinforce the need for downscaling of climate data for regional applications, and further demonstrates the challenges of using raw GCM data to make local projections. In addition, it reinforces the need to make projections across a range of global climate models. The project demonstrates the potential for improving streamflow forecasts by using model parameters that are adjusted for future climate conditions, but suggests that even with improved streamflow models and reduced climate uncertainty through the use of downscaled data, there is still large uncertainty is the streamflow projections. The most useful output from the project is the bottom-up vulnerability driven approach to examining possible climate and land use change impacts on streamflow. Here, we demonstrate an inexpensive and easy to apply methodology that uses Classification and Regression Trees (CART) to define the climate and environmental parameters space that can produce vulnerabilities in the system, and then feeds in the downscaled projections to determine the probability top transitioning to a vulnerable sate. Vulnerabilities, in this case, are defined by the end user.

The Influence of Weather Conditions on Joint Pain in Older People with Osteoarthritis: Results from the European Project on OSteoArthritis

NARCIS (Netherlands)

Timmermans, E.J.; Schaap, L.A.; Herbolsheimer, F.; Dennison, E.M.; Maggi, S.; Pedersen, N.L.; Castell, M.V; Denkinger, M.D.; Edwards, M.H.; Limongi, F.; Sanchez-Martinez, M.; Siviero, P.; Queipo, R.; Peter, R.; van der Pas, S.; Deeg, D.J.H.

2015-01-01

Objective. This study examined whether daily weather conditions, 3-day average weather conditions, and changes in weather conditions influence joint pain in older people with osteoarthritis (OA) in 6 European countries. Methods. Data from the population-based European Project on OSteoArthritis were

High Accuracy Human Activity Recognition Based on Sparse Locality Preserving Projections.

Science.gov (United States)

Zhu, Xiangbin; Qiu, Huiling

2016-01-01

Human activity recognition(HAR) from the temporal streams of sensory data has been applied to many fields, such as healthcare services, intelligent environments and cyber security. However, the classification accuracy of most existed methods is not enough in some applications, especially for healthcare services. In order to improving accuracy, it is necessary to develop a novel method which will take full account of the intrinsic sequential characteristics for time-series sensory data. Moreover, each human activity may has correlated feature relationship at different levels. Therefore, in this paper, we propose a three-stage continuous hidden Markov model (TSCHMM) approach to recognize human activities. The proposed method contains coarse, fine and accurate classification. The feature reduction is an important step in classification processing. In this paper, sparse locality preserving projections (SpLPP) is exploited to determine the optimal feature subsets for accurate classification of the stationary-activity data. It can extract more discriminative activities features from the sensor data compared with locality preserving projections. Furthermore, all of the gyro-based features are used for accurate classification of the moving data. Compared with other methods, our method uses significantly less number of features, and the over-all accuracy has been obviously improved.

High Accuracy Human Activity Recognition Based on Sparse Locality Preserving Projections.

Directory of Open Access Journals (Sweden)

Xiangbin Zhu

Full Text Available Human activity recognition(HAR from the temporal streams of sensory data has been applied to many fields, such as healthcare services, intelligent environments and cyber security. However, the classification accuracy of most existed methods is not enough in some applications, especially for healthcare services. In order to improving accuracy, it is necessary to develop a novel method which will take full account of the intrinsic sequential characteristics for time-series sensory data. Moreover, each human activity may has correlated feature relationship at different levels. Therefore, in this paper, we propose a three-stage continuous hidden Markov model (TSCHMM approach to recognize human activities. The proposed method contains coarse, fine and accurate classification. The feature reduction is an important step in classification processing. In this paper, sparse locality preserving projections (SpLPP is exploited to determine the optimal feature subsets for accurate classification of the stationary-activity data. It can extract more discriminative activities features from the sensor data compared with locality preserving projections. Furthermore, all of the gyro-based features are used for accurate classification of the moving data. Compared with other methods, our method uses significantly less number of features, and the over-all accuracy has been obviously improved.

[The inadequacy of official classification of work accidents in Brazil].

Science.gov (United States)

Cordeiro, Ricardo

2018-02-19

Traditionally, work accidents in Brazil have been categorized in government documents and legal and academic texts as typical work accidents and commuting accidents. Given the increase in urban violence and the increasingly precarious work conditions in recent decades, this article addresses the conceptual inadequacy of this classification and its implications for the underestimation of work accidents in the country. An alternative classification is presented as an example and a contribution to the discussion on the improvement of statistics on work-related injuries in Brazil.

Methodology for cost estimate in projects for nuclear power plants decommissioning

International Nuclear Information System (INIS)

Salij, L.M.

2008-01-01

The conceptual approaches to cost estimating of nuclear power plants units decommissioning projects were determined. The international experience and national legislative and regulatory basis were analyzed. The possible decommissioning project cost classification was given. It was shown the role of project costs of nuclear power plant units decommissioning as the most important criterion for the main project decisions. The technical and economic estimation of deductions to common-branch fund of decommissioning projects financing was substantiated

K3 projective models in scrolls

CERN Document Server

Johnsen, Trygve

2004-01-01

The exposition studies projective models of K3 surfaces whose hyperplane sections are non-Clifford general curves. These models are contained in rational normal scrolls. The exposition supplements standard descriptions of models of general K3 surfaces in projective spaces of low dimension, and leads to a classification of K3 surfaces in projective spaces of dimension at most 10. The authors bring further the ideas in Saint-Donat's classical article from 1974, lifting results from canonical curves to K3 surfaces and incorporating much of the Brill-Noether theory of curves and theory of syzygies developed in the mean time.

The paradox of atheoretical classification

DEFF Research Database (Denmark)

Hjørland, Birger

2016-01-01

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

Toward noncooperative iris recognition: a classification approach using multiple signatures.

Science.gov (United States)

Proença, Hugo; Alexandre, Luís A

2007-04-01

This paper focuses on noncooperative iris recognition, i.e., the capture of iris images at large distances, under less controlled lighting conditions, and without active participation of the subjects. This increases the probability of capturing very heterogeneous images (regarding focus, contrast, or brightness) and with several noise factors (iris obstructions and reflections). Current iris recognition systems are unable to deal with noisy data and substantially increase their error rates, especially the false rejections, in these conditions. We propose an iris classification method that divides the segmented and normalized iris image into six regions, makes an independent feature extraction and comparison for each region, and combines each of the dissimilarity values through a classification rule. Experiments show a substantial decrease, higher than 40 percent, of the false rejection rates in the recognition of noisy iris images.

Clay-illuvial soils in the Polish and international soil classifications

Directory of Open Access Journals (Sweden)

Kabała Cezary

2015-12-01

Full Text Available Soil with a clay-illuvial subsurface horizon are the most widespread soil type in Poland and significantly differ in morphology and properties developed under variable environmental conditions. Despite the long history of investigations, the rules of classification and cartography of clay-illuvial soils have been permanently discussed and modified. The distinction of clay-illuvial soils into three soil types, introduced to the Polish soil classification in 2011, has been criticized as excessively extended, non-coherent with the other parts and rules of the classification, hard to introduce in soil cartography and poorly correlated with the international soil classifications. One type of clay-illuvial soils (“gleby płowe” was justified and recommended to reintroduce in soil classification in Poland, as well as 10 soil subtypes listed in a hierarchical order. The subtypes may be combined if the soil has diagnostic features of more than one soil subtypes. Clear rules of soil name generalization (reduction of subtype number for one soil were suggested for soil cartography on various scales. One of the most important among the distinguished soil sub-types are the “eroded” or “truncated” clay-illuvial soils.

Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Sheng Wang

2007-07-01

Full Text Available Wireless sensor networks (WSNs are autonomous networks that have beenfrequently deployed to collaboratively perform target localization and classification tasks.Their autonomous and collaborative features resemble the characteristics of agents. Suchsimilarities inspire the development of heterogeneous agent architecture for WSN in thispaper. The proposed agent architecture views WSN as multi-agent systems and mobileagents are employed to reduce in-network communication. According to the architecture,an energy based acoustic localization algorithm is proposed. In localization, estimate oftarget location is obtained by steepest descent search. The search algorithm adapts tomeasurement environments by dynamically adjusting its termination condition. With theagent architecture, target classification is accomplished by distributed support vectormachine (SVM. Mobile agents are employed for feature extraction and distributed SVMlearning to reduce communication load. Desirable learning performance is guaranteed bycombining support vectors and convex hull vectors. Fusion algorithms are designed tomerge SVM classification decisions made from various modalities. Real world experimentswith MICAz sensor nodes are conducted for vehicle localization and classification.Experimental results show the proposed agent architecture remarkably facilitates WSNdesigns and algorithm implementation. The localization and classification algorithms alsoprove to be accurate and energy efficient.

A Soft Intelligent Risk Evaluation Model for Credit Scoring Classification

Directory of Open Access Journals (Sweden)

Mehdi Khashei

2015-09-01

Full Text Available Risk management is one of the most important branches of business and finance. Classification models are the most popular and widely used analytical group of data mining approaches that can greatly help financial decision makers and managers to tackle credit risk problems. However, the literature clearly indicates that, despite proposing numerous classification models, credit scoring is often a difficult task. On the other hand, there is no universal credit-scoring model in the literature that can be accurately and explanatorily used in all circumstances. Therefore, the research for improving the efficiency of credit-scoring models has never stopped. In this paper, a hybrid soft intelligent classification model is proposed for credit-scoring problems. In the proposed model, the unique advantages of the soft computing techniques are used in order to modify the performance of the traditional artificial neural networks in credit scoring. Empirical results of Australian credit card data classifications indicate that the proposed hybrid model outperforms its components, and also other classification models presented for credit scoring. Therefore, the proposed model can be considered as an appropriate alternative tool for binary decision making in business and finance, especially in high uncertainty conditions.

Transporter Classification Database (TCDB)

Data.gov (United States)

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

The Impact of Climatological Conditions on Low Enriched Uranium Loading Station Operations for the HEU Blend Down Project

International Nuclear Information System (INIS)

Chang, R.C.

2002-01-01

A computer model was developed using COREsim to perform a time motion study for the Low Enriched Uranium (LEU) Loading Station operations. The project is to blend Highly Enriched Uranium (HEU) with Natural Uranium (NU) to produce LEU to be shipped to Tennessee Valley Authority (TVA) for further processing. To cope with a project cost reduction, the LEU Loading Station concept has changed from an enclosed building with air-conditioning to a partially enclosed building without air conditioning. The LEU Loading Station is within a radiological contaminated area; two pairs of coveralls and negative pressure respirator are required. As a result, inclement weather conditions, especially heat stress, will affect and impact the LEU loading operations. The purposes of the study are to determine the climatological impacts on LEU Loading operations, resources required for committed throughputs, and to find out the optimum process pathways for multi crews working simultaneously in the space-lim ited LEU Loading Station

Application of the Safety Classification of Structures, Systems and Components in Nuclear Power Plants

International Nuclear Information System (INIS)

2016-04-01

This publication describes how to complete tasks associated with every step of the classification methodology set out in IAEA Safety Standards Series No. SSG-30, Safety Classification of Structures, Systems and Components in Nuclear Power Plants. In particular, how to capture all the structures, systems and components (SSCs) of a nuclear power plant to be safety classified. Emphasis is placed on the SSCs that are necessary to limit radiological releases to the public and occupational doses to workers in operational conditions This publication provides information for organizations establishing a comprehensive safety classification of SSCs compliant with IAEA recommendations, and to support regulators in reviewing safety classification submitted by licensees

A new tool in the classification of rational conformal field theories

International Nuclear Information System (INIS)

Christe, P.; Ravanini, F.

1988-10-01

The fact that in any rational conformal field theory (RCFT) 4-point functions on the sphere must satisfy an ordinary differential equation gives a simple condition on the conformal dimensions of primary fields. We discuss how this can help in the classification program of RCFT. As an example all associative fusion rules with less than four non-trivial primary fields and N ijk <<1 are discussed. Another application to the classification of chiral algebras is briefly mentioned. (orig.)

IMAGE Project: Results of Laboratory Tests on Tracers for Supercritical Conditions.

Science.gov (United States)

Brandvoll, Øyvind; Opsahl Viig, Sissel; Nardini, Isabella; Muller, Jiri

2016-04-01

The use of tracers is a well-established technique for monitoring dynamic behaviour of water and gas through a reservoir. In geothermal reservoirs special challenges are encountered due to high temperatures and pressures. In this work, tracer candidates for monitoring water at supercritical conditions (temperature > 374°C, pressure ca 218 bar), are tested in laboratory experiments. Testing of tracers at supercritical water conditions requires experimental set-ups which tolerate harsh conditions with respect to high temperature and pressure. In addition stringent HES (health, environment and safety) factors have to be taken into consideration when designing and performing the experiments. The setup constructed in this project consists of a pressure vessel, high pressure pump, instrumentation for pressure and temperature control and instrumentation required for accurate sampling of tracers. In order to achieve accurate results, a special focus has been paid to the development of the tracer sampling technique. Perfluorinated cyclic hydrocarbons (PFCs) have been selected as tracer candidates. This group of compounds is today commonly used as gas tracers in oil reservoirs. According to the literature they are stable at temperatures up to 400°C. To start with, five PFCs have been tested for thermal stability in static experiments at 375°C and 108 bar in the experimental setup described above. The tracer candidates will be further tested for several months at the relevant conditions. Preliminary results indicate that some of the PFC compounds show stability after three months. However, in order to arrive at conclusive results, the experiments have to be repeated over a longer period and paying special attention to more accurate sampling procedures.

Monitoring nanotechnology using patent classifications: an overview and comparison of nanotechnology classification schemes

Energy Technology Data Exchange (ETDEWEB)

Jürgens, Björn, E-mail: bjurgens@agenciaidea.es [Agency of Innovation and Development of Andalusia, CITPIA PATLIB Centre (Spain); Herrero-Solana, Victor, E-mail: victorhs@ugr.es [University of Granada, SCImago-UGR (SEJ036) (Spain)

2017-04-15

Patents are an essential information source used to monitor, track, and analyze nanotechnology. When it comes to search nanotechnology-related patents, a keyword search is often incomplete and struggles to cover such an interdisciplinary discipline. Patent classification schemes can reveal far better results since they are assigned by experts who classify the patent documents according to their technology. In this paper, we present the most important classifications to search nanotechnology patents and analyze how nanotechnology is covered in the main patent classification systems used in search systems nowadays: the International Patent Classification (IPC), the United States Patent Classification (USPC), and the Cooperative Patent Classification (CPC). We conclude that nanotechnology has a significantly better patent coverage in the CPC since considerable more nanotechnology documents were retrieved than by using other classifications, and thus, recommend its use for all professionals involved in nanotechnology patent searches.

Monitoring nanotechnology using patent classifications: an overview and comparison of nanotechnology classification schemes

International Nuclear Information System (INIS)

Jürgens, Björn; Herrero-Solana, Victor

2017-01-01

Patents are an essential information source used to monitor, track, and analyze nanotechnology. When it comes to search nanotechnology-related patents, a keyword search is often incomplete and struggles to cover such an interdisciplinary discipline. Patent classification schemes can reveal far better results since they are assigned by experts who classify the patent documents according to their technology. In this paper, we present the most important classifications to search nanotechnology patents and analyze how nanotechnology is covered in the main patent classification systems used in search systems nowadays: the International Patent Classification (IPC), the United States Patent Classification (USPC), and the Cooperative Patent Classification (CPC). We conclude that nanotechnology has a significantly better patent coverage in the CPC since considerable more nanotechnology documents were retrieved than by using other classifications, and thus, recommend its use for all professionals involved in nanotechnology patent searches.

