Domino effect in chemical accidents: main features and accident sequences.

PubMed

Darbra, R M; Palacios, Adriana; Casal, Joaquim

2010-11-15

The main features of domino accidents in process/storage plants and in the transportation of hazardous materials were studied through an analysis of 225 accidents involving this effect. Data on these accidents, which occurred after 1961, were taken from several sources. Aspects analyzed included the accident scenario, the type of accident, the materials involved, the causes and consequences and the most common accident sequences. The analysis showed that the most frequent causes are external events (31%) and mechanical failure (29%). Storage areas (35%) and process plants (28%) are by far the most common settings for domino accidents. Eighty-nine per cent of the accidents involved flammable materials, the most frequent of which was LPG. The domino effect sequences were analyzed using relative probability event trees. The most frequent sequences were explosion→fire (27.6%), fire→explosion (27.5%) and fire→fire (17.8%). Copyright © 2010 Elsevier B.V. All rights reserved.

Detection of silicate emission features in the 8- to 13-micron spectra of main belt asteroids

NASA Technical Reports Server (NTRS)

Feierberg, M. A.; Witteborn, F. C.; Lebofsky, L. A.

1983-01-01

A presentation is given of 8.0-13.0 micron spectra (Delta lambda/lambda = 0.02-0.03) for six main belt asteroids, which range from 58 to 220 km in diameter and sample the five principal taxonomic classes (C, S, M, R and E). Narrow, well-defined silicate emission features are present on two of the asteroids, the C-type 19 Fortuna and the M-type 21 Lutetia. No comparable emission features are observed on the S-types 11 Parthenope and 14 Irene, the R-type 349 Dembowska or the E-type 64 Angelina.

Practical achievements on biomass steam gasification in a rotary tubular coiled-downdraft reactor.

PubMed

Andrew, Renny; Gokak, D T; Sharma, Pankaj; Gupta, Shalini

2016-12-01

Today, the impending stringent environmental norms and concerns about the depletion of fossil fuel reserves have added impetus on development of cutting edge technologies for production of alternative fuels from renewable sources, like biomass. The concept of biomass pyro-gasification offers a platform for production of (a) hydrogen, (b) hydrocarbons and (c) value added chemicals, etc. In this context, there exists potential for hydrogen production from biomass by superheated steam gasification. Apart from H 2 , gaseous products of biomass steam gasification contain CO, CH 4 and other hydrocarbons that can be converted to hydrogen through cracking, steam reforming and water gas shift reactions. In the present work, the characteristics of biomass steam gasification in an indigenously designed rotary tubular coiled-downdraft reactor for high value gaseous fuel production from rice husk was studied through a series of experiments. The robust reactor system enhances biomass conversion to gaseous products by improved mass and heat transfer within the system induced by a coiled flow pattern with increased heat transfer area. Also, the system has improved upon the reliability of operation and offered greater continuity of the process and easier control in comparison with a conventional process by making use of an innovative gas cooler assembly and efficient venturi-mixing system for biomass and steam. Subsequently, the effects of reactor temperature, steam-to-biomass ratio and residence time on overall product gas yield and hydrogen yield were investigated. From the experimental results, it can be deduced that an optimum reactor temperature of 750 °C, steam-to-biomass ratio of 2.0 and a residence time of 3.0 min contributed highest gas yield (1.252 Nm 3  kg -1 moisture-free biomass). Based on the obtained experimental results, a projected potential hydrogen yield of 8.6 wt% of the moisture-free biomass could be achieved, and is also practical for production of

The new European legislation on traditional herbal medicines: main features and perspectives.

PubMed

Silano, Marco; De Vincenzi, Massimo; De Vincenzi, Alessandro; Silano, Vittorio

2004-03-01

Under the Italian Presidency of the Council of the European Union (July 2003-December 2003) an agreement has been reached by the European Parliament and the Council on the approval of the proposal of Directive of the European Parliament and the Council amending the Directive 2001/83/EC as regards traditional herbal medicinal products. Once implemented in the E.U. Member States, this new Directive will remove the constraints that have made it difficult granting marketing authorisations of herbal substances and preparations as traditional medicinal products under the pre-existing Community legislation. The main features (i.e. traditional herbal medicine definition, simplified registration procedure, provisions for Community herbal monographs and Community list of herbal substances and preparations and establishment of the Committee for Herbal Medicinal Products) of this new Community legislation are analysed and discussed in the present paper together with some expected positive public health impacts.

Experimental study of wood downdraft gasification for an improved producer gas quality through an innovative two-stage air and premixed air/gas supply approach.

PubMed

Jaojaruek, Kitipong; Jarungthammachote, Sompop; Gratuito, Maria Kathrina B; Wongsuwan, Hataitep; Homhual, Suwan

2011-04-01

This study conducted experiments on three different downdraft gasification approaches: single stage, conventional two-stage, and an innovative two-stage air and premixed air/gas supply approach. The innovative two-stage approach has two nozzle locations, one for air supply at combustion zone and the other located at the pyrolysis zone for supplying the premixed gas (air and producer gas). The producer gas is partially bypassed to mix with air and supplied to burn at the pyrolysis zone. The result shows that producer gas quality generated by the innovative two-stage approach improved as compared to conventional two-stage. The higher heating value (HHV) increased from 5.4 to 6.5 MJ/Nm(3). Tar content in producer gas reduced to less than 45 mg/Nm(3). With this approach, gas can be fed directly to an internal combustion engine. Furthermore, the gasification thermal efficiency also improved by approximately 14%. The approach gave double benefits on gas qualities and energy savings. Copyright © 2010 Elsevier Ltd. All rights reserved.

A Observational Study of the Internal Structure of Airmass Thunderstorms

NASA Astrophysics Data System (ADS)

Kingsmill, David Edmund

The internal structure of airmass thunderstorms is examined with Doppler and dual-polarization radar, photographic and rawinsonde data from the 1986 MIST project. A kinematic, dynamic and thermodynamic analysis of one well documented case shows a life cycle which closely resembles the Byers and Braham model for airmass storms. Other less detailed cases, examined to supplement this analysis, largely confirm these findings. However, several phenomena never documented for this storm-type are discussed. One of these is a midlevel inflow, which in one case caused a visible constriction in a storm cloud. This inflow appears to arise from the mass compensation required when a strong updraft driven by buoyancy from glaciation forms above a weaker updraft loaded down by the precipitation core. A downdraft at midlevels with an associated "weak-echo" trench is also observed. Its origin appears related to a shear induced wake entrainment process. In addition, microburst intensity surface outflows are observed. The downdrafts responsible for these events appear to be restricted to low levels and to be separate from the midlevel downdraft. One case shows this type of downdraft to be initiated by precipitation loading and intensified by negative thermal buoyancy. In light of these new features, the Byers and Braham model of the cumulus, mature and dissipating stages is reexamined.

Aircraft measurements and analysis of severe storms: 1976 field experiment

NASA Technical Reports Server (NTRS)

Sinclair, P. C.

1982-01-01

Severe storm aircraft measurements are documented, as well as the instrumentation and operational features of aircraft mobility capabilities. The measurements and data analyses indicate that the concept of a highly mobile research aircraft capability for obtaining detailed measurements of wind, temperature, moisture, spherics, etc., near and within severe storm systems, forecast 48 hours in advance in a 1000 nm operating radius, is feasible, and was successfully demonstrated. The measurements and analyses reveal several severe storm features and insights with respect to storm air flow circulations and inflow-outflow orientation. Precipitation downdraft air is recirculated back into the updraft core below the scud cloud in both back and front feeder type storms. In a back feeder type storm, the downdraft outflow air ahead of the storm is also recirculated back into the updraft region near cloud base.

Automated feature extraction and spatial organization of seafloor pockmarks, Belfast Bay, Maine, USA

USGS Publications Warehouse

Andrews, Brian D.; Brothers, Laura L.; Barnhardt, Walter A.

2010-01-01

Seafloor pockmarks occur worldwide and may represent millions of m3 of continental shelf erosion, but few numerical analyses of their morphology and spatial distribution of pockmarks exist. We introduce a quantitative definition of pockmark morphology and, based on this definition, propose a three-step geomorphometric method to identify and extract pockmarks from high-resolution swath bathymetry. We apply this GIS-implemented approach to 25 km2 of bathymetry collected in the Belfast Bay, Maine USA pockmark field. Our model extracted 1767 pockmarks and found a linear pockmark depth-to-diameter ratio for pockmarks field-wide. Mean pockmark depth is 7.6 m and mean diameter is 84.8 m. Pockmark distribution is non-random, and nearly half of the field's pockmarks occur in chains. The most prominent chains are oriented semi-normal to the steepest gradient in Holocene sediment thickness. A descriptive model yields field-wide spatial statistics indicating that pockmarks are distributed in non-random clusters. Results enable quantitative comparison of pockmarks in fields worldwide as well as similar concave features, such as impact craters, dolines, or salt pools.

Maine Ingredients

ERIC Educational Resources Information Center

Waters, John K.

2009-01-01

This article features Maine Learning Technology Initiative (MLTI), the nation's first-ever statewide 1-to-1 laptop program which marks its seventh birthday by expanding into high schools, providing an occasion to celebrate--and to examine the components of its success. The plan to put laptops into the hands of every teacher and student in grades 7…

Digitization of a geologic map for the Quebec-Maine-Gulf of Maine global geoscience transect

USGS Publications Warehouse

Wright, Bruce E.; Stewart, David B.

1990-01-01

The Bedrock Geologic Map of Maine was digitized and combined with digital geologic data for Quebec and the Gulf of Maine for the Quebec-Maine-Gulf of Maine Geologic Transect Project. This map is being combined with digital geophysical data to produce three-dimensional depictions of the subsurface geology and to produce cross sections of the Earth's crust. It is an essential component of a transect that stretches from the craton near Quebec City, Quebec, to the Atlantic Ocean Basin south of Georges Bank. The transect is part of the Global Geosciences Transect Project of the International Lithosphere Program. The Digital Line Graph format is used for storage of the digitized data. A coding scheme similar to that used for base category planimetric data was developed to assign numeric codes to the digitized geologic data. These codes were used to assign attributes to polygon and line features to describe rock type, age, name, tectonic setting of original deposition, mineralogy, and composition of igneous plutonic rocks, as well as faults and other linear features. The digital geologic data can be readily edited, rescaled, and reprojected. The attribute codes allow generalization and selective retrieval of the geologic features. The codes allow assignment of map colors based on age, lithology, or other attribute. The Digital Line Graph format is a general transfer format that is supported by many software vendors and is easily transferred between systems.

Salient features of the dayside low latitude ionospheric response to the main phase step-I of the 17 March 2015 geomagnetic storm

NASA Astrophysics Data System (ADS)

Bagiya, Mala S.; Sunil, A. S.; Chakrabarty, D.; Sunda, Surendra

2017-10-01

Based on TEC observations by India's GPS Aided GEO Augmented Navigation (GAGAN) GPS network, we report the dayside low latitude ionospheric variations over the Indian region during the moderate main phase step-I of the 17 March 2015 geomagnetic storm. In addition, we assess the efficacy of GPS inferred TEC maps by International GNSS service (IGS) in capturing large scale diurnal features of equatorial ionization anomaly (EIA) over the Indian region during this period. Following the prompt penetration electric field (PPE) at ∼0605 UT, equatorial electrojet (EEJ) enhances by ∼55 nT over 75 ± 3oE longitudes where main phase step-I is coincided with local noon. Initial moderate EIA gradually strengthens with the storm commencement. Although GAGAN TEC exhibits more intense EIA evolution compare to IGS TEC maps, latitudinal extent of EIA are comparable in both. The enhanced EEJ reverses by ∼0918 UT under the effect of overshielding electric field, the later is accompanied by northward turning of interplanetary magnetic field (IMF) Bz. The weakening of well evolved EIA reflects in IGS TEC maps after ∼45 min of the overshielding occurrence. In contrary, GAGAN TEC shows the corresponding feature after ∼0115 h. Resurgence of EIA, following the PPE ∼1115 UT, shows up in GAGAN TEC but IGS TEC maps fails in capturing this feature. The observed low latitude TEC variations and EIA modulations are explained in terms of the varying storm time disturbance electric fields. The anomalies between the GAGAN TEC and IGS TEC maps are discussed in terms of the possible limitations of the IGS TEC maps in capturing storm time EIA variability over the Indian region.

Effect of rice husk ash mass on sustainability pyrolysis zone of fixed bed downdraft gasifier with capacity of 10 kg/hour

NASA Astrophysics Data System (ADS)

Surjosatyo, Adi; Haq, Imaduddin; Dafiqurrohman, Hafif; Gibran, Felly Rihlat

2017-03-01

The formation of pyrolysis sustainability (Sustainable Pyrolysis) is the objective of the gasification process. Pyrolysis zone in the gasification process is the result of the endothermic reaction that get heat from oxidation (combustion) of the fuel with oxygen, where cracking biomass rice husk result of such as charcoal, water vapor, steam tar, and gas - gas (CO, H 2, CH 4, CO 2 and N 2) and must be maintained at a pyrolysis temperature to obtain results plentiful gas (producer gas) or syngas (synthetic gas). Obtaining continuously syngas is indicated by flow rate (discharge) producer gas well and the consistency of the flame on the gas burner, it is highly influenced by the gasification process and the operation of the gasifier and the mass balance (mass balance) between the feeding rate of rice husk with the disposal of ash (ash removal). In experiments conducted is using fixed bed gasifier type downdraft capacity of 10 kg/h. Besides setting the mass of rice husks into the gasifier and disposal arrangements rice husk ash may affect the sustainability of the pyrolysis process, but tar produced during the gasification process causes sticky rice husk ash in the plenum gasifier. Modifications disposal system rice husk ash can facilitate the arrangement of ash disposal then could control the temperature pyrolysis with pyrolysis at temperatures between 500-750 ° C. The experimental study was conducted to determine the effect of mass quantities of rice husk ash issued against sustainability pyrolysis temperature which is obtained at each time disposal of rice husk ash to produce 60-90 grams of ash issued. From some experimental phenomena is expected to be seen pyrolysis and its effect on the flow rate of syngas and the stability of the flame on the gas burner so that this research can find a correlation to obtain performance (performance) gasifier optimal.

Latent cooling and microphysics effects in deep convection

NASA Astrophysics Data System (ADS)

Fernández-González, S.; Wang, P. K.; Gascón, E.; Valero, F.; Sánchez, J. L.

2016-11-01

Water phase changes within a storm are responsible for the enhancement of convection and therefore the elongation of its lifespan. Specifically, latent cooling absorbed during evaporation, melting and sublimation is considered the main cause of the intensification of downdrafts. In order to know more accurately the consequences of latent cooling caused by each of these processes (together with microphysical effects that they induce), four simulations were developed with the Wisconsin Dynamical and Microphysical Model (WISCDYMM): one with all the microphysical processes; other without sublimation; melting was suppressed in the third simulation; and evaporation was disabled in the fourth. The results show that sublimation cooling is not essential to maintain the vertical currents of the storm. This is demonstrated by the fact that in the simulation without sublimation, maximum updrafts are in the same range as in the control simulation, and the storm lifespan is similar or even longer. However, melting was of vital importance. The storm in the simulation without melting dissipated prematurely, demonstrating that melting is indispensable to the enhancement of downdrafts below the freezing level and for avoiding the collapse of low level updrafts. Perhaps the most important finding is the crucial influence of evaporative cooling above the freezing level that maintains and enhances mid-level downdrafts in the storm. It is believed that this latent cooling comes from the evaporation of supercooled liquid water connected with the Bergeron-Findeisen process. Therefore, besides its influence at low levels (which was already well known), this evaporative cooling is essential to strengthen mid-level downdrafts and ultimately achieve a quasi-steady state.

Calibration of a convective parameterization scheme in the WRF model and its impact on the simulation of East Asian summer monsoon precipitation

DOE PAGES

Yang, Ben; Zhang, Yaocun; Qian, Yun; ...

2014-03-26

Reasonably modeling the magnitude, south-north gradient and seasonal propagation of precipitation associated with the East Asian Summer Monsoon (EASM) is a challenging task in the climate community. In this study we calibrate five key parameters in the Kain-Fritsch convection scheme in the WRF model using an efficient importance-sampling algorithm to improve the EASM simulation. We also examine the impacts of the improved EASM precipitation on other physical process. Our results suggest similar model sensitivity and values of optimized parameters across years with different EASM intensities. By applying the optimal parameters, the simulated precipitation and surface energy features are generally improved.more » The parameters related to downdraft, entrainment coefficients and CAPE consumption time (CCT) can most sensitively affect the precipitation and atmospheric features. Larger downdraft coefficient or CCT decrease the heavy rainfall frequency, while larger entrainment coefficient delays the convection development but build up more potential for heavy rainfall events, causing a possible northward shift of rainfall distribution. The CCT is the most sensitive parameter over wet region and the downdraft parameter plays more important roles over drier northern region. Long-term simulations confirm that by using the optimized parameters the precipitation distributions are better simulated in both weak and strong EASM years. Due to more reasonable simulated precipitation condensational heating, the monsoon circulations are also improved. Lastly, by using the optimized parameters the biases in the retreating (beginning) of Mei-yu (northern China rainfall) simulated by the standard WRF model are evidently reduced and the seasonal and sub-seasonal variations of the monsoon precipitation are remarkably improved.« less

Analysis of Cloud-resolving Simulations of a Tropical Mesoscale Convective System Observed during TWP-ICE: Vertical Fluxes and Draft Properties in Convective and Stratiform Regions

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

Mrowiec, Agnieszka A.; Rio, Catherine; Fridlind, Ann

2012-10-02

We analyze three cloud-resolving model simulations of a strong convective event observed during the TWP-ICE campaign, differing in dynamical core, microphysical scheme or both. Based on simulated and observed radar reflectivity, simulations roughly reproduce observed convective and stratiform precipitating areas. To identify the characteristics of convective and stratiform drafts that are difficult to observe but relevant to climate model parameterization, independent vertical wind speed thresholds are calculated to capture 90% of total convective and stratiform updraft and downdraft mass fluxes. Convective updrafts are fairly consistent across simulations (likely owing to fixed large-scale forcings and surface conditions), except that hydrometeor loadingsmore » differ substantially. Convective downdraft and stratiform updraft and downdraft mass fluxes vary notably below the melting level, but share similar vertically uniform draft velocities despite differing hydrometeor loadings. All identified convective and stratiform downdrafts contain precipitation below ~10 km and nearly all updrafts are cloudy above the melting level. Cold pool properties diverge substantially in a manner that is consistent with convective downdraft mass flux differences below the melting level. Despite differences in hydrometeor loadings and cold pool properties, convective updraft and downdraft mass fluxes are linearly correlated with convective area, the ratio of ice in downdrafts to that in updrafts is ~0.5 independent of species, and the ratio of downdraft to updraft mass flux is ~0.5-0.6, which may represent a minimum evaporation efficiency under moist conditions. Hydrometeor loading in stratiform regions is found to be a fraction of hydrometeor loading in convective regions that ranges from ~10% (graupel) to ~90% (cloud ice). These findings may lead to improved convection parameterizations.« less

ReliefSeq: A Gene-Wise Adaptive-K Nearest-Neighbor Feature Selection Tool for Finding Gene-Gene Interactions and Main Effects in mRNA-Seq Gene Expression Data

PubMed Central

McKinney, Brett A.; White, Bill C.; Grill, Diane E.; Li, Peter W.; Kennedy, Richard B.; Poland, Gregory A.; Oberg, Ann L.

2013-01-01

Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k) for each gene to optimize the Relief-F test statistics (importance scores) for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak) Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to detect both main

Acoustic Features Influence Musical Choices Across Multiple Genres.

PubMed

Barone, Michael D; Bansal, Jotthi; Woolhouse, Matthew H

2017-01-01

Based on a large behavioral dataset of music downloads, two analyses investigate whether the acoustic features of listeners' preferred musical genres influence their choice of tracks within non-preferred, secondary musical styles. Analysis 1 identifies feature distributions for pairs of genre-defined subgroups that are distinct. Using correlation analysis, these distributions are used to test the degree of similarity between subgroups' main genres and the other music within their download collections. Analysis 2 explores the issue of main-to-secondary genre influence through the production of 10 feature-influence matrices, one per acoustic feature, in which cell values indicate the percentage change in features for genres and subgroups compared to overall population averages. In total, 10 acoustic features and 10 genre-defined subgroups are explored within the two analyses. Results strongly indicate that the acoustic features of people's main genres influence the tracks they download within non-preferred, secondary musical styles. The nature of this influence and its possible actuating mechanisms are discussed with respect to research on musical preference, personality, and statistical learning.

Acoustic Features Influence Musical Choices Across Multiple Genres

PubMed Central

Barone, Michael D.; Bansal, Jotthi; Woolhouse, Matthew H.

2017-01-01

Based on a large behavioral dataset of music downloads, two analyses investigate whether the acoustic features of listeners' preferred musical genres influence their choice of tracks within non-preferred, secondary musical styles. Analysis 1 identifies feature distributions for pairs of genre-defined subgroups that are distinct. Using correlation analysis, these distributions are used to test the degree of similarity between subgroups' main genres and the other music within their download collections. Analysis 2 explores the issue of main-to-secondary genre influence through the production of 10 feature-influence matrices, one per acoustic feature, in which cell values indicate the percentage change in features for genres and subgroups compared to overall population averages. In total, 10 acoustic features and 10 genre-defined subgroups are explored within the two analyses. Results strongly indicate that the acoustic features of people's main genres influence the tracks they download within non-preferred, secondary musical styles. The nature of this influence and its possible actuating mechanisms are discussed with respect to research on musical preference, personality, and statistical learning. PMID:28725200

Using thermodynamic data to reproduce main seismic features of transition zone

NASA Astrophysics Data System (ADS)

Fomin, Ilya; Saukko, Anna; Edwards, Paul; Schiffer, Christian

2016-04-01

Most of the seismic tomography studies nowadays are based on comprehensive models with optimization of lots of parameters. These models are able to resolve very subtle features of the Earth's mantle, but the influence of each specific parameter is not seen directly. In our research we try to minimize the number of processed parameters to produce simple synthetic cases. The main goals of our model are to see how water content influences the depth of the transition zone, and if melting at the transition zone is plausible. We also attempt to see how water content and the presence of melts influence the signal strength of the transition zone in receiver functions. Our MATLAB-code calculates phase assemblage according to specific temperature and pressure within 2D numerical domain (e.g. 300x700 km). Phase properties are calculated with database of Stixrude and Lithgow-Bertelloni [2011], with corrections for water impact on elastic constants according to Liu et al., [2012]. We use the mantle phase composition 55% garnet and 45% olivine-polymorph, soliduses by Ohtani et al. [2004] and melt properties by Sakamaki et al. [2006]. These data are used to calculate seismic velocities and, furthermore, receiver functions with standard routines (e.g.[Schiffer et al., 2012]). Model predicts Vs within 5 to 5.5 km/s and Vp around 9.5-10 km/s within transition zone (Vp/Vs = 1.84-1.87), which is close to standard values. The presence of water enlarges the wadsleyite region, but also dampens the peak of receiver functions down to background level. Increase in water content causes melting at much shallower depths. Using a normal thermal gradient, we can get up to 10% of melt at depths around 390 km with 80% of water saturation, shown by a negative anomaly on receiver functions. This result is similar to data obtained for Afar Plateau [Thompson et al., 2015]. With cratonic thermal gradient, the olivine-wadsleyite transition and corresponding melt layer appear at depths around 350 km

Main Features of a 3d GIS for a Monumental Complex with AN Historical-Cultural Relevance

NASA Astrophysics Data System (ADS)

Scianna, A.; La Guardia, M.

2017-05-01

The last achievements of technologies in geomatics especially in survey and restitution of 3D models (UAV/drones and laser scanner technologies) generated new procedures and higher standards of quality in representation of archaeological sites. Together with Geomatics, the recent development of Information and Communication Technologies (ICT) strongly contribute to document and the Cultural Heritage (CH). The representation and documentation of CH using these new technologies has became necessary in order to satisfy different needs: - for restorers in order to acquire a deep knowledge of the cultural good and to define possible strategies of restoration; - for the conservation of information, allowing to preserve the 3D geometry of the monumental complex with the integration of descriptions about architectural elements; - for touristic aims, giving the opportunity of sharing CH information on web, allowing users to visit and explore, in a virtual way, monumental complexes, acquiring information details about architectural elements or the history of monumental complex. Looking through these new scenarios, the development of a 3D Geographic Information System (GIS) applied to a cultural good could be, today, an added value of fundamental importance for full description and data management of monumental complexes. In this work, the main features necessary for the correct construction of a 3D GIS of a monumental complex will be analyzed, with a particular focus on the possibilities for creating a standardized procedure to follow.

Assigning Main Orientation to an EOH Descriptor on Multispectral Images.

PubMed

Li, Yong; Shi, Xiang; Wei, Lijun; Zou, Junwei; Chen, Fang

2015-07-01

This paper proposes an approach to compute an EOH (edge-oriented histogram) descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform) on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching keypoints between images of translation misalignment only. Observing this limitation, we propose assigning to keypoints the main orientation that is computed with PIIFD (partial intensity invariant feature descriptor). In the proposed method, SIFT keypoints are detected from images as the extrema of difference of Gaussians, and every keypoint is assigned to the main orientation computed with PIIFD. Then, EOH is computed for every keypoint with respect to its main orientation. In addition, an implementation variant is proposed for fast computation of the EOH descriptor. Experimental results show that the proposed approach performs more robustly than the original EOH on image pairs that have a rotation misalignment.

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

Taroyan, Youra; Williams, Thomas

The interaction of an intergranular downdraft with an embedded vertical magnetic field is examined. It is demonstrated that the downdraft may couple to small magnetic twists leading to an instability. The descending plasma exponentially amplifies the magnetic twists when it decelerates with depth due to increasing density. Most efficient amplification is found in the vicinity of the level, where the kinetic energy density of the downdraft reaches equipartition with the magnetic energy density. Continual extraction of energy from the decelerating plasma and growth in the total azimuthal energy occurs as a consequence of the wave-flow coupling along the downdraft. Themore » presented mechanism may drive vortices and torsional motions that have been detected between granules and in simulations of magnetoconvection.« less

Improving management of small natural features on private lands by negotiating the science-policy boundary for Maine vernal pools.

PubMed

Calhoun, Aram J K; Jansujwicz, Jessica S; Bell, Kathleen P; Hunter, Malcolm L

2014-07-29

Vernal pools are far more important for providing ecosystem services than one would predict based on their small size. However, prevailing resource-management strategies are not effectively conserving pools and other small natural features on private lands. Solutions are complicated by tensions between private property and societal rights, uncertainties over resource location and function, diverse stakeholders, and fragmented regulatory authority. The development and testing of new conservation approaches that link scientific knowledge, stakeholder decision-making, and conservation outcomes are important responses to this conservation dilemma. Drawing from a 15-y history of vernal pool conservation efforts in Maine, we describe the coevolution of pool conservation and research approaches, focusing on how research-based knowledge was produced and used in support of management decisions. As management shifted from reactive, top-down approaches to proactive and flexible approaches, research shifted from an ecology-focused program to an interdisciplinary program based on social-ecological systems. The most effective strategies for linking scientific knowledge with action changed as the decision-makers, knowledge needs, and context for vernal pool management advanced. Interactions among stakeholders increased the extent to which knowledge was coproduced and shifted the objective of stakeholder engagement from outreach to research collaboration and development of innovative conservation approaches. New conservation strategies were possible because of the flexible, solutions-oriented collaborations and trust between scientists and decision-makers (fostered over 15 y) and interdisciplinary, engaged research. Solutions to the dilemma of conserving small natural features on private lands, and analogous sustainability science challenges, will benefit from repeated negotiations of the science-policy boundary.

Improving management of small natural features on private lands by negotiating the science–policy boundary for Maine vernal pools

PubMed Central

Calhoun, Aram J. K.; Jansujwicz, Jessica S.; Bell, Kathleen P.; Hunter, Malcolm L.

2014-01-01

Vernal pools are far more important for providing ecosystem services than one would predict based on their small size. However, prevailing resource-management strategies are not effectively conserving pools and other small natural features on private lands. Solutions are complicated by tensions between private property and societal rights, uncertainties over resource location and function, diverse stakeholders, and fragmented regulatory authority. The development and testing of new conservation approaches that link scientific knowledge, stakeholder decision-making, and conservation outcomes are important responses to this conservation dilemma. Drawing from a 15-y history of vernal pool conservation efforts in Maine, we describe the coevolution of pool conservation and research approaches, focusing on how research-based knowledge was produced and used in support of management decisions. As management shifted from reactive, top-down approaches to proactive and flexible approaches, research shifted from an ecology-focused program to an interdisciplinary program based on social–ecological systems. The most effective strategies for linking scientific knowledge with action changed as the decision-makers, knowledge needs, and context for vernal pool management advanced. Interactions among stakeholders increased the extent to which knowledge was coproduced and shifted the objective of stakeholder engagement from outreach to research collaboration and development of innovative conservation approaches. New conservation strategies were possible because of the flexible, solutions-oriented collaborations and trust between scientists and decision-makers (fostered over 15 y) and interdisciplinary, engaged research. Solutions to the dilemma of conserving small natural features on private lands, and analogous sustainability science challenges, will benefit from repeated negotiations of the science–policy boundary. PMID:25002496

Main features of anthropogenic inner-urban soils in Szeged, Hungary

NASA Astrophysics Data System (ADS)

Puskás, Irén.; Farsang, Andrea

2010-05-01

At the beginning of the 21st century, due to the intensive urbanization it is necessary to gather more and more information on altered physical, chemical and biological parameters of urban soils in order to ensure their suitable management and protection for appropriate living conditions. Nowadays, these measures are very relevant since negative environmental effects can modify the soil forming factors in cities. Szeged, the 4th largest city of Hungary, proved to be an ideal sampling area for the research of urban soils since its original surface has been altered by intensive anthropogenic activities. The main objectives of my research are the investigation, description and evaluation of the altered soils in Szeged. For the physical and chemical analysis (humus, nitrogen, carbonate content, heavy metals, pH, artefacts etc.) of soils 124 samples were taken from the horizons of 25 profiles in Szeged and its peripherals (as control samples). The profiles were sampled at sites affected by different extent of artificial infill according to infill maps (1. profiles fully made up of infill; 2. so-called mixed profiles consisting of considerable amount of infill material and buried soil horizons; 3. natural profiles located in the peripherals of the city). With the help of the above-mentioned parameters, the studied soils of Szeged were assigned into the classification system of WRB(2006), which classifies the soils of urban and industrial areas as an individual soil group (under the term Technosols) for the first time. In accordance with the WRB(2006) nomenclature three main soil types can be identified in Szeged with respect to the degree of human influence: profiles slightly influenced, strongly modified, completely altered by human activities. During this poster, we present the peculiarities of typical urban profiles strongly and completely altered by human influence. Most profiles were placed into the group of Technosols due to the considerable transformation of their

Functional conjugated pyridines via main-group element tuning.

PubMed

Stolar, Monika; Baumgartner, Thomas

2018-03-29

Pyridine-based materials have seen widespread attention for the development of n-type organic materials. In recent years, the incorporation of main-group elements has also explored significant advantages for the development and tunability of organic conjugated materials. The unique chemical and electronic structure of main-group elements has led to several enhancements in conventional organic materials. This Feature article highlights recent main-group based pyridine materials by discussing property enhancements and application in organic electronics.

Submesoscale features and their interaction with fronts and internal tides in a high-resolution coupled atmosphere-ocean-wave model of the Bay of Bengal

NASA Astrophysics Data System (ADS)

Jensen, Tommy G.; Shulman, Igor; Wijesekera, Hemantha W.; Anderson, Stephanie; Ladner, Sherwin

2018-03-01

Large freshwater fluxes into the Bay of Bengal by rainfall and river discharges result in strong salinity fronts in the bay. In this study, a high-resolution coupled atmosphere-ocean-wave model with comprehensive physics is used to model the weather, ocean circulation, and wave field in the Bay of Bengal. Our objective is to explore the submesoscale activity that occurs in a realistic coupled model that resolves mesoscales and allows part of the submesoscale field. Horizontal resolution in the atmosphere varies from 2 to 6 km and is 13 km for surface waves, while the ocean model is submesoscale permitting with resolutions as high as 1.5 km and a vertical resolution of 0.5 m in the upper 10 m. In this paper, three different cases of oceanic submesoscale features are discussed. In the first case, heavy rainfall and intense downdrafts produced by atmospheric convection are found to force submesoscale currents, temperature, and salinity anomalies in the oceanic mixed layer and impact the mesoscale flow. In a second case, strong solitary-like waves are generated by semidiurnal tides in the Andaman Sea and interact with mesoscale flows and fronts and affect submesoscale features generated along fronts. A third source of submesoscale variability is found further north in the Bay of Bengal where river outflows help maintain strong salinity gradients throughout the year. For that case, a comparison with satellite observations of sea surface height anomalies, sea surface temperature, and chlorophyll shows that the model captures the observed mesoscale eddy features of the flow field, but in addition, submesoscale upwelling and downwelling patterns associated with ageostrophic secondary circulations along density fronts are also captured by the model.

The boundary layer moist static energy budget: Convection picks up moisture and leaves footprints in the marine boundary layer

NASA Astrophysics Data System (ADS)

de Szoeke, S. P.

2017-12-01

Averaged over the tropical marine boundary layer (BL), 130 W m-2 turbulent surface moist static energy (MSE) flux, 120 W m-2 of which is evaporation, is balanced by upward MSE flux at the BL top due to 1) incorporation of cold air by downdrafts from deep convective clouds, and 2) turbulent entrainment of dry air into the BL. Cold saturated downdraft air, and warm clear air entrained into the BL have distinct thermodynamic properties. This work observationally quantifies their respective MSE fluxes in the central Indian Ocean in 2011, under different convective conditions of the intraseasonal (40-90 day) Madden Julian oscillation (MJO). Under convectively suppressed conditions, entrainment and downdraft fluxes export equal shares (60 W m-2) of MSE from the BL. Downdraft fluxes are more variable, increasing for stronger convection. In the convectively active phase of the MJO, downdrafts export 90 W m-2 from the BL, compared to 40 W m-2 by entrainment. These processes that control the internal, latent (condensation), and MSE of the tropical marine atmospheric BL determine the parcel buoyancy and strength of tropical deep convection.

Identification of the emission features near 3.5 microns in the pre main sequence star HD 97048

NASA Technical Reports Server (NTRS)

Baas, F.; Allamandola, L. J.; Geballe, T. R.; Persson, S. E.; Lacy, J. H.

1982-01-01

The spectrum of HD97048 was measured with a resolving power of 450 between 3.37 and 3.64 microns. The prominent feature near 3.5 microns is well resolved, with a peak at 3.53 microns and a wing extending to a shorter wavelength. The weaker feature near 3.4 microns is found to peak at 3.43 microns, in contrast to the 3.40 micron feature seen in other astronomical objects. The observed spectrum strongly resembles laboratory spectra of mixtures of monomeric and dimeric formaldehyde embedded in low temperature solids. Of various possible excitation mechanisms, ultraviolet pumped infrared fluorescence of formaldehyde in interstellar grains provides the best explanation for the observed spectrum of HD 97048.

Kinematic, dynamic, and thermodynamic impacts of hook-echo hydrometeors, including explorations into the utilization of polarimetric radar data

NASA Astrophysics Data System (ADS)

Askelson, Mark Anthony

Recent studies have revealed that the thermodynamic properties of the rear flank downdraft (RFD) may dictate whether or not a supercell becomes tornadic. Since hydrometeors are thought to be an important driving force for the RFD, it is postulated that they may be important to its thermodynamic properties and, possibly, to tornadogenesis. The role hook-echo hydrometeors play in driving RFDs is investigated by estimating hook-echo hydrometeor types and amounts from polarimetric radar data and by using that information to drive a relatively simple downdraft model. Soundings for the individual cases are used to initialize the downdraft model in order to replicate the environments of the storms as closely as possible. Since this effort and others like it require the quantitative utilization of radar data, issues pertaining to this are explored. In addition to analyses of coordinate transformation equations and an innovative objective analysis technique for weather radar data, the difficult problem of response functions for arbitrary weight functions and data distributions was considered. A novel approach to this problem revealed that the local response function for distance dependent weighted averaging schemes is the complex conjugate of the normalized Fourier transform of the effective weight function. This facilitates new research avenues, especially regarding analyses of irregularly spaced data. Simulations of hydrometeor driven RFDs show that hydrometeor fields inferred from radar data are able to drive significant downdrafts without the influence of vertical perturbation pressure gradients. Moreover, they reveal that above the boundary layer supercell environments are relatively resistant to downdrafts whereas within the boundary layer they are generally supportive of downdrafts. It appears that in many supercell environments relatively large hail (≥1 cm in diameter) or vertical perturbation pressure gradients may be needed to drive deep midlevel downdrafts that

Photogrammetric Analysis of CPAS Main Parachutes

NASA Technical Reports Server (NTRS)

Ray, Eric; Bretz, David

2011-01-01

The Crew Exploration Vehicle Parachute Assembly System (CPAS) is being designed to land the Orion Crew Module (CM) at a safe rate of descent at splashdown with a cluster of two to three Main parachutes. The instantaneous rate of descent varies based on parachute fly-out angles and geometric inlet area. Parachutes in a cluster oscillate between significant fly-out angles and colliding into each other. The former presents a sub-optimal inlet area and the latter lowers the effective drag area as the parachutes interfere with each other. The fly-out angles are also important in meeting a twist torque requirement. Understanding cluster behavior necessitates measuring the Mains with photogrammetric analysis. Imagery from upward looking cameras is analyzed to determine parachute geometry. Fly-out angles are measured from each parachute vent to an axis determined from geometry. Determining the scale of the objects requires knowledge of camera and lens calibration as well as features of known size. Several points along the skirt are tracked to compute an effective circumference, diameter, and inlet area as a function of time. The effects of this geometry are clearly seen in the system drag coefficient time history. Photogrammetric analysis is key in evaluating the effects of design features such as an Over-Inflation Control Line (OICL), Main Line Length Ratio (MLLR), and geometric porosity, which are varied in an attempt to minimize cluster oscillations. The effects of these designs are evaluated through statistical analysis.

Origin of storm footprints on the sea seen by synthetic aperture radar.

PubMed

Atlas, D

1994-11-25

Spaceborne synthetic aperture radar can detect storm footprints on the sea. Coastal weather radar from Cape Hatteras provides evidence that the echo-free hole at the footprint core is the result of wave damping by rain. The increased radar cross section of the sea surrounding the echo-free hole results from the divergence of the precipitation-forced downdraft impacting the sea. The footprint boundary is the gust front; its oriention is aligned with the direction of the winds aloft, which are transported down with the downdraft, and its length implies downdraft impact 1 hour earlier at a quasi-stationary impact spot. The steady, localized nature of the storm remains a mystery.

27. VIEW LOOKING AFT ON STARBOARD SIDE OF MAIN DECK ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

27. VIEW LOOKING AFT ON STARBOARD SIDE OF MAIN DECK WITH TENDER ANNIE RUTH ALONGSIDE. COVER OF FORWARD COMPANIONWAY HAS BEEN PLACED ON MAIN DECK; SUN AWNING A TYPICAL FEATURE IN TROPICAL CLIMATES. CREW MEMBERS UNKNOWN Original 4-3/4'x6-3/4' photograph taken c. 1930? - Pilot Schooner "Alabama", Moored in harbor at Vineyard Haven, Vineyard Haven, Dukes County, MA

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.

PubMed

Qu, Kaiyang; Han, Ke; Wu, Song; Wang, Guohua; Wei, Leyi

2017-09-22

DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.

Analysis of a Destructive Wind Storm on 16 November 2008 in Brisbane, Australia

DOE PAGES

Richter, Harald; Peter, Justin; Collis, Scott

2014-08-25

During the late afternoon on 16 November 2008 the Brisbane (Australia) suburb of “The Gap” experienced extensive wind damage caused by an intense local thunderstorm. The CP2 research radar nearby detected near-surface radial velocities exceeding 44 m s -1 above The Gap while hail size reports did not exceed golf ball size, and no tornadoes were reported. This study shows that the storm environment was characterized by a layer of very moist (mixing ratios exceeding 12 g kg -1) near-surface air embedded in strong storm-relative low-level flow, whereas the storm-relative winds aloft were significantly weaker. And while the thermodynamic stormmore » environment contained a range of downdraft promoting ingredients such as a ~4 km high melting level above a ~2 km deep layer with nearly dry adiabatic lapse rates mostly collocated with dry ambient air, a ~1 km deep stable layer near the ground would generally lower expectations of destructive surface winds based on the downburst mechanism. We also found that once observed reflectivities exceed 70 dBZ that downdraft cooling due to hail melting and downdraft acceleration based on hail loading are likely to become non-negligible forcing mechanisms for a strong downdraft. The study found a close proximity of the hydrostatically and dynamically driven mesohigh at the base of the downdraft to a dynamically driven mesolow associated with a radar-observed low-level circulation. This proximity is hypothesized to have been instrumental in the observed anisotropic horizontal acceleration of the near-ground outflow and the ultimate strength of the Gap storm surface winds. Finally, we speculate that the 44 weak storm-relative midlevel winds allowed the downdraft to descend close to the low45 level circulation which set up this strong horizontal perturbation pressure gradient.« less

Main Oxidizer Valve Design

NASA Technical Reports Server (NTRS)

Addona, Brad; Eddleman, David

2015-01-01

A developmental Main Oxidizer Valve (MOV) was designed by NASA-MSFC using additive manufacturing processes. The MOV is a pneumatically actuated poppet valve to control the flow of liquid oxygen to an engine's injector. A compression spring is used to return the valve to the closed state when pneumatic pressure is removed from the valve. The valve internal parts are cylindrical in shape, which lends itself to traditional lathe and milling operations. However, the valve body represents a complicated shape and contains the majority of the mass of the valve. Additive manufacturing techniques were used to produce a part that optimized mass and allowed for design features not practical with traditional machining processes.

Space Shuttle Main Engine: Advanced Health Monitoring System

NASA Technical Reports Server (NTRS)

Singer, Chirs

1999-01-01

The main gola of the Space Shuttle Main Engine (SSME) Advanced Health Management system is to improve flight safety. To this end the new SSME has robust new components to improve the operating margen and operability. The features of the current SSME health monitoring system, include automated checkouts, closed loop redundant control system, catastropic failure mitigation, fail operational/ fail-safe algorithms, and post flight data and inspection trend analysis. The features of the advanced health monitoring system include: a real time vibration monitor system, a linear engine model, and an optical plume anomaly detection system. Since vibration is a fundamental measure of SSME turbopump health, it stands to reason that monitoring the vibration, will give some idea of the health of the turbopumps. However, how is it possible to avoid shutdown, when it is not necessary. A sensor algorithm has been developed which has been exposed to over 400 test cases in order to evaluate the logic. The optical plume anomaly detection (OPAD) has been developed to be a sensitive monitor of engine wear, erosion, and breakage.

Space moving target detection using time domain feature

NASA Astrophysics Data System (ADS)

Wang, Min; Chen, Jin-yong; Gao, Feng; Zhao, Jin-yu

2018-01-01

The traditional space target detection methods mainly use the spatial characteristics of the star map to detect the targets, which can not make full use of the time domain information. This paper presents a new space moving target detection method based on time domain features. We firstly construct the time spectral data of star map, then analyze the time domain features of the main objects (target, stars and the background) in star maps, finally detect the moving targets using single pulse feature of the time domain signal. The real star map target detection experimental results show that the proposed method can effectively detect the trajectory of moving targets in the star map sequence, and the detection probability achieves 99% when the false alarm rate is about 8×10-5, which outperforms those of compared algorithms.

Magnetic shuffling of coronal downdrafts

NASA Astrophysics Data System (ADS)

Petralia, A.; Reale, F.; Orlando, S.

2017-02-01

Context. Channelled fragmented downflows are ubiquitous in magnetized atmospheres, and have recently been addressed based on an observation after a solar eruption. Aims: We study the possible back-effect of the magnetic field on the propagation of confined flows. Methods: We compared two 3D magnetohydrodynamic simulations of dense supersonic plasma blobs that fall down along a coronal magnetic flux tube. In one, the blobs move strictly along the field lines; in the other, the initial velocity of the blobs is not perfectly aligned with the magnetic field and the field is weaker. Results: The aligned blobs remain compact while flowing along the tube, with the generated shocks. The misaligned blobs are disrupted and merge through the chaotic shuffling of the field lines. They are structured into thinner filaments. Alfvén wave fronts are generated together with shocks ahead of the dense moving front. Conclusions: Downflowing plasma fragments can be chaotically and efficiently mixed if their motion is misaligned with field lines, with broad implications for disk accretion in protostars, coronal eruptions, and rain, for example. Movies associated to Figs. 2 and 3 are available at http://www.aanda.org

Glamorous Education: Main Features and Manifestations

ERIC Educational Resources Information Center

Mikhailovna, Nikolaeva Evgeniya; Dmitrievich, Schelkunov Mikhail

2014-01-01

Being a powerful social trend glamour culture has significant effect on a high education that results in the phenomenon of glamorous education (glam-education). Prerequisites of this type of education are democratization of high school that introduces stereotypes of glam-culture in educational environment; commercialization of education that uses…

Opinion mining feature-level using Naive Bayes and feature extraction based analysis dependencies

NASA Astrophysics Data System (ADS)

Sanda, Regi; Baizal, Z. K. Abdurahman; Nhita, Fhira

2015-12-01

Development of internet and technology, has major impact and providing new business called e-commerce. Many e-commerce sites that provide convenience in transaction, and consumers can also provide reviews or opinions on products that purchased. These opinions can be used by consumers and producers. Consumers to know the advantages and disadvantages of particular feature of the product. Procuders can analyse own strengths and weaknesses as well as it's competitors products. Many opinions need a method that the reader can know the point of whole opinion. The idea emerged from review summarization that summarizes the overall opinion based on sentiment and features contain. In this study, the domain that become the main focus is about the digital camera. This research consisted of four steps 1) giving the knowledge to the system to recognize the semantic orientation of an opinion 2) indentify the features of product 3) indentify whether the opinion gives a positive or negative 4) summarizing the result. In this research discussed the methods such as Naï;ve Bayes for sentiment classification, and feature extraction algorithm based on Dependencies Analysis, which is one of the tools in Natural Language Processing (NLP) and knowledge based dictionary which is useful for handling implicit features. The end result of research is a summary that contains a bunch of reviews from consumers on the features and sentiment. With proposed method, accuration for sentiment classification giving 81.2 % for positive test data, 80.2 % for negative test data, and accuration for feature extraction reach 90.3 %.

Small main-belt asteroid spectroscopic survey: Initial results

NASA Technical Reports Server (NTRS)

Xu, Shui; Binzel, Richard P.; Burbine, Thomas H.; Bus, Schelte J.

1995-01-01

The spectral characterization of small asteroids is important for understanding the evolution of their compositional and mineralogical properties. We report the results of a CCD spectroscopic survey of small main-belt asteroids which we call the Small Main-belt Asteroid Spectroscopic Survey (SMASS). Spectra of 316 asteroids were obtained, with wavelength coverage ranging from 4000 to 10000 A (0.4 to 1 micrometers). More than half of the objects in our survey have diameters less than 20 km. Survey results include the identification of the first object resembling ordinary chondrite meteorites among the main-belt asteroids (Binzel, R. P., et al, 1993) and observations of more than 20 asteroids showing basaltic achondrite spectral absorption features that strongly link Vesta as the parent body for the basaltic achondrite meteorites (Binzel, R. P., and S. Xu 1993). A potential Mars-crossing asteroid analog to ordinary chondrite meteorites (H chondrites), 2078 Nanking, is reported here. Through a principal component analysis, we have assigned classifications to the members of our sample. The majority of the small main-belt asteroids belong to S and C classes, similar to large asteroids. Our analysis shows that two new classes are justified which we label as J and O. Small asteroids display more diversity in spectral absorption features than the larger ones, which may indicate a greater variation of compositions in the small asteroid population. We found a few candidates for olivine-rich asteroids within the S class. Although the total number of olivine-rich candidates is relatively small, we present evidence suggesting that such objects are more prevalent at smaller sizes.

Jupiter's Main Ring/Ring Halo

NASA Technical Reports Server (NTRS)

1997-01-01

A mosaic of four images taken through the clear filter (610 nanometers) of the solid state imaging (CCD) system aboard NASA's Galileo spacecraft on November 8, 1996, at a resolution of approximately 46 kilometers (28.5 miles) per picture element (pixel) along Jupiter's rings. Because the spacecraft was only about 0.5 degrees above the ring plane, the image is highly foreshortened in the vertical direction. The images were obtained when Galileo was in Jupiter's shadow, peering back toward the Sun; the ring was approximately 2.3 million kilometers (1.4 million miles) away. The arc on the far right of the image is produced when sunlight is scattered by small particles comprising Jupiter's upper atmospheric haze. The ring also efficiently scatters light, indicating that much of its brightness is due to particles that are microns or less in diameter. Such small particles are believed to have human-scale lifetimes, i.e., very brief compared to the solar system's age.

Jupiter's ring system is composed of three parts - - a flat main ring, a lenticular halo interior to the main ring, and the gossamer ring, outside the main ring. The near and far arms of Jupiter's main ring extend horizontally across the mosaic, joining together at the ring's ansa, on the figure's far left side. The near arm of the ring appears to be abruptly truncated close to the planet, at the point where it passes into Jupiter's shadow. Some radial structure is barely visible across the ring's ansa (top image). A faint mist of particles can be seen above and below the main rings. This vertically extended 'halo' is unusual in planetary rings, and is probably caused by electromagnetic forces pushing the smallest grains out of the ring plane. Because of shadowing, the halo is not visible close to Jupiter in the lower right part of the mosaic. To accentuate faint features in the bottom image of the ring halo, different brightnesses are shown through color. Brightest features are white or yellow and the

Assessment of Borderline Personality Features in Population Samples: Is the Personality Assessment Inventory-Borderline Features Scale Measurement Invariant across Sex and Age?

ERIC Educational Resources Information Center

De Moor, Marleen H. M.; Distel, Marijn A.; Trull, Timothy J.; Boomsma, Dorret I.

2009-01-01

Borderline personality disorder (BPD) is more often diagnosed in women than in men, and symptoms tend to decline with age. Using a large community sample, the authors investigated whether sex and age differences in four main features of BPD, measured with the "Personality Assessment Inventory-Borderline Features" scale (PAI-BOR; Morey,…

Feature and Region Selection for Visual Learning.

PubMed

Zhao, Ji; Wang, Liantao; Cabral, Ricardo; De la Torre, Fernando

2016-03-01

Visual learning problems, such as object classification and action recognition, are typically approached using extensions of the popular bag-of-words (BoWs) model. Despite its great success, it is unclear what visual features the BoW model is learning. Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: 1) our approach accommodates non-linear additive kernels, such as the popular χ(2) and intersection kernel; 2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; 3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; and 4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach.

Text feature extraction based on deep learning: a review.

PubMed

Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan

2017-01-01

Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.

Detail view to show the stylized "dragon" bracket feature that ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Detail view to show the stylized "dragon" bracket feature that stands guard by the outside door to the kitchen (north elevation of the main house) - Death Valley Ranch, Main House, Death Valley Junction, Inyo County, CA

Improving Representation of Convective Transport for Scale-Aware Parameterization, Part II: Analysis of Cloud-Resolving Model Simulations

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

Liu, Yi-Chin; Fan, Jiwen; Zhang, Guang J.

2015-04-27

Following Part I, in which 3-D cloud-resolving model (CRM) simulations of a squall line and mesoscale convective complex in the mid-latitude continental and the tropical regions are conducted and evaluated, we examine the scale-dependence of eddy transport of water vapor, evaluate different eddy transport formulations, and improve the representation of convective transport across all scales by proposing a new formulation that more accurately represents the CRM-calculated eddy flux. CRM results show that there are strong grid-spacing dependencies of updraft and downdraft fractions regardless of altitudes, cloud life stage, and geographical location. As for the eddy transport of water vapor, updraftmore » eddy flux is a major contributor to total eddy flux in the lower and middle troposphere. However, downdraft eddy transport can be as large as updraft eddy transport in the lower atmosphere especially at the mature stage of 38 mid-latitude continental convection. We show that the single updraft approach significantly underestimates updraft eddy transport of water vapor because it fails to account for the large internal variability of updrafts, while a single downdraft represents the downdraft eddy transport of water vapor well. We find that using as few as 3 updrafts can account for the internal variability of updrafts well. Based on evaluation with the CRM simulated data, we recommend a simplified eddy transport formulation that considers three updrafts and one downdraft. Such formulation is similar to the conventional one but much more accurately represents CRM-simulated eddy flux across all grid scales.« less

30. View of main deck at bow (looking aft from ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

30. View of main deck at bow (looking aft from samson post, upper deck removed), showing anchor windlass (left foreground), head (right foregound), and forward deckhouse; weather canopy overhead not an original or permanent feature - Schooner WAWONA, 1018 Valley Street, Seattle, King County, WA

Tool Wear Feature Extraction Based on Hilbert Marginal Spectrum

NASA Astrophysics Data System (ADS)

Guan, Shan; Song, Weijie; Pang, Hongyang

2017-09-01

In the metal cutting process, the signal contains a wealth of tool wear state information. A tool wear signal’s analysis and feature extraction method based on Hilbert marginal spectrum is proposed. Firstly, the tool wear signal was decomposed by empirical mode decomposition algorithm and the intrinsic mode functions including the main information were screened out by the correlation coefficient and the variance contribution rate. Secondly, Hilbert transform was performed on the main intrinsic mode functions. Hilbert time-frequency spectrum and Hilbert marginal spectrum were obtained by Hilbert transform. Finally, Amplitude domain indexes were extracted on the basis of the Hilbert marginal spectrum and they structured recognition feature vector of tool wear state. The research results show that the extracted features can effectively characterize the different wear state of the tool, which provides a basis for monitoring tool wear condition.

Outer Main Belt asteroids: Identification and distribution of four 3-μm spectral groups

NASA Astrophysics Data System (ADS)

Takir, Driss; Emery, Joshua P.

2012-06-01

This paper examines the distribution and the abundance of hydrated minerals (any mineral that contains H2O or OH) on outer Main Belt asteroids spanning the 2.5 < a < 4.0 AU region. The hypothesis we are testing is whether planetesimals that accreted closer to the Sun experienced a higher degree of aqueous alteration. We would expect then to see a gradual decline of the abundance of hydrated minerals among the outer Main Belt asteroids with increasing heliocentric distance (2.5 < a < 4.0 AU). We measured spectra (0.8-2.5 μm and 1.9-4.1 μm) of 28 outer Main Belt asteroids using the SpeX spectrograph/imager at the NASA Infrared Telescope Facility (IRTF). We identified four groups on the basis of the shape and the band center of the 3-μm feature. The first group, which we call "sharp", exhibits a sharp 3-μm feature, attributed to hydrated minerals (phyllosilicates). Most asteroids in this group are located in the 2.5 < a < 3.3 AU region. The second group, which we call "Ceres-like", consists of 10 Hygiea and 324 Bamberga. Like Asteroid Ceres, these asteroids exhibit a 3-μm feature with a band center of 3.05 ± 0.01 μm that is superimposed on a broader absorption feature from ˜2.8 to 3.7 μm. The third group, which we call "Europa-like", includes 52 Europa, 31 Euphrosyne, and 451 Patientia. Objects in this group exhibit a 3-μm feature with a band center of 3.15 ± 0.01 μm. Both the Ceres-like and Europa-like groups are concentrated in the 2.5 < a < 3.3 AU region. The fourth group, which we call "rounded", is concentrated in the 3.4 < a < 4.0 AU region. Asteroids in this group are characterized by a rounded 3-μm feature, attributed to H2O ice. A similar rounded 3-μm feature was also identified in 24 Themis and 65 Cybele. Unlike the sharp group, the rounded group did not experience aqueous alteration. Of the asteroids observed in this study, 140 Siwa, a P-type, is the only one that does not exhibit a 3-μm feature. These results are important to constrain the

Statistical research into low-power solar flares. Main phase duration

NASA Astrophysics Data System (ADS)

Borovik, Aleksandr; Zhdanov, Anton

2017-12-01

This paper is a sequel to earlier papers on time parameters of solar flares in the Hα line. Using data from the International Flare Patrol, an electronic database of solar flares for the period 1972-2010 has been created. The statistical analysis of the duration of the main phase has shown that it increases with increasing flare class and brightness. It has been found that the duration of the main phase depends on the type and features of development of solar flares. Flares with one brilliant point have the shortest main phase; flares with several intensity maxima and two-ribbon flares, the longest one. We have identified more than 3000 cases with an ultra-long duration of the main phase (more than 60 minutes). For 90% of such flares the duration of the main phase is 2-3 hrs, but sometimes it reaches 12 hrs.

