Erosional dynamics and morphological analysis along the southeastern Lake Ontario shoreline, New York state

International Nuclear Information System (INIS)

Covello, D.M.; Pinet, P.R.; McClennen, C.E.; Knotts, K.A.

1993-01-01

Glacial drumlins, trending near perpendicular to the southeastern shore of Lake Ontario, display two distinct forms of coastal erosion. Some drumlins are eroding into beachfront bluffs that feature amphitheater-shaped gullies with steep headwalls and moderately sloping floors, separated by narrow, resistant, steep-sided ridges. Other drumlins of similar till composition, vegetative cover, and wave exposure are eroding into bluff's characterized by steep, planar (i.e., ungullied) surfaces. Aerial photograph and topographic analyses, combines with field observations, clearly indicate that the dominant factors controlling these morphological differences are bluff height and the manner of erosional retreat. The large volume of sediments supplied to the base of high (>30 m) bluffs creates broad (≤15 m) and thick (≤2 m) colluvial terraces between the beach and bluff base. Except during severe storms, these colluvial deposits reduce or prevent wave undercutting of the cliff base and subsequent slumping of the cliff face. This results in channeling and headward erosion of the bluff faces that, in time, evolve into a deeply incensed (>10 m) gully system. In contrast, at the base of low (<20 m) bluffs, colluvial beach terraces are smaller (≤10 m broad; <0.5 m thick) or nonexistent because the rate of wave erosion exceeds the rate of sediment supply from the bluffs. Thus, the gullying effects of surface water runoff, mud flows, rain and wind attack, so influential on high bluffs, are overwhelmed by the frequency of the slumping and sliding processes, producing planar morphologies on low-lying bluffs. Drumlin bluffs of intermediate height are affected by both slumping and gullying processes, and tend to develop a quasi-planar channeled surface

Solitary eccrine syringofibroadenoma: a case report showing papillary tubular adenoma-like features

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Toshiyuki Yamamoto

2016-10-01

Full Text Available We herein describe a case showing eccrine syringofibroadenoma occurred on the dorsum of the right foot of a 46-year-old Japanese female. Histopathologic examination revealed anastomosing cords and strands of cuboidal epithelial cells extending from the epidermis to the upper dermis, with a number of well-defined ducts suggesting eccrine ductal origin. In addition, there were papillary tubular adenoma-like ductal structures lined by a few rows of epithelial cells with papillary projections into the lumen surrounded by fibrous stroma in the mid-dermis. It is of note that various histologic features showing different differentiation were seen in a single lesion of eccrine syringofibroadenoma.

Aggradational and erosional history of the Radioactive Waste Management Complex at the Idaho National Engineering Laboratory

International Nuclear Information System (INIS)

Dechert, T.V.; McDaniel, P.A.; Falen, A.L.

1994-09-01

Long-term performance of the low-level waste disposal site at the Radioactive Waste Management Complex (RWMC) is partially dependent on the stability of the land surface with respect to erosion of cover materials. This document discusses the aggradational and erosional history of the naturally occurring sediments and soils in and around the RWMC, focusing on the late-Pleistocene and Holocene epochs. Other related issues include the ages of the various deposits, the extent to which they have been altered by soil formation and other processes, their relationships to the basalt flows in the area, and the impact of human activity on the materials at the RWMC

Aggradational and erosional history of the Radioactive Waste Management Complex at the Idaho National Engineering Laboratory

Energy Technology Data Exchange (ETDEWEB)

Dechert, T.V.; McDaniel, P.A.; Falen, A.L. [Idaho Univ., Moscow, ID (United States)

1994-09-01

Long-term performance of the low-level waste disposal site at the Radioactive Waste Management Complex (RWMC) is partially dependent on the stability of the land surface with respect to erosion of cover materials. This document discusses the aggradational and erosional history of the naturally occurring sediments and soils in and around the RWMC, focusing on the late-Pleistocene and Holocene epochs. Other related issues include the ages of the various deposits, the extent to which they have been altered by soil formation and other processes, their relationships to the basalt flows in the area, and the impact of human activity on the materials at the RWMC.

Variable features on Mars. VII - Dark filamentary markings on Mars

Science.gov (United States)

Veverka, J.

1976-01-01

The paper discusses the location, variability, and possible nature of well-developed patterns of dark filamentary markings in the Mariner 9 photographic records. Although not common on Mars, the markings are concentrated in at least two areas: Depressio Hellespontica and Cerberus/Trivium Charontis. In certain localities, strong winds are required to bring these markings into prominence. The dark filamentary markings seem to be true albedo features controlled by local topography, it being unlikely that they are free linear dunes. The distinctive criss-cross pattern seen in many of the pictures suggests that jointing provides the controlling topographic grid. At this stage it cannot be inferred whether the markings are erosional or depositional in character.

Geological survey of Maryland using EREP flight data. [mining, mapping, Chesapeake Bay islands, coastal water features

Science.gov (United States)

Weaver, K. N. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Underflight photography has been used in the Baltimore County mined land inventory to determine areas of disturbed land where surface mining of sand and ground clay, or stone has taken place. Both active and abandoned pits and quarries were located. Aircraft data has been used to update cultural features of Calvert, Caroline, St. Mary's, Somerset, Talbot, and Wicomico Counties. Islands have been located and catalogued for comparison with older film and map data for erosion data. Strip mined areas are being mapped to obtain total area disturbed to aid in future mining and reclamation problems. Coastal estuarine and Atlantic Coast features are being studied to determine nearshore bedforms, sedimentary, and erosional patterns, and manmade influence on natural systems.

Analyzing post-wildfire erosional processes and topographic change using hydrologic monitoring and Structure-from-Motion photogrammetry at the storm event scale

Science.gov (United States)

Leeper, R. J.; Barth, N. C.; Gray, A. B.

2017-12-01

Hydro-geomorphic response in recently burned watersheds is highly dependent on the timing and magnitude of subsequent rainstorms. Recent advancements in surveying and monitoring techniques using Unmanned Aerial Vehicles (UAV) and Structure-from-Motion (SfM) photogrammetry can support the rapid estimation of near cm-scale topographic response of headwater catchments (ha to km2). However, surface change due to shallow erosional processes such as sheetwash and rilling remain challenging to measure at this spatial extent and the storm event scale. To address this issue, we combined repeat UAV-SfM surveys with hydrologic monitoring techniques and field investigations to characterize post-wildfire erosional processes and topographic change on a storm-by-storm basis. The Las Lomas watershed ( 15 ha) burned in the 2016 San Gabriel Complex Fire along the front range of the San Gabriel Mountains, southern California. Surveys were conducted with a consumer grade UAV; twenty-six SfM control markers; two rain gages, and two pressure transducers were installed in the watershed. The initial SfM-derived point cloud generated from 422 photos contains 258 million points; the DEM has a resolution of 2.42 cm/pixel and a point density of 17.1 pts/cm2. Rills began forming on hillslopes and minor erosion occurred within the channel network during the first low intensity storms of the rainy season. Later more intense storms resulted in substantial geomorphic change. Hydrologic data indicate that during one of the intense storms total cumulative rainfall was 58.20 mm and peak 5-min intensity was 38.4 mm/hr. Poststorm field surveys revealed evidence of debris flows, flash flooding, erosion, and fluvial aggradation in the channel network, and rill growth and gully formation on hillslopes. Analyses of the SfM models indicate erosion dominated topographic change in steep channels and on hillslopes; aggradation dominated change in low gradient channels. A contrast of 5 cm exists between field

Identification of erosional and inundation hazard zones in Ken-Betwa river linking area, India, using remote sensing and GIS.

Science.gov (United States)

Avtar, Ram; Singh, Chander Kumar; Shashtri, Satayanarayan; Mukherjee, Saumitra

2011-11-01

Ken-Betwa river link is one of the pilot projects of the Inter Linking of Rivers program of Government of India in Bundelkhand Region. It will connect the Ken and Betwa rivers through a system of dams, reservoirs, and canals to provide storage for excess rainfall during the monsoon season and avoid floods. The main objective of this study is to identify erosional and inundation prone zones of Ken-Betwa river linking site in India using remote sensing and geographic information system tools. In this study, Landsat Thematic Mapper data of year 2005, digital elevation model from the Shuttle Radar Topographic Mission, and other ancillary data were analyzed to create various thematic maps viz. geomorphology, land use/land cover, NDVI, geology, soil, drainage density, elevation, slope, and rainfall. The integrated thematic maps were used for hazard zonation. This is based on categorizing the different hydrological and geomorphological processes influencing the inundation and erosion intensity. Result shows that the southern part of the study area which lies in Panna district of Madhya Pradesh, India, is more vulnerable than the other areas.

Paleoenvironmental analyses of an organic deposit from an erosional landscape remnant, Arctic Coastal Plain of Alaska

Energy Technology Data Exchange (ETDEWEB)

Eisner, W R; Bockheim, J G; Hinkel, K M; Brown, T A; Nelson, F E; Peterson, K M; Jones, B M

2005-01-02

The dominant landscape process on the Arctic Coastal Plain of northern Alaska is the formation and drainage of thaw lakes. Lakes and drained thaw lake basins account for approximately 75% of the modern surface expression of the Barrow Peninsula. The thaw lake cycle usually obliterates lacustrine or peat sediments from previous cycles which could otherwise be used for paleoecological reconstruction of long-term landscape and vegetation changes. Several possible erosional remnants of a former topographic surface that predates the formation of the thaw lakes have been tentatively identified. These remnants are characterized by a higher elevation, a thick organic layer with very high ground ice content in the upper permafrost, and a plant community somewhat atypical of the region. Ten soil cores were collected from one site, and one core was intensively sampled for soil organic carbon content, pollen analysis, and {sup 14}C dating. The lowest level of the organic sediments represents the earliest phase of plant growth and dates to ca. 9000 cal BP. Palynological evidence indicates the presence of mesic shrub tundra (including sedge, birch, willow, and heath vegetation); and microfossil indicators point to wetter eutrophic conditions during this period. Carbon accumulation was rapid due to high net primary productivity in a relatively nutrient-rich environment. These results are interpreted as the local response to ameliorating climate during the early Holocene. The middle Holocene portion of the record contains an unconformity, indicating that between 8200 and 4200 cal BP sediments were eroded from the site, presumably in response to wind activity during a drier period centered around 4500 cal BP. The modern vegetation community of the erosional remnant was established after 4200 cal BP, and peat growth resumed. During the late Holocene, carbon accumulation rates were greatly reduced in response to the combined effects of declining productivity associated with climatic

Geomorphic evaluation of erosional stability at reclaimed surface mines in northwestern Colorado. Water Resources Investigation

International Nuclear Information System (INIS)

Elliott, J.G.

1990-01-01

The report identifies geomorphic, pedologic, vegetation, and hydrologic conditions that are associated with erosion of reclaimed surface-mined lands in northwestern Colorado. The report also presents methods for determining the appropriate values of geomorphic variables that can be manipulated during reclamation to increase erosional stability. A section on geomorphic principles associated with erosion of reclaimed land surfaces is designed for use as a primer by mine personnel and reclamation planners. The areas of interest in the study were those that were reclaimed under jurisdiction of current (1988) SMCRA reclamation regulations, yet were still affected by relatively rapid erosion rates several years after reclamation activities were completed. Geomorphic, pedologic, vegetation, and hydrologic data were collected onsite and from topographic maps. Data from reclaimed areas undergoing accelerated erosion were compared with data from reclaimed areas undergoing minimal erosion to identify conditions that controlled erosion on reclaimed surface-mined lands and to identify some postmining equilibrium landform characteristics. These data also were used to develop threshold relations

Quantifying Hillslope to Watershed Erosional Response Following Wildfire

Science.gov (United States)

Vega, S.; Pierson, F. B.; Williams, C. J.; Brooks, E. S.; Strand, E. K.; Seyfried, M. S.; Murdock, M.; Pierce, J. L.; Roehner, C.; Lindsay, K.; Robichaud, P. R.; Brown, R. E.

2017-12-01

Across the western US, wildfires in sagebrush vegetation are occurring at a more frequent rate and higher severity. This has resulted in a decline of sagebrush rangeland. The changing fire regime can be attributed to invasive plant species and warming climate conditions. As the result of wildfire, protective vegetation cover is removed leaving the soil bare and exposed to erosion. Erosion following wildfire is a main concern among land managers due to the threat it poses to resources, infrastructure, and human health. Numerous studies have used artificial rainfall to assess post-fire runoff and erosion and rehabilitation treatment effectiveness. These results have found that high intensity rain events typical of summer convective storms drive post-fire erosion. The purpose of this study is to improve scientific understanding of how site-specific physical and biological attributes affect hillslope to watershed scale sediment yield on a mountainous burned sagebrush landscape. This study uses natural rainfall and a network of silt fences to quantify hillslope to watershed scale erosion response. The erosional drivers over various spatial scales were evaluated in context with vegetation recovery for a 2 year post-fire period. A network of silt fences was installed over long and short hillslope distances and in swales within the 130 ha Murphy Creek catchment in the Reynolds Creek Experimental Watershed in southwestern Idaho. We evaluated: 1) vegetation, soils, and sediment delivery across multiple spatial scales associated with 30 silt fences spanning north and south facing aspects, 2) precipitation input at two meteorological stations, and 3) watershed streamflow and sediment discharge from an existing weir. During the first and second year post-fire, the swales on both aspects produced more sediment than the short and long hillslopes. The results suggest that significant amounts of sediment and organic matter were deposited in the swales creating drifts. Sediment

Clinicopathogical characteristics and mammographic features of breast cancer showing architectural distortion on a mammogram

International Nuclear Information System (INIS)

Kanzaki, Masao; Hirose, Naoko; Suwa, Kaori; Yoshida, Masayuki; Otuki, Yoshiro; Kobayashi, Hiroshi

2012-01-01

Seven hundred and twenty-seven cases of breast cancer were diagnosed in this clinic between January 2003 and December 2010. Of those, 97 patients who showed architectural distortion on mammography were examined regarding the clinicopathological characteristics and mammographic features. The overall rate of architectural distortion was 13.3%, which became higher with progression of the clinical stage. The rate of lymph node metastasis was 50.5% histologically, and the most common histological type was scirrhous carcinoma at 36.2%, papillotubular carcinoma at 33%, invasive lobular carcinoma at 12.1%, and ductal carcinoma in situ at 11%. Cases of extensive ductal spread beyond the breast quadrant, accompanied by microcalcifications or showing architectural distortion in two views on mammography, were present at significantly high rates. Cases showing architectural distortion in two views on mammography accounted for 66% of the total, and, when these cases were not associated with any other mammographic findings, the most suspected histology of the lesion was invasive lobular carcinoma or carcinoma in situ. (author)

Misrepresentation of hydro-erosional processes in rainfall simulations using disturbed soil samples

Science.gov (United States)

Thomaz, Edivaldo L.; Pereira, Adalberto A.

2017-06-01

Interrill erosion is a primary soil erosion process which consists of soil detachment by raindrop impact and particle transport by shallow flow. Interill erosion affects other soil erosion sub-processes, e.g., water infiltration, sealing, crusting, and rill initiation. Interrill erosion has been widely studied in laboratories, and the use of a sieved soil, i.e., disturbed soil, has become a standard method in laboratory experiments. The aims of our study are to evaluate the hydro-erosional response of undisturbed and disturbed soils in a laboratory experiment, and to quantify the extent to which hydraulic variables change during a rainstorm. We used a splash pan of 0.3 m width, 0.45 m length, and 0.1 m depth. A rainfall simulation of 58 mm h- 1 lasting for 30 min was conducted on seven replicates of undisturbed and disturbed soils. During the experiment, several hydro-physical parameters were measured, including splashed sediment, mean particle size, runoff, water infiltration, and soil moisture. We conclude that use of disturbed soil samples results in overestimation of interrill processes. Of the nine assessed parameters, four displayed greater responses in the undisturbed soil: infiltration, topsoil shear strength, mean particle size of eroded particles, and soil moisture. In the disturbed soil, five assessed parameters displayed greater responses: wash sediment, final runoff coefficient, runoff, splash, and sediment yield. Therefore, contextual soil properties are most suitable for understanding soil erosion, as well as for defining soil erodibility.

PACHE Trainee Spotlight: Roslyn Curry Featured on Thesis Thursday Radio Show

Science.gov (United States)

Roslyn Curry, a student at the University of Arizona (UA), was featured on a local radio program, Thesis Thursday, where she discussed her participation in the U54 PACHE Partnership for Native American Cancer Prevention (NACP) as a research trainee in Dr. William Montfort’s Lab at the University of Arizona Cancer Cente

Erosion and sedimentation during the September 2015 flooding of the Kinu River, central Japan.

Science.gov (United States)

Dan Matsumoto; Sawai, Yuki; Yamada, Masaki; Namegaya, Yuichi; Shinozaki, Tetsuya; Takeda, Daisuke; Fujino, Shigehiro; Tanigawa, Koichiro; Nakamura, Atsunori; Pilarczyk, Jessica E

2016-09-28

Erosional and sedimentary features associated with flooding have been documented in both modern and past cases. However, only a few studies have demonstrated the relationship between these features and the corresponding hydraulic conditions that produced them, making it difficult to evaluate the magnitude of paleo-flooding. This study describes the characteristics associated with inundation depth and flow direction, as well as the erosional and sedimentary features resulting from the disastrous flooding of the Kinu River, central Japan, in September 2015. Water levels rose rapidly due to heavy rainfall that eventually overtopped, and subsequently breached, a levee in Joso City, causing destructive flooding on the surrounding floodplain. Distinctive erosional features are found next to the breached levee, while depositional features, such as a sandy crevasse-splay deposit are found further away from the breach. The deposit can be divided into three units based on sedimentary facies. The vertical and lateral changes of these sedimentary facies may be the result of temporal and spatial changes associated with flow during the single flooding event. These observations and quantitative data provide information that can be used to reveal the paleohydrology of flood deposits in the stratigraphic record, leading to improved mitigation of future flooding disasters.

Pulmonary alveolar proteinosis versus exogenous lipoid pneumonia showing crazy-paving pattern: Comparison of their clinical features and high-resolution CT findings

Energy Technology Data Exchange (ETDEWEB)

Choi, Hei Kyung; Park, Chang Min; Goo, Jin Mo; Lee, Hyun Ju (Dept. of Radiology, Seoul National Univ. College of Medicine, and Inst. of Radiation Medicine, Seoul National Univ. Medical Research Center, Seoul (Korea)), e-mail: cmpark@radiol.snu.ac.kr

2010-05-15

Background: Although pulmonary alveolar proteinosis (PAP) and exogenous lipoid pneumonia (ELP) require different treatment strategies, both manifest as a crazy-paving pattern on CT and often have similar clinical manifestations and radiologic features. Purpose: To investigate the clinical features and high-resolution computed tomography (HRCT) findings of PAP and ELP showing the crazy-paving pattern. Material and Methods: The clinical features and HRCT findings of eight patients with pathologically proven PAP and six patients with pathologically proven ELP showing the crazy-paving pattern were retrospectively evaluated. Two radiologists analyzed the HRCT findings of PAP and ELP in consensus in terms of the presence, severity, and extent of illdefined centrilobular nodules, consolidations, ground-glass opacities (GGOs), reticulations, and the crazy-paving pattern. Results: With respect to the clinical features of these two diseases, all patients with ELP were retrospectively found to have a history of oil ingestion. In terms of the HRCT findings, ill-defined centrilobular nodules were seen in five of six patients (83%) with ELP, whereas they were not present in any patient with PAP (P=0.003). Consolidation was also more frequently present in patients with ELP (83%) than in those with PAP (11%), which was statistically different (P=0.0265). In terms of the severity and extent, the crazy-paving pattern and reticulations on HRCT were significantly more extensive and severe in patients with PAP than in those with ELP. Conclusion: PAP and ELP with the crazy-paving pattern have several distinctive characteristics with respect to their HRCT findings as well as history of oil ingestion, and can therefore be distinguished from one another

THE GEOMORPHOLOGIC FEATURES OF INTRUSIVE MAGMATIC STRUCTURES FROM BÂRGĂU MOUNTAINS (EASTERN CARPATHIANS, ROMANIA

Directory of Open Access Journals (Sweden)

Ioan Bâca

2016-08-01

Full Text Available Igneous intrusive structures from Bârgău Mountains belong to the group of central Neogene volcanic chain of the Eastern Carpathians of Romania. The evolution of the relief developed on these structures are three main stages: the stage of injection of structures (Pannonian, the stage of uncovering of igneous intrusive bodies from Oligo-Miocene sedimentary cover (Pliocene, and the stage of subaerial modeling of magmatic bodies (Pliocene-current.In those circumstances, the geodiversity of intrusive magmatic structures from Bârgău Mountains is represented by several types of landforms such as: polycyclic landforms (erosional levels, structural landforms (the configuration of igneous intrusive structures, petrographic landforms (andesites, lithological contact, fluvial landforms (valleys, slopes, ridges, periglacial landforms (cryogenic and crionival landforms, biogenic and anthropogenic landforms. This study highlights certain features of the landforms modeled on igneous intrusive bodies with the aim of developing some strategy for tourism recovery by local and county authorities.

Nonaggressive systemic mastocytosis (SM) without skin lesions associated with insect-induced anaphylaxis shows unique features versus other indolent SM.

Science.gov (United States)

Alvarez-Twose, Iván; Zanotti, Roberta; González-de-Olano, David; Bonadonna, Patrizia; Vega, Arantza; Matito, Almudena; Sánchez-Muñoz, Laura; Morgado, José Mário; Perbellini, Omar; García-Montero, Andrés; De Matteis, Giovanna; Teodósio, Cristina; Rossini, Maurizio; Jara-Acevedo, María; Schena, Donatella; Mayado, Andrea; Zamò, Alberto; Mollejo, Manuela; Sánchez-López, Paula; Cabañes, Nieves; Orfao, Alberto; Escribano, Luis

2014-02-01

Indolent systemic mastocytosis (ISM) without skin lesions (ISMs(-)) shows a higher prevalence in males, lower serum baseline tryptase levels, and KIT mutation more frequently restricted to bone marrow (BM) mast cells (MCs) than ISM with skin lesions (ISMs(+)). Interestingly, in almost one-half of ISMs(-) patients, MC-mediator release episodes are triggered exclusively by insects. We aimed to determine the clinical and laboratory features of ISMs(-) associated with insect-induced anaphylaxis (insectISMs(-)) versus other patients with ISM. A total of 335 patients presenting with MC activation syndrome, including 143 insectISMs(-), 72 ISMs(-) triggered by other factors (otherISMs(-)), 56 ISMs(+), and 64 nonclonal MC activation syndrome, were studied. Compared with otherISMs(-) and ISMs(+) patients, insectISMs(-) cases showed marked male predominance (78% vs 53% and 46%; P < .001), a distinct pattern of MC-related symptoms, and significantly lower median serum baseline tryptase levels (22.4 vs 28.7 and 45.8 μg/L; P ≤ .009). Moreover, insectISMs(-) less frequently presented BM MC aggregates (46% vs 70% and 81%; P ≤ .001), and they systematically showed MC-restricted KIT mutation. ISMs(-) patients with anaphylaxis triggered exclusively by insects display clinical and laboratory features that are significantly different from other ISM cases, including other ISMs(-) and ISMs(+) patients, suggesting that they represent a unique subgroup of ISM with a particularly low BM MC burden in the absence of adverse prognostic factors. Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

How did the AD 1755 tsunami impact on sand barriers across the southern coast of Portugal?

DEFF Research Database (Denmark)

Costa, Pedro J. M.; Costas, Susana; Gonzalez-Villanueva, R.

2016-01-01

1755 tsunami flood on a coastal segment located within the southern coast of Portugal. In particular, the work focuses on deciphering the impact of the tsunami waves over a coastal sand barrier enclosing two lowlands largely inundated by the tsunami flood. Erosional features documented by geophysical...... above mean sea level). Our work highlights the usefulness of erosional imprints preserved in the sediment record to interpret the impact of the extreme events on sand barriers....

Myofibroblasts in interstitial lung diseases show diverse electron microscopic and invasive features.

Science.gov (United States)

Karvonen, Henna M; Lehtonen, Siri T; Sormunen, Raija T; Harju, Terttu H; Lappi-Blanco, Elisa; Bloigu, Risto S; Kaarteenaho, Riitta L

2012-09-01

The characteristic features of myofibroblasts in various lung disorders are poorly understood. We have evaluated the ultrastructure and invasive capacities of myofibroblasts cultured from small volumes of diagnostic bronchoalveolar lavage (BAL) fluid samples from patients with different types of lung diseases. Cells were cultured from samples of BAL fluid collected from 51 patients that had undergone bronchoscopy and BAL for diagnostic purposes. The cells were visualized by transmission electron microscopy and immunoelectron microscopy to achieve ultrastructural localization of alpha-smooth muscle actin (α-SMA) and fibronectin. The levels of α-SMA protein and mRNA and fibronectin mRNA were measured by western blot and quantitative real-time reverse transcriptase polymerase chain reaction. The invasive capacities of the cells were evaluated. The cultured cells were either fibroblasts or myofibroblasts. The structure of the fibronexus, and the amounts of intracellular actin, extracellular fibronectin and cell junctions of myofibroblasts varied in different diseases. In electron and immunoelectron microscopy, cells cultured from interstitial lung diseases (ILDs) expressed more actin filaments and α-SMA than normal lung. The invasive capacity of the cells obtained from patients with idiopathic pulmonary fibrosis was higher than that from patients with other type of ILDs. Cells expressing more actin filaments had a higher invasion capacity. It is concluded that electron and immunoelectron microscopic studies of myofibroblasts can reveal differential features in various diseases. An analysis of myofibroblasts cultured from diagnostic BAL fluid samples may represent a new kind of tool for diagnostics and research into lung diseases.

Storage in alluvial deposits controls the timing of particle delivery from large watersheds, filtering upland erosional signals and delaying benefits from watershed best management practices

Science.gov (United States)

Pizzuto, J. E.; Skalak, K.; Karwan, D. L.

2017-12-01

Transport of suspended sediment and sediment-borne constituents (here termed fluvial particles) through large river systems can be significantly influenced by episodic storage in floodplains and other alluvial deposits. Geomorphologists quantify the importance of storage using sediment budgets, but these data alone are insufficient to determine how storage influences the routing of fluvial particles through river corridors across large spatial scales. For steady state systems, models that combine sediment budget data with "waiting time distributions" (to define how long deposited particles remain stored until being remobilized) and velocities during transport events can provide useful predictions. Limited field data suggest that waiting time distributions are well represented by power laws, extending from 104 years, while the probability of storage defined by sediment budgets varies from 0.1 km-1 for small drainage basins to 0.001 km-1 for the world's largest watersheds. Timescales of particle delivery from large watersheds are determined by storage rather than by transport processes, with most particles requiring 102 -104 years to reach the basin outlet. These predictions suggest that erosional "signals" induced by climate change, tectonics, or anthropogenic activity will be transformed by storage before delivery to the outlets of large watersheds. In particular, best management practices (BMPs) implemented in upland source areas, designed to reduce the loading of fluvial particles to estuarine receiving waters, will not achieve their intended benefits for centuries (or longer). For transient systems, waiting time distributions cannot be constant, but will vary as portions of transient sediment "pulses" enter and are later released from storage. The delivery of sediment pulses under transient conditions can be predicted by adopting the hypothesis that the probability of erosion of stored particles will decrease with increasing "age" (where age is defined as the

A prototype feature system for feature retrieval using relationships

Science.gov (United States)

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.

Long-term responses of rainforest erosional systems at different spatial scales to selective logging and climatic change

Science.gov (United States)

Walsh, R. P. D.; Bidin, K.; Blake, W. H.; Chappell, N. A.; Clarke, M. A.; Douglas, I.; Ghazali, R.; Sayer, A. M.; Suhaimi, J.; Tych, W.; Annammala, K. V.

2011-01-01

Long-term (21–30 years) erosional responses of rainforest terrain in the Upper Segama catchment, Sabah, to selective logging are assessed at slope, small and large catchment scales. In the 0.44 km2 Baru catchment, slope erosion measurements over 1990–2010 and sediment fingerprinting indicate that sediment sources 21 years after logging in 1989 are mainly road-linked, including fresh landslips and gullying of scars and toe deposits of 1994–1996 landslides. Analysis and modelling of 5–15 min stream-suspended sediment and discharge data demonstrate a reduction in storm-sediment response between 1996 and 2009, but not yet to pre-logging levels. An unmixing model using bed-sediment geochemical data indicates that 49 per cent of the 216 t km−2 a−1 2009 sediment yield comes from 10 per cent of its area affected by road-linked landslides. Fallout 210Pb and 137Cs values from a lateral bench core indicate that sedimentation rates in the 721 km2 Upper Segama catchment less than doubled with initially highly selective, low-slope logging in the 1980s, but rose 7–13 times when steep terrain was logged in 1992–1993 and 1999–2000. The need to keep steeplands under forest is emphasized if landsliding associated with current and predicted rises in extreme rainstorm magnitude-frequency is to be reduced in scale. PMID:22006973

An investigation of recent storm histories using Ground Penetrating Radar at Bay-Bay Spit, Bicol, Central Philippines

Science.gov (United States)

Switzer, Adam D.; Pile, Jeremy; Soria, Janneli Lea A.; Siringan, Fernando; Daag, Arturo; Brill, Dominik

2016-04-01

The Philippine archipelago lies in the path of seasonal tropical cyclones, and much of the coast is prone to periodic inundation and overwash during storm surges. On example is typhoon Durian a category 3 storm that made landfall on the 30th November 2006, in Bicol province, on the east central Philippine coast. Satellite imagery from May 2007 reveal that Durian breached a sandy spit that runs southeast from the mouth of the Quinale River at Bay-Bay village towards Tabaco City. The imagery also showed that, although the breach site showed signs of partial recovery, geomorphological evidence of the inundation event associated with typhoon Durian still remains. In 2012 we mapped the geomorphological features of Durian. In June 2013 we returned to conduct Ground Penetrating Radar (GPR) surveys on the Bay-Bay spit to investigate potential subsurface evidence of previous storm events. The GPR surveys comprised five, 1.5 km, longshore profiles and 12 cross-shore profiles, of 50 m - 200 m in length. The GPR system used for this study was a Sensors and Software Noggin with 100 Mhz antennas. Near surface velocities were determine using Hyperbolae matching in order to estimate depth. Topographic and positional data were collected using a dGPS system. After minimal processing depth of penetration during the survey varied from 2 - 8 m. The cross-shore GPR profiles reveal at least two erosional events prior to 2006 typhoon Durian, with approximately 10 m of recovery and progradation between each erosion surface. The GPR profiles that captured the erosional features were revisited in September 2013 for trial pitting, stratigraphic description, and sediment sampling. Sediment cores were taken horizontally from the trench walls and vertically from the trench bases to date sediments using Optically Stimulated Luminescence (OSL), which eventually could constrain the timing of the erosional surfaces.

Canyons off northwest Puerto Rico

International Nuclear Information System (INIS)

Gardner, W.D.; Glover, L.K.; Hollister, C.D.

1980-01-01

The Nuclear-Research Submarine NR-1 was used to study morphoplogy, sediment, and sediment-water interactions off the northwest coast of Puerto Rico. New detailed bathymetry from the surface-support ship, USS Portland, shows several submarine canyons in the area, some of them unreported previously. The north coast canyons, Arecibo, Tiberones and Quebradillas, are primarily erosional features although no recent turbidity-current evidence is seen. The canyons are presently filling with river-transported sediments. (orig./ME)

Analytical Features: A Knowledge-Based Approach to Audio Feature Generation

Directory of Open Access Journals (Sweden)

Pachet François

2009-01-01

Full Text Available We present a feature generation system designed to create audio features for supervised classification tasks. The main contribution to feature generation studies is the notion of analytical features (AFs, a construct designed to support the representation of knowledge about audio signal processing. We describe the most important aspects of AFs, in particular their dimensional type system, on which are based pattern-based random generators, heuristics, and rewriting rules. We show how AFs generalize or improve previous approaches used in feature generation. We report on several projects using AFs for difficult audio classification tasks, demonstrating their advantage over standard audio features. More generally, we propose analytical features as a paradigm to bring raw signals into the world of symbolic computation.

Honored Teacher Shows Commitment.

Science.gov (United States)

Ratte, Kathy

1987-01-01

Part of the acceptance speech of the 1985 National Council for the Social Studies Teacher of the Year, this article describes the censorship experience of this honored social studies teacher. The incident involved the showing of a videotape version of the feature film entitled "The Seduction of Joe Tynan." (JDH)

Cascade model for fluvial geomorphology

Science.gov (United States)

Newman, W. I.; Turcotte, D. L.

1990-01-01

Erosional landscapes are generally scale invariant and fractal. Spectral studies provide quantitative confirmation of this statement. Linear theories of erosion will not generate scale-invariant topography. In order to explain the fractal behavior of landscapes a modified Fourier series has been introduced that is the basis for a renormalization approach. A nonlinear dynamical model has been introduced for the decay of the modified Fourier series coefficients that yield a fractal spectra. It is argued that a physical basis for this approach is that a fractal (or nearly fractal) distribution of storms (floods) continually renews erosional features on all scales.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Feature displacement interpolation

DEFF Research Database (Denmark)

Nielsen, Mads; Andresen, Per Rønsholt

1998-01-01

Given a sparse set of feature matches, we want to compute an interpolated dense displacement map. The application may be stereo disparity computation, flow computation, or non-rigid medical registration. Also estimation of missing image data, may be phrased in this framework. Since the features...... often are very sparse, the interpolation model becomes crucial. We show that a maximum likelihood estimation based on the covariance properties (Kriging) show properties more expedient than methods such as Gaussian interpolation or Tikhonov regularizations, also including scale......-selection. The computational complexities are identical. We apply the maximum likelihood interpolation to growth analysis of the mandibular bone. Here, the features used are the crest-lines of the object surface....

FEATURE SELECTION METHODS BASED ON MUTUAL INFORMATION FOR CLASSIFYING HETEROGENEOUS FEATURES

Directory of Open Access Journals (Sweden)

Ratri Enggar Pawening

2016-06-01

Full Text Available Datasets with heterogeneous features can affect feature selection results that are not appropriate because it is difficult to evaluate heterogeneous features concurrently. Feature transformation (FT is another way to handle heterogeneous features subset selection. The results of transformation from non-numerical into numerical features may produce redundancy to the original numerical features. In this paper, we propose a method to select feature subset based on mutual information (MI for classifying heterogeneous features. We use unsupervised feature transformation (UFT methods and joint mutual information maximation (JMIM methods. UFT methods is used to transform non-numerical features into numerical features. JMIM methods is used to select feature subset with a consideration of the class label. The transformed and the original features are combined entirely, then determine features subset by using JMIM methods, and classify them using support vector machine (SVM algorithm. The classification accuracy are measured for any number of selected feature subset and compared between UFT-JMIM methods and Dummy-JMIM methods. The average classification accuracy for all experiments in this study that can be achieved by UFT-JMIM methods is about 84.47% and Dummy-JMIM methods is about 84.24%. This result shows that UFT-JMIM methods can minimize information loss between transformed and original features, and select feature subset to avoid redundant and irrelevant features.