CLASSIFICATION OF CROPLANDS THROUGH FUSION OF OPTICAL AND SAR TIME SERIES DATA

Directory of Open Access Journals (Sweden)

S. Park

2016-06-01

Full Text Available Many satellite sensors including Landsat series have been extensively used for land cover classification. Studies have been conducted to mitigate classification problems associated with the use of single data (e.g., such as cloud contamination through multi-sensor data fusion and the use of time series data. This study investigated two areas with different environment and climate conditions: one in South Korea and the other in US. Cropland classification was conducted by using multi-temporal Landsat 5, Radarsat-1 and digital elevation models (DEM based on two machine learning approaches (i.e., random forest and support vector machines. Seven classification scenarios were examined and evaluated through accuracy assessment. Results show that SVM produced the best performance (overall accuracy of 93.87% when using all temporal and spectral data as input variables. Normalized Difference Water Index (NDWI, SAR backscattering, and Normalized Difference Vegetation Index (NDVI were identified as more contributing variables than the others for cropland classification.

Assimilation of a knowledge base and physical models to reduce errors in passive-microwave classifications of sea ice

Science.gov (United States)

Maslanik, J. A.; Key, J.

1992-01-01

An expert system framework has been developed to classify sea ice types using satellite passive microwave data, an operational classification algorithm, spatial and temporal information, ice types estimated from a dynamic-thermodynamic model, output from a neural network that detects the onset of melt, and knowledge about season and region. The rule base imposes boundary conditions upon the ice classification, modifies parameters in the ice algorithm, determines a `confidence' measure for the classified data, and under certain conditions, replaces the algorithm output with model output. Results demonstrate the potential power of such a system for minimizing overall error in the classification and for providing non-expert data users with a means of assessing the usefulness of the classification results for their applications.

A proposal of criteria for the classification of systemic sclerosis.

Science.gov (United States)

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

2004-11-01

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

Discovering beaten paths in collaborative ontology-engineering projects using Markov chains.

Science.gov (United States)

Walk, Simon; Singer, Philipp; Strohmaier, Markus; Tudorache, Tania; Musen, Mark A; Noy, Natalya F

2014-10-01

Biomedical taxonomies, thesauri and ontologies in the form of the International Classification of Diseases as a taxonomy or the National Cancer Institute Thesaurus as an OWL-based ontology, play a critical role in acquiring, representing and processing information about human health. With increasing adoption and relevance, biomedical ontologies have also significantly increased in size. For example, the 11th revision of the International Classification of Diseases, which is currently under active development by the World Health Organization contains nearly 50,000 classes representing a vast variety of different diseases and causes of death. This evolution in terms of size was accompanied by an evolution in the way ontologies are engineered. Because no single individual has the expertise to develop such large-scale ontologies, ontology-engineering projects have evolved from small-scale efforts involving just a few domain experts to large-scale projects that require effective collaboration between dozens or even hundreds of experts, practitioners and other stakeholders. Understanding the way these different stakeholders collaborate will enable us to improve editing environments that support such collaborations. In this paper, we uncover how large ontology-engineering projects, such as the International Classification of Diseases in its 11th revision, unfold by analyzing usage logs of five different biomedical ontology-engineering projects of varying sizes and scopes using Markov chains. We discover intriguing interaction patterns (e.g., which properties users frequently change after specific given ones) that suggest that large collaborative ontology-engineering projects are governed by a few general principles that determine and drive development. From our analysis, we identify commonalities and differences between different projects that have implications for project managers, ontology editors, developers and contributors working on collaborative ontology

Discovering Beaten Paths in Collaborative Ontology-Engineering Projects using Markov Chains

Science.gov (United States)

Walk, Simon; Singer, Philipp; Strohmaier, Markus; Tudorache, Tania; Musen, Mark A.; Noy, Natalya F.

2014-01-01

Biomedical taxonomies, thesauri and ontologies in the form of the International Classification of Diseases as a taxonomy or the National Cancer Institute Thesaurus as an OWL-based ontology, play a critical role in acquiring, representing and processing information about human health. With increasing adoption and relevance, biomedical ontologies have also significantly increased in size. For example, the 11th revision of the International Classification of Diseases, which is currently under active development by the World Health Organization contains nearly 50, 000 classes representing a vast variety of different diseases and causes of death. This evolution in terms of size was accompanied by an evolution in the way ontologies are engineered. Because no single individual has the expertise to develop such large-scale ontologies, ontology-engineering projects have evolved from small-scale efforts involving just a few domain experts to large-scale projects that require effective collaboration between dozens or even hundreds of experts, practitioners and other stakeholders. Understanding the way these different stakeholders collaborate will enable us to improve editing environments that support such collaborations. In this paper, we uncover how large ontology-engineering projects, such as the International Classification of Diseases in its 11th revision, unfold by analyzing usage logs of five different biomedical ontology-engineering projects of varying sizes and scopes using Markov chains. We discover intriguing interaction patterns (e.g., which properties users frequently change after specific given ones) that suggest that large collaborative ontology-engineering projects are governed by a few general principles that determine and drive development. From our analysis, we identify commonalities and differences between different projects that have implications for project managers, ontology editors, developers and contributors working on collaborative ontology

[Current aspects of harmonization of classification of occupational hearing loss].

Science.gov (United States)

Pankova, V B; Sinëva, E L; Tavartkiladze, G A; Fedina, I N; Preobrazhenskaia, E A; Mukhamedova, G R

2013-01-01

The objective of the present work was to develop unified criteria for the evaluation of the severity of noise-induced hearing loss. Current approaches to taking expert decisions based on the results of medical examination of the patients with impaired hearing are substantially different due to the considerable difference between the criteria for the estimation of hearing envisaged by the international classification, occupational pathology classification, and the national system of medico-social expertise. We undertook an attempt to correct and harmonize the existing criteria for the estimation of severity of occupational hearing loss based on the integration of all the three classification in order to "reduce them to a common denominator" and thereby to ensure the basis for the unified diagnostic and expert decisions for the cases of hearing impairment of any etiology. The project proposed in this paper makes it possible to use unified criteria for the assessment of the degree of hearing loss caused by occupational noises for diagnostic purposes and expertise compatible with the internationally accepted approaches.

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

Science.gov (United States)

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

1990-01-01

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

Small-scale classification schemes

DEFF Research Database (Denmark)

Hertzum, Morten

2004-01-01

Small-scale classification schemes are used extensively in the coordination of cooperative work. This study investigates the creation and use of a classification scheme for handling the system requirements during the redevelopment of a nation-wide information system. This requirements...... classification inherited a lot of its structure from the existing system and rendered requirements that transcended the framework laid out by the existing system almost invisible. As a result, the requirements classification became a defining element of the requirements-engineering process, though its main...... effects remained largely implicit. The requirements classification contributed to constraining the requirements-engineering process by supporting the software engineers in maintaining some level of control over the process. This way, the requirements classification provided the software engineers...

An ECG Lab Project for Teaching Signal Conditioning Systems in a Master's Degree in Mechatronic Engineering

Science.gov (United States)

Martín, Francisco Javier Ferrero; Martínez, Alberto López; Llopis, Marta Valledor; Rodriguez, Juan Carlos Campo; Viejo, Cecilio Blanco; Vershinin, Yuri A.

2015-01-01

Ongoing technological progress in measurement systems triggered the development of an in­novative, hands-on teaching program to help students toward a fuller understanding of recent changes in the field. This paper presents a lab project that links theoretical principles with the practical issues of signal conditioning systems. This is…

A new circulation type classification based upon Lagrangian air trajectories

Directory of Open Access Journals (Sweden)

Alexandre M. Ramos

2014-10-01

Full Text Available A new classification method of the large-scale circulation characteristic for a specific target area (NW Iberian Peninsula is presented, based on the analysis of 90-h backward trajectories arriving in this area calculated with the 3-D Lagrangian particle dispersion model FLEXPART. A cluster analysis is applied to separate the backward trajectories in up to five representative air streams for each day. Specific measures are then used to characterise the distinct air streams (e.g., curvature of the trajectories, cyclonic or anticyclonic flow, moisture evolution, origin and length of the trajectories. The robustness of the presented method is demonstrated in comparison with the Eulerian Lamb weather type classification.A case study of the 2003 heatwave is discussed in terms of the new Lagrangian circulation and the Lamb weather type classifications. It is shown that the new classification method adds valuable information about the pertinent meteorological conditions, which are missing in an Eulerian approach. The new method is climatologically evaluated for the five-year time period from December 1999 to November 2004. The ability of the method to capture the inter-seasonal circulation variability in the target region is shown. Furthermore, the multi-dimensional character of the classification is shortly discussed, in particular with respect to inter-seasonal differences. Finally, the relationship between the new Lagrangian classification and the precipitation in the target area is studied.

[Investigation on standard application of industrial dust hazard classification].

Science.gov (United States)

Lu, Y; Zhang, M; Chen, W H

2017-04-20

Objective: To investigate the application and effectiveness evaluation of the standard of GBZ/T 229.1-2010 in practice, and to explore the applicability, aiming to provide technical evidence for the revision of GBZ/T 229.1-2010. Methods: There were 2 questionnaire surveys carried out in the study, including general survey and specific survey. Databases were established and data were input with Excel 2010 and Epidata version 3.1 software. SPSS version 19.0 software was used for data cleaning and statistical analysis. Results: The general survey received 100 questionnaires, with 43 from facilities and 57 from professional expertise. There were 59 questionnaires from occupational health technical service organizations held by government, and 11 from colleges and universities. The leading three jobs using GBZ/T 229.1-2010 were the occupational hazards evaluation for constructive project (69.0%) , lecturing/training (55.0%) , occupational hazards monitoring (50.0%) , respectively. The high frequency used contents of GBZ/T 229.1-2010 were the fourth part "classification" (67.0%) , the fifth part "the principles of classification management" (59.0%) , annex A "the correct use instructions" (52.0%) , respectively. In the results of feasibility, scores of the fourth part "classification" , the fifth part "the principles of classification management" , annex A "the correct use instructions" were 3.07, 3.03, 3.23, respectively. The parts needed to be modified as priories were the fourth part "classification" (22.0%) , the fifth part "the principles of classification management" (13.0%) , annex A "the correct use instructions" (12.0%) . The specific survey received 15 questionnaires, with 12 from the employers and 3 from occupational health technical service organizations. The awareness rate of GBZ/T 229.1-2010 among occupational health professionals was 83.3%. Classification results in the employers were used for guidance on improvement measures (66.7%) , health surveillance

Information gathering for CLP classification

Directory of Open Access Journals (Sweden)

Ida Marcello

2011-01-01

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

Territorial pattern and classification of soils of Kryvyi Rih Iron-Ore Basin

OpenAIRE

О. О. Dolina; О. М. Smetana

2014-01-01

The authors developed the classification of soils and adapted it to the conditions of Krivyi Rih industrial region. It became the basis for determining the degree of soil cover transformation in the iron-ore basin under technogenesis. The classification represents the system of hierarchical objects of different taxonomic levels. It allows determination of relationships between objects and their properties. Researched patterns of soil cover structures’ distribution were the basis for the relev...

ASIST SIG/CR Classification Workshop 2000: Classification for User Support and Learning.

Science.gov (United States)

Soergel, Dagobert

2001-01-01

Reports on papers presented at the 62nd Annual Meeting of ASIST (American Society for Information Science and Technology) for the Special Interest Group in Classification Research (SIG/CR). Topics include types of knowledge; developing user-oriented classifications, including domain analysis; classification in the user interface; and automatic…

Couinaud's classification v.s. Cho's classification. Their feasibility in the right hepatic lobe

International Nuclear Information System (INIS)

Shioyama, Yasukazu; Ikeda, Hiroaki; Sato, Motohito; Yoshimi, Fuyo; Kishi, Kazushi; Sato, Morio; Kimura, Masashi

2008-01-01

The objective of this study was to investigate if the new classification system proposed by Cho is feasible to clinical usage comparing with the classical Couinaud's one. One hundred consecutive cases of abdominal CT were studied using a 64 or an 8 slice multislice CT and created three dimensional portal vein images for analysis by the Workstation. We applied both Cho's classification and the classical Couinaud's one for each cases according to their definitions. Three diagnostic radiologists assessed their feasibility as category one (unable to classify) to five (clear to classify with total suit with the original classification criteria). And in each cases, we tried to judge whether Cho's or the classical Couinaud' classification could more easily transmit anatomical information. Analyzers could classified portal veins clearly (category 5) in 77 to 80% of cases and clearly (category 5) or almost clearly (category 4) in 86-93% along with both classifications. In the feasibility of classification, there was no statistically significant difference between two classifications. In 15 cases we felt that using Couinaud's classification is more convenient for us to transmit anatomical information to physicians than using Cho's one, because in these cases we noticed two large portal veins ramify from right main portal vein cranialy and caudaly and then we could not classify P5 as a branch of antero-ventral segment (AVS). Conversely in 17 cases we felt Cho's classification is more convenient because we could not divide right posterior branch as P6 and P7 and in these cases the right posterior portal vein ramified to several small branches. The anterior fissure vein was clearly noticed in only 60 cases. Comparing the classical Couinaud's classification and Cho's one in feasility of classification, there was no statistically significant difference. We propose we routinely report hepatic anatomy with the classical Couinauds classification and in the preoperative cases we

Automatic parquet block sorting using real-time spectral classification

Science.gov (United States)

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.

The new UN international framework classification for reserves/resources and its relation to uranium resource classification

International Nuclear Information System (INIS)

Barthel, F.H.; Kelter, D.

2001-01-01

Resources traditionally are classified according to the degree of geological confidence and economic attractiveness. Various names are in use to describe nationally the different resource categories. Commonly, proven, probable or A+B are terms for the category RESERVES, meaning the recoverable portion of a resource under prevailing economic conditions. Since 1965 uranium resources are classified by the Nuclear Energy Agency of OECD and International Atomic Energy Agency using the terms Reasonably Assured Resources (RAR) and Estimated Additional Resources (EAR) in combination with cost categories. The definitions for RAR and EAR have been refined over the time and cost categories have been adapted according to market developments. For practical purposes a comparison of RAR and EAR with major national classification systems is provided in each of the NEA-IAEA publication on 'Uranium Resources Production and Demand' (Red Book). RAR of uranium are defined as quantities recoverable at given production costs with proven mining and processing technology, commonly RAR of the lowest cost category are referred to as Reserves. In 1992 the Committee on Energy - Working Party on Coal of the UN Economic Commission for Europe (UN/ECE) started to develop a new scheme for resource classification under the coordination of one of the authors (Kelter). The main purpose was to create an instrument permitting the classification of reserves and resources on an internationally consistent and uniform basis using market economic criteria. In April 1997 the UN/ECE approved the new 'United Nations International Framework Classification for Reserves/Resources-Solid Fuels and Mineral Commodities' at its 50th Anniversary Session. The new classification will enable the incorporation of national systems into an unified framework in order to make them compatible and comparable. Assistance will be given to economies in transition in reassessing their deposits according to market economy criteria and

A unified model for context-based behavioural modelling and classification.

CSIR Research Space (South Africa)

Dabrowski, JJ

2015-11-01

Full Text Available the continuous dynamics of a entity and incorporating various contextual elements that influence behaviour. The entity is classified according to its behaviour. Classification is expressed as a conditional probability of the entity class given its tracked...