Online feature selection with streaming features.

PubMed

Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan

2013-05-01

We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.

76 FR 59151 - Announcement of Funding Awards; HOPE VI Main Street Grant Program, Fiscal Year (FY) 2009

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-23

... central business district or ``Main Street'' area by replacing unused commercial space in buildings with... historic or traditional architecture or design features in Main Street areas; (3) enhance economic...

Classification of product inspection items using nonlinear features

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.; Lee, H.-W.

1998-03-01

Automated processing and classification of real-time x-ray images of randomly oriented touching pistachio nuts is discussed. The ultimate objective is the development of a system for automated non-invasive detection of defective product items on a conveyor belt. This approach involves two main steps: preprocessing and classification. Preprocessing locates individual items and segments ones that touch using a modified watershed algorithm. The second stage involves extraction of features that allow discrimination between damaged and clean items (pistachio nuts). This feature extraction and classification stage is the new aspect of this paper. We use a new nonlinear feature extraction scheme called the maximum representation and discriminating feature (MRDF) extraction method to compute nonlinear features that are used as inputs to a classifier. The MRDF is shown to provide better classification and a better ROC (receiver operating characteristic) curve than other methods.

Histologic features of alopecias: part II: scarring alopecias.

PubMed

Bernárdez, C; Molina-Ruiz, A M; Requena, L

2015-05-01

The diagnosis of disorders of the hair and scalp can generally be made on clinical grounds, but clinical signs are not always diagnostic and in some cases more invasive techniques, such as a biopsy, may be necessary. This 2-part article is a detailed review of the histologic features of the main types of alopecia based on the traditional classification of these disorders into 2 major groups: scarring and nonscarring alopecias. Scarring alopecias are disorders in which the hair follicle is replaced by fibrous scar tissue, a process that leads to permanent hair loss. In nonscarring alopecias, the follicles are preserved and hair growth can resume when the cause of the problem is eliminated. In the second part of this review, we describe the histologic features of the main forms of scarring alopecia. Since a close clinical-pathological correlation is essential for making a correct histopathologic diagnosis of alopecia, we also include a brief description of the clinical features of the principal forms of this disorder. Copyright © 2014 Elsevier España, S.L.U. and AEDV. All rights reserved.

Histologic features of alopecias-part I: nonscarring alopecias.

PubMed

Bernárdez, C; Molina-Ruiz, A M; Requena, L

2015-04-01

The diagnosis of disorders of the hair and scalp can generally be made on clinical grounds, but clinical signs are not always diagnostic and in some cases more invasive techniques, such as a biopsy, may be necessary. This 2-part article is a detailed review of the histologic features of the main types of alopecia based on the traditional classification of these disorders into 2 major groups: scarring and nonscarring alopecias. Scarring alopecias are disorders in which the hair follicle is replaced by fibrous scar tissue, a process that leads to permanent hair loss. In nonscarring alopecias, the follicles are preserved and hair growth can resume when the cause of the problem is eliminated. In the first part of this review, we describe the histologic features of the main forms of nonscarring alopecia. Since a close clinical-pathological correlation is essential for making a correct histologic diagnosis of alopecia, we also include a brief description of the clinical features of the principal forms of this disorder. Copyright © 2014 Elsevier España, S.L.U. and AEDV. All rights reserved.

A Check List for Evaluating Persuasive Features of Mathematics Courseware

ERIC Educational Resources Information Center

Aris, Baharuddin; Gharbaghi, Alireza; Ahmad, Maizah Hura; Rosli, Mohd Shafie

2013-01-01

The main purpose of this study is to introduce a check list for evaluating persuasive features of mathematics courseware. Since mathematics is a source of anxiety among students (Zeidner & Matthews, 2010), this research is an attempt to employ persuasive features that can be used in mathematics courseware. Specifically, we sought to determine…

Blind image quality assessment based on aesthetic and statistical quality-aware features

NASA Astrophysics Data System (ADS)

Jenadeleh, Mohsen; Masaeli, Mohammad Masood; Moghaddam, Mohsen Ebrahimi

2017-07-01

The main goal of image quality assessment (IQA) methods is the emulation of human perceptual image quality judgments. Therefore, the correlation between objective scores of these methods with human perceptual scores is considered as their performance metric. Human judgment of the image quality implicitly includes many factors when assessing perceptual image qualities such as aesthetics, semantics, context, and various types of visual distortions. The main idea of this paper is to use a host of features that are commonly employed in image aesthetics assessment in order to improve blind image quality assessment (BIQA) methods accuracy. We propose an approach that enriches the features of BIQA methods by integrating a host of aesthetics image features with the features of natural image statistics derived from multiple domains. The proposed features have been used for augmenting five different state-of-the-art BIQA methods, which use statistical natural scene statistics features. Experiments were performed on seven benchmark image quality databases. The experimental results showed significant improvement of the accuracy of the methods.

Kinematic structure of convective-scale elements in the rainbands of Hurricanes Katrina and Rita (2005)

NASA Astrophysics Data System (ADS)

Hence, Deanna A.; Houze, Robert A.

2008-08-01

Airborne Doppler radar data collected during the Hurricane Rainband and Intensity Change Experiment (RAINEX) show the convective-scale air motions embedded in the principal rainbands of hurricanes Katrina and Rita. These embedded convective cells have overturning updrafts and low-level downdrafts (originating at 2-4 km) that enter the rainband on its radially outward side and cross over each other within the rainband as well as a strong downdraft emanating from upper levels (6+ km) on the radially inward side. These vertical motion structures repeat from one convective cell to another along each rainband. The resulting net vertical mass transport is upward in the upwind portion of the band and greatest in the middle sector of the principal rainband, where the updraft motions contribute generally to an increase of potential vorticity below the 3-4 km level. Because the convective cells in the middle sector are systematically located radially just inside the secondary horizontal wind maximum (SHWM), the local increase in vorticity implied by the convective mass transport is manifest locally as an increase in the strength of the SHWM at midlevels (˜4 km). The overturning updrafts of the convective cells tilt, stretch, and vertically transport vorticity such that the convergence of the vertical flux of vorticity strengthens the vorticity anomaly associated with the SHWM. This process could strengthen the SHWM by several meters per second per hour, and may explain how high wave number convective-scale features can influence a low wave number feature such as the principal rainband, and subsequently influence the primary vortex.

General view of a Space Shuttle Main Engine (SSME) mounted ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view of a Space Shuttle Main Engine (SSME) mounted on an SSME engine handler, taken in the SSME Processing Facility at Kennedy Space Center. The most prominent features of the engine assembly in this view are the Low-Pressure Fuel Turbopump Discharge Duct looping around the right side and underneath the assembly, the High-Pressure Fuel Turbopump located on the lower left portion of the assembly, the Engine Controller and Main Fuel Valve Hydraulic Actuator located on the upper portion of the assembly and the Low-Pressure Oxidizer Turbopump Discharge Duct at the top of the engine assembly in this view. - Space Transportation System, Space Shuttle Main Engine, Lyndon B. Johnson Space Center, 2101 NASA Parkway, Houston, Harris County, TX

Histopathological features of Proteus syndrome.

PubMed

Hoey, S E H; Eastwood, D; Monsell, F; Kangesu, L; Harper, J I; Sebire, N J

2008-05-01

Proteus syndrome is a rare, sporadic overgrowth disorder for which the underlying genetic defect remains unknown. Although the clinical course is well-described there is no systematic histopathological description of the lesional pathology. To describe the histopathological features encountered in a series of patients with Proteus syndrome from a single centre. Patients with Proteus syndrome who had undergone therapeutic surgical resection or biopsy were identified from a database and the histopathological findings were reviewed, with particular regard to descriptive features of the underlying tissue abnormality. There were 18 surgical specimens from nine patients, median age 4 years (range 1-9), classified into four main categories: soft-tissue swellings (lipomatous lesions), vascular anomalies (vascular malformation and haemangioma), macrodactyly (hamartomatous overgrowth) and others (sebaceous naevus and nonspecific features). In all cases, the clinical features of overgrowth were due to increased amounts of disorganized tissue, indicating a hamartomatous-type defect in which normal tissue constituents were present, but with an abnormal distribution and architecture. Vascular malformations represented a prominent category of lesions, accounting for 50% of the specimens, predominantly comprising lymphatic and lymphovascular malformations. No malignancy or cytological atypia was identified in any case. The histopathological features of lesions resected from children with Proteus syndrome predominantly include hamartomatous mixed connective tissue lesions, benign neoplasms such as lipomata, and lymphatic-rich vascular malformations.

Saliency image of feature building for image quality assessment

NASA Astrophysics Data System (ADS)

Ju, Xinuo; Sun, Jiyin; Wang, Peng

2011-11-01

The purpose and method of image quality assessment are quite different for automatic target recognition (ATR) and traditional application. Local invariant feature detectors, mainly including corner detectors, blob detectors and region detectors etc., are widely applied for ATR. A saliency model of feature was proposed to evaluate feasibility of ATR in this paper. The first step consisted of computing the first-order derivatives on horizontal orientation and vertical orientation, and computing DoG maps in different scales respectively. Next, saliency images of feature were built based auto-correlation matrix in different scale. Then, saliency images of feature of different scales amalgamated. Experiment were performed on a large test set, including infrared images and optical images, and the result showed that the salient regions computed by this model were consistent with real feature regions computed by mostly local invariant feature extraction algorithms.

Novel clinical features of nonconvulsive status epilepticus

PubMed Central

Nagayama, Masao; Yang, Sunghoon; Geocadin, Romergryko G.; Kaplan, Peter W.; Hoshiyama, Eisei; Shiromaru-Sugimoto, Azusa; Kawamura, Mitsuru

2017-01-01

Nonconvulsive status epilepticus (NCSE) has rapidly expanded from classical features such as staring, repetitive blinking, chewing, swallowing, and automatism to include coma, prolonged apnea, cardiac arrest, dementia, and higher brain dysfunction, which were demonstrated mainly after the 2000s by us and other groups. This review details novel clinical features of NCSE as a manifestation of epilepsy, but one that is underdiagnosed, with the best available evidence. Also, we describe the new concept of epilepsy-related organ dysfunction (Epi-ROD) and a novel electrode and headset which enables prompt electroencephalography. PMID:28979770

Joint Feature Selection and Classification for Multilabel Learning.

PubMed

Huang, Jun; Li, Guorong; Huang, Qingming; Wu, Xindong

2018-03-01

Multilabel learning deals with examples having multiple class labels simultaneously. It has been applied to a variety of applications, such as text categorization and image annotation. A large number of algorithms have been proposed for multilabel learning, most of which concentrate on multilabel classification problems and only a few of them are feature selection algorithms. Current multilabel classification models are mainly built on a single data representation composed of all the features which are shared by all the class labels. Since each class label might be decided by some specific features of its own, and the problems of classification and feature selection are often addressed independently, in this paper, we propose a novel method which can perform joint feature selection and classification for multilabel learning, named JFSC. Different from many existing methods, JFSC learns both shared features and label-specific features by considering pairwise label correlations, and builds the multilabel classifier on the learned low-dimensional data representations simultaneously. A comparative study with state-of-the-art approaches manifests a competitive performance of our proposed method both in classification and feature selection for multilabel learning.

Numerical simulation of mesoscale surface pressure features with trailing stratiform squall lines using WRF -ARW model over Gangetic West Bengal region

NASA Astrophysics Data System (ADS)

Dawn, Soma; Satyanarayana, A. N. V.

2018-01-01

In the present study, an attempt has been made to investigate the simulation of mesoscale surface pressure patterns like pre-squall mesolow, mesohigh and wake low associated with leading convective line-trailing stratiform (TS) squall lines over Gangetic West Bengal (GWB). For this purpose, a two way interactive triple nested domain with high resolution WRF model having2 km grid length in the innermost domain is used. The model simulated results are compared with the available in-situ observations obtained as a part of Severe Thunderstorm: Observations and Regional Modeling (STORM) programme, reflectivity products of Doppler Weather Radar (DWR) Kolkata and TRMM rainfall. Three TS squall lines (15 May 2009, 5 May 2010 and 7 May 2010) are chosen during pre-monsoon thunderstorm season for this study. The model simulated results of diurnal variation of temperature, relative humidity, wind speed and direction at the station Kharagpur in GWB region reveal a sudden fall in temperature, increase in the amount of relative humidity and sudden rise in wind speed during the arrival of the storms. Such results are well comparable with the observations though there are some leading or lagging of time in respect of actual occurrences of such events. The study indicates that the model is able to predict the occurrences of three typical surface pressure features namely: pre-squall mesolow, meso high and wake low. The predicted surface parameters like accumulated rainfall, maximum reflectivity and vertical profiles (temperature, relative humidity and winds) are well accorded with the observations. The convective and stratiform precipitation region of the TS squall lines are well represented by the model. A strong downdraft is observed to be a contributory factor for formation of mesohigh in the convective region of the squall line. Wake low is observed to reside in the stratiform rain region and the descending dry air at this place has triggered the wake low through adiabatic

Psychoacoustic Testing of Modulated Blade Spacing for Main Rotors

NASA Technical Reports Server (NTRS)

Edwards, Bryan; Booth, Earl R., Jr. (Technical Monitor)

2002-01-01

Psychoacoustic testing of simulated helicopter main rotor noise is described, and the subjective results are presented. The objective of these tests was to evaluate the potential acoustic benefits of main rotors with modulated (uneven) blade spacing. Sound simulations were prepared for six main rotor configurations. A baseline 4-blade main rotor with regular blade spacing was based on the Bell Model 427 helicopter. A 5-blade main rotor with regular spacing was designed to approximate the performance of the 427, but at reduced tipspeed. Four modulated rotors - one with "optimum" spacing and three alternate configurations - were derived from the 5 bladed regular spacing rotor. The sounds were played to 2 subjects at a time, with care being taken in the speaker selection and placement to ensure that the sounds were identical for each subject. A total of 40 subjects participated. For each rotor configuration, the listeners were asked to evaluate the sounds in terms of noisiness. The test results indicate little to no "annoyance" benefit for the modulated blade spacing. In general, the subjects preferred the sound of the 5-blade regular spaced rotor over any of the modulated ones. A conclusion is that modulated blade spacing is not a promising design feature to reduce the annoyance for helicopter main rotors.

ECOSYSTEM MODELING IN COBSCOOK BAY, MAINE:A SUMMARY, PERSPECTIVE, AND LOOK FORWARD

EPA Science Inventory

In the mid-1990s, an interdisciplinary, multi-institutional team of scientists was assembled to address basic issues concerning biological productivity and the unique co-occurrence of many unusual ecological features in Cobscook Bay, Maine. Cobscook Bay is a geologically complex,...

Relativistic Effects and the Chemistry of the Heaviest Main-Group Elements

ERIC Educational Resources Information Center

Thayer, John S.

2005-01-01

The chemical properties of the heaviest main-group elements often show features not found in their lighter counterparts while relativistic effects play an important role in the chemistry of these elements. The unusual properties and their relation to relativistic effects with emphasis on the new research are emphasized.

76 FR 38408 - Notice of Funding Availability (NOFA) for HUD's Fiscal Year 2011 HOPE VI Main Street Grants

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-30

... traditional central business district or ``Main Street'' area by replacing unused commercial space in... areas; 2. Preserve historic or traditional architecture or design features in Main Street areas; 3...

The Main Portal of the Cathedral of Monreale: First Geometric Analysis and Interpretive Assessment of Architectural Features

NASA Astrophysics Data System (ADS)

Lo Brutto, M.; Dardanelli, G.; Ebolese, D.; Milazzo, G.; Pipitone, C.; Sciortino, R.

2017-05-01

Nowadays, 3D documentation of architectural assets is becoming a demanding task for the valorisation of Cultural Heritage especially after a restoration project. The 3D documentation can be used for detailed analysis of specific elements, for monitoring the state of conservation and for valorisation actions. The paper describes the results of the 3D close-range photogrammetry survey of the main portal of the Cathedral of Monreale (Palermo, Italy). The Cathedral is one the most important monumental complexes in Sicily that, for its high historical and artistic importance has been inscribed on UNESCO's World Heritage List since 2015. The main portal of the Cathedral has been recently restored. The restoration work has given the opportunity to evidence small details of the sculptural decorations and to carry out new interpretative analysis of the bas-reliefs. The main purpose of the work is to obtain a detailed 3D model and a high-resolution ortophoto of the entire portal and of some architectural details. The study was used to evaluate the most appropriate technical solutions for the 3D survey and to define the most suitable parameters for image acquisition and data processing.

Collisionality and temperature dependence of the edge main-ion co-current rotation profile feature on DIII-D

NASA Astrophysics Data System (ADS)

Haskey, Shaun; Grierson, Brian; Ashourvan, Arash; Battaglia, Devon; Chrystal, Colin; Burrell, Keith; Groebner, Richard; Degrassie, John; Stagner, Luke; Stoltzfus-Dueck, Timothy; Pablant, Novimir

2017-10-01

A new edge main-ion (D+) CER system and upgraded edge impurity system are revealing clear differences between the main-ion and dominant impurity (C6+) toroidal rotation from the pedestal top to the scrape off layer on DIII-D with implications for intrinsic rotation studies. A peaked co-current edge toroidal rotation is observed for the main ion species near the outboard midplane separatrix with values up to 140 km/s for low collisionality QH modes. In lower power (PNBI = 0.8MW) H-modes the edge rotation is still present but reduced to 50km/s. D+ and C6+ toroidal rotation differences are presented for a variety of scenarios covering a significant range of edge collisionality and Ti. Observations are compared with predictions from several models including collisionless ion orbit loss calculations and more complete modeling using the XGC0 code, which also predicts 140km/s edge rotation for low collisionality QH mode cases. Work supported by the U.S. DOE under DE-AC02-09CH11466, No. DE-FC02-04ER54698, and DE-FC02-95ER54309.

Semi-Supervised Geographical Feature Detection

NASA Astrophysics Data System (ADS)

Yu, H.; Yu, L.; Kuo, K. S.

2016-12-01

Extraction and tracking geographical features is a fundamental requirement in many geoscience fields. However, this operation has become an increasingly challenging task for domain scientists when tackling a large amount of geoscience data. Although domain scientists may have a relatively clear definition of features, it is difficult to capture the presence of features in an accurate and efficient fashion. We propose a semi-supervised approach to address large geographical feature detection. Our approach has two main components. First, we represent a heterogeneous geoscience data in a unified high-dimensional space, which can facilitate us to evaluate the similarity of data points with respect to geolocation, time, and variable values. We characterize the data from these measures, and use a set of hash functions to parameterize the initial knowledge of the data. Second, for any user query, our approach can automatically extract the initial results based on the hash functions. To improve the accuracy of querying, our approach provides a visualization interface to display the querying results and allow users to interactively explore and refine them. The user feedback will be used to enhance our knowledge base in an iterative manner. In our implementation, we use high-performance computing techniques to accelerate the construction of hash functions. Our design facilitates a parallelization scheme for feature detection and extraction, which is a traditionally challenging problem for large-scale data. We evaluate our approach and demonstrate the effectiveness using both synthetic and real world datasets.

Classification of epileptic EEG signals based on simple random sampling and sequential feature selection.

PubMed

Ghayab, Hadi Ratham Al; Li, Yan; Abdulla, Shahab; Diykh, Mohammed; Wan, Xiangkui

2016-06-01

Electroencephalogram (EEG) signals are used broadly in the medical fields. The main applications of EEG signals are the diagnosis and treatment of diseases such as epilepsy, Alzheimer, sleep problems and so on. This paper presents a new method which extracts and selects features from multi-channel EEG signals. This research focuses on three main points. Firstly, simple random sampling (SRS) technique is used to extract features from the time domain of EEG signals. Secondly, the sequential feature selection (SFS) algorithm is applied to select the key features and to reduce the dimensionality of the data. Finally, the selected features are forwarded to a least square support vector machine (LS_SVM) classifier to classify the EEG signals. The LS_SVM classifier classified the features which are extracted and selected from the SRS and the SFS. The experimental results show that the method achieves 99.90, 99.80 and 100 % for classification accuracy, sensitivity and specificity, respectively.

Feature selection methods for big data bioinformatics: A survey from the search perspective.

PubMed

Wang, Lipo; Wang, Yaoli; Chang, Qing

2016-12-01

This paper surveys main principles of feature selection and their recent applications in big data bioinformatics. Instead of the commonly used categorization into filter, wrapper, and embedded approaches to feature selection, we formulate feature selection as a combinatorial optimization or search problem and categorize feature selection methods into exhaustive search, heuristic search, and hybrid methods, where heuristic search methods may further be categorized into those with or without data-distilled feature ranking measures. Copyright © 2016 Elsevier Inc. All rights reserved.

General view of a Space Shuttle Main Engine (SSME) mounted ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view of a Space Shuttle Main Engine (SSME) mounted on an SSME engine handler, taken in the SSME Processing Facility at Kennedy Space Center. The most prominent features of the engine assembly in this view are the Low-Pressure Fuel Turbopump Discharge Duct looping diagonally across the top of the assembly and connecting to the High-Pressure Fuel Turbopump, the Low-Pressure Oxidizer Turbopump (LPOTP) located center right of the assembly and the LPOTP Discharge Duct looping around from the pump to the underside of the engine assembly in this view. - Space Transportation System, Space Shuttle Main Engine, Lyndon B. Johnson Space Center, 2101 NASA Parkway, Houston, Harris County, TX

On the analysis of local and global features for hyperemia grading

NASA Astrophysics Data System (ADS)

Sánchez, L.; Barreira, N.; Sánchez, N.; Mosquera, A.; Pena-Verdeal, H.; Yebra-Pimentel, E.

2017-03-01

In optometry, hyperemia is the accumulation of blood flow in the conjunctival tissue. Dry eye syndrome or allergic conjunctivitis are two of its main causes. Its main symptom is the presence of a red hue in the eye that optometrists evaluate according to a scale in a subjective manner. In this paper, we propose an automatic approach to the problem of hyperemia grading in the bulbar conjunctiva. We compute several image features on images of the patients' eyes, analyse the relations among them by using feature selection techniques and transform the feature vector of each image to the value in the adequate range by means of machine learning techniques. We analyse different areas of the conjunctiva to evaluate their importance for the diagnosis. Our results show that it is possible to mimic the experts' behaviour through the proposed approach.

Feature engineering for drug name recognition in biomedical texts: feature conjunction and feature selection.

PubMed

Liu, Shengyu; Tang, Buzhou; Chen, Qingcai; Wang, Xiaolong; Fan, Xiaoming

2015-01-01

Drug name recognition (DNR) is a critical step for drug information extraction. Machine learning-based methods have been widely used for DNR with various types of features such as part-of-speech, word shape, and dictionary feature. Features used in current machine learning-based methods are usually singleton features which may be due to explosive features and a large number of noisy features when singleton features are combined into conjunction features. However, singleton features that can only capture one linguistic characteristic of a word are not sufficient to describe the information for DNR when multiple characteristics should be considered. In this study, we explore feature conjunction and feature selection for DNR, which have never been reported. We intuitively select 8 types of singleton features and combine them into conjunction features in two ways. Then, Chi-square, mutual information, and information gain are used to mine effective features. Experimental results show that feature conjunction and feature selection can improve the performance of the DNR system with a moderate number of features and our DNR system significantly outperforms the best system in the DDIExtraction 2013 challenge.

Feature hashing for fast image retrieval

NASA Astrophysics Data System (ADS)

Yan, Lingyu; Fu, Jiarun; Zhang, Hongxin; Yuan, Lu; Xu, Hui

2018-03-01

Currently, researches on content based image retrieval mainly focus on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large scale images, which is very timeconsuming and unscalable. Hence, we need to pay much attention to the efficiency of image retrieval. In this paper, we propose a feature hashing method for image retrieval which not only generates compact fingerprint for image representation, but also prevents huge semantic loss during the process of hashing. To generate the fingerprint, an objective function of semantic loss is constructed and minimized, which combine the influence of both the neighborhood structure of feature data and mapping error. Since the machine learning based hashing effectively preserves neighborhood structure of data, it yields visual words with strong discriminability. Furthermore, the generated binary codes leads image representation building to be of low-complexity, making it efficient and scalable to large scale databases. Experimental results show good performance of our approach.

Adversarial Feature Selection Against Evasion Attacks.

PubMed

Zhang, Fei; Chan, Patrick P K; Biggio, Battista; Yeung, Daniel S; Roli, Fabio

2016-03-01

Pattern recognition and machine learning techniques have been increasingly adopted in adversarial settings such as spam, intrusion, and malware detection, although their security against well-crafted attacks that aim to evade detection by manipulating data at test time has not yet been thoroughly assessed. While previous work has been mainly focused on devising adversary-aware classification algorithms to counter evasion attempts, only few authors have considered the impact of using reduced feature sets on classifier security against the same attacks. An interesting, preliminary result is that classifier security to evasion may be even worsened by the application of feature selection. In this paper, we provide a more detailed investigation of this aspect, shedding some light on the security properties of feature selection against evasion attacks. Inspired by previous work on adversary-aware classifiers, we propose a novel adversary-aware feature selection model that can improve classifier security against evasion attacks, by incorporating specific assumptions on the adversary's data manipulation strategy. We focus on an efficient, wrapper-based implementation of our approach, and experimentally validate its soundness on different application examples, including spam and malware detection.

Hybrid feature selection for supporting lightweight intrusion detection systems

NASA Astrophysics Data System (ADS)

Song, Jianglong; Zhao, Wentao; Liu, Qiang; Wang, Xin

2017-08-01

Redundant and irrelevant features not only cause high resource consumption but also degrade the performance of Intrusion Detection Systems (IDS), especially when coping with big data. These features slow down the process of training and testing in network traffic classification. Therefore, a hybrid feature selection approach in combination with wrapper and filter selection is designed in this paper to build a lightweight intrusion detection system. Two main phases are involved in this method. The first phase conducts a preliminary search for an optimal subset of features, in which the chi-square feature selection is utilized. The selected set of features from the previous phase is further refined in the second phase in a wrapper manner, in which the Random Forest(RF) is used to guide the selection process and retain an optimized set of features. After that, we build an RF-based detection model and make a fair comparison with other approaches. The experimental results on NSL-KDD datasets show that our approach results are in higher detection accuracy as well as faster training and testing processes.

Recent Development of the Two-Stroke Engine. II - Design Features. 2; Design Features

NASA Technical Reports Server (NTRS)

Zeman, J.

1945-01-01

Completing the first paper dealing with charging methods and arrangements, the present paper discusses the design forms of two-stroke engines. Features which largely influence piston running are: (a) The shape and surface condition of the sliding parts. (b) The cylinder and piston materials. (c) Heat conditions in the piston, and lubrication. There is little essential difference between four-stroke and two-stroke engines with ordinary pistons. In large engines, for example, are always found separately cast or welded frames in which the stresses are taken up by tie rods. Twin piston and timing piston engines often differ from this design. Examples can be found in many engines of German or foreign make. Their methods of operation will be dealt with in the third part of the present paper, which also includes the bibliography. The development of two-stroke engine design is, of course, mainly concerned with such features as are inherently difficult to master; that is, the piston barrel and the design of the gudgeon pin bearing. Designers of four-stroke engines now-a-days experience approximately the same difficulties, since heat stresses have increased to the point of influencing conditions in the piston barrel. Features which notably affect this are: (a) The material. (b) Prevailing heat conditions.

Main Road Extraction from ZY-3 Grayscale Imagery Based on Directional Mathematical Morphology and VGI Prior Knowledge in Urban Areas

PubMed Central

Liu, Bo; Wu, Huayi; Wang, Yandong; Liu, Wenming

2015-01-01

Main road features extracted from remotely sensed imagery play an important role in many civilian and military applications, such as updating Geographic Information System (GIS) databases, urban structure analysis, spatial data matching and road navigation. Current methods for road feature extraction from high-resolution imagery are typically based on threshold value segmentation. It is difficult however, to completely separate road features from the background. We present a new method for extracting main roads from high-resolution grayscale imagery based on directional mathematical morphology and prior knowledge obtained from the Volunteered Geographic Information found in the OpenStreetMap. The two salient steps in this strategy are: (1) using directional mathematical morphology to enhance the contrast between roads and non-roads; (2) using OpenStreetMap roads as prior knowledge to segment the remotely sensed imagery. Experiments were conducted on two ZiYuan-3 images and one QuickBird high-resolution grayscale image to compare our proposed method to other commonly used techniques for road feature extraction. The results demonstrated the validity and better performance of the proposed method for urban main road feature extraction. PMID:26397832

[Essence and main features of marketing in the market place of services and goods of the medical-manufacturing complex].

PubMed

Golukhov, G N; Reihart, D V; Shilenko, Iu V

1998-01-01

The essence and specific features of marketing are disclosed, based on the results of studies of the drug market. The market of outpatient and hospital services is analyzed using the marketing means. The succession of compartments of the marketing programs applied is presented.

Multidisciplinary analysis of Skylab photography for highway engineering purposes. [Maine

NASA Technical Reports Server (NTRS)

Stoeckeler, E. G.; Woodman, R. G. (Principal Investigator); Farrell, R. S.

1975-01-01

The author has identified the following significant results. The greatly increased resolution of ground features by Skylab as compared with LANDSAT is considered to be best in the S190B high resolution film, followed by S190A camera stations 4, 5, and 6 respectfully. Results of the study of vegetation damage sites using data derived from S190A film were disappointing. The major cause of detection problems is the graininess of the CIR film. Good results were achieved for the hydrology-land use study. Both camera systems gave better agreement with the ground truth than did LANDSAT imagery. Surficial geology and glacial landform areas were clearly visible in single scenes. Several previously unmapped or unknown features were detected, especially in eastern coastal Maine.

Vertical Feature Mask Feature Classification Flag Extraction

Atmospheric Science Data Center

2013-03-28

  Vertical Feature Mask Feature Classification Flag Extraction This routine demonstrates extraction of the ... in a CALIPSO Lidar Level 2 Vertical Feature Mask feature classification flag value. It is written in Interactive Data Language (IDL) ...

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

Fang, Ming; Albrecht, Bruce A.; Ghate, Virendra P.

This study first illustrates the utility of using the Doppler spectrum width from millimetrewavelength radar to calculate the energy dissipation rate and then to use the energy dissipation rate to study turbulence structure in a continental stratocumulus cloud. It is shown that the turbulence kinetic energy dissipation rate calculated from the radar-measured Doppler spectrum width agrees well with that calculated from the Doppler velocity power spectrum. During the 16-h stratocumulus cloud event, the small-scale turbulence contributes 40%of the total velocity variance at cloud base, 50% at normalized cloud depth=0.8 and 70% at cloud top, which suggests that small-scale turbulence playsmore » a critical role near the cloud top where the entrainment and cloud-top radiative cooling act. The 16-h mean vertical integral length scale decreases from about 160 m at cloud base to 60 m at cloud top, and this signifies that the larger scale turbulence dominates around cloud base whereas the small-scale turbulence dominates around cloud top. The energy dissipation rate, total variance and squared spectrum width exhibit diurnal variations, but unlike marine stratocumulus they are high during the day and lowest around sunset at all levels; energy dissipation rates increase at night with the intensification of the cloud-top cooling. In the normalized coordinate system, the averaged coherent structure of updrafts is characterized by low energy dissipation rates in the updraft core and higher energy dissipation rates surround the updraft core at the top and along the edges. In contrast, the energy dissipation rate is higher inside the downdraft core indicating that the downdraft core is more turbulent. The turbulence around the updraft is weaker at night and stronger during the day; the opposite is true around the downdraft. This behaviour indicates that the turbulence in the downdraft has a diurnal cycle similar to that observed in marine stratocumuluswhereas the turbulence

Mars and earth - Comparison of cold-climate features

NASA Technical Reports Server (NTRS)

Lucchitta, B. K.

1981-01-01

On earth, glacial and periglacial features are common in areas of cold climate. On Mars, the temperature of the present-day surface is appropriate for permafrost, and the presence of water is suspected from data relating to the outgassing of the planet, from remote-sensing measurements over the polar caps and elsewhere on the Martian surface, and from recognition of fluvial morphological features such as channels. These observations and the possibility that ice could be in equilibrium with the high latitudes north and south of + or - 40 deg latitude suggest that glacial and periglacial features should exist on the planet. Morphological studies based mainly on Viking pictures indicate many features that can be attributed to the action of ice. Among these features are extensive talus aprons; debris avalanches; flows that resemble glaciers or rock glaciers; ridges that look like moraines; various types of patterned ground, scalloped scarps, and chaotically collapsed terrain that could be attributed to thermokarst processes; and landforms that may reflect the interaction of volcanism and ice.

Extraction of linear features on SAR imagery

NASA Astrophysics Data System (ADS)

Liu, Junyi; Li, Deren; Mei, Xin

2006-10-01

Linear features are usually extracted from SAR imagery by a few edge detectors derived from the contrast ratio edge detector with a constant probability of false alarm. On the other hand, the Hough Transform is an elegant way of extracting global features like curve segments from binary edge images. Randomized Hough Transform can reduce the computation time and memory usage of the HT drastically. While Randomized Hough Transform will bring about a great deal of cells invalid during the randomized sample. In this paper, we propose a new approach to extract linear features on SAR imagery, which is an almost automatic algorithm based on edge detection and Randomized Hough Transform. The presented improved method makes full use of the directional information of each edge candidate points so as to solve invalid cumulate problems. Applied result is in good agreement with the theoretical study, and the main linear features on SAR imagery have been extracted automatically. The method saves storage space and computational time, which shows its effectiveness and applicability.

Further Examination of the Thermodynamic Modification of the Inflow Layer of Tropical Cyclones by Vertical Wind Shear

DTIC Science & Technology

2013-01-11

Q. J. Roy. Meteor. Soc., in review, 2012. Srivastava , R . C.: A model of intense downdrafts driven by the melt- ing and evaporation of precipitation, J...formation and intensity of downdrafts ( Srivastava , 1987). 5A brief discussion of the potential consequences of the envi- ronmental wind profile can be found...the time series is shown. (b) As in (a) but for RMN68 (da k r d), 10RMN68 (light red), ICE68 (dark grey), and 10ICE68 (light grey). Note that the tilt

General view of a Space Shuttle Main Engine (SSME) mounted ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view of a Space Shuttle Main Engine (SSME) mounted on an SSME engine handler, taken in the SSME Processing Facility at Kennedy Space Center. The most prominent features of the engine assembly in this view are the Low-Pressure Oxidizer Turbopump Discharge Duct looping around the right side of the engine assembly then turning in and connecting to the High-Pressure Oxidizer Turbopump. The sphere in the approximate center of the assembly is the POGO System Accumulator, the Engine Controller is located on the bottom and slightly left of the center of the Engine Assembly in this view. - Space Transportation System, Space Shuttle Main Engine, Lyndon B. Johnson Space Center, 2101 NASA Parkway, Houston, Harris County, TX

General view of the Space Shuttle Main Engine (SSME) assembly ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view of the Space Shuttle Main Engine (SSME) assembly with the expansion nozzle removed and resting on a cushioned mat on the floor of the SSME Processing Facility. The most prominent features in this view are the Low-Pressure Fuel Turbopump (LPFTP) on the upper left of the engine assembly, the LPFTP Discharge Duct looping around the assembly, the Gimbal Bearing on the top center of the assembly, the Electrical Interface Panel sits just below the Gimbal Bearing and the Low-Pressure Oxidizer Turbopump is mounted on the top right of the engine assembly in this view. - Space Transportation System, Space Shuttle Main Engine, Lyndon B. Johnson Space Center, 2101 NASA Parkway, Houston, Harris County, TX

Sensor feature fusion for detecting buried objects

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

Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.

1993-04-01

Given multiple registered images of the earth`s surface from dual-band sensors, our system fuses information from the sensors to reduce the effects of clutter and improve the ability to detect buried or surface target sites. The sensor suite currently includes two sensors (5 micron and 10 micron wavelengths) and one ground penetrating radar (GPR) of the wide-band pulsed synthetic aperture type. We use a supervised teaming pattern recognition approach to detect metal and plastic land mines buried in soil. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in amore » two step process to classify a subimage. Thee first step, referred to as feature selection, determines the features of sub-images which result in the greatest separability among the classes. The second step, image labeling, uses the selected features and the decisions from a pattern classifier to label the regions in the image which are likely to correspond to buried mines. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the sensors add value to the detection system. The most important features from the various sensors are fused using supervised teaming pattern classifiers (including neural networks). We present results of experiments to detect buried land mines from real data, and evaluate the usefulness of fusing feature information from multiple sensor types, including dual-band infrared and ground penetrating radar. The novelty of the work lies mostly in the combination of the algorithms and their application to the very important and currently unsolved operational problem of detecting buried land mines from an airborne standoff platform.« less

Cytological features of "noninvasive follicular thyroid neoplasm with papillary-like nuclear features" and their correlation with tumor histology.

PubMed

Maletta, Francesca; Massa, Federica; Torregrossa, Liborio; Duregon, Eleonora; Casadei, Gian Piero; Basolo, Fulvio; Tallini, Giovanni; Volante, Marco; Nikiforov, Yuri E; Papotti, Mauro

2016-08-01

Among thyroid papillary carcinomas (PTCs), the follicular variant is the most common and includes encapsulated forms (EFVPTCs). Noninvasive EFVPTCs have very low risk of recurrence or other adverse events and have been recently proposed to be designated as noninvasive follicular thyroid neoplasm with papillary-like nuclear features or NIFTP, thus eliminating the term carcinoma. This proposal is expected to significantly impact the risk of malignancy associated with the currently used diagnostic categories of thyroid cytology. In this study, we analyzed the fine needle aspiration biopsy (FNAB) cytology features of 96 histologically proven NIFTPs and determined how the main nuclear features of NIFTP correlate between cytological and histological samples. Blind review of FNAB cytology from NIFTP nodules yielded the diagnosis of "follicular neoplasm" (Bethesda category IV) in 56% of cases, "suspicious for malignancy" (category V) in 27%, "atypia of undetermined significance/follicular lesion of undetermined significance" (category III) in 15%, and "malignant" (category VI) in 2%. We found good correlation (κ=0.62) of nuclear features between histological and cytological specimens. NIFTP nuclear features (size, irregularities of contours, and chromatin clearing) were significantly different from those of benign nodules but not from those of invasive EFVPTC. Our data indicate that most of the NIFTP nodules yield an indeterminate cytological diagnosis in FNAB cytology and nuclear features found in cytology samples are reproducibly identified in corresponding histology samples. Because of the overlapping nuclear features with invasive EFVPTC, NIFTP cannot be reliably diagnosed preoperatively but should be listed in differential diagnosis of all indeterminate categories of thyroid cytology. Copyright © 2016 Elsevier Inc. All rights reserved.

Unsteady Analysis of Turbine Main Flow Coupled with Secondary Air Flow

NASA Technical Reports Server (NTRS)

Hah, Chunill

2006-01-01

Two numerical approaches are used to model the interaction between the turbine main gas flow and the wheelspace cavity seal flow. The 3-D, unsteady Reynolds-averaged Navier-Stokes equations are solved with a CFD code based on a structured grid to study the interaction between the turbine main gas flow and the wheelspace cavity seal flow. A CFD code based on an unstructured grid is used to solve detailed flow feature in the cavity seal which has a complex geometry. The numerical results confirm various observations from earlier experimental studies under similar flow conditions. When the flow rate through the rim cavity seal is increased, the ingestion of the main turbine flow into the rim seal area decreases drastically. However, a small amount of main gas flow is ingested to the rim seal area even with very high level of seal flow rate. This is due to the complex nature of 3-D, unsteady flow interaction near the hub of the turbine stage.

A harmonic linear dynamical system for prominent ECG feature extraction.

PubMed

Thi, Ngoc Anh Nguyen; Yang, Hyung-Jeong; Kim, SunHee; Do, Luu Ngoc

2014-01-01

Unsupervised mining of electrocardiography (ECG) time series is a crucial task in biomedical applications. To have efficiency of the clustering results, the prominent features extracted from preprocessing analysis on multiple ECG time series need to be investigated. In this paper, a Harmonic Linear Dynamical System is applied to discover vital prominent features via mining the evolving hidden dynamics and correlations in ECG time series. The discovery of the comprehensible and interpretable features of the proposed feature extraction methodology effectively represents the accuracy and the reliability of clustering results. Particularly, the empirical evaluation results of the proposed method demonstrate the improved performance of clustering compared to the previous main stream feature extraction approaches for ECG time series clustering tasks. Furthermore, the experimental results on real-world datasets show scalability with linear computation time to the duration of the time series.

Mapping Surface Features Produced by an Active Landslide

NASA Astrophysics Data System (ADS)

Parise, Mario; Gueguen, Erwan; Vennari, Carmela

2016-10-01

A large landslide reactivated on December 2013, at Montescaglioso, southern Italy, after 56 hours of rainfall. The landslide disrupted over 500 m of a freeway, involved a few warehouses, a supermarket, and private homes. After the event, it has been performed field surveys, aided by visual analysis of terrestrial and helicopter photographs, to compile a map of the surface deformations. The geomorphological features mapped included single fractures, sets of fractures, tension cracks, trenches, and pressure ridges. In this paper we present the methodology used, the map obtained through the intensive field work, and discuss the main surface features produced by the landslide.

Numerical study of compressible magnetoconvection with an open transitional boundary

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

Hanami, H.; Tajima, T.

1990-08-01

We study by computer simulation nonlinear evolution of magnetoconvection in a system with a dynamical open boundary between the convection region and corona of the sun. We study a model in which the fluid is subject to the vertical gravitation, magnetohydrodynamics (MHD), and high stratification, through an MHD code with the MacCormack-Donner cell hybrid scheme in order to well represent convective phenomena. Initially the vertical fluid flux penetrates from the convectively unstable zone at the bottom into the upper diffuse atmosphere. As the instability develops, the magnetic fields are twisted by the convection motion and the folding magnetic fields ismore » observed. When the magnetic pressure is comparable to the thermal pressure in the upper layer of convective zone, strong flux expulsion from the convective cell interior toward the cell boundary appears. Under appropriate conditions our simulation exhibits no shock formation incurred by the fluid convected to the photosphere, in contrast to earlier works with box boundaries. The magnetic field patterns observed are those of concentrated magnetic flux tubes, accumulation of dynamo flux near the bottom boundary, pinched flux near the downdraft region, and the surface movement of magnetic flux toward the downdraft region. Many of these computationally observed features are reminiscent of solar observations of the fluid and magnetic structures of their motions.« less

Models for some aspects of atmospheric vortices

NASA Technical Reports Server (NTRS)

Deissler, R. G.

1977-01-01

A frictionless adiabatic model is used to study the growth of random vortices in an atmosphere with buoyant instability and vertical wind shear, taking account of the effects of axial drag, heat transfer and precipitation-induced downdrafts. It is found that downdrafts of tornadic magnitude may occur in negatively buoyant columns. The radial-inflow velocity required to maintain a given maximum tangential velocity in a tornado is determined by using a turbulent vortex model. A tornado model which involves a rotating parent cloud as well as buoyancy and precipitation effects is also discussed.

Near-infrared Spectroscopy Of Outer Main Belt Asteroids

NASA Astrophysics Data System (ADS)

Takir, Driss; Emery, J.

2009-09-01

We have recently begun a spectral survey of the outer Main Belt population (3.2 AU < a < 4.6 AU), using near-infrared spectroscopy (0.8-2.5 μm). The objective of this survey is to search for signatures of H2O, organics, hydrated silicates, and/or anhydrous silicates on this group of asteroids. Studying the outer Main Belt asteroids will allow us to better understand the dynamical evolution of the Solar System and provide crucial constrains on nebular composition. Our first observing run, using the SpeX spectrograph/imager at the NASA IRTF, took place remotely form the University of Tennessee Knoxville on the nights of April 15, 16, and 17, 2009 (UT). More observing runs will be conducted this year and the beginning of next year. The initial data reduction process reveals that some of these asteroids exhibit weak and strong absorption features. We will present some of these initial spectra and results.

Heavy hydrocarbon main injector technology program

NASA Technical Reports Server (NTRS)

Arbit, H. A.; Tuegel, L. M.; Dodd, F. E.

1991-01-01

The Heavy Hydrocarbon Main Injector Program was an analytical, design, and test program to demonstrate an injection concept applicable to an Isolated Combustion Compartment of a full-scale, high pressure, LOX/RP-1 engine. Several injector patterns were tested in a 3.4-in. combustor. Based on these results, features of the most promising injector design were incorporated into a 5.7-in. injector which was then hot-fire tested. In turn, a preliminary design of a 5-compartment 2D combustor was based on this pattern. Also the additional subscale injector testing and analysis was performed with an emphasis on improving analytical techniques and acoustic cavity design methodology. Several of the existing 3.5-in. diameter injectors were hot-fire tested with and without acoustic cavities for spontaneous and dynamic stability characteristics.

Closeup view of the bottom area of Space Shuttle Main ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Close-up view of the bottom area of Space Shuttle Main Engine (SSME) 2052 engine assembly mounted in a SSME Engine Handler in the Horizontal Processing area of the SSME Processing Facility at Kennedy Space Center. The most prominent features in this view are the Low-Pressure Oxidizer Discharge Duct toward the bottom of the assembly, the SSME Engine Controller and the Main Fuel Valve Hydraulic Actuator are in the approximate center of the assembly in this view, the Low-Pressure Fuel Turbopump (LPFTP), the LPFTP Discharge Duct are to the left on the assembly in this view and the High-Pressure Fuel Turbopump is located toward the top of the engine assembly in this view. The ring of tabs in the right side of the image, at the approximate location of the Nozzle and the Coolant Outlet Manifold interface is the Heat Shield Support Ring. - Space Transportation System, Space Shuttle Main Engine, Lyndon B. Johnson Space Center, 2101 NASA Parkway, Houston, Harris County, TX

General view of a Space Shuttle Main Engine (SSME) mounted ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view of a Space Shuttle Main Engine (SSME) mounted on an SSME engine handler, taken in the SSME Processing Facility at Kennedy Space Center. The most prominent feature in this view is the Expansion Nozzle . The rings that loop around the nozzle, vertically in this view, add structural stability to the nozzle walls and are referred to Hatbands. The ring on the left most edge of the nozzle is the Coolant Inlet Manifold. The tubes that branch off and connect to the manifold are Coolant Transfer Ducts and the tubes that terminate with a visible opening at the manifold are Drain Lines. - Space Transportation System, Space Shuttle Main Engine, Lyndon B. Johnson Space Center, 2101 NASA Parkway, Houston, Harris County, TX

Closeup view of a Space Shuttle Main Engine (SSME) mounted ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Close-up view of a Space Shuttle Main Engine (SSME) mounted on an SSME engine handler, taken in the SSME Processing Facility at Kennedy Space Center. The most prominent feature in this view is the Expansion Nozzle . The rings that loop around the nozzle, vertically in this view, add structural stability to the nozzle walls and are referred to Hatbands. The ring on the left most edge of the nozzle is the Coolant Inlet Manifold. The tubes that branch off and connect to the manifold are Coolant Transfer Ducts and the tubes that terminate with a visible opening at the manifold are Drain Lines. - Space Transportation System, Space Shuttle Main Engine, Lyndon B. Johnson Space Center, 2101 NASA Parkway, Houston, Harris County, TX

Closeup view of the top of Space Shuttle Main Engine ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Close-up view of the top of Space Shuttle Main Engine (SSME) 2057 mounted in a SSME Engine Handler in the Vertical Processing area of the SSME Processing Facility at Kennedy Space Center. The most prominent components in this view is the large Low-Pressure Oxidizer Turbopump (LPOTP) Discharge Duct wrapping itself around the right side of the engine assembly. The smaller tube to the left of LPOTP Discharge Duct is the High-Pressure Oxidizer Duct used to supply the turbine of the LPOTP. The other major feature in this view is the Low-Pressure Fuel Turbopump at the top of the engine assembly. - Space Transportation System, Space Shuttle Main Engine, Lyndon B. Johnson Space Center, 2101 NASA Parkway, Houston, Harris County, TX

STE thrust chamber technology: Main injector technology program and nozzle Advanced Development Program (ADP)

NASA Technical Reports Server (NTRS)

1993-01-01

The purpose of the STME Main Injector Program was to enhance the technology base for the large-scale main injector-combustor system of oxygen-hydrogen booster engines in the areas of combustion efficiency, chamber heating rates, and combustion stability. The initial task of the Main Injector Program, focused on analysis and theoretical predictions using existing models, was complemented by the design, fabrication, and test at MSFC of a subscale calorimetric, 40,000-pound thrust class, axisymmetric thrust chamber operating at approximately 2,250 psi and a 7:1 expansion ratio. Test results were used to further define combustion stability bounds, combustion efficiency, and heating rates using a large injector scale similar to the Pratt & Whitney (P&W) STME main injector design configuration including the tangential entry swirl coaxial injection elements. The subscale combustion data was used to verify and refine analytical modeling simulation and extend the database range to guide the design of the large-scale system main injector. The subscale injector design incorporated fuel and oxidizer flow area control features which could be varied; this allowed testing of several design points so that the STME conditions could be bracketed. The subscale injector design also incorporated high-reliability and low-cost fabrication techniques such as a one-piece electrical discharged machined (EDMed) interpropellant plate. Both subscale and large-scale injectors incorporated outer row injector elements with scarfed tip features to allow evaluation of reduced heating rates to the combustion chamber.

Late electrophysiological modulations of feature-based attention to object shapes.

PubMed

Stojanoski, Bobby Boge; Niemeier, Matthias

2014-03-01

Feature-based attention has been shown to aid object perception. Our previous ERP effects revealed temporally late feature-based modulation in response to objects relative to motion. The aim of the current study was to confirm the timing of feature-based influences on object perception while cueing within the feature dimension of shape. Participants were told to expect either "pillow" or "flower" objects embedded among random white and black lines. Participants more accurately reported the object's main color for valid compared to invalid shapes. ERPs revealed modulation from 252-502 ms, from occipital to frontal electrodes. Our results are consistent with previous findings examining the time course for processing similar stimuli (illusory contours). Our results provide novel insights into how attending to features of higher complexity aids object perception presumably via feed-forward and feedback mechanisms along the visual hierarchy. Copyright © 2014 Society for Psychophysiological Research.

[Acute cholangitis in interstenosis space accompanied by two-component unit of the main bile duct].

PubMed

Yurchenko, V V

2016-02-01

Palliative treatment of obstructive jaundice with the help of biliary endoprosthesis due to the possible complication of post-intervention in the form of insolvency stent deformation or dislocation. The study features in the postoperative period of the main bile duct endoprosthesis about their two-component unit, described the syndrome of the closed space of the bile ducts. On the basis of observation of 14 patients with the given anatomical feature of endoscopic, who were underwent stenting, was assessed frequency of the syndrome and possibilities of its prevention. Interstenosis space expansion of the main bile duct can be a reason for local cholangitis. For the prevention of cholangitis, it should be carried out a separate drainage of interstenosis space with the help of endoprosthesis or by proximal supra-stenotic extension of two or more stents.

The origin of infrasonic ionosphere oscillations over tropospheric thunderstorms

NASA Astrophysics Data System (ADS)

Shao, Xuan-Min; Lay, Erin H.

2016-07-01

Thunderstorms have been observed to introduce infrasonic oscillations in the ionosphere, but it is not clear what processes or which parts of the thunderstorm generate the oscillations. In this paper, we present a new technique that uses an array of ground-based GPS total electron content (TEC) measurements to locate the source of the infrasonic oscillations and compare the source locations with thunderstorm features to understand the possible source mechanisms. The location technique utilizes instantaneous phase differences between pairs of GPS-TEC measurements and an algorithm to best fit the measured and the expected phase differences for assumed source positions and other related parameters. In this preliminary study, the infrasound waves are assumed to propagate along simple geometric raypaths from the source to the measurement locations to avoid extensive computations. The located sources are compared in time and space with thunderstorm development and lightning activity. Sources are often found near the main storm cells, but they are more likely related to the downdraft process than to the updraft process. The sources are also commonly found in the convectively quiet stratiform regions behind active cells and are in good coincidence with extensive lightning discharges and inferred high-altitude sprites discharges.

Numerical Modeling of the Global Atmosphere

NASA Technical Reports Server (NTRS)

Arakawa, Akio; Mechoso, Carlos R.

1996-01-01

Under this grant, we continued development and evaluation of the updraft downdraft model for cumulus parameterization. The model includes the mass, rainwater and vertical momentum budget equations for both updrafts and downdrafts. The rainwater generated in an updraft falls partly inside and partly outside the updraft. Two types of stationary solutions are identified for the coupled rainwater budget and vertical momentum equations: (1) solutions for small tilting angles, which are unstable; (2) solutions for large tilting angles, which are stable. In practical applications, we select the smallest stable tilting angle as an optimum value. The model has been incorporated into the Arakawa-Schubert (A-S) cumulus parameterization. The results of semi-prognostic and single-column prognostic tests of the revised A-S parameterization show drastic improvement in predicting the humidity field. Cheng and Arakawa presents the rationale and basic design of the updraft-downdraft model, together with these test results. Cheng and Arakawa, on the other hand gives technical details of the model as implemented in current version of the UCLA GCM.

Music psychopathology. V. Objective features of instrumental performance and psychopathology.

PubMed

Steinberg, R; Fani, M; Raith, L

1992-01-01

Mental disease systematically impairs musical expression according to nosologic classification. This was demonstrated with a polarity profile of the instrumental performances of 60 inpatients and 14 controls matched for musical aptitude. Objective performance characteristics such as irregularities and playing faults were analyzed too. No meaningful correlation between these features and psychopathology resulted. This indicates that even in severe psychopathologic alterations performance features, which depend mainly on education and actual training, are not altered in a systematic manner, in contrast to expressive qualities.

Layout optimization with assist features placement by model based rule tables for 2x node random contact

NASA Astrophysics Data System (ADS)

Jun, Jinhyuck; Park, Minwoo; Park, Chanha; Yang, Hyunjo; Yim, Donggyu; Do, Munhoe; Lee, Dongchan; Kim, Taehoon; Choi, Junghoe; Luk-Pat, Gerard; Miloslavsky, Alex

2015-03-01

As the industry pushes to ever more complex illumination schemes to increase resolution for next generation memory and logic circuits, sub-resolution assist feature (SRAF) placement requirements become increasingly severe. Therefore device manufacturers are evaluating improvements in SRAF placement algorithms which do not sacrifice main feature (MF) patterning capability. There are known-well several methods to generate SRAF such as Rule based Assist Features (RBAF), Model Based Assist Features (MBAF) and Hybrid Assisted Features combining features of the different algorithms using both RBAF and MBAF. Rule Based Assist Features (RBAF) continue to be deployed, even with the availability of Model Based Assist Features (MBAF) and Inverse Lithography Technology (ILT). Certainly for the 3x nm node, and even at the 2x nm nodes and lower, RBAF is used because it demands less run time and provides better consistency. Since RBAF is needed now and in the future, what is also needed is a faster method to create the AF rule tables. The current method typically involves making masks and printing wafers that contain several experiments, varying the main feature configurations, AF configurations, dose conditions, and defocus conditions - this is a time consuming and expensive process. In addition, as the technology node shrinks, wafer process changes and source shape redesigns occur more frequently, escalating the cost of rule table creation. Furthermore, as the demand on process margin escalates, there is a greater need for multiple rule tables: each tailored to a specific set of main-feature configurations. Model Assisted Rule Tables(MART) creates a set of test patterns, and evaluates the simulated CD at nominal conditions, defocused conditions and off-dose conditions. It also uses lithographic simulation to evaluate the likelihood of AF printing. It then analyzes the simulation data to automatically create AF rule tables. It means that analysis results display the cost of

Content-based cell pathology image retrieval by combining different features

NASA Astrophysics Data System (ADS)

Zhou, Guangquan; Jiang, Lu; Luo, Limin; Bao, Xudong; Shu, Huazhong

2004-04-01

Content Based Color Cell Pathology Image Retrieval is one of the newest computer image processing applications in medicine. Recently, some algorithms have been developed to achieve this goal. Because of the particularity of cell pathology images, the result of the image retrieval based on single characteristic is not satisfactory. A new method for pathology image retrieval by combining color, texture and morphologic features to search cell images is proposed. Firstly, nucleus regions of leukocytes in images are automatically segmented by K-mean clustering method. Then single leukocyte region is detected by utilizing thresholding algorithm segmentation and mathematics morphology. The features that include color, texture and morphologic features are extracted from single leukocyte to represent main attribute in the search query. The features are then normalized because the numerical value range and physical meaning of extracted features are different. Finally, the relevance feedback system is introduced. So that the system can automatically adjust the weights of different features and improve the results of retrieval system according to the feedback information. Retrieval results using the proposed method fit closely with human perception and are better than those obtained with the methods based on single feature.

LBT Distributed Archive: Status and Features

NASA Astrophysics Data System (ADS)

Knapic, C.; Smareglia, R.; Thompson, D.; Grede, G.