VARIATION IN CROSION/DEPOSITION RATES OVER THE LAST FIFTTY YEARS ON ALLUVIAL FAN SURFACES OF L. PLEISTOCENE-MID HOLOCENE AGE, ESTIMATIONS USING 137CS SOIL PROFILE DATA, AMARGOSA VALLEY, NEVADA

International Nuclear Information System (INIS)

C. Harrington; R. Kelly; K.T. Ebert

2005-01-01

Variations in erosion and deposition for the last fifty years (based on estimates from 137Cs profiles) on surfaces (Late Pleistocene to Late Holocene in age) making up the Fortymile Wash alluvial fan south of Yucca Mountain, is a function of surface age and of desert pavement development or absence. For purposes of comparing erosion and deposition, the surfaces can be examined as three groups: (1) Late Pleistocene surfaces possess areas of desert pavement development with thin Av or sandy A horizons, formed by the trapping capabilities of the pavements. These zones of deposition are complemented by coppice dune formation on similar parts of the surface. Areas on the surface where no pavement development has occurred are erosional in nature with 0.0 +/- 0.0 cm to 1.5 +/- 0.5 cm of erosion occurring primarily by winds blowing across the surface. Overall these surfaces may show either a small net depositional gain or small erosional loss. (2) Early Holocene surfaces have no well-developed desert pavements, but may have residual gravel deposits in small areas on the surfaces. These surfaces show the most consistent erosional surface areas on which it ranges from 1.0 +/-.01 cm to 2.0+/- .01 cm. Fewer depositional forms are found on this age of surface so there is probably a net loss of 1.5 cm across these surfaces. (3) The Late Holocene surfaces show the greatest variability in erosion and deposition. Overbank deposition during floods cover many edges of these surfaces and coppice dune formation also creates depositional features. Erosion rates are highly variable and range from 0.0 +/- 0.0 to a maximum of 2.0+/-.01. Erosion occurs because of the lack of protection of the surface. However, the common areas of deposition probably result in the surface having a small net depositional gain across these surfaces. Thus, the interchannel surfaces of the Fortymile Wash fan show a variety of erosional styles as well as areas of deposition. The fan, therefore, is a dynamic

Guilt by Association: The 13 micron Dust Feature in Circumstellar Shells and Related Spectral Features

Science.gov (United States)

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.

Depositional History of the Western Amundsen Basin, Arctic Ocean, and Implications for Neogene Climate and Oceanographic Conditions

Science.gov (United States)

Hopper, J. R.; Castro, C. F.; Knutz, P. C.; Funck, T.

2017-12-01

Seismic reflection data collected in the western Amundsen Basin as part of the Law of the Sea program for the Kingdom of Denmark show a uniform and continuous cover of sediments over oceanic basement. An interpretation of seismic facies units shows that the depositional history of the basin reflects changing tectonic, climatic, and oceanographic conditions throughout the Cenozoic. In this contribution, the Miocene to present history is summarized. Two distinct changes in the depositional environment are proposed, first in response to the development of a deep water connection between the Arctic and North Atlantic, and the second in response to the onset of perennial sea ice cover in the Arctic. In the early to mid-Miocene, a buildup of contourite deposits indicates a distinct change in sedimentation that is particularly well developed near the flank of the Lomonosov Ridge. It is suggested that this is a response to the opening of the Fram Strait and the establishment of geostrophic bottom currents that flowed from the Laptev Sea towards Greenland. These deposits are overlain by a seismic facies unit characterized by buried channels and erosional features. These include prominent basinward levee systems that suggest a channel morphology maintained by overbank deposition of muddy sediments carried by suspension currents periodically spilling over the channel pathway. These deposits indicate a change to a much higher energy environment that is proposed to be a response to brine formation associated with the onset of perennial sea ice cover in the Arctic Ocean. This interpretation implies that the development of extensive sea ice cover results in a significant change in the energy environment of the ocean that is reflected in the depositional and erosional patterns observed. The lack of similar high energy erosional features and the presence of contourite deposits throughout most of the Miocene may indicate the Arctic Ocean was relatively ice-free until the very latest

Feature selection for splice site prediction: A new method using EDA-based feature ranking

Directory of Open Access Journals (Sweden)

Rouzé Pierre

2004-05-01

Full Text Available Abstract Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features.

Feature-Based Retinal Image Registration Using D-Saddle Feature

Directory of Open Access Journals (Sweden)

Roziana Ramli

2017-01-01

Full Text Available 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.

Erosional and depositional contourite features at the transition between the western Scotia Sea and southern South Atlantic Ocean: links with regional water-mass circulation since the Middle Miocene

Science.gov (United States)

Pérez, Lara F.; Hernández-Molina, F. Javier; Esteban, Federico D.; Tassone, Alejandro; Piola, Alberto R.; Maldonado, Andrés; Preu, Benedict; Violante, Roberto A.; Lodolo, Emanuele

2015-08-01

The aim of the present study was to characterise the morpho-sedimentary features and main stratigraphic stacking pattern off the Tierra del Fuego continental margin, the north-western sector of the Scotia Sea abyssal plain (Yaghan Basin) and the Malvinas/Falkland depression, based on single- and multi-channel seismic profiles. Distinct contourite features were identified within the sedimentary record from the Middle Miocene onwards. Each major drift developed in a water depth range coincident with a particular water mass, contourite terraces on top of some of these drifts being associated with interfaces between water masses. Two major palaeoceanographic changes were identified. One took place in the Middle Miocene with the onset of Antarctic Intermediate Water flow and the enhancement of Circumpolar Deep Water (CDW) flow, coevally with the onset of Weddell Sea Deep Water flow in the Scotia Sea. Another palaeoceanographic change occurred on the abyssal plain of the Yaghan Basin in the Late Miocene as a consequence of the onset of Southeast Pacific Deep Water flow and its complex interaction with the lower branch of the CDW. Interestingly, these two periods of change in bottom currents are coincident with regional tectonic episodes, as well as climate and Antarctic ice sheet oscillations. The results convincingly demonstrate that the identification of contourite features on the present-day seafloor and within the sedimentary record is the key for decoding the circulation of water masses in the past. Nevertheless, further detailed studies, especially the recovery of drill cores, are necessary to establish a more robust chronology of the evolutionary stages at the transition between the western Scotia Sea and the southern South Atlantic Ocean.

Hurricane impacts on coastal wetlands: a half-century record of storm-generated features from southern Louisiana

Science.gov (United States)

Morton, Robert A.; Barras, John A.

2011-01-01

Temporally and spatially repeated patterns of wetland erosion, deformation, and deposition are observed on remotely sensed images and in the field after hurricanes cross the coast of Louisiana. The diagnostic morphological wetland features are products of the coupling of high-velocity wind and storm-surge water and their interaction with the underlying, variably resistant, wetland vegetation and soils. Erosional signatures include construction of orthogonal-elongate ponds and amorphous ponds, pond expansion, plucked marsh, marsh denudation, and shoreline erosion. Post-storm gravity reflux of floodwater draining from the wetlands forms dendritic incisions around the pond margins and locally integrates drainage pathways forming braided channels. Depositional signatures include emplacement of broad zones of organic wrack on topographic highs and inorganic deposits of variable thicknesses and lateral extents in the form of shore-parallel sandy washover terraces and interior-marsh mud blankets. Deformational signatures primarily involve laterally compressed marsh and displaced marsh mats and balls. Prolonged water impoundment and marsh salinization also are common impacts associated with wetland flooding by extreme storms. Many of the wetland features become legacies that record prior storm impacts and locally influence subsequent storm-induced morphological changes. Wetland losses caused by hurricane impacts depend directly on impact duration, which is controlled by the diameter of hurricane-force winds, forward speed of the storm, and wetland distance over which the storm passes. Distinguishing between wetland losses caused by storm impacts and losses associated with long-term delta-plain processes is critical for accurate modeling and prediction of future conversion of land to open water.

WheelerLab: An interactive program for sequence stratigraphic analysis of seismic sections, outcrops and well sections and the generation of chronostratigraphic sections and dynamic chronostratigraphic sections

OpenAIRE

Adewale Amosu; Yuefeng Sun

2017-01-01

WheelerLab is an interactive program that facilitates the interpretation of stratigraphic data (seismic sections, outcrop data and well sections) within a sequence stratigraphic framework and the subsequent transformation of the data into the chronostratigraphic domain. The transformation enables the identification of significant geological features, particularly erosional and non-depositional features that are not obvious in the original seismic domain. Although there are some software produ...

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Changes in erosional and depositional processes with time and management of Goa Coast, central west coast of India

Science.gov (United States)

Nayak, Ganapati; D'Souza, Joseph

2010-05-01

with seasonal morphological changes and annual cyclicity. The coastal zone in Goa is exposed to environmental and anthropogenic pressures. Some of the factors attributing to these pressures can be due to demographic settings and population growth, rapid urbanization, migration, recreation and tourism activities, fishery activities, transportation problems, socio-economic shift and transformation in occupation like, fishing, tourism, trade, salt industry; wetlands conversion, degradation of agriculture land and fallow lands. Shoreline changes observed overlapping the data after 32 years showed that all along the coast of Goa, from north to south, there is large variation in depositional and erosional processes. Deposition is specifically observed at Morjim, Baga, Campal, Miramar, Mobor and erosion is specifically observed at Kerim, Anjuna, Velsao. The present study reveals that all along the estuarine systems, there is net deposition. Further change detection study carried out overlapping the data after 38 years showed transformation of Khazan lands, conversion of marshy swampy and water logged areas, increase in Mangrove areas and decrease in salt pans. The present paper has succeeded in delineating various coastal ecosystems, coastal land forms, their resource potentials and transformation, if any. The study has helped earmarking the coastal region into conservation, development and utilization areas.

Showing Value (Editorial

Directory of Open Access Journals (Sweden)

Denise Koufogiannakis

2009-06-01

librarians on student achievement. Todd notes, “If we do not show value, we will not have a future. Evidence-based practice is not about the survival of school librarians, it’s about the survival of our students” (40. In this issue we feature school libraries and their connection to evidence based practice. Former Editor-in-Chief, Lindsay Glynn, began putting the wheels in motion for this feature almost a year ago. She invited Carol Gordon and Ross Todd to act as guest editors of the section, drawing upon their contacts and previous work in this field. The result is an issue with five feature articles exploring different aspects of the connection between school libraries and evidence based practice, from the theoretical to the practical. In addition, there is a thought-provoking Commentary by David Loertscher, asking whether we need the evolutionary model of evidence based practice, or something more revolutionary!In addition to the Feature section, we have a well-rounded issue with articles on the topics of library human resources, and the development of a scholars’ portal. As well, there are a record 10 evidence summaries and our educational EBL101 column. I hope there is something for everyone in this issue of EBLIP – enjoy, and see you soon in Stockholm!

Particle swarm optimization based feature enhancement and feature selection for improved emotion recognition in speech and glottal signals.

Science.gov (United States)

Muthusamy, Hariharan; Polat, Kemal; Yaacob, Sazali

2015-01-01

In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively. Three different emotional speech databases were utilized to gauge the proposed method. Extreme learning machine (ELM) was employed to classify the different types of emotions. Different experiments were conducted and the results show that the proposed method significantly improves the speech emotion recognition performance compared to previous works published in the literature.

Erosional Landforms Images

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The hydrologic system, which includes all possible paths of motion of Earth's near-surface fluids including air and water, is largely responsible for the variety of...

Online feature selection with streaming features.

Science.gov (United States)

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.

Understanding Legacy Features with Featureous

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2011-01-01

Java programs called Featureous that addresses this issue. Featureous allows a programmer to easily establish feature-code traceability links and to analyze their characteristics using a number of visualizations. Featureous is an extension to the NetBeans IDE, and can itself be extended by third...

Addressing scalability while feature requests persist. A look at NASA Worldview's new features and their implementation.

Science.gov (United States)

King, B. A.

2017-12-01

Worldview is a high-traffic web mapping application created using the JavaScript mapping library, OpenLayers. This presentation will primarily focus on three new features: A wrapping component that seamlessly shows satellite imagery over the dateline where most maps either stop or wrap the imagery of the same date. An animation feature that allows users to select date ranges over which they can animate. An A/B comparison feature that gives users the power to compare imagery between dates and layers. In response to an increasingly large codebase caused by ongoing feature requests, Worldview is transitioning to a smaller core codebase comprised of external reusable modules. When creating a module with the intention of having someone else reuse it for a different task, one inherently starts generating code that is easier to read and easier to maintain. This presentation will show demos of these features and cover development techniques used to create them.

7-11-year-old children show an advantage for matching and recognizing the internal features of familiar faces: evidence against a developmental shift.

Science.gov (United States)

Bonner, Lesley; Burton, Mike

2004-08-01

Adults are better at recognizing familiar faces from the internal facial features (eyes, nose, mouth) than from the external facial features (hair, face outline). However, previous research suggests that this "internal advantage" does not appear until relatively late in childhood, and some studies suggest that children rely on external features to recognize all faces, whether familiar or not. We use a matching task to examine face processing in 7-8- and 10-11-year-old children. We use a design in which all face stimuli can be used as familiar items (for participants who are classmates) and unfamiliar items (for participants from a different school). Using this design, we find an internal feature advantage for matching familiar faces, for both groups of children. The same children were then shown the external and internal features of their classmates and were asked to name or otherwise identify them. Again, both age groups identified more of their classmates correctly from the internal than the external features. This is the first time an internal advantage has been reported in this age group. Results suggest that children as young as 7 process faces in the same way as do adults, and that once procedural difficulties are overcome, the standard effects of familiarity are observed.

High mountain soils and periglacial features at the Torres del Paine, National Park Torres del Paine, Chile.

Science.gov (United States)

Senra, Eduardo; Schaefer, Carlos; Simas, Felipe; Gjorup, Davi

2015-04-01

The Torres del Paine National Park (TPNP) is located on the southern limit of the Andean Southern Ice Field, part of the Magallanes and Antartica Chilena region, in the province of Ultima Esperanza. The TPNP has a very heterogeneous climate due to orographic influence and wet air masses from the Pacific. The geology is basically Cretaceous metasedimentary rocks and Miocene granitic plutons and batholiths. We studied the main soils and geoenvironments of Mt Ferrier mountain and its surroundings, based on soils , landforms and vegetation aspects. The geoenvironmental stratification was based on the combined variation and integration of pedo-litho-geomorphological features with the vegetation. WE used detailed geological maps, a DEM and slope maps and WorlView II satellite images. Fifteen soils profiles were sampled and classified according to Soil Taxonomy (2010) at all genovironments, ranging from 50 m a.s.l to the at high plateau just below the permanent snowline, under periglacial conditions (~1004m asl). Three soil temperature and moisture monitoring sites were set, allowing for 24 consecutive months (2011 to 2013). Seven geoenvironments were identified with distinct soil and landform characteristics, all with a similar geological substrate. The landform and vegetation have a strong connection with the landscape dynamic, controlling erosional and depositional processes, resulting from glacier advances and retreats in the Late Quaternary. Wind blown materials is widespread, in the form of loess material, accumulating in the higher parts of the landscape. On the other hand, accumulation of organic matter in the water-saturated depressions is common in all altitudes. Generally the soils are acidic and dystrophic, with little exceptions. The following geoenvironments were identified: Periglacial Tundra, Loess slopes, Talus and scarpmentd, Fluvio-glacial terraces, Fluvio-lacustrine plains, Moraines and Paleodunes. The regional pedology show the occurrence of five soil

Simultaneous Channel and Feature Selection of Fused EEG Features Based on Sparse Group Lasso

Directory of Open Access Journals (Sweden)

Jin-Jia Wang

2015-01-01

Full Text Available Feature extraction and classification of EEG signals are core parts of brain computer interfaces (BCIs. Due to the high dimension of the EEG feature vector, an effective feature selection algorithm has become an integral part of research studies. In this paper, we present a new method based on a wrapped Sparse Group Lasso for channel and feature selection of fused EEG signals. The high-dimensional fused features are firstly obtained, which include the power spectrum, time-domain statistics, AR model, and the wavelet coefficient features extracted from the preprocessed EEG signals. The wrapped channel and feature selection method is then applied, which uses the logistical regression model with Sparse Group Lasso penalized function. The model is fitted on the training data, and parameter estimation is obtained by modified blockwise coordinate descent and coordinate gradient descent method. The best parameters and feature subset are selected by using a 10-fold cross-validation. Finally, the test data is classified using the trained model. Compared with existing channel and feature selection methods, results show that the proposed method is more suitable, more stable, and faster for high-dimensional feature fusion. It can simultaneously achieve channel and feature selection with a lower error rate. The test accuracy on the data used from international BCI Competition IV reached 84.72%.

Feature Binding in Zebrafish

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P Neri

2012-07-01

Full Text Available Binding operations are primarily ascribed to cortex or similarly complex avian structures. My experiments show that the zebrafish, a lower vertebrate lacking cortex, supports visual feature binding of form and motion for the purpose of social behavior. These results challenge the notion that feature binding may require highly evolved neural structures and demonstrate that the nervous system of lower vertebrates can afford unexpectedly complex computations.

Unsupervised feature learning for autonomous rock image classification

Science.gov (United States)

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

2017-09-01

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

Assessing blood flow, microvasculature, erythema and redness in hypertrophic scars: A cross sectional study showing different features that require precise definitions.

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Jaspers, M E H; Stekelenburg, C M; Simons, J M; Brouwer, K M; Vlig, M; van den Kerckhove, E; Middelkoop, E; van Zuijlen, P P M

2017-08-01

In hypertrophic scar assessment, laser Doppler imaging (LDI), colorimetry and subjective assessment (POSAS) can be used to evaluate blood flow, erythema and redness, respectively. In addition, the microvasculature (i.e. presence of microvessels) can be determined by immunohistochemistry. These measurement techniques are frequently used in clinical practice and/or in research to evaluate treatment response and monitor scar development. However, until now it has not been tested to what extent the outcomes of these techniques are associated, whilst the outcome terms are frequently used interchangeably or replaced by the umbrella term 'vascularization'. This is confusing, as every technique seems to measure a specific feature. Therefore, we evaluated the correlations of the four measurement techniques. We included 32 consecutive patients, aged ≥18 years, who underwent elective resection of a hypertrophic scar. Pre-operatively, we performed LDI (measuring blood flow), colorimetry (measuring erythema) and the POSAS (subjective redness) within the predefined scar area of interest (∼1.5cm). Subsequently, the scar was excised and the area of interest was sent for immunohistochemistry, to determine the presence of microvessels. Only a statistically significant correlation was found between erythema values (colorimetry) and subjective redness assessment (POSAS) (r=0.403, p=0.030). We found no correlations between the outcomes of LDI, immunohistochemistry and colorimetry. Blood flow, the presence of microvessels and erythema appear to be different hypertrophic scar features because they show an absence of correlation. Therefore, in the field of scar assessment, these outcome terms cannot be used interchangeably. In addition, we conclude that the term 'vascularization' does not seem appropriate to serve as an umbrella term. The use of precise definitions in research as well as in clinical practice is recommended. Copyright © 2017 Elsevier Ltd and ISBI. All rights reserved.

Disruption of River Networks in Nature and Models

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Perron, J. T.; Black, B. A.; Stokes, M.; McCoy, S. W.; Goldberg, S. L.

2017-12-01

Many natural systems display especially informative behavior as they respond to perturbations. Landscapes are no exception. For example, longitudinal elevation profiles of rivers responding to changes in uplift rate can reveal differences among erosional mechanisms that are obscured while the profiles are in equilibrium. The responses of erosional river networks to perturbations, including disruption of their network structure by diversion, truncation, resurfacing, or river capture, may be equally revealing. In this presentation, we draw attention to features of disrupted erosional river networks that a general model of landscape evolution should be able to reproduce, including the consequences of different styles of planetary tectonics and the response to heterogeneous bedrock structure and deformation. A comparison of global drainage directions with long-wavelength topography on Earth, Mars, and Saturn's moon Titan reveals the extent to which persistent and relatively rapid crustal deformation has disrupted river networks on Earth. Motivated by this example and others, we ask whether current models of river network evolution adequately capture the disruption of river networks by tectonic, lithologic, or climatic perturbations. In some cases the answer appears to be no, and we suggest some processes that models may be missing.

Identification of soil erosion land surfaces by Landsat data analysis and processing

International Nuclear Information System (INIS)

Lo Curzio, S.

2009-01-01

In this paper, we outline the typical relationship between the spectral reflectance of aileron's on newly-formed land surfaces and the geo morphological features of the land surfaces at issue. These latter represent the products of superficial erosional processes due to the action of the gravity and/or water; thus, such land surfaces are highly representative of the strong soil degradation occurring in a wide area located on the boundary between Molise and Puglia regions (Southern Italy). The results of this study have been reported on thematic maps; on such maps, the detected erosional land surfaces have been mapped on the basis of their typical spectral signature. The study has been performed using Landsat satellite imagery data which have been then validated by means of field survey data. The satellite data have been processed using remote sensing techniques, such as: false colour composite, contrast stretching, principal component analysis and decorrelation stretching. The study has permitted to produce, in a relatively short time and at low expense, a map of the eroded land surfaces. Such a result represents a first and fundamental step in evaluating and monitoring the erosional processes in the study area [it

Flow-like Features On Europa

Science.gov (United States)

1997-01-01

This image shows features on Jupiter's moon Europa that may be 'flows' from ice volcanoes. It was taken by the Galileo spacecraft solid state imaging (CCD) system during its seventh orbit around Jupiter. North is to the top of the image. The sun illuminates the scene from the left, showing features with shapes similar to lava flows on Earth. Two such features can be seen in the northwest corner of the image. The southern feature appears to have flowed over a ridge along its western edge. Scientists use these types of relationships to determine which feature formed first. In this case, the ridge probably formed before the flow-like feature that covers it.The image, centered at 22.6 degrees north latitude and 106.7 degrees west longitude, covers an area of 180 by 215 kilometers (112 by 134 miles). The smallest distinguishable features in the image are about 1.1 kilometers (0.7 miles) across. This image was obtained on April 28, 1997, when Galileo was 27,590 kilometers (16,830 miles) from Europa.The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC. JPL is an operating division of California Institute of Technology (Caltech).This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Feature extraction for magnetic domain images of magneto-optical recording films using gradient feature segmentation

International Nuclear Information System (INIS)

Quanqing, Zhu.; Xinsai, Wang; Xuecheng, Zou; Haihua, Li; Xiaofei, Yang

2002-01-01

In this paper, we present a method to realize feature extraction on low contrast magnetic domain images of magneto-optical recording films. The method is based on the following three steps: first, Lee-filtering method is adopted to realize pre-filtering and noise reduction; this is followed by gradient feature segmentation, which separates the object area from the background area; finally the common linking method is adopted and the characteristic parameters of magnetic domain are calculated. We describe these steps with particular emphasis on the gradient feature segmentation. The results show that this method has advantages over other traditional ones for feature extraction of low contrast images

Evolution of the eastern part of the Kuusamo Ice Lobe, based on geomorphological interpretation of high-resolution LiDAR data

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P. Sarala

2017-12-01

Full Text Available In this article, we present new glacial geomorphological data from the eastern part of the Kuusamo Ice Lobe (KIL in eastern Finland. The focus is on glacial lineations (about 9000 individual features and interpretation of ice lobe evolution based on streamlined erosional and depositional formations, hummocky and ribbed moraines and glaciofluvial formations. Glacial geomorphological mapping was performed based on interpretation and classification of LiDAR data according to the Geological Survey of Finland’s new Glacier Dynamic database. The results revealed that modern surficial deposits were formed during three different ice flow phases. The oldest remains are seen as occasional NW-SE megalineations and unclassified glacially lineated terrains and erosional valleys representing the Middle Weichselian glaciation. The younger morphologies were formed from the two overlapping drumlin fields of the Tuoppajärvi and Kuusamo ice flow phases, with origins in the Late Weichselian deglaciation. Analysis of different erosional and depositional formation patterns was used to separate ice flow phases and estimate the evolution, subglacial conditions and mass balance of KIL during the last deglaciation. The morphological interpretation revealed that the Tuoppajärvi ice flow stage was large and homogeneous, while the later Kuusamo ice flow stage was more concentrated, narrower and heterogeneous, following a fan-type pattern that is also emphasised by the meltwater channel systems, including both erosional and depositional features. Furthermore, on both margins (northern and southern, part of the ice masses formed stagnant areas. The length of the lineations also indicates both glacier flow velocity and transport distances, which in the case of megalineations and drumlins are longer than in the fluted terrain. Ribbed moraines in the western (core part of KIL indicate a very different depositional environment relating to strong quarrying and short transport

Morphologic and seismic evidence of rapid submergence offshore Cide-Sinop in the southern Black Sea shelf

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Ocakoğlu, Neslihan; İşcan, Yeliz; Kılıç, Fatmagül; Özel, Oğuz

2018-06-01

Multi-beam bathymetric and multi-channel seismic reflection data obtained offshore Cide-Sinop have revealed important records on the latest transgression of the Black Sea for the first time. A relatively large shelf plain within the narrow southern continental shelf characterized by a flat seafloor morphology at -100 water depth followed by a steep continental slope leading to -500 m depth. This area is widely covered by submerged morphological features such as dunes, lagoons, possible aeolianites, an eroded anticline and small channels that developed by aeolian and fluvial processes. These morphological features sit upon an erosional surface that truncates the top of all seismic units and constitutes the seafloor over the whole shelf. The recent prograded delta deposits around the shelf break are also truncated by the similar erosional surface. These results indicate that offshore Cide-Sinop was once a terrestrial landscape that was then submerged. The interpreted paleoshoreline varies from -100 to -120 m. This variation can be explained by not only sea level changes but also the active faults observed on the seismic section. The effective protection of morphological features on the seafloor is the evidence of abrupt submergence rather than gradual. In addition, the absence of coastal onlaps suggests that these morphological features should have developed at low sea level before the latest sea level rise in the Black Sea.

Using Wind Driven Tumbleweed Rovers to Explore Martian Gully Features

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Antol, Jeffrey; Woodard, Stanley E.; Hajos, Gregory A.; Heldmann, Jennifer L.; Taylor, Bryant D.

2005-01-01

Gully features have been observed on the slopes of numerous Martian crater walls, valleys, pits, and graben. Several mechanisms for gully formation have been proposed, including: liquid water aquifers (shallow and deep), melting ground ice, snow melt, CO2 aquifers, and dry debris flow. Remote sensing observations indicate that the most likely erosional agent is liquid water. Debate concerns the source of this water. Observations favor a liquid water aquifer as the primary candidate. The current strategy in the search for life on Mars is to "follow the water." A new vehicle known as a Tumbleweed rover may be able to conduct in-situ investigations in the gullies, which are currently inaccessible by conventional rovers. Deriving mobility through use of the surface winds on Mars, Tumbleweed rovers would be lightweight and relatively inexpensive thus allowing multiple rovers to be deployed in a single mission to survey areas for future exploration. NASA Langley Research Center (LaRC) is developing deployable structure Tumbleweed concepts. An extremely lightweight measurement acquisition system and sensors are proposed for the Tumbleweed rover that greatly increases the number of measurements performed while having negligible mass increase. The key to this method is the use of magnetic field response sensors designed as passive inductor-capacitor circuits that produce magnetic field responses whose attributes correspond to values of physical properties for which the sensors measure. The sensors do not need a physical connection to a power source or to data acquisition equipment resulting in additional weight reduction. Many of the sensors and interrogating antennae can be directly placed on the Tumbleweed using film deposition methods such as photolithography thus providing further weight reduction. Concepts are presented herein for methods to measure subsurface water, subsurface metals, planetary winds and environmental gases.

Feedback of Erosional-Depositional Processes Generating Anabranching Patterns in a Mega-River the Case of the PARANÁ River, Argentina

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Latrubesse, E. M.; Pereira, M.; Ramonell, C. G.; Szupiany, R. N.

2011-12-01

A new category of "very large" rivers was recently proposed and defined as mega-rivers, which are those rivers with a Qmean of more than ~17,000m3/s. This category includes the nine largest rivers on Earth and the Parana River is one of the selected members of that peculiar group. The planform adjustment of mega-rivers is a variety of anabranching patterns characterized by the existence of alluvial islands. The processes and mechanisms involved in the generation of the different anabranching styles, however, are not well understood. The Paraná channel pattern has been classified as a low to moderate anabranching, low sinuosity with tendency to braided and having a meandering thalweg. We analyzed a reach of the middle Paraná in Argentina applying a combined multitemporal, hydraulic, sedimentologic and geomorphologic approach. Multitemporal geomorphologic maps, sedimentary descriptions of bars, islands and banks, volumetric calculations using multitemporal bathymetric charts, measurements with ADCP and bathymetric surveys with echosound, sediment transport estimations and the hydrological analysis of available data from gauge stations were some of the tools used in our research. The evolution of the reach was studied from 1908 to present. The reach is subdivided in two sub-reaches (named Chapeton and Curtiembre) which are comprised between nodal points. Chapeton has been in a more mature quasi-equilibrium state through the XX Century but the main channel in Curtiembre evolved from a single pattern to anabranching pattern since 1950s. We conclude that the generation of the anabranching pattern in the studied reach depends of a combination of factors such as the architecture of the floodplain and islands, the main role played by the morphodynamics and shifting of the thalweg, the availability and path of sandy sediments bedforms architecture and the temporal variability of the effective discharge among other secondary factors. A feedback system coupling erosional

Feature Vector Construction Method for IRIS Recognition

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Odinokikh, G.; Fartukov, A.; Korobkin, M.; Yoo, J.

2017-05-01

One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent comparison. Thorough investigation of feature vectors obtained from iris showed that not all the vector elements are equally relevant. There are two characteristics which determine the vector element utility: fragility and discriminability. Conventional iris feature extraction methods consider the concept of fragility as the feature vector instability without respect to the nature of such instability appearance. This work separates sources of the instability into natural and encodinginduced which helps deeply investigate each source of instability independently. According to the separation concept, a novel approach of iris feature vector construction is proposed. The approach consists of two steps: iris feature extraction using Gabor filtering with optimal parameters and quantization with separated preliminary optimized fragility thresholds. The proposed method has been tested on two different datasets of iris images captured under changing environmental conditions. The testing results show that the proposed method surpasses all the methods considered as a prior art by recognition accuracy on both datasets.

Inflation and WMAP three year data. Features have a feature.

Energy Technology Data Exchange (ETDEWEB)

Covi, L.; Hamann, J. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Melchiorri, A. [INFN, Roma (Italy)]|[Rome-3 Univ. (Italy). Dipt. di Fisica; Slosar, A. [Ljubljana Univ. (Slovenia). Faculty of Mathematics and Physics; Sorbera, I. [Rome-3 Univ. (Italy). Dipt. di Fisica

2006-06-15

The new three year WMAP data seem to confirm the presence of non-standard large scale features in the Cosmic Microwave Anisotropies power spectrum. While these features may hint at uncorrected experimental systematics, it is also possible to generate, in a cosmological way, oscillations on large angular scales by introducing a sharp step in the inflaton potential. Using current cosmological data, we derive constraints on the position, magnitude and gradient of a possible step in the inflaton potential. We show that a step in the potential, while strongly constrained by current data, is still allowed and may provide an interesting explanation to the currently measured deviations from the standard featureless spectrum. (Orig.)

Morphometric analysis of molars in a Middle Pleistocene population shows a mosaic of 'modern' and Neanderthal features.

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Martinón-Torres, María; Spěváčková, Petra; Gracia-Téllez, Ana; Martínez, Ignacio; Bruner, Emiliano; Arsuaga, Juan Luis; Bermúdez de Castro, José María

2013-10-01

Previous studies of upper first molar (M1) crown shape have shown significant differences between Homo sapiens and Homo neanderthalensis that were already present in the European Middle Pleistocene populations, including the large dental sample from Atapuerca-Sima de los Huesos (SH). Analysis of other M1 features such as the total crown base area, cusp proportions, cusp angles and occlusal polygon have confirmed the differences between both lineages, becoming a useful tool for the taxonomic assignment of isolated teeth from Late Pleistocene sites. However, until now the pattern of expression of these variables has not been known for the SH sample. This fossil sample, the largest collection from the European Middle Pleistocene, is generally interpreted as being from the direct ancestors of Neanderthals, and thus is a reference sample for assessing the origin of the Neanderthal morphologies. Surprisingly, our study reveals that SH M(1) s present a unique mosaic of H. neanderthalensis and H. sapiens features. Regarding the cusp angles and the relative occlusal polygon area, SH matches the H. neanderthalensis pattern. However, regarding the total crown base area and relative cusps size, SH M(1) s are similar to H. sapiens, with a small crown area, a strong hypocone reduction and a protocone enlargement, although the protocone expansion in SH is significantly larger than in any other group studied. The SH dental sample calls into question the uniqueness of some so-called modern traits. Our study also sounds a note of caution on the use of M(1) occlusal morphology for the alpha taxonomy of isolated M(1) s. © 2013 Anatomical Society.

Using LiDAR to Estimate Surface Erosion Volumes within the Post-storm 2012 Bagley Fire

Science.gov (United States)

Mikulovsky, R. P.; De La Fuente, J. A.; Mondry, Z. J.

2014-12-01

The total post-storm 2012 Bagley fire sediment budget of the Squaw Creek watershed in the Shasta-Trinity National Forest was estimated using many methods. A portion of the budget was quantitatively estimated using LiDAR. Simple workflows were designed to estimate the eroded volume's of debris slides, fill failures, gullies, altered channels and streams. LiDAR was also used to estimate depositional volumes. Thorough manual mapping of large erosional features using the ArcGIS 10.1 Geographic Information System was required as these mapped features determined the eroded volume boundaries in 3D space. The 3D pre-erosional surface for each mapped feature was interpolated based on the boundary elevations. A surface difference calculation was run using the estimated pre-erosional surfaces and LiDAR surfaces to determine volume of sediment potentially delivered into the stream system. In addition, cross sections of altered channels and streams were taken using stratified random selection based on channel gradient and stream order respectively. The original pre-storm surfaces of channel features were estimated using the cross sections and erosion depth criteria. Open source software Inkscape was used to estimate cross sectional areas for randomly selected channel features and then averaged for each channel gradient and stream order classes. The average areas were then multiplied by the length of each class to estimate total eroded altered channel and stream volume. Finally, reservoir and in-channel depositional volumes were estimated by mapping channel forms and generating specific reservoir elevation zones associated with depositional events. The in-channel areas and zones within the reservoir were multiplied by estimated and field observed sediment thicknesses to attain a best guess sediment volume. In channel estimates included re-occupying stream channel cross sections established before the fire. Once volumes were calculated, other erosion processes of the Bagley

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

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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.

Finger vein recognition based on the hyperinformation feature

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Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Yang, Lu

2014-01-01

The finger vein is a promising biometric pattern for personal identification due to its advantages over other existing biometrics. In finger vein recognition, feature extraction is a critical step, and many feature extraction methods have been proposed to extract the gray, texture, or shape of the finger vein. We treat them as low-level features and present a high-level feature extraction framework. Under this framework, base attribute is first defined to represent the characteristics of a certain subcategory of a subject. Then, for an image, the correlation coefficient is used for constructing the high-level feature, which reflects the correlation between this image and all base attributes. Since the high-level feature can reveal characteristics of more subcategories and contain more discriminative information, we call it hyperinformation feature (HIF). Compared with low-level features, which only represent the characteristics of one subcategory, HIF is more powerful and robust. In order to demonstrate the potential of the proposed framework, we provide a case study to extract HIF. We conduct comprehensive experiments to show the generality of the proposed framework and the efficiency of HIF on our databases, respectively. Experimental results show that HIF significantly outperforms the low-level features.

Cascaded face alignment via intimacy definition feature

Science.gov (United States)

Li, Hailiang; Lam, Kin-Man; Chiu, Man-Yau; Wu, Kangheng; Lei, Zhibin

2017-09-01

Recent years have witnessed the emerging popularity of regression-based face aligners, which directly learn mappings between facial appearance and shape-increment manifolds. We propose a random-forest based, cascaded regression model for face alignment by using a locally lightweight feature, namely intimacy definition feature. This feature is more discriminative than the pose-indexed feature, more efficient than the histogram of oriented gradients feature and the scale-invariant feature transform feature, and more compact than the local binary feature (LBF). Experimental validation of our algorithm shows that our approach achieves state-of-the-art performance when testing on some challenging datasets. Compared with the LBF-based algorithm, our method achieves about twice the speed, 20% improvement in terms of alignment accuracy and saves an order of magnitude on memory requirement.

Video genre classification using multimodal features

Science.gov (United States)

Jin, Sung Ho; Bae, Tae Meon; Choo, Jin Ho; Ro, Yong Man

2003-12-01

We propose a video genre classification method using multimodal features. The proposed method is applied for the preprocessing of automatic video summarization or the retrieval and classification of broadcasting video contents. Through a statistical analysis of low-level and middle-level audio-visual features in video, the proposed method can achieve good performance in classifying several broadcasting genres such as cartoon, drama, music video, news, and sports. In this paper, we adopt MPEG-7 audio-visual descriptors as multimodal features of video contents and evaluate the performance of the classification by feeding the features into a decision tree-based classifier which is trained by CART. The experimental results show that the proposed method can recognize several broadcasting video genres with a high accuracy and the classification performance with multimodal features is superior to the one with unimodal features in the genre classification.