The DSM-5: Classification and criteria changes.

Science.gov (United States)

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

2013-06-01

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) marks the first significant revision of the publication since the DSM-IV in 1994. Changes to the DSM were largely informed by advancements in neuroscience, clinical and public health need, and identified problems with the classification system and criteria put forth in the DSM-IV. Much of the decision-making was also driven by a desire to ensure better alignment with the International Classification of Diseases and its upcoming 11th edition (ICD-11). In this paper, we describe select revisions in the DSM-5, with an emphasis on changes projected to have the greatest clinical impact and those that demonstrate efforts to enhance international compatibility, including integration of cultural context with diagnostic criteria and changes that facilitate DSM-ICD harmonization. It is anticipated that this collaborative spirit between the American Psychiatric Association (APA) and the World Health Organization (WHO) will continue as the DSM-5 is updated further, bringing the field of psychiatry even closer to a singular, cohesive nosology. Copyright © 2013 World Psychiatric Association.

How is it going? Peformance assessment in major projects

DEFF Research Database (Denmark)

Maylor, Harvey; Johnson, Mark; Turner, Neil

2017-01-01

an enhanced service performance model. This was then tested using a survey and a structural equation model derived. Development of this yielded new classifications but most importantly, provided a more meaningful method for measuring the performance of operational transformation projects. Specifically......Determining the performance of a major project is a challenge for both practitioners and scholars. In the context of operational change projects the challenge is exacerbated by the service-intensive nature of the transformation, temporal disconnects between contracting and delivery and lack...... management in major projects from an OM perspective....

Evaluating heat-related mortality in Korea by objective classifications of 'air masses'

Czech Academy of Sciences Publication Activity Database

Kyselý, Jan; Huth, Radan; Kim, J.

2010-01-01

Roč. 30, č. 10 (2010), s. 1484-1501 ISSN 0899-8418 R&D Projects: GA ČR GC205/07/J044 Institutional research plan: CEZ:AV0Z30420517 Keywords : weather type classifications * air masses * biometeorology * human mortality * South Korea Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 2.479, year: 2010

Decomposition and classification of electroencephalography data

DEFF Research Database (Denmark)

Frølich, Laura

. To enforce orthonormality of projection matrices, objective functions quantifying class discrimination were optimised on a cross-product of Stiefel (orthonormal matrix) manifolds. Supervised feature extraction outperformed unsupervised methods, but the choice of supervised method mattered less. We suggested......_MARC was also used to inspect effects of artefacts on motor imagery based Brain-Computer Interfaces (BCIs) in two studies, where removing artefactual ICs had little performance impact. Finally, we investigated multi-linear classification on single trials of EEG data, proposing a rigorous optimisation approach...... completions of methods to include both PARAFAC and Tucker structures. The two structures provided similar performances, making the more interpretable PARAFAC models appealing....

Algebraic geometry and effective lagrangians

International Nuclear Information System (INIS)

Martinec, E.J.; Chicago Univ., IL

1989-01-01

N=2 supersymmetric Landau-Ginsburg fixed points describe nonlinear models whose target spaces are algebraic varieties in certain generalized projective spaces; the defining equation is precisely the zero set of the superpotential, considered as a condition in the projective space. The ADE classification of modular invariants arises as the classification of projective descriptions of P 1 ; in general, the hierarchy of fixed points is conjectured to be isomorphic to the classification of quasihomogeneous singularities. The condition of vanishing first Chern class is an integrality condition on the Virasoro central charge; the central charge is determined by the superpotential. The operator algebra is given by the algebra of Wick contractions of perturbations of the superpotential. (orig.)

Classification with support hyperplanes

NARCIS (Netherlands)

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

2006-01-01

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

Fine Resolution Probabilistic Land Cover Classification of Landscapes in the Southeastern United States

Directory of Open Access Journals (Sweden)

Joseph St. Peter

2018-03-01

Full Text Available Land cover classification provides valuable information for prioritizing management and conservation operations across large landscapes. Current regional scale land cover geospatial products within the United States have a spatial resolution that is too coarse to provide the necessary information for operations at the local and project scales. This paper describes a methodology that uses recent advances in spatial analysis software to create a land cover classification over a large region in the southeastern United States at a fine (1 m spatial resolution. This methodology used image texture metrics and principle components derived from National Agriculture Imagery Program (NAIP aerial photographic imagery, visually classified locations, and a softmax neural network model. The model efficiently produced classification surfaces at 1 m resolution across roughly 11.6 million hectares (28.8 million acres with less than 10% average error in modeled probability. The classification surfaces consist of probability estimates of 13 visually distinct classes for each 1 m cell across the study area. This methodology and the tools used in this study constitute a highly flexible fine resolution land cover classification that can be applied across large extents using standard computer hardware, common and open source software and publicly available imagery.

Classification of Flotation Frothers

Directory of Open Access Journals (Sweden)

Jan Drzymala

2018-02-01

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

Sound classification schemes in Europe - Quality classes intended for renovated housing

DEFF Research Database (Denmark)

Rasmussen, Birgit

2010-01-01

exposure in the home included in the proposed main objectives for a housing policy. In most countries in Europe, building regulations specify minimum requirements concerning acoustical conditions for new dwellings. In addition, several countries have introduced sound classification schemes with classes...... intended to reflect different levels of acoustical comfort. Consequently, acoustic requirements for a dwelling can be specified as the legal minimum requirements or as a specific class in a classification scheme. Most schemes have both higher classes than corresponding to the regulatory requirements...

European Wind Farm Project Costs History and Projections 2008 Study

Energy Technology Data Exchange (ETDEWEB)

2008-10-15

over which developers and financiers will be most focused over the development process. The concept of a power station for which the fuel is entirely free is attractive. However, this advantage is balanced by the variability of the wind which, to the uninitiated, may make an investment in such a scheme appear highly risky. In order to assess the energy production of a wind farm over the project life, it is necessary to determine accurately the long-term mean wind speed at a potential site. The prediction of energy production of a wind farm is dependent on many inputs for which the uncertainties can be objectively defined. This area therefore lends itself to a statistical assessment of the risks associated with a project. The wind analyst will review the uncertainties associated with the assessment and will obtain a 'standard deviation' for the analysis that can be applied to the central estimate. Based upon GH experience, where appropriate wind measurements have been made and diligently analysed and wind turbines with a good track record are used, it is likely that the 10-year 90% exceeding level (P90) for the wind farm production will be of the order of 10% to 15% below the central estimate (P50) of energy production for the wind farm. It is typical for an Operation and Management contract to be let to the turbine supplier for the duration of the defects liability period. Where the initial warranty period is only 2 years in term, the service period may extend to 5 years and cover unscheduled maintenance (repair) as well as routine servicing. Project Life Modern wind turbines are typically designed to be suitable for use within a specific envelope of climatic conditions over a 20 year design life. This lifetime assumption is generally supported by independent certification by a classification society such as Germanischer Lloyd or Det Norske Veritas, which has the primary purpose of ensuring that a design is compliant with specific safety requirements. Despite

Model of Numerical Spatial Classification for Sustainable Agriculture in Badung Regency and Denpasar City, Indonesia

Science.gov (United States)

Trigunasih, N. M.; Lanya, I.; Subadiyasa, N. N.; Hutauruk, J.

2018-02-01

Increasing number and activity of the population to meet the needs of their lives greatly affect the utilization of land resources. Land needs for activities of the population continue to grow, while the availability of land is limited. Therefore, there will be changes in land use. As a result, the problems faced by land degradation and conversion of agricultural land become non-agricultural. The objectives of this research are: (1) to determine parameter of spatial numerical classification of sustainable food agriculture in Badung Regency and Denpasar City (2) to know the projection of food balance in Badung Regency and Denpasar City in 2020, 2030, 2040, and 2050 (3) to specify of function of spatial numerical classification in the making of zonation model of sustainable agricultural land area in Badung regency and Denpasar city (4) to determine the appropriate model of the area to protect sustainable agricultural land in spatial and time scale in Badung and Denpasar regencies. The method used in this research was quantitative method include: survey, soil analysis, spatial data development, geoprocessing analysis (spatial analysis of overlay and proximity analysis), interpolation of raster digital elevation model data, and visualization (cartography). Qualitative methods consisted of literature studies, and interviews. The parameters observed for a total of 11 parameters Badung regency and Denpasar as much as 9 parameters. Numerical classification parameter analysis results used the standard deviation and the mean of the population data and projections relationship rice field in the food balance sheet by modelling. The result of the research showed that, the number of different numerical classification parameters in rural areas (Badung) and urban areas (Denpasar), in urban areas the number of parameters is less than the rural areas. The based on numerical classification weighting and scores generate population distribution parameter analysis results of a standard

Classification of JET Neutron and Gamma Emissivity Profiles

Science.gov (United States)

Craciunescu, T.; Murari, A.; Kiptily, V.; Vega, J.; Contributors, JET

2016-05-01

In thermonuclear plasmas, emission tomography uses integrated measurements along lines of sight (LOS) to determine the two-dimensional (2-D) spatial distribution of the volume emission intensity. Due to the availability of only a limited number views and to the coarse sampling of the LOS, the tomographic inversion is a limited data set problem. Several techniques have been developed for tomographic reconstruction of the 2-D gamma and neutron emissivity on JET. In specific experimental conditions the availability of LOSs is restricted to a single view. In this case an explicit reconstruction of the emissivity profile is no longer possible. However, machine learning classification methods can be used in order to derive the type of the distribution. In the present approach the classification is developed using the theory of belief functions which provide the support to fuse the results of independent clustering and supervised classification. The method allows to represent the uncertainty of the results provided by different independent techniques, to combine them and to manage possible conflicts.

An algebraic approach towards the classification of 2 dimensional conformal field theories

International Nuclear Information System (INIS)

Bouwknegt, P.G.

1988-01-01

This thesis treats an algebraic method for the construction of 2-dimensional conformal field theories. The method consists of the study of the representation theory of the Virasoro algebra and suitable extensions of this. The classification of 2-dimensional conformal field theories is translated into the classification of combinations of representations which satisfy certain consistence conditions (unitarity and modular invariance). For a certain class of 2-dimensional field theories, namely the one with central charge c = 1 from the theory of Kac-Moody algebra's. there exist indications, but as yet mainly hope, that this construction will finally lead to a classification of 2-dimensional conformal field theories. 182 refs.; 2 figs.; 26 tabs

Asteroid taxonomic classifications

International Nuclear Information System (INIS)

Tholen, D.J.

1989-01-01

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

New concept for condition management of plants as a result of the KUNTO project. New operations approach reduces costs

Energy Technology Data Exchange (ETDEWEB)

McNiven, U.; Tamminen, L.

1998-07-01

IVO Generation Services Ltd. has carried out a project at the IVO Naantali power plant to develop the plants condition management. The project defines critical and monitored components for each system. In addition, recommendations for further action, investment proposals and suggestions for changes in maintenance and operations practices were supplied for the various systems in the plant. The systematic approach which was the result of the projects integrated into maintenance and operations practices where data collection and analysis is part of the routine. Up-to-date data is utilized in focusing maintenance and investments, in planning and reporting functions

Transient classification for the IRIS reactor using self-organized maps built in free platform

International Nuclear Information System (INIS)

Doraskevicius Junior, Waldemar

2005-01-01

Kohonen's Self Organized Maps (SOM) were tested with data from several operational conditions of the nuclear reactor IRIS (International Reactor Innovative and Secure) to develop an effective tool in the classification and transient identification in nuclear reactors. The data were derived from 56 simulations of the operation of IRIS, from steady-state conditions to accidents. The digital system built for the tests was based on the JAVA platform for the portability and scalability, and for being one of the free development platforms. Satisfactory results of operation classification were obtained with reasonable processing time in personal computers; about two to five minutes were spent for ordination and convergence of the learning on the data base. The methodology of this work was extended to the supervision of logistics of natural gas for Brazilian pipelines, showing satisfactory results for the classification of deliveries for simultaneous measurement in several points. (author)

EC-funded project (HTR-L) for the definition of a European safety approach for HTR's

International Nuclear Information System (INIS)

Ehster, S.; Dominguez, M.T.; Coe, I.; Brinkmann, G.; Lensa, W. von; Mheen, W. van der; Alessandroni, C.; Pirson, J.

2002-01-01

The inherent safety features of the HTRs make events leading to severe core damage highly unlikely and constitute the main differentiating aspects compared to LWRs. While a known and stable regulatory environment has long been established for Light Water Reactors, a different approach is necessary for the licensing of HTR based power plants. Among the R and D projects funded by the European Commission for HTR reactors, the HTR-L project is dedicated to the definition of a common and coherent European safety approach and the identification of the main licensing issues for the licensing framework of the Modular HTRs. Other specific objectives of this project are : To develop a methodology to classify the accidental conditions; To define the preliminary requirements for the confinement of radioactive products and to assess the need for a 'conventional' containment structure; To establish a SSC (2) classification and to define the rules for equipment qualification; To identify the key issues that need to be addressed in the licensing process of the HTRs; To organize a workshop with the concerned Safety Authorities at the end of the project. This paper will explain the project objectives and its final expected outcomes. (author)

Impacts of land use/cover classification accuracy on regional climate simulations

Science.gov (United States)

Ge, Jianjun; Qi, Jiaguo; Lofgren, Brent M.; Moore, Nathan; Torbick, Nathan; Olson, Jennifer M.

2007-03-01

Land use/cover change has been recognized as a key component in global change. Various land cover data sets, including historically reconstructed, recently observed, and future projected, have been used in numerous climate modeling studies at regional to global scales. However, little attention has been paid to the effect of land cover classification accuracy on climate simulations, though accuracy assessment has become a routine procedure in land cover production community. In this study, we analyzed the behavior of simulated precipitation in the Regional Atmospheric Modeling System (RAMS) over a range of simulated classification accuracies over a 3 month period. This study found that land cover accuracy under 80% had a strong effect on precipitation especially when the land surface had a greater control of the atmosphere. This effect became stronger as the accuracy decreased. As shown in three follow-on experiments, the effect was further influenced by model parameterizations such as convection schemes and interior nudging, which can mitigate the strength of surface boundary forcings. In reality, land cover accuracy rarely obtains the commonly recommended 85% target. Its effect on climate simulations should therefore be considered, especially when historically reconstructed and future projected land covers are employed.

A Database for Climatic Conditions around Europe for Promoting GSHP Solutions

Directory of Open Access Journals (Sweden)

Michele De Carli

2018-02-01

Full Text Available Weather plays an important role for energy uses in buildings. For this reason, it is required to define the proper boundary conditions in terms of the different parameters affecting energy and comfort in buildings. They are also the basis for determining the ground temperature in different locations, as well as for determining the potential for using geothermal energy. This paper presents a database for climates in Europe that has been used in a freeware tool developed as part of the H2020 research project named “Cheap-GSHPs”. The standard Köppen-Geiger climate classification has been matched with the weather data provided by the ENERGYPLUS and METEONORM software database. The Test Reference Years of more than 300 locations have been considered. These locations have been labelled according to the degree-days for heating and cooling, as well as by the Köppen-Geiger scale. A comprehensive data set of weather conditions in Europe has been created and used as input for a GSHP sizing software, helping the user in selecting the weather conditions closest to the location of interest. The proposed method is based on lapse rates and has been tested at two locations in Switzerland and Ireland. It has been demonstrated as quite valid for the project purposes, considering the spatial distribution and density of available data and the lower computing load, in particular for locations where altitude is the main factor controlling on the temperature variations.