2011-07-01

After the first release of the LBT Distributed Archive, this successful collaboration is continuing within the LBT corporation. The IA2 (Italian Center for Astronomical Archive) team had updated the LBT DA with new features in order to facilitate user data retrieval while abiding by VO standards. To facilitate the integration of data from any new instruments, we have migrated to a new database, developed new data distribution software, and enhanced features in the LBT User Interface. The DBMS engine has been changed to MySQL. Consequently, the data handling software now uses java thread technology to update and synchronize the main storage archives on Mt. Graham and in Tucson, as well as archives in Trieste and Heidelberg, with all metadata and proprietary data. The LBT UI has been updated with additional features allowing users to search by instrument and some of the more important characteristics of the images. Finally, instead of a simple cone search service over all LBT image data, new instrument specific SIAP and cone search services have been developed. They will be published in the IVOA framework later this fall.

Convective cloud vertical velocity and mass-flux characteristics from radar wind profiler observations during GoAmazon2014/5: VERTICAL VELOCITY GOAMAZON2014/5

DOE PAGES

Giangrande, Scott E.; Toto, Tami; Jensen, Michael P.; ...

2016-11-15

A radar wind profiler data set collected during the 2 year Department of Energy Atmospheric Radiation Measurement Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) campaign is used to estimate convective cloud vertical velocity, area fraction, and mass flux profiles. Vertical velocity observations are presented using cumulative frequency histograms and weighted mean profiles to provide insights in a manner suitable for global climate model scale comparisons (spatial domains from 20 km to 60 km). Convective profile sensitivity to changes in environmental conditions and seasonal regime controls is also considered. Aggregate and ensemble average vertical velocity, convective area fraction, andmore » mass flux profiles, as well as magnitudes and relative profile behaviors, are found consistent with previous studies. Updrafts and downdrafts increase in magnitude with height to midlevels (6 to 10 km), with updraft area also increasing with height. Updraft mass flux profiles similarly increase with height, showing a peak in magnitude near 8 km. Downdrafts are observed to be most frequent below the freezing level, with downdraft area monotonically decreasing with height. Updraft and downdraft profile behaviors are further stratified according to environmental controls. These results indicate stronger vertical velocity profile behaviors under higher convective available potential energy and lower low-level moisture conditions. Sharp contrasts in convective area fraction and mass flux profiles are most pronounced when retrievals are segregated according to Amazonian wet and dry season conditions. During this deployment, wet season regimes favored higher domain mass flux profiles, attributed to more frequent convection that offsets weaker average convective cell vertical velocities.« less

Diverse Electron and Ion Acceleration Characteristics Observed Over Jupiter's Main Aurora

NASA Astrophysics Data System (ADS)

Mauk, B. H.; Haggerty, D. K.; Paranicas, C.; Clark, G.; Kollmann, P.; Rymer, A. M.; Peachey, J. M.; Bolton, S. J.; Levin, S. M.; Adriani, A.; Allegrini, F.; Bagenal, F.; Bonfond, B.; Connerney, J. E. P.; Ebert, R. W.; Gladstone, G. R.; Kurth, W. S.; McComas, D. J.; Ranquist, D.; Valek, P.

2018-02-01

Two new Juno-observed particle features of Jupiter's main aurora demonstrate substantial diversity of processes generating Jupiter's mysterious auroral emissions. It was previously speculated that sometimes-observed potential-driven aurora (up to 400 kV) can turn into broadband stochastic acceleration (dominating at Jupiter) by means of instability. Here direct evidence for such a process is revealed with a "mono-energetic" electron inverted-V rising in energy to 200 keV, transforming into a region of broadband acceleration with downward energy fluxes tripling to 3,000 mW/m2, and then transforming back into a mono-energetic structure ramping down from 200 keV. But a second feature of interest observed nearby is unlikely to have operated in the same way. Here a downward accelerated proton inverted-V, with inferred potentials to 300-400 kV, occurred simultaneously with downward accelerated broadband electrons with downward energy fluxes as high as any observed ( 3,000 mW/m2). This latter feature has no known precedent with Earth auroral observations.

Convolutional neural network features based change detection in satellite images

NASA Astrophysics Data System (ADS)

Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

2016-07-01

With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

A prototype feature system for feature retrieval using relationships

USGS Publications Warehouse

Choi, J.; Usery, E.L.

2009-01-01

Using a feature data model, geographic phenomena can be represented effectively by integrating space, theme, and time. This paper extends and implements a feature data model that supports query and visualization of geographic features using their non-spatial and temporal relationships. A prototype feature-oriented geographic information system (FOGIS) is then developed and storage of features named Feature Database is designed. Buildings from the U.S. Marine Corps Base, Camp Lejeune, North Carolina and subways in Chicago, Illinois are used to test the developed system. The results of the applications show the strength of the feature data model and the developed system 'FOGIS' when they utilize non-spatial and temporal relationships in order to retrieve and visualize individual features.

Lightweight Boom For Rescue Helicopter

NASA Technical Reports Server (NTRS)

Haslim, Leonard A.

1993-01-01

Telescoping boom and associated mechanisms attached to helicopter aid rescue operations by extending lifeline beyond sweep of main rotor. Pilot observes rescuee and control position of helicopter more effectively than if rescuee directly below and hidden from pilot's view. Rescuee outside downdraft of rotor, which is often powerful enough to blow away or submerge someone in water. Used for marine or land operations. Boom thin and lightweight because it need not support weight of rescuee. Lifeline pulls away from boom after secured around rescuee, who is lifted directly into cabin by winch. Potential application for in situ erection of telescopic space structures.

Dynamo action in stratified convection with overshoot

NASA Technical Reports Server (NTRS)

Nordlund, Ake; Brandenburg, Axel; Jennings, Richard L.; Rieutord, Michel; Ruokolainen, Juha; Stein, Robert F.; Tuominen, Ilkka

1992-01-01

Results are presented from direct simulations of turbulent compressible hydromagnetic convection above a stable overshoot layer. Spontaneous dynamo action occurs followed by saturation, with most of the generated magnetic field appearing as coherent flux tubes in the vicinity of strong downdrafts, where both the generation and destruction of magnetic field is most vigorous. Whether or not this field is amplified depends on the sizes of the magnetic Reynolds and magnetic Prandtl numbers. Joule dissipation is balanced mainly by the work done against the magnetic curvature force. It is this curvature force which is also responsible for the saturation of the dynamo.

Exploring spatial-temporal dynamics of fire regime features in mainland Spain

NASA Astrophysics Data System (ADS)

Jiménez-Ruano, Adrián; Rodrigues Mimbrero, Marcos; de la Riva Fernández, Juan

2017-10-01

This paper explores spatial-temporal dynamics in fire regime features, such as fire frequency, burnt area, large fires and natural- and human-caused fires, as an essential part of fire regime characterization. Changes in fire features are analysed at different spatial - regional and provincial/NUTS3 - levels, together with summer and winter temporal scales, using historical fire data from Spain for the period 1974-2013. Temporal shifts in fire features are investigated by means of change point detection procedures - Pettitt test, AMOC (at most one change), PELT (pruned exact linear time) and BinSeg (binary segmentation) - at a regional level to identify changes in the time series of the features. A trend analysis was conducted using the Mann-Kendall and Sen's slope tests at both the regional and NUTS3 level. Finally, we applied a principal component analysis (PCA) and varimax rotation to trend outputs - mainly Sen's slope values - to summarize overall temporal behaviour and to explore potential links in the evolution of fire features. Our results suggest that most fire features show remarkable shifts between the late 1980s and the first half of the 1990s. Mann-Kendall outputs revealed negative trends in the Mediterranean region. Results from Sen's slope suggest high spatial and intra-annual variability across the study area. Fire activity related to human sources seems to be experiencing an overall decrease in the northwestern provinces, particularly pronounced during summer. Similarly, the Hinterland and the Mediterranean coast are gradually becoming less fire affected. Finally, PCA enabled trends to be synthesized into four main components: winter fire frequency (PC1), summer burnt area (PC2), large fires (PC3) and natural fires (PC4).

Feature selection in feature network models: finding predictive subsets of features with the Positive Lasso.

PubMed

Frank, Laurence E; Heiser, Willem J

2008-05-01

A set of features is the basis for the network representation of proximity data achieved by feature network models (FNMs). Features are binary variables that characterize the objects in an experiment, with some measure of proximity as response variable. Sometimes features are provided by theory and play an important role in the construction of the experimental conditions. In some research settings, the features are not known a priori. This paper shows how to generate features in this situation and how to select an adequate subset of features that takes into account a good compromise between model fit and model complexity, using a new version of least angle regression that restricts coefficients to be non-negative, called the Positive Lasso. It will be shown that features can be generated efficiently with Gray codes that are naturally linked to the FNMs. The model selection strategy makes use of the fact that FNM can be considered as univariate multiple regression model. A simulation study shows that the proposed strategy leads to satisfactory results if the number of objects is less than or equal to 22. If the number of objects is larger than 22, the number of features selected by our method exceeds the true number of features in some conditions.

Temporal properties of material categorization and material rating: visual vs non-visual material features.

PubMed

Nagai, Takehiro; Matsushima, Toshiki; Koida, Kowa; Tani, Yusuke; Kitazaki, Michiteru; Nakauchi, Shigeki

2015-10-01

Humans can visually recognize material categories of objects, such as glass, stone, and plastic, easily. However, little is known about the kinds of surface quality features that contribute to such material class recognition. In this paper, we examine the relationship between perceptual surface features and material category discrimination performance for pictures of materials, focusing on temporal aspects, including reaction time and effects of stimulus duration. The stimuli were pictures of objects with an identical shape but made of different materials that could be categorized into seven classes (glass, plastic, metal, stone, wood, leather, and fabric). In a pre-experiment, observers rated the pictures on nine surface features, including visual (e.g., glossiness and transparency) and non-visual features (e.g., heaviness and warmness), on a 7-point scale. In the main experiments, observers judged whether two simultaneously presented pictures were classified as the same or different material category. Reaction times and effects of stimulus duration were measured. The results showed that visual feature ratings were correlated with material discrimination performance for short reaction times or short stimulus durations, while non-visual feature ratings were correlated only with performance for long reaction times or long stimulus durations. These results suggest that the mechanisms underlying visual and non-visual feature processing may differ in terms of processing time, although the cause is unclear. Visual surface features may mainly contribute to material recognition in daily life, while non-visual features may contribute only weakly, if at all. Copyright © 2014 Elsevier Ltd. All rights reserved.

Feature integration, attention, and fixations during visual search.

PubMed

Khani, Abbas; Ordikhani-Seyedlar, Mehdi

2017-01-01

We argue that mechanistic premises of "item-based" theories are not invalidated by the fixation-based approach. We use item-based theories to propose an account that does not advocate strict serial item processing and integrates fixations. The main focus of this account is feature integration within fixations. We also suggest that perceptual load determines the size of the fixations.

Cultural Diffusion Was the Main Driving Mechanism of the Neolithic Transition in Southern Africa

PubMed Central

Jerardino, Antonieta; Fort, Joaquim; Isern, Neus; Rondelli, Bernardo

2014-01-01

It is well known that the Neolithic transition spread across Europe at a speed of about 1 km/yr. This result has been previously interpreted as a range expansion of the Neolithic driven mainly by demic diffusion (whereas cultural diffusion played a secondary role). However, a long-standing problem is whether this value (1 km/yr) and its interpretation (mainly demic diffusion) are characteristic only of Europe or universal (i.e. intrinsic features of Neolithic transitions all over the world). So far Neolithic spread rates outside Europe have been barely measured, and Neolithic spread rates substantially faster than 1 km/yr have not been previously reported. Here we show that the transition from hunting and gathering into herding in southern Africa spread at a rate of about 2.4 km/yr, i.e. about twice faster than the European Neolithic transition. Thus the value 1 km/yr is not a universal feature of Neolithic transitions in the world. Resorting to a recent demic-cultural wave-of-advance model, we also find that the main mechanism at work in the southern African Neolithic spread was cultural diffusion (whereas demic diffusion played a secondary role). This is in sharp contrast to the European Neolithic. Our results further suggest that Neolithic spread rates could be mainly driven by cultural diffusion in cases where the final state of this transition is herding/pastoralism (such as in southern Africa) rather than farming and stockbreeding (as in Europe). PMID:25517968

The granulocytes are the main immunocompetent hemocytes in Crassostrea gigas.

PubMed

Wang, Weilin; Li, Meijia; Wang, Lingling; Chen, Hao; Liu, Zhaoqun; Jia, Zhihao; Qiu, Limei; Song, Linsheng

2017-02-01

Hemocytes comprise diverse cell types with morphological and functional heterogeneity and play indispensable roles in immunological homeostasis of invertebrates. The morphological classification of different hemocytes in mollusk has been studied since the 1970's, yet the involvement of the different sub-populations in immune functions is far from clear. In the present study, three types of hemocytes were morphologically identified and separated as agranulocytes, semi-granulocytes and granulocytes by flow cytometry and Percoll ® density gradient centrifugation. The granulocytes were characterized functionally as the main phagocytic and encapsulating population, while semi-granulocytes and agranulocytes exhibited low or no such capacities, respectively. Meanwhile, the lysosome activity and the productions of ROS and NO were all mainly concentrated in granulocytes under both normal and immune-activated situations. Further, the mRNA transcripts of some immune related genes, including CgTLR, CgClathrin, CgATPeV, CgLysozyme, CgDefensin and CgIL-17, were mainly expressed in granulocytes, lower in semi-granulocytes and agranulocytes. These results collectively suggested that the granulocytes were the main immunocompetent hemocytes in oyster C. gigas, and a differentiation relationship among these three sub-population hemocytes was inferred based on the gradual changes in morphological, functional and molecular features. Copyright © 2016 Elsevier Ltd. All rights reserved.

Distinguish self- and hetero-perceived stress through behavioral imaging and physiological features.

PubMed

Spodenkiewicz, Michel; Aigrain, Jonathan; Bourvis, Nadège; Dubuisson, Séverine; Chetouani, Mohamed; Cohen, David

2018-03-02

Stress reactivity is a complex phenomenon associated to multiple and multimodal expressions. Response to stressors has an obvious survival function and may be seen as an internal regulation to adapt to threat or danger. The intensity of this internal response can be assessed as the self-perception of the stress response. In species with social organization, this response also serves a communicative function, so-called hetero-perception. Our study presents multimodal stress detection assessment - a new methodology combining behavioral imaging and physiological monitoring for analyzing stress from these two perspectives. The system is based on automatic extraction of 39 behavioral (2D+3D video recording) and 62 physiological (Nexus-10 recording) features during a socially evaluated mental arithmetic test. The analysis with machine learning techniques for automatic classification using Support Vector Machine (SVM) show that self-perception and hetero-perception of social stress are both close but different phenomena: self-perception was significantly correlated with hetero-perception but significantly differed from it. Also, assessing stress with SVM through multimodality gave excellent classification results (F1 score values: 0.9±0.012 for hetero-perception and 0.87±0.021 for self-perception). In the best selected feature subsets, we found some common behavioral and physiological features that allow classification of both self- and hetero-perceived stress. However, we also found the contributing features for automatic classifications had opposite distributions: self-perception classification was mainly based on physiological features and hetero-perception was mainly based on behavioral features. Copyright © 2017. Published by Elsevier Inc.

Space shuttle main engine fault detection using neural networks

NASA Technical Reports Server (NTRS)

Bishop, Thomas; Greenwood, Dan; Shew, Kenneth; Stevenson, Fareed

1991-01-01

A method for on-line Space Shuttle Main Engine (SSME) anomaly detection and fault typing using a feedback neural network is described. The method involves the computation of features representing time-variance of SSME sensor parameters, using historical test case data. The network is trained, using backpropagation, to recognize a set of fault cases. The network is then able to diagnose new fault cases correctly. An essential element of the training technique is the inclusion of randomly generated data along with the real data, in order to span the entire input space of potential non-nominal data.

A method for real-time implementation of HOG feature extraction

NASA Astrophysics Data System (ADS)

Luo, Hai-bo; Yu, Xin-rong; Liu, Hong-mei; Ding, Qing-hai

2011-08-01

Histogram of oriented gradient (HOG) is an efficient feature extraction scheme, and HOG descriptors are feature descriptors which is widely used in computer vision and image processing for the purpose of biometrics, target tracking, automatic target detection(ATD) and automatic target recognition(ATR) etc. However, computation of HOG feature extraction is unsuitable for hardware implementation since it includes complicated operations. In this paper, the optimal design method and theory frame for real-time HOG feature extraction based on FPGA were proposed. The main principle is as follows: firstly, the parallel gradient computing unit circuit based on parallel pipeline structure was designed. Secondly, the calculation of arctangent and square root operation was simplified. Finally, a histogram generator based on parallel pipeline structure was designed to calculate the histogram of each sub-region. Experimental results showed that the HOG extraction can be implemented in a pixel period by these computing units.

Critical product features' identification using an opinion analyzer.

PubMed

Shamim, Azra; Balakrishnan, Vimala; Tahir, Muhammad; Shiraz, Muhammad

2014-01-01

The increasing use and ubiquity of the Internet facilitate dissemination of word-of-mouth through blogs, online forums, newsgroups, and consumer's reviews. Online consumer's reviews present tremendous opportunities and challenges for consumers and marketers. One of the challenges is to develop interactive marketing practices for making connections with target consumers that capitalize consumer-to-consumer communications for generating product adoption. Opinion mining is employed in marketing to help consumers and enterprises in the analysis of online consumers' reviews by highlighting the strengths and weaknesses of the products. This paper describes an opinion mining system based on novel review and feature ranking methods to empower consumers and enterprises for identifying critical product features from enormous consumers' reviews. Consumers and business analysts are the main target group for the proposed system who want to explore consumers' feedback for determining purchase decisions and enterprise strategies. We evaluate the proposed system on real dataset. Results show that integration of review and feature-ranking methods improves the decision making processes significantly.

Borderline personality features in depressed or anxious patients.

PubMed

Distel, Marijn A; Smit, Johannes H; Spinhoven, Philip; Penninx, Brenda W J H

2016-07-30

Anxiety and depression frequently co-occur with borderline personality disorder. Relatively little research examined the presence of borderline personality features and its main domains (affective instability, identity problems, negative relationships and self-harm) in individuals with remitted and current anxiety and depression. Participants with current (n=597) or remitted (n=1115) anxiety and/or depression and healthy controls (n=431) were selected from the Netherlands Study of Depression and Anxiety. Assessments included the Personality Assessment Inventory - Borderline Features Scale and several clinical characteristics of anxiety and depression. Borderline personality features were more common in depression than in anxiety. Current comorbid anxiety and depression was associated with most borderline personality features. Anxiety and depression status explained 29.7% of the variance in borderline personality features and 3.8% (self-harm) to 31% (identity problems) of the variance in the four domains. A large part of the variance was shared between anxiety and depression but both disorders also explained a significant amount of unique variance. The severity of anxiety and depression and the level of daily dysfunctioning was positively associated with borderline personality features. Individuals with a longer duration of anxiety and depression showed more affective instability and identity problems. These findings suggest that patients with anxiety and depression may benefit from an assessment of personality pathology as it may have implications for psychological and pharmacological treatment. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Enhancing facial features by using clear facial features

NASA Astrophysics Data System (ADS)

Rofoo, Fanar Fareed Hanna

2017-09-01

The similarity of features between individuals of same ethnicity motivated the idea of this project. The idea of this project is to extract features of clear facial image and impose them on blurred facial image of same ethnic origin as an approach to enhance a blurred facial image. A database of clear images containing 30 individuals equally divided to five different ethnicities which were Arab, African, Chines, European and Indian. Software was built to perform pre-processing on images in order to align the features of clear and blurred images. And the idea was to extract features of clear facial image or template built from clear facial images using wavelet transformation to impose them on blurred image by using reverse wavelet. The results of this approach did not come well as all the features did not align together as in most cases the eyes were aligned but the nose or mouth were not aligned. Then we decided in the next approach to deal with features separately but in the result in some cases a blocky effect was present on features due to not having close matching features. In general the available small database did not help to achieve the goal results, because of the number of available individuals. The color information and features similarity could be more investigated to achieve better results by having larger database as well as improving the process of enhancement by the availability of closer matches in each ethnicity.

Spatial features register: toward standardization of spatial features

USGS Publications Warehouse

Cascio, Janette

1994-01-01

As the need to share spatial data increases, more than agreement on a common format is needed to ensure that the data is meaningful to both the importer and the exporter. Effective data transfer also requires common definitions of spatial features. To achieve this, part 2 of the Spatial Data Transfer Standard (SDTS) provides a model for a spatial features data content specification and a glossary of features and attributes that fit this model. The model provides a foundation for standardizing spatial features. The glossary now contains only a limited subset of hydrographic and topographic features. For it to be useful, terms and definitions must be included for other categories, such as base cartographic, bathymetric, cadastral, cultural and demographic, geodetic, geologic, ground transportation, international boundaries, soils, vegetation, water, and wetlands, and the set of hydrographic and topographic features must be expanded. This paper will review the philosophy of the SDTS part 2 and the current plans for creating a national spatial features register as one mechanism for maintaining part 2.

Deep Learning Methods for Underwater Target Feature Extraction and Recognition

PubMed Central

Peng, Yuan; Qiu, Mengran; Shi, Jianfei; Liu, Liangliang

2018-01-01

The classification and recognition technology of underwater acoustic signal were always an important research content in the field of underwater acoustic signal processing. Currently, wavelet transform, Hilbert-Huang transform, and Mel frequency cepstral coefficients are used as a method of underwater acoustic signal feature extraction. In this paper, a method for feature extraction and identification of underwater noise data based on CNN and ELM is proposed. An automatic feature extraction method of underwater acoustic signals is proposed using depth convolution network. An underwater target recognition classifier is based on extreme learning machine. Although convolution neural networks can execute both feature extraction and classification, their function mainly relies on a full connection layer, which is trained by gradient descent-based; the generalization ability is limited and suboptimal, so an extreme learning machine (ELM) was used in classification stage. Firstly, CNN learns deep and robust features, followed by the removing of the fully connected layers. Then ELM fed with the CNN features is used as the classifier to conduct an excellent classification. Experiments on the actual data set of civil ships obtained 93.04% recognition rate; compared to the traditional Mel frequency cepstral coefficients and Hilbert-Huang feature, recognition rate greatly improved. PMID:29780407

Aqueous alteration on main-belt asteroids

NASA Astrophysics Data System (ADS)

Fornasier, S.; Lantz, C.; Barucci, M.; Lazzarin, M.

2014-07-01

The study of aqueous alteration is particularly important for unraveling the processes occurring during the earliest times in Solar System history, as it can give information both on the thermal processes and on the localization of water sources in the asteroid belt, and for the associated astrobiological implications. The aqueous alteration process produces the low temperature (< 320 K) chemical alteration of materials by liquid water which acts as a solvent and produces materials like phyllosilicates, sulphates, oxides, carbonates, and hydroxides. This means that liquid water was present in the primordial asteroids, produced by the melting of water ice by heating sources, very probably by ^{26}Al decay. Hydrated minerals have been found mainly on Mars surface, on primitive main-belt asteroids (C, G, B, F, and P-type, following the classification scheme by Tholen, 1984) and possibly also on few transneptunian objects. Reflectance spectroscopy of aqueous altered asteroids shows absorption features in the 0.6-0.9 and 2.5-3.5-micron regions, which are diagnostic of, or associated with, hydrated minerals. In this work, we investigate the aqueous alteration process on a large sample of 600 visible spectra of C-complex asteroids available in the literature. We analyzed all these spectra in a similar way to characterize the absorption-band parameters (band center, depth, and width) and spectral slope, and to look for possible correlations between the aqueous alteration process and the asteroids taxonomic classes, orbital elements, heliocentric distances, albedo, and sizes. We find that 4.6 % of P, 7.7 % of F, 9.8 % of B, 50.5 % of C, and 100 % of the G-type asteroids have absorption bands in the visible region due to hydrated silicates. Our analysis shows that the aqueous alteration sequence starts from the P-type objects, practically unaltered, and increases through the P → F → B → C → G asteroids, these last being widely aqueously altered, strengthening thus

A red tide of Alexandrium fundyense in the Gulf of Maine.

PubMed

McGillicuddy, D J; Brosnahan, M L; Couture, D A; He, R; Keafer, B A; Manning, J P; Martin, J L; Pilskaln, C H; Townsend, D W; Anderson, D M

2014-05-01

In early July 2009, an unusually high concentration of the toxic dinoflagellate Alexandrium fundyense occurred in the western Gulf of Maine, causing surface waters to appear reddish brown to the human eye. The discolored water appeared to be the southern terminus of a large-scale event that caused shellfish toxicity along the entire coast of Maine to the Canadian border. Rapid-response shipboard sampling efforts together with satellite data suggest the water discoloration in the western Gulf of Maine was a highly ephemeral feature of less than two weeks in duration. Flow cytometric analysis of surface samples from the red water indicated the population was undergoing sexual reproduction. Cyst fluxes downstream of the discolored water were the highest ever measured in the Gulf of Maine, and a large deposit of new cysts was observed that fall. Although the mechanisms causing this event remain unknown, its timing coincided with an anomalous period of downwelling-favorable winds that could have played a role in aggregating upward-swimming cells. Regardless of the underlying causes, this event highlights the importance of short-term episodic phenomena on regional population dynamics of A. fundyense .

A red tide of Alexandrium fundyense in the Gulf of Maine

PubMed Central

McGillicuddy, D.J.; Brosnahan, M.L.; Couture, D.A.; He, R.; Keafer, B.A.; Manning, J.P.; Martin, J.L.; Pilskaln, C.H.; Townsend, D.W.; Anderson, D.M.

2013-01-01

In early July 2009, an unusually high concentration of the toxic dinoflagellate Alexandrium fundyense occurred in the western Gulf of Maine, causing surface waters to appear reddish brown to the human eye. The discolored water appeared to be the southern terminus of a large-scale event that caused shellfish toxicity along the entire coast of Maine to the Canadian border. Rapid-response shipboard sampling efforts together with satellite data suggest the water discoloration in the western Gulf of Maine was a highly ephemeral feature of less than two weeks in duration. Flow cytometric analysis of surface samples from the red water indicated the population was undergoing sexual reproduction. Cyst fluxes downstream of the discolored water were the highest ever measured in the Gulf of Maine, and a large deposit of new cysts was observed that fall. Although the mechanisms causing this event remain unknown, its timing coincided with an anomalous period of downwelling-favorable winds that could have played a role in aggregating upward-swimming cells. Regardless of the underlying causes, this event highlights the importance of short-term episodic phenomena on regional population dynamics of A. fundyense. PMID:25170191

A red tide of Alexandrium fundyense in the Gulf of Maine

NASA Astrophysics Data System (ADS)

McGillicuddy, D. J.; Brosnahan, M. L.; Couture, D. A.; He, R.; Keafer, B. A.; Manning, J. P.; Martin, J. L.; Pilskaln, C. H.; Townsend, D. W.; Anderson, D. M.

2014-05-01

In early July 2009, an unusually high concentration of the toxic dinoflagellate Alexandrium fundyense occurred in the western Gulf of Maine, causing surface waters to appear reddish brown to the human eye. The discolored water appeared to be the southern terminus of a large-scale event that caused shellfish toxicity along the entire coast of Maine to the Canadian border. Rapid-response shipboard sampling efforts together with satellite data suggest the water discoloration in the western Gulf of Maine was a highly ephemeral feature of less than two weeks in duration. Flow cytometric analysis of surface samples from the red water indicated the population was undergoing sexual reproduction. Cyst fluxes downstream of the discolored water were the highest ever measured in the Gulf of Maine, and a large deposit of new cysts was observed that fall. Although the mechanisms causing this event remain unknown, its timing coincided with an anomalous period of downwelling-favorable winds that could have played a role in aggregating upward-swimming cells. Regardless of the underlying causes, this event highlights the importance of short-term episodic phenomena on regional population dynamics of A. fundyense.

Enhanced HMAX model with feedforward feature learning for multiclass categorization.

PubMed

Li, Yinlin; Wu, Wei; Zhang, Bo; Li, Fengfu

2015-01-01

In recent years, the interdisciplinary research between neuroscience and computer vision has promoted the development in both fields. Many biologically inspired visual models are proposed, and among them, the Hierarchical Max-pooling model (HMAX) is a feedforward model mimicking the structures and functions of V1 to posterior inferotemporal (PIT) layer of the primate visual cortex, which could generate a series of position- and scale- invariant features. However, it could be improved with attention modulation and memory processing, which are two important properties of the primate visual cortex. Thus, in this paper, based on recent biological research on the primate visual cortex, we still mimic the first 100-150 ms of visual cognition to enhance the HMAX model, which mainly focuses on the unsupervised feedforward feature learning process. The main modifications are as follows: (1) To mimic the attention modulation mechanism of V1 layer, a bottom-up saliency map is computed in the S1 layer of the HMAX model, which can support the initial feature extraction for memory processing; (2) To mimic the learning, clustering and short-term memory to long-term memory conversion abilities of V2 and IT, an unsupervised iterative clustering method is used to learn clusters with multiscale middle level patches, which are taken as long-term memory; (3) Inspired by the multiple feature encoding mode of the primate visual cortex, information including color, orientation, and spatial position are encoded in different layers of the HMAX model progressively. By adding a softmax layer at the top of the model, multiclass categorization experiments can be conducted, and the results on Caltech101 show that the enhanced model with a smaller memory size exhibits higher accuracy than the original HMAX model, and could also achieve better accuracy than other unsupervised feature learning methods in multiclass categorization task.

Effects of Self-Paced Encoding and Practice on Age-Related Deficits in Binding Three Features

ERIC Educational Resources Information Center

Kinjo, Hikari

2010-01-01

Although much literature suggests that the age-related decline in episodic memory could be due to difficulties in binding features of information, previous studies focused mainly on memory of paired associations rather than memory of multiple bound features. In reality, however, there are many situations that require binding multiple features…

Peculiar Features of Attaining the CERA Designation in Canada

ERIC Educational Resources Information Center

Fursenko, Tetiana

2018-01-01

The article sets out peculiar features of attaining the CERA credential from the Canadian Institute of Actuaries. The analysis results show that there are scores of ways available to candidates perusing the aim of becoming a CERA. There have been singled out the main models following which it is possible to get the designation which is…

[Physiological features of skin ageing in human].

PubMed

Tikhonova, I V; Tankanag, A V; Chemeris, N K

2013-01-01

The issue deals with the actual problem of gerontology, notably physiological features of human skin ageing. In the present review the authors have considered the kinds of ageing, central factors, affected on the ageing process (ultraviolet radiation and oxidation stress), as well as the research guidelines of the ageing changes in the skin structure and fuctions: study of mechanical properties, microcirculation, pH and skin thickness. The special attention has been payed to the methods of assessment of skin blood flow, and to results of investigations of age features of peripheral microhemodynamics. The laser Doppler flowmetry technique - one of the modern, noninvasive and extensively used methods for the assessmant of skin blood flow microcirculation system has been expanded in the review. The main results of the study of the ageing changes of skin blood perfusion using this method has been also presented.

Tornadoes and other atmospheric vortices

NASA Technical Reports Server (NTRS)

Deissler, R. G.

1976-01-01

The growth of random vortices in an atmosphere with buoyant instability and vertical wind shear is studied along with the velocities in a single gravity-driven vortex; a frictionless adiabatic model which is supported by laboratory experiments is first considered. The effects of axial drag, heat transfer, and precipitation-induced downdrafts are then calculated. Heat transfer and axial drag tend to have stabilizing effects; they reduce the downdrafts of updrafts due to buoyancy. It is found that downdrafts or tornadic magnitude might occur in negatively-buoyant columns. The radial-inflow velocity required to maintain a given maximum tangential velocity in a tornado is determined by using a turbulent vortex model. Conditions under which radial-inflow velocities become sufficiently large to produce tangential velocities of tornadic magnitude are determined. The radial velocities in the outer regions, as well as the tangential velocities in the inner regions may be large enough to cause damage. The surface boundary layer, which is a region where large radial inflows can occur, is studied, and the thickness of the radial-inflow friction layer is estimated. A tornado model which involves a rotating parent cloud, as well as buoyancy and precipitation effects, is discussed.

Convective storms and non-classical low-level jets during high ozone level episodes in the Amazon region: An ARM/GOAMAZON case study

NASA Astrophysics Data System (ADS)

Dias-Junior, Cléo Q.; Dias, Nelson Luís; Fuentes, José D.; Chamecki, Marcelo

2017-04-01

In this work, we investigate the ozone dynamics during the occurrence of both downdrafts associated with mesoscale convective storms and non-classical low-level jets. Extensive data sets, comprised of air chemistry and meteorological observations made in the Amazon region of Brazil over the course of 2014-15, are analyzed to address several questions. A first objective is to investigate the atmospheric thermodynamic and dynamic conditions associated with storm-generated ozone enhancements in the Amazon region. A second objective is to determine the magnitude and the frequency of ground-level ozone enhancements related to low-level jets. Ozone enhancements are analyzed as a function of wind shear, low-level jet maximum wind speed, and altitude of jet core. Strong and sudden increases in ozone levels are associated with simultaneous changes in variables such as horizontal wind speed, convective available potential energy, turbulence intensity and vertical velocity skewness. Rapid increases in vertical velocity skewness give support to the hypothesis that the ozone enhancements are directly related to downdrafts. Low-level jets associated with advancing density currents are often present during and after storm downdrafts that transport ozone-enriched air from aloft to the surface.

Features and heterogeneities in growing network models

NASA Astrophysics Data System (ADS)

Ferretti, Luca; Cortelezzi, Michele; Yang, Bin; Marmorini, Giacomo; Bianconi, Ginestra

2012-06-01

Many complex networks from the World Wide Web to biological networks grow taking into account the heterogeneous features of the nodes. The feature of a node might be a discrete quantity such as a classification of a URL document such as personal page, thematic website, news, blog, search engine, social network, etc., or the classification of a gene in a functional module. Moreover the feature of a node can be a continuous variable such as the position of a node in the embedding space. In order to account for these properties, in this paper we provide a generalization of growing network models with preferential attachment that includes the effect of heterogeneous features of the nodes. The main effect of heterogeneity is the emergence of an “effective fitness” for each class of nodes, determining the rate at which nodes acquire new links. The degree distribution exhibits a multiscaling behavior analogous to the the fitness model. This property is robust with respect to variations in the model, as long as links are assigned through effective preferential attachment. Beyond the degree distribution, in this paper we give a full characterization of the other relevant properties of the model. We evaluate the clustering coefficient and show that it disappears for large network size, a property shared with the Barabási-Albert model. Negative degree correlations are also present in this class of models, along with nontrivial mixing patterns among features. We therefore conclude that both small clustering coefficients and disassortative mixing are outcomes of the preferential attachment mechanism in general growing networks.

General view of the Space Shuttle Main Engine (SSME) assembly ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view of the Space Shuttle Main Engine (SSME) assembly with the expansion nozzle removed and resting on a cushioned mat on the floor of the SSME Processing Facility. The most prominent features in this view are the Low-pressure oxidizer Turbopump discharge Duct looping from the upper left side of the engine assembly to the lower left side of the assembly, the Low-Pressure Fuel Turbopump (LPFTP) is on the upper left of the assembly in this view and the LPFTP Discharge Duct loops from the upper left to upper right then turns back and down the assembly to the High-Pressure Fuel Turbopump on the lower right of the assembly. The Engine Controller and the Main fuel Valve Hydraulic Actuator are on the lower left portion of the assembly. The vertical rod that is in the approximate center of the engine assembly is a piece of ground support equipment call a Gimbal Actuator Replacement Strut which are used on the SSMEs when they are not installed in an orbiter. - Space Transportation System, Space Shuttle Main Engine, Lyndon B. Johnson Space Center, 2101 NASA Parkway, Houston, Harris County, TX

Vertical-velocity skewness in the marine stratus-topped boundary layer

NASA Technical Reports Server (NTRS)

Moeng, Chin-Hoh; Rotunno, Richard; Paluch, Ilga R.

1990-01-01

Vertical-velocity skewness, S(sub w), in a turbulent flow is important in several regards. S(sub w) is indicative of the structure of the motion when it is positive, updrafts are narrower and stronger than surrounding downdrafts, and vice versa. Aircraft measurements often suggest cool, narrow downdrafts at some distance below the stratus cloud top, indicating a negative S(sub w) (Nicholls and Leighton, 1986). This seems natural as the turbulence within the stratus-topped boundary layer (CTBL) is driven mainly by the radiative cooling at the cloud top (although sometimes surface heating can also play a major role). One expects intuitively (e.g., Nicolls, 1984) that, in the situations where cloud-top cooling and surface heating coexist, the turbulence statistics in the upper part of the CTBL are influenced more by the cloud-top cooling, while those in the lower part, more by the surface heating. Thus one expects negative S(sub w) in the upper part, and positive in the lower part, in this case. In contradistinction, large-eddy simulations (LES) of the CTBL show just the opposite: the S(sub w) is positive in the upper part and negative in the lower part of the layer. To understand the nature of vertical-velocity skewness, the simplest type of buoyancy-driven turbulence (turbulent Rayleigh-Benard convection) is studied through direct numerical simulation.

Identifying significant environmental features using feature recognition.

DOT National Transportation Integrated Search

2015-10-01

The Department of Environmental Analysis at the Kentucky Transportation Cabinet has expressed an interest in feature-recognition capability because it may help analysts identify environmentally sensitive features in the landscape, : including those r...

Flow Distribution Around the SSME Main Injector Assembly Using Porosity Formulation

NASA Technical Reports Server (NTRS)

Cheng, Gary C.; Chen, Yen-Sen; Wang, Ten-See

1995-01-01

Hot gas turbulent flow distribution around the main injector assembly of the Space Shuttle Main Engine (SSME) and Liquid Oxidizer (LOX) flow distribution through the LOX posts have a great effect on the combustion phenomena inside the main combustion chamber. In order to design a CFD model to be an effective engineering analysis tool with good computational turn- around time (especially for 3-D flow problems) and still maintain good accuracy in describing the flow features, the concept of porosity was employed to describe the effects of blockage and drag force due to the presence of the LOX posts in the turbulent flow field around the main injector assembly of the SSME. 2-D numerical studies were conducted to identify the drag coefficients of the flows both through tube banks and around the shielded posts over a wide range of Reynolds numbers. Empirical, analytical expressions of the drag coefficient as a function of local flow Reynolds number were then deduced. The porosity model was applied to the turbulent flow around the main injector assembly of the SSME, and analyses were performed. The 3-D CFD analysis was divided into three parts, LOX dome, hot gas injector assembly, and hydrogen cavity. The numerical results indicate that the mixture ratio at the downstream of injector face was close to stoichiometric around baffle elements.

Flow Distribution Around the SSME Main Injector Assembly Using Porosity Formulation

NASA Technical Reports Server (NTRS)

Cheng, Gary C.; Chen, Yen-Sen; Wang, Ten-See

1995-01-01

Hot gas turbulent flow distribution around the main injector assembly of the Space Shuttle Main Engine (SSME) and Liquid Oxidizer (LOX) flow distribution through the LOX posts have a great effect on the combustion phenomena inside the main combustion chamber. In order to design a CFD model to be an effective engineering analysis tool with good computational turn-around time (especially for 3-D flow problems) and still maintain good accuracy in describing the flow features, the concept of porosity was employed to describe the effects of blockage and drag force due to the presence of the LOX posts in the turbulent flow field around the main injector assembly of the SSME. 2-D numerical studies were conducted to identify the drag coefficients of the flows both through tube banks and around the shielded posts over a wide range of Reynolds numbers. Empirical, analytical expressions of the drag coefficient as a function of local flow Reynolds number were then deduced. The porosity model was applied to the turbulent flow around the main injector assembly of the SSME, and analyses were performed. The 3-D CFD analysis was divided into three parts, LOX dome, hot gas injector assembly, and hydrogen cavity. The numerical results indicate that the mixture ratio at the downstream of injector face was close to stoichiometric around baffle elements.

Closeup side view of Space Shuttle Main Engine (SSME) 2059 ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Close-up side view of Space Shuttle Main Engine (SSME) 2059 mounted in a SSME Engine Handler near the Drying Area in the High Bay section of the SSME Processing Facility. The prominent features of the SSME in this view are the hot-gas expansion nozzle extending from the approximate image center toward the image right. The main-engine components extend from the approximate image center toward image right until it meets up with the mount for the SSME Engine Handler. The engine is rotated to a position where the major components in the view are the Low-Pressure Fuel Turbopump Discharge Duct with reflective foil insulation on the upper side of the engine, the Low-Pressure Oxidizer Turbopump and its Discharge Duct on the right side of the engine assembly extending itself down and wrapping under the bottom side of the assembly to the High-Pressure Oxidizer Turbopump pump. The High-Pressure Oxidizer Turbopump Discharge Duct exists the turbopump and extends up to the top side of the assembly where it enters the main oxidizer valve. The sphere on the lower side of the engine assembly is an accumulator that is part of the SSMEs POGO suppression system. - Space Transportation System, Space Shuttle Main Engine, Lyndon B. Johnson Space Center, 2101 NASA Parkway, Houston, Harris County, TX

75 FR 27863 - Savings Bank of Maine, MHC and Savings Bank of Maine, Gardiner, Maine; Approval of Conversion...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-18

... DEPARTMENT OF THE TREASURY Office of Thrift Supervision [AC-38: OTS Nos. 06947 and H 4709] Savings Bank of Maine, MHC and Savings Bank of Maine, Gardiner, Maine; Approval of Conversion Application Notice is hereby given that on May 7, 2010, the Office of Thrift Supervision approved the application of...

PAH emissions from old and new types of domestic hot water boilers.

PubMed

Horak, Jiri; Kubonova, Lenka; Krpec, Kamil; Hopan, Frantisek; Kubesa, Petr; Motyka, Oldrich; Laciok, Vendula; Dej, Milan; Ochodek, Tadeas; Placha, Daniela

2017-06-01

Five different domestic heating boilers (automatic, over-fire, with down-draft combustion and gasification) and three types of fuel (lignite, wood and mixed fuel) were examined in 25 combustion tests and correlated with the emissions of particulate matter (PM), carbon monoxide (CO), total organic carbon (TOC) and 12 polycyclic aromatic hydrocarbons (PAHs with MW = 178-278 g/mol) focusing on particle phase. However, the distribution of 12 PAHs in gas phase was considered as well due to the presence mainly of lighter PAHs in gas phase. The PAHs, as well as the CO and TOC, are the indicators of incomplete combustion, and in this study PAH emission increased significantly with increasing emissions of CO and TOC. The PAHs were mainly detected on PM 2.5 , their contents were increasing linearly with increasing PM 2.5 emissions. The highest emission factors of PAHs were measured for boilers of old construction, such as over-fire boiler (5.8-929 mg/kg) and boiler with down-draft combustion (3.1-54.1 mg/kg). Modern types of boilers produced much lower emissions of PAHs, in particular, automatic boiler (0.3-3.3 mg/kg) and gasification boilers (0.2-6.7 mg/kg). In general, the inefficient combustion at reduced output of boilers generated 1.4-17.7 times more emissions of PAHs than the combustion at nominal output of boilers. It is recommended to operate boilers at nominal output with sufficient air supply and to use the proper fuel to minimise PAHs emissions from domestic heating appliances. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Influence of Universities' Organizational Features on Professorial Intellectual Leadership

ERIC Educational Resources Information Center

Uslu, Baris; Welch, Anthony

2018-01-01

This research examines the intellectual leadership behaviours of senior academics at professoriate level, and the influences of institutional support practices, climate and communication in universities as main organizational features on these behaviours. To explore relations among research variables, qualitative data were collected by interviews…

Task-induced frequency modulation features for brain-computer interfacing

NASA Astrophysics Data System (ADS)

Jayaram, Vinay; Hohmann, Matthias; Just, Jennifer; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2017-10-01

Objective. Task-induced amplitude modulation of neural oscillations is routinely used in brain-computer interfaces (BCIs) for decoding subjects’ intents, and underlies some of the most robust and common methods in the field, such as common spatial patterns and Riemannian geometry. While there has been some interest in phase-related features for classification, both techniques usually presuppose that the frequencies of neural oscillations remain stable across various tasks. We investigate here whether features based on task-induced modulation of the frequency of neural oscillations enable decoding of subjects’ intents with an accuracy comparable to task-induced amplitude modulation. Approach. We compare cross-validated classification accuracies using the amplitude and frequency modulated features, as well as a joint feature space, across subjects in various paradigms and pre-processing conditions. We show results with a motor imagery task, a cognitive task, and also preliminary results in patients with amyotrophic lateral sclerosis (ALS), as well as using common spatial patterns and Laplacian filtering. Main results. The frequency features alone do not significantly out-perform traditional amplitude modulation features, and in some cases perform significantly worse. However, across both tasks and pre-processing in healthy subjects the joint space significantly out-performs either the frequency or amplitude features alone. This result only does not hold for ALS patients, for whom the dataset is of insufficient size to draw any statistically significant conclusions. Significance. Task-induced frequency modulation is robust and straight forward to compute, and increases performance when added to standard amplitude modulation features across paradigms. This allows more information to be extracted from the EEG signal cheaply and can be used throughout the field of BCIs.

Chinese character recognition based on Gabor feature extraction and CNN

NASA Astrophysics Data System (ADS)

Xiong, Yudian; Lu, Tongwei; Jiang, Yongyuan

2018-03-01

As an important application in the field of text line recognition and office automation, Chinese character recognition has become an important subject of pattern recognition. However, due to the large number of Chinese characters and the complexity of its structure, there is a great difficulty in the Chinese character recognition. In order to solve this problem, this paper proposes a method of printed Chinese character recognition based on Gabor feature extraction and Convolution Neural Network(CNN). The main steps are preprocessing, feature extraction, training classification. First, the gray-scale Chinese character image is binarized and normalized to reduce the redundancy of the image data. Second, each image is convoluted with Gabor filter with different orientations, and the feature map of the eight orientations of Chinese characters is extracted. Third, the feature map through Gabor filters and the original image are convoluted with learning kernels, and the results of the convolution is the input of pooling layer. Finally, the feature vector is used to classify and recognition. In addition, the generalization capacity of the network is improved by Dropout technology. The experimental results show that this method can effectively extract the characteristics of Chinese characters and recognize Chinese characters.

Critical Product Features' Identification Using an Opinion Analyzer

PubMed Central

Shamim, Azra; Balakrishnan, Vimala

2014-01-01

The increasing use and ubiquity of the Internet facilitate dissemination of word-of-mouth through blogs, online forums, newsgroups, and consumer's reviews. Online consumer's reviews present tremendous opportunities and challenges for consumers and marketers. One of the challenges is to develop interactive marketing practices for making connections with target consumers that capitalize consumer-to-consumer communications for generating product adoption. Opinion mining is employed in marketing to help consumers and enterprises in the analysis of online consumers' reviews by highlighting the strengths and weaknesses of the products. This paper describes an opinion mining system based on novel review and feature ranking methods to empower consumers and enterprises for identifying critical product features from enormous consumers' reviews. Consumers and business analysts are the main target group for the proposed system who want to explore consumers' feedback for determining purchase decisions and enterprise strategies. We evaluate the proposed system on real dataset. Results show that integration of review and feature-ranking methods improves the decision making processes significantly. PMID:25506612

Hyperspectral remote sensing image retrieval system using spectral and texture features.

PubMed

Zhang, Jing; Geng, Wenhao; Liang, Xi; Li, Jiafeng; Zhuo, Li; Zhou, Qianlan

2017-06-01

Although many content-based image retrieval systems have been developed, few studies have focused on hyperspectral remote sensing images. In this paper, a hyperspectral remote sensing image retrieval system based on spectral and texture features is proposed. The main contributions are fourfold: (1) considering the "mixed pixel" in the hyperspectral image, endmembers as spectral features are extracted by an improved automatic pixel purity index algorithm, then the texture features are extracted with the gray level co-occurrence matrix; (2) similarity measurement is designed for the hyperspectral remote sensing image retrieval system, in which the similarity of spectral features is measured with the spectral information divergence and spectral angle match mixed measurement and in which the similarity of textural features is measured with Euclidean distance; (3) considering the limited ability of the human visual system, the retrieval results are returned after synthesizing true color images based on the hyperspectral image characteristics; (4) the retrieval results are optimized by adjusting the feature weights of similarity measurements according to the user's relevance feedback. The experimental results on NASA data sets can show that our system can achieve comparable superior retrieval performance to existing hyperspectral analysis schemes.

18. MAIN FLOOR HOLDING TANKS Main floor, looking at ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

18. MAIN FLOOR - HOLDING TANKS Main floor, looking at holding tanks against the west wall, from which sluice gates are seen protruding. Right foreground-wooden holding tanks. Note narrow wooden flumes through which fish were sluiced into holding and brining tanks. - Hovden Cannery, 886 Cannery Row, Monterey, Monterey County, CA

The morphing of geographical features by Fourier transformation.

PubMed

Li, Jingzhong; Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features' continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable.

A record of planet migration in the main asteroid belt.

PubMed

Minton, David A; Malhotra, Renu

2009-02-26

The main asteroid belt lies between the orbits of Mars and Jupiter, but the region is not uniformly filled with asteroids. There are gaps, known as the Kirkwood gaps, in distinct locations that are associated with orbital resonances with the giant planets; asteroids placed in these locations will follow chaotic orbits and be removed. Here we show that the observed distribution of main belt asteroids does not fill uniformly even those regions that are dynamically stable over the age of the Solar System. We find a pattern of excess depletion of asteroids, particularly just outward of the Kirkwood gaps associated with the 5:2, the 7:3 and the 2:1 Jovian resonances. These features are not accounted for by planetary perturbations in the current structure of the Solar System, but are consistent with dynamical ejection of asteroids by the sweeping of gravitational resonances during the migration of Jupiter and Saturn approximately 4 Gyr ago.

Using Activity-Related Behavioural Features towards More Effective Automatic Stress Detection

PubMed Central

Giakoumis, Dimitris; Drosou, Anastasios; Cipresso, Pietro; Tzovaras, Dimitrios; Hassapis, George; Gaggioli, Andrea; Riva, Giuseppe

2012-01-01

This paper introduces activity-related behavioural features that can be automatically extracted from a computer system, with the aim to increase the effectiveness of automatic stress detection. The proposed features are based on processing of appropriate video and accelerometer recordings taken from the monitored subjects. For the purposes of the present study, an experiment was conducted that utilized a stress-induction protocol based on the stroop colour word test. Video, accelerometer and biosignal (Electrocardiogram and Galvanic Skin Response) recordings were collected from nineteen participants. Then, an explorative study was conducted by following a methodology mainly based on spatiotemporal descriptors (Motion History Images) that are extracted from video sequences. A large set of activity-related behavioural features, potentially useful for automatic stress detection, were proposed and examined. Experimental evaluation showed that several of these behavioural features significantly correlate to self-reported stress. Moreover, it was found that the use of the proposed features can significantly enhance the performance of typical automatic stress detection systems, commonly based on biosignal processing. PMID:23028461

29. MAIN CONTROL ROOM, PANELS WEST OF MAIN CONTROL AREA, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

29. MAIN CONTROL ROOM, PANELS WEST OF MAIN CONTROL AREA, LOOKING SOUTH (LOCATION Q) - Shippingport Atomic Power Station, On Ohio River, 25 miles Northwest of Pittsburgh, Shippingport, Beaver County, PA

28. MAIN CONTROL ROOM, PANELS WEST OF MAIN CONTROL AREA, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

28. MAIN CONTROL ROOM, PANELS WEST OF MAIN CONTROL AREA, LOOKING NORTH (LOCATION Q) - Shippingport Atomic Power Station, On Ohio River, 25 miles Northwest of Pittsburgh, Shippingport, Beaver County, PA

Tiled vector data model for the geographical features of symbolized maps.

PubMed

Li, Lin; Hu, Wei; Zhu, Haihong; Li, You; Zhang, Hang

2017-01-01

Electronic maps (E-maps) provide people with convenience in real-world space. Although web map services can display maps on screens, a more important function is their ability to access geographical features. An E-map that is based on raster tiles is inferior to vector tiles in terms of interactive ability because vector maps provide a convenient and effective method to access and manipulate web map features. However, the critical issue regarding rendering tiled vector maps is that geographical features that are rendered in the form of map symbols via vector tiles may cause visual discontinuities, such as graphic conflicts and losses of data around the borders of tiles, which likely represent the main obstacles to exploring vector map tiles on the web. This paper proposes a tiled vector data model for geographical features in symbolized maps that considers the relationships among geographical features, symbol representations and map renderings. This model presents a method to tailor geographical features in terms of map symbols and 'addition' (join) operations on the following two levels: geographical features and map features. Thus, these maps can resolve the visual discontinuity problem based on the proposed model without weakening the interactivity of vector maps. The proposed model is validated by two map data sets, and the results demonstrate that the rendered (symbolized) web maps present smooth visual continuity.

Tensor-driven extraction of developmental features from varying paediatric EEG datasets.

PubMed

Kinney-Lang, Eli; Spyrou, Loukianos; Ebied, Ahmed; Chin, Richard Fm; Escudero, Javier

2018-05-21

Constant changes in developing children's brains can pose a challenge in EEG dependant technologies. Advancing signal processing methods to identify developmental differences in paediatric populations could help improve function and usability of such technologies. Taking advantage of the multi-dimensional structure of EEG data through tensor analysis may offer a framework for extracting relevant developmental features of paediatric datasets. A proof of concept is demonstrated through identifying latent developmental features in resting-state EEG. Approach. Three paediatric datasets (n = 50, 17, 44) were analyzed using a two-step constrained parallel factor (PARAFAC) tensor decomposition. Subject age was used as a proxy measure of development. Classification used support vector machines (SVM) to test if PARAFAC identified features could predict subject age. The results were cross-validated within each dataset. Classification analysis was complemented by visualization of the high-dimensional feature structures using t-distributed Stochastic Neighbour Embedding (t-SNE) maps. Main Results. Development-related features were successfully identified for the developmental conditions of each dataset. SVM classification showed the identified features could accurately predict subject at a significant level above chance for both healthy and impaired populations. t-SNE maps revealed suitable tensor factorization was key in extracting the developmental features. Significance. The described methods are a promising tool for identifying latent developmental features occurring throughout childhood EEG. © 2018 IOP Publishing Ltd.

125. Pre1911. Crew on main deck, starboard side at main ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

125. Pre-1911. Crew on main deck, starboard side at main hatch, looking aft. Note dark object in center of photo that may be original main deck capstan. Fred Heick collection. (K9.9571) - Ship BALCLUTHA, 2905 Hyde Street Pier, San Francisco, San Francisco County, CA

Monocular precrash vehicle detection: features and classifiers.

PubMed

Sun, Zehang; Bebis, George; Miller, Ronald

2006-07-01

Robust and reliable vehicle detection from images acquired by a moving vehicle (i.e., on-road vehicle detection) is an important problem with applications to driver assistance systems and autonomous, self-guided vehicles. The focus of this work is on the issues of feature extraction and classification for rear-view vehicle detection. Specifically, by treating the problem of vehicle detection as a two-class classification problem, we have investigated several different feature extraction methods such as principal component analysis, wavelets, and Gabor filters. To evaluate the extracted features, we have experimented with two popular classifiers, neural networks and support vector machines (SVMs). Based on our evaluation results, we have developed an on-board real-time monocular vehicle detection system that is capable of acquiring grey-scale images, using Ford's proprietary low-light camera, achieving an average detection rate of 10 Hz. Our vehicle detection algorithm consists of two main steps: a multiscale driven hypothesis generation step and an appearance-based hypothesis verification step. During the hypothesis generation step, image locations where vehicles might be present are extracted. This step uses multiscale techniques not only to speed up detection, but also to improve system robustness. The appearance-based hypothesis verification step verifies the hypotheses using Gabor features and SVMs. The system has been tested in Ford's concept vehicle under different traffic conditions (e.g., structured highway, complex urban streets, and varying weather conditions), illustrating good performance.

22. View showing main anchor arm, as viewed from main ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

22. View showing main anchor arm, as viewed from main cantilever arm looking south. Note upper chord eyebar arrangement. - Williamstown-Marietta Bridge, Spanning Ohio River between Williamstown & Marietta, Williamstown, Wood County, WV

Constraints on inflation with LSS surveys: features in the primordial power spectrum

NASA Astrophysics Data System (ADS)

Palma, Gonzalo A.; Sapone, Domenico; Sypsas, Spyros

2018-06-01

We analyse the efficiency of future large scale structure surveys to unveil the presence of scale dependent features in the primordial spectrum—resulting from cosmic inflation—imprinted in the distribution of galaxies. Features may appear as a consequence of non-trivial dynamics during cosmic inflation, in which one or more background quantities experienced small but rapid deviations from their characteristic slow-roll evolution. We consider two families of features: localised features and oscillatory extended features. To characterise them we employ various possible templates parametrising their scale dependence and provide forecasts on the constraints on these parametrisations for LSST like surveys. We perform a Fisher matrix analysis for three observables: cosmic microwave background (CMB), galaxy clustering and weak lensing. We find that the combined data set of these observables will be able to limit the presence of features down to levels that are more restrictive than current constraints coming from CMB observations only. In particular, we address the possibility of gaining information on currently known deviations from scale invariance inferred from CMB data, such as the feature appearing at the l ~ 20 multipole (which is the main contribution to the low-l deficit) and another one around l ~ 800.