MetaFIND: A feature analysis tool for metabolomics data

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Cunningham Pádraig

2008-11-01

Full Text Available Abstract Background Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectroscopy or Mass Spectrometry. Such analysis produces a set of peaks, or features, indicative of the metabolic composition of the sample and may be used as a basis for sample classification. Feature selection may be employed to improve classification accuracy or aid model explanation by establishing a subset of class discriminating features. Factors such as experimental noise, choice of technique and threshold selection may adversely affect the set of selected features retrieved. Furthermore, the high dimensionality and multi-collinearity inherent within metabolomics data may exacerbate discrepancies between the set of features retrieved and those required to provide a complete explanation of metabolite signatures. Given these issues, the latter in particular, we present the MetaFIND application for 'post-feature selection' correlation analysis of metabolomics data. Results In our evaluation we show how MetaFIND may be used to elucidate metabolite signatures from the set of features selected by diverse techniques over two metabolomics datasets. Importantly, we also show how MetaFIND may augment standard feature selection and aid the discovery of additional significant features, including those which represent novel class discriminating metabolites. MetaFIND also supports the discovery of higher level metabolite correlations. Conclusion Standard feature selection techniques may fail to capture the full set of relevant features in the case of high dimensional, multi-collinear metabolomics data. We show that the MetaFIND 'post-feature selection' analysis tool may aid metabolite signature elucidation, feature discovery and inference of metabolic correlations.

Iris recognition based on key image feature extraction.

Science.gov (United States)

Ren, X; Tian, Q; Zhang, J; Wu, S; Zeng, Y

2008-01-01

In iris recognition, feature extraction can be influenced by factors such as illumination and contrast, and thus the features extracted may be unreliable, which can cause a high rate of false results in iris pattern recognition. In order to obtain stable features, an algorithm was proposed in this paper to extract key features of a pattern from multiple images. The proposed algorithm built an iris feature template by extracting key features and performed iris identity enrolment. Simulation results showed that the selected key features have high recognition accuracy on the CASIA Iris Set, where both contrast and illumination variance exist.

Changes in erosional input and environmental conditions at Lake Gerzensee, Switzerland, during Termination 1

Science.gov (United States)

van Raden, U. J.; Gilli, A.; van Leeuwen, J.; Ammann, B.

2012-04-01

The lateglacial record from Lake Gerzensee became an iconic figure since the early days of correlating terrestrial records with the results of polar ice core studies as initiated by Siegenthaler, Eicher, Oeschger and Dansgaard in 1984. Recently, the stable isotope record of Gerzensee was refined using a new sediment core retrieved in autumn 2008 in unprecedented resolution of 0.5cm (= 8-14 years). Depending on the sedimentation rate, the inferred temporal sample resolution of this new stable isotope record is between 8 and 14 years. A robust chronology was established through wiggle matching of the δ18O records from Gerzensee and NGRIP. Primary tie points between the two records were the prominent δ18O-shifts at the beginning and end of the Bølling/Allerød (B/A) and the Younger Dryas (YD). Then, three minor oscillations (Gerzensee, GI-1c2, and Aegelsee Oscillation) clearly visible in both, the NGRIP and Gerzensee δ18O record, were correlated. XRF core scanning was then applied to the sediments of Lake Gerzensee to establish high-resolution elemental records with a spatial resolution of 2mm. These elemental concentrations allow studying the influence of the lateglacial climate pattern on the environment and the lake system in great detail. It can be observed that environmental thresholds such as vegetation density play a mayor role on the erosive input into a lake system. Detrital elements (like Al, K, Zr, Rb, and Ti) reflect the erosional influx, which strongly decreases during the Bølling/Allerød reaching lowest concentration at the onset of the GI-1c2 oscillation. This coincides precisely with the full development of a stable pine forest in the vicinity of Lake Gerzensee demonstrating the strong coupling between vegetation and erosion. A comparable study (Lauterbach et al., 2011) at Mondsee, Austria allows to compare the same linkages between erosive input and pine forest development and to elaborate regional differences in this coupling. Initiated by

Mammographic feature enhancement by multiscale analysis

International Nuclear Information System (INIS)

Laine, A.F.; Schuler, S.; Fan, J.; Huda, W.

1994-01-01

This paper introduces a novel approach for accomplishing mammographic feature analysis by overcomplete multiresolution representations. The authors show that efficient representations may be identified within a continuum of scale-space and used to enhance features of importance to mammography. Methods of contrast enhancement are described based on three overcomplete multiscale representations: (1) the dyadic wavelet transform (separable), (2) the var-phi-transform (nonseparable, nonorthogonal), and (3) the hexagonal wavelet transform (nonseparable). Multiscale edges identified within distinct levels of transform space provide local support for image enhancement. Mammograms are reconstructed from wavelet coefficients modified at one or more levels by local and global nonlinear operators. In each case, edges and gain parameters are identified adaptively by a measure of energy within each level of scale-space. The authors show quantitatively that transform coefficients, modified by adaptive nonlinear operators, can make more obvious unseen or barely seen features of mammography without requiring additional radiation. The results are compared with traditional image enhancement techniques by measuring the local contrast of known mammographic features. The authors demonstrate that features extracted from multiresolution representations can provide an adaptive mechanism for accomplishing local contrast enhancement. By improving the visualization of breast pathology, they can improve chances of early detection while requiring less time to evaluate mammograms for most patients

DYNAMIC FEATURE SELECTION FOR WEB USER IDENTIFICATION ON LINGUISTIC AND STYLISTIC FEATURES OF ONLINE TEXTS

Directory of Open Access Journals (Sweden)

A. A. Vorobeva

2017-01-01

Full Text Available The paper deals with identification and authentication of web users participating in the Internet information processes (based on features of online texts.In digital forensics web user identification based on various linguistic features can be used to discover identity of individuals, criminals or terrorists using the Internet to commit cybercrimes. Internet could be used as a tool in different types of cybercrimes (fraud and identity theft, harassment and anonymous threats, terrorist or extremist statements, distribution of illegal content and information warfare. Linguistic identification of web users is a kind of biometric identification, it can be used to narrow down the suspects, identify a criminal and prosecute him. Feature set includes various linguistic and stylistic features extracted from online texts. We propose dynamic feature selection for each web user identification task. Selection is based on calculating Manhattan distance to k-nearest neighbors (Relief-f algorithm. This approach improves the identification accuracy and minimizes the number of features. Experiments were carried out on several datasets with different level of class imbalance. Experiment results showed that features relevance varies in different set of web users (probable authors of some text; features selection for each set of web users improves identification accuracy by 4% at the average that is approximately 1% higher than with the use of static set of features. The proposed approach is most effective for a small number of training samples (messages per user.

Feature-level domain adaptation

DEFF Research Database (Denmark)

Kouw, Wouter M.; Van Der Maaten, Laurens J P; Krijthe, Jesse H.

2016-01-01

-level domain adaptation (flda), that models the dependence between the two domains by means of a feature-level transfer model that is trained to describe the transfer from source to target domain. Subsequently, we train a domain-adapted classifier by minimizing the expected loss under the resulting transfer...... modeled via a dropout distribution, which allows the classiffier to adapt to differences in the marginal probability of features in the source and the target domain. Our experiments on several real-world problems show that flda performs on par with state-of-the-art domainadaptation techniques.......Domain adaptation is the supervised learning setting in which the training and test data are sampled from different distributions: training data is sampled from a source domain, whilst test data is sampled from a target domain. This paper proposes and studies an approach, called feature...

EOG feature relevance determination for microsleep detection

Directory of Open Access Journals (Sweden)

Golz Martin

2017-09-01

Full Text Available Automatic relevance determination (ARD was applied to two-channel EOG recordings for microsleep event (MSE recognition. 10 s immediately before MSE and also before counterexamples of fatigued, but attentive driving were analysed. Two type of signal features were extracted: the maximum cross correlation (MaxCC and logarithmic power spectral densities (PSD averaged in spectral bands of 0.5 Hz width ranging between 0 and 8 Hz. Generalised learn-ing vector quantisation (GRLVQ was used as ARD method to show the potential of feature reduction. This is compared to support-vector machines (SVM, in which the feature reduction plays a much smaller role. Cross validation yielded mean normalised relevancies of PSD features in the range of 1.6 – 4.9 % and 1.9 – 10.4 % for horizontal and vertical EOG, respectively. MaxCC relevancies were 0.002 – 0.006 % and 0.002 – 0.06 %, respectively. This shows that PSD features of vertical EOG are indispensable, whereas MaxCC can be neglected. Mean classification accuracies were estimated at 86.6±b 1.3 % and 92.3±b 0.2 % for GRLVQ and SVM, respectively. GRLVQ permits objective feature reduction by inclusion of all processing stages, but is not as accurate as SVM.

EOG feature relevance determination for microsleep detection

Directory of Open Access Journals (Sweden)

Golz Martin

2017-09-01

Full Text Available Automatic relevance determination (ARD was applied to two-channel EOG recordings for microsleep event (MSE recognition. 10 s immediately before MSE and also before counterexamples of fatigued, but attentive driving were analysed. Two type of signal features were extracted: the maximum cross correlation (MaxCC and logarithmic power spectral densities (PSD averaged in spectral bands of 0.5 Hz width ranging between 0 and 8 Hz. Generalised learn-ing vector quantisation (GRLVQ was used as ARD method to show the potential of feature reduction. This is compared to support-vector machines (SVM, in which the feature reduction plays a much smaller role. Cross validation yielded mean normalised relevancies of PSD features in the range of 1.6 - 4.9 % and 1.9 - 10.4 % for horizontal and vertical EOG, respectively. MaxCC relevancies were 0.002 - 0.006 % and 0.002 - 0.06 %, respectively. This shows that PSD features of vertical EOG are indispensable, whereas MaxCC can be neglected. Mean classification accuracies were estimated at 86.6±b 1.3 % and 92.3±b 0.2 % for GRLVQ and SVM, respec-tively. GRLVQ permits objective feature reduction by inclu-sion of all processing stages, but is not as accurate as SVM.

Aggrecan-based extracellular matrix shows unique cortical features and conserved subcortical principles of mammalian brain organization in the Madagascan lesser hedgehog tenrec (Echinops telfairi Martin, 1838).

Science.gov (United States)

Morawski, M; Brückner, G; Jäger, C; Seeger, G; Künzle, H; Arendt, T

2010-02-03

The Madagascan tenrecs (Afrotheria), an ancient mammalian clade, are characterized by unique brain anatomy. Striking features are an expanded paleocortex but a small and poorly differentiated neocortex devoid of a distinct granular layer IV. To investigate the organization of cortical areas we analyzed extracellular matrix components in perineuronal nets (PNs) using antibodies to aggrecan, lectin staining and hyaluronan-binding protein. Selected subcortical regions were studied to correlate the cortical patterns with features in evolutionary conserved systems. In the neocortex, paleocortex and hippocampus PNs were associated with nonpyramidal neurons. Quantitative analysis in the cerebral cortex revealed area-specific proportions and laminar distribution patterns of neurons ensheathed by PNs. Cortical PNs showed divergent structural phenotypes. Diffuse PNs forming a cotton wool-like perisomatic rim were characteristic of the paleocortex. These PNs were associated with a dense pericellular plexus of calretinin-immunoreactive fibres. Clearly contoured PNs were devoid of a calretinin-positive plexus and predominated in the neocortex and hippocampus. The organization of the extracellular matrix in subcortical nuclei followed the widely distributed mammalian type. We conclude that molecular properties of the aggrecan-based extracellular matrix are conserved during evolution of mammals; however, the matrix scaffold is adapted to specific wiring patterns of cortical and subcortical neuronal networks. Copyright 2010 IBRO. Published by Elsevier Ltd. All rights reserved.

Classification Using Markov Blanket for Feature Selection

DEFF Research Database (Denmark)

Zeng, Yifeng; Luo, Jian

2009-01-01

Selecting relevant features is in demand when a large data set is of interest in a classification task. It produces a tractable number of features that are sufficient and possibly improve the classification performance. This paper studies a statistical method of Markov blanket induction algorithm...... for filtering features and then applies a classifier using the Markov blanket predictors. The Markov blanket contains a minimal subset of relevant features that yields optimal classification performance. We experimentally demonstrate the improved performance of several classifiers using a Markov blanket...... induction as a feature selection method. In addition, we point out an important assumption behind the Markov blanket induction algorithm and show its effect on the classification performance....

A performance evaluation of point pair features

DEFF Research Database (Denmark)

Kiforenko, Lilita; Drost, Bertram; Tombari, Federico

2018-01-01

have low resolution data, where local histogram features show a higher performance than PPFs. We also found that PPFs compared to most local histogram features degrade faster under disturbances such as occlusion and clutter, however, PPFs still remain more descriptive on an absolute scale. The main...

Erosional scarps on Io

International Nuclear Information System (INIS)

McCauley, J.F.; Soderblom, L.A.; Smith, B.A.

1979-01-01

Irregular or fretted scarps on Io as revealed during the voyager 1 mission are similar to those found on Earth and Mars. A sapping mechanism involving liquid SO 2 is proposed to explain these complexly eroded terrains on Io. (author)

Multi-scale salient feature extraction on mesh models

KAUST Repository

Yang, Yongliang; Shen, ChaoHui

2012-01-01

We present a new method of extracting multi-scale salient features on meshes. It is based on robust estimation of curvature on multiple scales. The coincidence between salient feature and the scale of interest can be established straightforwardly, where detailed feature appears on small scale and feature with more global shape information shows up on large scale. We demonstrate this multi-scale description of features accords with human perception and can be further used for several applications as feature classification and viewpoint selection. Experiments exhibit that our method as a multi-scale analysis tool is very helpful for studying 3D shapes. © 2012 Springer-Verlag.

Controllable edge feature sharpening for dental applications.

Science.gov (United States)

Fan, Ran; Jin, Xiaogang

2014-01-01

This paper presents a new approach to sharpen blurred edge features in scanned tooth preparation surfaces generated by structured-light scanners. It aims to efficiently enhance the edge features so that the embedded feature lines can be easily identified in dental CAD systems, and to avoid unnatural oversharpening geometry. We first separate the feature regions using graph-cut segmentation, which does not require a user-defined threshold. Then, we filter the face normal vectors to propagate the geometry from the smooth region to the feature region. In order to control the degree of the sharpness, we propose a feature distance measure which is based on normal tensor voting. Finally, the vertex positions are updated according to the modified face normal vectors. We have applied the approach to scanned tooth preparation models. The results show that the blurred edge features are enhanced without unnatural oversharpening geometry.

Controllable Edge Feature Sharpening for Dental Applications

Directory of Open Access Journals (Sweden)

Ran Fan

2014-01-01

Full Text Available This paper presents a new approach to sharpen blurred edge features in scanned tooth preparation surfaces generated by structured-light scanners. It aims to efficiently enhance the edge features so that the embedded feature lines can be easily identified in dental CAD systems, and to avoid unnatural oversharpening geometry. We first separate the feature regions using graph-cut segmentation, which does not require a user-defined threshold. Then, we filter the face normal vectors to propagate the geometry from the smooth region to the feature region. In order to control the degree of the sharpness, we propose a feature distance measure which is based on normal tensor voting. Finally, the vertex positions are updated according to the modified face normal vectors. We have applied the approach to scanned tooth preparation models. The results show that the blurred edge features are enhanced without unnatural oversharpening geometry.

Morphometric analysis of molars in a Middle Pleistocene population shows a mosaic of ‘modern’ and Neanderthal features

Science.gov (United States)

Martinón-Torres, María; Spěváčková, Petra; Gracia-Téllez, Ana; Martínez, Ignacio; Bruner, Emiliano; Arsuaga, Juan Luis; Bermúdez de Castro, José María

2013-01-01

Previous studies of upper first molar (M1) crown shape have shown significant differences between Homo sapiens and Homo neanderthalensis that were already present in the European Middle Pleistocene populations, including the large dental sample from Atapuerca-Sima de los Huesos (SH). Analysis of other M1 features such as the total crown base area, cusp proportions, cusp angles and occlusal polygon have confirmed the differences between both lineages, becoming a useful tool for the taxonomic assignment of isolated teeth from Late Pleistocene sites. However, until now the pattern of expression of these variables has not been known for the SH sample. This fossil sample, the largest collection from the European Middle Pleistocene, is generally interpreted as being from the direct ancestors of Neanderthals, and thus is a reference sample for assessing the origin of the Neanderthal morphologies. Surprisingly, our study reveals that SH M1s present a unique mosaic of H. neanderthalensis and H. sapiens features. Regarding the cusp angles and the relative occlusal polygon area, SH matches the H. neanderthalensis pattern. However, regarding the total crown base area and relative cusps size, SH M1s are similar to H. sapiens, with a small crown area, a strong hypocone reduction and a protocone enlargement, although the protocone expansion in SH is significantly larger than in any other group studied. The SH dental sample calls into question the uniqueness of some so-called modern traits. Our study also sounds a note of caution on the use of M1 occlusal morphology for the alpha taxonomy of isolated M1s. PMID:23914934

Shelves around the Iberian Peninsula (II): Evolutionary sedimentary patterns; Las plataformas continentales de la Peninsula Iberica (II): Patrones sedimentarios evolutivos

Energy Technology Data Exchange (ETDEWEB)

Lobo, F. J.; Duran, R.; Roque, C.; Ribo, M.; Carrera, G.; Mendes, I.; Ferrin, A.; Fernandez-Salas, L. M.; Garcia-Gil, S.; Galpalsoro, I.; Rosa, F.; Barcenas, P.

2015-07-01

We present a synthetic view of continental-shelf evolutionary patterns around the Iberian Peninsula, focusing on proposed sequence stratigraphy interpretations and attempting a comparison between Atlantic- and Mediterranean-type shelf-margin constructions. Most of the studied shelves show a dominance of regressive to low stand deposition through successive pro gradations, particularly evident in the Pliocene-Quaternary, documenting the influence of glacio-eustasy. Transgressive to high stand development predating the Last Glacial Maximum seems to be favoured off major rivers, but the highest variability is seen during post glacial evolution. Transgressive deposits tend to show a higher spatial variability, ranging from pro graded para sequences to extensive sand sheets. Holocene high- stand deposits usually show a more homogeneous character, with development of proximal wedge-shaped deposits and a distal sheet-like deposition. Atlantic continental shelves off Iberia display three different types of shelf growth: depositional shelves, shelves with restricted pro gradation and erosional shelves. They result from the interplay between depositional and hydrodynamic regimes, with the occurrence of a latitudinal gradation from erosional shelves in the Cantabrian continental shelf to depositional shelves in the northern Gulf of Cadiz shelf. Some shelf sectors do not correspond to this general pattern, as shelf sedimentation is mainly controlled by morpho-structural features (e.g., ria environments and shelves crossed by major tectonic accidents). The Mediterranean continental shelves of Iberia show two basic types, high- versus low-supply shelves, and their growth patterns are mainly a response to the amount of fluvial supply. The low-supply style is clearly the most frequent type, and it may show further complexity according to the occurrence of submarine canyons and/or morpho-structural control. (Author)

Habitat associations of three crayfish endemic to the Ouachita Mountain Ecoregion

Science.gov (United States)

Dyer, Joseph J.; Brewer, Shannon K.

2018-01-01

Many crayfish are of conservation concern because of their use of unique habitats and often narrow ranges. In this study, we determined fine-scale habitat use by 3 crayfishes that are endemic to the Ouachita Mountains, in Oklahoma and Arkansas. We sampled Faxonius menae (Mena Crayfish), F. leptogonopodus (Little River Creek Crayfish), and Fallicambarus tenuis (Ouachita Mountain Crayfish) from wet and dry erosional channel units of 29 reaches within the Little River catchment. We compared channel-unit and microhabitat selection for each species. Crayfish of all species and life stages selected erosional channel units more often than depositional units, even though these sites were often dry. Accordingly, crayfish at all life stages typically selected the shallowest available microhabitats. Adult crayfish of all species and juvenile Little River Creek Crayfish selected patches of coarse substrate, and all crayfish tended to use the lowest amount of bedrock available. In general, we showed that these endemic crayfish used erosional channel units of streams, even when the channel units were dry. Conservation efforts that protect erosional channel units and mitigate actions that cause channel downcutting to bedrock would benefit these crayfish, particularly during harsh, summer drying periods.

Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features

Science.gov (United States)

Mousavi Kahaki, Seyed Mostafa; Nordin, Md Jan; Ashtari, Amir H.; J. Zahra, Sophia

2016-01-01

An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics—such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient—are insufficient for achieving adequate results under different image deformations. Thus, new descriptor’s similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence. PMID:26985996

Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features.

Directory of Open Access Journals (Sweden)

Seyed Mostafa Mousavi Kahaki

Full Text Available An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics--such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient--are insufficient for achieving adequate results under different image deformations. Thus, new descriptor's similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence.

Robust Features Of Surface Electromyography Signal

Science.gov (United States)

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

Robust Features Of Surface Electromyography Signal

International Nuclear Information System (INIS)

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

2013-01-01

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

EEG feature selection method based on decision tree.

Science.gov (United States)

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

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

Science.gov (United States)

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.

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods

Directory of Open Access Journals (Sweden)

Kaiyang Qu

2017-09-01

Full Text Available 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.

Optimized feature subsets for epileptic seizure prediction studies.

Science.gov (United States)

Direito, Bruno; Ventura, Francisco; Teixeira, César; Dourado, António

2011-01-01

The reduction of the number of EEG features to give as inputs to epilepsy seizure predictors is a needed step towards the development of a transportable device for real-time warning. This paper presents a comparative study of three feature selection methods, based on Support Vector Machines. Minimum-Redundancy Maximum-Relevance, Recursive Feature Elimination, Genetic Algorithms, show that, for three patients of the European Database on Epilepsy, the most important univariate features are related to spectral information and statistical moments.

Feature-Space Clustering for fMRI Meta-Analysis

DEFF Research Database (Denmark)

Goutte, Cyril; Hansen, Lars Kai; Liptrot, Mathew G.

2001-01-01

MRI sequences containing several hundreds of images, it is sometimes necessary to invoke feature extraction to reduce the dimensionality of the data space. A second interesting application is in the meta-analysis of fMRI experiment, where features are obtained from a possibly large number of single......-voxel analyses. In particular this allows the checking of the differences and agreements between different methods of analysis. Both approaches are illustrated on a fMRI data set involving visual stimulation, and we show that the feature space clustering approach yields nontrivial results and, in particular......, shows interesting differences between individual voxel analysis performed with traditional methods. © 2001 Wiley-Liss, Inc....

The influence of the land use in the development of the erosion processes (gully erosion and landslides in Aiud and Stejeriş basins (Măhăceni Tableland

Directory of Open Access Journals (Sweden)

Bogdan ONAC

2010-05-01

Full Text Available Land use has got a great influence upon actual erosional slope processes development and evolution and the stability of slopes. Tree clearing and degradation of agroterraces in Aiud and Stejeriş catchments, led to destabilization of the slopes and the quick development of gullzprocesses and landslides. The present paper gives example of a present-day model, which shows that, changing landuse style, can be the setting point in the formation and rapid development of actual slope erosional processes.

Consistency relations for sharp inflationary non-Gaussian features

Energy Technology Data Exchange (ETDEWEB)

Mooij, Sander; Palma, Gonzalo A.; Panotopoulos, Grigoris [Departamento de Física, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Blanco Encalada 2008, Santiago (Chile); Soto, Alex, E-mail: sander.mooij@ing.uchile.cl, E-mail: gpalmaquilod@ing.uchile.cl, E-mail: gpanotop@ing.uchile.cl, E-mail: gatogeno@gmail.com [Departamento de Física, Facultad de Ciencias, Universidad de Chile, Las Palmeras 3425, Ñuñoa, Santiago (Chile)

2016-09-01

If cosmic inflation suffered tiny time-dependent deviations from the slow-roll regime, these would induce the existence of small scale-dependent features imprinted in the primordial spectra, with their shapes and sizes revealing information about the physics that produced them. Small sharp features could be suppressed at the level of the two-point correlation function, making them undetectable in the power spectrum, but could be amplified at the level of the three-point correlation function, offering us a window of opportunity to uncover them in the non-Gaussian bispectrum. In this article, we show that sharp features may be analyzed using only data coming from the three point correlation function parametrizing primordial non-Gaussianity. More precisely, we show that if features appear in a particular non-Gaussian triangle configuration (e.g. equilateral, folded, squeezed), these must reappear in every other configuration according to a specific relation allowing us to correlate features across the non-Gaussian bispectrum. As a result, we offer a method to study scale-dependent features generated during inflation that depends only on data coming from measurements of non-Gaussianity, allowing us to omit data from the power spectrum.

Consistency relations for sharp inflationary non-Gaussian features

International Nuclear Information System (INIS)

Mooij, Sander; Palma, Gonzalo A.; Panotopoulos, Grigoris; Soto, Alex

2016-01-01

If cosmic inflation suffered tiny time-dependent deviations from the slow-roll regime, these would induce the existence of small scale-dependent features imprinted in the primordial spectra, with their shapes and sizes revealing information about the physics that produced them. Small sharp features could be suppressed at the level of the two-point correlation function, making them undetectable in the power spectrum, but could be amplified at the level of the three-point correlation function, offering us a window of opportunity to uncover them in the non-Gaussian bispectrum. In this article, we show that sharp features may be analyzed using only data coming from the three point correlation function parametrizing primordial non-Gaussianity. More precisely, we show that if features appear in a particular non-Gaussian triangle configuration (e.g. equilateral, folded, squeezed), these must reappear in every other configuration according to a specific relation allowing us to correlate features across the non-Gaussian bispectrum. As a result, we offer a method to study scale-dependent features generated during inflation that depends only on data coming from measurements of non-Gaussianity, allowing us to omit data from the power spectrum.

Biometric feature extraction using local fractal auto-correlation

International Nuclear Information System (INIS)

Chen Xi; Zhang Jia-Shu

2014-01-01

Image texture feature extraction is a classical means for biometric recognition. To extract effective texture feature for matching, we utilize local fractal auto-correlation to construct an effective image texture descriptor. Three main steps are involved in the proposed scheme: (i) using two-dimensional Gabor filter to extract the texture features of biometric images; (ii) calculating the local fractal dimension of Gabor feature under different orientations and scales using fractal auto-correlation algorithm; and (iii) linking the local fractal dimension of Gabor feature under different orientations and scales into a big vector for matching. Experiments and analyses show our proposed scheme is an efficient biometric feature extraction approach. (condensed matter: structural, mechanical, and thermal properties)

Feature Extraction in Radar Target Classification

Directory of Open Access Journals (Sweden)

Z. Kus

1999-09-01

Full Text Available This paper presents experimental results of extracting features in the Radar Target Classification process using the J frequency band pulse radar. The feature extraction is based on frequency analysis methods, the discrete-time Fourier Transform (DFT and Multiple Signal Characterisation (MUSIC, based on the detection of Doppler effect. The analysis has turned to the preference of DFT with implemented Hanning windowing function. We assumed to classify targets-vehicles into two classes, the wheeled vehicle and tracked vehicle. The results show that it is possible to classify them only while moving. The feature of the class results from a movement of moving parts of the vehicle. However, we have not found any feature to classify the wheeled and tracked vehicles while non-moving, although their engines are on.

Critical feature analysis of a radiotherapy machine

International Nuclear Information System (INIS)

Rae, Andrew; Jackson, Daniel; Ramanan, Prasad; Flanz, Jay; Leyman, Didier

2005-01-01

The software implementation of the emergency shutdown feature in a major radiotherapy system was analyzed, using a directed form of code review based on module dependences. Dependences between modules are labelled by particular assumptions; this allows one to trace through the code, and identify those fragments responsible for critical features. An 'assumption tree' is constructed in parallel, showing the assumptions which each module makes about others. The root of the assumption tree is the critical feature of interest, and its leaves represent assumptions which, if not valid, might cause the critical feature to fail. The analysis revealed some unexpected assumptions that motivated improvements to the code

Your Town Television Show: SMART Program (Part 1) [video

OpenAIRE

Naval Postgraduate School, (U.S.); Sanders, John; Millsaps, Knox; Shifflett, Deborah

2010-01-01

From "Your Town" television show. SMART Scholarship Program featured on Your Town television program in Monterey, California. Host John Sanders, Special Collections Manager of the Naval Postgraduate School's Dudley Knox Library, interviews Dr. Knox Millsaps, Executive Agent for the SMART Program, and Deborah Shifflett, SMART Program Manager.

Your Town Television Show: SMART Program (Part 3) [video

OpenAIRE

Naval Postgraduate School, (U.S.); Sanders, John; Millsaps, Knox; Shifflett, Deborah

2010-01-01

From "Your Town" television show. SMART Scholarship Program featured on Your Town television program in Monterey, California. Host John Sanders, Special Collections Manager of the Naval Postgraduate School's Dudley Knox Library, interviews Dr. Knox Millsaps, Executive Agent for the SMART Program, and Deborah Shifflett, SMART Program Manager.

Naive Bayes-Guided Bat Algorithm for Feature Selection

Directory of Open Access Journals (Sweden)

Ahmed Majid Taha

2013-01-01

Full Text Available When the amount of data and information is said to double in every 20 months or so, feature selection has become highly important and beneficial. Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. The results showed that BANB significantly outperformed other algorithms in selecting lower number of features, hence removing irrelevant, redundant, or noisy features while maintaining the classification accuracy. BANB is also proven to be more stable than other methods and is capable of producing more general feature subsets.

Naive Bayes-Guided Bat Algorithm for Feature Selection

Science.gov (United States)

Taha, Ahmed Majid; Mustapha, Aida; Chen, Soong-Der

2013-01-01

When the amount of data and information is said to double in every 20 months or so, feature selection has become highly important and beneficial. Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. The results showed that BANB significantly outperformed other algorithms in selecting lower number of features, hence removing irrelevant, redundant, or noisy features while maintaining the classification accuracy. BANB is also proven to be more stable than other methods and is capable of producing more general feature subsets. PMID:24396295

Improving scale invariant feature transform-based descriptors with shape-color alliance robust feature

Science.gov (United States)

Wang, Rui; Zhu, Zhengdan; Zhang, Liang

2015-05-01

Constructing appropriate descriptors for interest points in image matching is a critical aspect task in computer vision and pattern recognition. A method as an extension of the scale invariant feature transform (SIFT) descriptor called shape-color alliance robust feature (SCARF) descriptor is presented. To address the problem that SIFT is designed mainly for gray images and lack of global information for feature points, the proposed approach improves the SIFT descriptor by means of a concentric-rings model, as well as integrating the color invariant space and shape context with SIFT to construct the SCARF descriptor. The SCARF method developed is more robust than the conventional SIFT with respect to not only the color and photometrical variations but also the measuring similarity as a global variation between two shapes. A comparative evaluation of different descriptors is carried out showing that the SCARF approach provides better results than the other four state-of-the-art related methods.

Features for detecting smoke in laparoscopic videos

Directory of Open Access Journals (Sweden)

Jalal Nour Aldeen

2017-09-01

Full Text Available Video-based smoke detection in laparoscopic surgery has different potential applications, such as the automatic addressing of surgical events associated with the electrocauterization task and the development of automatic smoke removal. In the literature, video-based smoke detection has been studied widely for fire surveillance systems. Nevertheless, the proposed methods are insufficient for smoke detection in laparoscopic videos because they often depend on assumptions which rarely hold in laparoscopic surgery such as static camera. In this paper, ten visual features based on motion, texture and colour of smoke are proposed and evaluated for smoke detection in laparoscopic videos. These features are RGB channels, energy-based feature, texture features based on gray level co-occurrence matrix (GLCM, HSV colour space feature, features based on the detection of moving regions using optical flow and the smoke colour in HSV colour space. These features were tested on four laparoscopic cholecystectomy videos. Experimental observations show that each feature can provide valuable information in performing the smoke detection task. However, each feature has weaknesses to detect the presence of smoke in some cases. By combining all proposed features smoke with high and even low density can be identified robustly and the classification accuracy increases significantly.

Feature-specific encoding flexibility in visual working memory.

Directory of Open Access Journals (Sweden)

Aki Kondo

Full Text Available The current study examined selective encoding in visual working memory by systematically investigating interference from task-irrelevant features. The stimuli were objects defined by three features (color, shape, and location, and during a delay period, any of the features could switch between two objects. Additionally, single- and whole-probe trials were randomized within experimental blocks to investigate effects of memory retrieval. A series of relevant-feature switch detection tasks, where one feature was task-irrelevant, showed that interference from the task-irrelevant feature was only observed in the color-shape task, suggesting that color and shape information could be successfully filtered out, but location information could not, even when location was a task-irrelevant feature. Therefore, although location information is added to object representations independent of task demands in a relatively automatic manner, other features (e.g., color, shape can be flexibly added to object representations.

Feature-specific encoding flexibility in visual working memory.

Science.gov (United States)

Kondo, Aki; Saiki, Jun

2012-01-01

The current study examined selective encoding in visual working memory by systematically investigating interference from task-irrelevant features. The stimuli were objects defined by three features (color, shape, and location), and during a delay period, any of the features could switch between two objects. Additionally, single- and whole-probe trials were randomized within experimental blocks to investigate effects of memory retrieval. A series of relevant-feature switch detection tasks, where one feature was task-irrelevant, showed that interference from the task-irrelevant feature was only observed in the color-shape task, suggesting that color and shape information could be successfully filtered out, but location information could not, even when location was a task-irrelevant feature. Therefore, although location information is added to object representations independent of task demands in a relatively automatic manner, other features (e.g., color, shape) can be flexibly added to object representations.

MRI features of placenta accreta

International Nuclear Information System (INIS)

Cao Manrui; Du Mu; Huang Yi; Liu Bingguang; Zhang Fangjing; Guo Jimin; Zhu Zhijun

2012-01-01

Objective: To investigate the MRI features of placenta accreta. Methods: From Apr 2009 to Jun 2011, 15 patients with placenta accrete received MRI examination. In them, placenta accreta was diagnosed based on clinical manifestations or postoperative histopathology. The MR features of placenta accreta in them (study group) were retrospectively analyzed and compared with those in 15 pregnant women without placenta accreta (control group) with Fisher exact test. Results: In the 15 patients with placenta accreta,uterine bulging and (or) a focal outward contour bulge was detected in 14 patients; heterogeneous signal intensity in the placenta was detected in 15 patients; dark intraplacental bands on T 2 -weighted images was detected in 15 patients; and increased subplacental vascularity was detected in 11 patients on T 1 - weighted images. In the study group, 14 patients showed at least three of the above four features, and in all of them uterine bulging and (or) a focal outward contour bulge, heterogeneous signal intensity in the placenta and dark intraplacental bands on T 2 -weighted images were detected; one patient showed heterogeneous signal intensity in the placenta, dark intraplacental bands on T 2 -weighted images and increased subplacental vascularity. In the control group,none patient had three of the above features.Uterine bulging and (or) a focal outward contour bulge, heterogeneous signal intensity in the placenta, dark intraplacental bands on T 2 -weighted images and increased subplacental vascularity were detected in 3, 6, 3 and 4 patients (P=0.000, 0.001, 0.000 and 0.027), respectively. Conclusions: The main MRI features of placenta accreta are uterine bulging and (or) a focal outward contour bulge, heterogeneous signal intensity in the placenta and dark intraplacental bands on T 2 -weighted images Besides, increased subplacental vascularity also could provide useful information for the diagnosis of placenta accreta. (authors)

We're Playing "Jeremy Kyle"! Television Talk Shows in the Playground

Science.gov (United States)

Marsh, Jackie; Bishop, Julia

2014-01-01

This paper focuses on an episode of play in a primary school playground in England, which featured a group of children re-enacting elements of the television talk show "The Jeremy Kyle Show". The episode is analysed in the light of work that has identified the key elements of the talk show genre and the children's play is examined in…

Correlation optics in progress: introduction to the feature issue

DEFF Research Database (Denmark)

Angelsky, Oleg V.; Desyatnikov, Anton S.; Gbur, Gregory J.