Activation analysis and classification to source of samples from the Kimberley Reef Conglomerates

International Nuclear Information System (INIS)

Rasmussen, S.E.

1977-01-01

Three boreholes were drilled in the west, central, and eastern sections of the Durban Roodepoort Deep Mine, and twelve distinct strata were intersected. Twenty-two samples from the three borehole cores were analysed in triplicate for twenty-six elements, and, including standards, a total of 2000 determinations were made. Statistical analysis of the results obtained for twenty-four elements shows a successful back-classification of 98 per cent, whereas, if the conglomerates or quartzites are treated separately, 100 per cent success is obtained. When the present data are used for classification of the samples from the three cores analysed during the first phase of this project, 100 per cent accuracy of classification is achieved by use of only ten selected elements. The objects of this investigation have therefore been met successfully, and extension to further strata and to sampling beyond the confines of the mine is justified [af

Classification of brain tumours using short echo time 1H MR spectra

Science.gov (United States)

Devos, A.; Lukas, L.; Suykens, J. A. K.; Vanhamme, L.; Tate, A. R.; Howe, F. A.; Majós, C.; Moreno-Torres, A.; van der Graaf, M.; Arús, C.; Van Huffel, S.

2004-09-01

The purpose was to objectively compare the application of several techniques and the use of several input features for brain tumour classification using Magnetic Resonance Spectroscopy (MRS). Short echo time 1H MRS signals from patients with glioblastomas ( n = 87), meningiomas ( n = 57), metastases ( n = 39), and astrocytomas grade II ( n = 22) were provided by six centres in the European Union funded INTERPRET project. Linear discriminant analysis, least squares support vector machines (LS-SVM) with a linear kernel and LS-SVM with radial basis function kernel were applied and evaluated over 100 stratified random splittings of the dataset into training and test sets. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of binary classifiers, while the percentage of correct classifications was used to evaluate the multiclass classifiers. The influence of several factors on the classification performance has been tested: L2- vs. water normalization, magnitude vs. real spectra and baseline correction. The effect of input feature reduction was also investigated by using only the selected frequency regions containing the most discriminatory information, and peak integrated values. Using L2-normalized complete spectra the automated binary classifiers reached a mean test AUC of more than 0.95, except for glioblastomas vs. metastases. Similar results were obtained for all classification techniques and input features except for water normalized spectra, where classification performance was lower. This indicates that data acquisition and processing can be simplified for classification purposes, excluding the need for separate water signal acquisition, baseline correction or phasing.

Evaluation of Current Approaches to Stream Classification and a Heuristic Guide to Developing Classifications of Integrated Aquatic Networks

Science.gov (United States)

Melles, S. J.; Jones, N. E.; Schmidt, B. J.

2014-03-01

Conservation and management of fresh flowing waters involves evaluating and managing effects of cumulative impacts on the aquatic environment from disturbances such as: land use change, point and nonpoint source pollution, the creation of dams and reservoirs, mining, and fishing. To assess effects of these changes on associated biotic communities it is necessary to monitor and report on the status of lotic ecosystems. A variety of stream classification methods are available to assist with these tasks, and such methods attempt to provide a systematic approach to modeling and understanding complex aquatic systems at various spatial and temporal scales. Of the vast number of approaches that exist, it is useful to group them into three main types. The first involves modeling longitudinal species turnover patterns within large drainage basins and relating these patterns to environmental predictors collected at reach and upstream catchment scales; the second uses regionalized hierarchical classification to create multi-scale, spatially homogenous aquatic ecoregions by grouping adjacent catchments together based on environmental similarities; and the third approach groups sites together on the basis of similarities in their environmental conditions both within and between catchments, independent of their geographic location. We review the literature with a focus on more recent classifications to examine the strengths and weaknesses of the different approaches. We identify gaps or problems with the current approaches, and we propose an eight-step heuristic process that may assist with development of more flexible and integrated aquatic classifications based on the current understanding, network thinking, and theoretical underpinnings.

A project by the SIDeMaST Immunopathology Group on cutaneous vasculitis.

Science.gov (United States)

Papini, M; Quaglino, P; La Placa, M; Marzano, A V

2015-04-01

Vasculitides are a challenge to the clinician, in terms of both diagnosis and therapy. Multiple classification systems have been implemented and the numerous classification schemes reflect the complexity of establishing a simple classification that could be functional for daily care. Although vasculitis classification has become increasingly elaborated, some areas remain ill defined. Some forms of vasculitis are still difficult to assign to a specific disease entity. Generally accepted operational criteria are available for many vasculitides, but for some entities there are no effective criteria. Moreover, diagnostic criteria for vasculitis with sufficient strength and/or confidence that can be universally accepted are not yet available. The need for diagnostic criteria validated and agreed upon is particularly relevant in the context of cutaneous vasculitis. The project of the SIDeMaST Italian Group of Immunopathology on cutaneous vasculitis is a national prospective observational study designed to develop and validate diagnostic criteria and to improve and validate classification criteria for cutaneous small vessel vasculitis also known as leukocytoclastic vasculitis (CLV). Primary objective of the study will also be that of developing the CUtaneous VAsculitis Severity Index (CUVASI). Secondary objectives of the project will be: 1) definition of the etiological agents that are most frequently associated with CLV; 2) search for possible correlations between causative agent and peculiar clinical and/or histopathological aspects; 3) evaluation of immunofluorescence pattern observed in this specific group of primitive cutaneous vasculitis in order to characterize the diagnostic sensitivity and specificity of this technique; 4) identification of a set of clinical investigations and laboratory tests to be performed for a correct CLV assessment. Actually 15 Italian dermatological clinics are contributing to the project and anticipated recruiting >100 patients with CLV

A review of software project testing

Directory of Open Access Journals (Sweden)

Jose Calvo-Manzano Villalón

2016-03-01

Full Text Available In this article a review of software projects based on a taxonomy project is established, allowing the development team or testing personnel to identify the tests to which the project must be subjected for validation. The taxonomy is focused on identifying software projects according to their technology. To establish the taxonomy, a development method comprised of 5 phases was applied. The developed taxonomy is comprised of 10 categories and 35 subcategories and was validated by a group of information technology (IT managers and professionals in the field of IT through the use of a survey. The results obtained from the survey are subjected to the Mann-Whitney U test, which indicates that the taxonomy is validated. The taxonomy can be implemented in development organizations with or without a testing team that provides a classification for technology projects.

Bohunice Simulator Data Collection Project

International Nuclear Information System (INIS)

Cillik, Ivan; Prochaska, Jan

2002-01-01

The paper describes the way and results of human reliability data analysis collected as a part of the Bohunice Simulator Data Collection Project (BSDCP), which was performed by VUJE Trnava, Inc. with funding support from the U.S. DOE, National Nuclear Security Administration. The goal of the project was to create a methodology for simulator data collection and analysis to support activities in probabilistic safety assessment (PSA) and human reliability assessment for Jaslovske Bohunice nuclear power plant consisting of two sets of twin units: two VVER 440/V-230 (V1) and two VVER 440/V-213 (V2) reactors. During the project training of V-2 control room crews was performed at VUJE-Trnava simulator. The simulator training and the data collection were done in parallel. The main goal of BSDCP was to collect suitable data of human errors under simulated conditions requiring the use of symptom-based emergency operating procedures (SBEOPs). The subjects of the data collection were scenario progress time data, operator errors, and real-time technological parameters. The paper contains three main parts. The first part presents preparatory work and semi-automatic computer-based methods used to collect data and to check technological parameters in order to find hidden errors of operators, to be able to retrace the course of each scenario for purposes of further analysis, and to document the whole training process. The first part gives also an overview of collected data scope, human error taxonomy, and state classifications for SBEOP instructions coding. The second part describes analytical work undertaken to describe time distribution necessary for execution of various kinds of instructions performed by operators according to the classification for coding of SBEOP instructions. It also presents the methods used for determination of probability distribution for different operator errors. Results from the data evaluation are presented in the last part of the paper. An overview of

Bohunice Simulator Data Collection Project

International Nuclear Information System (INIS)

Cillik, I.; Prochaska, J.

2002-01-01

The paper describes the way and results of human reliability data analysis collected as a part of the Bohunice Simulator Data Collection Project (BSDCP), which was performed by VUJE Trnava, Inc. with funding support from the U.S. DOE, National Nuclear Security Administration. The goal of the project was to create a methodology for simulator data collection and analysis to support activities in probabilistic safety assessment (PSA) and human reliability assessment for Jaslovske Bohunice nuclear power plant consisting of two sets of twin units: two VVER 440/V-230 (V1) and two VVER 440/V-213 (V2) reactors. During the project, training of V-2 control room crews was performed at VUJE Trnava simulator. The simulator training and the data collection were done in parallel. The main goal of BSDCP was to collect suitable data of human errors under simulated conditions requiring the use of symptom-based emergency operating procedures (SBEOPs). The subjects of the data collection were scenario progress time data, operator errors, and real-time technological parameters. The paper contains three main parts. The first part presents preparatory work and semi-automatic computer-based methods used to collect data and to check technological parameters in order to find hidden errors of operators, to be able to retrace the course of each scenario for purposes of further analysis, and to document the whole training process. The first part gives also an overview of collected data scope, human error taxonomy, and state classifications for SBEOP instructions coding. The second part describes analytical work undertaken to describe time distribution necessary for execution of various kinds of instructions performed by operators according to the classification for coding of SBEOP instructions. It also presents the methods used for determination of probability distribution for various operator errors. Results from the data evaluation are presented in the last part of the paper. An overview of

Maximum values and classifications of radionuclides

International Nuclear Information System (INIS)

1993-01-01

The primary means of controlling the use of radiation are safety license procedure and the monitoring of radiation exposure and working conditions at places of radiation use. In Section 17 of the Finnish Radiation Act (592/91) certain operations are exempted from the safety license. The exemption limits for the licensing of radioactive materials, the radiotoxicity classification of radionuclides related to such exemption limits, the annual limits on intake of radionuclides to be followed when monitoring internal radiation dose, as well as concentration limits in the breathing air are specified in the guide. Also the surface contamination limits which must be followed when monitoring working conditions at places of radiation use are presented. (4 refs., 6 tabs.)

A Novel Anti-classification Approach for Knowledge Protection.

Science.gov (United States)

Lin, Chen-Yi; Chen, Tung-Shou; Tsai, Hui-Fang; Lee, Wei-Bin; Hsu, Tien-Yu; Kao, Yuan-Hung

2015-10-01

Classification is the problem of identifying a set of categories where new data belong, on the basis of a set of training data whose category membership is known. Its application is wide-spread, such as the medical science domain. The issue of the classification knowledge protection has been paid attention increasingly in recent years because of the popularity of cloud environments. In the paper, we propose a Shaking Sorted-Sampling (triple-S) algorithm for protecting the classification knowledge of a dataset. The triple-S algorithm sorts the data of an original dataset according to the projection results of the principal components analysis so that the features of the adjacent data are similar. Then, we generate noise data with incorrect classes and add those data to the original dataset. In addition, we develop an effective positioning strategy, determining the added positions of noise data in the original dataset, to ensure the restoration of the original dataset after removing those noise data. The experimental results show that the disturbance effect of the triple-S algorithm on the CLC, MySVM, and LibSVM classifiers increases when the noise data ratio increases. In addition, compared with existing methods, the disturbance effect of the triple-S algorithm is more significant on MySVM and LibSVM when a certain amount of the noise data added to the original dataset is reached.

On classification of N=2 supersymmetric theories

International Nuclear Information System (INIS)

Cecotti, S.; Vafa, C.

1993-01-01

We find a relation between the spectrum of solitons of massive N=2 quantum field theories in d=2 and the scaling dimensions of chiral fields at the conformal point. The condition that the scaling dimensions be real imposes restrictions on the soliton numbers and leads to a classification program for symmetric N=2 conformal theories and their massive deformations in terms of a suitable generalization of Dynkin diagrams (which coincides with the A-D-E Dynkin diagrams for minimal models). The Landau-Ginzburg theories are a proper subset of this classification. In the particular case of LG theories we relate the soliton numbers with intersection of vanishing cycles of the corresponding singularity; the relation between soliton numbers and the scaling dimensions in this particular case is a well known application of Picard-Lefschetz theory. (orig.)

Classification Schedules as Subject Enhancement in Online Catalogs. A Review of a Conference Sponsored by Forest Press, the OCLC Online Computer Library Center, and the Council on Library Resources.

Science.gov (United States)

Mandel, Carol A.

This paper presents a synthesis of the ideas and issues developed at a conference convened to review the results of the Dewey Decimal Classification Online Project and explore the potential for future use of the Dewey Decimal Classification (DDC) and Library of Congress Classification (LCC) schedules in online library catalogs. Conference…

Application of wavelet transform for PDZ domain classification.

Directory of Open Access Journals (Sweden)

Khaled Daqrouq

Full Text Available PDZ domains have been identified as part of an array of signaling proteins that are often unrelated, except for the well-conserved structural PDZ domain they contain. These domains have been linked to many disease processes including common Avian influenza, as well as very rare conditions such as Fraser and Usher syndromes. Historically, based on the interactions and the nature of bonds they form, PDZ domains have most often been classified into one of three classes (class I, class II and others - class III, that is directly dependent on their binding partner. In this study, we report on three unique feature extraction approaches based on the bigram and trigram occurrence and existence rearrangements within the domain's primary amino acid sequences in assisting PDZ domain classification. Wavelet packet transform (WPT and Shannon entropy denoted by wavelet entropy (WE feature extraction methods were proposed. Using 115 unique human and mouse PDZ domains, the existence rearrangement approach yielded a high recognition rate (78.34%, which outperformed our occurrence rearrangements based method. The recognition rate was (81.41% with validation technique. The method reported for PDZ domain classification from primary sequences proved to be an encouraging approach for obtaining consistent classification results. We anticipate that by increasing the database size, we can further improve feature extraction and correct classification.

Annotated Bibliography for the DEWPOINT project

Energy Technology Data Exchange (ETDEWEB)

Oehmen, Christopher S.

2009-04-21

This bibliography covers aspects of the Detection and Early Warning of Proliferation from Online INdicators of Threat (DEWPOINT) project including 1) data management and querying, 2) baseline and advanced methods for classifying free text, and 3) algorithms to achieve the ultimate goal of inferring intent from free text sources. Metrics for assessing the quality and correctness of classification are addressed in the second group. Data management and querying include methods for efficiently storing, indexing, searching, and organizing the data we expect to operate on within the DEWPOINT project.

Final Report for Project. Quark matter under extreme conditions

Energy Technology Data Exchange (ETDEWEB)

Incera, Vivian [Univ. of Texas, El Paso, TX (United States); Ferrer, Efrain [Univ. of Texas, El Paso, TX (United States)

2015-12-31

The results obtained in the two years of the grant have served to shine new light on several important questions about the phases of quantum chromodynamics (QCD) under extreme conditions that include quark matter at high density, as well quark-gluon plasma at high temperatures, both in the presence of strong magnetic fields. The interest in including an external magnetic field on these studies is motivated by the generation of large magnetic fields in off-central heavy-ion collisions and by their common presence in astrophysical compact objects, the two scenarios where the physics of quark matter becomes relevant. The tasks carried out in this DOE project led us, among other things, to discover the first connection between the physics of very dense quark matter and novel materials as for instance topological insulators and Weyl semimetals; they allowed us to find a physical explanation for and a solution to a standing puzzle in the apparent effect of a magnetic field on the critical temperature of the QCD chiral transition; and they led us to establish by the first time that the core of the observed two-solar-mass neutron stars could be made up of quark matter in certain inhomogeneous chiral phases in a magnetic field and that this was consistent with current astrophysical observations. A major goal established by the Nuclear Science Advisory committee in its most recent report “Reaching for the Horizon” has been “to truly understand how nuclei and strongly interacting matter in all its forms behave and can predict their behavior in new settings.” The results found in this DOE project have all contributed to address this goal, and thus they are important for advancing fundamental knowledge in the area of nuclear physics and for enhancing our understanding of the role of strong magnetic fields in the two settings where they are most relevant, neutron stars and heavy-ion collisions.