Rhetorical features facilitate prosodic processing while handicapping ease of semantic comprehension.

PubMed

Menninghaus, Winfried; Bohrn, Isabel C; Knoop, Christine A; Kotz, Sonja A; Schlotz, Wolff; Jacobs, Arthur M

2015-10-01

Studies on rhetorical features of language have reported both enhancing and adverse effects on ease of processing. We hypothesized that two explanations may account for these inconclusive findings. First, the respective gains and losses in ease of processing may apply to different dimensions of language processing (specifically, prosodic and semantic processing) and different types of fluency (perceptual vs. conceptual) and may well allow for an integration into a more comprehensive framework. Second, the effects of rhetorical features may be sensitive to interactions with other rhetorical features; employing a feature separately or in combination with others may then predict starkly different effects. We designed a series of experiments in which we expected the same rhetorical features of the very same sentences to exert adverse effects on semantic (conceptual) fluency and enhancing effects on prosodic (perceptual) fluency. We focused on proverbs that each employ three rhetorical features: rhyme, meter, and brevitas (i.e., artful shortness). The presence of these target features decreased ease of conceptual fluency (semantic comprehension) while enhancing perceptual fluency as reflected in beauty and succinctness ratings that were mainly driven by prosodic features. The rhetorical features also predicted choices for persuasive purposes, yet only for the sentence versions featuring all three rhetorical features; the presence of only one or two rhetorical features had an adverse effect on the choices made. We suggest that the facilitating effects of a combination of rhyme, meter, and rhetorical brevitas on perceptual (prosodic) fluency overcompensated for their adverse effects on conceptual (semantic) fluency, thus resulting in a total net gain both in processing ease and in choices for persuasive purposes. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Computed tomography in hypersensitivity pneumonitis: main findings, differential diagnosis and pitfalls.

PubMed

Dias, Olívia Meira; Baldi, Bruno Guedes; Pennati, Francesca; Aliverti, Andrea; Chate, Rodrigo Caruso; Sawamura, Márcio Valente Yamada; Carvalho, Carlos Roberto Ribeiro de; Albuquerque, André Luis Pereira de

2018-01-01

Hypersensitivity pneumonitis (HP) is a disease with variable clinical presentation in which inflammation in the lung parenchyma is caused by the inhalation of specific organic antigens or low molecular weight substances in genetically susceptible individuals. Alterations of the acute, subacute and chronic forms may eventually overlap, and the diagnosis based on temporality and presence of fibrosis (acute/inflammatory HP vs. chronic HP) seems to be more feasible and useful in clinical practice. Differential diagnosis of chronic HP with other interstitial fibrotic diseases is challenging due to the overlap of the clinical history, and the functional and imaging findings of these pathologies in the terminal stages. Areas covered: This article reviews the essential features of HP with emphasis on imaging features. Moreover, the main methodological limitations of high-resolution computed tomography (HRCT) interpretation are discussed, as well as new perspectives with volumetric quantitative CT analysis as a useful tool for retrieving detailed and accurate information from the lung parenchyma. Expert commentary: Mosaic attenuation is a prominent feature of this disease, but air trapping in chronic HP seems overestimated. Quantitative analysis has the potential to estimate the involvement of the pulmonary parenchyma more accurately and could correlate better with pulmonary function results.

[Results of testing of MINISKAN mobile gamma-ray camera and specific features of its design].

PubMed

Utkin, V M; Kumakhov, M A; Blinov, N N; Korsunskiĭ, V N; Fomin, D K; Kolesnikova, N V; Tultaev, A V; Nazarov, A A; Tararukhina, O B

2007-01-01

The main results of engineering, biomedical, and clinical testing of MINISKAN mobile gamma-ray camera are presented. Specific features of the camera hardware and software, as well as the main technical specifications, are described. The gamma-ray camera implements a new technology based on reconstructive tomography, aperture encoding, and digital processing of signals.

Evaluation of space shuttle main engine fluid dynamic frequency response characteristics

NASA Technical Reports Server (NTRS)

Gardner, T. G.

1980-01-01

In order to determine the POGO stability characteristics of the space shuttle main engine liquid oxygen (LOX) system, the fluid dynamic frequency response functions between elements in the SSME LOX system was evaluated, both analytically and experimentally. For the experimental data evaluation, a software package was written for the Hewlett-Packard 5451C Fourier analyzer. The POGO analysis software is documented and consists of five separate segments. Each segment is stored on the 5451C disc as an individual program and performs its own unique function. Two separate data reduction methods, a signal calibration, coherence or pulser signal based frequency response function blanking, and automatic plotting features are included in the program. The 5451C allows variable parameter transfer from program to program. This feature is used to advantage and requires only minimal user interface during the data reduction process. Experimental results are included and compared with the analytical predictions in order to adjust the general model and arrive at a realistic simulation of the POGO characteristics.

A novel feature extraction approach for microarray data based on multi-algorithm fusion

PubMed Central

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions. PMID:25780277

A novel feature extraction approach for microarray data based on multi-algorithm fusion.

PubMed

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions.

Shallow convection on day 261 of GATE - Mesoscale arcs

NASA Technical Reports Server (NTRS)

Warner, C.; Simpson, J.; Martin, D. W.; Suchman, D.; Mosher, F. R.; Reinking, R. F.

1979-01-01

Cloudy convection in the moist layer of a cloud cluster growing in the GATE ship array is examined. Analyses suggest that the moist layer was dominated by features of horizontal dimension roughly 40 km and lifetime roughly 2 h, with arc patterns triggered by dense downdraft air accompanying rainfall, and composed of many small cumulus clouds. Aircraft recorded data on thermodynamic quantities and winds, indicating that the arcs persisted as mesoscale circulations driven by the release of latent heat in the clouds, rather than being driven by the original density current at the surface. It is also suggested that the mesoscale cloud patterns of the moist layer play a primary role in heat transfer upward within this layer, and contribute to the forcing of showering midtropospheric clouds.

A Review of Feature Extraction Software for Microarray Gene Expression Data

PubMed Central

Tan, Ching Siang; Ting, Wai Soon; Mohamad, Mohd Saberi; Chan, Weng Howe; Deris, Safaai; Ali Shah, Zuraini

2014-01-01

When gene expression data are too large to be processed, they are transformed into a reduced representation set of genes. Transforming large-scale gene expression data into a set of genes is called feature extraction. If the genes extracted are carefully chosen, this gene set can extract the relevant information from the large-scale gene expression data, allowing further analysis by using this reduced representation instead of the full size data. In this paper, we review numerous software applications that can be used for feature extraction. The software reviewed is mainly for Principal Component Analysis (PCA), Independent Component Analysis (ICA), Partial Least Squares (PLS), and Local Linear Embedding (LLE). A summary and sources of the software are provided in the last section for each feature extraction method. PMID:25250315

The origin of infrasonic ionosphere oscillations over tropospheric thunderstorms

DOE PAGES

Shao, Xuan -Min; Lay, Erin Hoffmann

2016-07-01

Thunderstorms have been observed to introduce infrasonic oscillations in the ionosphere, but it is not clear what processes or which parts of the thunderstorm generate the oscillations. In this paper, we present a new technique that uses an array of ground-based GPS total electron content (TEC) measurements to locate the source of the infrasonic oscillations and compare the source locations with thunderstorm features to understand the possible source mechanisms. The location technique utilizes instantaneous phase differences between pairs of GPS-TEC measurements and an algorithm to best fit the measured and the expected phase differences for assumed source positions and othermore » related parameters. In this preliminary study, the infrasound waves are assumed to propagate along simple geometric raypaths from the source to the measurement locations to avoid extensive computations. The located sources are compared in time and space with thunderstorm development and lightning activity. Sources are often found near the main storm cells, but they are more likely related to the downdraft process than to the updraft process. As a result, the sources are also commonly found in the convectively quiet stratiform regions behind active cells and are in good coincidence with extensive lightning discharges and inferred high-altitude sprites discharges.« less

The origin of infrasonic ionosphere oscillations over tropospheric thunderstorms

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

Shao, Xuan -Min; Lay, Erin Hoffmann

Thunderstorms have been observed to introduce infrasonic oscillations in the ionosphere, but it is not clear what processes or which parts of the thunderstorm generate the oscillations. In this paper, we present a new technique that uses an array of ground-based GPS total electron content (TEC) measurements to locate the source of the infrasonic oscillations and compare the source locations with thunderstorm features to understand the possible source mechanisms. The location technique utilizes instantaneous phase differences between pairs of GPS-TEC measurements and an algorithm to best fit the measured and the expected phase differences for assumed source positions and othermore » related parameters. In this preliminary study, the infrasound waves are assumed to propagate along simple geometric raypaths from the source to the measurement locations to avoid extensive computations. The located sources are compared in time and space with thunderstorm development and lightning activity. Sources are often found near the main storm cells, but they are more likely related to the downdraft process than to the updraft process. As a result, the sources are also commonly found in the convectively quiet stratiform regions behind active cells and are in good coincidence with extensive lightning discharges and inferred high-altitude sprites discharges.« less

Extracting the driving force from ozone data using slow feature analysis

NASA Astrophysics Data System (ADS)

Wang, Geli; Yang, Peicai; Zhou, Xiuji

2016-05-01

Slow feature analysis (SFA) is a recommended technique for extracting slowly varying features from a quickly varying signal. In this work, we apply SFA to total ozone data from Arosa, Switzerland. The results show that the signal of volcanic eruptions can be found in the driving force, and wavelet analysis of this driving force shows that there are two main dominant scales, which may be connected with the effect of climate mode such as North Atlantic Oscillation (NAO) and solar activity. The findings of this study represent a contribution to our understanding of the causality from observed climate data.

Unsupervised Pattern Classifier for Abnormality-Scaling of Vibration Features for Helicopter Gearbox Fault Diagnosis

NASA Technical Reports Server (NTRS)

Jammu, Vinay B.; Danai, Kourosh; Lewicki, David G.

1996-01-01

A new unsupervised pattern classifier is introduced for on-line detection of abnormality in features of vibration that are used for fault diagnosis of helicopter gearboxes. This classifier compares vibration features with their respective normal values and assigns them a value in (0, 1) to reflect their degree of abnormality. Therefore, the salient feature of this classifier is that it does not require feature values associated with faulty cases to identify abnormality. In order to cope with noise and changes in the operating conditions, an adaptation algorithm is incorporated that continually updates the normal values of the features. The proposed classifier is tested using experimental vibration features obtained from an OH-58A main rotor gearbox. The overall performance of this classifier is then evaluated by integrating the abnormality-scaled features for detection of faults. The fault detection results indicate that the performance of this classifier is comparable to the leading unsupervised neural networks: Kohonen's Feature Mapping and Adaptive Resonance Theory (AR72). This is significant considering that the independence of this classifier from fault-related features makes it uniquely suited to abnormality-scaling of vibration features for fault diagnosis.

Robust Features Of Surface Electromyography Signal

NASA Astrophysics Data System (ADS)

Sabri, M. I.; Miskon, M. F.; Yaacob, M. R.

2013-12-01

Nowadays, application of robotics in human life has been explored widely. Robotics exoskeleton system are one of drastically areas in recent robotic research that shows mimic impact in human life. These system have been developed significantly to be used for human power augmentation, robotics rehabilitation, human power assist, and haptic interaction in virtual reality. This paper focus on solving challenges in problem using neural signals and extracting human intent. Commonly, surface electromyography signal (sEMG) are used in order to control human intent for application exoskeleton robot. But the problem lies on difficulty of pattern recognition of the sEMG features due to high noises which are electrode and cable motion artifact, electrode noise, dermic noise, alternating current power line interface, and other noise came from electronic instrument. The main objective in this paper is to study the best features of electromyography in term of time domain (statistical analysis) and frequency domain (Fast Fourier Transform).The secondary objectives is to map the relationship between torque and best features of muscle unit activation potential (MaxPS and RMS) of biceps brachii. This project scope use primary data of 2 male sample subject which using same dominant hand (right handed), age between 20-27 years old, muscle diameter 32cm to 35cm and using single channel muscle (biceps brachii muscle). The experiment conduct 2 times repeated task of contraction and relaxation of biceps brachii when lifting different load from no load to 3kg with ascending 1kg The result shows that Fast Fourier Transform maximum power spectrum (MaxPS) has less error than mean value of reading compare to root mean square (RMS) value. Thus, Fast Fourier Transform maximum power spectrum (MaxPS) show the linear relationship against torque experience by elbow joint to lift different load. As the conclusion, the best features is MaxPS because it has the lowest error than other features and show

Desired features of smartphone applications promoting physical activity.

PubMed

Rabin, Carolyn; Bock, Beth

2011-12-01

Approximately one-third of adults in the United States are physically inactive. This is a significant public health concern as physical activity (PA) can influence the risk of cardiovascular disease, diabetes, and certain forms of cancer. To minimize these health risks, effective PA interventions must be developed and disseminated to the vast number of individuals who remain sedentary. Smartphone technology presents an exciting opportunity for delivering PA interventions remotely. Although a number of PA applications are currently available for smartphones, these "apps" are not based on established theories of health behavior change and most do not include evidence-based features (e.g., reinforcement and goal setting). Our aim was to collect formative data to develop a smartphone PA app that is empirically and theoretically-based and incorporates user preferences. We recruited 15 sedentary adults to test three currently available PA smartphone apps and provide qualitative and quantitative feedback. Findings indicate that users have a number of specific preferences with regard to PA app features, including that apps provide automatic tracking of PA (e.g., steps taken and calories burned), track progress toward PA goals, and integrate a music feature. Participants also preferred that PA apps be flexible enough to be used with several types of PA, and have well-documented features and user-friendly interfaces (e.g., a one-click main page). When queried by the researcher, most participants endorsed including goal-setting and problem-solving features. These findings provide a blue print for developing a smartphone PA app that incorporates evidence-based components and user preferences.

Varying irrelevant phonetic features hinders learning of the feature being trained.

PubMed

Antoniou, Mark; Wong, Patrick C M

2016-01-01

Learning to distinguish nonnative words that differ in a critical phonetic feature can be difficult. Speech training studies typically employ methods that explicitly direct the learner's attention to the relevant nonnative feature to be learned. However, studies on vision have demonstrated that perceptual learning may occur implicitly, by exposing learners to stimulus features, even if they are irrelevant to the task, and it has recently been suggested that this task-irrelevant perceptual learning framework also applies to speech. In this study, subjects took part in a seven-day training regimen to learn to distinguish one of two nonnative features, namely, voice onset time or lexical tone, using explicit training methods consistent with most speech training studies. Critically, half of the subjects were exposed to stimuli that varied not only in the relevant feature, but in the irrelevant feature as well. The results showed that subjects who were trained with stimuli that varied in the relevant feature and held the irrelevant feature constant achieved the best learning outcomes. Varying both features hindered learning and generalization to new stimuli.

A Physical Mechanism for the Asymmetry in Top-Down and Bottom-Up Diffusion.

NASA Astrophysics Data System (ADS)

Wyngaard, J. C.

1987-04-01

Recent large-eddy simulations of the vertical diffusion of a passive, conservative scalar through the convective boundary layer (CBL) show strikingly different eddy diffusivity profiles in the `top-down' and `bottom-up' cases. These results indicate that for a given turbulent velocity field and associated scalar flux, the mean change in scalar mixing ratio across the CBL is several times larger if the flux originates at the top of the boundary layer (i.e., in top-down diffusion) rather than at the bottom. The large-eddy simulation (LES) data show that this asymmetry is due to a breakdown of the eddy-diffusion concept.A simple updraft-downdraft model of the CBL reveals a physical mechanism that could cause this unexpected behavior. The large, positive skewness of the convectively driven vertical velocity gives an appreciably higher probability of downdrafts than updrafts; this excess probability of downdrafts, interacting with the time changes of the mean mixing ratio caused by the nonstationarity of the bottom-up and top-down diffusion processes, decreases the equilibrium value of mean mixing-ratio jump across the mixed layer in the bottom-up case and increases it in the top-down case. The resulting diffusion asymmetry agrees qualitatively with that found through LES.

[Clinical features of Enterococcus faecium meningitis in children].

PubMed

Wang, Li-Yuan; Cai, Xiao-Tang; Wang, Zhi-Ling; Liu, Shun-Li; Xie, Yong-Mei; Zhou, Hui

2018-03-01

To summarize the clinical features of Enterococcus faecium meningitis in children. The clinical data of nine children with Enterococcus faecium meningitis were analyzed. In all the nine children, Enterococcus faecium was isolated from blood, cerebrospinal fluid, or peripherally inserted central catheters; 6 (67%) patients were neonates, 2 (22%) patients were younger than 6 months, and 1 (11%) patient was three years and four months of age. In those patients, 56% had high-risk factors before onset, which included intestinal infection, resettlement of drainage tube after surgery for hydrocephalus, skull fracture, perinatal maternal infection history, and catheter-related infection. The main symptoms were fever and poor response. In those patients, 22% had seizures; no child had meningeal irritation sign or disturbance of consciousness. The white blood cell count and level of C-reactive protein were normal or increased; the nucleated cell count in cerebrospinal fluid was normal or mildly elevated; the protein level was substantially elevated; the glucose level was decreased. The drug sensitivity test showed that bacteria were all sensitive to vancomycin and the vancomycin treatment was effective. Only one child had the complication of hydrocephalus. Enterococcus faecium meningitis occurs mainly in neonates and infants. The patients have atypical clinical features. A high proportion of patients with Enterococcus faecium meningitis have high-risk factors. Enterococcus faecium is sensitive to vancomycin.

Simultenious binary hash and features learning for image retrieval

NASA Astrophysics Data System (ADS)

Frantc, V. A.; Makov, S. V.; Voronin, V. V.; Marchuk, V. I.; Semenishchev, E. A.; Egiazarian, K. O.; Agaian, S.

2016-05-01

Content-based image retrieval systems have plenty of applications in modern world. The most important one is the image search by query image or by semantic description. Approaches to this problem are employed in personal photo-collection management systems, web-scale image search engines, medical systems, etc. Automatic analysis of large unlabeled image datasets is virtually impossible without satisfactory image-retrieval technique. It's the main reason why this kind of automatic image processing has attracted so much attention during recent years. Despite rather huge progress in the field, semantically meaningful image retrieval still remains a challenging task. The main issue here is the demand to provide reliable results in short amount of time. This paper addresses the problem by novel technique for simultaneous learning of global image features and binary hash codes. Our approach provide mapping of pixel-based image representation to hash-value space simultaneously trying to save as much of semantic image content as possible. We use deep learning methodology to generate image description with properties of similarity preservation and statistical independence. The main advantage of our approach in contrast to existing is ability to fine-tune retrieval procedure for very specific application which allow us to provide better results in comparison to general techniques. Presented in the paper framework for data- dependent image hashing is based on use two different kinds of neural networks: convolutional neural networks for image description and autoencoder for feature to hash space mapping. Experimental results confirmed that our approach has shown promising results in compare to other state-of-the-art methods.

Suspect identification by facial features.

PubMed

Lee, Eric; Whalen, Thomas; Sakalauskas, John; Baigent, Glen; Bisesar, Chandra; McCarthy, Andrew; Reid, Glenda; Wotton, Cynthia

2004-06-10

Often during criminal investigations, witnesses must examine photographs of known offenders, colloquially called 'mug shots'. As witnesses view increasing numbers of mug shots that are presented in an arbitrary order, they become more likely to identify the wrong suspect. An alternative is a subjective feature-based mug shot retrieval system in which witnesses first complete a questionnaire about the appearance of the suspect, and then examine photographs in order of decreasing resemblance to their description. In the first experiment, this approach is found to be more efficient and more accurate than searching an album. The next three experiments show that it makes little difference if the witness has seen the suspect in person or only seen a photograph. In the last two experiments, it is shown that the feature-based retrieval system is effective even when the witness has seen the suspect in realistic natural settings. The results show that the main conclusions drawn from previous studies, where witnesses searched for faces seen only in photographs, also apply when witnesses are searching for a face that they saw live in naturalistic settings. Additionally, it is shown that is it better to have two raters than one create the database, but that more than two raters yield rapidly diminishing returns for the extra cost.

The Importance of Three Physical Processes in a Minimal Three-Dimensional Tropical Cyclone Model.

NASA Astrophysics Data System (ADS)

Zhu, Hongyan; Smith, Roger K.

2002-06-01

The minimal three-dimensional tropical cyclone model developed by Zhu et al. is used to explore the role of shallow convection, precipitation-cooled downdrafts, and the vertical transport of momentum by deep convection on the dynamics of tropical cyclone intensification. The model is formulated in coordinates and has three vertical levels, one characterizing a shallow boundary layer, and the other two representing the upper and lower troposphere, respectively. It has three options for treating cumulus convection on the subgrid scale and a simple scheme for the explicit release of latent heat on the grid scale.In the model, as in reality, shallow convection transports air with low moist static energy from the lower troposphere to the boundary layer, stabilizing the atmosphere not only to itself, but also to deep convection. Also it moistens and cools the lower troposphere. For realistic parameter values, the stabilization in the vortex core region is the primary effect: it reduces the deep convective mass flux and therefore the rate of heating and drying in the troposphere. This reduced heating, together with the direct cooling of the lower troposphere by shallow convection, diminishes the buoyancy in the vortex core and thereby the vortex intensification rate.The effects of precipitation-cooled downdrafts depend on the closure scheme chosen for deep convection. In the two closures in which the deep cloud mass flux depends on the degree of convective instability, the downdrafts do not change the total mass flux of air that subsides into the boundary layer, but they carry air with a lower moist static energy into this layer than does subsidence outside downdrafts. As a result they decrease the rate of intensification during the early development stage. Nevertheless, by reducing the deep convective mass flux and the drying effect of compensating subsidence, they enable grid scale saturation, and therefore rapid intensification, to occur earlier than in calculations

Features extraction in anterior and posterior cruciate ligaments analysis.

PubMed

Zarychta, P

2015-12-01

The main aim of this research is finding the feature vectors of the anterior and posterior cruciate ligaments (ACL and PCL). These feature vectors have to clearly define the ligaments structure and make it easier to diagnose them. Extraction of feature vectors is obtained by analysis of both anterior and posterior cruciate ligaments. This procedure is performed after the extraction process of both ligaments. In the first stage in order to reduce the area of analysis a region of interest including cruciate ligaments (CL) is outlined in order to reduce the area of analysis. In this case, the fuzzy C-means algorithm with median modification helping to reduce blurred edges has been implemented. After finding the region of interest (ROI), the fuzzy connectedness procedure is performed. This procedure permits to extract the anterior and posterior cruciate ligament structures. In the last stage, on the basis of the extracted anterior and posterior cruciate ligament structures, 3-dimensional models of the anterior and posterior cruciate ligament are built and the feature vectors created. This methodology has been implemented in MATLAB and tested on clinical T1-weighted magnetic resonance imaging (MRI) slices of the knee joint. The 3D display is based on the Visualization Toolkit (VTK). Copyright © 2015 Elsevier Ltd. All rights reserved.

Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching

PubMed Central

Guo, Yanrong; Gao, Yaozong

2016-01-01

Automatic and reliable segmentation of the prostate is an important but difficult task for various clinical applications such as prostate cancer radiotherapy. The main challenges for accurate MR prostate localization lie in two aspects: (1) inhomogeneous and inconsistent appearance around prostate boundary, and (2) the large shape variation across different patients. To tackle these two problems, we propose a new deformable MR prostate segmentation method by unifying deep feature learning with the sparse patch matching. First, instead of directly using handcrafted features, we propose to learn the latent feature representation from prostate MR images by the stacked sparse auto-encoder (SSAE). Since the deep learning algorithm learns the feature hierarchy from the data, the learned features are often more concise and effective than the handcrafted features in describing the underlying data. To improve the discriminability of learned features, we further refine the feature representation in a supervised fashion. Second, based on the learned features, a sparse patch matching method is proposed to infer a prostate likelihood map by transferring the prostate labels from multiple atlases to the new prostate MR image. Finally, a deformable segmentation is used to integrate a sparse shape model with the prostate likelihood map for achieving the final segmentation. The proposed method has been extensively evaluated on the dataset that contains 66 T2-wighted prostate MR images. Experimental results show that the deep-learned features are more effective than the handcrafted features in guiding MR prostate segmentation. Moreover, our method shows superior performance than other state-of-the-art segmentation methods. PMID:26685226

Backscattered electron simulations to evaluate sensitivity against electron dosage of buried semiconductor features

NASA Astrophysics Data System (ADS)

Mukhtar, Maseeh; Thiel, Bradley

2018-03-01

In fabrication, overlay measurements of semiconductor device patterns have conventionally been performed using optical methods. Beginning with image-based techniques using box-in-box to the more recent diffraction-based overlay (DBO). Alternatively, use of SEM overlay is under consideration for in-device overlay. Two main application spaces are measurement features from multiple mask levels on the same surface and buried features. Modern CD-SEMs are adept at measuring overlay for cases where all features are on the surface. In order to measure overlay of buried features, HV-SEM is needed. Gate-to-fin and BEOL overlay are important use cases for this technique. A JMONSEL simulation exercise was performed for these two cases using 10 nm line/space gratings of graduated increase in depth of burial. Backscattered energy loss results of these simulations were used to calculate the sensitivity measurements of buried features versus electron dosage for an array of electron beam voltages.

3D facial expression recognition using maximum relevance minimum redundancy geometrical features

NASA Astrophysics Data System (ADS)

Rabiu, Habibu; Saripan, M. Iqbal; Mashohor, Syamsiah; Marhaban, Mohd Hamiruce

2012-12-01

In recent years, facial expression recognition (FER) has become an attractive research area, which besides the fundamental challenges, it poses, finds application in areas, such as human-computer interaction, clinical psychology, lie detection, pain assessment, and neurology. Generally the approaches to FER consist of three main steps: face detection, feature extraction and expression recognition. The recognition accuracy of FER hinges immensely on the relevance of the selected features in representing the target expressions. In this article, we present a person and gender independent 3D facial expression recognition method, using maximum relevance minimum redundancy geometrical features. The aim is to detect a compact set of features that sufficiently represents the most discriminative features between the target classes. Multi-class one-against-one SVM classifier was employed to recognize the seven facial expressions; neutral, happy, sad, angry, fear, disgust, and surprise. The average recognition accuracy of 92.2% was recorded. Furthermore, inter database homogeneity was investigated between two independent databases the BU-3DFE and UPM-3DFE the results showed a strong homogeneity between the two databases.

Topographic Feature Names on Venus: Progress in 2000, Review of 1997-2000 Development, Current State, and Prospective

NASA Technical Reports Server (NTRS)

Burba, G. A.; Blue, J.; Campbell, D. B.; Dollfus, A.; Gaddis, L.; Jurgens, R. F.; Marov, M. Ya.; Pettengill, G. H.; Stofan, E. R.

2001-01-01

12 names assigned on Venus in 2000. The current list includes 1821 names of 21 feature types. 95% of names present 11 types of features. The main named types are craters - 872, and coronae - 267. These two types possess 62% of the names. Additional information is contained in the original extended abstract.

Comprehensive chlorophyll composition in the main edible seaweeds.

PubMed

Chen, Kewei; Ríos, José Julián; Pérez-Gálvez, Antonio; Roca, María

2017-08-01

Natural chlorophylls present in seaweeds have been studied regarding their biological activities and health benefit effects. However, detailed studies regarding characterization of the complete chlorophyll profile either qualitatively and quantitatively are scarce. This work deals with the comprehensive spectrometric study of the chlorophyll derivatives present in the five main coloured edible seaweeds. The novel complete MS 2 characterization of five chlorophyll derivatives: chlorophyll c 2 , chlorophyll c 1 , purpurin-18 a, pheophytin d and phytyl-purpurin-18 a has allowed to obtain fragmentation patterns associated with their different structural features. New chlorophyll derivatives have been identified and quantified by first time in red, green and brown seaweeds, including some oxidative structures. Quantitative data of the chlorophyll content comes to achieve significant information for food composition databases in bioactive compounds. Copyright © 2017 Elsevier Ltd. All rights reserved.

Recognizing human activities using appearance metric feature and kinematics feature

NASA Astrophysics Data System (ADS)

Qian, Huimin; Zhou, Jun; Lu, Xinbiao; Wu, Xinye

2017-05-01

The problem of automatically recognizing human activities from videos through the fusion of the two most important cues, appearance metric feature and kinematics feature, is considered. And a system of two-dimensional (2-D) Poisson equations is introduced to extract the more discriminative appearance metric feature. Specifically, the moving human blobs are first detected out from the video by background subtraction technique to form a binary image sequence, from which the appearance feature designated as the motion accumulation image and the kinematics feature termed as centroid instantaneous velocity are extracted. Second, 2-D discrete Poisson equations are employed to reinterpret the motion accumulation image to produce a more differentiated Poisson silhouette image, from which the appearance feature vector is created through the dimension reduction technique called bidirectional 2-D principal component analysis, considering the balance between classification accuracy and time consumption. Finally, a cascaded classifier based on the nearest neighbor classifier and two directed acyclic graph support vector machine classifiers, integrated with the fusion of the appearance feature vector and centroid instantaneous velocity vector, is applied to recognize the human activities. Experimental results on the open databases and a homemade one confirm the recognition performance of the proposed algorithm.

Investigating Relationships between Features of Learning Designs and Student Learning Outcomes

ERIC Educational Resources Information Center

McNaught, Carmel; Lam, Paul; Cheng, Kin Fai

2012-01-01

This article reports a study of eLearning in 21 courses in Hong Kong universities that had a blended design of face-to-face classes combined with online learning. The main focus of the study was to examine possible relationships between features of online learning designs and student learning outcomes. Data-collection strategies included expert…

Qualitative Features Extraction from Sensor Data using Short-time Fourier Transform

NASA Technical Reports Server (NTRS)

Amini, Abolfazl M.; Figueroa, Fernando

2004-01-01

The information gathered from sensors is used to determine the health of a sensor. Once a normal mode of operation is established any deviation from the normal behavior indicates a change. This change may be due to a malfunction of the sensor(s) or the system (or process). The step-up and step-down features, as well as sensor disturbances are assumed to be exponential. An RC network is used to model the main process, which is defined by a step-up (charging), drift, and step-down (discharging). The sensor disturbances and spike are added while the system is in drift. The system runs for a period of at least three time-constants of the main process every time a process feature occurs (e.g. step change). The Short-Time Fourier Transform of the Signal is taken using the Hamming window. Three window widths are used. The DC value is removed from the windowed data prior to taking the FFT. The resulting three dimensional spectral plots provide good time frequency resolution. The results indicate distinct shapes corresponding to each process.

Feature-based attention elicits surround suppression in feature space.

PubMed

Störmer, Viola S; Alvarez, George A

2014-09-08

It is known that focusing attention on a particular feature (e.g., the color red) facilitates the processing of all objects in the visual field containing that feature [1-7]. Here, we show that such feature-based attention not only facilitates processing but also actively inhibits processing of similar, but not identical, features globally across the visual field. We combined behavior and electrophysiological recordings of frequency-tagged potentials in human observers to measure this inhibitory surround in feature space. We found that sensory signals of an attended color (e.g., red) were enhanced, whereas sensory signals of colors similar to the target color (e.g., orange) were suppressed relative to colors more distinct from the target color (e.g., yellow). Importantly, this inhibitory effect spreads globally across the visual field, thus operating independently of location. These findings suggest that feature-based attention comprises an excitatory peak surrounded by a narrow inhibitory zone in color space to attenuate the most distracting and potentially confusable stimuli during visual perception. This selection profile is akin to what has been reported for location-based attention [8-10] and thus suggests that such center-surround mechanisms are an overarching principle of attention across different domains in the human brain. Copyright © 2014 Elsevier Ltd. All rights reserved.

Selection of the best features for leukocytes classification in blood smear microscopic images

NASA Astrophysics Data System (ADS)

Sarrafzadeh, Omid; Rabbani, Hossein; Talebi, Ardeshir; Banaem, Hossein Usefi

2014-03-01

Automatic differential counting of leukocytes provides invaluable information to pathologist for diagnosis and treatment of many diseases. The main objective of this paper is to detect leukocytes from a blood smear microscopic image and classify them into their types: Neutrophil, Eosinophil, Basophil, Lymphocyte and Monocyte using features that pathologists consider to differentiate leukocytes. Features contain color, geometric and texture features. Colors of nucleus and cytoplasm vary among the leukocytes. Lymphocytes have single, large, round or oval and Monocytes have singular convoluted shape nucleus. Nucleus of Eosinophils is divided into 2 segments and nucleus of Neutrophils into 2 to 5 segments. Lymphocytes often have no granules, Monocytes have tiny granules, Neutrophils have fine granules and Eosinophils have large granules in cytoplasm. Six color features is extracted from both nucleus and cytoplasm, 6 geometric features only from nucleus and 6 statistical features and 7 moment invariants features only from cytoplasm of leukocytes. These features are fed to support vector machine (SVM) classifiers with one to one architecture. The results obtained by applying the proposed method on blood smear microscopic image of 10 patients including 149 white blood cells (WBCs) indicate that correct rate for all classifiers are above 93% which is in a higher level in comparison with previous literatures.

Geology of the Cupsuptic quadrangle, Maine

USGS Publications Warehouse

Harwood, David S.

1966-01-01

The Cupsuptic quadrangle, in west-central Maine, lies in a relatively narrow belt of pre-Silurian rocks extending from the Connecticut River valley across northern New Hampshire to north-central Maine. The Albee Formation, composed of green, purple, and black phyllite with interbedded-quartzite, is exposed in the core of a regional anticlinorium overlain to the southeast by greenstone of the Oquossoc Formation which in turn is overlain by black slate of the Kamankeag Formation. In the northern part of the quadrangle the Albee Formation is overlain by black slate, feldspathic graywacke, and minor greenstone of the Dixville Formation. The Kamankeag Formation is dated as 1-ate Middle Ordovician by graptolites (zone 12) found near the base of the unit. The Dixville Formation is correlated with the Kamankeag Formation and Oquossoc Formation and is considered to be Middle Ordovician. The Albee Formation is considered to be Middle to Lower Ordovician from correlations with similar rocks in northeastern and southwestern Vermont. The Oquossoc and Kamankeag Formations are correlated with the Amonoosuc and Partridge Formations of northern New Hampshire. The pre-Silurian rocks are unconformably overlain by unnamed rocks of Silurian age in the southeast, west-central, and northwest ninths of the quadrangle. The basal Silurian units are boulder to cobble polymict conglomerate and quartz-pebble conglomerate of late Lower Silurian (Upper Llandovery) age. The overlying rocks are either well-bedded slate and quartzite, silty limestone, or arenaceous limestone. Thearenaceous limestone contains Upper Silurian (Lower Ludlow) brachiopods. The stratified rocks have been intruded by three stocks of biotite-muscovite quartz monzonite, a large body of metadiorite and associated serpentinite, smaller bodies of gabbro, granodiorite, and intrusive felsite, as well as numerous diabase and quartz monzonite dikes. The metadiorite and serpentinite, and possibly the gabbro and granodiorite are Late

[Clinical and histopathological features of myositis associated with anti-mitochondrial antibodies].

PubMed

Shimizu, Jun

2013-01-01

Anti-mitochondrial antibodies (AMA) are known to be characteristic markers of primary biliary cirrhosis (PBC). The association of PBC with myositis has been reported mainly as case reports, and comprehensive studies of the clinical and histopathological features of patients with myositis and AMAs or PBC have not been conducted thus far. We retrospectively reviewed 212 patients with inflammatory myopathies in our laboratory and found 24 patients with AMA-positive myositis (11%) (seven patients with PBC and 17 patients without PBC). The analysis of clinical and histopathological features revealed that myositis associated with AMAs frequently include patients with a clinically chronic disease course, muscle atrophy, cardiopulmonary involvement and granulomatous inflammation, regardless of the presence or absence of PBC. We also reviewed and analyzed the clinical features of previously reported patients. The analysis of 75 patients, which have been described in previous case reports including the ones of meeting abstracts, also showed the similar results about clinical features of myositis associated with AMAs and supported our findings. Our study suggests that myositis associated with AMAs form a characteristic subgroup.

Frequency of the first feature in action sequences influences feature binding.

PubMed

Mattson, Paul S; Fournier, Lisa R; Behmer, Lawrence P

2012-10-01

We investigated whether binding among perception and action feature codes is a preliminary step toward creating a more durable memory trace of an action event. If so, increasing the frequency of a particular event (e.g., a stimulus requiring a movement with the left or right hand in an up or down direction) should increase the strength and speed of feature binding for this event. The results from two experiments, using a partial-repetition paradigm, confirmed that feature binding increased in strength and/or occurred earlier for a high-frequency (e.g., left hand moving up) than for a low-frequency (e.g., right hand moving down) event. Moreover, increasing the frequency of the first-specified feature in the action sequence alone (e.g., "left" hand) increased the strength and/or speed of action feature binding (e.g., between the "left" hand and movement in an "up" or "down" direction). The latter finding suggests an update to the theory of event coding, as not all features in the action sequence equally determine binding strength. We conclude that action planning involves serial binding of features in the order of action feature execution (i.e., associations among features are not bidirectional but are directional), which can lead to a more durable memory trace. This is consistent with physiological evidence suggesting that serial order is preserved in an action plan executed from memory and that the first feature in the action sequence may be critical in preserving this serial order.

Main neuroendocrine features and therapy in primary sleep troubles.

PubMed

Amihăesei, Ioana Cristina; Mungiu, O C

2012-01-01

Insomnia is a sleep trouble in which the patient has difficulties in falling or in staying asleep. There are patients who fall asleep easily, but wake up too early; others have troubles in falling asleep and a third category has troubles with both falling and staying asleep. Independent of the type of insomnia, the final result is a poor-quality sleep, responsible for depressive or irritable mood, loss in concentration, learning and memory capacities. Sleep is essential to emotional and physical health. Inadequate sleep over a period of time is increasing the risks for obesity, diabetes, heart disease and depression. People suffering of chronic insomnia show an increased predisposition for psychiatric problems. People who had sleep troubles reported impaired ability to fulfill tasks involving memory, learning, logical reasoning and mathematical operations. New studies show that insomnia might be a result of the decrease of gamma-aminobutyric acid (GABA), a neurochemical responsible for the decrease of activity in many brain areas. Lower brain GABA levels were also found in people with major depressive disorder and anxiety disorders. Hypnotics, such as benzodiazepines are acting increasing the activity of the GABA neurons. Exposure to stress is associated with a greater risk for insomnia, with individual differences. Stress activates the sympathetic nervous system and the hypothalamic-pituitary-adrenal (HPA) axis. Increased activity of HPA axis is stimulating the secretion of corticotropin-releasing hormone, further inducing sleep disruption. Insomnia is also associated with depression and anxiety disorders, in which the HPA axis is characteristically overactive. People who show predisposition to sleep troubles have a hyperactive sympathetic nervous system, they are usually suffering from hyperarousal and they have a more intense response to stressful events. Primary sleep troubles (insomnia) has no apparent causes, is lasting more than one month, and is affecting approximately a quarter of the adult population. Secondary insomnia is associated with chronic heart and/or lung diseases, medication which interfere with onset or duration of sleep, constant change of the sleep habits, restless leg syndrome, etc. Besides lifestyle changes and cogn itive-behavioral therapy, in the treatment of insomnia are used hypnotic medicines, advised to be prescribed on short-term cures of one or two weeks. Benzodiazepines are inducing and maintaining sleep. Longer use is responsible for severe side effects--dependency and withdrawal syndrome, daytime drowsiness and dizziness, low blood pressure, memory troubles and change in the melatonin secretion during night-time period. For these reasons were created non-benzodiazepines hypnotics--zolpidem, zaleplon, which are as effective as benzodiazepines, but have fewer side effects. Nevertheless the use of these hypnotics is also restricted to 7-10 days. Zopiclone (Imovane) another short-acting non-benzodiazepine hypnotic has a different chemical structure, but a pharmacologic profile similar to that of the benzod iazepines; the treatment should be of maximum four weeks. Besides generally known concerns related to the use of hypnotics (residual sedative effects, memory impairment, rebound insomnia, abuse, dose escalation, dependency and withdrawal problems) it was signaled a risk of death associated with the use of current hypnotic medications.

Associations between park features and adolescent park use for physical activity.

PubMed

Edwards, Nicole; Hooper, Paula; Knuiman, Matthew; Foster, Sarah; Giles-Corti, Billie

2015-02-18

Eighty per cent of adolescents globally do insufficient physical activity. Parks are a popular place for adolescents to be active. However, little is known about which park features are associated with higher levels of park use by adolescents. This study aimed to examine which environmental park features, and combination of features, were correlated with higher levels of park use for physical activity among adolescents. By examining park features in parks used by adolescents for physical activity, this study also aimed to create a park 'attractiveness' score predictive of adolescent park use, and to identify factors that might predict use of their closest park. Adolescents (n = 1304) living in Geraldton, a large rural centre of Western Australia, completed a survey that measured physical activity behaviour, perceptions of park availability and the main park used for physical activity. All parks in the study area (n = 58) were digitized using a Geographic Information System (GIS) and features audited using the Public Open Space Desktop Auditing Tool (POSDAT). Only 27% of participants reported using their closest park for physical activity. Park use was associated with seven features: presence of a skate park, walking paths, barbeques, picnic table, public access toilets, lighting around courts and equipment and number of trees >25. When combined to create an overall attractiveness score, every additional 'attractive' feature present, resulted in a park being nearly three times more likely to be in the high use category. To increase park use for physical activity, urban planners and designers should incorporate park features attractive to adolescents.

Effect of fuels and domestic heating appliance types on emission factors of selected organic pollutants.

PubMed

Šyc, Michal; Horák, Jiří; Hopan, František; Krpec, Kamil; Tomšej, Tomáš; Ocelka, Tomáš; Pekárek, Vladimír

2011-11-01

This study reports on the first complex data set of emission factors (EFs) of selected pollutants from combustion of five fuel types (lignite, bituminous coal, spruce, beech, and maize) in six different domestic heating appliances of various combustion designs. The effect of fuel as well as the effect of boiler type was studied. In total, 46 combustion runs were performed, during which numerous EFs were measured, including the EFs of particulate matter (PM), carbon monoxide, polyaromatic hydrocarbons (PAH), hexachlorobenzene (HxCBz), polychlorinated dibenzo-p-dioxins and furans (PCDD/F), etc. The highest EFs of nonchlorinated pollutants were measured for old-type boilers with over-fire and under-fire designs and with manual stoking and natural draft. Emissions of the above-mentioned pollutants from modern-type boilers (automatic, downdraft) were 10 times lower or more. The decisive factor for emission rate of nonchlorinated pollutants was the type of appliance; the type of fuel plays only a minor role. Emissions of chlorinated pollutants were proportional mainly to the chlorine content in fuel, but the type of appliance also influenced the rate of emissions significantly. Surprisingly, higher EFs of PCDD/F from combustion of chlorinated bituminous coal were observed for modern-type boilers (downdraft, automatic) than for old-type ones. On the other hand, when bituminous coal was burned, higher emissions of HxCBz were found for old-type boilers than for modern-type ones.

Numerical simulation of intense multi-scale vortices generated by supercell thunderstorms

NASA Astrophysics Data System (ADS)

Finley, Catherine Ann

1998-11-01

downdraft played an important role in tilting horizontal vorticity into the vertical just above the surface in the near tornado environment where horizontal convergence could then act to amplify it. A comparison with the proposed tornadogenesis process(es) in classical supercells is also presented. The May 15, 1991, simulation produced a classical supercell which developed along the dryline in the Texas panhandle. This supercell in turn produced a tornado which lasted for 50 minutes in the simulation. During a ten minute period toward the end of the simulation, six secondary vortices developed within the main tornado vortex. The simulated secondary vortices had many features in common with multiple-vortex tornadoes and secondary vortices produced in laboratory vortices. The evolution and structure of the simulated secondary vortices is presented, and physical mechanisms responsible for their development and dissipation are discussed.

Feature-to-Feature Inference Under Conditions of Cue Restriction and Dimensional Correlation.

PubMed

Lancaster, Matthew E; Homa, Donald

2017-01-01

The present study explored feature-to-feature and label-to-feature inference in a category task for different category structures. In the correlated condition, each of the 4 dimensions comprising the category was positively correlated to each other and to the category label. In the uncorrelated condition, no correlation existed between the 4 dimensions comprising the category, although the dimension to category label correlation matched that of the correlated condition. After learning, participants made inference judgments of a missing feature, given 1, 2, or 3 feature cues; on half the trials, the category label was also included as a cue. The results showed superior inference of features following training on the correlated structure, with accurate inference when only a single feature was presented. In contrast, a single-feature cue resulted in chance levels of inference for the uncorrelated structure. Feature inference systematically improved with number of cues after training on the correlated structure. Surprisingly, a similar outcome was obtained for the uncorrelated structure, an outcome that must have reflected mediation via the category label. A descriptive model is briefly introduced to explain the results, with a suggestion that this paradigm might be profitably extended to hierarchical structures where the levels of feature-to-feature inference might vary with the depth of the hierarchy.

Recent Arecibo Radar Observations of Main-Belt Asteroids.

NASA Astrophysics Data System (ADS)

Shepard, Michael K.; Howell, Ellen; Nolan, Michael; Taylor, Patrick; Springmann, Alessondra; Giorgini, Jon; Benner, Lance; Magri, Christopher

2014-11-01

We recently observed main-belt asteroids 12 Victoria (Tholen S-class, Bus L-class), 246 Asporina (A-class), and 2035 Stearns with the S-band (12 cm) Arecibo radar. Signal-to-noise ratios for Asporina and Stearns were only strong enough for continuous-wave (CW) analysis. Signal-to-noise ratios for Victoria were high enough for delay-Doppler imaging. Stearns exhibited a high radar polarization ratio of unity, higher than any other main-belt E-class, but similar to near-Earth E-class asteroids [Benner et al. Icarus 198, 294-304, 2008; Shepard et al. Icarus 215, 547-551, 2011]. The A-class asteroids show spectral absorption features consistent with olivine and have been suggested as the source of pallasite meteorites or the rare brachinites [Cruikshank and Hartmann, Science 223, 281-283, 1984]. The radar cross-section measured for Asporina leads to a radar albedo estimate of 0.11, suggesting a low near-surface bulk density, and by inference, a low metal content. This suggests that the brachinites are a better analog for Asporina than the iron-rich pallasites. Victoria has been observed by radar in the past and the continuous-wave echoes suggest it has a large concavity or is a contact binary [Mitchell et al. Icarus 118, 105-131, 1995]. Our new imaging observations should determine which is more likely.

Defeating feature fatigue.

PubMed

Rust, Roland T; Thompson, Debora Viana; Hamilton, Rebecca W

2006-02-01

Consider a coffeemaker that offers 12 drink options, a car with more than 700 features on the dashboard, and a mouse pad that's also a clock, calculator, and FM radio. All are examples of "feature bloat", or "featuritis", the result of an almost irresistible temptation to load products with lots of bells and whistles. The problem is that the more features a product boasts, the harder it is to use. Manufacturers that increase a product's capability--the number of useful functions it can perform--at the expense of its usability are exposing their customers to feature fatigue. The authors have conducted three studies to gain a better understanding of how consumers weigh a product's capability relative to its usability. They found that even though consumers know that products with more features are harder to use, they initially choose high-feature models. They also pile on more features when given the chance to customize a product for their needs. Once consumers have actually worked with a product, however, usability starts to matter more to them than capability. For managers in consumer products companies, these findings present a dilemma: Should they maximize initial sales by designing high-feature models, which consumers consistently choose, or should they limit the number of features in order to enhance the lifetime value of their customers? The authors' analytical model guides companies toward a happy middle ground: maximizing the net present value of the typical customer's profit stream. The authors also advise companies to build simpler products, help consumers learn which products suit their needs, develop products that do one thing very well, and design market research in which consumers use actual products or prototypes.

Slim Battery Modelling Features

NASA Astrophysics Data System (ADS)

Borthomieu, Y.; Prevot, D.

2011-10-01

Saft has developed a life prediction model for VES and MPS cells and batteries. The Saft Li-ion Model (SLIM) is a macroscopic electrochemical model based on energy (global at cell level). The main purpose is to predict the battery performances during the life for GEO, MEO and LEO missions. This model is based on electrochemical characteristics such as Energy, Capacity, EMF, Internal resistance, end of charge voltage. It uses fading and calendar law effects on energy and internal impedance vs. time, temperature, End of Charge voltage. Based on the mission profile, satellite power system characteristics, the model proposes the various battery configurations. For each configuration, the model gives the battery performances using mission figures and profiles: power, duration, DOD, end of charge voltages, temperatures during eclipses and solstices, thermal dissipations and cell failures. For the GEO/MEO missions, eclipse and solstice periods can include specific profile such as plasmic propulsion fires and specific balancing operations. For LEO missions, the model is able to simulate high power peaks to predict radar pulses. Saft's main customers have been using the SLIM model available in house for two years. The purpose is to have the satellite builder power engineers able to perform by themselves in the battery pre-dimensioning activities their own battery simulations. The simulations can be shared with Saft engineers to refine the power system designs. This model has been correlated with existing life and calendar tests performed on all the VES and MPS cells. In comparing with more than 10 year lasting life tests, the accuracy of the model from a voltage point of view is less than 10 mV at end Of Life. In addition, thethe comparison with in-orbit data has been also done. b This paper will present the main features of the SLIM software and outputs comparison with real life tests. b0

Realistic Solar Surface Convection Simulations

NASA Technical Reports Server (NTRS)

Stein, Robert F.; Nordlund, Ake

2000-01-01

We perform essentially parameter free simulations with realistic physics of convection near the solar surface. We summarize the physics that is included and compare the simulation results with observations. Excellent agreement is obtained for the depth of the convection zone, the p-mode frequencies, the p-mode excitation rate, the distribution of the emergent continuum intensity, and the profiles of weak photospheric lines. We describe how solar convection is nonlocal. It is driven from a thin surface thermal boundary layer where radiative cooling produces low entropy gas which forms the cores of the downdrafts in which most of the buoyancy work occurs. We show that turbulence and vorticity are mostly confined to the intergranular lanes and underlying downdrafts. Finally, we illustrate our current work on magneto-convection.

Combining morphometric features and convolutional networks fusion for glaucoma diagnosis

NASA Astrophysics Data System (ADS)

Perdomo, Oscar; Arevalo, John; González, Fabio A.

2017-11-01

Glaucoma is an eye condition that leads to loss of vision and blindness. Ophthalmoscopy exam evaluates the shape, color and proportion between the optic disc and physiologic cup, but the lack of agreement among experts is still the main diagnosis problem. The application of deep convolutional neural networks combined with automatic extraction of features such as: the cup-to-disc distance in the four quadrants, the perimeter, area, eccentricity, the major radio, the minor radio in optic disc and cup, in addition to all the ratios among the previous parameters may help with a better automatic grading of glaucoma. This paper presents a strategy to merge morphological features and deep convolutional neural networks as a novel methodology to support the glaucoma diagnosis in eye fundus images.

A nonlinear discriminant algorithm for feature extraction and data classification.

PubMed

Santa Cruz, C; Dorronsoro, J R

1998-01-01

This paper presents a nonlinear supervised feature extraction algorithm that combines Fisher's criterion function with a preliminary perceptron-like nonlinear projection of vectors in pattern space. Its main motivation is to combine the approximation properties of multilayer perceptrons (MLP's) with the target free nature of Fisher's classical discriminant analysis. In fact, although MLP's provide good classifiers for many problems, there may be some situations, such as unequal class sizes with a high degree of pattern mixing among them, that may make difficult the construction of good MLP classifiers. In these instances, the features extracted by our procedure could be more effective. After the description of its construction and the analysis of its complexity, we will illustrate its use over a synthetic problem with the above characteristics.

3D Structures of the Sea-Breeze Front in Dual-Doppler Lidar Analysis and a State-of-the-Art Modeling System

NASA Astrophysics Data System (ADS)

Chen, G.; Iwai, H.; Seko, H.; Saito, K. K.; Sha, W.; Iwasaki, T.

2017-12-01

Sea breeze occurs at coastal regions around the world, with great impacts on the weather and air quality. Observations and forecasts of the fine-scale structures and local impacts of sea-breeze front (SBF) are a challenge. Three-dimensional structures of a quasi-stationary SBF were observed by dual-Doppler lidar over Sendai Airport in June 2007. Using a state-of-the-art local prediction system in which a computational fluid dynamics model is nested to a mesoscale model with data assimilation, we perform a realistic simulation of the observed SBF structures at 10-m resolution. Numerical simulations reproduce the detailed features of the SBF, such as frontal lobes/clefts, intense updrafts, rear downdrafts, and Kelvin-Helmholtz billows, consistent with lidar observations. Several localized maxima of updrafts occur at the active SBF lobes with ascending marine air mass and adjacent windward sides, where the ambient warm flows encounter a steep front face and penetrate SBF aloft. Strong downdrafts of marine cool air dominate at the SBF rear where they trap a high concentration of air pollutants. These features are regularly activated by the arc-shaped gravity currents at a horizontal scale of several kilometers and a period of 30 minutes. They are also influenced by the coastal buildings and strongly regulate the spatio-temporal variations of local winds near surface. The findings suggest that a novel full-scale nested prediction system has potential for forecasting coastal weather and environment at high precision, which are valuable for aviation safety, marine activities, and air quality monitoring. AcknowledgmentsThis study was supported by the Strategic Programs for Innovative Research (SPIRE) funded by the Japan Ministry of Education, Culture, Sports, Science and Technology (MEXT). The numerical calculations were performed using the K computer at RIKEN Advanced Institute for Computational Science (Proposal numbers hp130012 and hp140220). The observational data were

Observational features of equatorial coronal hole jets

NASA Astrophysics Data System (ADS)

Nisticò, G.; Bothmer, V.; Patsourakos, S.; Zimbardo, G.

2010-03-01

Collimated ejections of plasma called "coronal hole jets" are commonly observed in polar coronal holes. However, such coronal jets are not only a specific features of polar coronal holes but they can also be found in coronal holes appearing at lower heliographic latitudes. In this paper we present some observations of "equatorial coronal hole jets" made up with data provided by the STEREO/SECCHI instruments during a period comprising March 2007 and December 2007. The jet events are selected by requiring at least some visibility in both COR1 and EUVI instruments. We report 15 jet events, and we discuss their main features. For one event, the uplift velocity has been determined as about 200 km s-1, while the deceleration rate appears to be about 0.11 km s-2, less than solar gravity. The average jet visibility time is about 30 min, consistent with jet observed in polar regions. On the basis of the present dataset, we provisionally conclude that there are not substantial physical differences between polar and equatorial coronal hole jets.

ECG feature extraction and disease diagnosis.

PubMed

Bhyri, Channappa; Hamde, S T; Waghmare, L M

2011-01-01

An important factor to consider when using findings on electrocardiograms for clinical decision making is that the waveforms are influenced by normal physiological and technical factors as well as by pathophysiological factors. In this paper, we propose a method for the feature extraction and heart disease diagnosis using wavelet transform (WT) technique and LabVIEW (Laboratory Virtual Instrument Engineering workbench). LabVIEW signal processing tools are used to denoise the signal before applying the developed algorithm for feature extraction. First, we have developed an algorithm for R-peak detection using Haar wavelet. After 4th level decomposition of the ECG signal, the detailed coefficient is squared and the standard deviation of the squared detailed coefficient is used as the threshold for detection of R-peaks. Second, we have used daubechies (db6) wavelet for the low resolution signals. After cross checking the R-peak location in 4th level, low resolution signal of daubechies wavelet P waves and T waves are detected. Other features of diagnostic importance, mainly heart rate, R-wave width, Q-wave width, T-wave amplitude and duration, ST segment and frontal plane axis are also extracted and scoring pattern is applied for the purpose of heart disease diagnosis. In this study, detection of tachycardia, bradycardia, left ventricular hypertrophy, right ventricular hypertrophy and myocardial infarction have been considered. In this work, CSE ECG data base which contains 5000 samples recorded at a sampling frequency of 500 Hz and the ECG data base created by the S.G.G.S. Institute of Engineering and Technology, Nanded (Maharashtra) have been used.

Use of liquefaction-induced features for paleoseismic analysis - An overview of how seismic liquefaction features can be distinguished from other features and how their regional distribution and properties of source sediment can be used to infer the location and strength of Holocene paleo-earthquakes

USGS Publications Warehouse

Obermeier, S.F.