2014-01-01

This feature issue of Applied Optics contains a series of selected papers reflecting recent progress of correlation optics and showing, in part, the trend from micro-optics to nano-optics.......This feature issue of Applied Optics contains a series of selected papers reflecting recent progress of correlation optics and showing, in part, the trend from micro-optics to nano-optics....

Enhancing facial features by using clear facial features

Science.gov (United States)

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.

A Novel Real-Time Feature Matching Scheme

Directory of Open Access Journals (Sweden)

Ying Liu

2014-02-01

Full Text Available Affine Scale Invariant Feature Transform (ASIFT can obtain fully affine invariance, however, its time cost reaches about twice that in Scale Invariant Feature Transform (SIFT. We propose an improved ASIFT algorithm based on feature points in scale space for real-time application. In order to detect the affine invariant feature point, we establish a second-order difference of Gaussian (DOG pyramid and replace the extreme detection in the DOG pyramid by zero detection in the proposed second-order DOG pyramid, which decreases the complexity of the scheme. Experimental results show that the proposed method has a big progress in the real-time performance compared to the traditional one, while preserving the fully affine invariance and precision.

Spatial features register: toward standardization of spatial features

Science.gov (United States)

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.

Feature singletons attract spatial attention independently of feature priming.

Science.gov (United States)

Yashar, Amit; White, Alex L; Fang, Wanghaoming; Carrasco, Marisa

2017-08-01

People perform better in visual search when the target feature repeats across trials (intertrial feature priming [IFP]). Here, we investigated whether repetition of a feature singleton's color modulates stimulus-driven shifts of spatial attention by presenting a probe stimulus immediately after each singleton display. The task alternated every two trials between a probe discrimination task and a singleton search task. We measured both stimulus-driven spatial attention (via the distance between the probe and singleton) and IFP (via repetition of the singleton's color). Color repetition facilitated search performance (IFP effect) when the set size was small. When the probe appeared at the singleton's location, performance was better than at the opposite location (stimulus-driven attention effect). The magnitude of this attention effect increased with the singleton's set size (which increases its saliency) but did not depend on whether the singleton's color repeated across trials, even when the previous singleton had been attended as a search target. Thus, our findings show that repetition of a salient singleton's color affects performance when the singleton is task relevant and voluntarily attended (as in search trials). However, color repetition does not affect performance when the singleton becomes irrelevant to the current task, even though the singleton does capture attention (as in probe trials). Therefore, color repetition per se does not make a singleton more salient for stimulus-driven attention. Rather, we suggest that IFP requires voluntary selection of color singletons in each consecutive trial.

Automatic processing of unattended object features by functional connectivity

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Katja Martina Mayer

2013-05-01

Full Text Available Observers can selectively attend to object features that are relevant for a task. However, unattended task-irrelevant features may still be processed and possibly integrated with the attended features. This study investigated the neural mechanisms for processing both task-relevant (attended and task-irrelevant (unattended object features. The Garner paradigm was adapted for functional magnetic resonance imaging (fMRI to test whether specific brain areas process the conjunction of features or whether multiple interacting areas are involved in this form of feature integration. Observers attended to shape, colour, or non-rigid motion of novel objects while unattended features changed from trial to trial (change blocks or remained constant (no-change blocks during a given block. This block manipulation allowed us to measure the extent to which unattended features affected neural responses which would reflect the extent to which multiple object features are automatically processed. We did not find Garner interference at the behavioural level. However, we designed the experiment to equate performance across block types so that any fMRI results could not be due solely to differences in task difficulty between change and no-change blocks. Attention to specific features localised several areas known to be involved in object processing. No area showed larger responses on change blocks compared to no-change blocks. However, psychophysiological interaction analyses revealed that several functionally-localised areas showed significant positive interactions with areas in occipito-temporal and frontal areas that depended on block type. Overall, these findings suggest that both regional responses and functional connectivity are crucial for processing multi-featured objects.

Geomorphology and Sediment Stability of a Segment of the U.S. Continental Slope off New Jersey.

Science.gov (United States)

Robb, J M; Hampson, J C; Twichell, D C

1981-02-27

The morphology of complex deposits of Pleistocene sediments covering the upper continental slope between Lindenkohl Canyon and South Toms Canyon results from both depositional and erosional processes. Small slump or slide features were detected primarily on the flanks of canyons or valleys and were observed to occur only within Pleistocene-aged sediments. Eocene to Miocene sediments are exposed over much of the mid- and lower slope in this area.

Some new data on the Češnjice and Zlatenek deposits

Directory of Open Access Journals (Sweden)

Ivan Mlakar

1995-12-01

Full Text Available In the paper detailed data on geological structure of the ore-bearing area and new information on the abandoned Pb, Zn (Cu deposit Češnjice and Cu deposit Zlatenek are presented. Among the newly established features the erosional-discordantcontact of Ladinian limestone with Paleozoic and Lower Triassic beds and the position of both deposits deep in the Carboniferous sequence of beds should be mentioned.

Classification of line features from remote sensing data

OpenAIRE

Kolankiewiczová, Soňa

2009-01-01

This work deals with object-based classification of high resolution data. The aim of the thesis (paper, work) is to develope an acceptable classification process of linear features (roads and railways) from high-resolution satellite images. The first part shows different approaches of the linear feature classification and compares theoretic differences between an object-oriented and a pixel-based classification. Linear feature classification was created in the second part. The high-resolution...

Generalised Brown Clustering and Roll-up Feature Generation

DEFF Research Database (Denmark)

Derczynski, Leon; Chester, Sean

2016-01-01

active set size. Moreover, the generalisation permits a novel approach to feature selection from Brown clusters: We show that the standard approach of shearing the Brown clustering output tree at arbitrary bitlengths is lossy and that features should be chosen instead by rolling up Generalised Brown...

Effective traffic features selection algorithm for cyber-attacks samples

Science.gov (United States)

Li, Yihong; Liu, Fangzheng; Du, Zhenyu

2018-05-01

By studying the defense scheme of Network attacks, this paper propose an effective traffic features selection algorithm based on k-means++ clustering to deal with the problem of high dimensionality of traffic features which extracted from cyber-attacks samples. Firstly, this algorithm divide the original feature set into attack traffic feature set and background traffic feature set by the clustering. Then, we calculates the variation of clustering performance after removing a certain feature. Finally, evaluating the degree of distinctiveness of the feature vector according to the result. Among them, the effective feature vector is whose degree of distinctiveness exceeds the set threshold. The purpose of this paper is to select out the effective features from the extracted original feature set. In this way, it can reduce the dimensionality of the features so as to reduce the space-time overhead of subsequent detection. The experimental results show that the proposed algorithm is feasible and it has some advantages over other selection algorithms.

Discovering highly informative feature set over high dimensions

KAUST Repository

Zhang, Chongsheng; Masseglia, Florent; Zhang, Xiangliang

2012-01-01

For many textual collections, the number of features is often overly large. These features can be very redundant, it is therefore desirable to have a small, succinct, yet highly informative collection of features that describes the key characteristics of a dataset. Information theory is one such tool for us to obtain this feature collection. With this paper, we mainly contribute to the improvement of efficiency for the process of selecting the most informative feature set over high-dimensional unlabeled data. We propose a heuristic theory for informative feature set selection from high dimensional data. Moreover, we design data structures that enable us to compute the entropies of the candidate feature sets efficiently. We also develop a simple pruning strategy that eliminates the hopeless candidates at each forward selection step. We test our method through experiments on real-world data sets, showing that our proposal is very efficient. © 2012 IEEE.

Discovering highly informative feature set over high dimensions

KAUST Repository

Zhang, Chongsheng

2012-11-01

For many textual collections, the number of features is often overly large. These features can be very redundant, it is therefore desirable to have a small, succinct, yet highly informative collection of features that describes the key characteristics of a dataset. Information theory is one such tool for us to obtain this feature collection. With this paper, we mainly contribute to the improvement of efficiency for the process of selecting the most informative feature set over high-dimensional unlabeled data. We propose a heuristic theory for informative feature set selection from high dimensional data. Moreover, we design data structures that enable us to compute the entropies of the candidate feature sets efficiently. We also develop a simple pruning strategy that eliminates the hopeless candidates at each forward selection step. We test our method through experiments on real-world data sets, showing that our proposal is very efficient. © 2012 IEEE.

Sexual dimorphism in medulloblastoma features.

Science.gov (United States)

Zannoni, Gian Franco; Ciucci, Alessandra; Marucci, Gianluca; Travaglia, Daniele; Stigliano, Egidio; Foschini, Maria Pia; Scambia, Giovanni; Gallo, Daniela

2016-03-01

Male sex is a risk factor for medulloblastoma (MB), and is also a negative predictor for clinical outcome. The aim of this study was to assess sex differences in tumour biological features and hormone receptor profiles in a cohort of MB patients. Sixty-four MBs and five normal cerebella were included in the study. Cell proliferation (Ki67), apoptosis (cleaved caspase-3) and microvessel density (CD31) were evaluated in tumours by immunohistochemistry. Tissues were analysed for oestrogen receptor (ER)α, ERβ1, ERβ2, ERβ5 and androgen receptor (AR) expression. The results demonstrated sex-specific features in MBs, with tumours from females showing a higher apoptosis/proliferation ratio and less tumour vascularization than tumours from males. MBs were negative for ERα and AR, but expressed ERβ isoforms at similar levels between the sexes. Altogether, these findings indicate that signalling mechanisms that control cell turnover and angiogenesis operate more efficiently in females than in males. The lack of sex differences in the hormone receptor profiles suggests that circulating oestrogens could be the major determinants of the sexual dimorphism observed in MB features. Here, we provide molecular support for epidemiological data showing sex differences in MB incidence and outcome, completely defining the hormone receptor profile of the tumours. © 2015 John Wiley & Sons Ltd.

Imaging features of thalassemia

Energy Technology Data Exchange (ETDEWEB)

Tunaci, M.; Tunaci, A.; Engin, G.; Oezkorkmaz, B.; Acunas, G.; Acunas, B. [Dept. of Radiology, Istanbul Univ. (Turkey); Dincol, G. [Dept. of Internal Medicine, Istanbul Univ. (Turkey)

1999-07-01

Thalassemia is a kind of chronic, inherited, microcytic anemia characterized by defective hemoglobin synthesis and ineffective erythropoiesis. In all thalassemias clinical features that result from anemia, transfusional, and absorptive iron overload are similar but vary in severity. The radiographic features of {beta}-thalassemia are due in large part to marrow hyperplasia. Markedly expanded marrow space lead to various skeletal manifestations including spine, skull, facial bones, and ribs. Extramedullary hematopoiesis (ExmH), hemosiderosis, and cholelithiasis are among the non-skeletal manifestations of thalassemia. The skeletal X-ray findings show characteristics of chronic overactivity of the marrow. In this article both skeletal and non-skeletal manifestations of thalassemia are discussed with an overview of X-ray findings, including MRI and CT findings. (orig.)

Imaging features of thalassemia

International Nuclear Information System (INIS)

Tunaci, M.; Tunaci, A.; Engin, G.; Oezkorkmaz, B.; Acunas, G.; Acunas, B.; Dincol, G.

1999-01-01

Thalassemia is a kind of chronic, inherited, microcytic anemia characterized by defective hemoglobin synthesis and ineffective erythropoiesis. In all thalassemias clinical features that result from anemia, transfusional, and absorptive iron overload are similar but vary in severity. The radiographic features of β-thalassemia are due in large part to marrow hyperplasia. Markedly expanded marrow space lead to various skeletal manifestations including spine, skull, facial bones, and ribs. Extramedullary hematopoiesis (ExmH), hemosiderosis, and cholelithiasis are among the non-skeletal manifestations of thalassemia. The skeletal X-ray findings show characteristics of chronic overactivity of the marrow. In this article both skeletal and non-skeletal manifestations of thalassemia are discussed with an overview of X-ray findings, including MRI and CT findings. (orig.)

Effective Feature Selection for Classification of Promoter Sequences.

Directory of Open Access Journals (Sweden)

Kouser K

Full Text Available Exploring novel computational methods in making sense of biological data has not only been a necessity, but also productive. A part of this trend is the search for more efficient in silico methods/tools for analysis of promoters, which are parts of DNA sequences that are involved in regulation of expression of genes into other functional molecules. Promoter regions vary greatly in their function based on the sequence of nucleotides and the arrangement of protein-binding short-regions called motifs. In fact, the regulatory nature of the promoters seems to be largely driven by the selective presence and/or the arrangement of these motifs. Here, we explore computational classification of promoter sequences based on the pattern of motif distributions, as such classification can pave a new way of functional analysis of promoters and to discover the functionally crucial motifs. We make use of Position Specific Motif Matrix (PSMM features for exploring the possibility of accurately classifying promoter sequences using some of the popular classification techniques. The classification results on the complete feature set are low, perhaps due to the huge number of features. We propose two ways of reducing features. Our test results show improvement in the classification output after the reduction of features. The results also show that decision trees outperform SVM (Support Vector Machine, KNN (K Nearest Neighbor and ensemble classifier LibD3C, particularly with reduced features. The proposed feature selection methods outperform some of the popular feature transformation methods such as PCA and SVD. Also, the methods proposed are as accurate as MRMR (feature selection method but much faster than MRMR. Such methods could be useful to categorize new promoters and explore regulatory mechanisms of gene expressions in complex eukaryotic species.

The origin and evolution of terrestrial and Martian rock labyrinths

Science.gov (United States)

Brook, G. A.

1984-01-01

The morphological characteristics and evolutionary development of rock labyrinths on Earth (in sandstone, volcanics, and carbonates) are compared with those on Mars. On Earth rock labyrinths originate as parallel, an echelon, or intersecting narrow grabens, or develop where fault and joint networks are selectively eroded. Labyrinths frequently contain both downfaulted and erosional elements. Closed labyrinths contain depressions; open labyrinths do not, they are simple part of a fluvial network generally of low order. As closed labyrinths made up of intersecting grabens or made up of connected erosional depressions are extremely common on Mars, the research focussed on an understanding of these labyrinth types. Field investigations were carried out in Canyonlands National Park, Utah, and in the Chirachahua Mountains of Arizona. Martian labyrinths were investigated using Viking orbiter images. In addition, research was undertaken on apparent thermokarst features in Lunae Planum and Chryse Planitia where closed depressions are numerous and resemble atlas topography.

Modeling Megacusps and Dune Erosion

Science.gov (United States)

Orzech, M.; Reniers, A. J.; Thornton, E. B.

2009-12-01

Megacusps are large, concave, erosional features of beaches, of O(200m) alongshore wavelength, which sometimes occur when rip channel bathymetry is present. It is commonly hypothesized that erosion of the dune and back beach will be greater at the alongshore locations of the megacusp embayments, principally because the beach width is narrower there and larger waves can more easily reach the dune toe (e.g., Short, J. Geol., 1979, Thornton, et al., Mar. Geol., 2007). At present, available field data in southern Monterey Bay provide some support for this hypothesis, but not enough to fully confirm or refute it. This analysis utilizes XBeach, a 2DH nearshore sediment transport model, to test the above hypothesis under a range of wave conditions over several idealized rip-megacusp bathymetries backed by dunes. Model results suggest that while specific wave conditions may result in erosional hot spots at megacusp embayments, other factors such as tides, wave direction, and surf zone bathymetry can often play an equal or stronger role.

Discriminating Induced-Microearthquakes Using New Seismic Features

Science.gov (United States)

Mousavi, S. M.; Horton, S.

2016-12-01

We studied characteristics of induced-microearthquakes on the basis of the waveforms recorded on a limited number of surface receivers using machine-learning techniques. Forty features in the time, frequency, and time-frequency domains were measured on each waveform, and several techniques such as correlation-based feature selection, Artificial Neural Networks (ANNs), Logistic Regression (LR) and X-mean were used as research tools to explore the relationship between these seismic features and source parameters. The results show that spectral features have the highest correlation to source depth. Two new measurements developed as seismic features for this study, spectral centroids and 2D cross-correlations in the time-frequency domain, performed better than the common seismic measurements. These features can be used by machine learning techniques for efficient automatic classification of low energy signals recorded at one or more seismic stations. We applied the technique to 440 microearthquakes-1.7Reference: Mousavi, S.M., S.P. Horton, C. A. Langston, B. Samei, (2016) Seismic features and automatic discrimination of deep and shallow induced-microearthquakes using neural network and logistic regression, Geophys. J. Int. doi: 10.1093/gji/ggw258.

Identifying significant environmental features using feature recognition.

Science.gov (United States)

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...

Disruption of visual feature binding in working memory.

Science.gov (United States)

Ueno, Taiji; Allen, Richard J; Baddeley, Alan D; Hitch, Graham J; Saito, Satoru

2011-01-01

In a series of five experiments, we studied the effect of a visual suffix on the retention in short-term visual memory of both individual visual features and objects involving the binding of two features. Experiments 1A, 1B, and 2 involved suffixes consisting of features external to the to-be-remembered set and revealed a modest but equivalent disruption on individual and bound feature conditions. Experiments 3A and 3B involved suffixes comprising features that could potentially have formed part of the to-be-remembered set (but did not on that trial). Both experiments showed greater disruption of retention for objects comprising bound features than for their individual features. The results are interpreted as differentiating two components of suffix interference, one affecting memory for features and bindings equally, the other affecting memory for bindings. The general component is tentatively identified with the attentional cost of operating a filter to prevent the suffix from entering visual working memory, whereas the specific component is attributed to the particular fragility of bound representations when the filter fails.

A Feature Subset Selection Method Based On High-Dimensional Mutual Information

Directory of Open Access Journals (Sweden)

Chee Keong Kwoh

2011-04-01

Full Text Available Feature selection is an important step in building accurate classifiers and provides better understanding of the data sets. In this paper, we propose a feature subset selection method based on high-dimensional mutual information. We also propose to use the entropy of the class attribute as a criterion to determine the appropriate subset of features when building classifiers. We prove that if the mutual information between a feature set X and the class attribute Y equals to the entropy of Y , then X is a Markov Blanket of Y . We show that in some cases, it is infeasible to approximate the high-dimensional mutual information with algebraic combinations of pairwise mutual information in any forms. In addition, the exhaustive searches of all combinations of features are prerequisite for finding the optimal feature subsets for classifying these kinds of data sets. We show that our approach outperforms existing filter feature subset selection methods for most of the 24 selected benchmark data sets.

A Polygon and Point-Based Approach to Matching Geospatial Features

Directory of Open Access Journals (Sweden)

Juan J. Ruiz-Lendínez

2017-12-01

Full Text Available A methodology for matching bidimensional entities is presented in this paper. The matching is proposed for both area and point features extracted from geographical databases. The procedure used to obtain homologous entities is achieved in a two-step process: The first matching, polygon to polygon matching (inter-element matching, is obtained by means of a genetic algorithm that allows the classifying of area features from two geographical databases. After this, we apply a point to point matching (intra-element matching based on the comparison of changes in their turning functions. This study shows that genetic algorithms are suitable for matching polygon features even if these features are quite different. Our results show up to 40% of matched polygons with differences in geometrical attributes. With regards to point matching, the vertex from homologous polygons, the function and threshold values proposed in this paper show a useful method for obtaining precise vertex matching.

Spatial and Time Domain Feature of ERP Speller System Extracted via Convolutional Neural Network.

Science.gov (United States)

Yoon, Jaehong; Lee, Jungnyun; Whang, Mincheol

2018-01-01

Feature of event-related potential (ERP) has not been completely understood and illiteracy problem remains unsolved. To this end, P300 peak has been used as the feature of ERP in most brain-computer interface applications, but subjects who do not show such peak are common. Recent development of convolutional neural network provides a way to analyze spatial and temporal features of ERP. Here, we train the convolutional neural network with 2 convolutional layers whose feature maps represented spatial and temporal features of event-related potential. We have found that nonilliterate subjects' ERP show high correlation between occipital lobe and parietal lobe, whereas illiterate subjects only show correlation between neural activities from frontal lobe and central lobe. The nonilliterates showed peaks in P300, P500, and P700, whereas illiterates mostly showed peaks in around P700. P700 was strong in both subjects. We found that P700 peak may be the key feature of ERP as it appears in both illiterate and nonilliterate subjects.

Feature selection from a facial image for distinction of sasang constitution.

Science.gov (United States)

Koo, Imhoi; Kim, Jong Yeol; Kim, Myoung Geun; Kim, Keun Ho

2009-09-01

Recently, oriental medicine has received attention for providing personalized medicine through consideration of the unique nature and constitution of individual patients. With the eventual goal of globalization, the current trend in oriental medicine research is the standardization by adopting western scientific methods, which could represent a scientific revolution. The purpose of this study is to establish methods for finding statistically significant features in a facial image with respect to distinguishing constitution and to show the meaning of those features. From facial photo images, facial elements are analyzed in terms of the distance, angle and the distance ratios, for which there are 1225, 61 250 and 749 700 features, respectively. Due to the very large number of facial features, it is quite difficult to determine truly meaningful features. We suggest a process for the efficient analysis of facial features including the removal of outliers, control for missing data to guarantee data confidence and calculation of statistical significance by applying ANOVA. We show the statistical properties of selected features according to different constitutions using the nine distances, 10 angles and 10 rates of distance features that are finally established. Additionally, the Sasang constitutional meaning of the selected features is shown here.

Classification of Textures Using Filter Based Local Feature Extraction

Directory of Open Access Journals (Sweden)

Bocekci Veysel Gokhan

2016-01-01

Full Text Available In this work local features are used in feature extraction process in image processing for textures. The local binary pattern feature extraction method from textures are introduced. Filtering is also used during the feature extraction process for getting discriminative features. To show the effectiveness of the algorithm before the extraction process, three different noise are added to both train and test images. Wiener filter and median filter are used to remove the noise from images. We evaluate the performance of the method with Naïve Bayesian classifier. We conduct the comparative analysis on benchmark dataset with different filtering and size. Our experiments demonstrate that feature extraction process combine with filtering give promising results on noisy images.

Segmented Coastal Uplift Along an Erosional Subduction Margin, Northern Hikurangi Fore Arc, North Island, New Zealand

Science.gov (United States)

Marshall, J. S.; Litchfield, N. J.; Berryman, K. R.; Clark, K.; Cochran, U. A.

2013-12-01

The Hikurangi subduction margin along North Island, New Zealand accommodates oblique convergence of the Pacific plate westward beneath the Australian plate at 45 mm/yr. Along the southern margin, frontal accretion and pronounced forearc uplift occur inboard of the subducting Hikurangi plateau. In the north, subduction erosion and segmented uplift occur inboard of subducting seamounts along the plateau flank. Prior workers have established a robust foundation for coastal terrace studies along the northern Hikurangi margin (e.g., Berryman et al., 1989; Ota et al., 1992; Berryman, 1993; Wilson et al., 2006, 2007; Clark et al., 2010; Litchfield et al, 2007, 2010). New field observations presented here provide additional constraints on terrace uplift along this erosional subduction margin. Along Raukumara Peninsula (north of Poverty Bay), multiple Holocene to late Pleistocene marine and fluvial terraces occur at varying elevations, recording differential uplift across six coastal segments from Gisborne to East Cape (Ota et al., 1992; Wilson et al., 2007). In this study, two to three late Pleistocene terraces were observed on rocky headlands within the first segment (Gisborne to Whangara) at elevations of 80-185 m above msl. Preliminary correlation with OIS 5a-e sea level high stands (80-125 ka) indicates net uplift at 1.2-1.5 m/ky. Uplifted Holocene wavecut platforms occur in steps along the seaward edge of these terraces, consistent with coseismic uplift. At Makorori Point, an uplifted bench occurs along the modern seacliff at 2.3 m above the cliff base. A fossil gastropod shell from paleo-beach gravels on the platform inner edge yielded a calibrated radiocarbon age of 1680 ×110 ybp. At Turihaua Point, a ≥1 m thick deposit of Holocene beach sands overlies an uplifted wavecut platform at ≥1.5 m above mean sea level. Carbonate-cemented beachrock at the base of the sand deposit yields a calibrated radiocarbon age of 2990 ×70 ybp. At Mahia Peninsula (between Poverty

Shielding voices: The modulation of binding processes between voice features and response features by task representations.

Science.gov (United States)

Bogon, Johanna; Eisenbarth, Hedwig; Landgraf, Steffen; Dreisbach, Gesine

2017-09-01

Vocal events offer not only semantic-linguistic content but also information about the identity and the emotional-motivational state of the speaker. Furthermore, most vocal events have implications for our actions and therefore include action-related features. But the relevance and irrelevance of vocal features varies from task to task. The present study investigates binding processes for perceptual and action-related features of spoken words and their modulation by the task representation of the listener. Participants reacted with two response keys to eight different words spoken by a male or a female voice (Experiment 1) or spoken by an angry or neutral male voice (Experiment 2). There were two instruction conditions: half of participants learned eight stimulus-response mappings by rote (SR), and half of participants applied a binary task rule (TR). In both experiments, SR instructed participants showed clear evidence for binding processes between voice and response features indicated by an interaction between the irrelevant voice feature and the response. By contrast, as indicated by a three-way interaction with instruction, no such binding was found in the TR instructed group. These results are suggestive of binding and shielding as two adaptive mechanisms that ensure successful communication and action in a dynamic social environment.

Color and neighbor edge directional difference feature for image retrieval

Institute of Scientific and Technical Information of China (English)

Chaobing Huang; Shengsheng Yu; Jingli Zhou; Hongwei Lu

2005-01-01

@@ A novel image feature termed neighbor edge directional difference unit histogram is proposed, in which the neighbor edge directional difference unit is defined and computed for every pixel in the image, and is used to generate the neighbor edge directional difference unit histogram. This histogram and color histogram are used as feature indexes to retrieve color image. The feature is invariant to image scaling and translation and has more powerful descriptive for the natural color images. Experimental results show that the feature can achieve better retrieval performance than other color-spatial features.

Featureous: infrastructure for feature-centric analysis of object-oriented software

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2010-01-01

The decentralized nature of collaborations between objects in object-oriented software makes it difficult to understand how user-observable program features are implemented and how their implementations relate to each other. It is worthwhile to improve this situation, since feature-centric program...... understanding and modification are essential during software evolution and maintenance. In this paper, we present an infrastructure built on top of the NetBeans IDE called Featureous that allows for rapid construction of tools for feature-centric analysis of object-oriented software. Our infrastructure...... encompasses a lightweight feature location mechanism, a number of analytical views and an API allowing for addition of third-party extensions. To form a common conceptual framework for future feature-centric extensions, we propose to structure feature centric analysis along three dimensions: perspective...

Processes of Terrace Formation on the Piedmont of the Santa Cruz River Valley During Quaternary Time, Green Valley-Tubac Area, Southeastern Arizona

Science.gov (United States)

Lindsey, David A.; Van Gosen, Bradley S.

2010-01-01

In this report we describe a series of stepped Quaternary terraces on some piedmont tributaries of the Santa Cruz River valley in southeastern Arizona. These terraces began to form in early Pleistocene time, after major basin-and-range faulting ceased, with lateral planation of basin fill and deposition of thin fans of alluvium. At the end of this cycle of erosion and deposition, tributaries of the Santa Cruz River began the process of dissection and terrace formation that continues to the present. Vertical cutting alternated with periods of equilibrium, during which streams cut laterally and left thin deposits of channel fill. The distribution of terraces was mapped and compiled with adjacent mapping to produce a regional picture of piedmont stream history in the middle part of the Santa Cruz River valley. For selected tributaries, the thickness of terrace fill was measured, particle size and lithology of gravel were determined, and sedimentary features were photographed and described. Mapping of terrace stratigraphy revealed that on two tributaries, Madera Canyon Wash and Montosa Canyon Wash, stream piracy has played an important role in piedmont landscape development. On two other tributaries, Cottonwood Canyon Wash and Josephine Canyon Wash, rapid downcutting preempted piracy. Two types of terraces are recognized: erosional and depositional. Gravel in thin erosional terraces has Trask sorting coefficients and sedimentary structures typical of streamflood deposits, replete with bar-and-swale surface topography on young terraces. Erosional-terrace fill represents the channel fill of the stream that cuts the terrace; the thickness of the fill indicates the depth of channel scour. In contrast to erosional terraces, depositional terraces show evidence of repeated deposition and net aggradation, as indicated by their thickness (as much as 20+ m) and weakly bedded structure. Depositional terraces are common below mountain-front canyon mouths where streams drop their

Color Doppler Ultrasonographic Features of Hashimoto's Thyroiditis

Energy Technology Data Exchange (ETDEWEB)

Lee, Joo Hyuk; Kim, Mie Young; Rho, Eun Jin; Yi, Jeong Geun; Han, Chun Hwan [Kangnam General Hospital Public Corporation, Seoul (Korea, Republic of); Hwang, Hee Yong [Choong Ang Gil Hospital, Incheon (Korea, Republic of)

1995-06-15

Color Doppler ultrasonographic(US) features of 28 patients with Hashimato's thyroiditis were evaluated with regard to echo and color-flow patterns. Correlation of color-flow pattern with thyroid function was performed. All 28 patients showed varying degrees of diffuse enlargement of the thyroid gland and a heterogeneous echo pattern.Color-flow pattern of increased blood flow. Low to moderate, focally increased blood flow was seen in 26 patients(92.8%). Of these 26 patients, 24 patients showed subclinical hypothyroidism or euthyroidism. Two patients who showed hyperthyroidism showed several pieces of focally increased color flow, Which was noted during both systole and diastole. Diffuse, multifocal color-flow throughout thyroid gland was seen in two patients with Hashimato's thyroiditis: one with clinical hypothyroidism and the other with subclinical hypothyroidism. Even though Hashimoto's thyroiditis showed variable color-flow patterns, we believe that heterogenous parenchymal echopattern with low or moderately increased flow is a rather characteristic feature of Hashimoto's thyroiditis, and we suggest that color Doppler US provides additional information for evaluation of Hashimoto's thyroiditis

Color Doppler Ultrasonographic Features of Hashimoto's Thyroiditis

International Nuclear Information System (INIS)

Lee, Joo Hyuk; Kim, Mie Young; Rho, Eun Jin; Yi, Jeong Geun; Han, Chun Hwan; Hwang, Hee Yong

1995-01-01

Color Doppler ultrasonographic(US) features of 28 patients with Hashimato's thyroiditis were evaluated with regard to echo and color-flow patterns. Correlation of color-flow pattern with thyroid function was performed. All 28 patients showed varying degrees of diffuse enlargement of the thyroid gland and a heterogeneous echo pattern.Color-flow pattern of increased blood flow. Low to moderate, focally increased blood flow was seen in 26 patients(92.8%). Of these 26 patients, 24 patients showed subclinical hypothyroidism or euthyroidism. Two patients who showed hyperthyroidism showed several pieces of focally increased color flow, Which was noted during both systole and diastole. Diffuse, multifocal color-flow throughout thyroid gland was seen in two patients with Hashimato's thyroiditis: one with clinical hypothyroidism and the other with subclinical hypothyroidism. Even though Hashimoto's thyroiditis showed variable color-flow patterns, we believe that heterogenous parenchymal echopattern with low or moderately increased flow is a rather characteristic feature of Hashimoto's thyroiditis, and we suggest that color Doppler US provides additional information for evaluation of Hashimoto's thyroiditis

Pedestrian count estimation using texture feature with spatial distribution

Directory of Open Access Journals (Sweden)

Hongyu Hu

2016-12-01

Full Text Available We present a novel pedestrian count estimation approach based on global image descriptors formed from multi-scale texture features that considers spatial distribution. For regions of interest, local texture features are represented based on histograms of multi-scale block local binary pattern, which jointly constitute the feature vector of the whole image. Therefore, to achieve an effective estimation of pedestrian count, principal component analysis is used to reduce the dimension of the global representation features, and a fitting model between image global features and pedestrian count is constructed via support vector regression. The experimental result shows that the proposed method exhibits high accuracy on pedestrian count estimation and can be applied well in the real world.

Research on oral test modeling based on multi-feature fusion

Science.gov (United States)

Shi, Yuliang; Tao, Yiyue; Lei, Jun

2018-04-01

In this paper, the spectrum of speech signal is taken as an input of feature extraction. The advantage of PCNN in image segmentation and other processing is used to process the speech spectrum and extract features. And a new method combining speech signal processing and image processing is explored. At the same time of using the features of the speech map, adding the MFCC to establish the spectral features and integrating them with the features of the spectrogram to further improve the accuracy of the spoken language recognition. Considering that the input features are more complicated and distinguishable, we use Support Vector Machine (SVM) to construct the classifier, and then compare the extracted test voice features with the standard voice features to achieve the spoken standard detection. Experiments show that the method of extracting features from spectrograms using PCNN is feasible, and the fusion of image features and spectral features can improve the detection accuracy.

MRI features of peripheral traumatic neuromas

Energy Technology Data Exchange (ETDEWEB)

Ahlawat, Shivani [Johns Hopkins University School of Medicine, Musculoskeletal Radiology Section, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, MD (United States); Belzberg, Allan J. [The Johns Hopkins Hospital, Department of Neurosurgery, Baltimore, MD (United States); Montgomery, Elizabeth A. [The Johns Hopkins Hospital, Pathology, Oncology and Orthopedic Surgery, Baltimore, MD (United States); Fayad, Laura M. [Department of Orthopedic Surgery, Department of Radiology and Radiological Science, Musculoskeletal Imaging Section Chief, The Johns Hopkins Medical Institutions, Baltimore, MD (United States); The Johns Hopkins Medical Institutions, Department of Orthopedic Surgery, Baltimore, MD (United States)

2016-04-15

To describe the MRI appearance of traumatic neuromas on non-contrast and contrast-enhanced MRI sequences. This IRB-approved, HIPAA-compliant study retrospectively reviewed 13 subjects with 20 neuromas. Two observers reviewed pre-operative MRIs for imaging features of neuroma (size, margin, capsule, signal intensity, heterogeneity, enhancement, neurogenic features and denervation) and the nerve segment distal to the traumatic neuroma. Descriptive statistics were reported. Pearson's correlation was used to examine the relationship between size of neuroma and parent nerve. Of 20 neuromas, 13 were neuromas-in-continuity and seven were end-bulb neuromas. Neuromas had a mean size of 1.5 cm (range 0.6-4.8 cm), 100 % (20/20) had indistinct margins and 0 % (0/20) had a capsule. Eighty-eight percent (7/8) showed enhancement. All 100 % (20/20) had tail sign; 35 % (7/20) demonstrated discontinuity from the parent nerve. None showed a target sign. There was moderate positive correlation (r = 0.68, p = 0.001) with larger neuromas arising from larger parent nerves. MRI evaluation of the nerve segment distal to the neuroma showed increased size (mean size 0.5 cm ± 0.4 cm) compared to the parent nerve (mean size 0.3 cm ± 0.2 cm). Since MRI features of neuromas include enhancement, intravenous contrast medium cannot be used to distinguish neuromas from peripheral nerve sheath tumours. The clinical history of trauma with the lack of a target sign are likely the most useful clues. (orig.)

Feature Article

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. Feature Article. Articles in Resonance – Journal of Science Education. Volume 1 Issue 1 January 1996 pp 80-85 Feature Article. What's New in Computers Windows 95 · Vijnan Shastri · More Details Fulltext PDF. Volume 1 Issue 1 January 1996 pp 86-89 Feature ...

Featureous: A Tool for Feature-Centric Analysis of Java Software

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2010-01-01

Feature-centric comprehension of source code is necessary for incorporating user-requested modifications during software evolution and maintenance. However, such comprehension is difficult to achieve in case of large object-oriented programs due to the size, complexity, and implicit character...... of mappings between features and source code. To support programmers in overcoming these difficulties, we present a feature-centric analysis tool, Featureous. Our tool extends the NetBeans IDE with mechanisms for efficient location of feature implementations in legacy source code, and an extensive analysis...