Final Report for Project. Quark matter under extreme conditions

International Nuclear Information System (INIS)

Incera, Vivian; Ferrer, Efrain

2015-01-01

The results obtained in the two years of the grant have served to shine new light on several important questions about the phases of quantum chromodynamics (QCD) under extreme conditions that include quark matter at high density, as well quark-gluon plasma at high temperatures, both in the presence of strong magnetic fields. The interest in including an external magnetic field on these studies is motivated by the generation of large magnetic fields in off-central heavy-ion collisions and by their common presence in astrophysical compact objects, the two scenarios where the physics of quark matter becomes relevant. The tasks carried out in this DOE project led us, among other things, to discover the first connection between the physics of very dense quark matter and novel materials as for instance topological insulators and Weyl semimetals; they allowed us to find a physical explanation for and a solution to a standing puzzle in the apparent effect of a magnetic field on the critical temperature of the QCD chiral transition; and they led us to establish by the first time that the core of the observed two-solar-mass neutron stars could be made up of quark matter in certain inhomogeneous chiral phases in a magnetic field and that this was consistent with current astrophysical observations. A major goal established by the Nuclear Science Advisory committee in its most recent report 'Reaching for the Horizon' has been 'to truly understand how nuclei and strongly interacting matter in all its forms behave and can predict their behavior in new settings.' The results found in this DOE project have all contributed to address this goal, and thus they are important for advancing fundamental knowledge in the area of nuclear physics and for enhancing our understanding of the role of strong magnetic fields in the two settings where they are most relevant, neutron stars and heavy-ion collisions.

[The physiological classification of human thermal states under high environmental temperatures].

Science.gov (United States)

Bobrov, A F; Kuznets, E I

1995-01-01

The paper deals with the physiological classification of human thermal states in a hot environment. A review of the basic systems of classifications of thermal states is given, their main drawbacks are discussed. On the basis of human functional state research in a broad range of environmental temperatures the system of evaluation and classification of human thermal states is proposed. New integral one-dimensional multi-parametric criteria for evaluation are used. For the development of these criteria methods of factor, cluster and canonical correlation analyses are applied. Stochastic nomograms capable of identification of human thermal state for different intensity of influence are given. In this case evaluation of intensity is estimated according to one-dimensional criteria taking into account environmental temperature, physical load and time of man's staying in overheating conditions.

32 CFR 2001.15 - Classification guides.

Science.gov (United States)

2010-07-01

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

FACET CLASSIFICATIONS OF E-LEARNING TOOLS

Directory of Open Access Journals (Sweden)

Olena Yu. Balalaieva

2013-12-01

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

Vegetation of Europe: hierarchical floristic classification system of vascular plant, bryophyte, lichen, and algal communities

Czech Academy of Sciences Publication Activity Database

Mucina, L.; Bültmann, H.; Dierssen, K.; Theurillat, J. P.; Raus, T.; Carni, A.; Šumberová, Kateřina; Willner, W.; Dengler, J.; Gavilán García, R.; Chytrý, M.; Hájek, M.; Di Pietro, R.; Iakushenko, D.; Pallas, J.; Daniëls, F. J. A.; Bergmeier, E.; Santos Guerra, A.; Ermakov, N.; Valachovič, M.; Schaminée, J.H.J.; Lysenko, T.; Didukh, Y. P.; Pignatti, S.; Rodwell, J. S.; Capelo, J.; Weber, H. E.; Solomeshch, A.; Dimopoulos, P.; Aguiar, C.; Hennekens, S. M.; Tichý, L.

2016-01-01

Roč. 19, Suppl. 1 (2016), s. 3-264 ISSN 1402-2001 R&D Projects: GA ČR GB14-36079G Institutional support: RVO:67985939 Keywords : Europe * syntaxonomy * vegetation classification Subject RIV: EH - Ecology, Behaviour Impact factor: 2.474, year: 2016

Formalized classification of species-poor vegetation: a proposal of a consistent protocol for aquatic vegetation

Czech Academy of Sciences Publication Activity Database

Landucci, F.; Tichý, L.; Šumberová, Kateřina; Chytrý, M.

2015-01-01

Roč. 26, č. 4 (2015), s. 791-803 ISSN 1100-9233 R&D Projects: GA ČR GB14-36079G Institutional support: RVO:67985939 Keywords : vegetation classification * vegetation database * Coctail method Subject RIV: EF - Botanics Impact factor: 3.151, year: 2015

Impact of job classification on employment of seasonal workers

Directory of Open Access Journals (Sweden)

Zoran Pandža

2011-07-01

Full Text Available The paper aims to improve the existing work organization, thus improving success of business process and ultimately reducing company costs. A change in organizational structure is proposed with the objective of achieving better and more efficient use of resources available within the company. Since the existing organization and classification of jobs does not meet the requirements of the age we live in, there is a need for new classification which would address many changes that have taken place over the years, including changes that are yet to be made for the purpose of further development of the company. Organization and management of the company as well as reorganization and implementation of a new classification is necessary to make it possible for the company to perform regular adjustment of business activities, because the conditions in which the company operates are changing fast. New classification would not actually change the number of sectors. Rather, existing personnel would be allocated in a better way, which would result in reduced needs for seasonal work force. In the process of defining the new organizational structure, one should consider the type, way of doing business, structural variables (division of labour, unity of command, authority and responsibility, span of control, division in business units, etc.. Expected results include improved organization and classification of jobs, improved quality of work, speed and efficiency. It should result in a company organized according to standards that are adjusted to modern times.

Maxillectomy defects: a suggested classification scheme.

Science.gov (United States)

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

2013-06-01

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

Constructing criticality by classification

DEFF Research Database (Denmark)

Machacek, Erika

2017-01-01

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

Hierarchical multi-scale classification of nearshore aquatic habitats of the Great Lakes: Western Lake Erie

Science.gov (United States)

McKenna, J.E.; Castiglione, C.

2010-01-01

Classification is a valuable conservation tool for examining natural resource status and problems and is being developed for coastal aquatic habitats. We present an objective, multi-scale hydrospatial framework for nearshore areas of the Great Lakes. The hydrospatial framework consists of spatial units at eight hierarchical scales from the North American Continent to the individual 270-m spatial cell. Characterization of spatial units based on fish abundance and diversity provides a fish-guided classification of aquatic areas at each spatial scale and demonstrates how classifications may be generated from that framework. Those classification units then provide information about habitat, as well as biotic conditions, which can be compared, contrasted, and hierarchically related spatially. Examples within several representative coastal or open water zones of the Western Lake Erie pilot area highlight potential application of this classification system to management problems. This classification system can assist natural resource managers with planning and establishing priorities for aquatic habitat protection, developing rehabilitation strategies, or identifying special management actions.

Optical beam classification using deep learning: a comparison with rule- and feature-based classification

Science.gov (United States)

Alom, Md. Zahangir; Awwal, Abdul A. S.; Lowe-Webb, Roger; Taha, Tarek M.

2017-08-01

Deep-learning methods are gaining popularity because of their state-of-the-art performance in image classification tasks. In this paper, we explore classification of laser-beam images from the National Ignition Facility (NIF) using a novel deeplearning approach. NIF is the world's largest, most energetic laser. It has nearly 40,000 optics that precisely guide, reflect, amplify, and focus 192 laser beams onto a fusion target. NIF utilizes four petawatt lasers called the Advanced Radiographic Capability (ARC) to produce backlighting X-ray illumination to capture implosion dynamics of NIF experiments with picosecond temporal resolution. In the current operational configuration, four independent short-pulse ARC beams are created and combined in a split-beam configuration in each of two NIF apertures at the entry of the pre-amplifier. The subaperture beams then propagate through the NIF beampath up to the ARC compressor. Each ARC beamlet is separately compressed with a dedicated set of four gratings and recombined as sub-apertures for transport to the parabola vessel, where the beams are focused using parabolic mirrors and pointed to the target. Small angular errors in the compressor gratings can cause the sub-aperture beams to diverge from one another and prevent accurate alignment through the transport section between the compressor and parabolic mirrors. This is an off-normal condition that must be detected and corrected. The goal of the off-normal check is to determine whether the ARC beamlets are sufficiently overlapped into a merged single spot or diverged into two distinct spots. Thus, the objective of the current work is three-fold: developing a simple algorithm to perform off-normal classification, exploring the use of Convolutional Neural Network (CNN) for the same task, and understanding the inter-relationship of the two approaches. The CNN recognition results are compared with other machine-learning approaches, such as Deep Neural Network (DNN) and Support

12 CFR 403.4 - Derivative classification.

Science.gov (United States)

2010-01-01

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

Rehabilitation of life conditions in territories contaminated by Chernobyl accident. ETHOS project in Ukraine

International Nuclear Information System (INIS)

Rolevitch, I.; Pachkievitch, V.; Petroviet, V.; Lepicard, S.; Livolsi, P.; Lochard, J.; Schneider, T.; Ollagnon, H.; Pupin, V.; Heriard-Dubreuil, G.; Girard, P.; Guyonnet, J.F.; Le Cardinal, G.; Monroy, M.; Pena-Vega, A.; Rigby, J.

1999-01-01

This article presents the ETHOS project funded by European Union and whose aim is to stimulate a lasting rehabilitation of life conditions in the territories contaminated by Chernobyl nuclear accident. The daily life of people living in the contaminated regions has been affected not only on medical aspect but also on economic, ecological, social and cultural aspects. The strict regulations imposed by radiation protection authorities have been a major element to the degradation of the standard of living. ETHOS project is based on a cooperation between the authorities and the inhabitants and on a strong motivation of the people, for instance in the Olmany village 6 work groups have been organized around themes such as: the improvement of the quality of the milk and meat produced in the village, the radiation protection of children, the practical basics to know when living in a contaminated area, and the right management of home wastes like ashes that are particularly contaminated. (A.C.)

Robust tissue classification for reproducible wound assessment in telemedicine environments

Science.gov (United States)

Wannous, Hazem; Treuillet, Sylvie; Lucas, Yves

2010-04-01

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

Spectrum of gluten-related disorders: consensus on new nomenclature and classification

Directory of Open Access Journals (Sweden)

Sapone Anna

2012-02-01

Full Text Available Abstract A decade ago celiac disease was considered extremely rare outside Europe and, therefore, was almost completely ignored by health care professionals. In only 10 years, key milestones have moved celiac disease from obscurity into the popular spotlight worldwide. Now we are observing another interesting phenomenon that is generating great confusion among health care professionals. The number of individuals embracing a gluten-free diet (GFD appears much higher than the projected number of celiac disease patients, fueling a global market of gluten-free products approaching $2.5 billion (US in global sales in 2010. This trend is supported by the notion that, along with celiac disease, other conditions related to the ingestion of gluten have emerged as health care concerns. This review will summarize our current knowledge about the three main forms of gluten reactions: allergic (wheat allergy, autoimmune (celiac disease, dermatitis herpetiformis and gluten ataxia and possibly immune-mediated (gluten sensitivity, and also outline pathogenic, clinical and epidemiological differences and propose new nomenclature and classifications.

Supernova Photometric Lightcurve Classification

Science.gov (United States)

Zaidi, Tayeb; Narayan, Gautham

2016-01-01

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

45 CFR 601.5 - Derivative classification.

Science.gov (United States)

2010-10-01

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

Management of Innovative Projects for Ensuring the Economic Safety in the Conditions of Integration of Economies into the World Economy

Directory of Open Access Journals (Sweden)

T. K. Usmanova

2017-01-01

Full Text Available Purpose: the aim of the article is to reveal problems and prospects, formulate economic security within the framework of innovation projects management, plan technologies in the context of integrating economies into the world economy, identify opportunities for forming, organizing, financing, managing priority economic directions. The subject is the management of innovative projects to ensure the economic security of Russian regions. The relevance of the chosen topic is due to the study of the features of the current state and the problems of the formation of economic security, the development of innovative design solutions in the context of integrating economies into the world economy. Ensuring the economic security of the regions of Russia directly depends on the introduction of innovative technologies and project management in the sectors of the national economy of Russia. Methods: the methodology of the solution of objectives is based on usage of a method of dialectic research, methods of the economic analysis, forecasting, the situational and systemic analysis, expert evaluations and the analysis of empirical data. Hypothesis. Ensuring an economic safety requires formation of innovative solutions, change of the current legislation within the Strategy of social and economic development in the conditions of integration of economies into the world economy. Results: the practical significance of the work is to identify the interrelationship between the development processes of innovative projects that ensure the economic security of the regions of Russia within the framework of regulating the current legislation, forecasting effective economic activity within the framework of the New Industrialization Strategy, selecting optimal project planning models to ensure the country's economic security and competitiveness in the conditions of integration Economies into the world economy. Conclusions and Relevance: in the conditions of integration of

Learning features for tissue classification with the classification restricted Boltzmann machine

DEFF Research Database (Denmark)

van Tulder, Gijs; de Bruijne, Marleen

2014-01-01

Performance of automated tissue classification in medical imaging depends on the choice of descriptive features. In this paper, we show how restricted Boltzmann machines (RBMs) can be used to learn features that are especially suited for texture-based tissue classification. We introduce the convo...... outperform conventional RBM-based feature learning, which is unsupervised and uses only a generative learning objective, as well as often-used filter banks. We show that a mixture of generative and discriminative learning can produce filters that give a higher classification accuracy....

An Efficient Optimization Method for Solving Unsupervised Data Classification Problems

Directory of Open Access Journals (Sweden)

Parvaneh Shabanzadeh

2015-01-01

Full Text Available Unsupervised data classification (or clustering analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has its own advantages, limitations, and deficiencies. Hence, research for novel and effective approaches for unsupervised data classification is still active. In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species. Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them. To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms. Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.

Automatic Parallelization Tool: Classification of Program Code for Parallel Computing

Directory of Open Access Journals (Sweden)

Mustafa Basthikodi

2016-04-01

Full Text Available Performance growth of single-core processors has come to a halt in the past decade, but was re-enabled by the introduction of parallelism in processors. Multicore frameworks along with Graphical Processing Units empowered to enhance parallelism broadly. Couples of compilers are updated to developing challenges forsynchronization and threading issues. Appropriate program and algorithm classifications will have advantage to a great extent to the group of software engineers to get opportunities for effective parallelization. In present work we investigated current species for classification of algorithms, in that related work on classification is discussed along with the comparison of issues that challenges the classification. The set of algorithms are chosen which matches the structure with different issues and perform given task. We have tested these algorithms utilizing existing automatic species extraction toolsalong with Bones compiler. We have added functionalities to existing tool, providing a more detailed characterization. The contributions of our work include support for pointer arithmetic, conditional and incremental statements, user defined types, constants and mathematical functions. With this, we can retain significant data which is not captured by original speciesof algorithms. We executed new theories into the device, empowering automatic characterization of program code.