1996-01-01

Liquefaction features can be used in many field settings to estimate the recurrence interval and magnitude of strong earthquakes through much of the Holocene. These features include dikes, craters, vented sand, sills, and laterally spreading landslides. The relatively high seismic shaking level required for their formation makes them particularly valuable as records of strong paleo-earthquakes. This state-of-the-art summary for using liquefaction-induced features for paleoseismic interpretation and analysis takes into account both geological and geotechnical engineering perspectives. The driving mechanism for formation of the features is primarily the increased pore-water pressure associated with liquefaction of sand-rich sediment. The role of this mechanism is often supplemented greatly by the direct action of seismic shaking at the ground surface, which strains and breaks the clay-rich cap that lies immediately above the sediment that liquefied. Discussed in the text are the processes involved in formation of the features, as well as their morphology and characteristics in field settings. Whether liquefaction occurs is controlled mainly by sediment grain size, sediment packing, depth to the water table, and strength and duration of seismic shaking. Formation of recognizable features in the field generally requires a low-permeability cap above the sediment that liquefied. Field manifestations are controlled largely by the severity of liquefaction and the thickness and properties of the low-permeability cap. Criteria are presented for determining whether observed sediment deformation in the field originated by seismically induced liquefaction. These criteria have been developed mainly by observing historic effects of liquefaction in varied field settings. The most important criterion is that a seismic liquefaction origin requires widespread, regional development of features around a core area where the effects are most severe. In addition, the features must have a

Investigating a link between large and small-scale chaos features on Europa

NASA Astrophysics Data System (ADS)

Tognetti, L.; Rhoden, A.; Nelson, D. M.

2017-12-01

Chaos is one of the most recognizable, and studied, features on Europa's surface. Most models of chaos formation invoke liquid water at shallow depths within the ice shell; the liquid destabilizes the overlying ice layer, breaking it into mobile rafts and destroying pre-existing terrain. This class of model has been applied to both large-scale chaos like Conamara and small-scale features (i.e. microchaos), which are typically <10 km in diameter. Currently unknown, however, is whether both large-scale and small-scale features are produced together, e.g. through a network of smaller sills linked to a larger liquid water pocket. If microchaos features do form as satellites of large-scale chaos features, we would expect a drop off in the number density of microchaos with increasing distance from the large chaos feature; the trend should not be observed in regions without large-scale chaos features. Here, we test the hypothesis that large chaos features create "satellite" systems of smaller chaos features. Either outcome will help us better understand the relationship between large-scale chaos and microchaos. We focus first on regions surrounding the large chaos features Conamara and Murias (e.g. the Mitten). We map all chaos features within 90,000 sq km of the main chaos feature and assign each one a ranking (High Confidence, Probable, or Low Confidence) based on the observed characteristics of each feature. In particular, we look for a distinct boundary, loss of preexisting terrain, the existence of rafts or blocks, and the overall smoothness of the feature. We also note features that are chaos-like but lack sufficient characteristics to be classified as chaos. We then apply the same criteria to map microchaos features in regions of similar area ( 90,000 sq km) that lack large chaos features. By plotting the distribution of microchaos with distance from the center point of the large chaos feature or the mapping region (for the cases without a large feature), we

The Younger Dryas Main Line on Leka, Norway, as determined from a high resolution digital elevation model derived from airborne LiDAR data

NASA Astrophysics Data System (ADS)

Høgaas, Fredrik; Sveian, Harald

2015-02-01

The Main Line is a conspicuous late glacial erosive feature along parts of the Norwegian coastline. Although the shoreline has been much studied, the genesis of the ancient raised sea-level is still somewhat unaccounted for. In this study, the Main Line on Leka, Norway, is illuminated through a high resolution (1 m pixel size) digital elevation model (DEM) derived from airborne LiDAR data. The DEM allows a detailed mapping of the shoreline's dimensions and actual distribution and hence provides an improved foundation for interpreting the pronounced features. A new method for estimating cliff degradation during shoreline formation is presented. The Main Line is found from 106-112 m asl on Leka. Varying platform morphology across the island points to different shore-eroding mechanisms. The shoreline is thought to be developed through the interaction of sea-ice processes and freeze-thaw mechanisms, where the former agent is considered to be of particular importance where the platforms are most levelled. A bulge on the outermost part of the shoreline features is described for the first time and interpreted as a consequence of freeze-on plucking. Mean platform widths range from 9-29 m, while mean cliff degradation is estimated to be 140 m3 m- 1. By adapting the age span of Main Line formation reported elsewhere, maximum erosion rates over 1 Ma totals to 58 km. The study sheds light on the Main Line's potential as a reference level when assessing postglacial landscape development and highlights the significance of episodic erosional events in cold climate regimes.

JCE Feature Columns

NASA Astrophysics Data System (ADS)

Holmes, Jon L.

1999-05-01

The Features area of JCE Online is now readily accessible through a single click from our home page. In the Features area each column is linked to its own home page. These column home pages also have links to them from the online Journal Table of Contents pages or from any article published as part of that feature column. Using these links you can easily find abstracts of additional articles that are related by topic. Of course, JCE Online+ subscribers are then just one click away from the entire article. Finding related articles is easy because each feature column "site" contains links to the online abstracts of all the articles that have appeared in the column. In addition, you can find the mission statement for the column and the email link to the column editor that I mentioned above. At the discretion of its editor, a feature column site may contain additional resources. As an example, the Chemical Information Instructor column edited by Arleen Somerville will have a periodically updated bibliography of resources for teaching and using chemical information. Due to the increase in the number of these resources available on the WWW, it only makes sense to publish this information online so that you can get to these resources with a simple click of the mouse. We expect that there will soon be additional information and resources at several other feature column sites. Following in the footsteps of the Chemical Information Instructor, up-to-date bibliographies and links to related online resources can be made available. We hope to extend the online component of our feature columns with moderated online discussion forums. If you have a suggestion for an online resource you would like to see included, let the feature editor or JCE Online (jceonline@chem.wisc.edu) know about it. JCE Internet Features JCE Internet also has several feature columns: Chemical Education Resource Shelf, Conceptual Questions and Challenge Problems, Equipment Buyers Guide, Hal's Picks, Mathcad

Writers Identification Based on Multiple Windows Features Mining

NASA Astrophysics Data System (ADS)

Fadhil, Murad Saadi; Alkawaz, Mohammed Hazim; Rehman, Amjad; Saba, Tanzila

2016-03-01

Now a days, writer identification is at high demand to identify the original writer of the script at high accuracy. The one of the main challenge in writer identification is how to extract the discriminative features of different authors' scripts to classify precisely. In this paper, the adaptive division method on the offline Latin script has been implemented using several variant window sizes. Fragments of binarized text a set of features are extracted and classified into clusters in the form of groups or classes. Finally, the proposed approach in this paper has been tested on various parameters in terms of text division and window sizes. It is observed that selection of the right window size yields a well positioned window division. The proposed approach is tested on IAM standard dataset (IAM, Institut für Informatik und angewandte Mathematik, University of Bern, Bern, Switzerland) that is a constraint free script database. Finally, achieved results are compared with several techniques reported in the literature.

Real-time skin feature identification in a time-sequential video stream

NASA Astrophysics Data System (ADS)

Kramberger, Iztok

2005-04-01

Skin color can be an important feature when tracking skin-colored objects. Particularly this is the case for computer-vision-based human-computer interfaces (HCI). Humans have a highly developed feeling of space and, therefore, it is reasonable to support this within intelligent HCI, where the importance of augmented reality can be foreseen. Joining human-like interaction techniques within multimodal HCI could, or will, gain a feature for modern mobile telecommunication devices. On the other hand, real-time processing plays an important role in achieving more natural and physically intuitive ways of human-machine interaction. The main scope of this work is the development of a stereoscopic computer-vision hardware-accelerated framework for real-time skin feature identification in the sense of a single-pass image segmentation process. The hardware-accelerated preprocessing stage is presented with the purpose of color and spatial filtering, where the skin color model within the hue-saturation-value (HSV) color space is given with a polyhedron of threshold values representing the basis of the filter model. An adaptive filter management unit is suggested to achieve better segmentation results. This enables the adoption of filter parameters to the current scene conditions in an adaptive way. Implementation of the suggested hardware structure is given at the level of filed programmable system level integrated circuit (FPSLIC) devices using an embedded microcontroller as their main feature. A stereoscopic clue is achieved using a time-sequential video stream, but this shows no difference for real-time processing requirements in terms of hardware complexity. The experimental results for the hardware-accelerated preprocessing stage are given by efficiency estimation of the presented hardware structure using a simple motion-detection algorithm based on a binary function.

Functional Brain Connectivity as a New Feature for P300 Speller.

PubMed

Kabbara, Aya; Khalil, Mohamad; El-Falou, Wassim; Eid, Hassan; Hassan, Mahmoud

2016-01-01

The brain is a large-scale complex network often referred to as the "connectome". Cognitive functions and information processing are mainly based on the interactions between distant brain regions. However, most of the 'feature extraction' methods used in the context of Brain Computer Interface (BCI) ignored the possible functional relationships between different signals recorded from distinct brain areas. In this paper, the functional connectivity quantified by the phase locking value (PLV) was introduced to characterize the evoked responses (ERPs) obtained in the case of target and non-targets visual stimuli. We also tested the possibility of using the functional connectivity in the context of 'P300 speller'. The proposed approach was compared to the well-known methods proposed in the state of the art of "P300 Speller", mainly the peak picking, the area, time/frequency based features, the xDAWN spatial filtering and the stepwise linear discriminant analysis (SWLDA). The electroencephalographic (EEG) signals recorded from ten subjects were analyzed offline. The results indicated that phase synchrony offers relevant information for the classification in a P300 speller. High synchronization between the brain regions was clearly observed during target trials, although no significant synchronization was detected for a non-target trial. The results showed also that phase synchrony provides higher performance than some existing methods for letter classification in a P300 speller principally when large number of trials is available. Finally, we tested the possible combination of both approaches (classical features and phase synchrony). Our findings showed an overall improvement of the performance of the P300-speller when using Peak picking, the area and frequency based features. Similar performances were obtained compared to xDAWN and SWLDA when using large number of trials.

Uniform Local Binary Pattern Based Texture-Edge Feature for 3D Human Behavior Recognition.

PubMed

Ming, Yue; Wang, Guangchao; Fan, Chunxiao

2015-01-01

With the rapid development of 3D somatosensory technology, human behavior recognition has become an important research field. Human behavior feature analysis has evolved from traditional 2D features to 3D features. In order to improve the performance of human activity recognition, a human behavior recognition method is proposed, which is based on a hybrid texture-edge local pattern coding feature extraction and integration of RGB and depth videos information. The paper mainly focuses on background subtraction on RGB and depth video sequences of behaviors, extracting and integrating historical images of the behavior outlines, feature extraction and classification. The new method of 3D human behavior recognition has achieved the rapid and efficient recognition of behavior videos. A large number of experiments show that the proposed method has faster speed and higher recognition rate. The recognition method has good robustness for different environmental colors, lightings and other factors. Meanwhile, the feature of mixed texture-edge uniform local binary pattern can be used in most 3D behavior recognition.

Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Anbazhagan, Ashwin; Chen, Min; Reutens, David C.

2017-12-01

Objective. Epilepsy is a common neurological disorder characterized by recurrent, unprovoked seizures. The search for new treatments for seizures and epilepsy relies upon studies in animal models of epilepsy. To capture data on seizures, many applications require prolonged electroencephalography (EEG) with recordings that generate voluminous data. The desire for efficient evaluation of these recordings motivates the development of automated seizure detection algorithms. Approach. A new seizure detection method is proposed, based on multiple features and a simple thresholding technique. The features are derived from chaos theory, information theory and the power spectrum of EEG recordings and optimally exploit both linear and nonlinear characteristics of EEG data. Main result. The proposed method was tested with real EEG data from an experimental mouse model of epilepsy and distinguished seizures from other patterns with high sensitivity and specificity. Significance. The proposed approach introduces two new features: negative logarithm of adaptive correlation integral and power spectral coherence ratio. The combination of these new features with two previously described features, entropy and phase coherence, improved seizure detection accuracy significantly. Negative logarithm of adaptive correlation integral can also be used to compute the duration of automatically detected seizures.

An on-board pedestrian detection and warning system with features of side pedestrian

NASA Astrophysics Data System (ADS)

Cheng, Ruzhong; Zhao, Yong; Wong, ChupChung; Chan, KwokPo; Xu, Jiayao; Wang, Xin'an

2012-01-01

Automotive Active Safety(AAS) is the main branch of intelligence automobile study and pedestrian detection is the key problem of AAS, because it is related with the casualties of most vehicle accidents. For on-board pedestrian detection algorithms, the main problem is to balance efficiency and accuracy to make the on-board system available in real scenes, so an on-board pedestrian detection and warning system with the algorithm considered the features of side pedestrian is proposed. The system includes two modules, pedestrian detecting and warning module. Haar feature and a cascade of stage classifiers trained by Adaboost are first applied, and then HOG feature and SVM classifier are used to refine false positives. To make these time-consuming algorithms available in real-time use, a divide-window method together with operator context scanning(OCS) method are applied to increase efficiency. To merge the velocity information of the automotive, the distance of the detected pedestrian is also obtained, so the system could judge if there is a potential danger for the pedestrian in the front. With a new dataset captured in urban environment with side pedestrians on zebra, the embedded system and its algorithm perform an on-board available result on side pedestrian detection.

Classification Influence of Features on Given Emotions and Its Application in Feature Selection

NASA Astrophysics Data System (ADS)

Xing, Yin; Chen, Chuang; Liu, Li-Long

2018-04-01

In order to solve the problem that there is a large amount of redundant data in high-dimensional speech emotion features, we analyze deeply the extracted speech emotion features and select better features. Firstly, a given emotion is classified by each feature. Secondly, the recognition rate is ranked in descending order. Then, the optimal threshold of features is determined by rate criterion. Finally, the better features are obtained. When applied in Berlin and Chinese emotional data set, the experimental results show that the feature selection method outperforms the other traditional methods.

Detection and clustering of features in aerial images by neuron network-based algorithm

NASA Astrophysics Data System (ADS)

Vozenilek, Vit

2015-12-01

The paper presents the algorithm for detection and clustering of feature in aerial photographs based on artificial neural networks. The presented approach is not focused on the detection of specific topographic features, but on the combination of general features analysis and their use for clustering and backward projection of clusters to aerial image. The basis of the algorithm is a calculation of the total error of the network and a change of weights of the network to minimize the error. A classic bipolar sigmoid was used for the activation function of the neurons and the basic method of backpropagation was used for learning. To verify that a set of features is able to represent the image content from the user's perspective, the web application was compiled (ASP.NET on the Microsoft .NET platform). The main achievements include the knowledge that man-made objects in aerial images can be successfully identified by detection of shapes and anomalies. It was also found that the appropriate combination of comprehensive features that describe the colors and selected shapes of individual areas can be useful for image analysis.

Feature-based attentional modulation increases with stimulus separation in divided-attention tasks.

PubMed

Sally, Sharon L; Vidnyánsky, Zoltán; Papathomas, Thomas V

2009-01-01

Attention modifies our visual experience by selecting certain aspects of a scene for further processing. It is therefore important to understand factors that govern the deployment of selective attention over the visual field. Both location and feature-specific mechanisms of attention have been identified and their modulatory effects can interact at a neural level (Treue and Martinez-Trujillo, 1999). The effects of spatial parameters on feature-based attentional modulation were examined for the feature dimensions of orientation, motion and color using three divided-attention tasks. Subjects performed concurrent discriminations of two briefly presented targets (Gabor patches) to the left and right of a central fixation point at eccentricities of +/-2.5 degrees , 5 degrees , 10 degrees and 15 degrees in the horizontal plane. Gabors were size-scaled to maintain consistent single-task performance across eccentricities. For all feature dimensions, the data show a linear increase in the attentional effects with target separation. In a control experiment, Gabors were presented on an isoeccentric viewing arc at 10 degrees and 15 degrees at the closest spatial separation (+/-2.5 degrees ) of the main experiment. Under these conditions, the effects of feature-based attentional effects were largely eliminated. Our results are consistent with the hypothesis that feature-based attention prioritizes the processing of attended features. Feature-based attentional mechanisms may have helped direct the attentional focus to the appropriate target locations at greater separations, whereas similar assistance may not have been necessary at closer target spacings. The results of the present study specify conditions under which dual-task performance benefits from sharing similar target features and may therefore help elucidate the processes by which feature-based attention operates.

Therapeutic approaches against common structural features of toxic oligomers shared by multiple amyloidogenic proteins.

PubMed

Guerrero-Muñoz, Marcos J; Castillo-Carranza, Diana L; Kayed, Rakez

2014-04-15

Impaired proteostasis is one of the main features of all amyloid diseases, which are associated with the formation of insoluble aggregates from amyloidogenic proteins. The aggregation process can be caused by overproduction or poor clearance of these proteins. However, numerous reports suggest that amyloid oligomers are the most toxic species, rather than insoluble fibrillar material, in Alzheimer's, Parkinson's, and Prion diseases, among others. Although the exact protein that aggregates varies between amyloid disorders, they all share common structural features that can be used as therapeutic targets. In this review, we focus on therapeutic approaches against shared features of toxic oligomeric structures and future directions. Copyright © 2014 Elsevier Inc. All rights reserved.

Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion

PubMed Central

Zhao, Yuanshen; Gong, Liang; Huang, Yixiang; Liu, Chengliang

2016-01-01

Automatic recognition of mature fruits in a complex agricultural environment is still a challenge for an autonomous harvesting robot due to various disturbances existing in the background of the image. The bottleneck to robust fruit recognition is reducing influence from two main disturbances: illumination and overlapping. In order to recognize the tomato in the tree canopy using a low-cost camera, a robust tomato recognition algorithm based on multiple feature images and image fusion was studied in this paper. Firstly, two novel feature images, the  a*-component image and the I-component image, were extracted from the L*a*b* color space and luminance, in-phase, quadrature-phase (YIQ) color space, respectively. Secondly, wavelet transformation was adopted to fuse the two feature images at the pixel level, which combined the feature information of the two source images. Thirdly, in order to segment the target tomato from the background, an adaptive threshold algorithm was used to get the optimal threshold. The final segmentation result was processed by morphology operation to reduce a small amount of noise. In the detection tests, 93% target tomatoes were recognized out of 200 overall samples. It indicates that the proposed tomato recognition method is available for robotic tomato harvesting in the uncontrolled environment with low cost. PMID:26840313

Mass loss from pre-main-sequence accretion disks. I - The accelerating wind of FU Orionis

NASA Technical Reports Server (NTRS)

Calvet, Nuria; Hartmann, Lee; Kenyon, Scott J.

1993-01-01

We present evidence that the wind of the pre-main-sequence object FU Orionis arises from the surface of the luminous accretion disk. A disk wind model calculated assuming radiative equilibrium explains the differential behavior of the observed asymmetric absorption-line profiles. The model predicts that strong lines should be asymmetric and blueshifted, while weak lines should be symmetric and double-peaked due to disk rotation, in agreement with observations. We propose that many blueshifted 'shell' absorption features are not produced in a true shell of material, but rather form in a differentially expanding wind that is rapidly rotating. The inference of rapid rotation supports the proposal that pre-main-sequence disk winds are rotationally driven.

Comparison between flood prone areas' geomorphic features in the Abruzzo region

NASA Astrophysics Data System (ADS)

Orlando, D.; Giglioni, M.; Magnaldi, S.

2017-07-01

Flood risk maps are one of the main non-structural measures for risk mitigation, but, as the risk knowledge degree is directly proportional to the community interest and financial capability, many sites are devoid of flood inundation areas studies. Recently many authors have investigated the capability of flood prone areas individuation with geomorphological DIGITAL ELEVATION MODEL(DEM) based approaches. These approaches highlight the role of geomorphic features derived from DEM, in this case slope, curvature, elevation, and topographic wetness index, to preliminary inundated areas' identification, without using hydraulic simulations. The present studies aim to analyze the geomorphic features of different hazard levels that lie under the identified inundated areas that have been carried out by the Abruzzo Region Basin Authority. The Aterno-Pescara and Foro river basins have been investigated. The results show that the characteristics of the flooded areas can be clearly distinguished from those of the entire basin,however, the difficultly of geomorphic features in individuatingthe areas of different hazard classifications is obvious.

Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning.

PubMed

Qiao, Hong; Li, Yinlin; Li, Fengfu; Xi, Xuanyang; Wu, Wei

2016-10-01

Recently, many biologically inspired visual computational models have been proposed. The design of these models follows the related biological mechanisms and structures, and these models provide new solutions for visual recognition tasks. In this paper, based on the recent biological evidence, we propose a framework to mimic the active and dynamic learning and recognition process of the primate visual cortex. From principle point of view, the main contributions are that the framework can achieve unsupervised learning of episodic features (including key components and their spatial relations) and semantic features (semantic descriptions of the key components), which support higher level cognition of an object. From performance point of view, the advantages of the framework are as follows: 1) learning episodic features without supervision-for a class of objects without a prior knowledge, the key components, their spatial relations and cover regions can be learned automatically through a deep neural network (DNN); 2) learning semantic features based on episodic features-within the cover regions of the key components, the semantic geometrical values of these components can be computed based on contour detection; 3) forming the general knowledge of a class of objects-the general knowledge of a class of objects can be formed, mainly including the key components, their spatial relations and average semantic values, which is a concise description of the class; and 4) achieving higher level cognition and dynamic updating-for a test image, the model can achieve classification and subclass semantic descriptions. And the test samples with high confidence are selected to dynamically update the whole model. Experiments are conducted on face images, and a good performance is achieved in each layer of the DNN and the semantic description learning process. Furthermore, the model can be generalized to recognition tasks of other objects with learning ability.

Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

NASA Astrophysics Data System (ADS)

Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

2018-04-01

In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

EEG Sleep Stages Classification Based on Time Domain Features and Structural Graph Similarity.

PubMed

Diykh, Mohammed; Li, Yan; Wen, Peng

2016-11-01

The electroencephalogram (EEG) signals are commonly used in diagnosing and treating sleep disorders. Many existing methods for sleep stages classification mainly depend on the analysis of EEG signals in time or frequency domain to obtain a high classification accuracy. In this paper, the statistical features in time domain, the structural graph similarity and the K-means (SGSKM) are combined to identify six sleep stages using single channel EEG signals. Firstly, each EEG segment is partitioned into sub-segments. The size of a sub-segment is determined empirically. Secondly, statistical features are extracted, sorted into different sets of features and forwarded to the SGSKM to classify EEG sleep stages. We have also investigated the relationships between sleep stages and the time domain features of the EEG data used in this paper. The experimental results show that the proposed method yields better classification results than other four existing methods and the support vector machine (SVM) classifier. A 95.93% average classification accuracy is achieved by using the proposed method.

Deep feature learning for knee cartilage segmentation using a triplanar convolutional neural network.

PubMed

Prasoon, Adhish; Petersen, Kersten; Igel, Christian; Lauze, François; Dam, Erik; Nielsen, Mads

2013-01-01

Segmentation of anatomical structures in medical images is often based on a voxel/pixel classification approach. Deep learning systems, such as convolutional neural networks (CNNs), can infer a hierarchical representation of images that fosters categorization. We propose a novel system for voxel classification integrating three 2D CNNs, which have a one-to-one association with the xy, yz and zx planes of 3D image, respectively. We applied our method to the segmentation of tibial cartilage in low field knee MRI scans and tested it on 114 unseen scans. Although our method uses only 2D features at a single scale, it performs better than a state-of-the-art method using 3D multi-scale features. In the latter approach, the features and the classifier have been carefully adapted to the problem at hand. That we were able to get better results by a deep learning architecture that autonomously learns the features from the images is the main insight of this study.

Feature Extraction for Track Section Status Classification Based on UGW Signals

PubMed Central

Yang, Yuan; Shi, Lin

2018-01-01

Track status classification is essential for the stability and safety of railway operations nowadays, when railway networks are becoming more and more complex and broad. In this situation, monitoring systems are already a key element in applications dedicated to evaluating the status of a certain track section, often determining whether it is free or occupied by a train. Different technologies have already been involved in the design of monitoring systems, including ultrasonic guided waves (UGW). This work proposes the use of the UGW signals captured by a track monitoring system to extract the features that are relevant for determining the corresponding track section status. For that purpose, three features of UGW signals have been considered: the root mean square value, the energy, and the main frequency components. Experimental results successfully validated how these features can be used to classify the track section status into free, occupied and broken. Furthermore, spatial and temporal dependencies among these features were analysed in order to show how they can improve the final classification performance. Finally, a preliminary high-level classification system based on deep learning networks has been envisaged for future works. PMID:29673156

Analysis of geometric moments as features for firearm identification.

PubMed

Md Ghani, Nor Azura; Liong, Choong-Yeun; Jemain, Abdul Aziz

2010-05-20

The task of identifying firearms from forensic ballistics specimens is exacting in crime investigation since the last two decades. Every firearm, regardless of its size, make and model, has its own unique 'fingerprint'. These fingerprints transfer when a firearm is fired to the fired bullet and cartridge case. The components that are involved in producing these unique characteristics are the firing chamber, breech face, firing pin, ejector, extractor and the rifling of the barrel. These unique characteristics are the critical features in identifying firearms. It allows investigators to decide on which particular firearm that has fired the bullet. Traditionally the comparison of ballistic evidence has been a tedious and time-consuming process requiring highly skilled examiners. Therefore, the main objective of this study is the extraction and identification of suitable features from firing pin impression of cartridge case images for firearm recognition. Some previous studies have shown that firing pin impression of cartridge case is one of the most important characteristics used for identifying an individual firearm. In this study, data are gathered using 747 cartridge case images captured from five different pistols of type 9mm Parabellum Vektor SP1, made in South Africa. All the images of the cartridge cases are then segmented into three regions, forming three different set of images, i.e. firing pin impression image, centre of firing pin impression image and ring of firing pin impression image. Then geometric moments up to the sixth order were generated from each part of the images to form a set of numerical features. These 48 features were found to be significantly different using the MANOVA test. This high dimension of features is then reduced into only 11 significant features using correlation analysis. Classification results using cross-validation under discriminant analysis show that 96.7% of the images were classified correctly. These results demonstrate

Maine's forests 2008

Treesearch

George L. McCaskill; William H. McWilliams; Charles J. Barnett; Brett J. Butler; Mark A. Hatfield; Cassandra M. Kurtz; Randall S. Morin; W. Keith Moser; Charles H. Perry; Christopher W. Woodall

2011-01-01

The second annual inventory of Maine's forests was completed in 2008 after more than 3,160 forested plots were measured. Forest land occupies almost 17.7 million acres, which represents 82 percent of the total land area of Maine. The dominant forest-type groups are maple/beech/yellow birch, spruce/fir, white/red/jack pine, and aspen/white birch. Statewide volume...

Features: Real-Time Adaptive Feature and Document Learning for Web Search.

ERIC Educational Resources Information Center

Chen, Zhixiang; Meng, Xiannong; Fowler, Richard H.; Zhu, Binhai

2001-01-01

Describes Features, an intelligent Web search engine that is able to perform real-time adaptive feature (i.e., keyword) and document learning. Explains how Features learns from users' document relevance feedback and automatically extracts and suggests indexing keywords relevant to a search query, and learns from users' keyword relevance feedback…

[Type 1 Diabetes Mellitus: brief review of the main associated psychological factors].

PubMed

Gómez-Rico, I; Pérez-Marín, M; Montoya-Castilla, I

2015-01-01

Type 1 Diabetes Mellitus (T1DM) is a widespread chronic disease among children and adolescents. Diagnosis and evolution usually involves a significant burden on the patient, and their families must change various aspects of their lifestyle to fulfill the demands of treatment. This study aims to identify the main psychological, family, and adjustment to illness features of children and adolescents diagnosed with DM1 and, in particular to highlight the associated psychopathological factors. The methodology involved a systematic literature search in the main scientific databases. Due to the biopsychosocial impact of DM1 usually assumed in the life of the child and family, and how it may compromise the quality of life and emotional well-being of both, different studies have agreed on the importance of identifying the set of psychological factors involved in healthy adjustment to illness in the child and adolescent with DM1. Copyright © 2013 Asociación Española de Pediatría. Published by Elsevier Espana. All rights reserved.

Atorvastatin effect evaluation based on feature combination of three-dimension ultrasound images

NASA Astrophysics Data System (ADS)

Luo, Yongkang; Ding, Mingyue

2016-03-01

In the past decades, stroke has become the worldwide common cause of death and disability. It is well known that ischemic stroke is mainly caused by carotid atherosclerosis. As an inexpensive, convenient and fast means of detection, ultrasound technology is applied widely in the prevention and treatment of carotid atherosclerosis. Recently, many studies have focused on how to quantitatively evaluate local arterial effects of medicine treatment for carotid diseases. So the evaluation method based on feature combination was proposed to detect potential changes in the carotid arteries after atorvastatin treatment. And the support vector machine (SVM) and 10-fold cross-validation protocol were utilized on a database of 5533 carotid ultrasound images of 38 patients (17 atorvastatin groups and 21 placebo groups) at baseline and after 3 months of the treatment. With combination optimization of many features (including morphological and texture features), the evaluation results of single feature and different combined features were compared. The experimental results showed that the performance of single feature is poor and the best feature combination have good recognition ability, with the accuracy 92.81%, sensitivity 80.95%, specificity 95.52%, positive predictive value 80.47%, negative predictive value 95.65%, Matthew's correlation coefficient 76.27%, and Youden's index 76.48%. And the receiver operating characteristic (ROC) curve was also performed well with 0.9663 of the area under the ROC curve (AUC), which is better than all the features with 0.9423 of the AUC. Thus, it is proved that this novel method can reliably and accurately evaluate the effect of atorvastatin treatment.

Reefing Line Tension in CPAS Main Parachute Clusters

NASA Technical Reports Server (NTRS)

Ray, Eric S.

2013-01-01

Reefing lines are an essential feature to manage inflation loads. During each Engineering Development Unit (EDU) test of the Capsule Parachute Assembly System (CPAS), a chase aircraft is staged to be level with the cluster of Main ringsail parachutes during the initial inflation and reefed stages. This allows for capturing high-quality still photographs of the reefed skirt, suspension line, and canopy geometry. The over-inflation angles are synchronized with measured loads data in order to compute the tension force in the reefing line. The traditional reefing tension equation assumes radial symmetry, but cluster effects cause the reefed skirt of each parachute to elongate to a more elliptical shape. This effect was considered in evaluating multiple parachutes to estimate the semi-major and semi-minor axes. Three flight tests are assessed, including one with a skipped first stage, which had peak reefing line tension over three times higher than the nominal parachute disreef sequence.

When do letter features migrate? A boundary condition for feature-integration theory.

PubMed

Butler, B E; Mewhort, D J; Browse, R A

1991-01-01

Feature-integration theory postulates that a lapse of attention will allow letter features to change position and to recombine as illusory conjunctions (Treisman & Paterson, 1984). To study such errors, we used a set of uppercase letters known to yield illusory conjunctions in each of three tasks. The first, a bar-probe task, showed whole-character mislocations but not errors based on feature migration and recombination. The second, a two-alternative forced-choice detection task, allowed subjects to focus on the presence or absence of subletter features and showed illusory conjunctions based on feature migration and recombination. The third was also a two-alternative forced-choice detection task, but we manipulated the subjects' knowledge of the shape of the stimuli: In the case-certain condition, the stimuli were always in uppercase, but in the case-uncertain condition, the stimuli could appear in either upper- or lowercase. Subjects in the case-certain condition produced illusory conjunctions based on feature recombination, whereas subjects in the case-uncertain condition did not. The results suggest that when subjects can view the stimuli as feature groups, letter features regroup as illusory conjunctions; when subjects encode the stimuli as letters, whole items may be mislocated, but subletter features are not. Thus, illusory conjunctions reflect the subject's processing strategy, rather than the architecture of the visual system.

The West African Squall Line Observed on 23 June 1981 during COPT 81: Mesoscale Structure and Transports.

NASA Astrophysics Data System (ADS)

Chalon, J. P.; Jaubert, G.; Lafore, J. P.; Roux, F.

1988-10-01

Durirg the night of 23/24 June 1981, new Korhogo, Ivory Coast, a squall line passed over the instrumented area of the COPT 81 experiment. Observations were obtained with a dual-Doppler radar system, a sounding station and 22 automatic meteorological surface stations. Data from these instruments and from satellite pictures were analyzed to depict the kinematic and thermodynamic structure of the squall line. Composite analysis techniques were used to obtain a vertical cross section of the reflectivity structure and of the wind field relative to the line. The redistributions of air, moisture and thermodynamic energy by the convection wet calculated through averaged two-dimensional wind fields from a dual-Doppler radar system. The method also allowed the evaluation of the exchanges that were occurring between the convective and the stratiform regions.This squall line had many similarities with tropical squall lines previously described by others. The leading convective part, composed of intense updrafts and downdrafts, and the trailing part, containing weak mesoscale updraft and downdraft, were separated by a reflectivity trough. A notable feature of this line was the presence of a leading anvil induced by intense easterly environmental winds in the upper troposphere. Observations of the evolution of the system at different scales indicated that the mesoalpha-scale (following the classification of Orlanski) and the mosobeta-scale patterns combined to allow the system to have optimum conditions for maximum strength and a maximum lifetime.A rear-to-front flow was found at midlevels in the stratiform region. The flow sloped downward to the surface and took on the characteristics of a density current in the forward half of the squall lice. Entering the convective region, this flow was supplied with cold air by the convective downdrafts and played an important role in forcing upward the less dense monsoon flow entering at the leading edge.Calculations of mass, moisture and

An Eddy-Diffusivity Mass-flux (EDMF) closure for the unified representation of cloud and convective processes

NASA Astrophysics Data System (ADS)

Tan, Z.; Schneider, T.; Teixeira, J.; Lam, R.; Pressel, K. G.

2014-12-01

Sub-grid scale (SGS) closures in current climate models are usually decomposed into several largely independent parameterization schemes for different cloud and convective processes, such as boundary layer turbulence, shallow convection, and deep convection. These separate parameterizations usually do not converge as the resolution is increased or as physical limits are taken. This makes it difficult to represent the interactions and smooth transition among different cloud and convective regimes. Here we present an eddy-diffusivity mass-flux (EDMF) closure that represents all sub-grid scale turbulent, convective, and cloud processes in a unified parameterization scheme. The buoyant updrafts and precipitative downdrafts are parameterized with a prognostic multiple-plume mass-flux (MF) scheme. The prognostic term for the mass flux is kept so that the life cycles of convective plumes are better represented. The interaction between updrafts and downdrafts are parameterized with the buoyancy-sorting model. The turbulent mixing outside plumes is represented by eddy diffusion, in which eddy diffusivity (ED) is determined from a turbulent kinetic energy (TKE) calculated from a TKE balance that couples the environment with updrafts and downdrafts. Similarly, tracer variances are decomposed consistently between updrafts, downdrafts and the environment. The closure is internally coupled with a probabilistic cloud scheme and a simple precipitation scheme. We have also developed a relatively simple two-stream radiative scheme that includes the longwave (LW) and shortwave (SW) effects of clouds, and the LW effect of water vapor. We have tested this closure in a single-column model for various regimes spanning stratocumulus, shallow cumulus, and deep convection. The model is also run towards statistical equilibrium with climatologically relevant large-scale forcings. These model tests are validated against large-eddy simulation (LES) with the same forcings. The comparison of

Functional feature embedded space mapping of fMRI data.

PubMed

Hu, Jin; Tian, Jie; Yang, Lei

2006-01-01

We have proposed a new method for fMRI data analysis which is called Functional Feature Embedded Space Mapping (FFESM). Our work mainly focuses on the experimental design with periodic stimuli which can be described by a number of Fourier coefficients in the frequency domain. A nonlinear dimension reduction technique Isomap is applied to the high dimensional features obtained from frequency domain of the fMRI data for the first time. Finally, the presence of activated time series is identified by the clustering method in which the information theoretic criterion of minimum description length (MDL) is used to estimate the number of clusters. The feasibility of our algorithm is demonstrated by real human experiments. Although we focus on analyzing periodic fMRI data, the approach can be extended to analyze non-periodic fMRI data (event-related fMRI) by replacing the Fourier analysis with a wavelet analysis.

Maine Forests 2013

Treesearch

George L. McCaskill; Thomas Albright; Charles J. Barnett; Brett J. Butler; Susan J. Crocker; Cassandra M. Kurtz; William H. McWilliams; Patrick D. Miles; Randall S. Morin; Mark D. Nelson; Richard H. Widmann; Christopher W. Woodall

2016-01-01

The third 5-year annualized inventory of Maine's forests was completed in 2013 after more than 3170 forested plots were measured. Maine contains more than 17.6 million acres of forest land, an area that has been quite stable since 1960, covering more than 82 percent of the total land area. The number of live trees greater than 1 inch in diameter are approaching 24...

Predicting age groups of Twitter users based on language and metadata features.

PubMed

Morgan-Lopez, Antonio A; Kim, Annice E; Chew, Robert F; Ruddle, Paul

2017-01-01

Health organizations are increasingly using social media, such as Twitter, to disseminate health messages to target audiences. Determining the extent to which the target audience (e.g., age groups) was reached is critical to evaluating the impact of social media education campaigns. The main objective of this study was to examine the separate and joint predictive validity of linguistic and metadata features in predicting the age of Twitter users. We created a labeled dataset of Twitter users across different age groups (youth, young adults, adults) by collecting publicly available birthday announcement tweets using the Twitter Search application programming interface. We manually reviewed results and, for each age-labeled handle, collected the 200 most recent publicly available tweets and user handles' metadata. The labeled data were split into training and test datasets. We created separate models to examine the predictive validity of language features only, metadata features only, language and metadata features, and words/phrases from another age-validated dataset. We estimated accuracy, precision, recall, and F1 metrics for each model. An L1-regularized logistic regression model was conducted for each age group, and predicted probabilities between the training and test sets were compared for each age group. Cohen's d effect sizes were calculated to examine the relative importance of significant features. Models containing both Tweet language features and metadata features performed the best (74% precision, 74% recall, 74% F1) while the model containing only Twitter metadata features were least accurate (58% precision, 60% recall, and 57% F1 score). Top predictive features included use of terms such as "school" for youth and "college" for young adults. Overall, it was more challenging to predict older adults accurately. These results suggest that examining linguistic and Twitter metadata features to predict youth and young adult Twitter users may be helpful for

Innovations in individual feature history management - The significance of feature-based temporal model

USGS Publications Warehouse

Choi, J.; Seong, J.C.; Kim, B.; Usery, E.L.

2008-01-01

A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.

Structural features based genome-wide characterization and prediction of nucleosome organization

PubMed Central

2012-01-01

Background Nucleosome distribution along chromatin dictates genomic DNA accessibility and thus profoundly influences gene expression. However, the underlying mechanism of nucleosome formation remains elusive. Here, taking a structural perspective, we systematically explored nucleosome formation potential of genomic sequences and the effect on chromatin organization and gene expression in S. cerevisiae. Results We analyzed twelve structural features related to flexibility, curvature and energy of DNA sequences. The results showed that some structural features such as DNA denaturation, DNA-bending stiffness, Stacking energy, Z-DNA, Propeller twist and free energy, were highly correlated with in vitro and in vivo nucleosome occupancy. Specifically, they can be classified into two classes, one positively and the other negatively correlated with nucleosome occupancy. These two kinds of structural features facilitated nucleosome binding in centromere regions and repressed nucleosome formation in the promoter regions of protein-coding genes to mediate transcriptional regulation. Based on these analyses, we integrated all twelve structural features in a model to predict more accurately nucleosome occupancy in vivo than the existing methods that mainly depend on sequence compositional features. Furthermore, we developed a novel approach, named DLaNe, that located nucleosomes by detecting peaks of structural profiles, and built a meta predictor to integrate information from different structural features. As a comparison, we also constructed a hidden Markov model (HMM) to locate nucleosomes based on the profiles of these structural features. The result showed that the meta DLaNe and HMM-based method performed better than the existing methods, demonstrating the power of these structural features in predicting nucleosome positions. Conclusions Our analysis revealed that DNA structures significantly contribute to nucleosome organization and influence chromatin structure and gene

Model-based assist feature insertion for sub-40nm memory device

NASA Astrophysics Data System (ADS)

Suh, Sungsoo; Lee, Suk-joo; Choi, Seong-woon; Lee, Sung-Woo; Park, Chan-hoon

2009-04-01

Many issues need to be resolved for a production-worthy model based assist feature insertion flow for single and double exposure patterning process to extend low k1 process at 193 nm immersion technology. Model based assist feature insertion is not trivial to implement either for single and double exposure patterning compared to rule based methods. As shown in Fig. 1, pixel based mask inversion technology in itself has difficulties in mask writing and inspection although it presents as one of key technology to extend single exposure for contact layer. Thus far, inversion technology is tried as a cooptimization of target mask to simultaneously generate optimized main and sub-resolution assists features for a desired process window. Alternatively, its technology can also be used to optimize for a target feature after an assist feature types are inserted in order to simplify the mask complexity. Simplification of inversion mask is one of major issue with applying inversion technology to device development even if a smaller mask feature can be fabricated since the mask writing time is also a major factor. As shown in Figure 2, mask writing time may be a limiting factor in determining whether or not an inversion solution is viable. It can be reasoned that increased number of shot counts relates to increase in margin for inversion methodology. On the other hand, there is a limit on how complex a mask can be in order to be production worthy. There is also source and mask co-optimization which influences the final mask patterns and assist feature sizes and positions for a given target. In this study, we will discuss assist feature insertion methods for sub 40-nm technology.

Modernizing Main Street

ERIC Educational Resources Information Center

Oguntoyinbo, Lekan

2010-01-01

This article features Entrepreneurship Pioneers Initiative (EPI), a nine-month-long educational program targeted to first-generation, small business owners offered through the Rutgers University Center for Urban Entrepreneurship and Economic Development. In its second year, EPI has worked with more than 40 businesses out of an applicant pool of…

Working Memory Units Are All in Your Head: Factors That Influence Whether Features or Objects Are the Favored Units

ERIC Educational Resources Information Center

Vergauwe, Evie; Cowan, Nelson

2015-01-01

We compared two contrasting hypotheses of how multifeatured objects are stored in visual working memory (vWM); as integrated objects or as independent features. A new procedure was devised to examine vWM representations of several concurrently held objects and their features and our main measure was reaction time (RT), allowing an examination of…

A proposed framework on hybrid feature selection techniques for handling high dimensional educational data

NASA Astrophysics Data System (ADS)

Shahiri, Amirah Mohamed; Husain, Wahidah; Rashid, Nur'Aini Abd

2017-10-01

Huge amounts of data in educational datasets may cause the problem in producing quality data. Recently, data mining approach are increasingly used by educational data mining researchers for analyzing the data patterns. However, many research studies have concentrated on selecting suitable learning algorithms instead of performing feature selection process. As a result, these data has problem with computational complexity and spend longer computational time for classification. The main objective of this research is to provide an overview of feature selection techniques that have been used to analyze the most significant features. Then, this research will propose a framework to improve the quality of students' dataset. The proposed framework uses filter and wrapper based technique to support prediction process in future study.

Fast multi-scale feature fusion for ECG heartbeat classification

NASA Astrophysics Data System (ADS)

Ai, Danni; Yang, Jian; Wang, Zeyu; Fan, Jingfan; Ai, Changbin; Wang, Yongtian

2015-12-01

Electrocardiogram (ECG) is conducted to monitor the electrical activity of the heart by presenting small amplitude and duration signals; as a result, hidden information present in ECG data is difficult to determine. However, this concealed information can be used to detect abnormalities. In our study, a fast feature-fusion method of ECG heartbeat classification based on multi-linear subspace learning is proposed. The method consists of four stages. First, baseline and high frequencies are removed to segment heartbeat. Second, as an extension of wavelets, wavelet-packet decomposition is conducted to extract features. With wavelet-packet decomposition, good time and frequency resolutions can be provided simultaneously. Third, decomposed confidences are arranged as a two-way tensor, in which feature fusion is directly implemented with generalized N dimensional ICA (GND-ICA). In this method, co-relationship among different data information is considered, and disadvantages of dimensionality are prevented; this method can also be used to reduce computing compared with linear subspace-learning methods (PCA). Finally, support vector machine (SVM) is considered as a classifier in heartbeat classification. In this study, ECG records are obtained from the MIT-BIT arrhythmia database. Four main heartbeat classes are used to examine the proposed algorithm. Based on the results of five measurements, sensitivity, positive predictivity, accuracy, average accuracy, and t-test, our conclusion is that a GND-ICA-based strategy can be used to provide enhanced ECG heartbeat classification. Furthermore, large redundant features are eliminated, and classification time is reduced.

An inadvertent capture cell for orbital debris and micrometeorites - The main electronics box thermal blanket of the solar maximum satellite

NASA Technical Reports Server (NTRS)

Rietmeijer, F. J. M.; Schramm, L. S.; Barrett, R. A.; Mckay, D. S.; Zook, H. A.

1986-01-01

The physical properties of impact features in the Solar Max main electronics box thermal blanket are consistent with hypervelocity impacts of particles in the near-earth space environment. The majority of particles are orbital debris and include spacecraft paints and bismuth-rich particles. At least 30 percent of all impact features are caused by micrometeorites, which include silicates and sulfides. Some micrometeorites survive impact with only minor shock-metamorphic effects or chemical fractionation. Currently calibration experiments are under way to relate flux to particle diameter (or mass).

Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study.

PubMed

Najdi, Shirin; Gharbali, Ali Abdollahi; Fonseca, José Manuel

2017-08-18

Nowadays, sleep quality is one of the most important measures of healthy life, especially considering the huge number of sleep-related disorders. Identifying sleep stages using polysomnographic (PSG) signals is the traditional way of assessing sleep quality. However, the manual process of sleep stage classification is time-consuming, subjective and costly. Therefore, in order to improve the accuracy and efficiency of the sleep stage classification, researchers have been trying to develop automatic classification algorithms. Automatic sleep stage classification mainly consists of three steps: pre-processing, feature extraction and classification. Since classification accuracy is deeply affected by the extracted features, a poor feature vector will adversely affect the classifier and eventually lead to low classification accuracy. Therefore, special attention should be given to the feature extraction and selection process. In this paper the performance of seven feature selection methods, as well as two feature rank aggregation methods, were compared. Pz-Oz EEG, horizontal EOG and submental chin EMG recordings of 22 healthy males and females were used. A comprehensive feature set including 49 features was extracted from these recordings. The extracted features are among the most common and effective features used in sleep stage classification from temporal, spectral, entropy-based and nonlinear categories. The feature selection methods were evaluated and compared using three criteria: classification accuracy, stability, and similarity. Simulation results show that MRMR-MID achieves the highest classification performance while Fisher method provides the most stable ranking. In our simulations, the performance of the aggregation methods was in the average level, although they are known to generate more stable results and better accuracy. The Borda and RRA rank aggregation methods could not outperform significantly the conventional feature ranking methods. Among

Confidence-Based Feature Acquisition

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; desJardins, Marie; MacGlashan, James

2010-01-01

Confidence-based Feature Acquisition (CFA) is a novel, supervised learning method for acquiring missing feature values when there is missing data at both training (learning) and test (deployment) time. To train a machine learning classifier, data is encoded with a series of input features describing each item. In some applications, the training data may have missing values for some of the features, which can be acquired at a given cost. A relevant JPL example is that of the Mars rover exploration in which the features are obtained from a variety of different instruments, with different power consumption and integration time costs. The challenge is to decide which features will lead to increased classification performance and are therefore worth acquiring (paying the cost). To solve this problem, CFA, which is made up of two algorithms (CFA-train and CFA-predict), has been designed to greedily minimize total acquisition cost (during training and testing) while aiming for a specific accuracy level (specified as a confidence threshold). With this method, it is assumed that there is a nonempty subset of features that are free; that is, every instance in the data set includes these features initially for zero cost. It is also assumed that the feature acquisition (FA) cost associated with each feature is known in advance, and that the FA cost for a given feature is the same for all instances. Finally, CFA requires that the base-level classifiers produce not only a classification, but also a confidence (or posterior probability).

FEATURE C, TYPE 1 PILLBOX, WEST SIDE, FEATURE D IN ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

FEATURE C, TYPE 1 PILLBOX, WEST SIDE, FEATURE D IN BACKGROUND, VIEW FACING EAST. - Naval Air Station Barbers Point, Shore Pillbox Complex-Type 1 Pillbox, Along shoreline, seaward of Coral Sea Road, Ewa, Honolulu County, HI

The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

PubMed

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep

Space Transportation Main Engine

NASA Technical Reports Server (NTRS)

Monk, Jan C.

1992-01-01

The topics are presented in viewgraph form and include the following: Space Transportation Main Engine (STME) definition, design philosophy, robust design, maximum design condition, casting vs. machined and welded forgings, operability considerations, high reliability design philosophy, engine reliability enhancement, low cost design philosophy, engine systems requirements, STME schematic, fuel turbopump, liquid oxygen turbopump, main injector, and gas generator. The major engine components of the STME and the Space Shuttle Main Engine are compared.

Designing using manufacturing features

NASA Astrophysics Data System (ADS)

Szecsi, T.; Hoque, A. S. M.

2012-04-01

This paper presents a design system that enables the composition of a part using manufacturing features. Features are selected from feature libraries. Upon insertion, the system ensures that the feature does not contradict the design-for-manufacture rules. This helps eliminating costly manufacturing problems. The system is developed as an extension to a commercial CAD/CAM system Pro/Engineer.

A DETAILED FAR-ULTRAVIOLET SPECTRAL ATLAS OF MAIN-SEQUENCE B STARS

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

Smith, Myron A.

2010-02-01

We have constructed a detailed spectral atlas covering the wavelength region 930-1225 A for 10 sharp-lined B0-B9 stars near the main sequence. Most of the spectra we assembled are from the archives of the Far Ultraviolet Spectroscopic Explorer satellite, but for nine stars, wavelength coverage above 1188 A was taken from high-resolution International Ultraviolet Explorer or echelle Hubble Space Telescope/Space Telescope Imaging Spectrograph spectra. To represent the tenth star at type B0.2 V, we used the Copernicus atlas of {tau} Sco. We made extensive line identifications in the region 949-1225 A of all atomic features having published oscillator strengths atmore » types B0, B2, and B8. These are provided as a supplementary data product-hence the term detailed atlas. Our list of found features totals 2288, 1612, and 2469 lines, respectively. We were able to identify 92%, 98%, and 98% of these features with known atomic transitions with varying degrees of certainty in these spectra. The remaining lines do not have published oscillator strengths. Photospheric lines account for 94%, 87%, and 91%, respectively, of all our identifications, with the remainder being due to interstellar (usually molecular H{sub 2}) lines. We also discuss the numbers of lines with respect to the distributions of various ions for these three most studied spectral subtypes. A table is also given of 162 least blended lines that can be used as possible diagnostics of physical conditions in B star atmospheres.« less

The forests of Maine: 2003

Treesearch

William H. McWilliams; Brett J. Butler; Laurence E. Caldwell; Douglas M. Griffith; Michael L. Hoppus; Kenneth M. Laustsen; Andrew J. Lister; Tonya W. Lister; Jacob W. Metzler; Randall S. Morin; Steven A. Sader; Lucretia B. Stewart; James R. Steinman; James, A. Westfall; David A. Williams; Andrew Whitman; Christopher W. Woodall; Christopher W. Woodall

2005-01-01

In 1999, the Maine Forest Service and USDA Forest Service's Forest Inventory and Analysis program implemented a new system for inventorying and monitoring Maine's forests. The effects of the spruce budworm epidemic continue to affect the composition, structure, and distribution of Maine's forested ecosystems. The area of forest land in Maine has remained...

Jupiter's Main Ring

NASA Technical Reports Server (NTRS)

1997-01-01

A mosaic of four images taken through the clear filter (610 nanometers) of the solid state imaging (CCD) system aboard NASA's Galileo spacecraft on November 8, 1996, at a resolution of approximately 46 kilometers (km) per picture element (pixel) along the rings; however, because the spacecraft was only about 0.5 degrees above the ring plane, the image is highly foreshortened in the vertical direction. The images were obtained when Galileo was in Jupiter's shadow peering back toward the Sun; the ring was approximately 2,300,000 kilometers (km) away. The arc on the far right of the image is produced by sunlight scattered by small particles comprising Jupiter's upper atmospheric haze. The ring also efficiently scatters light, indicating that much of its brightness is due to particles that are microns or less in diameter. Such small particles are believed to have human-scale lifetimes, i.e., very brief compared to the solar system's age.

Jupiter's ring system is composed of three parts -- a flat main ring, a lenticular halo interior to the main ring, and the gossamer ring, which lies exterior to the main ring. The near and far arms of Jupiter's main ring extend horizontally across the mosaic, joining together at the ring's ansa, on the far left side of the figure. The near arm of the ring appears to be abruptly truncated close to the planet, at the point where it passes into Jupiter's shadow. Some radial structure is barely visible across the ring's ansa. A faint mist of particles can be seen above and below the main rings; this vertically extended 'halo' is unusual in planetary rings, and is probably caused by electromagnetic forces pushing the smallest grains out of the ring plane. Because of shadowing, the halo is not visible close to Jupiter in the lower right part of the mosaic.

Jupiter's main ring is a thin strand of material encircling the planet. The diffuse innermost boundary begins at approximately 123,000 km. The main ring's outer radius is found to be

Well-characterized sequence features of eukaryote genomes and implications for ab initio gene prediction.

PubMed

Huang, Ying; Chen, Shi-Yi; Deng, Feilong

2016-01-01

In silico analysis of DNA sequences is an important area of computational biology in the post-genomic era. Over the past two decades, computational approaches for ab initio prediction of gene structure from genome sequence alone have largely facilitated our understanding on a variety of biological questions. Although the computational prediction of protein-coding genes has already been well-established, we are also facing challenges to robustly find the non-coding RNA genes, such as miRNA and lncRNA. Two main aspects of ab initio gene prediction include the computed values for describing sequence features and used algorithm for training the discriminant function, and by which different combinations are employed into various bioinformatic tools. Herein, we briefly review these well-characterized sequence features in eukaryote genomes and applications to ab initio gene prediction. The main purpose of this article is to provide an overview to beginners who aim to develop the related bioinformatic tools.

A Comparison of the Near-Infrared Spectral Features of Early-Type Galaxies in the Virgo and Coma Clusters

NASA Astrophysics Data System (ADS)

Houdashelt, M. L.

1992-05-01

Initial results are presented from an examination of near-infrared spectra (6800 - 9200 Angstroms) of 34 early-type galaxies - 17 in the Virgo cluster, 10 in the Coma cluster and seven field members. It has previously been speculated that E/S0 galaxies of similar luminosity in the Virgo and Coma clusters have different red stellar populations. To explore this possibility, pseudo-equivalent widths of a number of near-IR spectral features have been measured. The important features studied include the TiO bands near 7100, 7890, 8197, 8500 and 8950 Angstroms, which are mainly produced by the late-type stars whose flux contributes only about 10-20\\ the near-IR. The strengths of the Ca triplet (8498, 8542, 8662 Angstroms) and Na I doublet (8183, 8195 Angstroms) are also measured, since these features are affected by the relative contribution of dwarf stars to the red light. Although the main focus of this work is the search for spectral differences among the Coma, Virgo and field E/S0 populations, each subgroup of galaxies (and the sample as a whole) are also examined for correlations among the feature strengths, galaxy color and luminosity.

FEATURE 3, LARGE GUN POSITION, ARMCO HUT (FEATURE 4) IN ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

FEATURE 3, LARGE GUN POSITION, ARMCO HUT (FEATURE 4) IN BACKGROUND, VIEW FACING NORTH. - Naval Air Station Barbers Point, Anti-Aircraft Battery Complex-Large Gun Position, East of Coral Sea Road, northwest of Hamilton Road, Ewa, Honolulu County, HI

Physical properties of Moving Magnetic Features observed around a pore

NASA Astrophysics Data System (ADS)

Criscuoli, S.; Del Moro, D.; Giannattasio, F.; Viticchié, B.; Giorgi, F.; Ermolli, I.; Zuccarello, F.; Berrilli, F.

2012-06-01

Movies of magnetograms of sunspots often show small-size magnetic patches that move radially away and seem to be expelled from the field of the spot. These patches are named Moving Magnetic Features (MMFs). They have been mostly observed around spots and have been interpreted as manifestations of penumbral filaments. Nevertheless, few observations of MMFS streaming out from spots without penumbra have been reported. He we investigate the physical properties of MMFs observed around the field of a pore derived by the analyses of high spectral, spatial and temporal resolution data acquired at the Dunn Solar Telescope with IBIS. We find that the main properties of the investigated features agree with those reported for MMFs observed around regular spots. These results indicate that an improvement of current numerical simulations is required to understand the generation of MMFs in the lack of penumbrae.