Learning features for tissue classification with the classification restricted Boltzmann machine

DEFF Research Database (Denmark)

van Tulder, Gijs; de Bruijne, Marleen

2014-01-01

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

Film showing - Higgs: into the heart of imagination

CERN Multimedia

CERN Bulletin

2010-01-01

On 29 April at 7pm Dutch filmmakers, Hannie van den Bergh and Jan van den Berg, will introduce their directorial debut, Higgs: into the heart of imagination in CERN’s Main Auditorium.   This documentary is about the curiousity, passion and imaginative powers of science. Featuring physicists working at CERN, in particular in ATLAS, and filmed over four years, the film-makers have created a cinematic journey into the heart of imagination. They follow Stan Bentvelsen, head of the Dutch research group at CERN, and watch as he prepares his team for the start of the LHC, as well as the scientific competition to find the elusive Higgs particle. The film also features Peter Higgs as he discusses his work from 1964. The directors have created theatre productions and other multimedia projects under the title The Imagination of Invisible Dimensions, which allow for adventurous dialogues between art and science. All are welcome to attend this showing and afterwards there will be a short question...

Familiarity and Within-Person Facial Variability: The Importance of the Internal and External Features.

Science.gov (United States)

Kramer, Robin S S; Manesi, Zoi; Towler, Alice; Reynolds, Michael G; Burton, A Mike

2018-01-01

As faces become familiar, we come to rely more on their internal features for recognition and matching tasks. Here, we assess whether this same pattern is also observed for a card sorting task. Participants sorted photos showing either the full face, only the internal features, or only the external features into multiple piles, one pile per identity. In Experiments 1 and 2, we showed the standard advantage for familiar faces-sorting was more accurate and showed very few errors in comparison with unfamiliar faces. However, for both familiar and unfamiliar faces, sorting was less accurate for external features and equivalent for internal and full faces. In Experiment 3, we asked whether external features can ever be used to make an accurate sort. Using familiar faces and instructions on the number of identities present, we nevertheless found worse performance for the external in comparison with the internal features, suggesting that less identity information was available in the former. Taken together, we show that full faces and internal features are similarly informative with regard to identity. In comparison, external features contain less identity information and produce worse card sorting performance. This research extends current thinking on the shift in focus, both in attention and importance, toward the internal features and away from the external features as familiarity with a face increases.

Spatial and Time Domain Feature of ERP Speller System Extracted via Convolutional Neural Network

Directory of Open Access Journals (Sweden)

Jaehong Yoon

2018-01-01

Full Text Available Feature of event-related potential (ERP has not been completely understood and illiteracy problem remains unsolved. To this end, P300 peak has been used as the feature of ERP in most brain–computer interface applications, but subjects who do not show such peak are common. Recent development of convolutional neural network provides a way to analyze spatial and temporal features of ERP. Here, we train the convolutional neural network with 2 convolutional layers whose feature maps represented spatial and temporal features of event-related potential. We have found that nonilliterate subjects’ ERP show high correlation between occipital lobe and parietal lobe, whereas illiterate subjects only show correlation between neural activities from frontal lobe and central lobe. The nonilliterates showed peaks in P300, P500, and P700, whereas illiterates mostly showed peaks in around P700. P700 was strong in both subjects. We found that P700 peak may be the key feature of ERP as it appears in both illiterate and nonilliterate subjects.

Feature Selection from a Facial Image for Distinction of Sasang Constitution

Directory of Open Access Journals (Sweden)

Imhoi Koo

2009-01-01

Full Text Available Recently, oriental medicine has received attention for providing personalized medicine through consideration of the unique nature and constitution of individual patients. With the eventual goal of globalization, the current trend in oriental medicine research is the standardization by adopting western scientific methods, which could represent a scientific revolution. The purpose of this study is to establish methods for finding statistically significant features in a facial image with respect to distinguishing constitution and to show the meaning of those features. From facial photo images, facial elements are analyzed in terms of the distance, angle and the distance ratios, for which there are 1225, 61 250 and 749 700 features, respectively. Due to the very large number of facial features, it is quite difficult to determine truly meaningful features. We suggest a process for the efficient analysis of facial features including the removal of outliers, control for missing data to guarantee data confidence and calculation of statistical significance by applying ANOVA. We show the statistical properties of selected features according to different constitutions using the nine distances, 10 angles and 10 rates of distance features that are finally established. Additionally, the Sasang constitutional meaning of the selected features is shown here.

Feature Selection from a Facial Image for Distinction of Sasang Constitution

Science.gov (United States)

Koo, Imhoi; Kim, Jong Yeol; Kim, Myoung Geun

2009-01-01

Recently, oriental medicine has received attention for providing personalized medicine through consideration of the unique nature and constitution of individual patients. With the eventual goal of globalization, the current trend in oriental medicine research is the standardization by adopting western scientific methods, which could represent a scientific revolution. The purpose of this study is to establish methods for finding statistically significant features in a facial image with respect to distinguishing constitution and to show the meaning of those features. From facial photo images, facial elements are analyzed in terms of the distance, angle and the distance ratios, for which there are 1225, 61 250 and 749 700 features, respectively. Due to the very large number of facial features, it is quite difficult to determine truly meaningful features. We suggest a process for the efficient analysis of facial features including the removal of outliers, control for missing data to guarantee data confidence and calculation of statistical significance by applying ANOVA. We show the statistical properties of selected features according to different constitutions using the nine distances, 10 angles and 10 rates of distance features that are finally established. Additionally, the Sasang constitutional meaning of the selected features is shown here. PMID:19745013

18F-FDG PET radiomics approaches: comparing and clustering features in cervical cancer.

Science.gov (United States)

Tsujikawa, Tetsuya; Rahman, Tasmiah; Yamamoto, Makoto; Yamada, Shizuka; Tsuyoshi, Hideaki; Kiyono, Yasushi; Kimura, Hirohiko; Yoshida, Yoshio; Okazawa, Hidehiko

2017-11-01

The aims of our study were to find the textural features on 18 F-FDG PET/CT which reflect the different histological architectures between cervical cancer subtypes and to make a visual assessment of the association between 18 F-FDG PET textural features in cervical cancer. Eighty-three cervical cancer patients [62 squamous cell carcinomas (SCCs) and 21 non-SCCs (NSCCs)] who had undergone pretreatment 18 F-FDG PET/CT were enrolled. A texture analysis was performed on PET/CT images, from which 18 PET radiomics features were extracted including first-order features such as standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), second- and high-order textural features using SUV histogram, normalized gray-level co-occurrence matrix (NGLCM), and neighborhood gray-tone difference matrix, respectively. These features were compared between SCC and NSCC using a Bonferroni adjusted P value threshold of 0.0028 (0.05/18). To assess the association between PET features, a heat map analysis with hierarchical clustering, one of the radiomics approaches, was performed. Among 18 PET features, correlation, a second-order textural feature derived from NGLCM, was a stable parameter and it was the only feature which showed a robust trend toward significant difference between SCC and NSCC. Cervical SCC showed a higher correlation (0.70 ± 0.07) than NSCC (0.64 ± 0.07, P = 0.0030). The other PET features did not show any significant differences between SCC and NSCC. A higher correlation in SCC might reflect higher structural integrity and stronger spatial/linear relationship of cancer cells compared with NSCC. A heat map with a PET feature dendrogram clearly showed 5 distinct clusters, where correlation belonged to a cluster including MTV and TLG. However, the association between correlation and MTV/TLG was not strong. Correlation was a relatively independent PET feature in cervical cancer. 18 F-FDG PET textural features might reflect the

Two-dimensional echocardiographic features of right ventricular infarction

International Nuclear Information System (INIS)

D'Arcy, B.; Nanda, N.C.

1982-01-01

Real-time, two-dimensional echocardiographic studies were performed in 10 patients with acute myocardial infarction who had clinical features suggestive of right ventricular involvement. All patients showed right ventricular wall motion abnormalities. In the four-chamber view, seven patients showed akinesis of the entire right ventricular diaphragmatic wall and three showed akinesis of segments of the diaphragmatic wall. Segmental dyskinetic areas involving the right ventricular free wall were identified in four patients. One patient showed a large right ventricular apical aneurysm. Other echocardiographic features included enlargement of the right ventricle in eight cases, paradoxical ventricular septal motion in seven cases, tricuspid incompetence in eight cases, dilation of the stomach in four cases and localized pericardial effusion in two cases. Right ventricular infarction was confirmed by radionuclide methods in seven patients, at surgery in one patient and at autopsy in two patients

Laboratory simulation of infrared astrophysical features

International Nuclear Information System (INIS)

Rose, L.A.

1979-01-01

Laboratory infrared emission and absorption spectra have been taken of terrestrial silicates, meteorites and lunar soils in the form of micrometer and sub-micrometer grains. The emission spectra were taken in a way that imitates telescopic observations. The purpose was to see which materials best simulate the 10 μm astrophysical feature. The emission spectra of dunite, fayalite and Allende give a good fit to the 10 μm broadband emission feature of comets Bennett and Kohoutek. A study of the effect of grain size on the presence of the 10 μm emission features of dunite shows that for particles larger than 37 μm no feature is seen. The emission spectrum of the Murray meteorite, a Type 2 carbonaceous chondrite, is quite similar to the intermediate resolution spectrum of comet Kohoutek in the 10 μm region. Hydrous silicates or amorphous magnesium silicates in combination with high-temperature condensates, such as olivine or anorthite, would yield spectra that match the intermediate resolution spectrum of comet Kohoutek in the 10 μm region. Glassy olivine and glassy anorthite in approximately equal proportions would also give a spectrum that is a good fit to the cometary 10 μm feature. (Auth.)

MR Imaging Features of Fibrocystic Change of the Breast

Science.gov (United States)

Chen, Jeon-Hor; Liu, Hui; Baek, Hyeon-Man; Nalcioglu, Orhan; Su, Min-Ying

2008-01-01

Purpose Studies specifically reporting MR imaging of fibrocystic change (FCC) of the breast are very few and its MR imaging features are not clearly known. The purpose of this study was to analyze the MR imaging features of FCC of the breast. Materials and Methods Thirty one patients of pathologically proved FCC of the breast were retrospectively reviewed. The MRI study was performed using a 1.5 T MR scanner with standard bilateral breast coil. The imaging protocol consisted of pre-contrast T1W imaging and dynamic contrast-enhanced axial T1W imaging. The MRI features were interpreted based on the morphologic and enhancement kinetic descriptors defined on ACR BIRADS-MRI lexicon. Results FCC of the breast had a wide spectrum of morphologic and kinetic features on MRI. Two types of FCC were found, including a more diffuse type of non-mass lesion (12/31, 39%) showing benign enhancement kinetic pattern with medium wash-in in early phase (9/10, 90%) and a focal mass type lesion (11/31, 35%) with enhancement kinetic usually showing rapid up-slope mimicking a breast cancer (8/11, 73%). Conclusion MRI is able to elaborate the diverse imaging features of fibrocystic change of the breast. Our result showed that FCC presenting as focal mass type lesion were usually over-diagnosed as malignancy. Understanding MR imaging of FCC is important to determine which cohort of patients should be followed up alone or receive aggressive management. PMID:18436406

Integration of heterogeneous features for remote sensing scene classification

Science.gov (United States)

Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

2018-01-01

Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.

Pluto's Paleoglaciation: Processes and Bounds.

Science.gov (United States)

Umurhan, O. M.; Howard, A. D.; White, O. L.; Moore, J. M.; Grundy, W. M.; Schenk, P.; Beyer, R. A.; McKinnon, W. B.; Singer, K. N.; Lauer, T.; Cheng, A. F.; Stern, A.; Weaver, H. A., Jr.; Young, L. A.; Ennico Smith, K.; Olkin, C.

2017-12-01

New Horizons imaging of Pluto's surface shows eroded landscapes reminiscent of assorted glaciated terrains found on the Earth such as alpine valleys, dendritic networks and others. For example, LORRI imaging of fluted craters show radially oriented ridging which also resembles Pluto's washboard terrain. Digital elevation modeling indicates that these down-gradient oriented ridges are about 3-4 km spaced apart with depths ranging from 0.2-0.5 km. Present day glaciation on Pluto is characterized by moving N2 ice blocks presumably riding over a H2O ice bedrock substrate. Assuming Pluto's ancient surface was sculpted by N2 glaciation, what remains a mystery is the specific nature of the glacial erosion mechanism(s) responsible for the observed features. To better resolve this puzzle, we perform landform evolution modeling of several glacial erosion processes known from terrestrial H2O ice glaciation studies. These terrestrial processes, which depend upon whether or not the glacier's base is wet or dry, include quarrying/plucking and fluvial erosion. We also consider new erosional processes (to be described in this presentation) which are unique to the highly insulating character of solid N2 including both phase change induced hydrofracture and geothermally driven basal melt. Until improvements in our knowledge of solid N2's rheology are made available (including its mechanical behavior as a binary/trinary mixture of CH4 and CO), it is difficult to assess with high precision which of the aforementioned erosion mechanisms are responsible for the observed surface etchings. Nevertheless, we consider a model crater surface and examine its erosional development due to flowing N2 glacial ice as built up over time according to N2 deposition rates based on GCM modeling of Pluto's ancient atmosphere. For given erosional mechanism our aim is to determine the permissible ranges of model input parameters (e.g., ice strength, flow rates, grain sizes, quarrying rates, etc.) that best

Saliency image of feature building for image quality assessment

Science.gov (United States)

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.

Boosting Discriminant Learners for Gait Recognition Using MPCA Features

Directory of Open Access Journals (Sweden)

Haiping Lu

2009-01-01

Full Text Available This paper proposes a boosted linear discriminant analysis (LDA solution on features extracted by the multilinear principal component analysis (MPCA to enhance gait recognition performance. Three-dimensional gait objects are projected in the MPCA space first to obtain low-dimensional tensorial features. Then, lower-dimensional vectorial features are obtained through discriminative feature selection. These feature vectors are then fed into an LDA-style booster, where several regularized and weakened LDA learners work together to produce a strong learner through a novel feature weighting and sampling process. The LDA learner employs a simple nearest-neighbor classifier with a weighted angle distance measure for classification. The experimental results on the NIST/USF “Gait Challenge” data-sets show that the proposed solution has successfully improved the gait recognition performance and outperformed several state-of-the-art gait recognition algorithms.

Detection of Fraudulent Emails by Employing Advanced Feature Abundance

DEFF Research Database (Denmark)

Nizamani, Sarwat; Memon, Nasrullah; Glasdam, Mathies

2014-01-01

In this paper, we present a fraudulent email detection model using advanced feature choice. We extracted various kinds of features and compared the performance of each category of features with the others in terms of the fraudulent email detection rate. The different types of features...... are incorporated step by step. The detection of fraudulent email has been considered as a classification problem and it is evaluated using various state-of-the art algorithms and on CCM [1] which is authors' previous cluster based classification model. The experiments have been performed on diverse feature sets...... and the different classification methods. The comparison of the results is also presented and the evaluations shows that for the fraudulent email detection tasks, the feature set is more important regardless of classification method. The results of the study suggest that the task of fraudulent emails detection...

Prominent feature extraction for review analysis: an empirical study

Science.gov (United States)

Agarwal, Basant; Mittal, Namita

2016-05-01

Sentiment analysis (SA) research has increased tremendously in recent times. SA aims to determine the sentiment orientation of a given text into positive or negative polarity. Motivation for SA research is the need for the industry to know the opinion of the users about their product from online portals, blogs, discussion boards and reviews and so on. Efficient features need to be extracted for machine-learning algorithm for better sentiment classification. In this paper, initially various features are extracted such as unigrams, bi-grams and dependency features from the text. In addition, new bi-tagged features are also extracted that conform to predefined part-of-speech patterns. Furthermore, various composite features are created using these features. Information gain (IG) and minimum redundancy maximum relevancy (mRMR) feature selection methods are used to eliminate the noisy and irrelevant features from the feature vector. Finally, machine-learning algorithms are used for classifying the review document into positive or negative class. Effects of different categories of features are investigated on four standard data-sets, namely, movie review and product (book, DVD and electronics) review data-sets. Experimental results show that composite features created from prominent features of unigram and bi-tagged features perform better than other features for sentiment classification. mRMR is a better feature selection method as compared with IG for sentiment classification. Boolean Multinomial Naïve Bayes) algorithm performs better than support vector machine classifier for SA in terms of accuracy and execution time.

Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval.

Science.gov (United States)

Zhang, Yu; Wu, Jianxin; Cai, Jianfei

2016-05-01

In large-scale visual recognition and image retrieval tasks, feature vectors, such as Fisher vector (FV) or the vector of locally aggregated descriptors (VLAD), have achieved state-of-the-art results. However, the combination of the large numbers of examples and high-dimensional vectors necessitates dimensionality reduction, in order to reduce its storage and CPU costs to a reasonable range. In spite of the popularity of various feature compression methods, this paper shows that the feature (dimension) selection is a better choice for high-dimensional FV/VLAD than the feature (dimension) compression methods, e.g., product quantization. We show that strong correlation among the feature dimensions in the FV and the VLAD may not exist, which renders feature selection a natural choice. We also show that, many dimensions in FV/VLAD are noise. Throwing them away using feature selection is better than compressing them and useful dimensions altogether using feature compression methods. To choose features, we propose an efficient importance sorting algorithm considering both the supervised and unsupervised cases, for visual recognition and image retrieval, respectively. Combining with the 1-bit quantization, feature selection has achieved both higher accuracy and less computational cost than feature compression methods, such as product quantization, on the FV and the VLAD image representations.

Detection of fraudulent emails by employing advanced feature abundance

Directory of Open Access Journals (Sweden)

Sarwat Nizamani

2014-11-01

Full Text Available In this paper, we present a fraudulent email detection model using advanced feature choice. We extracted various kinds of features and compared the performance of each category of features with the others in terms of the fraudulent email detection rate. The different types of features are incorporated step by step. The detection of fraudulent email has been considered as a classification problem and it is evaluated using various state-of-the art algorithms and on CCM (Nizamani et al., 2011 [1] which is authors’ previous cluster based classification model. The experiments have been performed on diverse feature sets and the different classification methods. The comparison of the results is also presented and the evaluation show that for the fraudulent email detection tasks, the feature set is more important regardless of classification method. The results of the study suggest that the task of fraudulent emails detection requires the better choice of feature set; while the choice of classification method is of less importance.

Salient Region Detection via Feature Combination and Discriminative Classifier

Directory of Open Access Journals (Sweden)

Deming Kong

2015-01-01

Full Text Available We introduce a novel approach to detect salient regions of an image via feature combination and discriminative classifier. Our method, which is based on hierarchical image abstraction, uses the logistic regression approach to map the regional feature vector to a saliency score. Four saliency cues are used in our approach, including color contrast in a global context, center-boundary priors, spatially compact color distribution, and objectness, which is as an atomic feature of segmented region in the image. By mapping a four-dimensional regional feature to fifteen-dimensional feature vector, we can linearly separate the salient regions from the clustered background by finding an optimal linear combination of feature coefficients in the fifteen-dimensional feature space and finally fuse the saliency maps across multiple levels. Furthermore, we introduce the weighted salient image center into our saliency analysis task. Extensive experiments on two large benchmark datasets show that the proposed approach achieves the best performance over several state-of-the-art approaches.

A feature-based approach to modeling protein-protein interaction hot spots.

Science.gov (United States)

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-05-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions.

A feature-based approach to modeling protein–protein interaction hot spots

Science.gov (United States)

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-01-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to π–related interactions, especially π · · · π interactions. PMID:19273533

Tectonics and sedimentary process in the continental talud in Uruguay

International Nuclear Information System (INIS)

De Santa Ana, H.; Soto, M.; Morales, E.; Tomasini, J.; Hernandez-Molina, F.; Veroslavsky, G.

2012-01-01

The morphology and evolution of the continental margin of Uruguay is due to the interaction of an important set of sedimentary processes. The contourite and turbiditic are the most significant processes which are associated with the development of submarine canyons as well as the gravitational mass respect to major landslides. These processes generate erosional and depositional features with a direct impact on different areas of application, which have potential environmental risks (gravitational landslides, earthquakes, tsunamis) and potential economic resources

A Meta-Heuristic Regression-Based Feature Selection for Predictive Analytics

Directory of Open Access Journals (Sweden)

Bharat Singh

2014-11-01

Full Text Available A high-dimensional feature selection having a very large number of features with an optimal feature subset is an NP-complete problem. Because conventional optimization techniques are unable to tackle large-scale feature selection problems, meta-heuristic algorithms are widely used. In this paper, we propose a particle swarm optimization technique while utilizing regression techniques for feature selection. We then use the selected features to classify the data. Classification accuracy is used as a criterion to evaluate classifier performance, and classification is accomplished through the use of k-nearest neighbour (KNN and Bayesian techniques. Various high dimensional data sets are used to evaluate the usefulness of the proposed approach. Results show that our approach gives better results when compared with other conventional feature selection algorithms.

The urban features of informal settlements in Jakarta, Indonesia

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Waleed Alzamil

2017-12-01

Full Text Available This data article contains the urban features of three informal settlements in Jakarta: A. Kampung Bandan; B. Kampung Luar Batang; And C. Kampung Muara Baru. The data describes the urban features of physical structures, infrastructures, and public services. These data include maps showing locations of these settlements, photography of urban status, and examples of urban fabric. The data are obtained from the statistical records and field surveys of three settlements cases. Keywords: Informal settlements, Physical, Features, Urban, Kampung, Jakarta, Indonesia

The geology of Burnsville Cove, Bath and Highland Counties, Virginia

Science.gov (United States)

Swezey, Christopher; Haynes, John T.; Lambert, Richard A.; White, William B.; Lucas, Philip C.; Garrity, Christopher P.

2015-01-01

Burnsville Cove is a karst region in Bath and Highland Counties of Virginia. A new geologic map of the area reveals various units of limestone, sandstone, and siliciclastic mudstone (shale) of Silurian through Devonian age, as well as structural features such as northeast-trending anticlines and synclines, minor thrust faults, and prominent joints. Quaternary features include erosional (strath) terraces and accumulations of mud, sand, and gravel. The caves of Burnsville Cove are located within predominantly carbonate strata above the Silurian Williamsport Sandstone and below the Devonian Oriskany Sandstone. Most of the caves are located within the Silurian Tonoloway Limestone, rather than the Silurian-Devonian Keyser Limestone as reported previously.

Erosional consequence of saltcedar control

Science.gov (United States)

Vincent, K.R.; Friedman, J.M.; Griffin, E.R.

2009-01-01

Removal of nonnative riparian trees is accelerating to conserve water and improve habitat for native species. Widespread control of dominant species, however, can lead to unintended erosion. Helicopter herbicide application in 2003 along a 12-km reach of the Rio Puerco, New Mexico, eliminated the target invasive species saltcedar (Tamarix spp.), which dominated the floodplain, as well as the native species sandbar willow (Salix exigua Nuttall), which occurred as a fringe along the channel. Herbicide application initiated a natural experiment testing the importance of riparian vegetation for bank stability along this data-rich river. A flood three years later eroded about 680,000 m3 of sediment, increasing mean channel width of the sprayed reach by 84%. Erosion upstream and downstream from the sprayed reach during this flood was inconsequential. Sand eroded from channel banks was transported an average of 5 km downstream and deposited on the floodplain and channel bed. Although vegetation was killed across the floodplain in the sprayed reach, erosion was almost entirely confined to the channel banks. The absence of dense, flexible woody stems on the banks reduced drag on the flow, leading to high shear stress at the toe of the banks, fluvial erosion, bank undercutting, and mass failure. The potential for increased erosion must be included in consideration of phreatophyte control projects. ?? 2009 U.S. Government.

Erosional losses of fallout plutonium

International Nuclear Information System (INIS)

Foster, G.R.; Hakonson, T.E.

1987-01-01

Plutonium from fallout after atmospheric explosion of nuclear weapons in the 1950's and 1960s is being redistributed over the landscape by soil erosion and carried on sediment by streams to oceans. Erosion rates computed with the Universal Soil Loss Equation for more than 200,000 sample points on nonfederal land across the US were used to estimate plutonium removal rates by soil erosion. On the average, only about 4% of the eroded sediment reaches the outlet of a major river. The remaining sediment is deposited en route, and because deposition is a selective process, the sediment is enriched in fine particles having the highest concentration of plutonium because of the element's strong association with clay and silt-sized sediment. Estimated enrichment ratios, sediment delivery ratios, and erosion rates were used to estimate annual delivery of fallout plutonium. These estimates ranged from 0.002% of the initial fallout plutonium inventory for the Savannah River basin to 0.01% for the Columbia River basin, to 0.02% for the Hudson and Rio Grande River basins, to 0.08% for the Mississippi River basin. If the deposition of plutonium had been uniformly 1 mCi/km 2 , the estimated plutonium activity on suspended sediment would range from about 7 fCi/g of sediment of the Savannah River basin, to 9 fCi/g for the Mississippi River basin, to 12 fCi/g for the Hudson River basin, to 14 fCi/g for the Columbia and Rio Grande River basins. 45 references, 2 figures, 17 tables

Erosional Consequence of Saltcedar Control

Science.gov (United States)

Vincent, Kirk R.; Friedman, Jonathan M.; Griffin, Eleanor R.

2009-08-01

Removal of nonnative riparian trees is accelerating to conserve water and improve habitat for native species. Widespread control of dominant species, however, can lead to unintended erosion. Helicopter herbicide application in 2003 along a 12-km reach of the Rio Puerco, New Mexico, eliminated the target invasive species saltcedar ( Tamarix spp.), which dominated the floodplain, as well as the native species sandbar willow ( Salix exigua Nuttall), which occurred as a fringe along the channel. Herbicide application initiated a natural experiment testing the importance of riparian vegetation for bank stability along this data-rich river. A flood three years later eroded about 680,000 m3 of sediment, increasing mean channel width of the sprayed reach by 84%. Erosion upstream and downstream from the sprayed reach during this flood was inconsequential. Sand eroded from channel banks was transported an average of 5 km downstream and deposited on the floodplain and channel bed. Although vegetation was killed across the floodplain in the sprayed reach, erosion was almost entirely confined to the channel banks. The absence of dense, flexible woody stems on the banks reduced drag on the flow, leading to high shear stress at the toe of the banks, fluvial erosion, bank undercutting, and mass failure. The potential for increased erosion must be included in consideration of phreatophyte control projects.

Localized scleroderma: imaging features

International Nuclear Information System (INIS)

Liu, P.; Uziel, Y.; Chuang, S.; Silverman, E.; Krafchik, B.; Laxer, R.

1994-01-01

Localized scleroderma is distinct from the diffuse form of scleroderma and does not show Raynaud's phenomenon and visceral involvement. The imaging features in 23 patients ranging from 2 to 17 years of age (mean 11.1 years) were reviewed. Leg length discrepancy and muscle atrophy were the most common findings (five patients), with two patients also showing modelling deformity of the fibula. One patient with lower extremity involvement showed abnormal bone marrow signals on MR. Disabling joint contracture requiring orthopedic intervention was noted in one patient. In two patients with ''en coup de sabre'' facial deformity, CT and MR scans revealed intracranial calcifications and white matter abnormality in the ipsilateral frontal lobes, with one also showing migrational abnormality. In a third patient, CT revealed white matter abnormality in the ipsilateral parietal lobe. In one patient with progressive facial hemiatrophy, CT and MR scans showed the underlying hypoplastic left maxillary antrum and cheek. Imaging studies of areas of clinical concern revealed positive findings in half our patients. (orig.)

Alexnet Feature Extraction and Multi-Kernel Learning for Objectoriented Classification

Science.gov (United States)

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

2018-04-01

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

ALEXNET FEATURE EXTRACTION AND MULTI-KERNEL LEARNING FOR OBJECTORIENTED CLASSIFICATION

Directory of Open Access Journals (Sweden)

L. Ding

2018-04-01

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

Linear Regression on Sparse Features for Single-Channel Speech Separation

DEFF Research Database (Denmark)

Schmidt, Mikkel N.; Olsson, Rasmus Kongsgaard

2007-01-01

In this work we address the problem of separating multiple speakers from a single microphone recording. We formulate a linear regression model for estimating each speaker based on features derived from the mixture. The employed feature representation is a sparse, non-negative encoding of the speech...... mixture in terms of pre-learned speaker-dependent dictionaries. Previous work has shown that this feature representation by itself provides some degree of separation. We show that the performance is significantly improved when regression analysis is performed on the sparse, non-negative features, both...

Visual attention to features by associative learning.

Science.gov (United States)

Gozli, Davood G; Moskowitz, Joshua B; Pratt, Jay

2014-11-01

Expecting a particular stimulus can facilitate processing of that stimulus over others, but what is the fate of other stimuli that are known to co-occur with the expected stimulus? This study examined the impact of learned association on feature-based attention. The findings show that the effectiveness of an uninformative color transient in orienting attention can change by learned associations between colors and the expected target shape. In an initial acquisition phase, participants learned two distinct sequences of stimulus-response-outcome, where stimuli were defined by shape ('S' vs. 'H'), responses were localized key-presses (left vs. right), and outcomes were colors (red vs. green). Next, in a test phase, while expecting a target shape (80% probable), participants showed reliable attentional orienting to the color transient associated with the target shape, and showed no attentional orienting with the color associated with the alternative target shape. This bias seemed to be driven by learned association between shapes and colors, and not modulated by the response. In addition, the bias seemed to depend on observing target-color conjunctions, since encountering the two features disjunctively (without spatiotemporal overlap) did not replicate the findings. We conclude that associative learning - likely mediated by mechanisms underlying visual object representation - can extend the impact of goal-driven attention to features associated with a target stimulus. Copyright © 2014 Elsevier B.V. All rights reserved.

Definitions of engineered safety features and related features for nuclear power plants

International Nuclear Information System (INIS)

1986-01-01

In light water moderated, light water cooled nuclear power plants, definitions are given of engineered safety features which are designed to suppress or prevent dispersion of radioactive materials due to damage etc. of fuel at the times of power plant failures, and of related features which are designed to actuate or operate the engineered safety features. Contents are the following: scope of engineered safety features and of related features; classification of engineered safety features (direct systems and indirect systems) and of related features (auxiliaries, emergency power supply, and protective means). (Mori, K.)

Magnetic resonance imaging features of fibrocystic change of the breast.

Science.gov (United States)

Chen, Jeon-Hor; Liu, Hui; Baek, Hyeon-Man; Nalcioglu, Orhan; Su, Min-Ying

2008-11-01

Studies specifically reporting MRI of fibrocystic change (FCC) of the breast are very few and its MRI features are not clearly known. The purpose of this study was to analyze the MRI features of FCC of the breast. Thirty-one patients with pathologically proven FCC of the breast were retrospectively reviewed. The MRI study was performed using a 1.5-T MR scanner with standard bilateral breast coil. The imaging protocol consisted of pre-contrast T1-weighed imaging and dynamic contrast-enhanced axial T1-weighed imaging. The MRI features were interpreted based on the morphologic and enhancement kinetic descriptors defined on ACR BIRADS-MRI lexicon. FCC of the breast had a wide spectrum of morphologic and kinetic features on MRI. Two types of FCC were found, including a more diffuse type of nonmass lesion (12/31, 39%) showing benign enhancement kinetic pattern with medium wash-in in early phase (9/10, 90%) and a focal mass-type lesion (11/31, 35%) with enhancement kinetic usually showing rapid up-slope mimicking a breast cancer (8/11, 73%). MRI is able to elaborate the diverse imaging features of FCC of the breast. Our result showed that FCC presenting as a focal mass-type lesion was usually overdiagnosed as malignancy. Understanding MRI of FCC is important to determine which cohort of patients should be followed up alone or receive aggressive management.

Unconscious analyses of visual scenes based on feature conjunctions.

Science.gov (United States)

Tachibana, Ryosuke; Noguchi, Yasuki

2015-06-01

To efficiently process a cluttered scene, the visual system analyzes statistical properties or regularities of visual elements embedded in the scene. It is controversial, however, whether those scene analyses could also work for stimuli unconsciously perceived. Here we show that our brain performs the unconscious scene analyses not only using a single featural cue (e.g., orientation) but also based on conjunctions of multiple visual features (e.g., combinations of color and orientation information). Subjects foveally viewed a stimulus array (duration: 50 ms) where 4 types of bars (red-horizontal, red-vertical, green-horizontal, and green-vertical) were intermixed. Although a conscious perception of those bars was inhibited by a subsequent mask stimulus, the brain correctly analyzed the information about color, orientation, and color-orientation conjunctions of those invisible bars. The information of those features was then used for the unconscious configuration analysis (statistical processing) of the central bars, which induced a perceptual bias and illusory feature binding in visible stimuli at peripheral locations. While statistical analyses and feature binding are normally 2 key functions of the visual system to construct coherent percepts of visual scenes, our results show that a high-level analysis combining those 2 functions is correctly performed by unconscious computations in the brain. (c) 2015 APA, all rights reserved).

A new karren feature: hummocky karren

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Plan Lukas

2012-01-01

Full Text Available Karren are small-scale landforms on karst surfaces and many types have been described so far. Here we present an apparently new feature which was found on the Hochschwab karst massive in the Northern Calcareous Alps of Austria. So far only few outcrops each having less than 1 m² within a very restricted area have been found. Morphometric analysis reveals that the karren consist of a randomly distributed, dispersed assemblage of small hummocks and depressions in between. The mean distance between neighbouring hummocks is 4 to 5 cm and the mean height is 0.85 cm. Longitudinal sections are gently sinuous. The occurrences are delimited by thin soil cover with grassy vegetation and the karren continue below that vegetation cover. Therefore, it is clear that the features have formed subcutaneously. Corroded fissures where water could infiltrate into the epikarst are absent. The bedrock lithology is Middle Triassic limestone of the Wetterstein Formation in lagoonal facies. Geological structures do not govern the feature. The surface is not a bedding plane and small joints and fractures do not govern the arrangement of the hummocks. Thin section analysis regarding rock texture and dolomite components show that there is no compositional difference between hummocks and depressions. Geochemical analyses show that the limestone is very pure with a very low content of Magnesia. Slightly higher Magnesia contents at the hummock surfaces are significant. The data obtained so far only indicate that some dissolution mechanism but not any rock property governs the irregular array. As there exist no descriptions of comparable features in literature, the name “hummocky karren” is suggested for that type of karren landform.

Systematic Review and Meta-Analysis of CT Features for Differentiating Complicated and Uncomplicated Appendicitis.

Science.gov (United States)

Kim, Hae Young; Park, Ji Hoon; Lee, Yoon Jin; Lee, Sung Soo; Jeon, Jong-June; Lee, Kyoung Ho

2018-04-01

Purpose To perform a systematic review and meta-analysis to identify computed tomographic (CT) features for differentiating complicated appendicitis in patients suspected of having appendicitis and to summarize their diagnostic accuracy. Materials and Methods Studies on diagnostic accuracy of CT features for differentiating complicated appendicitis (perforated or gangrenous appendicitis) in patients suspected of having appendicitis were searched in Ovid-MEDLINE, EMBASE, and the Cochrane Library. Overlapping descriptors used in different studies to denote the same image finding were subsumed under a single CT feature. Pooled diagnostic accuracy of the CT features was calculated by using a bivariate random effects model. CT features with pooled diagnostic odds ratios with 95% confidence intervals not including 1 were considered as informative. Results Twenty-three studies were included, and 184 overlapping descriptors for various CT findings were subsumed under 14 features. Of these, 10 features were informative for complicated appendicitis. There was a general tendency for these features to show relatively high specificity but low sensitivity. Extraluminal appendicolith, abscess, appendiceal wall enhancement defect, extraluminal air, ileus, periappendiceal fluid collection, ascites, intraluminal air, and intraluminal appendicolith showed pooled specificity greater than 70% (range, 74%-100%), but sensitivity was limited (range, 14%-59%). Periappendiceal fat stranding was the only feature that showed high sensitivity (94%; 95% confidence interval: 86%, 98%) but low specificity (40%; 95% confidence interval, 23%, 60%). Conclusion Ten informative CT features for differentiating complicated appendicitis were identified in this study, nine of which showed high specificity, but low sensitivity. © RSNA, 2017 Online supplemental material is available for this article.

Featured Image: Diamonds in a Meteorite

Science.gov (United States)

Kohler, Susanna

2018-04-01

This unique image which measures only 60 x 80 micrometers across reveals details in the Kapoeta meteorite, an 11-kg stone that fell in South Sudan in 1942. The sparkle in the image? A cluster of nanodiamonds discovered embedded in the stone in a recent study led by Yassir Abdu (University of Sharjah, United Arab Emirates). Abdu and collaborators showed that these nanodiamonds have similar spectral features to the interiors of dense interstellar clouds and they dont show any signs of shock features. This may suggest that the nanodiamonds were formed by condensation of nebular gases early in the history of the solar system. The diamonds were trapped in the surface material of the Kapoeta meteorites parent body, thought to be the asteroid Vesta. To read more about the authors study, check out the original article below.CitationYassir A. Abdu et al 2018 ApJL 856 L9. doi:10.3847/2041-8213/aab433

JCE Feature Columns

Science.gov (United States)

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

Hybrid feature selection for supporting lightweight intrusion detection systems

Science.gov (United States)

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.