ADHD classification using bag of words approach on network features

Science.gov (United States)

Solmaz, Berkan; Dey, Soumyabrata; Rao, A. Ravishankar; Shah, Mubarak

2012-02-01

Attention Deficit Hyperactivity Disorder (ADHD) is receiving lots of attention nowadays mainly because it is one of the common brain disorders among children and not much information is known about the cause of this disorder. In this study, we propose to use a novel approach for automatic classification of ADHD conditioned subjects and control subjects using functional Magnetic Resonance Imaging (fMRI) data of resting state brains. For this purpose, we compute the correlation between every possible voxel pairs within a subject and over the time frame of the experimental protocol. A network of voxels is constructed by representing a high correlation value between any two voxels as an edge. A Bag-of-Words (BoW) approach is used to represent each subject as a histogram of network features; such as the number of degrees per voxel. The classification is done using a Support Vector Machine (SVM). We also investigate the use of raw intensity values in the time series for each voxel. Here, every subject is represented as a combined histogram of network and raw intensity features. Experimental results verified that the classification accuracy improves when the combined histogram is used. We tested our approach on a highly challenging dataset released by NITRC for ADHD-200 competition and obtained promising results. The dataset not only has a large size but also includes subjects from different demography and edge groups. To the best of our knowledge, this is the first paper to propose BoW approach in any functional brain disorder classification and we believe that this approach will be useful in analysis of many brain related conditions.

Synoptic-climatological evaluation of the classifications of atmospheric circulation patterns over Europe

Czech Academy of Sciences Publication Activity Database

Huth, Radan; Beck, Ch.; Kučerová, Monika

2016-01-01

Roč. 36, č. 7 (2016), s. 2710-2726 ISSN 0899-8418 R&D Projects: GA ČR(CZ) GPP209/12/P811; GA MŠk OC 115 Institutional support: RVO:68378289 Keywords : circulation types * classification * synoptic climatology * COST733 Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 3.760, year: 2016 http://onlinelibrary.wiley.com/doi/10.1002/joc.4546/full

Classification of smooth Fano polytopes

DEFF Research Database (Denmark)

Øbro, Mikkel

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

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

Science.gov (United States)

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

2015-12-01

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

Tremor entities and their classification: an update.

Science.gov (United States)

Gövert, Felix; Deuschl, Günther

2015-08-01

This review focuses on important new findings in the field of tremor and illustrates the consequences for the current definition and classification of tremor. Since 1998 when the consensus criteria for tremor were proposed, new variants of tremors and new diagnostic methods were discovered that have changed particularly the concepts of essential tremor and dystonic tremor. Accumulating evidence exists that essential tremor is not a single entity rather different conditions that share the common symptom action tremor without other major abnormalities. Tremor is a common feature in patients with adult-onset focal dystonia and may involve several different body parts and forms of tremor. Recent advances, in particular, in the field of genetics, suggest that dystonic tremor may even be present without overt dystonia. Monosymptomatic asymmetric rest and postural tremor has been further delineated, and apart from tremor-dominant Parkinson's disease, there are several rare conditions including rest and action tremor with normal dopamine transporter imaging (scans without evidence of dopaminergic deficit) and essential tremor with tremor at rest. Increasing knowledge in the last decades changed the view on tremors and highlights several caveats in the current tremor classification. Given the ambiguous assignment between tremor phenomenology and tremor etiology, a more cautious definition of tremors on the basis of clinical assessment data is needed.

Fear conditioning leads to alteration in specific genes expression in cortical and thalamic neurons that project to the lateral amygdala.

Science.gov (United States)

Katz, Ira K; Lamprecht, Raphael

2015-02-01

RNA transcription is needed for memory formation. However, the ability to identify genes whose expression is altered by learning is greatly impaired because of methodological difficulties in profiling gene expression in specific neurons involved in memory formation. Here, we report a novel approach to monitor the expression of genes after learning in neurons in specific brain pathways needed for memory formation. In this study, we aimed to monitor gene expression after fear learning. We retrogradely labeled discrete thalamic neurons that project to the lateral amygdala (LA) of rats. The labeled neurons were dissected, using laser microdissection microscopy, after fear conditioning learning or unpaired training. The RNAs from the dissected neurons were subjected to microarray analysis. The levels of selected RNAs detected by the microarray analysis to be altered by fear conditioning were also assessed by nanostring analysis. We observed that the expression of genes involved in the regulation of translation, maturation and degradation of proteins was increased 6 h after fear conditioning compared to unpaired or naïve trained rats. These genes were not expressed 24 h after training or in cortical neurons that project to the LA. The expression of genes involved in transcription regulation and neuronal development was altered after fear conditioning learning in the cortical-LA pathway. The present study provides key information on the identity of genes expressed in discrete thalamic and cortical neurons that project to the LA after fear conditioning. Such an approach could also serve to identify gene products as targets for the development of a new generation of therapeutic agents that could be aimed to functionally identified brain circuits to treat memory-related disorders. © 2014 International Society for Neurochemistry.

Standard characterization of phosphate rock samples from the FAO/IAEA phosphate project

International Nuclear Information System (INIS)

Binh, Truong; Zapata, F.

2002-01-01

Phosphate rocks (PR) are phosphate-bearing minerals that vary widely in their inherent characteristics and consequently their agronomic potential. In the framework of a FAO/IAEA networked research project, the evaluation of the agronomic effectiveness of natural and modified PR products under a variety of soil climate and crop management conditions was carried out. The characterization of phosphate rocks is the first and essential step in evaluating their suitability for direct application. If several PR sources are utilized, standardized methods should be used for comparison purposes to determine their agronomic potential. This paper describes the standard characterization of phosphate rock products utilized in the project, in particular the mineralogical and crystallographic analyses, physical analyses, chemical composition and solubility in conventional reagents. A total of 28 phosphate rock samples from 15 countries were collected and analyzed in specialized laboratories. The data on mineralogy, chemical composition and solubility in conventional reagents are closely interrelated. An arbitrary classification of the reactivity of the PR samples was made based on the solubility indices in conventional reagents. On another hand, the results of the crystallographic parameters, calculated indices of absolute solubility, specific surface and porosity reflect the variability of the physical state and the sample pre-conditioning treatment of the analyzed products. A proper characterization of phosphate rock samples should provide the maximum of basic information that can be obtained in a cost-effective manner in normal chemical laboratories. Based on the results of this characterization, the following determinations are recommended: a description of the sample, major elemental (total P, Ca, Mg) composition, solubility in conventional reagents (neutral ammonium citrate, citric and formic acid) and particle size analysis. The classification of PR samples for direct

Maximum mutual information regularized classification

KAUST Repository

Wang, Jim Jing-Yan

2014-09-07

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

Maximum mutual information regularized classification

KAUST Repository

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

2014-01-01

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

A project management quality cost information system for the construction industry

OpenAIRE

Love, PED; Irani, Z

2003-01-01

A prototype Project Management Quality Cost System (PROMQACS) was developed to determine quality costs in construction projects. The structure and information requirements that are needed to provide a classification system of quality costs were identified and discussed. The developed system was tested and implemented in two case study construction projects to determine the information and management issues needed to develop PROMQACS into a software program. In addition, the system was used to...

Categorization of allergic disorders in the new World Health Organization International Classification of Diseases.

Science.gov (United States)

Tanno, Luciana Kase; Calderon, Moises A; Goldberg, Bruce J; Akdis, Cezmi A; Papadopoulos, Nikolaos G; Demoly, Pascal

2014-01-01

Although efforts to improve the classification of hypersensitivity/allergic diseases have been made, they have not been considered a top-level category in the International Classification of Diseases (ICD)-10 and still are not in the ICD-11 beta phase linearization. ICD-10 is the most used classification system by the allergy community worldwide but it is not considered as appropriate for clinical practice. The Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) on the other hand contains a tightly integrated classification of hypersensitivity/allergic disorders based on the EAACI/WAO nomenclature and the World Health Organization (WHO) may plan to align ICD-11 with SNOMED CT so that they share a common ontological basis. With the aim of actively supporting the ongoing ICD-11 revision and the optimal practice of Allergology, we performed a careful comparison of ICD-10 and 11 beta phase linearization codes to identify gaps, areas of regression in allergy coding and possibly reach solutions, in collaboration with committees in charge of the ICD-11 revision. We have found a significant degree of misclassification of terms in the allergy-related hierarchies. This stems not only from unclear definitions of these conditions but also the use of common names that falsely imply allergy. The lack of understanding of the immune mechanisms underlying some of the conditions contributes to the difficulty in classification. More than providing data to support specific changes into the ongoing linearization, these results highlight the need for either a new chapter entitled Hypersensitivity/Allergic Disorders as in SNOMED CT or a high level structure in the Immunology chapter in order to make classification more appropriate and usable.

An Initial Classification of Neotropical Water Mites (Acari: Hydrachnidia Based on Habitat Preferences

Directory of Open Access Journals (Sweden)

Hugo R. Fernández

2011-01-01

Full Text Available Existing classifications of benthic and interstitial freshwater invertebrates are described and discussed. A classification is proposed for southern neotropical (south of latitude S 15 water mites in relation to their life style and habitat preferences. The classification includes planktonic, superficial, benthic, thermal, and subterranean forms. The diversity of the Hydrachnidia family and genera (22 families, 97 genera, and 521 species is then analyzed using the new classification. Ubiquitous stygobites deserve special consideration because they move through ecotone zones and tolerate extreme conditions. Water mite communities from a north-western Argentinean stream were first described using a surber net and consequently considered as benthic. Nineteen Hydrachnidia species (from benthic to stygobite were collected and classified. The vertical distribution observed during the year confirmed the permanent presence of benthic Hydrachnidia, even during the first flood, which is of special importance in running waters. The functional classification we propose will facilitate comparison of fauna from different areas that have different faunistic composition but may have similar functional distribution.

Classification of EEG signals using a genetic-based machine learning classifier.

Science.gov (United States)

Skinner, B T; Nguyen, H T; Liu, D K

2007-01-01

This paper investigates the efficacy of the genetic-based learning classifier system XCS, for the classification of noisy, artefact-inclusive human electroencephalogram (EEG) signals represented using large condition strings (108bits). EEG signals from three participants were recorded while they performed four mental tasks designed to elicit hemispheric responses. Autoregressive (AR) models and Fast Fourier Transform (FFT) methods were used to form feature vectors with which mental tasks can be discriminated. XCS achieved a maximum classification accuracy of 99.3% and a best average of 88.9%. The relative classification performance of XCS was then compared against four non-evolutionary classifier systems originating from different learning techniques. The experimental results will be used as part of our larger research effort investigating the feasibility of using EEG signals as an interface to allow paralysed persons to control a powered wheelchair or other devices.

Cluster Based Text Classification Model

DEFF Research Database (Denmark)

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

2011-01-01

We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

A classification scheme for LWR fuel assemblies

Energy Technology Data Exchange (ETDEWEB)

Moore, R.S.; Williamson, D.A.; Notz, K.J.

1988-11-01

With over 100 light water nuclear reactors operating nationwide, representing designs by four primary vendors, and with reload fuel manufactured by these vendors and additional suppliers, a wide variety of fuel assembly types are in existence. At Oak Ridge National Laboratory, both the Systems Integration Program and the Characteristics Data Base project required a classification scheme for these fuels. This scheme can be applied to other areas and is expected to be of value to many Office of Civilian Radioactive Waste Management programs. To develop the classification scheme, extensive information on the fuel assemblies that have been and are being manufactured by the various nuclear fuel vendors was compiled, reviewed, and evaluated. It was determined that it is possible to characterize assemblies in a systematic manner, using a combination of physical factors. A two-stage scheme was developed consisting of 79 assembly types, which are grouped into 22 assembly classes. The assembly classes are determined by the general design of the reactor cores in which the assemblies are, or were, used. The general BWR and PWR classes are divided differently but both are based on reactor core configuration. 2 refs., 15 tabs.

A classification scheme for LWR fuel assemblies

International Nuclear Information System (INIS)

Moore, R.S.; Williamson, D.A.; Notz, K.J.

1988-11-01

With over 100 light water nuclear reactors operating nationwide, representing designs by four primary vendors, and with reload fuel manufactured by these vendors and additional suppliers, a wide variety of fuel assembly types are in existence. At Oak Ridge National Laboratory, both the Systems Integration Program and the Characteristics Data Base project required a classification scheme for these fuels. This scheme can be applied to other areas and is expected to be of value to many Office of Civilian Radioactive Waste Management programs. To develop the classification scheme, extensive information on the fuel assemblies that have been and are being manufactured by the various nuclear fuel vendors was compiled, reviewed, and evaluated. It was determined that it is possible to characterize assemblies in a systematic manner, using a combination of physical factors. A two-stage scheme was developed consisting of 79 assembly types, which are grouped into 22 assembly classes. The assembly classes are determined by the general design of the reactor cores in which the assemblies are, or were, used. The general BWR and PWR classes are divided differently but both are based on reactor core configuration. 2 refs., 15 tabs

Social cost in construction projects

International Nuclear Information System (INIS)

Çelik, Tolga; Kamali, Saeed; Arayici, Yusuf

2017-01-01

Despite the fact that completion of construction projects has a direct positive impact on the growth of national and local economies as well as humans' wellbeing, construction projects, especially in the urban areas, generate serious environmental nuisances for the adjacent residents and have unintentional adverse impacts on their surrounding environment. Construction causative adverse impacts on the neighbouring communities are known as the social costs. This study aims to present a state-of-the-art overview of social costs in construction industry in terms of definition, consideration, classification and quantification. Furthermore, it is aimed to bring the construction social cost phenomenon for the agenda of Environmental Impact Assessors.

Social cost in construction projects

Energy Technology Data Exchange (ETDEWEB)

Çelik, Tolga, E-mail: tolga.celik@emu.edu.tr [Department of Civil Engineering, Eastern Mediterranean University, Famagusta, T.R. North Cyprus, Via Mersin 10 (Turkey); Kamali, Saeed, E-mail: saeedkamali2002@gmail.com [Civil Engineering Department, Middle East Technical University, 06800 Ankara (Turkey); Arayici, Yusuf, E-mail: yusuf.arayici@hku.edu.tr [Department of Civil Engineering, Hasan Kalyoncu University, Gaziantep (Turkey)

2017-05-15

Despite the fact that completion of construction projects has a direct positive impact on the growth of national and local economies as well as humans' wellbeing, construction projects, especially in the urban areas, generate serious environmental nuisances for the adjacent residents and have unintentional adverse impacts on their surrounding environment. Construction causative adverse impacts on the neighbouring communities are known as the social costs. This study aims to present a state-of-the-art overview of social costs in construction industry in terms of definition, consideration, classification and quantification. Furthermore, it is aimed to bring the construction social cost phenomenon for the agenda of Environmental Impact Assessors.

Classification of weed vegetation of arable land in the Czech Republic and Slovakia

Czech Academy of Sciences Publication Activity Database

Lososová, Z.; Chytrý, M.; Cimalová, Š.; Otýpková, Z.; Pyšek, Petr; Tichý, L.