The structure of Jupiter’s main ring from New Horizons: A comparison with other ring-moon systems

NASA Astrophysics Data System (ADS)

Chancia, Robert; Hedman, Matthew

2018-04-01

During New Horizon’s Jupiter flyby in 2007, the Long-Range Reconnaissance Imager (LORRI) took several images of the planet’s main ring. The data set contains two extended image-movies of the main ring, along with several brief observations at varying ring azimuths, and a small set of high phase angle images. Thus far, the only published work on the New Horizons Jupiter rings data set found seven bright clumps with sub-km equivalent radii embedded in the main ring (Showalter et al. 2007 Science). In this work, we searched the inner region of the main ring for any structures that might be perturbed at the 3:2 resonances with the rotation of Jupiter’s magnetic field or massive storms. We also examined the structure of the outer main ring in order to assess how it is shaped by the small moons Metis and Adrastea. Some of the features seen in Jupiter’s main ring are similar to those found in other dusty rings around Saturn, Uranus, and Neptune. By comparing these different rings, we can gain a better understanding of how small moons sculpt tenuous rings.

Tidal Disruptions of Main-sequence Stars of Varying Mass and Age: Inferences from the Composition of the Fallback Material

NASA Astrophysics Data System (ADS)

Gallegos-Garcia, Monica; Law-Smith, Jamie; Ramirez-Ruiz, Enrico

2018-04-01

We use a simple framework to calculate the time evolution of the composition of the fallback material onto a supermassive black hole arising from the tidal disruption of main-sequence stars. We study stars with masses between 0.8 and 3.0 M ⊙, at evolutionary stages from zero-age main sequence to terminal-age main sequence, built using the Modules for Experiments in Stellar Astrophysics code. We show that most stars develop enhancements in nitrogen (14N) and depletions in carbon (12C) and oxygen (16O) over their lifetimes, and that these features are more pronounced for higher mass stars. We find that, in an accretion-powered tidal disruption flare, these features become prominent only after the time of peak of the fallback rate and appear at earlier times for stars of increasing mass. We postulate that no severe compositional changes resulting from the fallback material should be expected near peak for a wide range of stellar masses and, as such, are unable to explain the extreme helium-to-hydrogen line ratios observed in some TDEs. On the other hand, the resulting compositional changes could help explain the presence of nitrogen-rich features, which are currently only detected after peak. When combined with the shape of the light curve, the time evolution of the composition of the fallback material provides a clear method to help constrain the nature of the disrupted star. This will enable a better characterization of the event by helping break the degeneracy between the mass of the star and the mass of the black hole when fitting tidal disruption light curves.

Schizophrenia with prominent catatonic features: A selective review.

PubMed

Ungvari, Gabor S; Gerevich, Jozsef; Takács, Rozália; Gazdag, Gábor

2017-08-14

A widely accepted consensus holds that a variety of motor symptoms subsumed under the term 'catatonia' have been an integral part of the symptomatology of schizophrenia since 1896, when Kraepelin proposed the concept of dementia praecox (schizophrenia). Until recently, psychiatric classifications included catatonic schizophrenia mainly through tradition, without compelling evidence of its validity as a schizophrenia subtype. This selective review briefly summarizes the history, psychopathology, demographic and epidemiological data, and treatment options for schizophrenia with prominent catatonic features. Although most catatonic signs and symptoms are easy to observe and measure, the lack of conceptual clarity of catatonia and consensus about the threshold and criteria for its diagnosis have hampered our understanding of how catatonia contributes to the pathophysiology of schizophrenic psychoses. Diverse study samples and methodologies have further hindered research on schizophrenia with prominent catatonic features. A focus on the motor aspects of broadly defined schizophrenia using modern methods of detecting and quantifying catatonic signs and symptoms coupled with sophisticated neuroimaging techniques offers a new approach to research in this long-overlooked field. Copyright © 2017. Published by Elsevier B.V.

Infrared vehicle recognition using unsupervised feature learning based on K-feature

NASA Astrophysics Data System (ADS)

Lin, Jin; Tan, Yihua; Xia, Haijiao; Tian, Jinwen

2018-02-01

Subject to the complex battlefield environment, it is difficult to establish a complete knowledge base in practical application of vehicle recognition algorithms. The infrared vehicle recognition is always difficult and challenging, which plays an important role in remote sensing. In this paper we propose a new unsupervised feature learning method based on K-feature to recognize vehicle in infrared images. First, we use the target detection algorithm which is based on the saliency to detect the initial image. Then, the unsupervised feature learning based on K-feature, which is generated by Kmeans clustering algorithm that extracted features by learning a visual dictionary from a large number of samples without label, is calculated to suppress the false alarm and improve the accuracy. Finally, the vehicle target recognition image is finished by some post-processing. Large numbers of experiments demonstrate that the proposed method has satisfy recognition effectiveness and robustness for vehicle recognition in infrared images under complex backgrounds, and it also improve the reliability of it.

Plant species classification using flower images—A comparative study of local feature representations

PubMed Central

Seeland, Marco; Rzanny, Michael; Alaqraa, Nedal; Wäldchen, Jana; Mäder, Patrick

2017-01-01

Steady improvements of image description methods induced a growing interest in image-based plant species classification, a task vital to the study of biodiversity and ecological sensitivity. Various techniques have been proposed for general object classification over the past years and several of them have already been studied for plant species classification. However, results of these studies are selective in the evaluated steps of a classification pipeline, in the utilized datasets for evaluation, and in the compared baseline methods. No study is available that evaluates the main competing methods for building an image representation on the same datasets allowing for generalized findings regarding flower-based plant species classification. The aim of this paper is to comparatively evaluate methods, method combinations, and their parameters towards classification accuracy. The investigated methods span from detection, extraction, fusion, pooling, to encoding of local features for quantifying shape and color information of flower images. We selected the flower image datasets Oxford Flower 17 and Oxford Flower 102 as well as our own Jena Flower 30 dataset for our experiments. Findings show large differences among the various studied techniques and that their wisely chosen orchestration allows for high accuracies in species classification. We further found that true local feature detectors in combination with advanced encoding methods yield higher classification results at lower computational costs compared to commonly used dense sampling and spatial pooling methods. Color was found to be an indispensable feature for high classification results, especially while preserving spatial correspondence to gray-level features. In result, our study provides a comprehensive overview of competing techniques and the implications of their main parameters for flower-based plant species classification. PMID:28234999

Ocean observing systems support operational forecasts for the timing of Maine's lobster fishery

NASA Astrophysics Data System (ADS)

Mills, K.; Hernandez, C.; Pershing, A. J.

2016-02-01

American lobster supports one of the most valuable fisheries in the United States, with a landed value in 2013 exceeding $460M. Although US lobstermen are free to fish throughout the year, the New England climate, lobster biology and fleet dynamics lead to a strong annual cycle with catch rates rising rapidly in early summer and landings peaking in late summer. When this annual cycle is disrupted, it can impact the supply and ultimately the price of lobsters. During the record warm conditions in 2012, the rise in catch rates occurred three weeks ahead of normal. Combined with higher than normal landings from the spring Canadian fishery, the early and high volume landings in 2012 led to a collapse in price that severely stressed the U. S. fishery, especially in Maine where over 85% of the landings occur. Based on this experience, we have been developing seasonal forecasts of the phenology of Maine lobster landings. Using temperatures at 50m from four NERACOOS buoys in the Gulf of Maine, we can reliably forecast the date when the Maine lobster fishery will `turn on' for the year, with prediction accuracy peaking in April. The high-landings period normally starts in July, and the 2-3 month lead-time provides some advance warning to dealers and processors of when their capacity needs to be ready and to fishermen of potential supply chain and market impacts such as we observed in 2012. We are currently working towards finer-scale regional forecasts along the Maine coast that may include other features that will provide information to help the lobster industry adapt to the rapid changes that are underway in the Gulf of Maine.

Spectral EEG Features of a Short Psycho-physiological Relaxation

NASA Astrophysics Data System (ADS)

Teplan, Michal; Krakovská, Anna; Špajdel, Marián

2014-08-01

Short-lasting psycho-physiological relaxation was investigated through an analysis of its bipolar electroencephalographic (EEG) characteristics. In 8 subjects, 6-channel EEG data of 3-minute duration were recorded during 88 relaxation sessions. Time course of spectral EEG features was examined. Alpha powers were decreasing during resting conditions of 3-minute sessions in lying position with eyes closed. This was followed by a decrease of total power in centro-parietal cortex regions and an increase of beta power in fronto-central areas. Represented by EEG coherences the interhemispheric communication between the parieto-occipital regions was enhanced within a frequency range of 2-10 Hz. In order to discern between higher and lower levels of relaxation distinguished according to self-rated satisfaction, EEG features were assessed and discriminating parameters were identified. Successful relaxation was determined mainly by the presence of decreased delta-1 power across the cortex. Potential applications for these findings include the clinical, pharmacological, and stress management fields.

Iterative feature refinement for accurate undersampled MR image reconstruction

NASA Astrophysics Data System (ADS)

Wang, Shanshan; Liu, Jianbo; Liu, Qiegen; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong

2016-05-01

Accelerating MR scan is of great significance for clinical, research and advanced applications, and one main effort to achieve this is the utilization of compressed sensing (CS) theory. Nevertheless, the existing CSMRI approaches still have limitations such as fine structure loss or high computational complexity. This paper proposes a novel iterative feature refinement (IFR) module for accurate MR image reconstruction from undersampled K-space data. Integrating IFR with CSMRI which is equipped with fixed transforms, we develop an IFR-CS method to restore meaningful structures and details that are originally discarded without introducing too much additional complexity. Specifically, the proposed IFR-CS is realized with three iterative steps, namely sparsity-promoting denoising, feature refinement and Tikhonov regularization. Experimental results on both simulated and in vivo MR datasets have shown that the proposed module has a strong capability to capture image details, and that IFR-CS is comparable and even superior to other state-of-the-art reconstruction approaches.

33 CFR 334.30 - Gulf of Maine off Pemaquid Point, Maine; naval sonobuoy test area.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., Maine; naval sonobuoy test area. 334.30 Section 334.30 Navigation and Navigable Waters CORPS OF....30 Gulf of Maine off Pemaquid Point, Maine; naval sonobuoy test area. (a) The area. The test area or... enforced by the Commanding Officer, U.S. Naval Air Station, Brunswick, Maine, or such agencies as he may...

33 CFR 334.30 - Gulf of Maine off Pemaquid Point, Maine; naval sonobuoy test area.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., Maine; naval sonobuoy test area. 334.30 Section 334.30 Navigation and Navigable Waters CORPS OF....30 Gulf of Maine off Pemaquid Point, Maine; naval sonobuoy test area. (a) The area. The test area or... enforced by the Commanding Officer, U.S. Naval Air Station, Brunswick, Maine, or such agencies as he may...

33 CFR 334.30 - Gulf of Maine off Pemaquid Point, Maine; naval sonobuoy test area.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., Maine; naval sonobuoy test area. 334.30 Section 334.30 Navigation and Navigable Waters CORPS OF....30 Gulf of Maine off Pemaquid Point, Maine; naval sonobuoy test area. (a) The area. The test area or... enforced by the Commanding Officer, U.S. Naval Air Station, Brunswick, Maine, or such agencies as he may...

33 CFR 334.30 - Gulf of Maine off Pemaquid Point, Maine; naval sonobuoy test area.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., Maine; naval sonobuoy test area. 334.30 Section 334.30 Navigation and Navigable Waters CORPS OF....30 Gulf of Maine off Pemaquid Point, Maine; naval sonobuoy test area. (a) The area. The test area or... enforced by the Commanding Officer, U.S. Naval Air Station, Brunswick, Maine, or such agencies as he may...

33 CFR 334.30 - Gulf of Maine off Pemaquid Point, Maine; naval sonobuoy test area.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., Maine; naval sonobuoy test area. 334.30 Section 334.30 Navigation and Navigable Waters CORPS OF....30 Gulf of Maine off Pemaquid Point, Maine; naval sonobuoy test area. (a) The area. The test area or... enforced by the Commanding Officer, U.S. Naval Air Station, Brunswick, Maine, or such agencies as he may...

Automated EEG artifact elimination by applying machine learning algorithms to ICA-based features

NASA Astrophysics Data System (ADS)

Radüntz, Thea; Scouten, Jon; Hochmuth, Olaf; Meffert, Beate

2017-08-01

Objective. Biological and non-biological artifacts cause severe problems when dealing with electroencephalogram (EEG) recordings. Independent component analysis (ICA) is a widely used method for eliminating various artifacts from recordings. However, evaluating and classifying the calculated independent components (IC) as artifact or EEG is not fully automated at present. Approach. In this study, we propose a new approach for automated artifact elimination, which applies machine learning algorithms to ICA-based features. Main results. We compared the performance of our classifiers with the visual classification results given by experts. The best result with an accuracy rate of 95% was achieved using features obtained by range filtering of the topoplots and IC power spectra combined with an artificial neural network. Significance. Compared with the existing automated solutions, our proposed method is not limited to specific types of artifacts, electrode configurations, or number of EEG channels. The main advantages of the proposed method is that it provides an automatic, reliable, real-time capable, and practical tool, which avoids the need for the time-consuming manual selection of ICs during artifact removal.

High-order graph matching based feature selection for Alzheimer's disease identification.

PubMed

Liu, Feng; Suk, Heung-Il; Wee, Chong-Yaw; Chen, Huafu; Shen, Dinggang

2013-01-01

One of the main limitations of l1-norm feature selection is that it focuses on estimating the target vector for each sample individually without considering relations with other samples. However, it's believed that the geometrical relation among target vectors in the training set may provide useful information, and it would be natural to expect that the predicted vectors have similar geometric relations as the target vectors. To overcome these limitations, we formulate this as a graph-matching feature selection problem between a predicted graph and a target graph. In the predicted graph a node is represented by predicted vector that may describe regional gray matter volume or cortical thickness features, and in the target graph a node is represented by target vector that include class label and clinical scores. In particular, we devise new regularization terms in sparse representation to impose high-order graph matching between the target vectors and the predicted ones. Finally, the selected regional gray matter volume and cortical thickness features are fused in kernel space for classification. Using the ADNI dataset, we evaluate the effectiveness of the proposed method and obtain the accuracies of 92.17% and 81.57% in AD and MCI classification, respectively.

Fuzzy Relational Compression Applied on Feature Vectors for Infant Cry Recognition

NASA Astrophysics Data System (ADS)

Reyes-Galaviz, Orion Fausto; Reyes-García, Carlos Alberto

Data compression is always advisable when it comes to handling and processing information quickly and efficiently. There are two main problems that need to be solved when it comes to handling data; store information in smaller spaces and processes it in the shortest possible time. When it comes to infant cry analysis (ICA), there is always the need to construct large sound repositories from crying babies. Samples that have to be analyzed and be used to train and test pattern recognition algorithms; making this a time consuming task when working with uncompressed feature vectors. In this work, we show a simple, but efficient, method that uses Fuzzy Relational Product (FRP) to compresses the information inside a feature vector, building with this a compressed matrix that will help us recognize two kinds of pathologies in infants; Asphyxia and Deafness. We describe the sound analysis, which consists on the extraction of Mel Frequency Cepstral Coefficients that generate vectors which will later be compressed by using FRP. There is also a description of the infant cry database used in this work, along with the training and testing of a Time Delay Neural Network with the compressed features, which shows a performance of 96.44% with our proposed feature vector compression.

Duct flow nonuniformities study for space shuttle main engine

NASA Technical Reports Server (NTRS)

Thoenes, J.

1985-01-01

To improve the Space Shuttle Main Engine (SSME) design and for future use in the development of generation rocket engines, a combined experimental/analytical study was undertaken with the goals of first, establishing an experimental data base for the flow conditions in the SSME high pressure fuel turbopump (HPFTP) hot gas manifold (HGM) and, second, setting up a computer model of the SSME HGM flow field. Using the test data to verify the computer model it should be possible in the future to computationally scan contemplated advanced design configurations and limit costly testing to the most promising design. The effort of establishing and using the computer model is detailed. The comparison of computational results and experimental data observed clearly demonstrate that computational fluid mechanics (CFD) techniques can be used successfully to predict the gross features of three dimensional fluid flow through configurations as intricate as the SSME turbopump hot gas manifold.

[Lithology feature extraction of CASI hyperspectral data based on fractal signal algorithm].

PubMed

Tang, Chao; Chen, Jian-Ping; Cui, Jing; Wen, Bo-Tao

2014-05-01

Hyperspectral data is characterized by combination of image and spectrum and large data volume dimension reduction is the main research direction. Band selection and feature extraction is the primary method used for this objective. In the present article, the authors tested methods applied for the lithology feature extraction from hyperspectral data. Based on the self-similarity of hyperspectral data, the authors explored the application of fractal algorithm to lithology feature extraction from CASI hyperspectral data. The "carpet method" was corrected and then applied to calculate the fractal value of every pixel in the hyperspectral data. The results show that fractal information highlights the exposed bedrock lithology better than the original hyperspectral data The fractal signal and characterized scale are influenced by the spectral curve shape, the initial scale selection and iteration step. At present, research on the fractal signal of spectral curve is rare, implying the necessity of further quantitative analysis and investigation of its physical implications.

Brachydactyly E: isolated or as a feature of a syndrome.

PubMed

Pereda, Arrate; Garin, Intza; Garcia-Barcina, Maria; Gener, Blanca; Beristain, Elena; Ibañez, Ane Miren; Perez de Nanclares, Guiomar

2013-09-12

Brachydactyly (BD) refers to the shortening of the hands, feet or both. There are different types of BD; among them, type E (BDE) is a rare type that can present as an isolated feature or as part of more complex syndromes, such as: pseudohypopthyroidism (PHP), hypertension with BD or Bilginturan BD (HTNB), BD with mental retardation (BDMR) or BDE with short stature, PTHLH type. Each syndrome has characteristic patterns of skeletal involvement. However, brachydactyly is not a constant feature and shows a high degree of phenotypic variability. In addition, there are other syndromes that can be misdiagnosed as brachydactyly type E, some of which will also be discussed. The objective of this review is to describe some of the syndromes in which BDE is present, focusing on clinical, biochemical and genetic characteristics as features of differential diagnoses, with the aim of establishing an algorithm for their differential diagnosis. As in our experience many of these patients are recruited at Endocrinology and/or Pediatric Endocrinology Services due to their short stature, we have focused the algorithm in those steps that could mainly help these professionals.

Brachydactyly E: isolated or as a feature of a syndrome

PubMed Central

2013-01-01

Brachydactyly (BD) refers to the shortening of the hands, feet or both. There are different types of BD; among them, type E (BDE) is a rare type that can present as an isolated feature or as part of more complex syndromes, such as: pseudohypopthyroidism (PHP), hypertension with BD or Bilginturan BD (HTNB), BD with mental retardation (BDMR) or BDE with short stature, PTHLH type. Each syndrome has characteristic patterns of skeletal involvement. However, brachydactyly is not a constant feature and shows a high degree of phenotypic variability. In addition, there are other syndromes that can be misdiagnosed as brachydactyly type E, some of which will also be discussed. The objective of this review is to describe some of the syndromes in which BDE is present, focusing on clinical, biochemical and genetic characteristics as features of differential diagnoses, with the aim of establishing an algorithm for their differential diagnosis. As in our experience many of these patients are recruited at Endocrinology and/or Pediatric Endocrinology Services due to their short stature, we have focused the algorithm in those steps that could mainly help these professionals. PMID:24028571

Feature extraction through parallel Probabilistic Principal Component Analysis for heart disease diagnosis

NASA Astrophysics Data System (ADS)

Shah, Syed Muhammad Saqlain; Batool, Safeera; Khan, Imran; Ashraf, Muhammad Usman; Abbas, Syed Hussnain; Hussain, Syed Adnan

2017-09-01

Automatic diagnosis of human diseases are mostly achieved through decision support systems. The performance of these systems is mainly dependent on the selection of the most relevant features. This becomes harder when the dataset contains missing values for the different features. Probabilistic Principal Component Analysis (PPCA) has reputation to deal with the problem of missing values of attributes. This research presents a methodology which uses the results of medical tests as input, extracts a reduced dimensional feature subset and provides diagnosis of heart disease. The proposed methodology extracts high impact features in new projection by using Probabilistic Principal Component Analysis (PPCA). PPCA extracts projection vectors which contribute in highest covariance and these projection vectors are used to reduce feature dimension. The selection of projection vectors is done through Parallel Analysis (PA). The feature subset with the reduced dimension is provided to radial basis function (RBF) kernel based Support Vector Machines (SVM). The RBF based SVM serves the purpose of classification into two categories i.e., Heart Patient (HP) and Normal Subject (NS). The proposed methodology is evaluated through accuracy, specificity and sensitivity over the three datasets of UCI i.e., Cleveland, Switzerland and Hungarian. The statistical results achieved through the proposed technique are presented in comparison to the existing research showing its impact. The proposed technique achieved an accuracy of 82.18%, 85.82% and 91.30% for Cleveland, Hungarian and Switzerland dataset respectively.

Distributed cable sensors with memory feature for post-disaster damage assessment

NASA Astrophysics Data System (ADS)

Chen, Genda; McDaniel, Ryan D.; Pommerenke, David J.; Sun, Shishuang

2005-05-01

A new design of distributed crack sensors is presented for the condition assessment of reinforced concrete (RC) structures during and immediately after an earthquake event. This study is mainly focused on the performance of cable sensors under dynamic loading, particularly their ability to memorize the crack history of an RC member. This unique memory feature enables the post-earthquake condition assessment of structural members such as RC columns, in which the earthquake-induced cracks are closed immediately after an earthquake event due to gravity loads and they are visually undetectable. Factors affecting the onset of the memory feature were investigated experimentally with small-scale RC beams under cyclic loading. Test results indicated that both crack width and the number of loading cycles were instrumental in the onset of the memory feature of cable sensors. Practical issues related to dynamic acquisition with the sensors were discussed. The sensors were proven to be fatigue resistant from the shake table tests of RC columns. They continued to show useful signal after the columns can no longer support additional loads.

General view of the Space Shuttle Main Engine (SSME) assembly ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view of the Space Shuttle Main Engine (SSME) assembly with the expansion nozzle removed and resting on a cushioned mat on the floor of the SSME Processing Facility. The most prominent features in this view are the Low-pressure Fuel Turbopump discharge Duct looping from the upper left side of the engine assembly to the lower left side of the assembly, the Low-Pressure Oxidizer Turbopump (LPOTP) is on the upper left of the assembly in this view and the LPOTP Discharge Duct loops from the upper left to upper right. The sphere in the middle right side of the assembly in this view is the POGO System Accumulator , the partial sphere to its left and slightly more toward the center of the assembly is the Heat Exchanger on the Oxidizer Preburner side of the Hot Gas Manifold, beneath that is the High-Pressure Oxidizer Turbopump (HPOTP) and the HPOTP Discharge duct loops from the pump around to the lower left of the assembly. The Pneumatic Control Assembly is in the approximate center of the engine assembly in this view. - Space Transportation System, Space Shuttle Main Engine, Lyndon B. Johnson Space Center, 2101 NASA Parkway, Houston, Harris County, TX

Identification of chemogenomic features from drug–target interaction networks using interpretable classifiers

PubMed Central

Tabei, Yasuo; Pauwels, Edouard; Stoven, Véronique; Takemoto, Kazuhiro; Yamanishi, Yoshihiro

2012-01-01

Motivation: Drug effects are mainly caused by the interactions between drug molecules and their target proteins including primary targets and off-targets. Identification of the molecular mechanisms behind overall drug–target interactions is crucial in the drug design process. Results: We develop a classifier-based approach to identify chemogenomic features (the underlying associations between drug chemical substructures and protein domains) that are involved in drug–target interaction networks. We propose a novel algorithm for extracting informative chemogenomic features by using L1 regularized classifiers over the tensor product space of possible drug–target pairs. It is shown that the proposed method can extract a very limited number of chemogenomic features without loosing the performance of predicting drug–target interactions and the extracted features are biologically meaningful. The extracted substructure–domain association network enables us to suggest ligand chemical fragments specific for each protein domain and ligand core substructures important for a wide range of protein families. Availability: Softwares are available at the supplemental website. Contact: yamanishi@bioreg.kyushu-u.ac.jp Supplementary Information: Datasets and all results are available at http://cbio.ensmp.fr/~yyamanishi/l1binary/ . PMID:22962471

Alternative large-scale conservation visions for northern Maine: interviews with decision leaders in Maine

Treesearch

Elizabeth Dennis Baldwin; Laura S. Kenefic; Will F. LaPage

2007-01-01

Based on confidential interviews with 21 decision leaders in Maine, Elizabeth Baldwin, Laura Kenefic, and Will LaPage examine the complexity of the conflicts over alternate visions for large-scale conservation in Maine. Exploring models that may be useful for policymakers grappling with competing values for Maine's forests, they present four alternatives: national...

Geology and impact features of Vargeão Dome, southern Brazil

NASA Astrophysics Data System (ADS)

Crósta, Alvaro P.; Kazzuo-Vieira, César; Pitarello, Lidia; Koeberl, Christian; Kenkmann, Thomas

2012-01-01

Vargeão Dome (southern Brazil) is a circular feature formed in lava flows of the Lower Cretaceous Serra Geral Formation and in sandstones of the Paraná Basin. Even though its impact origin was already proposed in the 1980s, little information about its geological and impact features is available in the literature. The structure has a rim-rim diameter of approximately 12 km and comprises several ring-like concentric features with multiple concentric lineaments. The presence of a central uplift is suggested by the occurrence of deformed sandstone strata of the Botucatu and Pirambóia formations. We present the morphological/structural characteristics of Vargeão Dome, characterize the different rock types that occur in its interior, mainly brecciated volcanic rocks (BVR) of the Serra Geral Formation, and discuss the deformation and shock features in the volcanic rocks and in sandstones. These features comprise shatter cones in sandstone and basalt, as well as planar microstructures in quartz. A geochemical comparison of the target rock equivalents from outside the structure with the shocked rocks from its interior shows that both the BVRs and the brecciated sandstone have a composition largely similar to that of the corresponding unshocked lithologies. No traces of meteoritic material have been found so far. The results confirm the impact origin of Vargeão Dome, making it one of the largest among the rare impact craters in basaltic targets known on Earth.

Coding of visual object features and feature conjunctions in the human brain.

PubMed

Martinovic, Jasna; Gruber, Thomas; Müller, Matthias M

2008-01-01

Object recognition is achieved through neural mechanisms reliant on the activity of distributed coordinated neural assemblies. In the initial steps of this process, an object's features are thought to be coded very rapidly in distinct neural assemblies. These features play different functional roles in the recognition process--while colour facilitates recognition, additional contours and edges delay it. Here, we selectively varied the amount and role of object features in an entry-level categorization paradigm and related them to the electrical activity of the human brain. We found that early synchronizations (approx. 100 ms) increased quantitatively when more image features had to be coded, without reflecting their qualitative contribution to the recognition process. Later activity (approx. 200-400 ms) was modulated by the representational role of object features. These findings demonstrate that although early synchronizations may be sufficient for relatively crude discrimination of objects in visual scenes, they cannot support entry-level categorization. This was subserved by later processes of object model selection, which utilized the representational value of object features such as colour or edges to select the appropriate model and achieve identification.

Determination of functions of controlling drives of main executive mechanisms of mining excavators

NASA Astrophysics Data System (ADS)

Lagunova, Yu A.; Komissarov, A. P.; Lukashuk, O. A.

2018-03-01

It is shown that a special shovel is a feature of the structure of the drives of the main mechanisms (mechanisms of lifting and pressure) of career excavators with working equipment, the presence in the transfer device of a two-crank-lever mechanism of working equipment that connects the main mechanisms with the working body (bucket). In this case, the transformation of the mechanical energy parameters of the motors into energy-force parameters realized at the cutting edge of the bucket (teeth) takes place depending on the type of the kinematic scheme of the two-link-lever mechanism. The concept of “control function” defining the relationship between the parameters characterizing the position of the bucket in the face (the coordinates of the tip of the cutting edge of the bucket, the digging speed) and the required control level are introduced. These are the values of the lifting and head speeds ensuring the bucket movement along a given trajectory.

Frequency of MELAS main mutation in a phenotype-targeted young ischemic stroke patient population.

PubMed

Tatlisumak, Turgut; Putaala, Jukka; Innilä, Markus; Enzinger, Christian; Metso, Tiina M; Curtze, Sami; von Sarnowski, Bettina; Amaral-Silva, Alexandre; Jungehulsing, Gerhard Jan; Tanislav, Christian; Thijs, Vincent; Rolfs, Arndt; Norrving, Bo; Fazekas, Franz; Suomalainen, Anu; Kolodny, Edwin H

2016-02-01

Mitochondrial diseases, predominantly mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS), may occasionally underlie or coincide with ischemic stroke (IS) in young and middle-aged individuals. We searched for undiagnosed patients with MELAS in a target subpopulation of unselected young IS patients enrolled in the Stroke in Young Fabry Patients study (sifap1). Among the 3291 IS patients aged 18-55 years recruited to the sifap1 study at 47 centers across 14 European countries, we identified potential MELAS patients with the following phenotypic features: (a) diagnosed cardiomyopathy or (b) presence of two of the three following findings: migraine, short stature (≤165 cm for males; ≤155 cm for females), and diabetes. Identified patients' blood samples underwent analysis of the common MELAS mutation, m.3243A>G in the MTTL1 gene of mitochondrial DNA. Clinical and cerebral MRI features of the mutation carriers were reviewed. We analyzed blood samples of 238 patients (177 with cardiomyopathy) leading to identification of four previously unrecognized MELAS main mutation carrier-patients. Their clinical and MRI characteristics were within the expectation for common IS patients except for severe hearing loss in one patient and hyperintensity of the pulvinar thalami on T1-weighted MRI in another one. Genetic testing for the m.3243A>G MELAS mutation in young patients with IS based on phenotypes suggestive of mitochondrial disease identifies previously unrecognized carriers of MELAS main mutation, but does not prove MELAS as the putative cause.

Large-Eddy Simulation of Shallow Cumulus over Land: A Composite Case Based on ARM Long-Term Observations at Its Southern Great Plains Site

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

Zhang, Yunyan; Klein, Stephen A.; Fan, Jiwen

Based on long-term observations by the Atmospheric Radiation Measurement program at its Southern Great Plains site, a new composite case of continental shallow cumulus (ShCu) convection is constructed for large-eddy simulations (LES) and single-column models. The case represents a typical daytime nonprecipitating ShCu whose formation and dissipation are driven by the local atmospheric conditions and land surface forcing and are not influenced by synoptic weather events. The case includes early morning initial profiles of temperature and moisture with a residual layer; diurnally varying sensible and latent heat fluxes, which represent a domain average over different land surface types; simplified large-scalemore » horizontal advective tendencies and subsidence; and horizontal winds with prevailing direction and average speed. Observed composite cloud statistics are provided for model evaluation. The observed diurnal cycle is well reproduced by LES; however, the cloud amount, liquid water path, and shortwave radiative effect are generally underestimated. LES are compared between simulations with an all-or-nothing bulk microphysics and a spectral bin microphysics. The latter shows improved agreement with observations in the total cloud cover and the amount of clouds with depths greater than 300 m. When compared with radar retrievals of in-cloud air motion, LES produce comparable downdraft vertical velocities, but a larger updraft area, velocity, and updraft mass flux. Both observations and LES show a significantly larger in-cloud downdraft fraction and downdraft mass flux than marine ShCu.« less

Large-Eddy Simulation of Shallow Cumulus over Land: A Composite Case Based on ARM Long-Term Observations at Its Southern Great Plains Site

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

Zhang, Yunyan; Klein, Stephen A.; Fan, Jiwen

Based on long-term observations by the Atmospheric Radiation Measurement program at its Southern Great Plains site, a new composite case of continental shallow cumulus (ShCu) convection is constructed for large-eddy simulations (LES) and single-column models. The case represents a typical daytime non-precipitating ShCu whose formation and dissipation are driven by the local atmospheric conditions and land-surface forcing, and are not influenced by synoptic weather events. The case includes: early-morning initial profiles of temperature and moisture with a residual layer; diurnally-varying sensible and latent heat fluxes which represent a domain average over different land-surface types; simplified large-scale horizontal advective tendencies andmore » subsidence; and horizontal winds with prevailing direction and average speed. Observed composite cloud statistics are provided for model evaluation. The observed diurnal cycle is well-reproduced by LES, however the cloud amount, liquid water path, and shortwave radiative effect are generally underestimated. LES are compared between simulations with an all-or-nothing bulk microphysics and a spectral bin microphysics. The latter shows improved agreement with observations in the total cloud cover and the amount of clouds with depths greater than 300 meters. When compared with radar retrievals of in-cloud air motion, LES produce comparable downdraft vertical velocities, but a larger updraft area, velocity and updraft mass flux. Finally, both observation and LES show a significantly larger in-cloud downdraft fraction and downdraft mass flux than marine ShCu.« less

Large-Eddy Simulation of Shallow Cumulus over Land: A Composite Case Based on ARM Long-Term Observations at Its Southern Great Plains Site

DOE PAGES

Zhang, Yunyan; Klein, Stephen A.; Fan, Jiwen; ...

2017-09-19

Based on long-term observations by the Atmospheric Radiation Measurement program at its Southern Great Plains site, a new composite case of continental shallow cumulus (ShCu) convection is constructed for large-eddy simulations (LES) and single-column models. The case represents a typical daytime non-precipitating ShCu whose formation and dissipation are driven by the local atmospheric conditions and land-surface forcing, and are not influenced by synoptic weather events. The case includes: early-morning initial profiles of temperature and moisture with a residual layer; diurnally-varying sensible and latent heat fluxes which represent a domain average over different land-surface types; simplified large-scale horizontal advective tendencies andmore » subsidence; and horizontal winds with prevailing direction and average speed. Observed composite cloud statistics are provided for model evaluation. The observed diurnal cycle is well-reproduced by LES, however the cloud amount, liquid water path, and shortwave radiative effect are generally underestimated. LES are compared between simulations with an all-or-nothing bulk microphysics and a spectral bin microphysics. The latter shows improved agreement with observations in the total cloud cover and the amount of clouds with depths greater than 300 meters. When compared with radar retrievals of in-cloud air motion, LES produce comparable downdraft vertical velocities, but a larger updraft area, velocity and updraft mass flux. Finally, both observation and LES show a significantly larger in-cloud downdraft fraction and downdraft mass flux than marine ShCu.« less

Characteristics of vertical air motion in isolated convective clouds

DOE PAGES

Yang, Jing; Wang, Zhien; Heymsfield, Andrew J.; ...

2016-08-11

The vertical velocity and air mass flux in isolated convective clouds are statistically analyzed using aircraft in situ data collected from three field campaigns: High-Plains Cumulus (HiCu) conducted over the midlatitude High Plains, COnvective Precipitation Experiment (COPE) conducted in a midlatitude coastal area, and Ice in Clouds Experiment-Tropical (ICE-T) conducted over a tropical ocean. The results show that small-scale updrafts and downdrafts (<  500 m in diameter) are frequently observed in the three field campaigns, and they make important contributions to the total air mass flux. The probability density functions (PDFs) and profiles of the observed vertical velocity are provided. The PDFsmore » are exponentially distributed. The updrafts generally strengthen with height. Relatively strong updrafts (>  20 m s −1) were sampled in COPE and ICE-T. The observed downdrafts are stronger in HiCu and COPE than in ICE-T. The PDFs of the air mass flux are exponentially distributed as well. The observed maximum air mass flux in updrafts is of the order 10 4 kg m −1 s −1. The observed air mass flux in the downdrafts is typically a few times smaller in magnitude than that in the updrafts. Since this study only deals with isolated convective clouds, and there are many limitations and sampling issues in aircraft in situ measurements, more observations are needed to better explore the vertical air motion in convective clouds.« less

Sensitivity of Tropical Cyclone Spinup Time to the Initial Entropy Deficit

NASA Astrophysics Data System (ADS)

Tang, B.; Corbosiero, K. L.; Rios-Berrios, R.; Alland, J.; Berman, J.

2014-12-01

The development timescale of a tropical cyclone from genesis to the start of rapid intensification in an axisymmetric model is hypothesized to be a function of the initial entropy deficit. We run a set of idealized simulations in which the initial entropy deficit between the boundary layer and free troposphere varies from 0 to 100 J kg-1 K-1. The development timescale is measured by changes in the integrated kinetic energy of the low-level vortex. This timescale is inversely related to the mean mass flux during the tropical cyclone gestation period. The mean mass flux, in turn, is a function of the statistics of convective updrafts and downdrafts. Contour frequency by altitude diagrams show that entrainment of dry air into updrafts is predominately responsible for differences in the mass flux between the experiments, while downdrafts play a secondary role. Analyses of the potential and kinetic energy budgets indicate less efficient conversion of available potential energy to kinetic energy in the experiments with higher entropy deficits. Entrainment leads to the loss of buoyancy and the destruction of available potential energy. In the presence of strong downdrafts, there can even be a reversal of the conversion term. Weaker and more radially confined radial inflow results in less convergence of angular momentum in the experiments with higher entropy deficits. The result is a slower vortex spinup and a reduction in steady-state vortex size, despite similar steady-state maximum intensities among the experiments.

Pathogenic features and characteristics of food borne pathogens biofilm: Biomass, viability and matrix.

PubMed

Lin, Shiqi; Yang, Ling; Chen, Gu; Li, Bing; Chen, Dingqiang; Li, Lin; Xu, Zhenbo

2017-10-01

Biofilm is a ubiquitous growth pattern of bacterial species survival but is notorious for its threat on public health and food contamination. Extensive studies of the biofilm structure, formation, quantification, quorum sensing system and underlying control strategies have been reported during the past decades. Insightful elucidation of the pathogenic features and characteristic of bacterial biofilm can facilitate in devising appropriate control strategies for biofilm eradication. Therefore, this review mainly summarized the pathogenic features of biofilms from food borne microorganisms, including the biomass (which could be quantified using crystal violet and fluorogenic dye Syto9 assays), viability (which could be determined by tetrazolium salts, fluorescein diacetate, resazurin staining and alamar blue assays) and matrix (which are commonly detected by dimethyl methylene blue and wheat germ agglutinin assays). In addition, three features were further compared with its particular benefits in specific application. Copyright © 2017 Elsevier Ltd. All rights reserved.

External facial features modify the representation of internal facial features in the fusiform face area.

PubMed

Axelrod, Vadim; Yovel, Galit

2010-08-15

Most studies of face identity have excluded external facial features by either removing them or covering them with a hat. However, external facial features may modify the representation of internal facial features. Here we assessed whether the representation of face identity in the fusiform face area (FFA), which has been primarily studied for internal facial features, is modified by differences in external facial features. We presented faces in which external and internal facial features were manipulated independently. Our findings show that the FFA was sensitive to differences in external facial features, but this effect was significantly larger when the external and internal features were aligned than misaligned. We conclude that the FFA generates a holistic representation in which the internal and the external facial features are integrated. These results indicate that to better understand real-life face recognition both external and internal features should be included. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Predicting age groups of Twitter users based on language and metadata features

PubMed Central

Morgan-Lopez, Antonio A.; Chew, Robert F.; Ruddle, Paul

2017-01-01

Health organizations are increasingly using social media, such as Twitter, to disseminate health messages to target audiences. Determining the extent to which the target audience (e.g., age groups) was reached is critical to evaluating the impact of social media education campaigns. The main objective of this study was to examine the separate and joint predictive validity of linguistic and metadata features in predicting the age of Twitter users. We created a labeled dataset of Twitter users across different age groups (youth, young adults, adults) by collecting publicly available birthday announcement tweets using the Twitter Search application programming interface. We manually reviewed results and, for each age-labeled handle, collected the 200 most recent publicly available tweets and user handles’ metadata. The labeled data were split into training and test datasets. We created separate models to examine the predictive validity of language features only, metadata features only, language and metadata features, and words/phrases from another age-validated dataset. We estimated accuracy, precision, recall, and F1 metrics for each model. An L1-regularized logistic regression model was conducted for each age group, and predicted probabilities between the training and test sets were compared for each age group. Cohen’s d effect sizes were calculated to examine the relative importance of significant features. Models containing both Tweet language features and metadata features performed the best (74% precision, 74% recall, 74% F1) while the model containing only Twitter metadata features were least accurate (58% precision, 60% recall, and 57% F1 score). Top predictive features included use of terms such as “school” for youth and “college” for young adults. Overall, it was more challenging to predict older adults accurately. These results suggest that examining linguistic and Twitter metadata features to predict youth and young adult Twitter users may be

Features of resilience

DOE PAGES

Connelly, Elizabeth B.; Allen, Craig R.; Hatfield, Kirk; ...

2017-02-20

The National Academy of Sciences (NAS) definition of resilience is used here to organize common concepts and synthesize a set of key features of resilience that can be used across diverse application domains. The features in common include critical functions (services), thresholds, cross-scale (both space and time) interactions, and memory and adaptive management. We propose a framework for linking these features to the planning, absorbing, recovering, and adapting phases identified in the NAS definition. As a result, the proposed delineation of resilience can be important in understanding and communicating resilience concepts.

Features of resilience

USGS Publications Warehouse

Connelly, Elizabeth B.; Allen, Craig R.; Hatfield, Kirk; Palma-Oliveira, José M.; Woods, David D.; Linkov, Igor

2017-01-01

The National Academy of Sciences (NAS) definition of resilience is used here to organize common concepts and synthesize a set of key features of resilience that can be used across diverse application domains. The features in common include critical functions (services), thresholds, cross-scale (both space and time) interactions, and memory and adaptive management. We propose a framework for linking these features to the planning, absorbing, recovering, and adapting phases identified in the NAS definition. The proposed delineation of resilience can be important in understanding and communicating resilience concepts.

Skin lesion computational diagnosis of dermoscopic images: Ensemble models based on input feature manipulation.

PubMed

Oliveira, Roberta B; Pereira, Aledir S; Tavares, João Manuel R S

2017-10-01

The number of deaths worldwide due to melanoma has risen in recent times, in part because melanoma is the most aggressive type of skin cancer. Computational systems have been developed to assist dermatologists in early diagnosis of skin cancer, or even to monitor skin lesions. However, there still remains a challenge to improve classifiers for the diagnosis of such skin lesions. The main objective of this article is to evaluate different ensemble classification models based on input feature manipulation to diagnose skin lesions. Input feature manipulation processes are based on feature subset selections from shape properties, colour variation and texture analysis to generate diversity for the ensemble models. Three subset selection models are presented here: (1) a subset selection model based on specific feature groups, (2) a correlation-based subset selection model, and (3) a subset selection model based on feature selection algorithms. Each ensemble classification model is generated using an optimum-path forest classifier and integrated with a majority voting strategy. The proposed models were applied on a set of 1104 dermoscopic images using a cross-validation procedure. The best results were obtained by the first ensemble classification model that generates a feature subset ensemble based on specific feature groups. The skin lesion diagnosis computational system achieved 94.3% accuracy, 91.8% sensitivity and 96.7% specificity. The input feature manipulation process based on specific feature subsets generated the greatest diversity for the ensemble classification model with very promising results. Copyright © 2017 Elsevier B.V. All rights reserved.

Satellite-observed cloud-top height changes in tornadic thunderstorms

NASA Technical Reports Server (NTRS)

Adler, R. F.; Fenn, D. D.

1981-01-01

Eleven tornadic storms are evaluated with respect to cloud top temperature changes relative to tornado touchdown. Digital IR data from the SMS/GOES geosynchronous satellites were employed for 10 F2 and one F1 tornadoes. A rapid ascent of the cloud tops 30-45 min before tornado touchdown, a temperature decrease of 0.4 K/min, and an ascent rate of about 3 m/sec were observed. The presence of an operating Doppler radar for three of the sample storms allowed detection of a mesocyclone coincident with the rapid cloud top ascent. The intensification and descent of the vortex to form a tornado is concluded to be due to a weakening of the updraft, the formation of a downdraft, and a shift of the vortex to the updraft-downdraft boundary, leading to dominance of the tilting term in the generation of vorticity.

Main Propulsion Test Article (MPTA)

NASA Technical Reports Server (NTRS)

Snoddy, Cynthia

2010-01-01

Scope: The Main Propulsion Test Article integrated the main propulsion subsystem with the clustered Space Shuttle Main Engines, the External Tank and associated GSE. The test program consisted of cryogenic tanking tests and short- and long duration static firings including gimbaling and throttling. The test program was conducted on the S1-C test stand (Position B-2) at the National Space Technology Laboratories (NSTL)/Stennis Space Center. 3 tanking tests and 20 hot fire tests conducted between December 21 1 1977 and December 17, 1980 Configuration: The main propulsion test article consisted of the three space shuttle main engines, flightweight external tank, flightweight aft fuselage, interface section and a boilerplate mid/fwd fuselage truss structure.

Automatic plankton image classification combining multiple view features via multiple kernel learning.

PubMed

Zheng, Haiyong; Wang, Ruchen; Yu, Zhibin; Wang, Nan; Gu, Zhaorui; Zheng, Bing

2017-12-28

Plankton, including phytoplankton and zooplankton, are the main source of food for organisms in the ocean and form the base of marine food chain. As the fundamental components of marine ecosystems, plankton is very sensitive to environment changes, and the study of plankton abundance and distribution is crucial, in order to understand environment changes and protect marine ecosystems. This study was carried out to develop an extensive applicable plankton classification system with high accuracy for the increasing number of various imaging devices. Literature shows that most plankton image classification systems were limited to only one specific imaging device and a relatively narrow taxonomic scope. The real practical system for automatic plankton classification is even non-existent and this study is partly to fill this gap. Inspired by the analysis of literature and development of technology, we focused on the requirements of practical application and proposed an automatic system for plankton image classification combining multiple view features via multiple kernel learning (MKL). For one thing, in order to describe the biomorphic characteristics of plankton more completely and comprehensively, we combined general features with robust features, especially by adding features like Inner-Distance Shape Context for morphological representation. For another, we divided all the features into different types from multiple views and feed them to multiple classifiers instead of only one by combining different kernel matrices computed from different types of features optimally via multiple kernel learning. Moreover, we also applied feature selection method to choose the optimal feature subsets from redundant features for satisfying different datasets from different imaging devices. We implemented our proposed classification system on three different datasets across more than 20 categories from phytoplankton to zooplankton. The experimental results validated that our system

Teaching Main Idea Comprehension.

ERIC Educational Resources Information Center

Baumann, James F., Ed.

Intended to help classroom teachers, curriculum developers, and researchers, this book provides current information on theoretical and instructional aspects of main idea comprehension. Titles and authors are as follows: "The Confused World of Main Idea" (James W. Cunningham and David W. Moore); "The Comprehension of Important…

Extending GIS Technology to Study Karst Features of Southeastern Minnesota

NASA Astrophysics Data System (ADS)

Gao, Y.; Tipping, R. G.; Alexander, E. C.; Alexander, S. C.

2001-12-01

This paper summarizes ongoing research on karst feature distribution of southeastern Minnesota. The main goals of this interdisciplinary research are: 1) to look for large-scale patterns in the rate and distribution of sinkhole development; 2) to conduct statistical tests of hypotheses about the formation of sinkholes; 3) to create management tools for land-use managers and planners; and 4) to deliver geomorphic and hydrogeologic criteria for making scientifically valid land-use policies and ethical decisions in karst areas of southeastern Minnesota. Existing county and sub-county karst feature datasets of southeastern Minnesota have been assembled into a large GIS-based database capable of analyzing the entire data set. The central database management system (DBMS) is a relational GIS-based system interacting with three modules: GIS, statistical and hydrogeologic modules. ArcInfo and ArcView were used to generate a series of 2D and 3D maps depicting karst feature distributions in southeastern Minnesota. IRIS ExplorerTM was used to produce satisfying 3D maps and animations using data exported from GIS-based database. Nearest-neighbor analysis has been used to test sinkhole distributions in different topographic and geologic settings. All current nearest-neighbor analyses testify that sinkholes in southeastern Minnesota are not evenly distributed in this area (i.e., they tend to be clustered). More detailed statistical methods such as cluster analysis, histograms, probability estimation, correlation and regression have been used to study the spatial distributions of some mapped karst features of southeastern Minnesota. A sinkhole probability map for Goodhue County has been constructed based on sinkhole distribution, bedrock geology, depth to bedrock, GIS buffer analysis and nearest-neighbor analysis. A series of karst features for Winona County including sinkholes, springs, seeps, stream sinks and outcrop has been mapped and entered into the Karst Feature Database

Feature-Based Retinal Image Registration Using D-Saddle Feature

PubMed Central

Hasikin, Khairunnisa; A. Karim, Noor Khairiah; Ahmedy, Fatimah

2017-01-01

Retinal image registration is important to assist diagnosis and monitor retinal diseases, such as diabetic retinopathy and glaucoma. However, registering retinal images for various registration applications requires the detection and distribution of feature points on the low-quality region that consists of vessels of varying contrast and sizes. A recent feature detector known as Saddle detects feature points on vessels that are poorly distributed and densely positioned on strong contrast vessels. Therefore, we propose a multiresolution difference of Gaussian pyramid with Saddle detector (D-Saddle) to detect feature points on the low-quality region that consists of vessels with varying contrast and sizes. D-Saddle is tested on Fundus Image Registration (FIRE) Dataset that consists of 134 retinal image pairs. Experimental results show that D-Saddle successfully registered 43% of retinal image pairs with average registration accuracy of 2.329 pixels while a lower success rate is observed in other four state-of-the-art retinal image registration methods GDB-ICP (28%), Harris-PIIFD (4%), H-M (16%), and Saddle (16%). Furthermore, the registration accuracy of D-Saddle has the weakest correlation (Spearman) with the intensity uniformity metric among all methods. Finally, the paired t-test shows that D-Saddle significantly improved the overall registration accuracy of the original Saddle. PMID:29204257

Identification of four class emotion from Indonesian spoken language using acoustic and lexical features

NASA Astrophysics Data System (ADS)

Kasyidi, Fatan; Puji Lestari, Dessi

2018-03-01

One of the important aspects in human to human communication is to understand emotion of each party. Recently, interactions between human and computer continues to develop, especially affective interaction where emotion recognition is one of its important components. This paper presents our extended works on emotion recognition of Indonesian spoken language to identify four main class of emotions: Happy, Sad, Angry, and Contentment using combination of acoustic/prosodic features and lexical features. We construct emotion speech corpus from Indonesia television talk show where the situations are as close as possible to the natural situation. After constructing the emotion speech corpus, the acoustic/prosodic and lexical features are extracted to train the emotion model. We employ some machine learning algorithms such as Support Vector Machine (SVM), Naive Bayes, and Random Forest to get the best model. The experiment result of testing data shows that the best model has an F-measure score of 0.447 by using only the acoustic/prosodic feature and F-measure score of 0.488 by using both acoustic/prosodic and lexical features to recognize four class emotion using the SVM RBF Kernel.

Feature Centrality and Property Induction

ERIC Educational Resources Information Center

Hadjichristidis, Constantinos; Sloman, Steven; Stevenson, Rosemary; Over, David

2004-01-01

A feature is central to a concept to the extent that other features depend on it. Four studies tested the hypothesis that people will project a feature from a base concept to a target concept to the extent that they believe the feature is central to the two concepts. This centrality hypothesis implies that feature projection is guided by a…

Stacked sparse autoencoder in hyperspectral data classification using spectral-spatial, higher order statistics and multifractal spectrum features

NASA Astrophysics Data System (ADS)

Wan, Xiaoqing; Zhao, Chunhui; Wang, Yanchun; Liu, Wu

2017-11-01

This paper proposes a novel classification paradigm for hyperspectral image (HSI) using feature-level fusion and deep learning-based methodologies. Operation is carried out in three main steps. First, during a pre-processing stage, wave atoms are introduced into bilateral filter to smooth HSI, and this strategy can effectively attenuate noise and restore texture information. Meanwhile, high quality spectral-spatial features can be extracted from HSI by taking geometric closeness and photometric similarity among pixels into consideration simultaneously. Second, higher order statistics techniques are firstly introduced into hyperspectral data classification to characterize the phase correlations of spectral curves. Third, multifractal spectrum features are extracted to characterize the singularities and self-similarities of spectra shapes. To this end, a feature-level fusion is applied to the extracted spectral-spatial features along with higher order statistics and multifractal spectrum features. Finally, stacked sparse autoencoder is utilized to learn more abstract and invariant high-level features from the multiple feature sets, and then random forest classifier is employed to perform supervised fine-tuning and classification. Experimental results on two real hyperspectral data sets demonstrate that the proposed method outperforms some traditional alternatives.

Maine's Employability Skills Program

ERIC Educational Resources Information Center

McMahon, John M.; Wolffe, Karen E.; Wolfe, Judy; Brooker, Carrie

2013-01-01

This Practice Report describes the development and implementation of the "Maine Employability Skills Program," a model employment program developed by the Maine Division for the Blind and Visually Impaired (DBVI). The program was designed to support the efforts of the chronically unemployed or underemployed. These consumers were either…

Main features of nucleation in model solutions of oral cavity

NASA Astrophysics Data System (ADS)

Golovanova, O. A.; Chikanova, E. S.; Punin, Yu. O.

2015-05-01

The regularities of nucleation in model solutions of oral cavity have been investigated, and the induction order and constants have been determined for two systems: saliva and dental plaque fluid (DPF). It is shown that an increase in the initial supersaturation leads to a transition from the heterogeneous nucleation of crystallites to a homogeneous one. Some additives are found to enhance nucleation: HCO{3/-} > C6H12O6 > F-, while others hinder this process: protein (casein) > Mg2+. It is established that crystallization in DPF occurs more rapidly and the DPF composition is favorable for the growth of small (52.6-26.1 μm) crystallites. On the contrary, the conditions implemented in the model saliva solution facilitate the formation of larger (198.4-41.8 μm) crystals.

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

NASA Astrophysics Data System (ADS)

Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

2017-11-01

Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

Toward an understanding of phyllosilicate mineralogy in the outer main asteroid belt

NASA Astrophysics Data System (ADS)

Takir, Driss; Emery, Joshua P.; McSween, Harry Y.

2015-09-01

Proposed mineralogical linkages between CM/CI carbonaceous chondrites and outer Main Belt asteroids remain uncertain due to a dearth of diagnostic absorptions in visible and near-infrared (∼0.4-2.5 μm) spectra of the two sets of objects. Absorptions near 3 μm in both sets hold promise for illuminating the potential linkages. Spectral comparisons of meteorites and asteroids have been challenging because meteorite spectra have usually been acquired in ambient terrestrial environments, and hence were contaminated by atmospheric water. In this study, we compare near-infrared spectra of chondrites measured in the laboratory under asteroid-like conditions (Takir, D. et al. [2013]. Meteorit. Planet. Sci. 48, 1618-1637) and spectra of asteroids measured with the long-wavelength cross-dispersed (LXD: 1.9-4.2-μm) mode of the SpeX spectrograph/imager at the NASA Infrared Telescope Facility (IRTF) (Takir, D., Emery, J.P. [2012]. Icarus 219, 641-654). Using the 3-μm band shape, we find that spectral Group 2 CM and CI (Ivuna) chondrites are possible meteorite analogs for asteroids with the sharp 3-μm features, which are predominately located in the 2.5 < a < 3.3 AU region. Spectral Group 2 CM chondrites contain phyllosilicate phases intermediate between endmembers Fe-serpentine and Mg-serpentine, with a petrological subtype ranging from 2.2 to 2.1 (Takir, D. et al. [2013]. Meteorit. Planet. Sci. 48, 1618-1637). No meteorite match was found for asteroids showing a rounded 3-μm feature, which tend to be located farther from the Sun (3.0 < a < 4.0 AU), or for asteroids with distinctive spectra like 1 Ceres or 52 Europa. The study of the 3-μm band in meteorites and asteroids has implications for the understanding of phyllosilicate mineralogy and its distribution in the outer Main Belt region.

Clinical Features and Treatment of Ocular Toxoplasmosis

PubMed Central

Park, Young-Hoon

2013-01-01

Ocular toxoplasmosis is a disease caused by the infection with Toxoplasma gondii through congenital or acquired routes. Once the parasite reaches the retina, it proliferates within host cells followed by rupture of the host cells and invasion into neighboring cells to make primary lesions. Sometimes the restricted parasite by the host immunity in the first scar is activated to infect another lesion nearby the scar. Blurred vision is the main complaint of ocular toxoplasmic patients and can be diagnosed by detection of antibodies or parasite DNA. Ocular toxoplasmosis needs therapy with several combinations of drugs to eliminate the parasite and accompanying inflammation; if not treated it sometimes leads to loss of vision. We describe here clinical features and currently available chemotherapy of ocular toxoplasmosis. PMID:24039281

Clinical features and treatment of ocular toxoplasmosis.