Principal Feature Analysis: A Multivariate Feature Selection Method for fMRI Data

Directory of Open Access Journals (Sweden)

Lijun Wang

2013-01-01

Full Text Available Brain decoding with functional magnetic resonance imaging (fMRI requires analysis of complex, multivariate data. Multivoxel pattern analysis (MVPA has been widely used in recent years. MVPA treats the activation of multiple voxels from fMRI data as a pattern and decodes brain states using pattern classification methods. Feature selection is a critical procedure of MVPA because it decides which features will be included in the classification analysis of fMRI data, thereby improving the performance of the classifier. Features can be selected by limiting the analysis to specific anatomical regions or by computing univariate (voxel-wise or multivariate statistics. However, these methods either discard some informative features or select features with redundant information. This paper introduces the principal feature analysis as a novel multivariate feature selection method for fMRI data processing. This multivariate approach aims to remove features with redundant information, thereby selecting fewer features, while retaining the most information.

TreeBASIS Feature Descriptor and Its Hardware Implementation

Directory of Open Access Journals (Sweden)

Spencer Fowers

2014-01-01

Full Text Available This paper presents a novel feature descriptor called TreeBASIS that provides improvements in descriptor size, computation time, matching speed, and accuracy. This new descriptor uses a binary vocabulary tree that is computed using basis dictionary images and a test set of feature region images. To facilitate real-time implementation, a feature region image is binary quantized and the resulting quantized vector is passed into the BASIS vocabulary tree. A Hamming distance is then computed between the feature region image and the effectively descriptive basis dictionary image at a node to determine the branch taken and the path the feature region image takes is saved as a descriptor. The TreeBASIS feature descriptor is an excellent candidate for hardware implementation because of its reduced descriptor size and the fact that descriptors can be created and features matched without the use of floating point operations. The TreeBASIS descriptor is more computationally and space efficient than other descriptors such as BASIS, SIFT, and SURF. Moreover, it can be computed entirely in hardware without the support of a CPU for additional software-based computations. Experimental results and a hardware implementation show that the TreeBASIS descriptor compares well with other descriptors for frame-to-frame homography computation while requiring fewer hardware resources.

High Dimensional Classification Using Features Annealed Independence Rules.

Science.gov (United States)

Fan, Jianqing; Fan, Yingying

2008-01-01

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

Image features for misalignment correction in medical flat-detector CT

International Nuclear Information System (INIS)

Wicklein, Julia; Kunze, Holger; Kalender, Willi A.; Kyriakou, Yiannis

2012-01-01

Purpose: Misalignment artifacts are a serious problem in medical flat-detector computed tomography. Generally, the geometrical parameters, which are essential for reconstruction, are provided by preceding calibration routines. These procedures are time consuming and the later use of stored parameters is sensitive toward external impacts or patient movement. The method of choice in a clinical environment would be a markerless online-calibration procedure that allows flexible scan trajectories and simultaneously corrects misalignment and motion artifacts during the reconstruction process. Therefore, different image features were evaluated according to their capability of quantifying misalignment. Methods: Projections of the FORBILD head and thorax phantoms were simulated. Additionally, acquisitions of a head phantom and patient data were used for evaluation. For the reconstruction different sources and magnitudes of misalignment were introduced in the geometry description. The resulting volumes were analyzed by entropy (based on the gray-level histogram), total variation, Gabor filter texture features, Haralick co-occurrence features, and Tamura texture features. The feature results were compared to the back-projection mismatch of the disturbed geometry. Results: The evaluations demonstrate the ability of several well-established image features to classify misalignment. The authors elaborated the particular suitability of the gray-level histogram-based entropy on identifying misalignment artifacts, after applying an appropriate window level (bone window). Conclusions: Some of the proposed feature extraction algorithms show a strong correlation with the misalignment level. Especially, entropy-based methods showed very good correspondence, with the best of these being the type that uses the gray-level histogram for calculation. This makes it a suitable image feature for online-calibration.

MRI features of chondroblastoma

International Nuclear Information System (INIS)

Cheng Xiaoguang; Liu Xia; Cheng Kebin; Liu Wei

2009-01-01

Objective: To evaluate the MR imaging features of chondroblastoma. Methods: MRI examinations of 20 patients with histological proven chondmblastoma were reviewed retrospectively. The MRI findings of chondroblastoma including the signal intensity, the shape, the growth patterns, and the surrounding bone marrow edema and the adjacent soft tissue edema, the periosteal reaction, the adjacent joint effusion were analyzed. Results: All 20 cases demonstrated heterogeneous MR signal intensity on T 1 WI and T 2 WI images and showed lobular margins. Sixteen cases demonstrated expansive growth patterns. Surrounding bone marrow edema was found in 18 cases and adjacent soft tissue edema in 14 cases. Periosteal reaction was identified in 6 cases. In 7 cases the tumor extended to adjacent soft tissue. Adjacent joint effusion was visible on MRI in 6 cases. Conclusion: Heterogeneous signal intensity, lobular margins and expansive growth pattern, adjacent bone marrow and soft tissue edema were the common features of chondroblastoma on MRI. (authors)

Intracranial meningeal masson's hemangioma: CT and angiographic features

International Nuclear Information System (INIS)

Chang, Kee Hyun; Chi, Je Gen; Han, Man Chung; Cho, Byung Kyu; Kim, Hyun Jip

1985-01-01

Masson's hemangioma is a rare benign vascular condition with a papillary intravascular endothelial proliferation which may appear either as a primary form as a secondary form in a pre-existing vascular process. CT and angiographic features of 2 cases with Masson's hemangioma were presented. Both of them were located extra-axially in the posterior fossa. CT findings were not specific in both cases; One showed homogeneously enhancing mass, simulating meningioma. And the other demonstrated a multiocular rim enhancing mass. However, the angiographic features were rather characteristic; Both cases showed persistent vascular poolings of contrast media which were supplied form the meningeal vessels. Angiographic differential diagnosis of similar lesions in the posterior fossa is discussed

Feature hashing for fast image retrieval

Science.gov (United States)

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.

Familiarity and within-person facial variability: the importance of the internal and external features

OpenAIRE

Kramer, R. S. S.; Manesi, Z.; Towler, A.; Reynolds, M. G.; Burton, A. M.

2018-01-01

As faces become familiar, we come to rely more on their internal features for recognition and matching tasks. Here, we assess whether this same pattern is also observed for a card sorting task. Participants sorted photos showing either the full face, only the internal features, or only the external features into multiple piles, one pile per identity. In Experiments 1 and 2, we showed the standard advantage for familiar faces—sorting was more accurate and showed very few errors in comparison w...

Classifying web pages with visual features

NARCIS (Netherlands)

de Boer, V.; van Someren, M.; Lupascu, T.; Filipe, J.; Cordeiro, J.

2010-01-01

To automatically classify and process web pages, current systems use the textual content of those pages, including both the displayed content and the underlying (HTML) code. However, a very important feature of a web page is its visual appearance. In this paper, we show that using generic visual

Prostatic adenocarcinoma with glomeruloid features.

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Pacelli, A; Lopez-Beltran, A; Egan, A J; Bostwick, D G

1998-05-01

A wide variety of architectural patterns of adenocarcinoma may be seen in the prostate. We have recently encountered a hitherto-undescribed pattern of growth characterized by intraluminal ball-like clusters of cancer cells reminiscent of renal glomeruli, which we refer to as prostatic adenocarcinoma with glomeruloid features. To define the architectural features, frequency, and distribution of prostatic adenocarcinoma with glomeruloid features, we reviewed 202 totally embedded radical prostatectomy specimens obtained between October 1992 and April 1994 from the files of the Mayo Clinic. This series was supplemented by 100 consecutive needle biopsies with prostatic cancer from January to February 1996. Prostatic adenocarcinoma with glomeruloid features was characterized by round to oval epithelial tufts growing within malignant acini, often supported by a fibrovascular core. The epithelial cells were sometimes arranged in semicircular concentric rows separated by clefted spaces. In the radical prostatectomy specimens, nine cases (4.5%) had glomeruloid features. The glomeruloid pattern constituted 5% to 20% of each cancer (mean, 8.33%) and was usually located at the apex or in the peripheral zone of the prostate. Seven cases were associated with a high Gleason score (7 or 8), one with a score of 6, and one with a score of 5. All cases were associated with high-grade prostatic intraepithelial neoplasia and extensive perineural invasion. Pathological stages included T2c (three cases), T3b (four cases), and T3c (two cases); one of the T3b cases had lymph node metastases (N1). Three (3%) of 100 consecutive routine needle biopsy specimens with cancer showed glomeruloid features, and this pattern constituted 5% to 10% of each cancer (mean, 6.7%). The Gleason score was 6 for two cases and 8 for one case. Two cases were associated with high-grade prostatic intraepithelial neoplasia, and one case had perineural invasion. Glomeruloid features were not observed in any benign or

Realistic Free-Spins Features Increase Preference for Slot Machines.

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Taylor, Lorance F; Macaskill, Anne C; Hunt, Maree J

2017-06-01

Despite increasing research into how the structural characteristics of slot machines influence gambling behaviour there have been no experimental investigations into the effect of free-spins bonus features-a structural characteristic that is commonly central to the design of slot machines. This series of three experiments investigated the free-spins feature using slot machine simulations to determine whether participants allocate more wagers to a machine with free spins, and, which components of free-spins features drive this preference. In each experiment, participants were exposed to two computer-simulated slot machines-one with a free-spins feature or similar bonus feature and one without. Participants then completed a testing phase where they could freely switch between the two machines. In Experiment 1, participants did not prefer the machine with a simple free-spins feature. In Experiment 2 the free-spins feature incorporated additional elements such as sounds, animations, and an increased win frequency; participants preferred to gamble on this machine. The Experiment 3 "bonus feature" machine resembled the free spins machine in Experiment 2 except spins were not free; participants showed a clear preference for this machine also. These findings indicate that (1) free-spins features have a major influence over machine choice and (2) the "freeness" of the free-spins bonus features is not an important driver of preference, contrary to self-report and interview research with gamblers.

Quality of radiomic features in glioblastoma multiforme: Impact of semi-automated tumor segmentation software

Energy Technology Data Exchange (ETDEWEB)

Lee, Myung Eun; Kim, Jong Hyo [Center for Medical-IT Convergence Technology Research, Advanced Institutes of Convergence Technology, Seoul National University, Suwon (Korea, Republic of); Woo, Bo Yeong [Dept. of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, Suwon (Korea, Republic of); Ko, Micheal D.; Jamshidi, Neema [Dept. of Radiological Sciences, University of California, Los Angeles, Los Angeles (United States)

2017-06-15

The purpose of this study was to evaluate the reliability and quality of radiomic features in glioblastoma multiforme (GBM) derived from tumor volumes obtained with semi-automated tumor segmentation software. MR images of 45 GBM patients (29 males, 16 females) were downloaded from The Cancer Imaging Archive, in which post-contrast T1-weighted imaging and fluid-attenuated inversion recovery MR sequences were used. Two raters independently segmented the tumors using two semi-automated segmentation tools (TumorPrism3D and 3D Slicer). Regions of interest corresponding to contrast-enhancing lesion, necrotic portions, and non-enhancing T2 high signal intensity component were segmented for each tumor. A total of 180 imaging features were extracted, and their quality was evaluated in terms of stability, normalized dynamic range (NDR), and redundancy, using intra-class correlation coefficients, cluster consensus, and Rand Statistic. Our study results showed that most of the radiomic features in GBM were highly stable. Over 90% of 180 features showed good stability (intra-class correlation coefficient [ICC] ≥ 0.8), whereas only 7 features were of poor stability (ICC < 0.5). Most first order statistics and morphometric features showed moderate-to-high NDR (4 > NDR ≥1), while above 35% of the texture features showed poor NDR (< 1). Features were shown to cluster into only 5 groups, indicating that they were highly redundant. The use of semi-automated software tools provided sufficiently reliable tumor segmentation and feature stability; thus helping to overcome the inherent inter-rater and intra-rater variability of user intervention. However, certain aspects of feature quality, including NDR and redundancy, need to be assessed for determination of representative signature features before further development of radiomics.

An ant colony optimization based feature selection for web page classification.

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Saraç, Esra; Özel, Selma Ayşe

2014-01-01

The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods.

Feature extraction with deep neural networks by a generalized discriminant analysis.

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Stuhlsatz, André; Lippel, Jens; Zielke, Thomas

2012-04-01

We present an approach to feature extraction that is a generalization of the classical linear discriminant analysis (LDA) on the basis of deep neural networks (DNNs). As for LDA, discriminative features generated from independent Gaussian class conditionals are assumed. This modeling has the advantages that the intrinsic dimensionality of the feature space is bounded by the number of classes and that the optimal discriminant function is linear. Unfortunately, linear transformations are insufficient to extract optimal discriminative features from arbitrarily distributed raw measurements. The generalized discriminant analysis (GerDA) proposed in this paper uses nonlinear transformations that are learnt by DNNs in a semisupervised fashion. We show that the feature extraction based on our approach displays excellent performance on real-world recognition and detection tasks, such as handwritten digit recognition and face detection. In a series of experiments, we evaluate GerDA features with respect to dimensionality reduction, visualization, classification, and detection. Moreover, we show that GerDA DNNs can preprocess truly high-dimensional input data to low-dimensional representations that facilitate accurate predictions even if simple linear predictors or measures of similarity are used.

Speech Emotion Feature Selection Method Based on Contribution Analysis Algorithm of Neural Network

International Nuclear Information System (INIS)

Wang Xiaojia; Mao Qirong; Zhan Yongzhao

2008-01-01

There are many emotion features. If all these features are employed to recognize emotions, redundant features may be existed. Furthermore, recognition result is unsatisfying and the cost of feature extraction is high. In this paper, a method to select speech emotion features based on contribution analysis algorithm of NN is presented. The emotion features are selected by using contribution analysis algorithm of NN from the 95 extracted features. Cluster analysis is applied to analyze the effectiveness for the features selected, and the time of feature extraction is evaluated. Finally, 24 emotion features selected are used to recognize six speech emotions. The experiments show that this method can improve the recognition rate and the time of feature extraction

Classification of radiolarian images with hand-crafted and deep features

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Keçeli, Ali Seydi; Kaya, Aydın; Keçeli, Seda Uzunçimen

2017-12-01

Radiolarians are planktonic protozoa and are important biostratigraphic and paleoenvironmental indicators for paleogeographic reconstructions. Radiolarian paleontology still remains as a low cost and the one of the most convenient way to obtain dating of deep ocean sediments. Traditional methods for identifying radiolarians are time-consuming and cannot scale to the granularity or scope necessary for large-scale studies. Automated image classification will allow making these analyses promptly. In this study, a method for automatic radiolarian image classification is proposed on Scanning Electron Microscope (SEM) images of radiolarians to ease species identification of fossilized radiolarians. The proposed method uses both hand-crafted features like invariant moments, wavelet moments, Gabor features, basic morphological features and deep features obtained from a pre-trained Convolutional Neural Network (CNN). Feature selection is applied over deep features to reduce high dimensionality. Classification outcomes are analyzed to compare hand-crafted features, deep features, and their combinations. Results show that the deep features obtained from a pre-trained CNN are more discriminative comparing to hand-crafted ones. Additionally, feature selection utilizes to the computational cost of classification algorithms and have no negative effect on classification accuracy.

Chinese wine classification system based on micrograph using combination of shape and structure features

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Wan, Yi

2011-06-01

Chinese wines can be classification or graded by the micrographs. Micrographs of Chinese wines show floccules, stick and granule of variant shape and size. Different wines have variant microstructure and micrographs, we study the classification of Chinese wines based on the micrographs. Shape and structure of wines' particles in microstructure is the most important feature for recognition and classification of wines. So we introduce a feature extraction method which can describe the structure and region shape of micrograph efficiently. First, the micrographs are enhanced using total variation denoising, and segmented using a modified Otsu's method based on the Rayleigh Distribution. Then features are extracted using proposed method in the paper based on area, perimeter and traditional shape feature. Eight kinds total 26 features are selected. Finally, Chinese wine classification system based on micrograph using combination of shape and structure features and BP neural network have been presented. We compare the recognition results for different choices of features (traditional shape features or proposed features). The experimental results show that the better classification rate have been achieved using the combinational features proposed in this paper.

Feature-Selective Attention Adaptively Shifts Noise Correlations in Primary Auditory Cortex.

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Downer, Joshua D; Rapone, Brittany; Verhein, Jessica; O'Connor, Kevin N; Sutter, Mitchell L

2017-05-24

Sensory environments often contain an overwhelming amount of information, with both relevant and irrelevant information competing for neural resources. Feature attention mediates this competition by selecting the sensory features needed to form a coherent percept. How attention affects the activity of populations of neurons to support this process is poorly understood because population coding is typically studied through simulations in which one sensory feature is encoded without competition. Therefore, to study the effects of feature attention on population-based neural coding, investigations must be extended to include stimuli with both relevant and irrelevant features. We measured noise correlations ( r noise ) within small neural populations in primary auditory cortex while rhesus macaques performed a novel feature-selective attention task. We found that the effect of feature-selective attention on r noise depended not only on the population tuning to the attended feature, but also on the tuning to the distractor feature. To attempt to explain how these observed effects might support enhanced perceptual performance, we propose an extension of a simple and influential model in which shifts in r noise can simultaneously enhance the representation of the attended feature while suppressing the distractor. These findings present a novel mechanism by which attention modulates neural populations to support sensory processing in cluttered environments. SIGNIFICANCE STATEMENT Although feature-selective attention constitutes one of the building blocks of listening in natural environments, its neural bases remain obscure. To address this, we developed a novel auditory feature-selective attention task and measured noise correlations ( r noise ) in rhesus macaque A1 during task performance. Unlike previous studies showing that the effect of attention on r noise depends on population tuning to the attended feature, we show that the effect of attention depends on the tuning

Localized scleroderma: imaging features

Energy Technology Data Exchange (ETDEWEB)

Liu, P. (Dept. of Diagnostic Imaging, Hospital for Sick Children, Toronto, ON (Canada)); Uziel, Y. (Div. of Rheumatology, Hospital for Sick Children, Toronto, ON (Canada)); Chuang, S. (Dept. of Diagnostic Imaging, Hospital for Sick Children, Toronto, ON (Canada)); Silverman, E. (Div. of Rheumatology, Hospital for Sick Children, Toronto, ON (Canada)); Krafchik, B. (Div. of Dermatology, Dept. of Pediatrics, Hospital for Sick Children, Toronto, ON (Canada)); Laxer, R. (Div. of Rheumatology, Hospital for Sick Children, Toronto, ON (Canada))

1994-06-01

Localized scleroderma is distinct from the diffuse form of scleroderma and does not show Raynaud's phenomenon and visceral involvement. The imaging features in 23 patients ranging from 2 to 17 years of age (mean 11.1 years) were reviewed. Leg length discrepancy and muscle atrophy were the most common findings (five patients), with two patients also showing modelling deformity of the fibula. One patient with lower extremity involvement showed abnormal bone marrow signals on MR. Disabling joint contracture requiring orthopedic intervention was noted in one patient. In two patients with ''en coup de sabre'' facial deformity, CT and MR scans revealed intracranial calcifications and white matter abnormality in the ipsilateral frontal lobes, with one also showing migrational abnormality. In a third patient, CT revealed white matter abnormality in the ipsilateral parietal lobe. In one patient with progressive facial hemiatrophy, CT and MR scans showed the underlying hypoplastic left maxillary antrum and cheek. Imaging studies of areas of clinical concern revealed positive findings in half our patients. (orig.)

LINGUISTIC FEATURES ANALYSIS OF THE ENGLISH ELECTRONIC COMMERCE WEBSITES

Directory of Open Access Journals (Sweden)

Siti Nurani

2014-06-01

Full Text Available This research aims at identifying linguistic features used in the English electronic commerce websites used in correlation with the field, tenor and mode of discourse as parts of Systemic Functional Linguistics (SFL approach. Findings have shown that in the field of discourse, the linguistic features are largely appeared in the experiential domain analysis which shows that all terms of registers function as technical terms, of which the two major forms of nouns and verbs were the most frequent categories among other kinds of technical terms. The goal orientation is considered to be as a long term and the social activity is exchange. In the tenor of discourse, the linguistic features are highly appeared in the social distance analysis which shows that the social distance between participants is considered minimal. The agentive role is said to be equal and the social role is considered as non-hierarchic. In the mode of discourse, the linguistic features are excessively occurred in the language role analysis which exists equally of both constitutive and ancillary. The channel is in graphic mode. The medium is in written with a visual contact as its device.

Neighbors Based Discriminative Feature Difference Learning for Kinship Verification

DEFF Research Database (Denmark)

Duan, Xiaodong; Tan, Zheng-Hua

2015-01-01

In this paper, we present a discriminative feature difference learning method for facial image based kinship verification. To transform feature difference of an image pair to be discriminative for kinship verification, a linear transformation matrix for feature difference between an image pair...... than the commonly used feature concatenation, leading to a low complexity. Furthermore, there is no positive semi-definitive constrain on the transformation matrix while there is in metric learning methods, leading to an easy solution for the transformation matrix. Experimental results on two public...... databases show that the proposed method combined with a SVM classification method outperforms or is comparable to state-of-the-art kinship verification methods. © Springer International Publishing AG, Part of Springer Science+Business Media...

Local Feature Learning for Face Recognition under Varying Poses

DEFF Research Database (Denmark)

Duan, Xiaodong; Tan, Zheng-Hua

2015-01-01

In this paper, we present a local feature learning method for face recognition to deal with varying poses. As opposed to the commonly used approaches of recovering frontal face images from profile views, the proposed method extracts the subject related part from a local feature by removing the pose...... related part in it on the basis of a pose feature. The method has a closed-form solution, hence being time efficient. For performance evaluation, cross pose face recognition experiments are conducted on two public face recognition databases FERET and FEI. The proposed method shows a significant...... recognition improvement under varying poses over general local feature approaches and outperforms or is comparable with related state-of-the-art pose invariant face recognition approaches. Copyright ©2015 by IEEE....

Joint Tensor Feature Analysis For Visual Object Recognition.

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Wong, Wai Keung; Lai, Zhihui; Xu, Yong; Wen, Jiajun; Ho, Chu Po

2015-11-01

Tensor-based object recognition has been widely studied in the past several years. This paper focuses on the issue of joint feature selection from the tensor data and proposes a novel method called joint tensor feature analysis (JTFA) for tensor feature extraction and recognition. In order to obtain a set of jointly sparse projections for tensor feature extraction, we define the modified within-class tensor scatter value and the modified between-class tensor scatter value for regression. The k-mode optimization technique and the L(2,1)-norm jointly sparse regression are combined together to compute the optimal solutions. The convergent analysis, computational complexity analysis and the essence of the proposed method/model are also presented. It is interesting to show that the proposed method is very similar to singular value decomposition on the scatter matrix but with sparsity constraint on the right singular value matrix or eigen-decomposition on the scatter matrix with sparse manner. Experimental results on some tensor datasets indicate that JTFA outperforms some well-known tensor feature extraction and selection algorithms.

Mobility as a feature: Evidence from Zulu

Directory of Open Access Journals (Sweden)

Jochen Zeller

2016-01-01

Full Text Available This paper provides evidence for the view that syntactic movement of an element Y to a position X is not driven by features of the target X, but by features of the moving element Y. The data that constitute evidence for this type of analysis come from A-bar movement constructions (object left and right dislocation; object relativisation in the Bantu language Zulu. As I show, only object-DPs that move out of the VP in Zulu are active Goals for Agree-relations and can trigger object agreement with the verb. The fact that the functional head responsible for object agreement must be able to identify a DP in its c-command domain as an active Goal entails that the “mobility” of this DP must be encoded as a property of the DP. Based on this conclusion, I also discuss two proposals about the nature of the feature that activates a DP for movement in Zulu and examine the conditions that determine how this feature is checked and deleted through movement.

Polarimetric SAR Image Classification Using Multiple-feature Fusion and Ensemble Learning

Directory of Open Access Journals (Sweden)

Sun Xun

2016-12-01

Full Text Available In this paper, we propose a supervised classification algorithm for Polarimetric Synthetic Aperture Radar (PolSAR images using multiple-feature fusion and ensemble learning. First, we extract different polarimetric features, including extended polarimetric feature space, Hoekman, Huynen, H/alpha/A, and fourcomponent scattering features of PolSAR images. Next, we randomly select two types of features each time from all feature sets to guarantee the reliability and diversity of later ensembles and use a support vector machine as the basic classifier for predicting classification results. Finally, we concatenate all prediction probabilities of basic classifiers as the final feature representation and employ the random forest method to obtain final classification results. Experimental results at the pixel and region levels show the effectiveness of the proposed algorithm.

Subsurface structures of buried features in the lunar Procellarum region

Science.gov (United States)

Wang, Wenrui; Heki, Kosuke

2017-07-01

The Gravity Recovery and Interior Laboratory (GRAIL) mission unraveled numbers of features showing strong gravity anomalies without prominent topographic signatures in the lunar Procellarum region. These features, located in different geologic units, are considered to have complex subsurface structures reflecting different evolution processes. By using the GRAIL level-1 data, we estimated the free-air and Bouguer gravity anomalies in several selected regions including such intriguing features. With the three-dimensional inversion technique, we recovered subsurface density structures in these regions.

Ovalbumin with Glycated Carboxyl Groups Shows Membrane-Damaging Activity

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Ching-Chia Tang

2017-02-01

Full Text Available The aim of the present study was to investigate whether glycated ovalbumin (OVA showed novel activity at the lipid-water interface. Mannosylated OVA (Man-OVA was prepared by modification of the carboxyl groups with p-aminophenyl α-dextro (d-mannopyranoside. An increase in the number of modified carboxyl groups increased the membrane-damaging activity of Man-OVA on cell membrane-mimicking vesicles, whereas OVA did not induce membrane permeability in the tested phospholipid vesicles. The glycation of carboxyl groups caused a notable change in the gross conformation of OVA. Moreover, owing to their spatial positions, the Trp residues in Man-OVA were more exposed, unlike those in OVA. Fluorescence quenching studies suggested that the Trp residues in Man-OVA were located on the interface binds with the lipid vesicles, and their microenvironment was abundant in positively charged residues. Although OVA and Man-OVA showed a similar binding affinity for lipid vesicles, the lipid-interacting feature of Man-OVA was distinct from that of OVA. Chemical modification studies revealed that Lys and Arg residues, but not Trp residues, played a crucial role in the membrane-damaging activity of Man-OVA. Taken together, our data suggest that glycation of carboxyl groups causes changes in the structural properties and membrane-interacting features of OVA, generating OVA with membrane-perturbing activities at the lipid-water interface.

Associations Between PET Textural Features and GLUT1 Expression, and the Prognostic Significance of Textural Features in Lung Adenocarcinoma.

Science.gov (United States)

Koh, Young Wha; Park, Seong Yong; Hyun, Seung Hyup; Lee, Su Jin

2018-02-01

We evaluated the association between positron emission tomography (PET) textural features and glucose transporter 1 (GLUT1) expression level and further investigated the prognostic significance of textural features in lung adenocarcinoma. We evaluated 105 adenocarcinoma patients. We extracted texture-based PET parameters of primary tumors. Conventional PET parameters were also measured. The relationships between PET parameters and GLUT1 expression levels were evaluated. The association between PET parameters and overall survival (OS) was assessed using Cox's proportional hazard regression models. In terms of PET textural features, tumors expressing high levels of GLUT1 exhibited significantly lower coarseness, contrast, complexity, and strength, but significantly higher busyness. On univariate analysis, the metabolic tumor volume, total lesion glycolysis, contrast, busyness, complexity, and strength were significant predictors of OS. Multivariate analysis showed that lower complexity (HR=2.017, 95%CI=1.032-3.942, p=0.040) was independently associated with poorer survival. PET textural features may aid risk stratification in lung adenocarcinoma patients. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Extraction of Lesion-Partitioned Features and Retrieval of Contrast-Enhanced Liver Images

Directory of Open Access Journals (Sweden)

Mei Yu

2012-01-01

Full Text Available The most critical step in grayscale medical image retrieval systems is feature extraction. Understanding the interrelatedness between the characteristics of lesion images and corresponding imaging features is crucial for image training, as well as for features extraction. A feature-extraction algorithm is developed based on different imaging properties of lesions and on the discrepancy in density between the lesions and their surrounding normal liver tissues in triple-phase contrast-enhanced computed tomographic (CT scans. The algorithm includes mainly two processes: (1 distance transformation, which is used to divide the lesion into distinct regions and represents the spatial structure distribution and (2 representation using bag of visual words (BoW based on regions. The evaluation of this system based on the proposed feature extraction algorithm shows excellent retrieval results for three types of liver lesions visible on triple-phase scans CT images. The results of the proposed feature extraction algorithm show that although single-phase scans achieve the average precision of 81.9%, 80.8%, and 70.2%, dual- and triple-phase scans achieve 86.3% and 88.0%.

A comparative analysis of DNA barcode microarray feature size

Directory of Open Access Journals (Sweden)

Smith Andrew M

2009-10-01

Full Text Available Abstract Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density, but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platform. The barcodes used in this study are the well-characterized set derived from the Yeast KnockOut (YKO collection used for screens of pooled yeast (Saccharomyces cerevisiae deletion mutants. We treated these pools with the glycosylation inhibitor tunicamycin as a test compound. Three generations of barcode microarrays at 30, 8 and 5 μm features sizes independently identified the primary target of tunicamycin to be ALG7. Conclusion We show that the data obtained with 5 μm feature size is of comparable quality to the 30 μm size and propose that further shrinking of features could yield barcode microarrays with equal or greater resolving power and, more importantly, higher density.

A Novel Approach for Automatic Machining Feature Recognition with Edge Blend Feature

OpenAIRE

Keong Chen Wong; Yusof Yusri

2017-01-01

This paper presents an algorithm for efficiently recognizing and determining the convexity of an edge blend feature. The algorithm first recognizes all of the edge blend features from the Boundary Representation of a part; then a series of convexity test have been run on the recognized edge blend features. The novelty of the presented algorithm lies in, instead of each recognized blend feature is suppressed as most of researchers did, the recognized blend features of this research are gone th...

Neither separate nor equivalent : Relationships between feature representations within bound objects

NARCIS (Netherlands)

Morey, Candice C.; Guerard, Katherine; Tremblay, Sebastien

2013-01-01

Evidence suggests that binding, or encoding a feature with respect to other features in time and space, can convey cognitive advantages. However, evidence across many kinds of stimuli and paradigms presents a mixed picture, alternatively showing cognitive costs or cognitive advantages associated

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

Science.gov (United States)

Guo, Yanrong; Gao, Yaozong; Shen, Dinggang

2016-04-01

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.

A Feature Subtraction Method for Image Based Kinship Verification under Uncontrolled Environments

DEFF Research Database (Denmark)

Duan, Xiaodong; Tan, Zheng-Hua

2015-01-01

The most fundamental problem of local feature based kinship verification methods is that a local feature can capture the variations of environmental conditions and the differences between two persons having a kin relation, which can significantly decrease the performance. To address this problem...... the feature distance between face image pairs with kinship and maximize the distance between non-kinship pairs. Based on the subtracted feature, the verification is realized through a simple Gaussian based distance comparison method. Experiments on two public databases show that the feature subtraction method...

News video story segmentation method using fusion of audio-visual features

Science.gov (United States)

Wen, Jun; Wu, Ling-da; Zeng, Pu; Luan, Xi-dao; Xie, Yu-xiang

2007-11-01

News story segmentation is an important aspect for news video analysis. This paper presents a method for news video story segmentation. Different form prior works, which base on visual features transform, the proposed technique uses audio features as baseline and fuses visual features with it to refine the results. At first, it selects silence clips as audio features candidate points, and selects shot boundaries and anchor shots as two kinds of visual features candidate points. Then this paper selects audio feature candidates as cues and develops different fusion method, which effectively using diverse type visual candidates to refine audio candidates, to get story boundaries. Experiment results show that this method has high efficiency and adaptability to different kinds of news video.

Adaptive feature selection using v-shaped binary particle swarm optimization.

Science.gov (United States)

Teng, Xuyang; Dong, Hongbin; Zhou, Xiurong

2017-01-01

Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers.

The importance of internal facial features in learning new faces.

Science.gov (United States)

Longmore, Christopher A; Liu, Chang Hong; Young, Andrew W

2015-01-01

For familiar faces, the internal features (eyes, nose, and mouth) are known to be differentially salient for recognition compared to external features such as hairstyle. Two experiments are reported that investigate how this internal feature advantage accrues as a face becomes familiar. In Experiment 1, we tested the contribution of internal and external features to the ability to generalize from a single studied photograph to different views of the same face. A recognition advantage for the internal features over the external features was found after a change of viewpoint, whereas there was no internal feature advantage when the same image was used at study and test. In Experiment 2, we removed the most salient external feature (hairstyle) from studied photographs and looked at how this affected generalization to a novel viewpoint. Removing the hair from images of the face assisted generalization to novel viewpoints, and this was especially the case when photographs showing more than one viewpoint were studied. The results suggest that the internal features play an important role in the generalization between different images of an individual's face by enabling the viewer to detect the common identity-diagnostic elements across non-identical instances of the face.

Processing of word stress related acoustic information: A multi-feature MMN study.

Science.gov (United States)

Honbolygó, Ferenc; Kolozsvári, Orsolya; Csépe, Valéria

2017-08-01

In the present study, we investigated the processing of word stress related acoustic features in a word context. In a passive oddball multi-feature MMN experiment, we presented a disyllabic pseudo-word with two acoustically similar syllables as standard stimulus, and five contrasting deviants that differed from the standard in that they were either stressed on the first syllable or contained a vowel change. Stress was realized by an increase of f0, intensity, vowel duration or consonant duration. The vowel change was used to investigate if phonemic and prosodic changes elicit different MMN components. As a control condition, we presented non-speech counterparts of the speech stimuli. Results showed all but one feature (non-speech intensity deviant) eliciting the MMN component, which was larger for speech compared to non-speech stimuli. Two other components showed stimulus related effects: the N350 and the LDN (Late Discriminative Negativity). The N350 appeared to the vowel duration and consonant duration deviants, specifically to features related to the temporal characteristics of stimuli, while the LDN was present for all features, and it was larger for speech than for non-speech stimuli. We also found that the f0 and consonant duration features elicited a larger MMN than other features. These results suggest that stress as a phonological feature is processed based on long-term representations, and listeners show a specific sensitivity to segmental and suprasegmental cues signaling the prosodic boundaries of words. These findings support a two-stage model in the perception of stress and phoneme related acoustical information. Copyright © 2017 Elsevier B.V. All rights reserved.

Post-cranial skeletons of hypothyroid cretins show a similar anatomical mosaic as Homo floresiensis.

Science.gov (United States)

Oxnard, Charles; Obendorf, Peter J; Kefford, Ben J

2010-09-27

Human remains, some as recent as 15 thousand years, from Liang Bua (LB) on the Indonesian island of Flores have been attributed to a new species, Homo floresiensis. The definition includes a mosaic of features, some like modern humans (hence derived: genus Homo), some like modern apes and australopithecines (hence primitive: not species sapiens), and some unique (hence new species: floresiensis). Conversely, because only modern humans (H. sapiens) are known in this region in the last 40 thousand years, these individuals have also been suggested to be genetic human dwarfs. Such dwarfs resemble small humans and do not show the mosaic combination of the most complete individuals, LB1 and LB6, so this idea has been largely dismissed. We have previously shown that some features of the cranium of hypothyroid cretins are like those of LB1. Here we examine cretin postcrania to see if they show anatomical mosaics like H. floresiensis. We find that hypothyroid cretins share at least 10 postcranial features with Homo floresiensis and unaffected humans not found in apes (or australopithecines when materials permit). They share with H. floresiensis, modern apes and australopithecines at least 11 postcranial features not found in unaffected humans. They share with H. floresiensis, at least 8 features not found in apes, australopithecines or unaffected humans. Sixteen features can be rendered metrically and multivariate analyses demonstrate that H. floresiensis co-locates with cretins, both being markedly separate from humans and chimpanzees (P0.999). We therefore conclude that LB1 and LB6, at least, are, most likely, endemic cretins from a population of unaffected Homo sapiens. This is consistent with recent hypothyroid endemic cretinism throughout Indonesia, including the nearby island of Bali.