2006-01-01

Roč. 41, - (2006), s. 259-273 ISSN 1211-9520 R&D Projects: GA ČR(CZ) GA526/00/1443; GA ČR(CZ) GA206/05/0020 Institutional research plan: CEZ:AV0Z60050516 Keywords : weed vegetation * phytosociological classification * Česko a Slovensko Subject RIV: EF - Botanics Impact factor: 1.196, year: 2006

Ontologies vs. Classification Systems

DEFF Research Database (Denmark)

Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

2009-01-01

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

A study on the validity of strategic classification processes

International Nuclear Information System (INIS)

Tae, Jae Woong; Shin, Dong Hun

2013-01-01

The commodity classification is to identify strategic commodity. The export license is to verify that exports have met the conditions required by the international export control system. NSSC (Nuclear Safety and Security Commission) operates the NEPS (Nuclear Export Promotion Service) for export control of nuclear items. NEPS contributed to reduce process time related to submission of documents, issuing certificates and licenses, etc. Nonetheless, it became necessary to enhance capacity to implement export control precisely and efficiently as development of Korean nuclear industry led to sharp increase of export. To provide more efficient ways, development of the advanced export control system, IXCS (Intelligent eXport Control System) was suggested. To build IXCS successfully, export control experts have analyzed Korean export control system. Two classification processes of items and technology were derived as a result of the research. However, it may reflect real cases insufficiently because it is derived by experts' discussion. This study evaluated how well the process explains real cases. Although the derived processes explained real cases well, some recommendations for improvement were found through this study. These evaluation results will help to make classification flow charts more compatible to the current export system. Most classification reports on equipment and material deliberated specification and functions while related systems were not considered. If a 'specification review' stage is added to the current process and delete unnecessary stages, this will improve accuracy of the flow chart. In the classification of nuclear technology, detailed process to identify specific information and data need to be specified to decrease subjectivity. Whether they are imitations or not is an unnecessary factor in both processes. The successful development of IXCS needs accurate export control processes as well as IT technology. If these classification processes are

Classification of operational characteristics of commercial cup-anemometers

Energy Technology Data Exchange (ETDEWEB)

Friis Pedersen, T; Schmidt Paulsen, U [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark)

1999-03-01

The present classification of cup-anemometers is based on a procedure for classification of operational characteristics of cup-anemometers that was proposed at the EWEC `97 conference in Dublin 1997. Three definitions of wind speed are considered. The average longitudinal wind speed (ID), the average horizontal wind speed (2D) and the average vector wind speed (3D). The classification is provided in these terms, and additionally, the turbulence intensities, which are defined from the same wind speed definitions. The commercial cup-anemometers have all been calibrated in wind tunnel for the normal calibrations and angular characteristics. Friction was measured by blywheel testing, where the surrounding temperatures were varied over a wide range. The characteristics of the cup-anemometers have been fitted to the heuristic dynamic model, and the response has been calculated in time domain for prescribed ranges of external operational conditions. The results are presented in ranges of maximum deviations of `measured` average wind speed. For each definition of wind speed and turbulence intensity, the cup-anemometers are ranked according to the most precise instrument. Finally, the most important systematic error sources are commented. (au)

Support Vector Machine Classification of Drunk Driving Behaviour.

Science.gov (United States)

Chen, Huiqin; Chen, Lei

2017-01-23

Alcohol is the root cause of numerous traffic accidents due to its pharmacological action on the human central nervous system. This study conducted a detection process to distinguish drunk driving from normal driving under simulated driving conditions. The classification was performed by a support vector machine (SVM) classifier trained to distinguish between these two classes by integrating both driving performance and physiological measurements. In addition, principal component analysis was conducted to rank the weights of the features. The standard deviation of R-R intervals (SDNN), the root mean square value of the difference of the adjacent R-R interval series (RMSSD), low frequency (LF), high frequency (HF), the ratio of the low and high frequencies (LF/HF), and average blink duration were the highest weighted features in the study. The results show that SVM classification can successfully distinguish drunk driving from normal driving with an accuracy of 70%. The driving performance data and the physiological measurements reported by this paper combined with air-alcohol concentration could be integrated using the support vector regression classification method to establish a better early warning model, thereby improving vehicle safety.

Support Vector Machine Classification of Drunk Driving Behaviour

Directory of Open Access Journals (Sweden)

Huiqin Chen

2017-01-01

Full Text Available Alcohol is the root cause of numerous traffic accidents due to its pharmacological action on the human central nervous system. This study conducted a detection process to distinguish drunk driving from normal driving under simulated driving conditions. The classification was performed by a support vector machine (SVM classifier trained to distinguish between these two classes by integrating both driving performance and physiological measurements. In addition, principal component analysis was conducted to rank the weights of the features. The standard deviation of R–R intervals (SDNN, the root mean square value of the difference of the adjacent R–R interval series (RMSSD, low frequency (LF, high frequency (HF, the ratio of the low and high frequencies (LF/HF, and average blink duration were the highest weighted features in the study. The results show that SVM classification can successfully distinguish drunk driving from normal driving with an accuracy of 70%. The driving performance data and the physiological measurements reported by this paper combined with air-alcohol concentration could be integrated using the support vector regression classification method to establish a better early warning model, thereby improving vehicle safety.

Refinement of diagnosis and disease classification in psychiatry.

Science.gov (United States)

Lecrubier, Yves

2008-03-01

Knowledge concerning the classification of mental disorders progressed substantially with the use of DSM III-IV and IDCD 10 because it was based on observed data, with precise definitions. These classifications a priori avoided to generate definitions related to etiology or treatment response. They are based on a categorical approach where diagnostic entities share common phenomenological features. Modifications proposed or discussed are related to the weak validity of the classification strategy described above. (a) Disorders are supposed to be independent but the current coexistence of two or more disorders is the rule; (b) They also are supposed to have stability, however anxiety disorders most of the time precede major depression. For GAD age at onset, family history, biology and symptomatology are close to those of depression. As a consequence broader entities such as depression-GAD spectrum, panic-phobias spectrum and OCD spectrum including eating disorders and pathological gambling are taken into consideration; (c) Diagnostic categories use thresholds to delimitate a border with normals. This creates "subthreshold" conditions. The relevance of such conditions is well documented. Measuring the presence and severity of different dimensions, independent from a threshold, will improve the relevance of the description of patients pathology. In addition, this dimensional approach will improve the problems posed by the mutually exclusive diagnoses (depression and GAD, schizophrenia and depression); (d) Some disorders are based on the coexistence of different dimensions. Patients may present only one set of symptoms and have different characteristics, evolution and response to treatment. An example would be negative symptoms in Schizophrenia; (e) Because no etiological model is available and most measures are subjective, objective measures (cognitive, biological) and genetics progresses created important hopes. None of these measures is pathognomonic and most appear

A canonical correlation analysis based EMG classification algorithm for eliminating electrode shift effect.

Science.gov (United States)

Zhe Fan; Zhong Wang; Guanglin Li; Ruomei Wang

2016-08-01

Motion classification system based on surface Electromyography (sEMG) pattern recognition has achieved good results in experimental condition. But it is still a challenge for clinical implement and practical application. Many factors contribute to the difficulty of clinical use of the EMG based dexterous control. The most obvious and important is the noise in the EMG signal caused by electrode shift, muscle fatigue, motion artifact, inherent instability of signal and biological signals such as Electrocardiogram. In this paper, a novel method based on Canonical Correlation Analysis (CCA) was developed to eliminate the reduction of classification accuracy caused by electrode shift. The average classification accuracy of our method were above 95% for the healthy subjects. In the process, we validated the influence of electrode shift on motion classification accuracy and discovered the strong correlation with correlation coefficient of >0.9 between shift position data and normal position data.

Classification for Inconsistent Decision Tables

KAUST Repository

Azad, Mohammad

2016-09-28

Decision trees have been used widely to discover patterns from consistent data set. But if the data set is inconsistent, where there are groups of examples with equal values of conditional attributes but different labels, then to discover the essential patterns or knowledge from the data set is challenging. Three approaches (generalized, most common and many-valued decision) have been considered to handle such inconsistency. The decision tree model has been used to compare the classification results among three approaches. Many-valued decision approach outperforms other approaches, and M_ws_entM greedy algorithm gives faster and better prediction accuracy.

Classification for Inconsistent Decision Tables

KAUST Repository

Azad, Mohammad; Moshkov, Mikhail

2016-01-01

Decision trees have been used widely to discover patterns from consistent data set. But if the data set is inconsistent, where there are groups of examples with equal values of conditional attributes but different labels, then to discover the essential patterns or knowledge from the data set is challenging. Three approaches (generalized, most common and many-valued decision) have been considered to handle such inconsistency. The decision tree model has been used to compare the classification results among three approaches. Many-valued decision approach outperforms other approaches, and M_ws_entM greedy algorithm gives faster and better prediction accuracy.

On the integrity of functional brain networks in schizophrenia, Parkinson's disease, and advanced age: Evidence from connectivity-based single-subject classification.

Science.gov (United States)

Pläschke, Rachel N; Cieslik, Edna C; Müller, Veronika I; Hoffstaedter, Felix; Plachti, Anna; Varikuti, Deepthi P; Goosses, Mareike; Latz, Anne; Caspers, Svenja; Jockwitz, Christiane; Moebus, Susanne; Gruber, Oliver; Eickhoff, Claudia R; Reetz, Kathrin; Heller, Julia; Südmeyer, Martin; Mathys, Christian; Caspers, Julian; Grefkes, Christian; Kalenscher, Tobias; Langner, Robert; Eickhoff, Simon B

2017-12-01

Previous whole-brain functional connectivity studies achieved successful classifications of patients and healthy controls but only offered limited specificity as to affected brain systems. Here, we examined whether the connectivity patterns of functional systems affected in schizophrenia (SCZ), Parkinson's disease (PD), or normal aging equally translate into high classification accuracies for these conditions. We compared classification performance between pre-defined networks for each group and, for any given network, between groups. Separate support vector machine classifications of 86 SCZ patients, 80 PD patients, and 95 older adults relative to their matched healthy/young controls, respectively, were performed on functional connectivity in 12 task-based, meta-analytically defined networks using 25 replications of a nested 10-fold cross-validation scheme. Classification performance of the various networks clearly differed between conditions, as those networks that best classified one disease were usually non-informative for the other. For SCZ, but not PD, emotion-processing, empathy, and cognitive action control networks distinguished patients most accurately from controls. For PD, but not SCZ, networks subserving autobiographical or semantic memory, motor execution, and theory-of-mind cognition yielded the best classifications. In contrast, young-old classification was excellent based on all networks and outperformed both clinical classifications. Our pattern-classification approach captured associations between clinical and developmental conditions and functional network integrity with a higher level of specificity than did previous whole-brain analyses. Taken together, our results support resting-state connectivity as a marker of functional dysregulation in specific networks known to be affected by SCZ and PD, while suggesting that aging affects network integrity in a more global way. Hum Brain Mapp 38:5845-5858, 2017. © 2017 Wiley Periodicals, Inc. © 2017

Policy and procedures for classification of Class III groundwater at UMTRA Project sites

International Nuclear Information System (INIS)

1989-03-01

The US Environmental Protection Agency (EPA) has recently proposed groundwater regulations for the US Department of Energy's )DOE) Uranium Mill Tailings Remedial Action (UMTRA) Project. These regulations allow the application of supplemental standards at UMTRA Project sites in specific situations. The designation of groundwater as Class III permits the application of supplemental standards. This document discusses a final UMTRA Project policy and procedures for identifying Class III groundwater, including identification of a review area, definition of water quality, quantification of aquifer yield, and identification of methods reasonably employed for public water supply systems. These items, either individually or collectively, need to be investigated in order to determine if groundwaters at UMTRA Project sites are Class III. This document provides a framework for the DOE to determine Class III groundwaters

Automatic Classification of Aerial Imagery for Urban Hydrological Applications

Science.gov (United States)

Paul, A.; Yang, C.; Breitkopf, U.; Liu, Y.; Wang, Z.; Rottensteiner, F.; Wallner, M.; Verworn, A.; Heipke, C.

2018-04-01

In this paper we investigate the potential of automatic supervised classification for urban hydrological applications. In particular, we contribute to runoff simulations using hydrodynamic urban drainage models. In order to assess whether the capacity of the sewers is sufficient to avoid surcharge within certain return periods, precipitation is transformed into runoff. The transformation of precipitation into runoff requires knowledge about the proportion of drainage-effective areas and their spatial distribution in the catchment area. Common simulation methods use the coefficient of imperviousness as an important parameter to estimate the overland flow, which subsequently contributes to the pipe flow. The coefficient of imperviousness is the percentage of area covered by impervious surfaces such as roofs or road surfaces. It is still common practice to assign the coefficient of imperviousness for each particular land parcel manually by visual interpretation of aerial images. Based on classification results of these imagery we contribute to an objective automatic determination of the coefficient of imperviousness. In this context we compare two classification techniques: Random Forests (RF) and Conditional Random Fields (CRF). Experimental results performed on an urban test area show good results and confirm that the automated derivation of the coefficient of imperviousness, apart from being more objective and, thus, reproducible, delivers more accurate results than the interactive estimation. We achieve an overall accuracy of about 85 % for both classifiers. The root mean square error of the differences of the coefficient of imperviousness compared to the reference is 4.4 % for the CRF-based classification, and 3.8 % for the RF-based classification.

Machine-learning methods in the classification of water bodies

Directory of Open Access Journals (Sweden)

Sołtysiak Marek

2016-06-01

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

Establishment of land model at the Shika Nuclear Power Plant. Mainly, on rock board classification

International Nuclear Information System (INIS)

Katagawa, Hideki; Hashimoto, Toru; Hirano, Shuji

1999-01-01

In order to grasp engineering properties of basic land of constructions, there is rock board classification as a method to classify whole of rock board to some groups considerable to be nearly equal on its properties. Among the method, various methods in response to its aim and characteristics are devised, and for a classification to hard rock board, the Denken type rock board classification considering degree of weathering to its main element and so forth are well known. The basic rock board of the Shika Nuclear Power Plant is composed of middle and hard types of rock, and its weathering is limited to its shallow portion, most of which are held at fresh condition. For such land, a new classification standard in response to characteristics of land was established. Here were introduced on a progress to establish a new classification standard, its application results and rock board properties. (G.K.)

Clinical use of dental classification.

Science.gov (United States)

Jones, Gordon

2008-01-01

The Dental Classification system used by the uniformed services is supposed to predict the incidence of dental emergencies in the operational setting, at least on the unit level. Since most Sailors and Marines are deployed without close dental support, the sea services have adopted a policy of early treatment of class 3 dental conditions during recruit training. The other services are beginning to do the same. Recently, two factors have emerged that are affecting this early dental class 3 treatment. These factors must be considered when planning to provide early dental treatment. First, changing population and dentist provider demographics in the civilian sector are beginning to affect the class 3 treatment needs of incoming military recruits. Second, attrition from recruit training results in treatment provided to recruits who leave military service before finishing their training. Some view this as a waste of resources, others as a cost of doing business. As operational jointness increases, the three services must develop and use a single dental classification terminology, as well as unified standards and guidelines, both for better research in this area and for the readiness and well-being of our patients.

Danish translation and validation of the International Skin Tear Advisory Panel Skin Tear Classification System

DEFF Research Database (Denmark)

Skiveren, J; Bermark, S; LeBlanc, K

2015-01-01

OBJECTIVE: The aim of this study was to translate, validate and establish reliability of the International Skin Tear Classification System in Danish. METHOD: Phase 1 of the project involved the translation of the International Skin Tear Advisory Panel (ISTAP) Skin Tear Classification System......) and social and health-care assistants (non-RN) from both primary health care and a Danish university hospital in Copenhagen. Thirty photographs, with equal representation of the three types of skin tears, were selected to test validity. The photographs chosen were those originally used for internal...... and external validation by the ISTAP group. The subjects were approached in their place of work and invited to participate in the study and to attend an educational session related to skin tears. RESULTS: The Danish translation of the ISTAP classification system was tested on 270 non-wound specialists...