PubMed

Park, Young-Hoon; Nam, Ho-Woo

2013-08-01

Ocular toxoplasmosis is a disease caused by the infection with Toxoplasma gondii through congenital or acquired routes. Once the parasite reaches the retina, it proliferates within host cells followed by rupture of the host cells and invasion into neighboring cells to make primary lesions. Sometimes the restricted parasite by the host immunity in the first scar is activated to infect another lesion nearby the scar. Blurred vision is the main complaint of ocular toxoplasmic patients and can be diagnosed by detection of antibodies or parasite DNA. Ocular toxoplasmosis needs therapy with several combinations of drugs to eliminate the parasite and accompanying inflammation; if not treated it sometimes leads to loss of vision. We describe here clinical features and currently available chemotherapy of ocular toxoplasmosis.

A hybrid feature selection approach for the early diagnosis of Alzheimer’s disease

NASA Astrophysics Data System (ADS)

Gallego-Jutglà, Esteve; Solé-Casals, Jordi; Vialatte, François-Benoît; Elgendi, Mohamed; Cichocki, Andrzej; Dauwels, Justin

2015-02-01

Objective. Recently, significant advances have been made in the early diagnosis of Alzheimer’s disease (AD) from electroencephalography (EEG). However, choosing suitable measures is a challenging task. Among other measures, frequency relative power (RP) and loss of complexity have been used with promising results. In the present study we investigate the early diagnosis of AD using synchrony measures and frequency RP on EEG signals, examining the changes found in different frequency ranges. Approach. We first explore the use of a single feature for computing the classification rate (CR), looking for the best frequency range. Then, we present a multiple feature classification system that outperforms all previous results using a feature selection strategy. These two approaches are tested in two different databases, one containing mild cognitive impairment (MCI) and healthy subjects (patients age: 71.9 ± 10.2, healthy subjects age: 71.7 ± 8.3), and the other containing Mild AD and healthy subjects (patients age: 77.6 ± 10.0 healthy subjects age: 69.4 ± 11.5). Main results. Using a single feature to compute CRs we achieve a performance of 78.33% for the MCI data set and of 97.56% for Mild AD. Results are clearly improved using the multiple feature classification, where a CR of 95% is found for the MCI data set using 11 features, and 100% for the Mild AD data set using four features. Significance. The new features selection method described in this work may be a reliable tool that could help to design a realistic system that does not require prior knowledge of a patient's status. With that aim, we explore the standardization of features for MCI and Mild AD data sets with promising results.

Feature-based Morphometry

PubMed Central

Toews, Matthew; Wells, William M.; Collins, Louis; Arbel, Tal

2013-01-01

This paper presents feature-based morphometry (FBM), a new, fully data-driven technique for identifying group-related differences in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between all subjects, FBM models images as a collage of distinct, localized image features which may not be present in all subjects. FBM thus explicitly accounts for the case where the same anatomical tissue cannot be reliably identified in all subjects due to disease or anatomical variability. A probabilistic model describes features in terms of their appearance, geometry, and relationship to sub-groups of a population, and is automatically learned from a set of subject images and group labels. Features identified indicate group-related anatomical structure that can potentially be used as disease biomarkers or as a basis for computer-aided diagnosis. Scale-invariant image features are used, which reflect generic, salient patterns in the image. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer’s (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and obtains an equal error classification rate of 0.78 on new subjects. PMID:20426102

[Dyskinesia in Parkinson's disease--major clinical features, aetiology, therapy].

PubMed

Ellrichmann, G; Russ, H; Müller, T

2007-07-01

Parkinson's disease (PD), a slowly, progressive degenerative disorder of the central nervous system, which affects about ten million people world-wide, is currently treated symptomatically. Current treatment aim i. e. to balance the decreased dopamine turnover in striatal neurons. Chronic exposure to dopaminergic agents, however, supports onset of motor complications and dyskinesia in the long term. Dyskinesia appear mainly as chorea, athetosis, dystonia, stereotypia, ballism or a combination. Sometimes excessive abnormal facial, body and limb movements depend on the overall dosage of dopaminergic substitution. This is why the main therapy is based on reducing the total dosage of dopaminergic substances. Either alternative or additional well-tried substances like apomorphine, amantadine or clozapine are used. New possibilities in treatment emerge from substances like sarizotan, istradefylline, fipampezol or talampanel. Even so disability and reduced quality of life in PD patients and their caregivers may exist. This survey describes the major clinical features, aetiology and demographics of treatment-associated dyskinesia in PD.

Main-Sequence CMEs as Magnetic Explosions: Compatibility with Observed Kinematics

NASA Technical Reports Server (NTRS)

Moore, Ron; Falconer, David; Sterling, Alphonse

2004-01-01

We examine the kinematics of 26 CMEs of the morphological main sequence of CMEs, those having the classic three-part bubble structure of (1) a bright front eveloping (2) a dark cavity within which rides (3) a bright blob/filamentary feature. Each CME is observed in Yohkoh/SXT images to originate from near the limb (> or equal to 0.7 R(sub Sun) from disk center). The basic data (from the SOHO LASCO CME Catalog) for the kinematics of each CME are the sequence of LASCO images of the CME, the time of each image, the measured radial distance of the front edge of the CME in each image, and the measured angular extent of the CME. About half of our CMEs (12) occur with a flare, and the rest (14) occur without a flare. While the average linear-fit speed of the flare CMEs (1000 km/s) is twice that of the non-flare CMEs (510 km/s), the flare CMEs and the non-flare CMEs are similar in that some have nearly flat velocity-height (radial extent) profiles (little acceleration), some have noticeably falling velocity profiles (noticeable deceleration), and the rest have velocity profiles that rise considerably through the outer corona (blatant acceleration). This suggests that in addition to sharing similar morphology, main-sequence CMEs all have basically the same driving mechanism. The observed radial progression of each of our 26 CMEs is fit by a simple model magnetic plasmoid that is in pressure balance with the radial magnetic field in the outer corona and that propels itself outward by magnetic expansion, doing no net work on its surroundings. On average over the 26 CMEs, this model fits the observations as well as the assumption of constant acceleration. This is compatible with main-sequence CMEs being magnetically driven, basically magnetic explosions, with the velocity profile in the outer corona being largely dictated by the initial Alfien speed in the CME (when the front is at approx. 3 (sub Sun), analogous to the mass of a main-sequence star dictating the luminosity.

Features of the Information and Communication Technology Application by the Subjects of Special Education

ERIC Educational Resources Information Center

Arhipova, Svetlana Vladimirovna; Sergeeva, Olesya Sergeevna

2015-01-01

The main purpose of this study is to reveal the features of information and communication technologies application by the subjects of education in the conditions of special (correctional) school type VIII, and to identify the level of computer literacy of special education. The study was conducted on the basis of the State Budgetary Special…

Main magnetic field of Jupiter and its implications for future orbiter missions

NASA Technical Reports Server (NTRS)

Acuna, M. H.; Ness, N. F.

1975-01-01

A very strong planetary magnetic field and an enormous magnetosphere with extremely intense radiation belts exist at Jupiter. Pioneer 10 and 11 fly-bys confirmed and extended the earlier ground based estimates of many of these characteristics but left unanswered or added to the list of several important and poorly understood features: the source mechanism and location of decametric emissions, and the absorption effects by the natural satellites Amalthea, Io, Europa and Ganymede. High inclination orbits (exceeding 60 deg) with low periapses (less than 2 Jupiter radii) are required to map the radiation belts and main magnetic field of Jupiter accurately so as to permit full investigation of these and associated phenomena.

Visual Cortex Inspired CNN Model for Feature Construction in Text Analysis

PubMed Central

Fu, Hongping; Niu, Zhendong; Zhang, Chunxia; Ma, Jing; Chen, Jie

2016-01-01

Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN) are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention modulation and memory processing of primate visual cortex. In this paper, we employ the above properties of primate visual cortex to improve CNN and propose a biological-mechanism-driven-feature-construction based answer recommendation method (BMFC-ARM), which is used to recommend the best answer for the corresponding given questions in community question answering. BMFC-ARM is an improved CNN with four channels respectively representing questions, answers, asker information and answerer information, and mainly contains two stages: biological mechanism driven feature construction (BMFC) and answer ranking. BMFC imitates the attention modulation property by introducing the asker information and answerer information of given questions and the similarity between them, and imitates the memory processing property through bringing in the user reputation information for answerers. Then the feature vector for answer ranking is constructed by fusing the asker-answerer similarities, answerer's reputation and the corresponding vectors of question, answer, asker, and answerer. Finally, the Softmax is used at the stage of answer ranking to get best answers by the feature vector. The experimental results of answer recommendation on the Stackexchange dataset show that BMFC-ARM exhibits better performance. PMID:27471460

Visual Cortex Inspired CNN Model for Feature Construction in Text Analysis.

PubMed

Fu, Hongping; Niu, Zhendong; Zhang, Chunxia; Ma, Jing; Chen, Jie

2016-01-01

Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN) are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention modulation and memory processing of primate visual cortex. In this paper, we employ the above properties of primate visual cortex to improve CNN and propose a biological-mechanism-driven-feature-construction based answer recommendation method (BMFC-ARM), which is used to recommend the best answer for the corresponding given questions in community question answering. BMFC-ARM is an improved CNN with four channels respectively representing questions, answers, asker information and answerer information, and mainly contains two stages: biological mechanism driven feature construction (BMFC) and answer ranking. BMFC imitates the attention modulation property by introducing the asker information and answerer information of given questions and the similarity between them, and imitates the memory processing property through bringing in the user reputation information for answerers. Then the feature vector for answer ranking is constructed by fusing the asker-answerer similarities, answerer's reputation and the corresponding vectors of question, answer, asker, and answerer. Finally, the Softmax is used at the stage of answer ranking to get best answers by the feature vector. The experimental results of answer recommendation on the Stackexchange dataset show that BMFC-ARM exhibits better performance.

77 FR 36298 - In the Matter of Maine Yankee Atomic Power Company; Maine Yankee Atomic Power Station...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-18

... the Matter of Maine Yankee Atomic Power Company; Maine Yankee Atomic Power Station; Confirmatory Order... Regulatory Commission (NRC or the Commission) issued a Confirmatory Order to Maine Yankee Atomic Power...: (301) 492-3342; Email: [email protected] . I Maine Yankee Atomic Power Company (Maine Yankee or the...

A short feature vector for image matching: The Log-Polar Magnitude feature descriptor

PubMed Central

Hast, Anders; Wählby, Carolina; Sintorn, Ida-Maria

2017-01-01

The choice of an optimal feature detector-descriptor combination for image matching often depends on the application and the image type. In this paper, we propose the Log-Polar Magnitude feature descriptor—a rotation, scale, and illumination invariant descriptor that achieves comparable performance to SIFT on a large variety of image registration problems but with much shorter feature vectors. The descriptor is based on the Log-Polar Transform followed by a Fourier Transform and selection of the magnitude spectrum components. Selecting different frequency components allows optimizing for image patterns specific for a particular application. In addition, by relying only on coordinates of the found features and (optionally) feature sizes our descriptor is completely detector independent. We propose 48- or 56-long feature vectors that potentially can be shortened even further depending on the application. Shorter feature vectors result in better memory usage and faster matching. This combined with the fact that the descriptor does not require a time-consuming feature orientation estimation (the rotation invariance is achieved solely by using the magnitude spectrum of the Log-Polar Transform) makes it particularly attractive to applications with limited hardware capacity. Evaluation is performed on the standard Oxford dataset and two different microscopy datasets; one with fluorescence and one with transmission electron microscopy images. Our method performs better than SURF and comparable to SIFT on the Oxford dataset, and better than SIFT on both microscopy datasets indicating that it is particularly useful in applications with microscopy images. PMID:29190737

A simple, analytical, axisymmetric microburst model for downdraft estimation

NASA Technical Reports Server (NTRS)

Vicroy, Dan D.

1991-01-01

A simple analytical microburst model was developed for use in estimating vertical winds from horizontal wind measurements. It is an axisymmetric, steady state model that uses shaping functions to satisfy the mass continuity equation and simulate boundary layer effects. The model is defined through four model variables: the radius and altitude of the maximum horizontal wind, a shaping function variable, and a scale factor. The model closely agrees with a high fidelity analytical model and measured data, particularily in the radial direction and at lower altitudes. At higher altitudes, the model tends to overestimate the wind magnitude relative to the measured data.

Examining Brain Morphometry Associated with Self-Esteem in Young Adults Using Multilevel-ROI-Features-Based Classification Method

PubMed Central

Peng, Bo; Lu, Jieru; Saxena, Aditya; Zhou, Zhiyong; Zhang, Tao; Wang, Suhong; Dai, Yakang

2017-01-01

Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR) images using multilevel-features-based classification method. Method: The multilevel region of interest (ROI) features consist of two types of features: (i) ROI features, which include gray matter volume, white matter volume, cerebrospinal fluid volume, cortical thickness, and cortical surface area, and (ii) similarity features, which are based on similarity calculation of cortical thickness between ROIs. For each feature type, a hybrid feature selection method, comprising of filter-based and wrapper-based algorithms, is used to select the most discriminating features. ROI features and similarity features are integrated by using multi-kernel support vector machines (SVMs) with appropriate weighting factor. Results: The classification performance is improved by using multilevel ROI features with an accuracy of 96.66%, a specificity of 96.62%, and a sensitivity of 95.67%. The most discriminating ROI features that are related to self-esteem spread over occipital lobe, frontal lobe, parietal lobe, limbic lobe, temporal lobe, and central region, mainly involving white matter and cortical thickness. The most discriminating similarity features are distributed in both the right and left hemisphere, including frontal lobe, occipital lobe, limbic lobe, parietal lobe, and central region, which conveys information of structural connections between different brain regions. Conclusion: By using ROI features and similarity features to exam self-esteem related brain morphometry, this paper provides a pilot evidence that self-esteem is linked to specific ROIs and structural connections between different brain regions. PMID:28588470

Examining Brain Morphometry Associated with Self-Esteem in Young Adults Using Multilevel-ROI-Features-Based Classification Method.

PubMed

Peng, Bo; Lu, Jieru; Saxena, Aditya; Zhou, Zhiyong; Zhang, Tao; Wang, Suhong; Dai, Yakang

2017-01-01

Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR) images using multilevel-features-based classification method. Method: The multilevel region of interest (ROI) features consist of two types of features: (i) ROI features, which include gray matter volume, white matter volume, cerebrospinal fluid volume, cortical thickness, and cortical surface area, and (ii) similarity features, which are based on similarity calculation of cortical thickness between ROIs. For each feature type, a hybrid feature selection method, comprising of filter-based and wrapper-based algorithms, is used to select the most discriminating features. ROI features and similarity features are integrated by using multi-kernel support vector machines (SVMs) with appropriate weighting factor. Results: The classification performance is improved by using multilevel ROI features with an accuracy of 96.66%, a specificity of 96.62%, and a sensitivity of 95.67%. The most discriminating ROI features that are related to self-esteem spread over occipital lobe, frontal lobe, parietal lobe, limbic lobe, temporal lobe, and central region, mainly involving white matter and cortical thickness. The most discriminating similarity features are distributed in both the right and left hemisphere, including frontal lobe, occipital lobe, limbic lobe, parietal lobe, and central region, which conveys information of structural connections between different brain regions. Conclusion: By using ROI features and similarity features to exam self-esteem related brain morphometry, this paper provides a pilot evidence that self-esteem is linked to specific ROIs and structural connections between different brain regions.

33 CFR 334.10 - Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 3 2012-07-01 2012-07-01 false Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area. 334.10 Section 334.10 Navigation and Navigable Waters CORPS... REGULATIONS § 334.10 Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area. (a) The danger...

33 CFR 334.10 - Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 3 2011-07-01 2011-07-01 false Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area. 334.10 Section 334.10 Navigation and Navigable Waters CORPS... REGULATIONS § 334.10 Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area. (a) The danger...

33 CFR 334.10 - Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 3 2013-07-01 2013-07-01 false Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area. 334.10 Section 334.10 Navigation and Navigable Waters CORPS... REGULATIONS § 334.10 Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area. (a) The danger...

33 CFR 334.10 - Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 3 2014-07-01 2014-07-01 false Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area. 334.10 Section 334.10 Navigation and Navigable Waters CORPS... REGULATIONS § 334.10 Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area. (a) The danger...

Dynamics of feature categorization.

PubMed

Martí, Daniel; Rinzel, John

2013-01-01

In visual and auditory scenes, we are able to identify shared features among sensory objects and group them according to their similarity. This grouping is preattentive and fast and is thought of as an elementary form of categorization by which objects sharing similar features are clustered in some abstract perceptual space. It is unclear what neuronal mechanisms underlie this fast categorization. Here we propose a neuromechanistic model of fast feature categorization based on the framework of continuous attractor networks. The mechanism for category formation does not rely on learning and is based on biologically plausible assumptions, for example, the existence of populations of neurons tuned to feature values, feature-specific interactions, and subthreshold-evoked responses upon the presentation of single objects. When the network is presented with a sequence of stimuli characterized by some feature, the network sums the evoked responses and provides a running estimate of the distribution of features in the input stream. If the distribution of features is structured into different components or peaks (i.e., is multimodal), recurrent excitation amplifies the response of activated neurons, and categories are singled out as emerging localized patterns of elevated neuronal activity (bumps), centered at the centroid of each cluster. The emergence of bump states through sequential, subthreshold activation and the dependence on input statistics is a novel application of attractor networks. We show that the extraction and representation of multiple categories are facilitated by the rich attractor structure of the network, which can sustain multiple stable activity patterns for a robust range of connectivity parameters compatible with cortical physiology.

Multiple mechanisms in the perception of face gender: Effect of sex-irrelevant features.

PubMed

Komori, Masashi; Kawamura, Satoru; Ishihara, Shigekazu

2011-06-01

Effects of sex-relevant and sex-irrelevant facial features on the evaluation of facial gender were investigated. Participants rated masculinity of 48 male facial photographs and femininity of 48 female facial photographs. Eighty feature points were measured on each of the facial photographs. Using a generalized Procrustes analysis, facial shapes were converted into multidimensional vectors, with the average face as a starting point. Each vector was decomposed into a sex-relevant subvector and a sex-irrelevant subvector which were, respectively, parallel and orthogonal to the main male-female axis. Principal components analysis (PCA) was performed on the sex-irrelevant subvectors. One principal component was negatively correlated with both perceived masculinity and femininity, and another was correlated only with femininity, though both components were orthogonal to the male-female dimension (and thus by definition sex-irrelevant). These results indicate that evaluation of facial gender depends on sex-irrelevant as well as sex-relevant facial features.

Depth estimation of features in video frames with improved feature matching technique using Kinect sensor

NASA Astrophysics Data System (ADS)

Sharma, Kajal; Moon, Inkyu; Kim, Sung Gaun

2012-10-01

Estimating depth has long been a major issue in the field of computer vision and robotics. The Kinect sensor's active sensing strategy provides high-frame-rate depth maps and can recognize user gestures and human pose. This paper presents a technique to estimate the depth of features extracted from video frames, along with an improved feature-matching method. In this paper, we used the Kinect camera developed by Microsoft, which captured color and depth images for further processing. Feature detection and selection is an important task for robot navigation. Many feature-matching techniques have been proposed earlier, and this paper proposes an improved feature matching between successive video frames with the use of neural network methodology in order to reduce the computation time of feature matching. The features extracted are invariant to image scale and rotation, and different experiments were conducted to evaluate the performance of feature matching between successive video frames. The extracted features are assigned distance based on the Kinect technology that can be used by the robot in order to determine the path of navigation, along with obstacle detection applications.

Fast-moving features in the debris disk around AU Microscopii.

PubMed

Boccaletti, Anthony; Thalmann, Christian; Lagrange, Anne-Marie; Janson, Markus; Augereau, Jean-Charles; Schneider, Glenn; Milli, Julien; Grady, Carol; Debes, John; Langlois, Maud; Mouillet, David; Henning, Thomas; Dominik, Carsten; Maire, Anne-Lise; Beuzit, Jean-Luc; Carson, Joseph; Dohlen, Kjetil; Engler, Natalia; Feldt, Markus; Fusco, Thierry; Ginski, Christian; Girard, Julien H; Hines, Dean; Kasper, Markus; Mawet, Dimitri; Ménard, François; Meyer, Michael R; Moutou, Claire; Olofsson, Johan; Rodigas, Timothy; Sauvage, Jean-Francois; Schlieder, Joshua; Schmid, Hans Martin; Turatto, Massimo; Udry, Stephane; Vakili, Farrokh; Vigan, Arthur; Wahhaj, Zahed; Wisniewski, John

2015-10-08

In the 1980s, excess infrared emission was discovered around main-sequence stars; subsequent direct-imaging observations revealed orbiting disks of cold dust to be the source. These 'debris disks' were thought to be by-products of planet formation because they often exhibited morphological and brightness asymmetries that may result from gravitational perturbation by planets. This was proved to be true for the β Pictoris system, in which the known planet generates an observable warp in the disk. The nearby, young, unusually active late-type star AU Microscopii hosts a well-studied edge-on debris disk; earlier observations in the visible and near-infrared found asymmetric localized structures in the form of intensity variations along the midplane of the disk beyond a distance of 20 astronomical units. Here we report high-contrast imaging that reveals a series of five large-scale features in the southeast side of the disk, at projected separations of 10-60 astronomical units, persisting over intervals of 1-4 years. All these features appear to move away from the star at projected speeds of 4-10 kilometres per second, suggesting highly eccentric or unbound trajectories if they are associated with physical entities. The origin, localization, morphology and rapid evolution of these features are difficult to reconcile with current theories.

Visual Odometry Based on Structural Matching of Local Invariant Features Using Stereo Camera Sensor

PubMed Central

Núñez, Pedro; Vázquez-Martín, Ricardo; Bandera, Antonio

2011-01-01

This paper describes a novel sensor system to estimate the motion of a stereo camera. Local invariant image features are matched between pairs of frames and linked into image trajectories at video rate, providing the so-called visual odometry, i.e., motion estimates from visual input alone. Our proposal conducts two matching sessions: the first one between sets of features associated to the images of the stereo pairs and the second one between sets of features associated to consecutive frames. With respect to previously proposed approaches, the main novelty of this proposal is that both matching algorithms are conducted by means of a fast matching algorithm which combines absolute and relative feature constraints. Finding the largest-valued set of mutually consistent matches is equivalent to finding the maximum-weighted clique on a graph. The stereo matching allows to represent the scene view as a graph which emerge from the features of the accepted clique. On the other hand, the frame-to-frame matching defines a graph whose vertices are features in 3D space. The efficiency of the approach is increased by minimizing the geometric and algebraic errors to estimate the final displacement of the stereo camera between consecutive acquired frames. The proposed approach has been tested for mobile robotics navigation purposes in real environments and using different features. Experimental results demonstrate the performance of the proposal, which could be applied in both industrial and service robot fields. PMID:22164016

The circumstellar environments of dusty main sequence stars

NASA Astrophysics Data System (ADS)

Gebrim, Antonio S. Hales

-light images of dust-disks around dust excess stars. This technique allows one to automatically suppress the unpolarised light from the central star, increasing the dynamic range for detecting polarised light scattered by the dust present in circumstellar discs. The detections of extended disks around the classical T Tauri star TW Hya and the Herbig Ac star HD 169142 are reported, as well as the strong but spatially unresolved polarization signals measured toward two other Herbig Ae stars. Monte Carlo scattering simulations are used to fit the J-, H- and K-band polarization images of the disk around TW Hya, providing new constraints on the geometry of TW Hya's disk. The third part of this thesis is dedicated to studying the gas content and dynamics around dust-excess stars. The evolution of circumstellar gas is thought to be strongly linked to the formation of gaseous giant planets similar to Jupiter, Saturn and most currently known extra-solar planets. However, the timescales over which circumstellar gas discs dissipate remains poorly constrained, mainly due to the observational difficulties associated with detecting small amounts of circumstellar gas. An analysis of high-resolution (R 50 000) optical spectroscopic data of a sample of 'Vega-like' candidates from the catalogue of Mannings & Barlow (1998) is presented. Analysis of the stellar spectra allows one to search for narrow absorption features due to circumstellar gas and possible Falling Evaporating Bodies, similar to the ones seen in the (3 Pictoris system. None of the stars from this sample show emission line activity in either Ha, Ca II or Na I, indicating that accretion of material onto the stars has ceased and suggesting they are true main sequence Vega-like stars. Four stars were found to exhibit narrow absorption features near the cores of the photospheric Ca II and Na I D lines, with HD 110058 being the strongest candidate to host a (3 Pictoris-like gas disk. If confirmed, HD 110058 would represent the Vega

Combined effects of inversion and feature removal on N170 responses elicited by faces and car fronts

PubMed Central

Kloth, Nadine; Itier, Roxane J.; Schweinberger, Stefan R.

2014-01-01

The face-sensitive N170 is typically enhanced for inverted compared to upright faces. Itier, Alain, Sedore, and McIntosh (2007) recently suggested that this N170 inversion effect is mainly driven by the eye region which becomes salient when the face configuration is disrupted. Here we tested whether similar effects could be observed with non-face objects that are structurally similar to faces in terms of possessing a homogeneous within-class first-order feature configuration. We presented upright and inverted pictures of intact car fronts, car fronts without lights, and isolated lights, in addition to analogous face conditions. Upright cars elicited substantial N170 responses of similar amplitude to those evoked by upright faces. In strong contrast to face conditions however, the car-elicited N170 was mainly driven by the global shape rather than the presence or absence of lights, and was dramatically reduced for isolated lights. Overall, our data confirm a differential influence of the eye region in upright and inverted faces. Results for car fronts do not suggest similar interactive encoding of eye-like features and configuration for non-face objects, even when these objects possess a similar feature configuration as faces. PMID:23485023

Features of two-phase flow in a microchannel of 0.05×20 mm

NASA Astrophysics Data System (ADS)

Ronshin, Fedor

2017-10-01

We have studied the two-phase flow in a microchannel with cross-section of 0.05×20 mm2. The following two-phase flow regimes have been registered: jet, bubble, stratified, annular, and churn ones. The main features of flow regimes in this channel such as formation of liquid droplets in all two-phase flows have been distinguished.

Internal versus external features in triggering the brain waveforms for conjunction and feature faces in recognition.

PubMed

Nie, Aiqing; Jiang, Jingguo; Fu, Qiao

2014-08-20

Previous research has found that conjunction faces (whose internal features, e.g. eyes, nose, and mouth, and external features, e.g. hairstyle and ears, are from separate studied faces) and feature faces (partial features of these are studied) can produce higher false alarms than both old and new faces (i.e. those that are exactly the same as the studied faces and those that have not been previously presented) in recognition. The event-related potentials (ERPs) that relate to conjunction and feature faces at recognition, however, have not been described as yet; in addition, the contributions of different facial features toward ERPs have not been differentiated. To address these issues, the present study compared the ERPs elicited by old faces, conjunction faces (the internal and the external features were from two studied faces), old internal feature faces (whose internal features were studied), and old external feature faces (whose external features were studied) with those of new faces separately. The results showed that old faces not only elicited an early familiarity-related FN400, but a more anterior distributed late old/new effect that reflected recollection. Conjunction faces evoked similar late brain waveforms as old internal feature faces, but not to old external feature faces. These results suggest that, at recognition, old faces hold higher familiarity than compound faces in the profiles of ERPs and internal facial features are more crucial than external ones in triggering the brain waveforms that are characterized as reflecting the result of familiarity.

Red Lesion Detection Using Dynamic Shape Features for Diabetic Retinopathy Screening.

PubMed

Seoud, Lama; Hurtut, Thomas; Chelbi, Jihed; Cheriet, Farida; Langlois, J M Pierre

2016-04-01

The development of an automatic telemedicine system for computer-aided screening and grading of diabetic retinopathy depends on reliable detection of retinal lesions in fundus images. In this paper, a novel method for automatic detection of both microaneurysms and hemorrhages in color fundus images is described and validated. The main contribution is a new set of shape features, called Dynamic Shape Features, that do not require precise segmentation of the regions to be classified. These features represent the evolution of the shape during image flooding and allow to discriminate between lesions and vessel segments. The method is validated per-lesion and per-image using six databases, four of which are publicly available. It proves to be robust with respect to variability in image resolution, quality and acquisition system. On the Retinopathy Online Challenge's database, the method achieves a FROC score of 0.420 which ranks it fourth. On the Messidor database, when detecting images with diabetic retinopathy, the proposed method achieves an area under the ROC curve of 0.899, comparable to the score of human experts, and it outperforms state-of-the-art approaches.

Breast cancer mitosis detection in histopathological images with spatial feature extraction

NASA Astrophysics Data System (ADS)

Albayrak, Abdülkadir; Bilgin, Gökhan

2013-12-01

In this work, cellular mitosis detection in histopathological images has been investigated. Mitosis detection is very expensive and time consuming process. Development of digital imaging in pathology has enabled reasonable and effective solution to this problem. Segmentation of digital images provides easier analysis of cell structures in histopathological data. To differentiate normal and mitotic cells in histopathological images, feature extraction step is very crucial step for the system accuracy. A mitotic cell has more distinctive textural dissimilarities than the other normal cells. Hence, it is important to incorporate spatial information in feature extraction or in post-processing steps. As a main part of this study, Haralick texture descriptor has been proposed with different spatial window sizes in RGB and La*b* color spaces. So, spatial dependencies of normal and mitotic cellular pixels can be evaluated within different pixel neighborhoods. Extracted features are compared with various sample sizes by Support Vector Machines using k-fold cross validation method. According to the represented results, it has been shown that separation accuracy on mitotic and non-mitotic cellular pixels gets better with the increasing size of spatial window.

Attentional Selection of Feature Conjunctions Is Accomplished by Parallel and Independent Selection of Single Features.

PubMed

Andersen, Søren K; Müller, Matthias M; Hillyard, Steven A

2015-07-08

Experiments that study feature-based attention have often examined situations in which selection is based on a single feature (e.g., the color red). However, in more complex situations relevant stimuli may not be set apart from other stimuli by a single defining property but by a specific combination of features. Here, we examined sustained attentional selection of stimuli defined by conjunctions of color and orientation. Human observers attended to one out of four concurrently presented superimposed fields of randomly moving horizontal or vertical bars of red or blue color to detect brief intervals of coherent motion. Selective stimulus processing in early visual cortex was assessed by recordings of steady-state visual evoked potentials (SSVEPs) elicited by each of the flickering fields of stimuli. We directly contrasted attentional selection of single features and feature conjunctions and found that SSVEP amplitudes on conditions in which selection was based on a single feature only (color or orientation) exactly predicted the magnitude of attentional enhancement of SSVEPs when attending to a conjunction of both features. Furthermore, enhanced SSVEP amplitudes elicited by attended stimuli were accompanied by equivalent reductions of SSVEP amplitudes elicited by unattended stimuli in all cases. We conclude that attentional selection of a feature-conjunction stimulus is accomplished by the parallel and independent facilitation of its constituent feature dimensions in early visual cortex. The ability to perceive the world is limited by the brain's processing capacity. Attention affords adaptive behavior by selectively prioritizing processing of relevant stimuli based on their features (location, color, orientation, etc.). We found that attentional mechanisms for selection of different features belonging to the same object operate independently and in parallel: concurrent attentional selection of two stimulus features is simply the sum of attending to each of those

A Featured-Based Strategy for Stereovision Matching in Sensors with Fish-Eye Lenses for Forest Environments

PubMed Central

Herrera, Pedro Javier; Pajares, Gonzalo; Guijarro, Maria; Ruz, José J.; Cruz, Jesús M.; Montes, Fernando

2009-01-01

This paper describes a novel feature-based stereovision matching process based on a pair of omnidirectional images in forest stands acquired with a stereovision sensor equipped with fish-eye lenses. The stereo analysis problem consists of the following steps: image acquisition, camera modelling, feature extraction, image matching and depth determination. Once the depths of significant points on the trees are obtained, the growing stock volume can be estimated by considering the geometrical camera modelling, which is the final goal. The key steps are feature extraction and image matching. This paper is devoted solely to these two steps. At a first stage a segmentation process extracts the trunks, which are the regions used as features, where each feature is identified through a set of attributes of properties useful for matching. In the second step the features are matched based on the application of the following four well known matching constraints, epipolar, similarity, ordering and uniqueness. The combination of the segmentation and matching processes for this specific kind of sensors make the main contribution of the paper. The method is tested with satisfactory results and compared against the human expert criterion. PMID:22303134

Mobile personal health records: an evaluation of features and functionality.

PubMed

Kharrazi, Hadi; Chisholm, Robin; VanNasdale, Dean; Thompson, Benjamin

2012-09-01

To evaluate stand-alone mobile personal health record (mPHR) applications for the three leading cellular phone platforms (iOS, BlackBerry, and Android), assessing each for content, function, security, and marketing characteristics. Nineteen stand-alone mPHR applications (8 for iOS, 5 for BlackBerry, and 6 for Android) were identified and evaluated. Main criteria used to include mPHRs were: operating standalone on a mobile platform; not requiring external connectivity; and covering a wide range of health topics. Selected mPHRs were analyzed considering product characteristics, data elements, and application features. We also reviewed additional features such as marketing tactics. Within and between the different mobile platforms attributes for the mPHR were highly variable. None of the mPHRs contained all attributes included in our evaluation. The top four mPHRs contained 13 of the 14 features omitting only the in-case-of emergency feature. Surprisingly, seven mPHRs lacked basic security measures as important as password protection. The mPHRs were relatively inexpensive: ranging from no cost to $9.99. The mPHR application cost varied in some instances based on whether it supported single or multiple users. Ten mPHRs supported multiple user profiles. Notably, eight mPHRs used scare tactics as marketing strategy. mPHR is an emerging health care technology. The majority of existing mPHR apps is limited by at least one of the attributes considered for this study; however, as the mobile market continues to expand it is likely that more comprehensive mPHRs will be developed in the near future. New advancements in mobile technology can be utilized to enhance mPHRs by long-term patient empowerment features. Marketing strategies for mPHRs should target specific subpopulations and avoid scare tactics. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Prediction of subjective ratings of emotional pictures by EEG features

NASA Astrophysics Data System (ADS)

McFarland, Dennis J.; Parvaz, Muhammad A.; Sarnacki, William A.; Goldstein, Rita Z.; Wolpaw, Jonathan R.

2017-02-01

Objective. Emotion dysregulation is an important aspect of many psychiatric disorders. Brain-computer interface (BCI) technology could be a powerful new approach to facilitating therapeutic self-regulation of emotions. One possible BCI method would be to provide stimulus-specific feedback based on subject-specific electroencephalographic (EEG) responses to emotion-eliciting stimuli. Approach. To assess the feasibility of this approach, we studied the relationships between emotional valence/arousal and three EEG features: amplitude of alpha activity over frontal cortex; amplitude of theta activity over frontal midline cortex; and the late positive potential over central and posterior mid-line areas. For each feature, we evaluated its ability to predict emotional valence/arousal on both an individual and a group basis. Twenty healthy participants (9 men, 11 women; ages 22-68) rated each of 192 pictures from the IAPS collection in terms of valence and arousal twice (96 pictures on each of 4 d over 2 weeks). EEG was collected simultaneously and used to develop models based on canonical correlation to predict subject-specific single-trial ratings. Separate models were evaluated for the three EEG features: frontal alpha activity; frontal midline theta; and the late positive potential. In each case, these features were used to simultaneously predict both the normed ratings and the subject-specific ratings. Main results. Models using each of the three EEG features with data from individual subjects were generally successful at predicting subjective ratings on training data, but generalization to test data was less successful. Sparse models performed better than models without regularization. Significance. The results suggest that the frontal midline theta is a better candidate than frontal alpha activity or the late positive potential for use in a BCI-based paradigm designed to modify emotional reactions.

Suppression effects in feature-based attention

PubMed Central

Wang, Yixue; Miller, James; Liu, Taosheng

2015-01-01

Attending to a feature enhances visual processing of that feature, but it is less clear what occurs to unattended features. Single-unit recording studies in middle temporal (MT) have shown that neuronal modulation is a monotonic function of the difference between the attended and neuron's preferred direction. Such a relationship should predict a monotonic suppressive effect in psychophysical performance. However, past research on suppressive effects of feature-based attention has remained inconclusive. We investigated the suppressive effect for motion direction, orientation, and color in three experiments. We asked participants to detect a weak signal among noise and provided a partially valid feature cue to manipulate attention. We measured performance as a function of the offset between the cued and signal feature. We also included neutral trials where no feature cues were presented to provide a baseline measure of performance. Across three experiments, we consistently observed enhancement effects when the target feature and cued feature coincided and suppression effects when the target feature deviated from the cued feature. The exact profile of suppression was different across feature dimensions: Whereas the profile for direction exhibited a “rebound” effect, the profiles for orientation and color were monotonic. These results demonstrate that unattended features are suppressed during feature-based attention, but the exact suppression profile depends on the specific feature. Overall, the results are largely consistent with neurophysiological data and support the feature-similarity gain model of attention. PMID:26067533

Endomyocardial fibrosis in Sudan: clinical and echocardiographic features

PubMed Central

Khalil, Siddiq Ibrahim; Khalil, Suha; El Tigani, Salma; Saad, Hanan A

2017-01-01

Summary Objective: Endomyocardial fibrosis (EMF) is a rare disease and is often an underdiagnosed and forgotten cardiomyopathy. The objective of this study was to document the current frequency of EMF in Sudan by defining and selecting cases from patients attending the echocardiography laboratory. Additionally we aimed to create an EMF registry for Sudan. Methods: The study started in January 2007 and is on-going. All the patients attending our echocardiography clinics in four different hospitals in Khartoum, Sudan, were included. Transthoracic echocardiography was used as the main diagnostic and selection tool. The diagnosis of EMF was based on predefined criteria and definitions, and was further supported by additional clinical, ECG, laboratory and chest X-ray findings. Results: Out of 4 332 cases studied, 23 (0.5%) were found to have features of EMF. Females constituted 52% and the age range was 24 to 67 years. All patients presented with dyspnoea grades III–IV. Advanced heart failure with gross fluid overload was seen in 54% of cases and ascites was seen in 30%. EMF was biventricular in 53%, left ventricular in 29% and right ventricular in 18% of cases. Apical and ventricular wall fibrosis was found in all cases, followed by atrial enlargement, atrioventricular valve incompetence, ventricular cavity obliteration, restrictive flow pattern and pericardial effusion. Additional echocardiographic features are defined and discussed. Conclusion: Although a rare disease, cases of EMF can be identified in Sudan if a high index of suspicion is observed. New echocardiographic features of ventricular wall layering, endocardial fibrous shelf and endomyocardiopericarial fibrosis were identified and are discussed. PMID:28906536

Recursive Feature Extraction in Graphs

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

2014-08-14

ReFeX extracts recursive topological features from graph data. The input is a graph as a csv file and the output is a csv file containing feature values for each node in the graph. The features are based on topological counts in the neighborhoods of each nodes, as well as recursive summaries of neighbors' features.

Prediction of protein post-translational modifications: main trends and methods

NASA Astrophysics Data System (ADS)

Sobolev, B. N.; Veselovsky, A. V.; Poroikov, V. V.

2014-02-01

The review summarizes main trends in the development of methods for the prediction of protein post-translational modifications (PTMs) by considering the three most common types of PTMs — phosphorylation, acetylation and glycosylation. Considerable attention is given to general characteristics of regulatory interactions associated with PTMs. Different approaches to the prediction of PTMs are analyzed. Most of the methods are based only on the analysis of the neighbouring environment of modification sites. The related software is characterized by relatively low accuracy of PTM predictions, which may be due both to the incompleteness of training data and the features of PTM regulation. Advantages and limitations of the phylogenetic approach are considered. The prediction of PTMs using data on regulatory interactions, including the modular organization of interacting proteins, is a promising field, provided that a more carefully selected training data will be used. The bibliography includes 145 references.

Structural and compositional features of high-rise buildings: experimental design in Yekaterinburg

NASA Astrophysics Data System (ADS)

Yankovskaya, Yulia; Lobanov, Yuriy; Temnov, Vladimir

2018-03-01

The study looks at the specifics of high-rise development in Yekaterinburg. High-rise buildings are considered in the context of their historical development, structural features, compositional and imaginative design techniques. Experience of Yekaterinburg architects in experimental design is considered and analyzed. Main issues and prospects of high-rise development within the Yekaterinburg structure are studied. The most interesting and significant conceptual approaches to the structural and compositional arrangement of high-rise buildings are discussed.

Features of Coping with Disease in Iranian Multiple Sclerosis Patients: a Qualitative Study.

PubMed

Dehghani, Ali; Dehghan Nayeri, Nahid; Ebadi, Abbas

2018-03-01

Introduction: Coping with disease is of the main components improving the quality of life in multiple sclerosis patients. Identifying the characteristics of this concept is based on the experiences of patients. Using qualitative research is essential to improve the quality of life. This study was conducted to explore the features of coping with the disease in patients with multiple sclerosis. Method: In this conventional content analysis study, eleven multiple sclerosis patients from Iran MS Society in Tehran (Iran) participated. Purposive sampling was used to select participants. Data were gathered using semi structured interviews. To analyze data, a conventional content analysis approach was used to identify meaning units and to make codes and categories. Results: Results showed that features of coping with disease in multiple sclerosis patients consists of (a) accepting the current situation, (b) maintenance and development of human interactions, (c) self-regulation and (d) self-efficacy. Each of these categories is composed of sub-categories and codes that showed the perception and experience of patients about the coping with disease. Conclusion: Accordingly, a unique set of features regarding features of coping with the disease were identified among the patients with multiple sclerosis. Therefore, working to ensure the emergence of, and subsequent reinforcement of these features in MS patients can be an important step in improving the adjustment and quality of their lives.

Basaltic lava flows covering active aeolian dunes in the Paraná Basin in southern Brazil: Features and emplacement aspects

NASA Astrophysics Data System (ADS)

Waichel, Breno L.; Scherer, Claiton M. S.; Frank, Heinrich T.

2008-03-01

Burial of active aeolian dunes by lava flows can preserve the morphology of the dunes and generate diverse features related to interaction between unconsolidated sediments and lavas. In the study area, located in southern Brazil, burial of aeolian deposits by Cretaceous basaltic lava flows completely preserved dunes, and generate sand-deformation features, sand diapirs and peperite-like breccia. The preserved dunes are crescentic and linear at the main contact with basalts, and smaller crescentic where interlayered with lavas. The various feature types formed on sediment surfaces by the advance of the flows reflect the emplacement style of the lavas which are compound pahoehoe type. Four feature types can be recognized: (a) type 1 features are related to the advance of sheet flows in dune-interdune areas with slopes > 5°, (b) type 2 is formed where the lava flows advance in lobes and climb the stoss slope of crescentic dunes (slopes 8-12°), (c) type 3 is generated by toes that descend the face of linear dunes (slopes 17-23°) and (d) type 4 occurs when lava lobes descend the stoss slope of crescentic dunes (slopes 10-15°). The direction of the flows, the disposition and morphology of the dunes and the ground slope are the main factors controlling formation of the features. The injection of unconsolidated sand in lava lobes forms diapirs and peperite-like breccias. Sand diapirs occur at the basal portion of lobes where the lava was more solidified. Peperite-like breccias occur in the inner portion where lava was more plastic, favoring the mingling of the components. The generation of both features is related to a mechanical process: the weight of the lava causes the injection of sand into the lava and the warming of the air in the pores of the sand facilitates this process. The lava-sediment interaction features presented here are consistent with previous reports of basalt lavas with unconsolidated arid sediments, and additional new sand-deformation features

Semivolatile and Volatile Organic Compound Emissions from Wood-Fired Hydronic Heaters

EPA Science Inventory

Four commercially available HH technologies were studied: a single-stage combustor with natural updraft, a three-stage downdraft combustion system, a bottom-fed pellet burner, and a two-stage heater with both a combustion and gasification chamber. The fuel consisted of three wood...

Guilt by Association: The 13 micron Dust Feature in Circumstellar Shells and Related Spectral Features

NASA Astrophysics Data System (ADS)

Sloan, G. C.; Kraemer, K. E.; Goebel, J. H.; Price, S. D.

A study of spectra from the SWS on ISO of optically thin oxygen-rich dust shells shows that the strength of the 13 micron dust emission feature is correlated with the CO2 bands (13--17 microns) and dust emission features at 19.8 and 28.1 microns. SRb variables tend to show stronger 13 micron features than Mira variables, suggesting that the presence of the 13 micron and related features depends on pulsation mode and mass-loss rate. The absence of any correlation to dust emission features at 16.8 and 32 microns makes spinel an unlikely carrier. The most plausible carrier of the 13 micron feature remains crystalline alumina, and we suggest that the related dust features may be crystalline silicates. When dust forms in regions of low density, it may condense into crystalline grain structures.

Higher criticism thresholding: Optimal feature selection when useful features are rare and weak.

PubMed

Donoho, David; Jin, Jiashun

2008-09-30

In important application fields today-genomics and proteomics are examples-selecting a small subset of useful features is crucial for success of Linear Classification Analysis. We study feature selection by thresholding of feature Z-scores and introduce a principle of threshold selection, based on the notion of higher criticism (HC). For i = 1, 2, ..., p, let pi(i) denote the two-sided P-value associated with the ith feature Z-score and pi((i)) denote the ith order statistic of the collection of P-values. The HC threshold is the absolute Z-score corresponding to the P-value maximizing the HC objective (i/p - pi((i)))/sqrt{i/p(1-i/p)}. We consider a rare/weak (RW) feature model, where the fraction of useful features is small and the useful features are each too weak to be of much use on their own. HC thresholding (HCT) has interesting behavior in this setting, with an intimate link between maximizing the HC objective and minimizing the error rate of the designed classifier, and very different behavior from popular threshold selection procedures such as false discovery rate thresholding (FDRT). In the most challenging RW settings, HCT uses an unconventionally low threshold; this keeps the missed-feature detection rate under better control than FDRT and yields a classifier with improved misclassification performance. Replacing cross-validated threshold selection in the popular Shrunken Centroid classifier with the computationally less expensive and simpler HCT reduces the variance of the selected threshold and the error rate of the constructed classifier. Results on standard real datasets and in asymptotic theory confirm the advantages of HCT.

Higher criticism thresholding: Optimal feature selection when useful features are rare and weak

PubMed Central

Donoho, David; Jin, Jiashun

2008-01-01

In important application fields today—genomics and proteomics are examples—selecting a small subset of useful features is crucial for success of Linear Classification Analysis. We study feature selection by thresholding of feature Z-scores and introduce a principle of threshold selection, based on the notion of higher criticism (HC). For i = 1, 2, …, p, let πi denote the two-sided P-value associated with the ith feature Z-score and π(i) denote the ith order statistic of the collection of P-values. The HC threshold is the absolute Z-score corresponding to the P-value maximizing the HC objective (i/p − π(i))/i/p(1−i/p). We consider a rare/weak (RW) feature model, where the fraction of useful features is small and the useful features are each too weak to be of much use on their own. HC thresholding (HCT) has interesting behavior in this setting, with an intimate link between maximizing the HC objective and minimizing the error rate of the designed classifier, and very different behavior from popular threshold selection procedures such as false discovery rate thresholding (FDRT). In the most challenging RW settings, HCT uses an unconventionally low threshold; this keeps the missed-feature detection rate under better control than FDRT and yields a classifier with improved misclassification performance. Replacing cross-validated threshold selection in the popular Shrunken Centroid classifier with the computationally less expensive and simpler HCT reduces the variance of the selected threshold and the error rate of the constructed classifier. Results on standard real datasets and in asymptotic theory confirm the advantages of HCT. PMID:18815365

Fishing for Features

ScienceCinema

Heredia-Langner, Alejandro; Cort, John; Bailey, Vanessa

2018-01-16

The Fishing for Features Signature Discovery project developed a framework for discovering signature features in challenging environments involving large and complex data sets or where phenomena may be poorly characterized or understood. Researchers at PNNL have applied the framework to the optimization of biofuels blending and to discover signatures of climate change on microbial soil communities.

Fishing for Features

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

Heredia-Langner, Alejandro; Cort, John; Bailey, Vanessa

2016-07-21

The Fishing for Features Signature Discovery project developed a framework for discovering signature features in challenging environments involving large and complex data sets or where phenomena may be poorly characterized or understood. Researchers at PNNL have applied the framework to the optimization of biofuels blending and to discover signatures of climate change on microbial soil communities.

A PCA aided cross-covariance scheme for discriminative feature extraction from EEG signals.

PubMed

Zarei, Roozbeh; He, Jing; Siuly, Siuly; Zhang, Yanchun

2017-07-01

Feature extraction of EEG signals plays a significant role in Brain-computer interface (BCI) as it can significantly affect the performance and the computational time of the system. The main aim of the current work is to introduce an innovative algorithm for acquiring reliable discriminating features from EEG signals to improve classification performances and to reduce the time complexity. This study develops a robust feature extraction method combining the principal component analysis (PCA) and the cross-covariance technique (CCOV) for the extraction of discriminatory information from the mental states based on EEG signals in BCI applications. We apply the correlation based variable selection method with the best first search on the extracted features to identify the best feature set for characterizing the distribution of mental state signals. To verify the robustness of the proposed feature extraction method, three machine learning techniques: multilayer perceptron neural networks (MLP), least square support vector machine (LS-SVM), and logistic regression (LR) are employed on the obtained features. The proposed methods are evaluated on two publicly available datasets. Furthermore, we evaluate the performance of the proposed methods by comparing it with some recently reported algorithms. The experimental results show that all three classifiers achieve high performance (above 99% overall classification accuracy) for the proposed feature set. Among these classifiers, the MLP and LS-SVM methods yield the best performance for the obtained feature. The average sensitivity, specificity and classification accuracy for these two classifiers are same, which are 99.32%, 100%, and 99.66%, respectively for the BCI competition dataset IVa and 100%, 100%, and 100%, for the BCI competition dataset IVb. The results also indicate the proposed methods outperform the most recently reported methods by at least 0.25% average accuracy improvement in dataset IVa. The execution time

Experience improves feature extraction in Drosophila.

PubMed

Peng, Yueqing; Xi, Wang; Zhang, Wei; Zhang, Ke; Guo, Aike

2007-05-09

Previous exposure to a pattern in the visual scene can enhance subsequent recognition of that pattern in many species from honeybees to humans. However, whether previous experience with a visual feature of an object, such as color or shape, can also facilitate later recognition of that particular feature from multiple visual features is largely unknown. Visual feature extraction is the ability to select the key component from multiple visual features. Using a visual flight simulator, we designed a novel protocol for visual feature extraction to investigate the effects of previous experience on visual reinforcement learning in Drosophila. We found that, after conditioning with a visual feature of objects among combinatorial shape-color features, wild-type flies exhibited poor ability to extract the correct visual feature. However, the ability for visual feature extraction was greatly enhanced in flies trained previously with that visual feature alone. Moreover, we demonstrated that flies might possess the ability to extract the abstract category of "shape" but not a particular shape. Finally, this experience-dependent feature extraction is absent in flies with defective MBs, one of the central brain structures in Drosophila. Our results indicate that previous experience can enhance visual feature extraction in Drosophila and that MBs are required for this experience-dependent visual cognition.

Multisensor-based real-time quality monitoring by means of feature extraction, selection and modeling for Al alloy in arc welding

NASA Astrophysics Data System (ADS)

Zhang, Zhifen; Chen, Huabin; Xu, Yanling; Zhong, Jiyong; Lv, Na; Chen, Shanben

2015-08-01

Multisensory data fusion-based online welding quality monitoring has gained increasing attention in intelligent welding process. This paper mainly focuses on the automatic detection of typical welding defect for Al alloy in gas tungsten arc welding (GTAW) by means of analzing arc spectrum, sound and voltage signal. Based on the developed algorithms in time and frequency domain, 41 feature parameters were successively extracted from these signals to characterize the welding process and seam quality. Then, the proposed feature selection approach, i.e., hybrid fisher-based filter and wrapper was successfully utilized to evaluate the sensitivity of each feature and reduce the feature dimensions. Finally, the optimal feature subset with 19 features was selected to obtain the highest accuracy, i.e., 94.72% using established classification model. This study provides a guideline for feature extraction, selection and dynamic modeling based on heterogeneous multisensory data to achieve a reliable online defect detection system in arc welding.

New Features for Neuron Classification.

PubMed

Hernández-Pérez, Leonardo A; Delgado-Castillo, Duniel; Martín-Pérez, Rainer; Orozco-Morales, Rubén; Lorenzo-Ginori, Juan V

2018-04-28

This paper addresses the problem of obtaining new neuron features capable of improving results of neuron classification. Most studies on neuron classification using morphological features have been based on Euclidean geometry. Here three one-dimensional (1D) time series are derived from the three-dimensional (3D) structure of neuron instead, and afterwards a spatial time series is finally constructed from which the features are calculated. Digitally reconstructed neurons were separated into control and pathological sets, which are related to three categories of alterations caused by epilepsy, Alzheimer's disease (long and local projections), and ischemia. These neuron sets were then subjected to supervised classification and the results were compared considering three sets of features: morphological, features obtained from the time series and a combination of both. The best results were obtained using features from the time series, which outperformed the classification using only morphological features, showing higher correct classification rates with differences of 5.15, 3.75, 5.33% for epilepsy and Alzheimer's disease (long and local projections) respectively. The morphological features were better for the ischemia set with a difference of 3.05%. Features like variance, Spearman auto-correlation, partial auto-correlation, mutual information, local minima and maxima, all related to the time series, exhibited the best performance. Also we compared different evaluators, among which ReliefF was the best ranked.

Improving Naive Bayes with Online Feature Selection for Quick Adaptation to Evolving Feature Usefulness

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

Pon, R K; Cardenas, A F; Buttler, D J

The definition of what makes an article interesting varies from user to user and continually evolves even for a single user. As a result, for news recommendation systems, useless document features can not be determined a priori and all features are usually considered for interestingness classification. Consequently, the presence of currently useless features degrades classification performance [1], particularly over the initial set of news articles being classified. The initial set of document is critical for a user when considering which particular news recommendation system to adopt. To address these problems, we introduce an improved version of the naive Bayes classifiermore » with online feature selection. We use correlation to determine the utility of each feature and take advantage of the conditional independence assumption used by naive Bayes for online feature selection and classification. The augmented naive Bayes classifier performs 28% better than the traditional naive Bayes classifier in recommending news articles from the Yahoo! RSS feeds.« less

Reduction of Marine Magnetic Data for Modeling the Main Field of the Earth

NASA Technical Reports Server (NTRS)

Baldwin, R. T.; Ridgway, J. R.; Davis, W. M.

1992-01-01

The marine data set archived at the National Geophysical Data Center (NGDC) consists of shipborne surveys conducted by various institutes worldwide. This data set spans four decades (1953, 1958, 1960-1987), and contains almost 13 million total intensity observations. These are often less than 1 km apart. These typically measure seafloor spreading anomalies with amplitudes of several hundred nanotesla (nT) which, since they originate in the crust, interfere with main field modeling. The source for these short wavelength features are confined within the magnetic crust (i.e., sources above the Curie isotherm). The main field, on the other hand, is of much longer wavelengths and originates within the earth's core. It is desirable to extract the long wavelength information from the marine data set for use in modeling the main field. This can be accomplished by averaging the data along the track. In addition, those data which are measured during periods of magnetic disturbance can be identified and eliminated. Thus, it should be possible to create a data set which has worldwide data distribution, spans several decades, is not contaminated with short wavelengths of the crustal field or with magnetic storm noise, and which is limited enough in size to be manageable for the main field modeling. The along track filtering described above has proved to be an effective means of condensing large numbers of shipborne magnetic data into a manageable and meaningful data set for main field modeling. Its simplicity and ability to adequately handle varying spatial and sampling constraints has outweighed consideration of more sophisticated approaches. This filtering technique also provides the benefits of smoothing out short wavelength crustal anomalies, discarding data recorded during magnetically noisy periods, and assigning reasonable error estimates to be used in the least square modeling. A useful data set now exists which spans 1953-1987.

Detection of acute lymphocyte leukemia using k-nearest neighbor algorithm based on shape and histogram features

NASA Astrophysics Data System (ADS)

Purwanti, Endah; Calista, Evelyn

2017-05-01

Leukemia is a type of cancer which is caused by malignant neoplasms in leukocyte cells. Leukemia disease which can cause death quickly enough for the sufferer is a type of acute lymphocyte leukemia (ALL). In this study, we propose automatic detection of lymphocyte leukemia through classification of lymphocyte cell images obtained from peripheral blood smear single cell. There are two main objectives in this study. The first is to extract featuring cells. The second objective is to classify the lymphocyte cells into two classes, namely normal and abnormal lymphocytes. In conducting this study, we use combination of shape feature and histogram feature, and the classification algorithm is k-nearest Neighbour with k variation is 1, 3, 5, 7, 9, 11, 13, and 15. The best level of accuracy, sensitivity, and specificity in this study are 90%, 90%, and 90%, and they were obtained from combined features of area-perimeter-mean-standard deviation with k=7.