Post-cranial skeletons of hypothyroid cretins show a similar anatomical mosaic as Homo floresiensis.

Directory of Open Access Journals (Sweden)

Charles Oxnard

Full Text Available Human remains, some as recent as 15 thousand years, from Liang Bua (LB on the Indonesian island of Flores have been attributed to a new species, Homo floresiensis. The definition includes a mosaic of features, some like modern humans (hence derived: genus Homo, some like modern apes and australopithecines (hence primitive: not species sapiens, and some unique (hence new species: floresiensis. Conversely, because only modern humans (H. sapiens are known in this region in the last 40 thousand years, these individuals have also been suggested to be genetic human dwarfs. Such dwarfs resemble small humans and do not show the mosaic combination of the most complete individuals, LB1 and LB6, so this idea has been largely dismissed. We have previously shown that some features of the cranium of hypothyroid cretins are like those of LB1. Here we examine cretin postcrania to see if they show anatomical mosaics like H. floresiensis. We find that hypothyroid cretins share at least 10 postcranial features with Homo floresiensis and unaffected humans not found in apes (or australopithecines when materials permit. They share with H. floresiensis, modern apes and australopithecines at least 11 postcranial features not found in unaffected humans. They share with H. floresiensis, at least 8 features not found in apes, australopithecines or unaffected humans. Sixteen features can be rendered metrically and multivariate analyses demonstrate that H. floresiensis co-locates with cretins, both being markedly separate from humans and chimpanzees (P0.999. We therefore conclude that LB1 and LB6, at least, are, most likely, endemic cretins from a population of unaffected Homo sapiens. This is consistent with recent hypothyroid endemic cretinism throughout Indonesia, including the nearby island of Bali.

FEATURE MATCHING OF HISTORICAL IMAGES BASED ON GEOMETRY OF QUADRILATERALS

Directory of Open Access Journals (Sweden)

F. Maiwald

2018-05-01

Full Text Available This contribution shows an approach to match historical images from the photo library of the Saxon State and University Library Dresden (SLUB in the context of a historical three-dimensional city model of Dresden. In comparison to recent images, historical photography provides diverse factors which make an automatical image analysis (feature detection, feature matching and relative orientation of images difficult. Due to e.g. film grain, dust particles or the digitalization process, historical images are often covered by noise interfering with the image signal needed for a robust feature matching. The presented approach uses quadrilaterals in image space as these are commonly available in man-made structures and façade images (windows, stones, claddings. It is explained how to generally detect quadrilaterals in images. Consequently, the properties of the quadrilaterals as well as the relationship to neighbouring quadrilaterals are used for the description and matching of feature points. The results show that most of the matches are robust and correct but still small in numbers.

Feature Selection and Kernel Learning for Local Learning-Based Clustering.

Science.gov (United States)

Zeng, Hong; Cheung, Yiu-ming

2011-08-01

The performance of the most clustering algorithms highly relies on the representation of data in the input space or the Hilbert space of kernel methods. This paper is to obtain an appropriate data representation through feature selection or kernel learning within the framework of the Local Learning-Based Clustering (LLC) (Wu and Schölkopf 2006) method, which can outperform the global learning-based ones when dealing with the high-dimensional data lying on manifold. Specifically, we associate a weight to each feature or kernel and incorporate it into the built-in regularization of the LLC algorithm to take into account the relevance of each feature or kernel for the clustering. Accordingly, the weights are estimated iteratively in the clustering process. We show that the resulting weighted regularization with an additional constraint on the weights is equivalent to a known sparse-promoting penalty. Hence, the weights of those irrelevant features or kernels can be shrunk toward zero. Extensive experiments show the efficacy of the proposed methods on the benchmark data sets.

The radiographic features of rheumatoid arthritis in HLA-B27-positive patients

Energy Technology Data Exchange (ETDEWEB)

Rundback, J.H. (Dept. of Radiology, Beth Israel Medical Center, New York, NY (United States)); Rosenberg, Z.S. (Dept. of Radiology, Hospital for Joint Diseases, Orthopaedic Inst., New York, NY (United States)); Solomon, G. (Dept. of Rheumatology, Hospital for Joint Diseases, Orthopaedic Institute, New York, NY (United States))

1993-05-01

Radiographs were reviewed in a group of nine patients with classical seropositive rheumatoid arthritis who on tissue typing were found to express the class I HLA-B27 allele. Radiographs were analyzed with regard to whether or not they demonstrated radiographic features of (1) classical rheumatoid arthritis, (2) seronegative arthritis, or (3) mixed features of rheumatoid and seronegative arthritis. Five patients (55%) displayed radiographic features consistent with a diagnosis of rheumatoid arthritis, two patients (22%) showed radiographic features of seronegative disorder (periostitis and sacroiliitis), and two patients (22%) showed a mixed picture with evidence of both rheumatoid arthritis and a seronegative disorder. Thus, the HLA-B27 allele contributed to the radiographic features in 44% of patients with rheumatoid arthritis and associated HLA-B27. Thus, the wide range of findings in our population indicates that the radiographic attributes are not specific enough to constitute a unique subpopulation of patients with rheumatoid arthritis. (orig.)

The radiographic features of rheumatoid arthritis in HLA-B27-positive patients

International Nuclear Information System (INIS)

Rundback, J.H.; Rosenberg, Z.S.; Solomon, G.

1993-01-01

Radiographs were reviewed in a group of nine patients with classical seropositive rheumatoid arthritis who on tissue typing were found to express the class I HLA-B27 allele. Radiographs were analyzed with regard to whether or not they demonstrated radiographic features of (1) classical rheumatoid arthritis, (2) seronegative arthritis, or (3) mixed features of rheumatoid and seronegative arthritis. Five patients (55%) displayed radiographic features consistent with a diagnosis of rheumatoid arthritis, two patients (22%) showed radiographic features of seronegative disorder (periostitis and sacroiliitis), and two patients (22%) showed a mixed picture with evidence of both rheumatoid arthritis and a seronegative disorder. Thus, the HLA-B27 allele contributed to the radiographic features in 44% of patients with rheumatoid arthritis and associated HLA-B27. Thus, the wide range of findings in our population indicates that the radiographic attributes are not specific enough to constitute a unique subpopulation of patients with rheumatoid arthritis. (orig.)

Victimization and psychopathic features in a population-based sample of Finnish adolescents.

Science.gov (United States)

Saukkonen, Suvi; Aronen, Eeva T; Laajasalo, Taina; Salmi, Venla; Kivivuori, Janne; Jokela, Markus

2016-10-01

We examined different forms of victimization experiences in relation to psychopathic features and whether these associations differed in boys and girls among 4855 Finnish school adolescents aged 15-16 years. Psychopathic features were measured with the Antisocial Process Screening Device- Self Report (APSD-SR). Victimization was assessed with questions about violent and abusive experiences across lifetime and within the last 12 months. Results from linear regression analysis showed that victimization was significantly associated with higher APSD-SR total scores, more strongly in girls than boys. Recent (12-month) victimization showed significance in the relationship between victimization and psychopathic features; especially recent sexual abuse and parental corporal punishment were strong determinants of higher APSD-SR total scores. The present study demonstrates novel findings on how severe victimization experiences relate to psychopathic features in community youth, especially in girls. The findings underscore the need for comprehensive evaluation of victimization experiences when psychopathic features are present in youth. Copyright © 2016 Elsevier Ltd. All rights reserved.

Diffusion tensor image registration using hybrid connectivity and tensor features.

Science.gov (United States)

Wang, Qian; Yap, Pew-Thian; Wu, Guorong; Shen, Dinggang

2014-07-01

Most existing diffusion tensor imaging (DTI) registration methods estimate structural correspondences based on voxelwise matching of tensors. The rich connectivity information that is given by DTI, however, is often neglected. In this article, we propose to integrate complementary information given by connectivity features and tensor features for improved registration accuracy. To utilize connectivity information, we place multiple anchors representing different brain anatomies in the image space, and define the connectivity features for each voxel as the geodesic distances from all anchors to the voxel under consideration. The geodesic distance, which is computed in relation to the tensor field, encapsulates information of brain connectivity. We also extract tensor features for every voxel to reflect the local statistics of tensors in its neighborhood. We then combine both connectivity features and tensor features for registration of tensor images. From the images, landmarks are selected automatically and their correspondences are determined based on their connectivity and tensor feature vectors. The deformation field that deforms one tensor image to the other is iteratively estimated and optimized according to the landmarks and their associated correspondences. Experimental results show that, by using connectivity features and tensor features simultaneously, registration accuracy is increased substantially compared with the cases using either type of features alone. Copyright © 2013 Wiley Periodicals, Inc.

Investigation of efficient features for image recognition by neural networks.

Science.gov (United States)

Goltsev, Alexander; Gritsenko, Vladimir

2012-04-01

In the paper, effective and simple features for image recognition (named LiRA-features) are investigated in the task of handwritten digit recognition. Two neural network classifiers are considered-a modified 3-layer perceptron LiRA and a modular assembly neural network. A method of feature selection is proposed that analyses connection weights formed in the preliminary learning process of a neural network classifier. In the experiments using the MNIST database of handwritten digits, the feature selection procedure allows reduction of feature number (from 60 000 to 7000) preserving comparable recognition capability while accelerating computations. Experimental comparison between the LiRA perceptron and the modular assembly neural network is accomplished, which shows that recognition capability of the modular assembly neural network is somewhat better. Copyright © 2011 Elsevier Ltd. All rights reserved.

Automatically measuring the effect of strategy drawing features on pupils' handwriting and gender

Science.gov (United States)

Tabatabaey-Mashadi, Narges; Sudirman, Rubita; Guest, Richard M.; Khalid, Puspa Inayat

2013-12-01

Children's dynamic drawing strategies have been recently recognized as indicators of handwriting ability. However the influence of each feature in predicting handwriting is unknown due to lack of a measuring system. An automated measuring algorithm suitable for psychological assessment and non-subjective scoring is presented here. Using the weight vector and classification rate of a machine learning algorithm, an overall feature's effect is calculated which is comparable in different groupings. In this study thirteen previously detected drawing strategy features are measured for their influence on handwriting and gender. Features are extracted from drawing a triangle, Beery VMI and Bender Gestalt tangent patterns. Samples are related to 203 pupils (77 below average writers, and 101 female). The results show that the number of strokes in drawing the triangle pattern plays a major role in both groupings; however Left Tendency flag feature is affected by children's handwriting about 2.5 times greater than their gender. Experiments indicate that different forms of a feature sometimes show different influences.

Multiscale deep features learning for land-use scene recognition

Science.gov (United States)

Yuan, Baohua; Li, Shijin; Li, Ning

2018-01-01

The features extracted from deep convolutional neural networks (CNNs) have shown their promise as generic descriptors for land-use scene recognition. However, most of the work directly adopts the deep features for the classification of remote sensing images, and does not encode the deep features for improving their discriminative power, which can affect the performance of deep feature representations. To address this issue, we propose an effective framework, LASC-CNN, obtained by locality-constrained affine subspace coding (LASC) pooling of a CNN filter bank. LASC-CNN obtains more discriminative deep features than directly extracted from CNNs. Furthermore, LASC-CNN builds on the top convolutional layers of CNNs, which can incorporate multiscale information and regions of arbitrary resolution and sizes. Our experiments have been conducted using two widely used remote sensing image databases, and the results show that the proposed method significantly improves the performance when compared to other state-of-the-art methods.

The Perceptions of Users’ on eBook Readers’ Features

Directory of Open Access Journals (Sweden)

Erhan DELEN

2014-12-01

Full Text Available The purpose of this study was to investigate eBook reader (ER users’ perceptions on eBook readers’ features and explore how users’ opinions differ based on their personal characteristics. The sample of the study was 82 ER users who had at least a bachelor’s degree. In order to figure out the reasons of using ERs, participants were asked several questions about technical, mobility, and access features of ERs. The collected data was analyzed with t-test and ANOVA. As a result, it was found that mobility features of ERs are the most important reasons for users to prefer using an ER. When users’ personal characteristics were considered, it was found that, users who use an ER in daily basis or for an academic purpose, use ERs’ technical and access features more than other users. Results also show that users don't tend to use very specific features of ERs such as text to speech and printing

Iris recognition using possibilistic fuzzy matching on local features.

Science.gov (United States)

Tsai, Chung-Chih; Lin, Heng-Yi; Taur, Jinshiuh; Tao, Chin-Wang

2012-02-01

In this paper, we propose a novel possibilistic fuzzy matching strategy with invariant properties, which can provide a robust and effective matching scheme for two sets of iris feature points. In addition, the nonlinear normalization model is adopted to provide more accurate position before matching. Moreover, an effective iris segmentation method is proposed to refine the detected inner and outer boundaries to smooth curves. For feature extraction, the Gabor filters are adopted to detect the local feature points from the segmented iris image in the Cartesian coordinate system and to generate a rotation-invariant descriptor for each detected point. After that, the proposed matching algorithm is used to compute a similarity score for two sets of feature points from a pair of iris images. The experimental results show that the performance of our system is better than those of the systems based on the local features and is comparable to those of the typical systems.

Weighted Feature Gaussian Kernel SVM for Emotion Recognition.

Science.gov (United States)

Wei, Wei; Jia, Qingxuan

2016-01-01

Emotion recognition with weighted feature based on facial expression is a challenging research topic and has attracted great attention in the past few years. This paper presents a novel method, utilizing subregion recognition rate to weight kernel function. First, we divide the facial expression image into some uniform subregions and calculate corresponding recognition rate and weight. Then, we get a weighted feature Gaussian kernel function and construct a classifier based on Support Vector Machine (SVM). At last, the experimental results suggest that the approach based on weighted feature Gaussian kernel function has good performance on the correct rate in emotion recognition. The experiments on the extended Cohn-Kanade (CK+) dataset show that our method has achieved encouraging recognition results compared to the state-of-the-art methods.

The urban features of informal settlements in Jakarta, Indonesia.

Science.gov (United States)

Alzamil, Waleed

2017-12-01

This data article contains the urban features of three informal settlements in Jakarta: A. Kampung Bandan; B. Kampung Luar Batang; And C. Kampung Muara Baru. The data describes the urban features of physical structures, infrastructures, and public services. These data include maps showing locations of these settlements, photography of urban status, and examples of urban fabric. The data are obtained from the statistical records and field surveys of three settlements cases.

Engineering and safety features of modular vault dry storage

International Nuclear Information System (INIS)

Deacon, D.; Wheeler, D.J.

1984-01-01

This paper discusses the need for interim dry storage and reviews detailed features of the Modular Vault Dry storage concept. The concept meets three basic utility requirements. Firstly, the technology and safety features have been demonstrated on existing plant; secondly, it can be built and licensed in an acceptably short timescale; and thirdly, economic analysis shows that a modular vault dry store is often the cheapest option for interim storage

Prototype Theory Based Feature Representation for PolSAR Images

OpenAIRE

Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

2016-01-01

This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our...

Comparison of Image Transform-Based Features for Visual Speech Recognition in Clean and Corrupted Videos

Directory of Open Access Journals (Sweden)

Seymour Rowan

2008-01-01

Full Text Available Abstract We present results of a study into the performance of a variety of different image transform-based feature types for speaker-independent visual speech recognition of isolated digits. This includes the first reported use of features extracted using a discrete curvelet transform. The study will show a comparison of some methods for selecting features of each feature type and show the relative benefits of both static and dynamic visual features. The performance of the features will be tested on both clean video data and also video data corrupted in a variety of ways to assess each feature type's robustness to potential real-world conditions. One of the test conditions involves a novel form of video corruption we call jitter which simulates camera and/or head movement during recording.

Comparison of Image Transform-Based Features for Visual Speech Recognition in Clean and Corrupted Videos

Directory of Open Access Journals (Sweden)

Ji Ming

2008-03-01

Full Text Available We present results of a study into the performance of a variety of different image transform-based feature types for speaker-independent visual speech recognition of isolated digits. This includes the first reported use of features extracted using a discrete curvelet transform. The study will show a comparison of some methods for selecting features of each feature type and show the relative benefits of both static and dynamic visual features. The performance of the features will be tested on both clean video data and also video data corrupted in a variety of ways to assess each feature type's robustness to potential real-world conditions. One of the test conditions involves a novel form of video corruption we call jitter which simulates camera and/or head movement during recording.

Unsupervised Feature Subset Selection

DEFF Research Database (Denmark)

Søndberg-Madsen, Nicolaj; Thomsen, C.; Pena, Jose

2003-01-01

This paper studies filter and hybrid filter-wrapper feature subset selection for unsupervised learning (data clustering). We constrain the search for the best feature subset by scoring the dependence of every feature on the rest of the features, conjecturing that these scores discriminate some ir...... irrelevant features. We report experimental results on artificial and real data for unsupervised learning of naive Bayes models. Both the filter and hybrid approaches perform satisfactorily....

Boosting instance prototypes to detect local dermoscopic features.

Science.gov (United States)

Situ, Ning; Yuan, Xiaojing; Zouridakis, George

2010-01-01

Local dermoscopic features are useful in many dermoscopic criteria for skin cancer detection. We address the problem of detecting local dermoscopic features from epiluminescence (ELM) microscopy skin lesion images. We formulate the recognition of local dermoscopic features as a multi-instance learning (MIL) problem. We employ the method of diverse density (DD) and evidence confidence (EC) function to convert MIL to a single-instance learning (SIL) problem. We apply Adaboost to improve the classification performance with support vector machines (SVMs) as the base classifier. We also propose to boost the selection of instance prototypes through changing the data weights in the DD function. We validate the methods on detecting ten local dermoscopic features from a dataset with 360 images. We compare the performance of the MIL approach, its boosting version, and a baseline method without using MIL. Our results show that boosting can provide performance improvement compared to the other two methods.

Polyarteritis nodosa presenting with clinical and radiologic features suggestive of polymyositis.

LENUS (Irish Health Repository)

Haroon, Muhammad

2011-02-18

We report a patient who presented with clinical and MRI findings suggestive of polymyositis but, in whom, muscle biopsy disclosed a strikingly different diagnosis. A 65-year-old woman presented with 3-week history of bilateral proximal muscle pain and weakness. Laboratory investigations showed markedly elevated inflammatory markers and mildly elevated muscle enzymes. MRI scans of lower limbs showed features suggestive of polymyositis. However, muscle biopsy showed features of a polyarteritis-type vasculitis affecting an intramuscular blood vessel. Our reports highlight the critical role of muscle biopsy in establishing the correct diagnosis in patients with suspected myositis.

Neural Tuning to Low-Level Features of Speech throughout the Perisylvian Cortex.

Science.gov (United States)

Berezutskaya, Julia; Freudenburg, Zachary V; Güçlü, Umut; van Gerven, Marcel A J; Ramsey, Nick F

2017-08-16

Despite a large body of research, we continue to lack a detailed account of how auditory processing of continuous speech unfolds in the human brain. Previous research showed the propagation of low-level acoustic features of speech from posterior superior temporal gyrus toward anterior superior temporal gyrus in the human brain (Hullett et al., 2016). In this study, we investigate what happens to these neural representations past the superior temporal gyrus and how they engage higher-level language processing areas such as inferior frontal gyrus. We used low-level sound features to model neural responses to speech outside of the primary auditory cortex. Two complementary imaging techniques were used with human participants (both males and females): electrocorticography (ECoG) and fMRI. Both imaging techniques showed tuning of the perisylvian cortex to low-level speech features. With ECoG, we found evidence of propagation of the temporal features of speech sounds along the ventral pathway of language processing in the brain toward inferior frontal gyrus. Increasingly coarse temporal features of speech spreading from posterior superior temporal cortex toward inferior frontal gyrus were associated with linguistic features such as voice onset time, duration of the formant transitions, and phoneme, syllable, and word boundaries. The present findings provide the groundwork for a comprehensive bottom-up account of speech comprehension in the human brain. SIGNIFICANCE STATEMENT We know that, during natural speech comprehension, a broad network of perisylvian cortical regions is involved in sound and language processing. Here, we investigated the tuning to low-level sound features within these regions using neural responses to a short feature film. We also looked at whether the tuning organization along these brain regions showed any parallel to the hierarchy of language structures in continuous speech. Our results show that low-level speech features propagate throughout the

Templates for Rejection: Configuring Attention to Ignore Task-Irrelevant Features

Science.gov (United States)

Arita, Jason T.; Carlisle, Nancy B.; Woodman, Geoffrey F.

2012-01-01

Theories of attention are compatible with the idea that we can bias attention to avoid selecting objects that have known nontarget features. Although this may underlie several existing phenomena, the explicit guidance of attention away from known nontargets has yet to be demonstrated. Here we show that observers can use feature cues (i.e., color)…

Joint Markov Blankets in Feature Sets Extracted from Wavelet Packet Decompositions

Directory of Open Access Journals (Sweden)

Gert Van Dijck

2011-07-01

Full Text Available Since two decades, wavelet packet decompositions have been shown effective as a generic approach to feature extraction from time series and images for the prediction of a target variable. Redundancies exist between the wavelet coefficients and between the energy features that are derived from the wavelet coefficients. We assess these redundancies in wavelet packet decompositions by means of the Markov blanket filtering theory. We introduce the concept of joint Markov blankets. It is shown that joint Markov blankets are a natural extension of Markov blankets, which are defined for single features, to a set of features. We show that these joint Markov blankets exist in feature sets consisting of the wavelet coefficients. Furthermore, we prove that wavelet energy features from the highest frequency resolution level form a joint Markov blanket for all other wavelet energy features. The joint Markov blanket theory indicates that one can expect an increase of classification accuracy with the increase of the frequency resolution level of the energy features.

Multi-task feature selection in microarray data by binary integer programming.

Science.gov (United States)

Lan, Liang; Vucetic, Slobodan

2013-12-20

A major challenge in microarray classification is that the number of features is typically orders of magnitude larger than the number of examples. In this paper, we propose a novel feature filter algorithm to select the feature subset with maximal discriminative power and minimal redundancy by solving a quadratic objective function with binary integer constraints. To improve the computational efficiency, the binary integer constraints are relaxed and a low-rank approximation to the quadratic term is applied. The proposed feature selection algorithm was extended to solve multi-task microarray classification problems. We compared the single-task version of the proposed feature selection algorithm with 9 existing feature selection methods on 4 benchmark microarray data sets. The empirical results show that the proposed method achieved the most accurate predictions overall. We also evaluated the multi-task version of the proposed algorithm on 8 multi-task microarray datasets. The multi-task feature selection algorithm resulted in significantly higher accuracy than when using the single-task feature selection methods.

Quality of Radiomic Features in Glioblastoma Multiforme: Impact of Semi-Automated Tumor Segmentation Software.

Science.gov (United States)

Lee, Myungeun; Woo, Boyeong; Kuo, Michael D; Jamshidi, Neema; Kim, Jong Hyo

2017-01-01

The purpose of this study was to evaluate the reliability and quality of radiomic features in glioblastoma multiforme (GBM) derived from tumor volumes obtained with semi-automated tumor segmentation software. MR images of 45 GBM patients (29 males, 16 females) were downloaded from The Cancer Imaging Archive, in which post-contrast T1-weighted imaging and fluid-attenuated inversion recovery MR sequences were used. Two raters independently segmented the tumors using two semi-automated segmentation tools (TumorPrism3D and 3D Slicer). Regions of interest corresponding to contrast-enhancing lesion, necrotic portions, and non-enhancing T2 high signal intensity component were segmented for each tumor. A total of 180 imaging features were extracted, and their quality was evaluated in terms of stability, normalized dynamic range (NDR), and redundancy, using intra-class correlation coefficients, cluster consensus, and Rand Statistic. Our study results showed that most of the radiomic features in GBM were highly stable. Over 90% of 180 features showed good stability (intra-class correlation coefficient [ICC] ≥ 0.8), whereas only 7 features were of poor stability (ICC NDR ≥1), while above 35% of the texture features showed poor NDR (software tools provided sufficiently reliable tumor segmentation and feature stability; thus helping to overcome the inherent inter-rater and intra-rater variability of user intervention. However, certain aspects of feature quality, including NDR and redundancy, need to be assessed for determination of representative signature features before further development of radiomics.

Global seafloor geomorphic features map: applications for ocean conservation and management

Science.gov (United States)

Harris, P. T.; Macmillan-Lawler, M.; Rupp, J.; Baker, E.

2013-12-01

Seafloor geomorphology, mapped and measured by marine scientists, has proven to be a very useful physical attribute for ocean management because different geomorphic features (eg. submarine canyons, seamounts, spreading ridges, escarpments, plateaus, trenches etc.) are commonly associated with particular suites of habitats and biological communities. Although we now have better bathymetric datasets than ever before, there has been little effort to integrate these data to create an updated map of seabed geomorphic features or habitats. Currently the best available global seafloor geomorphic features map is over 30 years old. A new global seafloor geomorphic features map (GSGM) has been created based on the analysis and interpretation of the SRTM (Shuttle Radar Topography Mission) 30 arc-second (~1 km) global bathymetry grid. The new map includes global spatial data layers for 29 categories of geomorphic features, defined by the International Hydrographic Organisation. The new geomorphic features map will allow: 1) Characterization of bioregions in terms of their geomorphic content (eg. GOODS bioregions, Large Marine Ecosystems (LMEs), ecologically or biologically significant areas (EBSA)); 2) Prediction of the potential spatial distribution of vulnerable marine ecosystems (VME) and marine genetic resources (MGR; eg. associated with hydrothermal vent communities, shelf-incising submarine canyons and seamounts rising to a specified depth); and 3) Characterization of national marine jurisdictions in terms of their inventory of geomorphic features and their global representativeness of features. To demonstrate the utility of the GSGM, we have conducted an analysis of the geomorphic feature content of the current global inventory of marine protected areas (MPAs) to assess the extent to which features are currently represented. The analysis shows that many features have very low representation, for example fans and rises have less than 1 per cent of their total area

Featureous: an Integrated Approach to Location, Analysis and Modularization of Features in Java Applications

DEFF Research Database (Denmark)

Olszak, Andrzej

, it is essential that features are properly modularized within the structural organization of software systems. Nevertheless, in many object-oriented applications, features are not represented explicitly. Consequently, features typically end up scattered and tangled over multiple source code units......, such as architectural layers, packages and classes. This lack of modularization is known to make application features difficult to locate, to comprehend and to modify in isolation from one another. To overcome these problems, this thesis proposes Featureous, a novel approach to location, analysis and modularization...... quantitative and qualitative results suggest that Featureous succeeds at efficiently locating features in unfamiliar codebases, at aiding feature-oriented comprehension and modification, and at improving modularization of features using Java packages....

Audiovisual laughter detection based on temporal features

NARCIS (Netherlands)

Petridis, Stavros; Nijholt, Antinus; Nijholt, A.; Pantic, M.; Pantic, Maja; Poel, Mannes; Poel, M.; Hondorp, G.H.W.

2008-01-01

Previous research on automatic laughter detection has mainly been focused on audio-based detection. In this study we present an audiovisual approach to distinguishing laughter from speech based on temporal features and we show that the integration of audio and visual information leads to improved

Invariant properties between stroke features in handwriting

NARCIS (Netherlands)

Teulings, H L; Schomaker, L R

A handwriting pattern is considered as a sequence of ballistic strokes. Replications of a pattern may be generated from a single, higher-level memory representation, acting as a motor program. Therefore, those stroke features which show the most invariant pattern are probably related to the

Optimization of an individual re-identification modeling process using biometric features

Energy Technology Data Exchange (ETDEWEB)

Heredia-Langner, Alejandro; Amidan, Brett G.; Matzner, Shari; Jarman, Kristin H.

2014-09-24

We present results from the optimization of a re-identification process using two sets of biometric data obtained from the Civilian American and European Surface Anthropometry Resource Project (CAESAR) database. The datasets contain real measurements of features for 2378 individuals in a standing (43 features) and seated (16 features) position. A genetic algorithm (GA) was used to search a large combinatorial space where different features are available between the probe (seated) and gallery (standing) datasets. Results show that optimized model predictions obtained using less than half of the 43 gallery features and data from roughly 16% of the individuals available produce better re-identification rates than two other approaches that use all the information available.

Orienting in virtual environments: How are surface features and environmental geometry weighted in an orientation task?

Science.gov (United States)

Kelly, Debbie M; Bischof, Walter F

2008-10-01

We investigated how human adults orient in enclosed virtual environments, when discrete landmark information is not available and participants have to rely on geometric and featural information on the environmental surfaces. In contrast to earlier studies, where, for women, the featural information from discrete landmarks overshadowed the encoding of the geometric information, Experiment 1 showed that when featural information is conjoined with the environmental surfaces, men and women encoded both types of information. Experiment 2 showed that, although both types of information are encoded, performance in locating a goal position is better if it is close to a geometrically or featurally distinct location. Furthermore, although features are relied upon more strongly than geometry, initial experience with an environment influences the relative weighting of featural and geometric cues. Taken together, these results show that human adults use a flexible strategy for encoding spatial information.

Design features to reduce occupational exposure

International Nuclear Information System (INIS)

Adam, J.A.; DiSabatino, A.A. Jr.; Vanasse, R.E.

1975-01-01

Some of the design principles which are important considerations in the evolution of a nuclear power plant design to ensure that occupational radiation exposures can be minimized are discussed. Emphasis is placed on the design features affecting the basic layout and equipment locations within the plant. Examples are provided showing how these design objectives are realized in the Stone and Webster Reference Nuclear Power Plant Design, with particular emphasis on the Annulus Building portion of the reference plant. Design features which are useful in reducing occupational exposure during normal operation are discussed initially, followed by those that chiefly affect exposures during maintenance activity. Finally, those provisions in the design which assist in preventing the spread of radioactive contamination are presented

High-level intuitive features (HLIFs) for intuitive skin lesion description.

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Amelard, Robert; Glaister, Jeffrey; Wong, Alexander; Clausi, David A

2015-03-01

A set of high-level intuitive features (HLIFs) is proposed to quantitatively describe melanoma in standard camera images. Melanoma is the deadliest form of skin cancer. With rising incidence rates and subjectivity in current clinical detection methods, there is a need for melanoma decision support systems. Feature extraction is a critical step in melanoma decision support systems. Existing feature sets for analyzing standard camera images are comprised of low-level features, which exist in high-dimensional feature spaces and limit the system's ability to convey intuitive diagnostic rationale. The proposed HLIFs were designed to model the ABCD criteria commonly used by dermatologists such that each HLIF represents a human-observable characteristic. As such, intuitive diagnostic rationale can be conveyed to the user. Experimental results show that concatenating the proposed HLIFs with a full low-level feature set increased classification accuracy, and that HLIFs were able to separate the data better than low-level features with statistical significance. An example of a graphical interface for providing intuitive rationale is given.

Characteristics of circular features on comet 67P/Churyumov-Gerasimenko

Science.gov (United States)

Deller, J. F.; Güttler, C.; Tubiana, C.; Hofmann, M.; Sierks, H.

2017-09-01

Comet 67P/Churyumov-Gerasimenko shows a large variety of circular structures such as pits, elevated roundish features in Imhotep, and even a single occurrence of a plausible fresh impact crater. Imaging the pits in the Ma'at region, aiming to understand their structure and origin drove the design of the final descent trajectory of the Rosetta spacecraft. The high-resolution images obtained during the last mission phase allow us to study these pits as exemplary circular features. A complete catalogue of circular features gives us the possibility to compare and classify these structures systematically.

Turkish Music Genre Classification using Audio and Lyrics Features

Directory of Open Access Journals (Sweden)

Önder ÇOBAN

2017-05-01

Full Text Available Music Information Retrieval (MIR has become a popular research area in recent years. In this context, researchers have developed music information systems to find solutions for such major problems as automatic playlist creation, hit song detection, and music genre or mood classification. Meta-data information, lyrics, or melodic content of music are used as feature resource in previous works. However, lyrics do not often used in MIR systems and the number of works in this field is not enough especially for Turkish. In this paper, firstly, we have extended our previously created Turkish MIR (TMIR dataset, which comprises of Turkish lyrics, by including the audio file of each song. Secondly, we have investigated the effect of using audio and textual features together or separately on automatic Music Genre Classification (MGC. We have extracted textual features from lyrics using different feature extraction models such as word2vec and traditional Bag of Words. We have conducted our experiments on Support Vector Machine (SVM algorithm and analysed the impact of feature selection and different feature groups on MGC. We have considered lyrics based MGC as a text classification task and also investigated the effect of term weighting method. Experimental results show that textual features can also be effective as well as audio features for Turkish MGC, especially when a supervised term weighting method is employed. We have achieved the highest success rate as 99,12\\% by using both audio and textual features together.

Pleomorphic xanthoastrocytoma with anaplastic features: one case report and review of literature

Directory of Open Access Journals (Sweden)

Cui-yun SUN

2014-12-01

Full Text Available Objective To investigate the clinicopathological features of pleomorphic xanthoastrocytoma with anaplastic features (PXA-A.  Methods The clinical manifestations, imaging, histopathological features, and immunophenotype were analyzed in one case of PXA-A, and relevant literatures were reviewed. Results The patient was a 58-year-old woman. MRI examination revealed a parenchyma mass with irregularly long T1 and long T2 signal in right temporal lobe and basal ganglia region. The border was clear and peritumoral edema was inconspicuous. The mesocephalon and right ventricle were compressed, and the midline was shifted to left. Enhanced MRI showed multiple flaky and nodular enhancement. Histologically, tumor cells showed remarkable cellular pleomorphism, and they were composed of mononuclear cells, multinuclear giant tumor cells, frothy tumor cells and spindle cells. Eosinophilic granular bodies and intranuclear inclusions were seen. Tumor cells in partial regions were intensively arranged, with obvious atypia. Immunohistochemical analysis showed immunoreactivity of the cells to glial fibrillary acidic protein (GFAP, Vimentin (Vim, S-100 protein (S-100, neuronal nuclei (NeuN and P53. The cells showed a negative reaction for synaptophysin (Syn, chromogranin A (CgA, neurofilament protein (NF, CD34 and isocitrate dehydrogenase 1 (IDH1. The Ki-67 label index was 8.20% .  Conclusions PXA-A is a rare tumor. The imaging features can offer a few diagnostic cues. However, a definite diagnosis depends on the histological and immunohistochemical features. doi: 10.3969/j.issn.1672-6731.2014.12.013

Dependency Parsing with Transformed Feature

Directory of Open Access Journals (Sweden)

Fuxiang Wu

2017-01-01

Full Text Available Dependency parsing is an important subtask of natural language processing. In this paper, we propose an embedding feature transforming method for graph-based parsing, transform-based parsing, which directly utilizes the inner similarity of the features to extract information from all feature strings including the un-indexed strings and alleviate the feature sparse problem. The model transforms the extracted features to transformed features via applying a feature weight matrix, which consists of similarities between the feature strings. Since the matrix is usually rank-deficient because of similar feature strings, it would influence the strength of constraints. However, it is proven that the duplicate transformed features do not degrade the optimization algorithm: the margin infused relaxed algorithm. Moreover, this problem can be alleviated by reducing the number of the nearest transformed features of a feature. In addition, to further improve the parsing accuracy, a fusion parser is introduced to integrate transformed and original features. Our experiments verify that both transform-based and fusion parser improve the parsing accuracy compared to the corresponding feature-based parser.

Improved pulmonary nodule classification utilizing quantitative lung parenchyma features.