The book classification of William Torrey Harris: influences of Bacon and Hegel in library classification

Directory of Open Access Journals (Sweden)

Rodrigo de Sales

2017-09-01

Full Text Available The studies of library classification generally interact with the historical contextualization approach and with the classification ideas typical of Philosophy. In the 19th century, the North-American philosopher and educator William Torrey Harris developed a book classification at the St. Louis Public School, based on Francis Bacon and Georg Wilhelm Friedrich Hegel. The objective of this essay is to analyze Harris’s classification, reflecting upon his theoretical and philosophical backgrounds. To achieve such objective, this essay adopts a critical-descriptive approach for analysis. Results show some influences of Bacon and Hegel in Harris’s classification.

Characterizing near-surface CO2 conditions before injection - Perspectives from a CCS project in the Illinois Basin, USA

Science.gov (United States)

Locke, R.A.; Krapac, I.G.; Lewicki, J.L.; Curtis-Robinson, E.

2011-01-01

The Midwest Geological Sequestration Consortium is conducting a large-scale carbon capture and storage (CCS) project in Decatur, Illinois, USA to demonstrate the ability of a deep saline formation to store one million tonnes of carbon dioxide (CO2) from an ethanol facility. Beginning in early 2011, CO2 will be injected at a rate of 1,000 tonnes/day for three years into the Mount Simon Sandstone at a depth of approximately 2,100 meters. An extensive Monitoring, Verification, and Accounting (MVA) program has been undertaken for the Illinois Basin Decatur Project (IBDP) and is focused on the 0.65 km2 project site. Goals include establishing baseline conditions to evaluate potential impacts from CO2 injection, demonstrating that project activities are protective of human health and the environment, and providing an accurate accounting of stored CO2. MVA efforts are being conducted pre-, during, and post- CO2 injection. Soil and net CO2 flux monitoring has been conducted for more than one year to characterize near-surface CO2 conditions. More than 2,200 soil CO2 flux measurements have been manually collected from a network of 118 soil rings since June 2009. Three ring types have been evaluated to determine which type may be the most effective in detecting potential CO 2 leakage. Bare soil, shallow-depth rings were driven 8 cm into the ground and were prepared to minimize surface vegetation in and near the rings. Bare soil, deep-depth rings were prepared similarly, but were driven 46 cm. Natural-vegetation, shallow-depth rings were driven 8 cm and are most representative of typical vegetation conditions. Bare-soil, shallow-depth rings had the smallest observed mean flux (1.78 ??mol m-2 s-1) versus natural-vegetation, shallow-depth rings (3.38 ??mol m-2 s-1). Current data suggest bare ring types would be more sensitive to small CO2 leak signatures than natural ring types because of higher signal to noise ratios. An eddy covariance (EC) system has been in use since June

Reliability of Oronasal Fistula Classification.

Science.gov (United States)

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

2018-01-01

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

A unified classification of alien species based on the magnitude of their environmental impacts

Czech Academy of Sciences Publication Activity Database

Blackburn, T. M.; Essl, F.; Evans, T.; Hulme, P. E.; Jeschke, J.M.; Kühn, I.; Kumschick, S.; Marková, Zuzana; Mrugala, A.; Nentwig, W.; Pergl, Jan; Pyšek, Petr; Rabitsch, W.; Ricciardi, A.; Richardson, D. M.; Sendek, A.; Vila, M.; Wilson, J. R. U.; Winter, M.; Genovesi, P.; Bacher, S.

2014-01-01

Roč. 12, č. 5 (2014), s. 1-11, e1001850 E-ISSN 1545-7885 R&D Projects: GA ČR(CZ) GAP504/11/1028; GA ČR GB14-36079G Institutional support: RVO:67985939 Keywords : biological invasions * classification * environmental impact Subject RIV: EF - Botanics Impact factor: 9.343, year: 2014

5 CFR 1312.7 - Derivative classification.

Science.gov (United States)

2010-01-01

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

Hydro-geomorphological characterization and classification of Chilean river networks using horizontal, vertical and climatological properties

Science.gov (United States)

Pereira, A. A.; Gironas, J. A.; Passalacqua, P.; Mejia, A.; Niemann, J. D.

2017-12-01

Previous work has shown that lithological, tectonic and climatic processes have a major influence in shaping the geomorphology of river networks. Accordingly, quantitative classification methods have been developed to identify and characterize network types (dendritic, parallel, pinnate, rectangular and trellis) based solely on the self-affinity of their planform properties, computed from available Digital Elevation Model (DEM) data. In contrast, this research aim is to include both horizontal and vertical properties to evaluate a quantitative classification method for river networks. We include vertical properties to consider the unique surficial conditions (e.g., large and steep height drops, volcanic activity, and complexity of stream networks) of the Andes Mountains. Furthermore, the goal of the research is also to explain the implications and possible relations between the hydro-geomorphological properties and climatic conditions. The classification method is applied to 42 basins in the southern Andes in Chile, ranging in size from 208 Km2 to 8,000 Km2. The planform metrics include the incremental drainage area, stream course irregularity and junction angles, while the vertical metrics include the hypsometric curve and the slope-area relationship. We introduce new network structures (Brush, Funnel and Low Sinuosity Rectangular), possibly unique to the Andes, that can be quantitatively differentiated from previous networks identified in other geographic regions. Then, this research evaluates the effect that excluding different Strahler order streams has on the horizontal properties and therefore in the classification. We found that climatic conditions are not only linked to horizontal parameters, but also to vertical ones, finding significant correlation between climatic variables (average near-surface temperature and rainfall) and vertical measures (parameters associated with the hypsometric curve and slope-area relation). The proposed classification shows

Munitions Classification Library

Science.gov (United States)

2016-04-04

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

DATA CLASSIFICATION WITH NEURAL CLASSIFIER USING RADIAL BASIS FUNCTION WITH DATA REDUCTION USING HIERARCHICAL CLUSTERING

Directory of Open Access Journals (Sweden)

M. Safish Mary

2012-04-01

Full Text Available Classification of large amount of data is a time consuming process but crucial for analysis and decision making. Radial Basis Function networks are widely used for classification and regression analysis. In this paper, we have studied the performance of RBF neural networks to classify the sales of cars based on the demand, using kernel density estimation algorithm which produces classification accuracy comparable to data classification accuracy provided by support vector machines. In this paper, we have proposed a new instance based data selection method where redundant instances are removed with help of a threshold thus improving the time complexity with improved classification accuracy. The instance based selection of the data set will help reduce the number of clusters formed thereby reduces the number of centers considered for building the RBF network. Further the efficiency of the training is improved by applying a hierarchical clustering technique to reduce the number of clusters formed at every step. The paper explains the algorithm used for classification and for conditioning the data. It also explains the complexities involved in classification of sales data for analysis and decision-making.

Self-organization comprehensive real-time state evaluation model for oil pump unit on the basis of operating condition classification and recognition

Science.gov (United States)

Liang, Wei; Yu, Xuchao; Zhang, Laibin; Lu, Wenqing

2018-05-01

In oil transmission station, the operating condition (OC) of an oil pump unit sometimes switches accordingly, which will lead to changes in operating parameters. If not taking the switching of OCs into consideration while performing a state evaluation on the pump unit, the accuracy of evaluation would be largely influenced. Hence, in this paper, a self-organization Comprehensive Real-Time State Evaluation Model (self-organization CRTSEM) is proposed based on OC classification and recognition. However, the underlying model CRTSEM is built through incorporating the advantages of Gaussian Mixture Model (GMM) and Fuzzy Comprehensive Evaluation Model (FCEM) first. That is to say, independent state models are established for every state characteristic parameter according to their distribution types (i.e. the Gaussian distribution and logistic regression distribution). Meanwhile, Analytic Hierarchy Process (AHP) is utilized to calculate the weights of state characteristic parameters. Then, the OC classification is determined by the types of oil delivery tasks, and CRTSEMs of different standard OCs are built to constitute the CRTSEM matrix. On the other side, the OC recognition is realized by a self-organization model that is established on the basis of Back Propagation (BP) model. After the self-organization CRTSEM is derived through integration, real-time monitoring data can be inputted for OC recognition. At the end, the current state of the pump unit can be evaluated by using the right CRTSEM. The case study manifests that the proposed self-organization CRTSEM can provide reasonable and accurate state evaluation results for the pump unit. Besides, the assumption that the switching of OCs will influence the results of state evaluation is also verified.

IAEA Classification of Uranium Deposits

International Nuclear Information System (INIS)

Bruneton, Patrice

2014-01-01

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

Projection-based curve clustering

International Nuclear Information System (INIS)

Auder, Benjamin; Fischer, Aurelie

2012-01-01

This paper focuses on unsupervised curve classification in the context of nuclear industry. At the Commissariat a l'Energie Atomique (CEA), Cadarache (France), the thermal-hydraulic computer code CATHARE is used to study the reliability of reactor vessels. The code inputs are physical parameters and the outputs are time evolution curves of a few other physical quantities. As the CATHARE code is quite complex and CPU time-consuming, it has to be approximated by a regression model. This regression process involves a clustering step. In the present paper, the CATHARE output curves are clustered using a k-means scheme, with a projection onto a lower dimensional space. We study the properties of the empirically optimal cluster centres found by the clustering method based on projections, compared with the 'true' ones. The choice of the projection basis is discussed, and an algorithm is implemented to select the best projection basis among a library of orthonormal bases. The approach is illustrated on a simulated example and then applied to the industrial problem. (authors)

32 CFR 2400.15 - Classification guides.

Science.gov (United States)

2010-07-01

... REGULATIONS TO IMPLEMENT E.O. 12356; OFFICE OF SCIENCE AND TECHNOLOGY POLICY INFORMATION SECURITY PROGRAM Derivative Classification § 2400.15 Classification guides. (a) OSTP shall issue and maintain classification guides to facilitate the proper and uniform derivative classification of information. These guides shall...

Classification and treatment of radiation maculopathy.

LENUS (Irish Health Repository)

Horgan, Noel

2012-02-01

PURPOSE OF REVIEW: Radiation maculopathy is a sight-limiting consequence of radiotherapy in the management of uveal melanoma and other intraocular tumors. In this review, we consider clinical, fluorescein angiographic and optical coherence tomographic findings, propose a classification for radiation maculopathy and discuss the management of this condition. RECENT FINDINGS: Radiation macular edema (RME) can be classified by optical coherence tomography into noncystoid or cystoid edema, with foveolar or extrafoveolar involvement. Optical coherence tomographic grading of RME has been found to correlate with visual acuity. Focal argon laser might have some limited benefit in the treatment of RME. Intravitreal triamcinolone and intravitreal antivascular endothelial growth factor agents can be of short-term benefit in the treatment of RME. In a randomized controlled trial, periocular triamcinolone significantly reduced rates of RME and vision loss up to 18 months following plaque radiotherapy for uveal melanoma. SUMMARY: Currently, there is no proven treatment for established RME, though periocular triamcinolone has been shown to have a preventive benefit. An accepted classification system for radiation maculopathy would be of benefit in planning and comparing future treatment trials.

Classification system for oral submucous fibrosis

Directory of Open Access Journals (Sweden)

Chandramani Bhagvan More

2012-01-01

Full Text Available Oral submucous fibrosis (OSMF is a potentially malignant disorder (PMD and crippling condition of oral mucosa. It is a chronic insidious scarring disease of oral cavity, pharynx and upper digestive tract, characterized by progressive inability to open the mouth due to loss of elasticity and development of vertical fibrous bands in labial and buccal tissues. OSMF is a debilitating but preventable oral disease. It predominantly affects people of Southeast Asia and Indian subcontinent, where chewing of arecanut and its commercial preparation is high. Presence of fibrous bands is the main characteristic feature of OSMF. The present literature review provides the compilation of various classification system based on clinical and/or histopathological features of OSMF from several databases. The advantages and drawbacks of these classifications supersede each other, leading to perplexity. An attempt is made to provide and update the knowledge about this potentially malignant disorder to health care providers in order to help in early detection and treatment, thus reducing the mortality of oral cancer.

Biomarkers for Musculoskeletal Pain Conditions: Use of Brain Imaging and Machine Learning.

Science.gov (United States)

Boissoneault, Jeff; Sevel, Landrew; Letzen, Janelle; Robinson, Michael; Staud, Roland

2017-01-01

Chronic musculoskeletal pain condition often shows poor correlations between tissue abnormalities and clinical pain. Therefore, classification of pain conditions like chronic low back pain, osteoarthritis, and fibromyalgia depends mostly on self report and less on objective findings like X-ray or magnetic resonance imaging (MRI) changes. However, recent advances in structural and functional brain imaging have identified brain abnormalities in chronic pain conditions that can be used for illness classification. Because the analysis of complex and multivariate brain imaging data is challenging, machine learning techniques have been increasingly utilized for this purpose. The goal of machine learning is to train specific classifiers to best identify variables of interest on brain MRIs (i.e., biomarkers). This report describes classification techniques capable of separating MRI-based brain biomarkers of chronic pain patients from healthy controls with high accuracy (70-92%) using machine learning, as well as critical scientific, practical, and ethical considerations related to their potential clinical application. Although self-report remains the gold standard for pain assessment, machine learning may aid in the classification of chronic pain disorders like chronic back pain and fibromyalgia as well as provide mechanistic information regarding their neural correlates.

Research on Entrepreneurial Intention: An Academic Literature Review and Classification

Directory of Open Access Journals (Sweden)

Aqeel Israr

2015-12-01

Full Text Available The purpose of this paper is to review the academic literature available in the field of Entrepreneurial Intention (EI, and conduct a content analysis of the same for the purpose of classification and provide a comprehensive bibliography. Emerald full text, online database was searched to review the available literature on EI. The search resulted in only 118 publications where EI was mentioned as the primary research topic. The sample was further refined to only include papers with empirical research in qualitative and quantitative realms. The resultant of the refined sample was 69 research publications, which were classified in to mutually exclusive categories. The content analysis led to classification of literature on the basis of six categories viz. Publication Year, Journal, Research Area, Research Type, Base Theory and Population. The study identifies the history of research on EI and hints towards future research prospects in research in terms of industry, area of study, methodology, type of study, etc. The paper provides a list of field projects accompanied by a comprehensive bibliography that will be useful to both academicians and practitioners for studying existing research as well as for contemplating future research. This may be considered as the basic compilation and classification of available literature in the field of EI.

More than one kind of inference: re-examining what's learned in feature inference and classification.

Science.gov (United States)

Sweller, Naomi; Hayes, Brett K

2010-08-01

Three studies examined how task demands that impact on attention to typical or atypical category features shape the category representations formed through classification learning and inference learning. During training categories were learned via exemplar classification or by inferring missing exemplar features. In the latter condition inferences were made about missing typical features alone (typical feature inference) or about both missing typical and atypical features (mixed feature inference). Classification and mixed feature inference led to the incorporation of typical and atypical features into category representations, with both kinds of features influencing inferences about familiar (Experiments 1 and 2) and novel (Experiment 3) test items. Those in the typical inference condition focused primarily on typical features. Together with formal modelling, these results challenge previous accounts that have characterized inference learning as producing a focus on typical category features. The results show that two different kinds of inference learning are possible and that these are subserved by different kinds of category representations.