Webcam classification using simple features

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features

PubMed Central

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B.; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes. PMID:28731430

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features.

PubMed

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.

Morphological and immunohistochemical features of Cryptosporidium andersoni in cattle.

PubMed

Masuno, K; Yanai, T; Hirata, A; Yonemaru, K; Sakai, H; Satoh, M; Masegi, T; Nakai, Y

2006-03-01

Light and electron microscopic features and immunohistochemical features of Cryptosporidium andersoni (C. andersoni) and host reaction in the mucosa were studied. Although the affected cattle demonstrated no apparent clinical signs, a severe infection of C. andersoni was observed in the abomasum. C. andersoni were round in shape, measured 6-8 microm in size and were mainly observed to be freely located in the gastric pits, being attached in occasional cases to the surface of the abomasum epithelium. Frequent inflammatory cells had infiltrated the lamina propria of the affected mucosa, and frequent mitotic figures were observed in epithelial cells at the dilated isthmus. To access the cell kinetics, the number of epithelial cells infected with C. andersoni were counted and compared with noninfected cattle. The number of gastric pit cells in infected cattle was significantly higher than that in the controls. The number of proliferative cells determined by the Ki-67 antigen in C. andersoni infected cattle was also significantly higher than that in the controls. Transmission electron microscopy and scanning electron microscopy revealed that the morphology of the C. andersoni organism was common to those of other Cryptosporidium spp. Immunohistochemically, several commercial antibodies against Cryptosporidium spp. showed positive reactions at the wall of these oocysts or parasitophorous vacuoles. This report is possibly the first to discuss the prominent hyperplasia of the abomasum mucosa, as well as morphologic features of C. andersoni in cattle.

Major depression with psychotic features

MedlinePlus

... this page: //medlineplus.gov/ency/article/000933.htm Major depression with psychotic features To use the sharing features on this page, please enable JavaScript. Major depression with psychotic features is a mental disorder in ...

Investigations on the 1.7 micron residual absorption feature in the vegetation reflection spectrum

NASA Technical Reports Server (NTRS)

Verdebout, J.; Jacquemoud, S.; Andreoli, G.; Hosgood, B.; Sieber, A.

1993-01-01

The detection and interpretation of the weak absorption features associated with the biochemical components of vegetation is of great potential interest to a variety of applications ranging from classification to global change studies. This recent subject is also challenging because the spectral signature of the biochemicals is only detectable as a small distortion of the infrared spectrum which is mainly governed by water. Furthermore, the interpretation is complicated by complexity of the molecules (lignin, cellulose, starch, proteins) which contain a large number of different and common chemical bonds. In this paper, we present investigations on the absorption feature centered at 1.7 micron; these were conducted both on AVIRIS data and laboratory reflectance spectra of leaves.

Identifying Key Features of Student Performance in Educational Video Games and Simulations through Cluster Analysis

ERIC Educational Resources Information Center

Kerr, Deirdre; Chung, Gregory K. W. K.

2012-01-01

The assessment cycle of "evidence-centered design" (ECD) provides a framework for treating an educational video game or simulation as an assessment. One of the main steps in the assessment cycle of ECD is the identification of the key features of student performance. While this process is relatively simple for multiple choice tests, when…

A signal-detection-based diagnostic-feature-detection model of eyewitness identification.

PubMed

Wixted, John T; Mickes, Laura

2014-04-01

The theoretical understanding of eyewitness identifications made from a police lineup has long been guided by the distinction between absolute and relative decision strategies. In addition, the accuracy of identifications associated with different eyewitness memory procedures has long been evaluated using measures like the diagnosticity ratio (the correct identification rate divided by the false identification rate). Framed in terms of signal-detection theory, both the absolute/relative distinction and the diagnosticity ratio are mainly relevant to response bias while remaining silent about the key issue of diagnostic accuracy, or discriminability (i.e., the ability to tell the difference between innocent and guilty suspects in a lineup). Here, we propose a signal-detection-based model of eyewitness identification, one that encourages the use of (and helps to conceptualize) receiver operating characteristic (ROC) analysis to measure discriminability. Recent ROC analyses indicate that the simultaneous presentation of faces in a lineup yields higher discriminability than the presentation of faces in isolation, and we propose a diagnostic feature-detection hypothesis to account for that result. According to this hypothesis, the simultaneous presentation of faces allows the eyewitness to appreciate that certain facial features (viz., those that are shared by everyone in the lineup) are non-diagnostic of guilt. To the extent that those non-diagnostic features are discounted in favor of potentially more diagnostic features, the ability to discriminate innocent from guilty suspects will be enhanced.

Feature Selection Methods for Robust Decoding of Finger Movements in a Non-human Primate

PubMed Central

Padmanaban, Subash; Baker, Justin; Greger, Bradley

2018-01-01

Objective: The performance of machine learning algorithms used for neural decoding of dexterous tasks may be impeded due to problems arising when dealing with high-dimensional data. The objective of feature selection algorithms is to choose a near-optimal subset of features from the original feature space to improve the performance of the decoding algorithm. The aim of our study was to compare the effects of four feature selection techniques, Wilcoxon signed-rank test, Relative Importance, Principal Component Analysis (PCA), and Mutual Information Maximization on SVM classification performance for a dexterous decoding task. Approach: A nonhuman primate (NHP) was trained to perform small coordinated movements—similar to typing. An array of microelectrodes was implanted in the hand area of the motor cortex of the NHP and used to record action potentials (AP) during finger movements. A Support Vector Machine (SVM) was used to classify which finger movement the NHP was making based upon AP firing rates. We used the SVM classification to examine the functional parameters of (i) robustness to simulated failure and (ii) longevity of classification. We also compared the effect of using isolated-neuron and multi-unit firing rates as the feature vector supplied to the SVM. Main results: The average decoding accuracy for multi-unit features and single-unit features using Mutual Information Maximization (MIM) across 47 sessions was 96.74 ± 3.5% and 97.65 ± 3.36% respectively. The reduction in decoding accuracy between using 100% of the features and 10% of features based on MIM was 45.56% (from 93.7 to 51.09%) and 4.75% (from 95.32 to 90.79%) for multi-unit and single-unit features respectively. MIM had best performance compared to other feature selection methods. Significance: These results suggest improved decoding performance can be achieved by using optimally selected features. The results based on clinically relevant performance metrics also suggest that the decoding

Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Huang, Xin; Chen, Huijun; Gong, Jianya

2018-01-01

Spaceborne multi-angle images with a high-resolution are capable of simultaneously providing spatial details and three-dimensional (3D) information to support detailed and accurate classification of complex urban scenes. In recent years, satellite-derived digital surface models (DSMs) have been increasingly utilized to provide height information to complement spectral properties for urban classification. However, in such a way, the multi-angle information is not effectively exploited, which is mainly due to the errors and difficulties of the multi-view image matching and the inaccuracy of the generated DSM over complex and dense urban scenes. Therefore, it is still a challenging task to effectively exploit the available angular information from high-resolution multi-angle images. In this paper, we investigate the potential for classifying urban scenes based on local angular properties characterized from high-resolution ZY-3 multi-view images. Specifically, three categories of angular difference features (ADFs) are proposed to describe the angular information at three levels (i.e., pixel, feature, and label levels): (1) ADF-pixel: the angular information is directly extrapolated by pixel comparison between the multi-angle images; (2) ADF-feature: the angular differences are described in the feature domains by comparing the differences between the multi-angle spatial features (e.g., morphological attribute profiles (APs)). (3) ADF-label: label-level angular features are proposed based on a group of urban primitives (e.g., buildings and shadows), in order to describe the specific angular information related to the types of primitive classes. In addition, we utilize spatial-contextual information to refine the multi-level ADF features using superpixel segmentation, for the purpose of alleviating the effects of salt-and-pepper noise and representing the main angular characteristics within a local area. The experiments on ZY-3 multi-angle images confirm that the proposed

The Influence of the Orbital Evolution of Main Belt Asteroids on Their Spin Vectors

NASA Astrophysics Data System (ADS)

Skoglöv, E.; Erikson, A.

2002-11-01

It was found that certain features in the observed spin vector distribution of main belt asteroids can be explained by the differences in the dynamical spin vector evolution between objects with high and low orbital inclinations. In particular, the deficiency of high-inclination objects whose spin vectors are close to the ecliptic plane can be accounted for. The present spin vector distribution of main belt asteroids is due to several factors connected with their collisional and dynamical evolution. In this paper, the influence of the orbital evolution on the spin axis of asteroids is examined in the case of 25 objects with typical main belt orbital evolution and 125 synthetic objects, during an integration over a time period of 1 Myr. This investigation produced the following general results: • The difference between maximum and minimum obliquity increases in an approximately linear fashion with increasing orbital inclination of the studied objects. • The inclination is the major factor influencing the magnitude of the obliquity variation. This variation is generally larger for asteroids with their initial spin vectors located close to the orbital plane. • In general, the regular obliquity differences are relatively insensitive to differences in the shape, composition, and spin rate of the asteroids. The result is compared with the properties of the observed spin vectors for 73 main belt asteroids and good agreement is found between the above results and the existing spin vector distribution.

Feature confirmation in object perception: Feature integration theory 26 years on from the Treisman Bartlett lecture.

PubMed

Humphreys, Glyn W

2016-10-01

The Treisman Bartlett lecture, reported in the Quarterly Journal of Experimental Psychology in 1988, provided a major overview of the feature integration theory of attention. This has continued to be a dominant account of human visual attention to this day. The current paper provides a summary of the work reported in the lecture and an update on critical aspects of the theory as applied to visual object perception. The paper highlights the emergence of findings that pose significant challenges to the theory and which suggest that revisions are required that allow for (a) several rather than a single form of feature integration, (b) some forms of feature integration to operate preattentively, (c) stored knowledge about single objects and interactions between objects to modulate perceptual integration, (d) the application of feature-based inhibition to object files where visual features are specified, which generates feature-based spreading suppression and scene segmentation, and (e) a role for attention in feature confirmation rather than feature integration in visual selection. A feature confirmation account of attention in object perception is outlined.

Automated Feature Identification and Classification Using Automated Feature Weighted Self Organizing Map (FWSOM)

NASA Astrophysics Data System (ADS)

Starkey, Andrew; Usman Ahmad, Aliyu; Hamdoun, Hassan

2017-10-01

This paper investigates the application of a novel method for classification called Feature Weighted Self Organizing Map (FWSOM) that analyses the topology information of a converged standard Self Organizing Map (SOM) to automatically guide the selection of important inputs during training for improved classification of data with redundant inputs, examined against two traditional approaches namely neural networks and Support Vector Machines (SVM) for the classification of EEG data as presented in previous work. In particular, the novel method looks to identify the features that are important for classification automatically, and in this way the important features can be used to improve the diagnostic ability of any of the above methods. The paper presents the results and shows how the automated identification of the important features successfully identified the important features in the dataset and how this results in an improvement of the classification results for all methods apart from linear discriminatory methods which cannot separate the underlying nonlinear relationship in the data. The FWSOM in addition to achieving higher classification accuracy has given insights into what features are important in the classification of each class (left and right-hand movements), and these are corroborated by already published work in this area.

33 CFR 334.20 - Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 3 2013-07-01 2013-07-01 false Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area. 334.20 Section 334.20 Navigation and Navigable Waters... REGULATIONS § 334.20 Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area. (a) The...

33 CFR 334.20 - Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 3 2011-07-01 2011-07-01 false Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area. 334.20 Section 334.20 Navigation and Navigable Waters... REGULATIONS § 334.20 Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area. (a) The...

33 CFR 334.20 - Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 3 2014-07-01 2014-07-01 false Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area. 334.20 Section 334.20 Navigation and Navigable Waters... REGULATIONS § 334.20 Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area. (a) The...

33 CFR 334.20 - Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 3 2010-07-01 2010-07-01 false Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area. 334.20 Section 334.20 Navigation and Navigable Waters... REGULATIONS § 334.20 Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area. (a) The...

33 CFR 334.20 - Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 3 2012-07-01 2012-07-01 false Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area. 334.20 Section 334.20 Navigation and Navigable Waters... REGULATIONS § 334.20 Gulf of Maine off Cape Small, Maine; naval aircraft practice mining range area. (a) The...

Mining Feature of Data Fusion in the Classification of Beer Flavor Information Using E-Tongue and E-Nose

PubMed Central

Men, Hong; Shi, Yan; Fu, Songlin; Jiao, Yanan; Qiao, Yu; Liu, Jingjing

2017-01-01

Multi-sensor data fusion can provide more comprehensive and more accurate analysis results. However, it also brings some redundant information, which is an important issue with respect to finding a feature-mining method for intuitive and efficient analysis. This paper demonstrates a feature-mining method based on variable accumulation to find the best expression form and variables’ behavior affecting beer flavor. First, e-tongue and e-nose were used to gather the taste and olfactory information of beer, respectively. Second, principal component analysis (PCA), genetic algorithm-partial least squares (GA-PLS), and variable importance of projection (VIP) scores were applied to select feature variables of the original fusion set. Finally, the classification models based on support vector machine (SVM), random forests (RF), and extreme learning machine (ELM) were established to evaluate the efficiency of the feature-mining method. The result shows that the feature-mining method based on variable accumulation obtains the main feature affecting beer flavor information, and the best classification performance for the SVM, RF, and ELM models with 96.67%, 94.44%, and 98.33% prediction accuracy, respectively. PMID:28753917

A study of severe storm electricity via storm intercept

NASA Technical Reports Server (NTRS)

Arnold, Roy T.; Horsburgh, Steven D.; Rust, W. David; Burgess, Don

1985-01-01

Storm electricity data, radar data, and visual observations were used both to present a case study for a supercell thunderstorm that occurred in the Texas Panhandle on 19 June 1980 and to search for insight into how lightning to ground might be related to storm dynamics in the updraft/downdraft couplet in supercell storms. It was observed that two-thirds of the lightning ground-strike points in the developing and maturing stages of a supercell thunderstorm occurred within the region surrounding the wall cloud (a cloud feature often characteristic of a supercell updraft) and on the southern flank of the precipitation. Electrical activity in the 19 June 1980 storm was atypical in that it was a right-mover. Lightning to ground reached a peak rate of 18/min and intracloud flashes were as frequent as 176/min in the final stages of the storm's life.

Feature-based interference from unattended visual field during attentional tracking in younger and older adults.

PubMed

Störmer, Viola S; Li, Shu-Chen; Heekeren, Hauke R; Lindenberger, Ulman

2011-02-01

The ability to attend to multiple objects that move in the visual field is important for many aspects of daily functioning. The attentional capacity for such dynamic tracking, however, is highly limited and undergoes age-related decline. Several aspects of the tracking process can influence performance. Here, we investigated effects of feature-based interference from distractor objects that appear in unattended regions of the visual field with a hemifield-tracking task. Younger and older participants performed an attentional tracking task in one hemifield while distractor objects were concurrently presented in the unattended hemifield. Feature similarity between objects in the attended and unattended hemifields as well as motion speed and the number of to-be-tracked objects were parametrically manipulated. The results show that increasing feature overlap leads to greater interference from the unattended visual field. This effect of feature-based interference was only present in the slow speed condition, indicating that the interference is mainly modulated by perceptual demands. High-performing older adults showed a similar interference effect as younger adults, whereas low-performing adults showed poor tracking performance overall.

Complex Topographic Feature Ontology Patterns

USGS Publications Warehouse

Varanka, Dalia E.; Jerris, Thomas J.

2015-01-01

Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

The modern instrumentation used for monitoring and controlling the main parameters of the regenerative electro-mechano-hydraulic drive systems

NASA Astrophysics Data System (ADS)

Cristescu, Corneliu; Drumea, Petrin; Krevey, Petrica

2009-01-01

In this work is presented the modern instrumentation used for monitoring and controlling the main parameters for one regenerative drive system, used to recovering the kinetic energy of motor vehicles, lost in the braking phase, storing and using this energy in the starting or accelerating phases. Is presented a Romanian technical solution for a regenerative driving system, based on a hybrid solution containing a hydro-mechanic module and an existing thermal motor drive, all conceived as a mechatronics system. In order to monitoring and controlling the evolution of the main parameters, the system contains a series of sensors and transducers that provide the moment, rotation, temperature, flow and pressure values. The main sensors and transducers of the regenerative drive system, their principal features and tehnical conecting solutions are presented in this paper, both with the menaging electronic and informational subsystems.

Improving mass candidate detection in mammograms via feature maxima propagation and local feature selection.

PubMed

Melendez, Jaime; Sánchez, Clara I; van Ginneken, Bram; Karssemeijer, Nico

2014-08-01

Mass candidate detection is a crucial component of multistep computer-aided detection (CAD) systems. It is usually performed by combining several local features by means of a classifier. When these features are processed on a per-image-location basis (e.g., for each pixel), mismatching problems may arise while constructing feature vectors for classification, which is especially true when the behavior expected from the evaluated features is a peaked response due to the presence of a mass. In this study, two of these problems, consisting of maxima misalignment and differences of maxima spread, are identified and two solutions are proposed. The first proposed method, feature maxima propagation, reproduces feature maxima through their neighboring locations. The second method, local feature selection, combines different subsets of features for different feature vectors associated with image locations. Both methods are applied independently and together. The proposed methods are included in a mammogram-based CAD system intended for mass detection in screening. Experiments are carried out with a database of 382 digital cases. Sensitivity is assessed at two sets of operating points. The first one is the interval of 3.5-15 false positives per image (FPs/image), which is typical for mass candidate detection. The second one is 1 FP/image, which allows to estimate the quality of the mass candidate detector's output for use in subsequent steps of the CAD system. The best results are obtained when the proposed methods are applied together. In that case, the mean sensitivity in the interval of 3.5-15 FPs/image significantly increases from 0.926 to 0.958 (p < 0.0002). At the lower rate of 1 FP/image, the mean sensitivity improves from 0.628 to 0.734 (p < 0.0002). Given the improved detection performance, the authors believe that the strategies proposed in this paper can render mass candidate detection approaches based on image location classification more robust to feature

Histogram of gradient and binarized statistical image features of wavelet subband-based palmprint features extraction

NASA Astrophysics Data System (ADS)

Attallah, Bilal; Serir, Amina; Chahir, Youssef; Boudjelal, Abdelwahhab

2017-11-01

Palmprint recognition systems are dependent on feature extraction. A method of feature extraction using higher discrimination information was developed to characterize palmprint images. In this method, two individual feature extraction techniques are applied to a discrete wavelet transform of a palmprint image, and their outputs are fused. The two techniques used in the fusion are the histogram of gradient and the binarized statistical image features. They are then evaluated using an extreme learning machine classifier before selecting a feature based on principal component analysis. Three palmprint databases, the Hong Kong Polytechnic University (PolyU) Multispectral Palmprint Database, Hong Kong PolyU Palmprint Database II, and the Delhi Touchless (IIDT) Palmprint Database, are used in this study. The study shows that our method effectively identifies and verifies palmprints and outperforms other methods based on feature extraction.

GridMass: a fast two-dimensional feature detection method for LC/MS.

PubMed

Treviño, Victor; Yañez-Garza, Irma-Luz; Rodriguez-López, Carlos E; Urrea-López, Rafael; Garza-Rodriguez, Maria-Lourdes; Barrera-Saldaña, Hugo-Alberto; Tamez-Peña, José G; Winkler, Robert; Díaz de-la-Garza, Rocío-Isabel

2015-01-01

One of the initial and critical procedures for the analysis of metabolomics data using liquid chromatography and mass spectrometry is feature detection. Feature detection is the process to detect boundaries of the mass surface from raw data. It consists of detected abundances arranged in a two-dimensional (2D) matrix of mass/charge and elution time. MZmine 2 is one of the leading software environments that provide a full analysis pipeline for these data. However, the feature detection algorithms provided in MZmine 2 are based mainly on the analysis of one-dimension at a time. We propose GridMass, an efficient algorithm for 2D feature detection. The algorithm is based on landing probes across the chromatographic space that are moved to find local maxima providing accurate boundary estimations. We tested GridMass on a controlled marker experiment, on plasma samples, on plant fruits, and in a proteome sample. Compared with other algorithms, GridMass is faster and may achieve comparable or better sensitivity and specificity. As a proof of concept, GridMass has been implemented in Java under the MZmine 2 environment and is available at http://www.bioinformatica.mty.itesm.mx/GridMass and MASSyPup. It has also been submitted to the MZmine 2 developing community. Copyright © 2015 John Wiley & Sons, Ltd.

Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation.

PubMed

Mourad, Raphaël; Cuvier, Olivier

2016-05-01

Recent advances in long-range Hi-C contact mapping have revealed the importance of the 3D structure of chromosomes in gene expression. A current challenge is to identify the key molecular drivers of this 3D structure. Several genomic features, such as architectural proteins and functional elements, were shown to be enriched at topological domain borders using classical enrichment tests. Here we propose multiple logistic regression to identify those genomic features that positively or negatively influence domain border establishment or maintenance. The model is flexible, and can account for statistical interactions among multiple genomic features. Using both simulated and real data, we show that our model outperforms enrichment test and non-parametric models, such as random forests, for the identification of genomic features that influence domain borders. Using Drosophila Hi-C data at a very high resolution of 1 kb, our model suggests that, among architectural proteins, BEAF-32 and CP190 are the main positive drivers of 3D domain borders. In humans, our model identifies well-known architectural proteins CTCF and cohesin, as well as ZNF143 and Polycomb group proteins as positive drivers of domain borders. The model also reveals the existence of several negative drivers that counteract the presence of domain borders including P300, RXRA, BCL11A and ELK1.

Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation

PubMed Central

Mourad, Raphaël; Cuvier, Olivier

2016-01-01

Recent advances in long-range Hi-C contact mapping have revealed the importance of the 3D structure of chromosomes in gene expression. A current challenge is to identify the key molecular drivers of this 3D structure. Several genomic features, such as architectural proteins and functional elements, were shown to be enriched at topological domain borders using classical enrichment tests. Here we propose multiple logistic regression to identify those genomic features that positively or negatively influence domain border establishment or maintenance. The model is flexible, and can account for statistical interactions among multiple genomic features. Using both simulated and real data, we show that our model outperforms enrichment test and non-parametric models, such as random forests, for the identification of genomic features that influence domain borders. Using Drosophila Hi-C data at a very high resolution of 1 kb, our model suggests that, among architectural proteins, BEAF-32 and CP190 are the main positive drivers of 3D domain borders. In humans, our model identifies well-known architectural proteins CTCF and cohesin, as well as ZNF143 and Polycomb group proteins as positive drivers of domain borders. The model also reveals the existence of several negative drivers that counteract the presence of domain borders including P300, RXRA, BCL11A and ELK1. PMID:27203237

Thermal Analysis of Unusual Local-scale Features on the Surface of Vesta

NASA Technical Reports Server (NTRS)

Tosi, F.; Capria, M. T.; DeSanctis, M. C.; Capaccioni, F.; Palomba, E.; Zambon, F.; Ammannito, E.; Blewett, D. T.; Combe, J.-Ph.; Denevi, B. W.;

Celluloid angels: a research study of nurses in feature films 1900-2007.

PubMed

Stanley, David J

2008-10-01

This paper is a report of a study examining the influence on how nursing and nurses are portrayed in feature films made between 1900 and 2007, with a nurse as their main or a principle character and a story-line related specifically to nursing. Nurses and the nursing profession are frequently portrayed negatively or stereotypically in the media, with nurses often being portrayed as feminine and caring but not as leaders or professionals capable of autonomous practice. A mixed method approach was used to examine feature films made in the Western world. Over 36,000 feature film synopses were reviewed (via CINAHL, ProQuest and relevant movie-specific literature) for the keywords 'nurse'/'nursing'. Identified films were analysed quantitatively to determine their country of production, genre, plot(s) and other relevant data, and qualitatively to identify the emergence of themes related to the image of nurses/nursing in films. For the period from 1900 to 2007, 280 relevant feature films were identified. Most films were made in the United States of America or United Kingdom, although in recent years films have been increasingly produced in other countries. Early films portrayed nurses as self-sacrificial heroines, sex objects and romantics. More recent films increasingly portray them as strong and self-confident, professionals. Nurse-related films offer a unique insight into the image of nurses and how they have been portrayed. Nurses need to be aware of the impact the film industry has on how nurses and nursing are perceived and represented in feature films.

Severe dysautonomia as a main feature of anti-GAD encephalitis: Report of a paediatric case and literature review.

PubMed

Ben Achour, Nedia; Ben Younes, Thouraya; Rebai, Ibtihel; Ben Ahmed, Melika; Kraoua, Ichraf; Ben Youssef-Turki, Ilhem

2018-05-01

Anti-glutamic acid decarboxylase (anti-GAD65) antibodies are a rare cause of autoimmune encephalitis. This entity is mainly recognized in adults and very few cases were reported in children. We report on a paediatric case of anti-GAD encephalitis with severe presentation and uncontrollable dysautonomia. A 9-year-old girl was referred to our department for refractory seizures and behavioral disturbances. Brain magnetic resonance imaging (MRI) was normal. Repeat screening for antineuronal antibodies showed negative results for anti-NMDA receptor antibodies but positive results for anti-GAD65 with a low positivity of anti-Ma2 antibodies. Although a transient improvement was noticed after immunomodulatory treatment, the patient developed severe intractable autonomic imbalance including dysrythmia, alternating bradycardia/tachycardia, hypotension/hypertension, hypothermia/hyperthermia and hyperhidrosis. She deceased six months after onset. Our report intends to raise awareness of autoimmune encephalitis with anti-GAD65 antibodies which may involve extralimbic brain regions and manifest with fatal dysautonomia. We highlight the need for prompt diagnosis and aggressive management for this underdiagnosed entity in children. Copyright © 2018 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

Aqueous alteration on main belt primitive asteroids: Results from visible spectroscopy

NASA Astrophysics Data System (ADS)

Fornasier, S.; Lantz, C.; Barucci, M. A.; Lazzarin, M.

2014-05-01

This work focuses on the study of the aqueous alteration process which acted in the main belt and produced hydrated minerals on the altered asteroids. Hydrated minerals have been found mainly on Mars surface, on main belt primitive asteroids and possibly also on few TNOs. These materials have been produced by hydration of pristine anhydrous silicates during the aqueous alteration process, that, to be active, needed the presence of liquid water under low temperature conditions (below 320 K) to chemically alter the minerals. The aqueous alteration is particularly important for unraveling the processes occurring during the earliest times of the Solar System history, as it can give information both on the asteroids thermal evolution and on the localization of water sources in the asteroid belt. To investigate this process, we present reflected light spectral observations in the visible region (0.4-0.94 μm) of 80 asteroids belonging to the primitive classes C (prevalently), G, F, B and P, following the Tholen (Tholen, D.J. [1984]. Ph.D. Dissertation, University of Arizona, Tucson). classification scheme. We find that about 65% of the C-type and all the G-type asteroids investigated reveal features suggesting the presence of hydrous materials, mainly a band centered around 0.7 μm, while we do not find evidence of hydrated materials in the other low albedo asteroids (B, F, and P) investigated. We combine the present observations with the visible spectra of asteroids available in the literature for a total of 600 primitive main belt asteroids. We analyze all these spectra in a similar way to characterize the absorption band parameters (band center, depth and width) and spectral slope, and to look for possible correlations between the aqueous alteration process and the asteroids taxonomic classes, orbital elements, heliocentric distances, albedo and sizes. Our analysis shows that the aqueous alteration sequence starts from the P-type objects, practically unaltered, and

Near infrared and visible face recognition based on decision fusion of LBP and DCT features

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-03-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In order to extract the discriminative complementary features between near infrared and visible images, in this paper, we proposed a novel near infrared and visible face fusion recognition algorithm based on DCT and LBP features. Firstly, the effective features in near-infrared face image are extracted by the low frequency part of DCT coefficients and the partition histograms of LBP operator. Secondly, the LBP features of visible-light face image are extracted to compensate for the lacking detail features of the near-infrared face image. Then, the LBP features of visible-light face image, the DCT and LBP features of near-infrared face image are sent to each classifier for labeling. Finally, decision level fusion strategy is used to obtain the final recognition result. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. The experiment results show that the proposed method extracts the complementary features of near-infrared and visible face images and improves the robustness of unconstrained face recognition. Especially for the circumstance of small training samples, the recognition rate of proposed method can reach 96.13%, which has improved significantly than 92.75 % of the method based on statistical feature fusion.

A SYSTEMATIC SEARCH FOR THE SPECTRA WITH FEATURES OF CRYSTALLINE SILICATES IN THE SPITZER IRS ENHANCED PRODUCTS

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

Chen, Rui; Luo, Ali; Liu, Jiaming

2016-06-01

The crystalline silicate features are mainly reflected in infrared bands. The Spitzer Infrared Spectrograph (IRS) collected numerous spectra of various objects and provided a big database to investigate crystalline silicates in a wide range of astronomical environments. We apply the manifold ranking algorithm to perform a systematic search for the spectra with crystalline silicate features in the Spitzer IRS Enhanced Products available. In total, 868 spectra of 790 sources are found to show the features of crystalline silicates. These objects are cross-matched with the SIMBAD database as well as with the Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST)/DR2. Themore » average spectrum of young stellar objects shows a variety of features dominated either by forsterite or enstatite or neither, while the average spectrum of evolved objects consistently present dominant features of forsterite in AGB, OH/IR, post-AGB, and planetary nebulae. They are identified optically as early-type stars, evolved stars, galaxies and so on. In addition, the strength of spectral features in typical silicate complexes is calculated. The results are available through CDS for the astronomical community to further study crystalline silicates.« less

Feature Selection Has a Large Impact on One-Class Classification Accuracy for MicroRNAs in Plants.

PubMed

Yousef, Malik; Saçar Demirci, Müşerref Duygu; Khalifa, Waleed; Allmer, Jens

2016-01-01

MicroRNAs (miRNAs) are short RNA sequences involved in posttranscriptional gene regulation. Their experimental analysis is complicated and, therefore, needs to be supplemented with computational miRNA detection. Currently computational miRNA detection is mainly performed using machine learning and in particular two-class classification. For machine learning, the miRNAs need to be parametrized and more than 700 features have been described. Positive training examples for machine learning are readily available, but negative data is hard to come by. Therefore, it seems prerogative to use one-class classification instead of two-class classification. Previously, we were able to almost reach two-class classification accuracy using one-class classifiers. In this work, we employ feature selection procedures in conjunction with one-class classification and show that there is up to 36% difference in accuracy among these feature selection methods. The best feature set allowed the training of a one-class classifier which achieved an average accuracy of ~95.6% thereby outperforming previous two-class-based plant miRNA detection approaches by about 0.5%. We believe that this can be improved upon in the future by rigorous filtering of the positive training examples and by improving current feature clustering algorithms to better target pre-miRNA feature selection.

Combined effects of inversion and feature removal on N170 responses elicited by faces and car fronts.

PubMed

Kloth, Nadine; Itier, Roxane J; Schweinberger, Stefan R

2013-04-01

The face-sensitive N170 is typically enhanced for inverted compared to upright faces. Itier, Alain, Sedore, and McIntosh (2007) recently suggested that this N170 inversion effect is mainly driven by the eye region which becomes salient when the face configuration is disrupted. Here we tested whether similar effects could be observed with non-face objects that are structurally similar to faces in terms of possessing a homogeneous within-class first-order feature configuration. We presented upright and inverted pictures of intact car fronts, car fronts without lights, and isolated lights, in addition to analogous face conditions. Upright cars elicited substantial N170 responses of similar amplitude to those evoked by upright faces. In strong contrast to face conditions however, the car-elicited N170 was mainly driven by the global shape rather than the presence or absence of lights, and was dramatically reduced for isolated lights. Overall, our data confirm a differential influence of the eye region in upright and inverted faces. Results for car fronts do not suggest similar interactive encoding of eye-like features and configuration for non-face objects, even when these objects possess a similar feature configuration as faces. Copyright © 2013 Elsevier Inc. All rights reserved.

What Do We Learn from Binding Features? Evidence for Multilevel Feature Integration

ERIC Educational Resources Information Center

Colzato, Lorenza S.; Raffone, Antonino; Hommel, Bernhard

2006-01-01

Four experiments were conducted to investigate the relationship between the binding of visual features (as measured by their after-effects on subsequent binding) and the learning of feature-conjunction probabilities. Both binding and learning effects were obtained, but they did not interact. Interestingly, (shape-color) binding effects…

Virtual Observatory and Colitec Software: Modules, Features, Methods

NASA Astrophysics Data System (ADS)

Pohorelov, A. V.; Khlamov, S. V.; Savanevych, V. E.; Briukhovetskyi, A. B.; Vlasenko, V. P.

In this article we described complex processing system created by the CoLiTec project. This system includes features, user-friendly tools for processing control, results reviewing, integration with online catalogs and a lot of different computational modules that are based on the developed methods. Some of them are described in the article.The main directions of the CoLiTec software development are the Virtual Observatory, software for automated asteroids and comets detection and software for brightness equalization.The CoLiTec software is widely used in a number of observatories in the CIS. It has been used in about 700 000 observations, during which 1560 asteroids, including 5 NEO, 21 Trojan asteroids of Jupiter, 1 Centaur and four comets were discovered.

Altered cerebral blood flow velocity features in fibromyalgia patients in resting-state conditions.

PubMed

Rodríguez, Alejandro; Tembl, José; Mesa-Gresa, Patricia; Muñoz, Miguel Ángel; Montoya, Pedro; Rey, Beatriz

2017-01-01

The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envelope CBFV and a different distribution of the power spectral density. In addition, it has been observed that complexity and spectral features show correlations with clinical pain parameters and emotional factors. The characterization features were used in a lineal model to discriminate between fibromyalgia patients and healthy controls, providing a high accuracy. These findings indicate that CBFV signals, specifically their complexity and spectral characteristics, contain information that may be relevant for the assessment of fibromyalgia patients in resting-state conditions.

GATOR: Requirements capturing of telephony features

NASA Technical Reports Server (NTRS)

Dankel, Douglas D., II; Walker, Wayne; Schmalz, Mark

1992-01-01

We are developing a natural language-based, requirements gathering system called GATOR (for the GATherer Of Requirements). GATOR assists in the development of more accurate and complete specifications of new telephony features. GATOR interacts with a feature designer who describes a new feature, set of features, or capability to be implemented. The system aids this individual in the specification process by asking for clarifications when potential ambiguities are present, by identifying potential conflicts with other existing features, and by presenting its understanding of the feature to the designer. Through user interaction with a model of the existing telephony feature set, GATOR constructs a formal representation of the new, 'to be implemented' feature. Ultimately GATOR will produce a requirements document and will maintain an internal representation of this feature to aid in future design and specification. This paper consists of three sections that describe (1) the structure of GATOR, (2) POND, GATOR's internal knowledge representation language, and (3) current research issues.

Feature Inference Learning and Eyetracking

ERIC Educational Resources Information Center

Rehder, Bob; Colner, Robert M.; Hoffman, Aaron B.

2009-01-01

Besides traditional supervised classification learning, people can learn categories by inferring the missing features of category members. It has been proposed that feature inference learning promotes learning a category's internal structure (e.g., its typical features and interfeature correlations) whereas classification promotes the learning of…

An effective method for cirrhosis recognition based on multi-feature fusion

NASA Astrophysics Data System (ADS)

Chen, Yameng; Sun, Gengxin; Lei, Yiming; Zhang, Jinpeng

2018-04-01

Liver disease is one of the main causes of human healthy problem. Cirrhosis, of course, is the critical phase during the development of liver lesion, especially the hepatoma. Many clinical cases are still influenced by the subjectivity of physicians in some degree, and some objective factors such as illumination, scale, edge blurring will affect the judgment of clinicians. Then the subjectivity will affect the accuracy of diagnosis and the treatment of patients. In order to solve the difficulty above and improve the recognition rate of liver cirrhosis, we propose a method of multi-feature fusion to obtain more robust representations of texture in ultrasound liver images, the texture features we extract include local binary pattern(LBP), gray level co-occurrence matrix(GLCM) and histogram of oriented gradient(HOG). In this paper, we firstly make a fusion of multi-feature to recognize cirrhosis and normal liver based on parallel combination concept, and the experimental results shows that the classifier is effective for cirrhosis recognition which is evaluated by the satisfying classification rate, sensitivity and specificity of receiver operating characteristic(ROC), and cost time. Through the method we proposed, it will be helpful to improve the accuracy of diagnosis of cirrhosis and prevent the development of liver lesion towards hepatoma.

Contributions of feature shapes and surface cues to the recognition of facial expressions.

PubMed

Sormaz, Mladen; Young, Andrew W; Andrews, Timothy J

2016-10-01

Theoretical accounts of face processing often emphasise feature shapes as the primary visual cue to the recognition of facial expressions. However, changes in facial expression also affect the surface properties of the face. In this study, we investigated whether this surface information can also be used in the recognition of facial expression. First, participants identified facial expressions (fear, anger, disgust, sadness, happiness) from images that were manipulated such that they varied mainly in shape or mainly in surface properties. We found that the categorization of facial expression is possible in either type of image, but that different expressions are relatively dependent on surface or shape properties. Next, we investigated the relative contributions of shape and surface information to the categorization of facial expressions. This employed a complementary method that involved combining the surface properties of one expression with the shape properties from a different expression. Our results showed that the categorization of facial expressions in these hybrid images was equally dependent on the surface and shape properties of the image. Together, these findings provide a direct demonstration that both feature shape and surface information make significant contributions to the recognition of facial expressions. Copyright © 2016 Elsevier Ltd. All rights reserved.

33 CFR 334.10 - Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 3 2010-07-01 2010-07-01 false Gulf of Maine off Seal Island... REGULATIONS § 334.10 Gulf of Maine off Seal Island, Maine; naval aircraft bombing target area. (a) The danger zone. A circular area with a radius of 1.5 nautical miles, having its center just easterly of Seal...

Features of Red Sea Water Masses

NASA Astrophysics Data System (ADS)

Kartadikaria, Aditya; Hoteit, Ibrahim

2015-04-01

Features of Red Sea water mass can be divided into three types but best to be grouped into two different classes that are split at the potential density line σθ=27.4. The surface water (0-50 m) and the intermediate water (50-200 m) have nearly identical types of water mass. They appear as a maxima salinity layer for the water mass that has σθ > 26.0, and as a minimum salinity layer for water mass that has σθ < 26.0. These types of water masses are strongly affected by mixing that is controlled by seasonal variability, fresh water intrusion of the Gulf of Aden Intermediate Water (GAIW), and eddies variability. Two types of mixing; isopycnal and diapycnal mixing are part of important physical phenomena that explain the change of water mass in the Red Sea. The isopycnal mixing occurs at the neutral potential density line, connecting the Red Sea with its adjacent channel, the Gulf of Aden. Diapycnal mixing is found as a dominant mixing mode in the surface of the Red Sea Water and mainly due to energetic eddy activity. Density gradients, across which diapycnal mixing occurs, in the Red Sea are mainly due to large variations in salinity. The isolation of an extreme haline water mass below the thermocline contributes to the generation of the latitudinal shift and low diapycnal mixing. This finding further explains the difference of spatial kinetic mixing between the RSW and the Indian Ocean basin.

Progressive Enrichment of Stemness Features and Tumor Stromal Alterations in Multistep Hepatocarcinogenesis.

PubMed

Yoo, Jeong Eun; Kim, Young-Joo; Rhee, Hyungjin; Kim, Haeryoung; Ahn, Ei Yong; Choi, Jin Sub; Roncalli, Massimo; Park, Young Nyun

2017-01-01

Cancer stem cells (CSCs), a subset of tumor cells, contribute to an aggressive biological behavior, which is also affected by the tumor stroma. Despite the role of CSCs and the tumor stroma in hepatocellular carcinoma (HCC), features of stemness have not yet been studied in relation to tumor stromal alterations in multistep hepatocarcinogenesis. We investigated the expression status of stemness markers and tumor stromal changes in B viral carcinogenesis, which is the main etiology of HCC in Asia. Stemness features of tumoral hepatocytes (EpCAM, K19, Oct3/4, c-KIT, c-MET, and CD133), and tumor stromal cells expressing α-smooth muscle actin (α-SMA), CD68, CD163, and IL-6 were analyzed in 36 low grade dysplastic nodules (DNs), 48 high grade DNs, 30 early HCCs (eHCCs), and 51 progressed HCCs (pHCCs) by immunohistochemistry or real-time PCR. Stemness features (EpCAM and K19 in particular) were progressively acquired during hepatocarcinogenesis in combination with enrichment of stromal cells (CAFs, TAMs, IL-6+ cells). Stemness features were seen sporadically in DNs, more consistent in eHCCs, and peaked in pHCCs. Likewise, stromal cells were discernable in DNs, showed up as consistent cell densities in eHCCs and peaked in pHCCs. The stemness features and tumor stromal alterations also peaked in less differentiated or larger HCCs. In conclusion, progression of B viral multistep hepatocarcinogenesis is characterized by an enrichment of stemness features of neoplastic hepatocytes and a parallel alteration of the tumor stroma. The modulation of neoplastic hepatocytes and stromal cells was at low levels in precancerous lesions (DNs), consistently increased in incipient cancer (eHCCs) and peaked in pHCCs. Thus, in B viral hepatocarcinogenesis, interactions between CSCs and the tumor stroma, although starting early, seem to play a major role in tumor progression.

Feature recognition and detection for ancient architecture based on machine vision

NASA Astrophysics Data System (ADS)

Zou, Zheng; Wang, Niannian; Zhao, Peng; Zhao, Xuefeng

2018-03-01

Ancient architecture has a very high historical and artistic value. The ancient buildings have a wide variety of textures and decorative paintings, which contain a lot of historical meaning. Therefore, the research and statistics work of these different compositional and decorative features play an important role in the subsequent research. However, until recently, the statistics of those components are mainly by artificial method, which consumes a lot of labor and time, inefficiently. At present, as the strong support of big data and GPU accelerated training, machine vision with deep learning as the core has been rapidly developed and widely used in many fields. This paper proposes an idea to recognize and detect the textures, decorations and other features of ancient building based on machine vision. First, classify a large number of surface textures images of ancient building components manually as a set of samples. Then, using the convolution neural network to train the samples in order to get a classification detector. Finally verify its precision.

Modifiable Neighborhood Features Associated With Adolescent Homicide

PubMed Central

Culyba, Alison J.; Jacoby, Sara F.; Richmond, Therese S.; Fein, Joel A.; Hohl, Bernadette C.; Branas, Charles C.

2016-01-01

IMPORTANCE Homicide is a leading cause of adolescent mortality. To our knowledge, relatively little has been studied in terms of the association between environmental neighborhood features, such as streets, buildings, and natural surroundings, and severe violent injury among youth. OBJECTIVE To assess associations between environmental neighborhood features and adolescent homicide in order to identify targets for future place-based interventions. DESIGN, SETTING, AND PARTICIPANTS Population-based case-control study conducted in Philadelphia, Pennsylvania, from April 15, 2008, to March 31, 2014. We identified adolescents who died by homicide at 13 to 20 years of age from 2010 to 2012 while residing in Philadelphia. We used incidence-density sampling and random-digit dialing to recruit control participants ages 13 to 20 years matched on sex and indoor-outdoor location at the time of each index case participant’s homicide. EXPOSURES To obtain environmental data about modifiable features that were present in the immediate surroundings of our case and control participants, blinded field researchers used standardized techniques to photograph case and control participant outdoor locations. Photographic data were stitched together to create 360° panoramic images that were coded for 60 elements of the visible environment. MAIN OUTCOME AND MEASURE Adolescent homicide. RESULTS We enrolled 143 homicide case participants (mean [SD] age, 18.4 [1.5] years) and 155 matched control participants (mean [SD] age, 17.2 [2.1] years) who were both outdoors at the time of the homicide. In adjusted analyses, multiple features of Philadelphia streets, buildings, and natural surroundings were associated with adolescent homicide. The presence of street lighting (odds ratio [OR], 0.24; 95% CI, 0.09-0.70), illuminated walk/don’t walk signs (OR, 0.16; 95% CI, 0.03-0.92), painted marked crosswalks (OR, 0.17; 95% CI, 0.04-0.63), public transportation (OR, 0.13; 95% CI, 0.03-0.49), parks (OR

The McIntosh Archive: A solar feature database spanning four solar cycles

NASA Astrophysics Data System (ADS)

Gibson, S. E.; Malanushenko, A. V.; Hewins, I.; McFadden, R.; Emery, B.; Webb, D. F.; Denig, W. F.

2016-12-01

The McIntosh Archive consists of a set of hand-drawn solar Carrington maps created by Patrick McIntosh from 1964 to 2009. McIntosh used mainly H-alpha, He-1 10830 and photospheric magnetic measurements from both ground-based and NASA satellite observations. With these he traced coronal holes, polarity inversion lines, filaments, sunspots and plage, yielding a unique 45-year record of the features associated with the large-scale solar magnetic field. We will present the results of recent efforts to preserve and digitize this archive. Most of the original hand-drawn maps have been scanned, a method for processing these scans into digital, searchable format has been developed and streamlined, and an archival repository at NOAA's National Centers for Environmental Information (NCEI) has been created. We will demonstrate how Solar Cycle 23 data may now be accessed and how it may be utilized for scientific applications. In addition, we will discuss how this database of human-recognized features, which overlaps with the onset of high-resolution, continuous modern solar data, may act as a training set for computer feature recognition algorithms.

Reflection features in the Galactic Center and past activity of Sagittarius A*

NASA Astrophysics Data System (ADS)

Clavel, Maïca; Terrier, Regis; Goldwurm, Andrea; Morris, Mark; Jin, Chichuan; Ponti, Gabriele; Chuard, Dimitri

2016-07-01

X-ray observations carried out over the past two decades have captured an increasing number of reflection features within the molecular clouds located in the inner regions of our Galaxy. The intensity of these structures along with the correlated variations which are detected over the entire central molecular zone are strong evidence that this diffuse emission is created by the past activity of the supermassive black hole at the Galactic center, Sagittarius A*. In particular, within the last centuries, Sgr A* is likely to have experienced several short outbursts during which the black hole was at least a million times brighter than today. However, the precise description of the corresponding past catastrophic events is difficult to assess, mainly because the properties of the reflection features that they create while propagating away from Sgr A* depend on the line-of-sight distance, the geometry, and the size of the reflecting clouds, all of which are poorly known. I will review the different attempts to reconstruct Sgr A*'s past activity from the constraints obtained through the observation of the reflection features in the Galactic center, including the current Chandra monitoring.

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

PubMed

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

Enhancement of the Feature Extraction Capability in Global Damage Detection Using Wavelet Theory

NASA Technical Reports Server (NTRS)

Saleeb, Atef F.; Ponnaluru, Gopi Krishna

2006-01-01

The main objective of this study is to assess the specific capabilities of the defect energy parameter technique for global damage detection developed by Saleeb and coworkers. The feature extraction is the most important capability in any damage-detection technique. Features are any parameters extracted from the processed measurement data in order to enhance damage detection. The damage feature extraction capability was studied extensively by analyzing various simulation results. The practical significance in structural health monitoring is that the detection at early stages of small-size defects is always desirable. The amount of changes in the structure's response due to these small defects was determined to show the needed level of accuracy in the experimental methods. The arrangement of fine/extensive sensor network to measure required data for the detection is an "unlimited" ability, but there is a difficulty to place extensive number of sensors on a structure. Therefore, an investigation was conducted using the measurements of coarse sensor network. The white and the pink noises, which cover most of the frequency ranges that are typically encountered in the many measuring devices used (e.g., accelerometers, strain gauges, etc.) are added to the displacements to investigate the effect of noisy measurements in the detection technique. The noisy displacements and the noisy damage parameter values are used to study the signal feature reconstruction using wavelets. The enhancement of the feature extraction capability was successfully achieved by the wavelet theory.

Sloshing in the Liquid Hydrogen and Liquid Oxygen Propellant Tanks After Main Engine Cut Off

NASA Technical Reports Server (NTRS)

Kim, Sura; West, Jeff

2011-01-01

NASA Marshall Space Flight Center is designing and developing the Main Propulsion System (MPS) for Ares launch vehicles. Propellant sloshing in the liquid hydrogen (LH2) and liquid oxygen (LO2) propellant tanks after Main Engine Cut Off (MECO) was modeled using the Volume of Fluid (VOF) module of the computational fluid dynamics code, CFD-ACE+. The present simulation shows that there is substantial sloshing side forces acting on the LH2 tank during the deceleration of the vehicle after MECO. The LH2 tank features a side wall drain pipe. The side loads result from the residual propellant mass motion in the LH2 tank which is initiated by the stop of flow into the drain pipe at MECO. The simulations show that radial force on the LH2 tank wall is less than 50 lbf and the radial moment calculated based up through the center of gravity of the vehicle is predicted to be as high as 300 lbf-ft. The LO2 tank features a bottom dome drain system and is equipped with sloshing baffles. The remaining LO2 in the tank slowly forms a liquid column along the centerline of tank under the zero gravity environments. The radial force on the LO2 tank wall is predicted to be less than 100 lbf. The radial moment calculated based on the center of gravity of the vehicle is predicted as high as 4500 lbf-ft just before MECO and dropped down to near zero after propellant draining stopped completely.

Hypothesis testing for differentially correlated features.

PubMed

Sheng, Elisa; Witten, Daniela; Zhou, Xiao-Hua

2016-10-01

In a multivariate setting, we consider the task of identifying features whose correlations with the other features differ across conditions. Such correlation shifts may occur independently of mean shifts, or differences in the means of the individual features across conditions. Previous approaches for detecting correlation shifts consider features simultaneously, by computing a correlation-based test statistic for each feature. However, since correlations involve two features, such approaches do not lend themselves to identifying which feature is the culprit. In this article, we instead consider a serial testing approach, by comparing columns of the sample correlation matrix across two conditions, and removing one feature at a time. Our method provides a novel perspective and favorable empirical results compared with competing approaches. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

IMPROVEMENT OF WATER MAIN INSPECTION TECHNOLOGY

EPA Science Inventory

This document is a handout of a slide presentation that addresses improvement of water main inspection technology. The slide presentation addresses the need for improved inspection technology (e.g., 237,000 main breaks/yr); the limits on main break prevention; and, the adverse ...

Escalator Design Features Evaluation

DOT National Transportation Integrated Search

1982-05-01

This study provides an evaluation of the effectiveness of several special design features associated with escalators in rail transit systems. The objective of the study was to evaluate the effectiveness of three escalator design features: (1) mat ope...

Small Main-Belt Asteroid Lightcurve Survey

NASA Technical Reports Server (NTRS)

Binzel, Richard P.; Xu, Shui; Bus, Schelte J.; Bowell, Edward

1992-01-01

The Small Main-Belt Asteroid Lightcurve Survey is the first to measure main-belt asteroid lightcurve properties for bodies with diameters smaller than 5 km. Attention is given to CCD lightcurves for 32 small main-belt asteroids. The objects of this sample have a mean rotational frequency which is faster than that of larger main-belt asteroids. All lightcurves were investigated for nonperiodic variations ascribable to free precession; no conclusive detection of this phenomenon has been made, however.

Effective and extensible feature extraction method using genetic algorithm-based frequency-domain feature search for epileptic EEG multiclassification

PubMed Central

Wen, Tingxi; Zhang, Zhongnan

2017-01-01

Abstract In this paper, genetic algorithm-based frequency-domain feature search (GAFDS) method is proposed for the electroencephalogram (EEG) analysis of epilepsy. In this method, frequency-domain features are first searched and then combined with nonlinear features. Subsequently, these features are selected and optimized to classify EEG signals. The extracted features are analyzed experimentally. The features extracted by GAFDS show remarkable independence, and they are superior to the nonlinear features in terms of the ratio of interclass distance and intraclass distance. Moreover, the proposed feature search method can search for features of instantaneous frequency in a signal after Hilbert transformation. The classification results achieved using these features are reasonable; thus, GAFDS exhibits good extensibility. Multiple classical classifiers (i.e., k-nearest neighbor, linear discriminant analysis, decision tree, AdaBoost, multilayer perceptron, and Naïve Bayes) achieve satisfactory classification accuracies by using the features generated by the GAFDS method and the optimized feature selection. The accuracies for 2-classification and 3-classification problems may reach up to 99% and 97%, respectively. Results of several cross-validation experiments illustrate that GAFDS is effective in the extraction of effective features for EEG classification. Therefore, the proposed feature selection and optimization model can improve classification accuracy. PMID:28489789

Effective and extensible feature extraction method using genetic algorithm-based frequency-domain feature search for epileptic EEG multiclassification.

PubMed

Wen, Tingxi; Zhang, Zhongnan

2017-05-01

In this paper, genetic algorithm-based frequency-domain feature search (GAFDS) method is proposed for the electroencephalogram (EEG) analysis of epilepsy. In this method, frequency-domain features are first searched and then combined with nonlinear features. Subsequently, these features are selected and optimized to classify EEG signals. The extracted features are analyzed experimentally. The features extracted by GAFDS show remarkable independence, and they are superior to the nonlinear features in terms of the ratio of interclass distance and intraclass distance. Moreover, the proposed feature search method can search for features of instantaneous frequency in a signal after Hilbert transformation. The classification results achieved using these features are reasonable; thus, GAFDS exhibits good extensibility. Multiple classical classifiers (i.e., k-nearest neighbor, linear discriminant analysis, decision tree, AdaBoost, multilayer perceptron, and Naïve Bayes) achieve satisfactory classification accuracies by using the features generated by the GAFDS method and the optimized feature selection. The accuracies for 2-classification and 3-classification problems may reach up to 99% and 97%, respectively. Results of several cross-validation experiments illustrate that GAFDS is effective in the extraction of effective features for EEG classification. Therefore, the proposed feature selection and optimization model can improve classification accuracy.

Performance comparison of phenomenology-based features to generic features for false alarm reduction in UWB SAR imagery

NASA Astrophysics Data System (ADS)

Marble, Jay A.; Gorman, John D.

1999-08-01

A feature based approach is taken to reduce the occurrence of false alarms in foliage penetrating, ultra-wideband, synthetic aperture radar data. A set of 'generic' features is defined based on target size, shape, and pixel intensity. A second set of features is defined that contains generic features combined with features based on scattering phenomenology. Each set is combined using a quadratic polynomial discriminant (QPD), and performance is characterized by generating a receiver operating characteristic (ROC) curve. Results show that the feature set containing phenomenological features improves performance against both broadside and end-on targets. Performance against end-on targets, however, is especially pronounced.

LC-IMS-MS Feature Finder

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

2013-03-07

LC-IMS-MS Feature Finder is a command line software application which searches for possible molecular ion signatures in multidimensional liquid chromatography, ion mobility spectrometry, and mass spectrometry data by clustering deisotoped peaks with similar monoisotopic mass values, charge states, elution times, and drift times. The software application includes an algorithm for detecting multiple conformations and co-eluting species in the ion mobility dimension. LC-IMS-MS Feature Finder is designed to create an output file with detected features that includes associated information about the detected features.

Distribution and Characteristics of Seafloor Seepage Features in the Active Margin Offshore of SW Taiwan

NASA Astrophysics Data System (ADS)

Chen, T. T.; Hsu, H. H.; Liu, C. S.; Su, C. C.; Paull, C. K.; Chen, Y. H.; Caress, D. W.; Gwiazda, R.; Lundsten, E. M.

2017-12-01

In the active margin offshore of southwest (SW) Taiwan, west-vergent imbricated thrusts, folds and dipping strata are the main structural features. This is also the area where gas hydrates are widely distributed beneath the seafloor. Fluids from deep strata may migrate upwards along porous dipping layers or faults and then vent out to form seafloor seepage features in many of the gas hydrate prospects. A joint survey was conducted in May 2017 using MBARI mapping AUV and miniROV to investigate the seafloor seepage features. Numerous comet-shaped depressions (CSD) are mapped along flanks of several anticlinal ridges, and four carbonate mounds around CSD are observed from the ultra-high-resolution (1-m lateral resolution) bathymetry data collected by AUV. Samples of the carbonate mounds were collected by the mini-ROV, and their mineral compositions contain dolomite and ankerite. The AUV collected chirp sonar profiles and previously collected surface ship multichannel seismic reflection profiles across these seafloor features show that potential fluid migration pathways connect free gas trapped below the base of gas hydrate stability zone and the seafloor in the vicinity of these features. Our study suggests that the CSD could be an indicator of seafloor seepage and may be distribution widely in the active margin setting.

[Research on syndrome distribution features, etiologies, and pathogeneses of Japanese encephalitis].

PubMed

Tu, Jin-Wen; Dong, Meng-Jiu; Liu, Zhi-Yong; Zhu, Qing-Jing; Zhu, Chao-Min; Li, Li; Wan, Hu; Lan, Ying; Li, Yun; Chen, Jun

2014-03-01