Science.gov (United States)

Dilger, Samantha K N; Uthoff, Johanna; Judisch, Alexandra; Hammond, Emily; Mott, Sarah L; Smith, Brian J; Newell, John D; Hoffman, Eric A; Sieren, Jessica C

2015-10-01

Current computer-aided diagnosis (CAD) models for determining pulmonary nodule malignancy characterize nodule shape, density, and border in computed tomography (CT) data. Analyzing the lung parenchyma surrounding the nodule has been minimally explored. We hypothesize that improved nodule classification is achievable by including features quantified from the surrounding lung tissue. To explore this hypothesis, we have developed expanded quantitative CT feature extraction techniques, including volumetric Laws texture energy measures for the parenchyma and nodule, border descriptors using ray-casting and rubber-band straightening, histogram features characterizing densities, and global lung measurements. Using stepwise forward selection and leave-one-case-out cross-validation, a neural network was used for classification. When applied to 50 nodules (22 malignant and 28 benign) from high-resolution CT scans, 52 features (8 nodule, 39 parenchymal, and 5 global) were statistically significant. Nodule-only features yielded an area under the ROC curve of 0.918 (including nodule size) and 0.872 (excluding nodule size). Performance was improved through inclusion of parenchymal (0.938) and global features (0.932). These results show a trend toward increased performance when the parenchyma is included, coupled with the large number of significant parenchymal features that support our hypothesis: the pulmonary parenchyma is influenced differentially by malignant versus benign nodules, assisting CAD-based nodule characterizations.

Psychopathological features in Noonan syndrome.

Science.gov (United States)

Perrino, Francesca; Licchelli, Serena; Serra, Giulia; Piccini, Giorgia; Caciolo, Cristina; Pasqualetti, Patrizio; Cirillo, Flavia; Leoni, Chiara; Digilio, Maria Cristina; Zampino, Giuseppe; Tartaglia, Marco; Alfieri, Paolo; Vicari, Stefano

2018-01-01

Noonan syndrome (NS) is an autosomal dominant disorder characterized by short stature, skeletal and haematological/lymphatic defects, distinctive facies, cryptorchidism, and a wide spectrum of congenital heart defects. Recurrent features also include variable cognitive deficits and behavioural problems. Recent research has been focused on the assessment of prevalence, age of onset and characterization of psychiatric features in this disorder. Herein, we evaluated the prevalence of attention deficit and hyperactivity disorder (ADHD), anxiety and depressive symptoms and syndromes in a cohort of individuals with clinical and molecular diagnosis of NS. The Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children Present and Lifetime version (K-SADS PL) has been used for the assessment of psychiatric disorders according to Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). Multidimensional Anxiety Scale for Children (MASC) and the Children's Depression Inventory (CDI) have been assessed for the evaluation of anxiety and depressive symptoms and syndromes, whereas Conners Teacher and Parent Rating Scales-long version (CRS-R) have been used to evaluate ADHD. The study included 27 individuals (67% males) with an average age of 10.4 years (range 6-18 years) receiving molecular diagnosis of NS or a clinically related condition, evaluated and treated at the Neuropsychiatric Unit of Children's Hospital Bambino Gesù and at the Center for Rare Diseases of Fondazione Policlinico Universitario Agostino Gemelli, in Rome. Twenty individuals showed mutations in PTPN11, five in SOS1 and two in SHOC2. The mean IQ was 94 (Standard Deviation = 17, min = 56, max = 130). Seventy percent of the individuals (n = 19; 95% Confidence Interval = 52-85%) showed ADHD features, with six individuals reaching DSM-IV-TR criteria for ADHD disorder, and thirteen showing subsyndromal traits. Symptoms or syndrome of anxiety were present in 37% of the cohort

Generating description with multi-feature fusion and saliency maps of image

Science.gov (United States)

Liu, Lisha; Ding, Yuxuan; Tian, Chunna; Yuan, Bo

2018-04-01

Generating description for an image can be regard as visual understanding. It is across artificial intelligence, machine learning, natural language processing and many other areas. In this paper, we present a model that generates description for images based on RNN (recurrent neural network) with object attention and multi-feature of images. The deep recurrent neural networks have excellent performance in machine translation, so we use it to generate natural sentence description for images. The proposed method uses single CNN (convolution neural network) that is trained on ImageNet to extract image features. But we think it can not adequately contain the content in images, it may only focus on the object area of image. So we add scene information to image feature using CNN which is trained on Places205. Experiments show that model with multi-feature extracted by two CNNs perform better than which with a single feature. In addition, we make saliency weights on images to emphasize the salient objects in images. We evaluate our model on MSCOCO based on public metrics, and the results show that our model performs better than several state-of-the-art methods.

Comparison on imaging features of central serous chorioretinopathy fundus

Directory of Open Access Journals (Sweden)

Ji-Jin Zhang

2014-10-01

Full Text Available AIM: To explore and analyze the image features, diagnosis and treatment of the central serous chorioretinopathy(CSCRfundus. METHODS: From May 2008 to May 2014, 97 cases of 121 eyes with central serous chorioretinopathy were treated in in our hospital. The imaging features were compared and analyzed through different methods. RESULTS: Sixty-one cases(61 eyeswere ≤45 years, including 13 case with disease in both eyes, single stove leak accounted for 48.6%, multifocal leakage(25.7%, atypical leakage accounted for 25.7%. Thirty-six cases(47 eyeswere >45 years, 11 cases with disease in both eyes, single focal leakage(8.5%, multifocal leakage(48.9%, atypical leakage accounted for 42.6%. FFA results showed acute hairstyle at the beginning of 89 eyes, chronic deferment type 32 eyes. OCT examination showed that the main features were neuroepithelial detachment, as well as the change of the retinal pigment epithelium(RPElayer, which was divided into RPE layer detachment 93 eyes, accounting for 76.9%, rough and RPE little ridges in 28 cases, accounting for 23.1%. The average thickness of macular center concave on the cortex of microns was 137.87±19.21μm, and there was no significant difference conpared with normal(137.32±4.98μmmicrons(t=0.30, P>0.05. The closer leakage area to macular fovea, the worse of eyesight.. CONCLUSION: Different imaging examination on central serous chorioretinopathy can show different features. For clinical diagnosis and treatment it had different and complementary roles, but were given significant help for diseases treatment.

Functionality of system components: Conservation of protein function in protein feature space

DEFF Research Database (Denmark)

Jensen, Lars Juhl; Ussery, David; Brunak, Søren

2003-01-01

well on organisms other than the one on which it was trained. We evaluate the performance of such a method, ProtFun, which relies on protein features as its sole input, and show that the method gives similar performance for most eukaryotes and performs much better than anticipated on archaea......Many protein features useful for prediction of protein function can be predicted from sequence, including posttranslational modifications, subcellular localization, and physical/chemical properties. We show here that such protein features are more conserved among orthologs than paralogs, indicating...... they are crucial for protein function and thus subject to selective pressure. This means that a function prediction method based on sequence-derived features may be able to discriminate between proteins with different function even when they have highly similar structure. Also, such a method is likely to perform...

FEATURE DESCRIPTOR BY CONVOLUTION AND POOLING AUTOENCODERS

Directory of Open Access Journals (Sweden)

L. Chen

2015-03-01

Full Text Available In this paper we present several descriptors for feature-based matching based on autoencoders, and we evaluate the performance of these descriptors. In a training phase, we learn autoencoders from image patches extracted in local windows surrounding key points determined by the Difference of Gaussian extractor. In the matching phase, we construct key point descriptors based on the learned autoencoders, and we use these descriptors as the basis for local keypoint descriptor matching. Three types of descriptors based on autoencoders are presented. To evaluate the performance of these descriptors, recall and 1-precision curves are generated for different kinds of transformations, e.g. zoom and rotation, viewpoint change, using a standard benchmark data set. We compare the performance of these descriptors with the one achieved for SIFT. Early results presented in this paper show that, whereas SIFT in general performs better than the new descriptors, the descriptors based on autoencoders show some potential for feature based matching.

Color Doppler Ultrasonographic Features of Hashimoto's Thyroiditis

Energy Technology Data Exchange (ETDEWEB)

Lee, Joo Hyuk; Kim, Mie Young; Rho, Eun Jin; Yi, Jeong Geun; Han, Chun Hwan [Kangnam General Hospital Public Corporation, Seoul (Korea, Republic of); Hwang, Hee Yong [Choong Ang Gil Hospital, Incheon (Korea, Republic of)

1995-06-15

Color Doppler ultrasonographic(US) features of 28 patients with Hashimato's thyroiditis were evaluated with regard to echo and color-flow patterns. Correlation of color-flow pattern with thyroid function was performed. All 28 patients showed varying degrees of diffuse enlargement of the thyroid gland and a heterogeneous echo pattern.Color-flow pattern of increased blood flow. Low to moderate, focally increased blood flow was seen in 26 patients(92.8%). Of these 26 patients, 24 patients showed subclinical hypothyroidism or euthyroidism. Two patients who showed hyperthyroidism showed several pieces of focally increased color flow, Which was noted during both systole and diastole. Diffuse, multifocal color-flow throughout thyroid gland was seen in two patients with Hashimato's thyroiditis: one with clinical hypothyroidism and the other with subclinical hypothyroidism. Even though Hashimoto's thyroiditis showed variable color-flow patterns, we believe that heterogenous parenchymal echopattern with low or moderately increased flow is a rather characteristic feature of Hashimoto's thyroiditis, and we suggest that color Doppler US provides additional information for evaluation of Hashimoto's thyroiditis

Characterizing the nature of visual conscious access: the distinction between features and locations.

Science.gov (United States)

Huang, Liqiang

2010-08-24

The difference between the roles of features and locations has been a central topic in the theoretical debates on visual attention. A recent theory proposed that momentary visual awareness is limited to one Boolean map, that is the linkage of one feature per dimension with a set of locations (L. Huang & H. Pashler, 2007). This theory predicts that: (a) access to the features of a set of objects is inefficient whereas access to their locations is efficient; (b) shuffling the locations of objects disrupts access to their features whereas shuffling the features of objects has little impact on access to their locations. Both of these predictions were confirmed in Experiments 1 and 2. Experiments 3 and 4 showed that this feature/location distinction remains when the task involves the detection of changes to old objects rather than the coding of new objects. Experiments 5 and 6 showed that, in a pre-specified set, one missing location can be readily detected, but detecting one missing color is difficult. Taken together, multiple locations seem to be accessed and represented together as a holistic pattern, but features have to be handled as separate labels, one at a time, and do not constitute a pattern in featural space.

Feature selection, statistical modeling and its applications to universal JPEG steganalyzer

Energy Technology Data Exchange (ETDEWEB)

Jalan, Jaikishan [Iowa State Univ., Ames, IA (United States)

2009-01-01

Steganalysis deals with identifying the instances of medium(s) which carry a message for communication by concealing their exisitence. This research focuses on steganalysis of JPEG images, because of its ubiquitous nature and low bandwidth requirement for storage and transmission. JPEG image steganalysis is generally addressed by representing an image with lower-dimensional features such as statistical properties, and then training a classifier on the feature set to differentiate between an innocent and stego image. Our approach is two fold: first, we propose a new feature reduction technique by applying Mahalanobis distance to rank the features for steganalysis. Many successful steganalysis algorithms use a large number of features relative to the size of the training set and suffer from a ”curse of dimensionality”: large number of feature values relative to training data size. We apply this technique to state-of-the-art steganalyzer proposed by Tom´as Pevn´y (54) to understand the feature space complexity and effectiveness of features for steganalysis. We show that using our approach, reduced-feature steganalyzers can be obtained that perform as well as the original steganalyzer. Based on our experimental observation, we then propose a new modeling technique for steganalysis by developing a Partially Ordered Markov Model (POMM) (23) to JPEG images and use its properties to train a Support Vector Machine. POMM generalizes the concept of local neighborhood directionality by using a partial order underlying the pixel locations. We show that the proposed steganalyzer outperforms a state-of-the-art steganalyzer by testing our approach with many different image databases, having a total of 20000 images. Finally, we provide a software package with a Graphical User Interface that has been developed to make this research accessible to local state forensic departments.

Quality of radiomic features in glioblastoma multiforme: Impact of semi-automated tumor segmentation software

International Nuclear Information System (INIS)

Lee, Myung Eun; Kim, Jong Hyo; Woo, Bo Yeong; Ko, Micheal D.; Jamshidi, Neema

2017-01-01

The purpose of this study was to evaluate the reliability and quality of radiomic features in glioblastoma multiforme (GBM) derived from tumor volumes obtained with semi-automated tumor segmentation software. MR images of 45 GBM patients (29 males, 16 females) were downloaded from The Cancer Imaging Archive, in which post-contrast T1-weighted imaging and fluid-attenuated inversion recovery MR sequences were used. Two raters independently segmented the tumors using two semi-automated segmentation tools (TumorPrism3D and 3D Slicer). Regions of interest corresponding to contrast-enhancing lesion, necrotic portions, and non-enhancing T2 high signal intensity component were segmented for each tumor. A total of 180 imaging features were extracted, and their quality was evaluated in terms of stability, normalized dynamic range (NDR), and redundancy, using intra-class correlation coefficients, cluster consensus, and Rand Statistic. Our study results showed that most of the radiomic features in GBM were highly stable. Over 90% of 180 features showed good stability (intra-class correlation coefficient [ICC] ≥ 0.8), whereas only 7 features were of poor stability (ICC NDR ≥1), while above 35% of the texture features showed poor NDR (< 1). Features were shown to cluster into only 5 groups, indicating that they were highly redundant. The use of semi-automated software tools provided sufficiently reliable tumor segmentation and feature stability; thus helping to overcome the inherent inter-rater and intra-rater variability of user intervention. However, certain aspects of feature quality, including NDR and redundancy, need to be assessed for determination of representative signature features before further development of radiomics

A threshold auto-adjustment algorithm of feature points extraction based on grid

Science.gov (United States)

Yao, Zili; Li, Jun; Dong, Gaojie

2018-02-01

When dealing with high-resolution digital images, detection of feature points is usually the very first important step. Valid feature points depend on the threshold. If the threshold is too low, plenty of feature points will be detected, and they may be aggregated in the rich texture regions, which consequently not only affects the speed of feature description, but also aggravates the burden of following processing; if the threshold is set high, the feature points in poor texture area will lack. To solve these problems, this paper proposes a threshold auto-adjustment method of feature extraction based on grid. By dividing the image into numbers of grid, threshold is set in every local grid for extracting the feature points. When the number of feature points does not meet the threshold requirement, the threshold will be adjusted automatically to change the final number of feature points The experimental results show that feature points produced by our method is more uniform and representative, which avoids the aggregation of feature points and greatly reduces the complexity of following work.

Finger vein recognition with personalized feature selection.

Science.gov (United States)

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Meng, Xianjing

2013-08-22

Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.

Finger Vein Recognition with Personalized Feature Selection

Directory of Open Access Journals (Sweden)

Xianjing Meng

2013-08-01

Full Text Available Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG. For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.

Machine learning spatial geometry from entanglement features

Science.gov (United States)

You, Yi-Zhuang; Yang, Zhao; Qi, Xiao-Liang

2018-02-01

Motivated by the close relations of the renormalization group with both the holography duality and the deep learning, we propose that the holographic geometry can emerge from deep learning the entanglement feature of a quantum many-body state. We develop a concrete algorithm, call the entanglement feature learning (EFL), based on the random tensor network (RTN) model for the tensor network holography. We show that each RTN can be mapped to a Boltzmann machine, trained by the entanglement entropies over all subregions of a given quantum many-body state. The goal is to construct the optimal RTN that best reproduce the entanglement feature. The RTN geometry can then be interpreted as the emergent holographic geometry. We demonstrate the EFL algorithm on a 1D free fermion system and observe the emergence of the hyperbolic geometry (AdS3 spatial geometry) as we tune the fermion system towards the gapless critical point (CFT2 point).

MRI features of tuberculosis of the knee

Energy Technology Data Exchange (ETDEWEB)

Sanghvi, Darshana A.; Iyer, Veena R.; Deshmukh, Tejaswini; Hoskote, Sumedh S. [Seth GS Medical College and KEM Hospital, Department of Radiology, Mumbai (India)

2009-03-15

The objective of this study was to describe the magnetic resonance imaging (MRI) features of tuberculosis (TB) of the knee joint. The MRI features in 15 patients with TB of the knee, as confirmed by histology of the biopsied joint synovium, were reviewed retrospectively. The images were assessed for intra-articular and peri-articular abnormalities. All patients had florid synovial proliferation. The proliferating synovium showed intermediate to low T2 signal intensity. In the patients who were administered intravenous contrast, the hypertrophic synovium was intensely enhancing. Marrow edema (n = 9), osteomyelitis (n = 4), cortical erosions (n = 5), myositis (n = 6), cellulitis (n = 2), abscesses (n = 3), and skin ulceration/sinus formation (n = 2) were seen in the adjacent bone and soft tissue. Synovial proliferation associated with tuberculous arthritis is typically hypointense on T2-weighted images. This appearance, in conjunction with other peri-articular MRI features described, can help in distinguishing TB arthritis from other proliferating synovial arthropathies. (orig.)

Multiscale wavelet representations for mammographic feature analysis

Science.gov (United States)

Laine, Andrew F.; Song, Shuwu

1992-12-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet coefficients, enhanced by linear, exponential and constant weight functions localized in scale space. By improving the visualization of breast pathology we can improve the changes of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).

Cases report of ossifying fibroma showing various radiographic appearances in posterior mandible

International Nuclear Information System (INIS)

Lee, Byung Do; Oh, Seung Hwan; Son, Hyun Jin

2010-01-01

Common radiographic appearances of ossifying fibroma (OF) are well demarcated margin, radiolucent or mixed lesion. Lesions for the radiographic differential diagnosis with OF include fibrous dysplasia, focal cemento-osseous dysplasia. Other confusing lesions might be the mixed lesions such as calcifying odontogenic cyst, adenomatoid odontogenic tumor, calcifying epithelial odontogenic tumor, and benign cementoblastoma. We reported three cases of OF in posterior mandible. These cases showed a little distinguished radiographic features of OF and diagnosed from a combination of clinical, radiographic, and histopathologic information. We need to further refine radiographic and histopathological features of OF and other confusing lesions with literatures review because some cases of these lesions are not easily differentiated radiographically and histopathologically.

Cases report of ossifying fibroma showing various radiographic appearances in posterior mandible

Energy Technology Data Exchange (ETDEWEB)

Lee, Byung Do; Oh, Seung Hwan [School of Dentistry, Wonkwang University, Seoul (Korea, Republic of); Son, Hyun Jin [Department of Pathology, School of Medicine, Eulji University, Daejeon (Korea, Republic of)

2010-06-15

Common radiographic appearances of ossifying fibroma (OF) are well demarcated margin, radiolucent or mixed lesion. Lesions for the radiographic differential diagnosis with OF include fibrous dysplasia, focal cemento-osseous dysplasia. Other confusing lesions might be the mixed lesions such as calcifying odontogenic cyst, adenomatoid odontogenic tumor, calcifying epithelial odontogenic tumor, and benign cementoblastoma. We reported three cases of OF in posterior mandible. These cases showed a little distinguished radiographic features of OF and diagnosed from a combination of clinical, radiographic, and histopathologic information. We need to further refine radiographic and histopathological features of OF and other confusing lesions with literatures review because some cases of these lesions are not easily differentiated radiographically and histopathologically.

Language Features and Culture Features on Short Message

Institute of Scientific and Technical Information of China (English)

王佳

2013-01-01

Mobile phone is regarded as“the fifth media”after newspaper,radio,TV and the Internet.The mobile phone short message further highlights the importance of written signs in communication.“The thumb revolution”is eagerly anticipating one kind of trend by the hand replace of mouth,sound substitute for the quiet around us. My paper will analyze the language features and the culture features of mobile phone short messages which are written in Chinese and English.

Two-Level Evaluation on Sensor Interoperability of Features in Fingerprint Image Segmentation

Directory of Open Access Journals (Sweden)

Ya-Shuo Li

2012-03-01

Full Text Available Features used in fingerprint segmentation significantly affect the segmentation performance. Various features exhibit different discriminating abilities on fingerprint images derived from different sensors. One feature which has better discriminating ability on images derived from a certain sensor may not adapt to segment images derived from other sensors. This degrades the segmentation performance. This paper empirically analyzes the sensor interoperability problem of segmentation feature, which refers to the feature’s ability to adapt to the raw fingerprints captured by different sensors. To address this issue, this paper presents a two-level feature evaluation method, including the first level feature evaluation based on segmentation error rate and the second level feature evaluation based on decision tree. The proposed method is performed on a number of fingerprint databases which are obtained from various sensors. Experimental results show that the proposed method can effectively evaluate the sensor interoperability of features, and the features with good evaluation results acquire better segmentation accuracies of images originating from different sensors.

Map showing Features and Displacements of the Scenic Drive Landslide, La Honda, California, During the Period March 31, 2005-November 5, 2006

Science.gov (United States)

Wells, Ray E.; Rymer, Michael J.; Prentice, Carol S.; Wheeler, Karen L.

2006-01-01

The Scenic Drive landslide in La Honda, San Mateo County, California began movement during the El Ni?o winter of 1997-98. Recurrent motion occurred during the mild El Ni?o winter of 2004-2005 and again during the winter of 2005-06. This report documents the changing geometry and motion of the Scenic Drive landslide in 2005-2006, and it documents changes and persistent features that we interpret to reflect underlying structural control of the landslide. We have also compared the displacement history to near-real time rainfall history at a continuously recording gauge for the period October 2004-November 2006.

Quantifying landscape change in an arctic coastal lowland using repeat airborne LiDAR

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Jones, Benjamin M.; Stoker, Jason M.; Gibbs, Ann E.; Grosse, Guido; Romanovsky, Vladimir E.; Douglas, Thomas A.; Kinsman, Nichole E.M.; Richmond, Bruce M.

2013-01-01

Increases in air, permafrost, and sea surface temperature, loss of sea ice, the potential for increased wave energy, and higher river discharge may all be interacting to escalate erosion of arctic coastal lowland landscapes. Here we use airborne light detection and ranging (LiDAR) data acquired in 2006 and 2010 to detect landscape change in a 100 km2 study area on the Beaufort Sea coastal plain of northern Alaska. We detected statistically significant change (99% confidence interval), defined as contiguous areas (>10 m2) that had changed in height by at least 0.55 m, in 0.3% of the study region. Erosional features indicative of ice-rich permafrost degradation were associated with ice-bonded coastal, river, and lake bluffs, frost mounds, ice wedges, and thermo-erosional gullies. These features accounted for about half of the area where vertical change was detected. Inferred thermo-denudation and thermo-abrasion of coastal and river bluffs likely accounted for the dominant permafrost-related degradational processes with respect to area (42%) and volume (51%). More than 300 thermokarst pits significantly subsided during the study period, likely as a result of storm surge flooding of low-lying tundra (impact of warm summers in the late-1980s and mid-1990s. Our results indicate that repeat airborne LiDAR can be used to detect landscape change in arctic coastal lowland regions at large spatial scales over sub-decadal time periods.

Nongaussian Features from Inflationary Particle Production

International Nuclear Information System (INIS)

Barnaby, Neil

2010-01-01

The inflaton field can be expected to couple to a number of additional fields whose energy density does not play any significant role in driving inflation. Such couplings may lead to isolated bursts of particle production during inflation, for example via parametric resonance or a phase transition, and leave observable imprints in the cosmological fluctuations. I illustrate this effect for a simple prototype interaction g 2 (φ - φ 0 ) 2 χ between the inflaton, φ, and iso-inflaton, χ. Using both classical lattice simulations and analytical quantum field theory computations, I show that this mechanism generates localized bump-like features in the power spectrum and also a completely new type of nongaussianity. Observations are consistent with relatively large features of this type and the nongaussianity from particle production may be observable in future missions.

Parabolic features and the erosion rate on Venus

Science.gov (United States)

Strom, Robert G.

1993-01-01

The impact cratering record on Venus consists of 919 craters covering 98 percent of the surface. These craters are remarkably well preserved, and most show pristine structures including fresh ejecta blankets. Only 35 craters (3.8 percent) have had their ejecta blankets embayed by lava and most of these occur in the Atla-Beta Regio region; an area thought to be recently active. parabolic features are associated with 66 of the 919 craters. These craters range in size from 6 to 105 km diameter. The parabolic features are thought to be the result of the deposition of fine-grained ejecta by winds in the dense venusian atmosphere. The deposits cover about 9 percent of the surface and none appear to be embayed by younger volcanic materials. However, there appears to be a paucity of these deposits in the Atla-Beta Regio region, and this may be due to the more recent volcanism in this area of Venus. Since parabolic features are probably fine-grain, wind-deposited ejecta, then all impact craters on Venus probably had these deposits at some time in the past. The older deposits have probably been either eroded or buried by eolian processes. Therefore, the present population of these features is probably associated with the most recent impact craters on the planet. Furthermore, the size/frequency distribution of craters with parabolic features is virtually identical to that of the total crater population. This suggests that there has been little loss of small parabolic features compared to large ones, otherwise there should be a significant and systematic paucity of craters with parabolic features with decreasing size compared to the total crater population. Whatever is erasing the parabolic features apparently does so uniformly regardless of the areal extent of the deposit. The lifetime of parabolic features and the eolian erosion rate on Venus can be estimated from the average age of the surface and the present population of parabolic features.

Application of textural features to the objective diagnosis of Alzheimer-type dementia

International Nuclear Information System (INIS)

Kodama, Naoki; Shimada, Tetsuo; Kaeriyama, Tomoharu; Kaneko, Tomoyuki; Fukumoto, Ichiro; Kobayashi, Yoshio

2003-01-01

In this study, patients with Alzheimer-type dementia were compared with healthy elderly individuals by means of 13 textural features to evaluate the application of these features to the objective diagnosis of the dementia. A statistically significant difference was found in 8 of the 13 textural features between dementia patients and healthy controls. Discriminant analysis using the eight features demonstrated a sensitivity of 91.2% and a specificity of 86.4%, with an overall accuracy of 89.1%. Multiple discriminant analysis using the eight features by dementia stage showed an overall accuracy of 78.2% for discrimination of four stages. These results indicate that quantitative textural feature measurements can be used as an objective diagnostic technique for Alzheimer-type dementia. (author)

Caudate nucleus reactivity predicts perceptual learning rate for visual feature conjunctions.

Science.gov (United States)

Reavis, Eric A; Frank, Sebastian M; Tse, Peter U

2015-04-15

Useful information in the visual environment is often contained in specific conjunctions of visual features (e.g., color and shape). The ability to quickly and accurately process such conjunctions can be learned. However, the neural mechanisms responsible for such learning remain largely unknown. It has been suggested that some forms of visual learning might involve the dopaminergic neuromodulatory system (Roelfsema et al., 2010; Seitz and Watanabe, 2005), but this hypothesis has not yet been directly tested. Here we test the hypothesis that learning visual feature conjunctions involves the dopaminergic system, using functional neuroimaging, genetic assays, and behavioral testing techniques. We use a correlative approach to evaluate potential associations between individual differences in visual feature conjunction learning rate and individual differences in dopaminergic function as indexed by neuroimaging and genetic markers. We find a significant correlation between activity in the caudate nucleus (a component of the dopaminergic system connected to visual areas of the brain) and visual feature conjunction learning rate. Specifically, individuals who showed a larger difference in activity between positive and negative feedback on an unrelated cognitive task, indicative of a more reactive dopaminergic system, learned visual feature conjunctions more quickly than those who showed a smaller activity difference. This finding supports the hypothesis that the dopaminergic system is involved in visual learning, and suggests that visual feature conjunction learning could be closely related to associative learning. However, no significant, reliable correlations were found between feature conjunction learning and genotype or dopaminergic activity in any other regions of interest. Copyright © 2015 Elsevier Inc. All rights reserved.

Feature Detector and Descriptor for Medical Images

Science.gov (United States)

Sargent, Dusty; Chen, Chao-I.; Tsai, Chang-Ming; Wang, Yuan-Fang; Koppel, Daniel

2009-02-01

The ability to detect and match features across multiple views of a scene is a crucial first step in many computer vision algorithms for dynamic scene analysis. State-of-the-art methods such as SIFT and SURF perform successfully when applied to typical images taken by a digital camera or camcorder. However, these methods often fail to generate an acceptable number of features when applied to medical images, because such images usually contain large homogeneous regions with little color and intensity variation. As a result, tasks like image registration and 3D structure recovery become difficult or impossible in the medical domain. This paper presents a scale, rotation and color/illumination invariant feature detector and descriptor for medical applications. The method incorporates elements of SIFT and SURF while optimizing their performance on medical data. Based on experiments with various types of medical images, we combined, adjusted, and built on methods and parameter settings employed in both algorithms. An approximate Hessian based detector is used to locate scale invariant keypoints and a dominant orientation is assigned to each keypoint using a gradient orientation histogram, providing rotation invariance. Finally, keypoints are described with an orientation-normalized distribution of gradient responses at the assigned scale, and the feature vector is normalized for contrast invariance. Experiments show that the algorithm detects and matches far more features than SIFT and SURF on medical images, with similar error levels.

Novel acoustic features for speech emotion recognition

Institute of Scientific and Technical Information of China (English)

ROH; Yong-Wan; KIM; Dong-Ju; LEE; Woo-Seok; HONG; Kwang-Seok

2009-01-01

This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech.The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform(FFT) spectral entropy,delta FFT spectral entropy,Mel-frequency filter bank(MFB) spectral entropy,and Delta MFB spectral entropy.Spectral-based entropy features are simple.They reflect frequency characteristic and changing characteristic in frequency of speech.We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance.Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results,respectively.These scores are first obtained from a pattern recognition procedure.The pattern recognition phase uses the Gaussian mixture model(GMM).We classify the four emotional states as anger,sadness,happiness and neutrality.The proposed method is evaluated using 45 sentences in each emotion for 30 subjects,15 males and 15 females.Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy,Zero Crossing Rate(ZCR),linear prediction coefficient(LPC),and pitch parameters.We demonstrate the effectiveness of the proposed approach.One of the proposed features,combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods.We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

Novel acoustic features for speech emotion recognition

Institute of Scientific and Technical Information of China (English)

ROH Yong-Wan; KIM Dong-Ju; LEE Woo-Seok; HONG Kwang-Seok

2009-01-01

This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech. The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform (FFT) spectral entropy, delta FFT spectral entropy, Mel-frequency filter bank (MFB)spectral entropy, and Delta MFB spectral entropy. Spectral-based entropy features are simple. They reflect frequency characteristic and changing characteristic in frequency of speech. We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance. Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results, respectively.These scores are first obtained from a pattern recognition procedure. The pattern recognition phase uses the Gaussian mixture model (GMM). We classify the four emotional states as anger, sadness,happiness and neutrality. The proposed method is evaluated using 45 sentences in each emotion for 30 subjects, 15 males and 15 females. Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy, Zero Crossing Rate (ZCR),linear prediction coefficient (LPC), and pitch parameters. We demonstrate the effectiveness of the proposed approach. One of the proposed features, combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods. We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

Feature selection using genetic algorithms for fetal heart rate analysis

International Nuclear Information System (INIS)

Xu, Liang; Redman, Christopher W G; Georgieva, Antoniya; Payne, Stephen J

2014-01-01

The fetal heart rate (FHR) is monitored on a paper strip (cardiotocogram) during labour to assess fetal health. If necessary, clinicians can intervene and assist with a prompt delivery of the baby. Data-driven computerized FHR analysis could help clinicians in the decision-making process. However, selecting the best computerized FHR features that relate to labour outcome is a pressing research problem. The objective of this study is to apply genetic algorithms (GA) as a feature selection method to select the best feature subset from 64 FHR features and to integrate these best features to recognize unfavourable FHR patterns. The GA was trained on 404 cases and tested on 106 cases (both balanced datasets) using three classifiers, respectively. Regularization methods and backward selection were used to optimize the GA. Reasonable classification performance is shown on the testing set for the best feature subset (Cohen's kappa values of 0.45 to 0.49 using different classifiers). This is, to our knowledge, the first time that a feature selection method for FHR analysis has been developed on a database of this size. This study indicates that different FHR features, when integrated, can show good performance in predicting labour outcome. It also gives the importance of each feature, which will be a valuable reference point for further studies. (paper)

Mid-Infrared Silicate Dust Features in Seyfert 1 Spectra

Science.gov (United States)

Thompson, Grant D.; Levenson, N. A.; Sirocky, M. M.; Uddin, S.

2007-12-01

Silicate dust emission dominates the mid-infrared spectra of galaxies, and the dust produces two spectral features, at 10 and 18 μm. These features' strengths (in emission or absorption) and peak wavelengths reveal the geometry of the dust distribution, and they are sensitive to the dust composition. We examine mid-infrared spectra of 32 Seyfert 1 active galactic nuclei (AGN), observed with the Infrared Spectrograph aboard the Spitzer Space Telescope. In the spectra, we typically find the shorter-wavelength feature in emission, at an average peak wavelength of 10.0 μm, although it is known historically as the "9.7 μm" feature. In addition, peak wavelength increases with feature strength. The 10 and 18 μm feature strengths together are sensitive to the dust geometry surrounding the central heating engine. Numerical calculations of radiative transfer distinguish between clumpy and smooth distributions, and we find that the surroundings of these AGN (the obscuring "tori" of unified AGN schemes) are clumpy. Polycyclic aromatic hydrocarbon (PAH) features are associated with star formation, and we find strong PAH emission (luminosity ≥ 1042 erg/s) in only four sources, three of which show independent evidence for starbursts. We will explore the effects of luminosity on dust geometry and chemistry in a comparison sample of quasars. We acknowledge work supported by the NSF under grant number 0237291.

No Effect of Featural Attention on Body Size Aftereffects

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Ian David Stephen

2016-08-01

Full Text Available Prolonged exposure to images of narrow bodies has been shown to induce a perceptual aftereffect, such that observers’ point of subjective normality (PSN for bodies shifts towards narrower bodies. The converse effect is shown for adaptation to wide bodies. In low-level stimuli, object attention (attention directed to the object and spatial attention (attention directed to the location of the object have been shown to increase the magnitude of visual aftereffects, while object-based attention enhances the adaptation effect in faces. It is not known whether featural attention (attention directed to a specific aspect of the object affects the magnitude of adaptation effects in body stimuli. Here, we manipulate the attention of Caucasian observers to different featural information in body images, by asking them to rate the fatness or sex typicality of male and female bodies manipulated to appear fatter or thinner than average. PSNs for body fatness were taken at baseline and after adaptation, and a change in PSN (ΔPSN was calculated. A body size adaptation effect was found, with observers who viewed fat bodies showing an increased PSN, and those exposed to thin bodies showing a reduced PSN. However, manipulations of featural attention to body fatness or sex typicality produced equivalent results, suggesting that featural attention may not affect the strength of the body size aftereffect.

No Effect of Featural Attention on Body Size Aftereffects.

Science.gov (United States)

Stephen, Ian D; Bickersteth, Chloe; Mond, Jonathan; Stevenson, Richard J; Brooks, Kevin R

2016-01-01

Prolonged exposure to images of narrow bodies has been shown to induce a perceptual aftereffect, such that observers' point of subjective normality (PSN) for bodies shifts toward narrower bodies. The converse effect is shown for adaptation to wide bodies. In low-level stimuli, object attention (attention directed to the object) and spatial attention (attention directed to the location of the object) have been shown to increase the magnitude of visual aftereffects, while object-based attention enhances the adaptation effect in faces. It is not known whether featural attention (attention directed to a specific aspect of the object) affects the magnitude of adaptation effects in body stimuli. Here, we manipulate the attention of Caucasian observers to different featural information in body images, by asking them to rate the fatness or sex typicality of male and female bodies manipulated to appear fatter or thinner than average. PSNs for body fatness were taken at baseline and after adaptation, and a change in PSN (ΔPSN) was calculated. A body size adaptation effect was found, with observers who viewed fat bodies showing an increased PSN, and those exposed to thin bodies showing a reduced PSN. However, manipulations of featural attention to body fatness or sex typicality produced equivalent results, suggesting that featural attention may not affect the strength of the body size aftereffect.

Effective automated feature construction and selection for classification of biological sequences.

Directory of Open Access Journals (Sweden)

Uday Kamath

Full Text Available Many open problems in bioinformatics involve elucidating underlying functional signals in biological sequences. DNA sequences, in particular, are characterized by rich architectures in which functional signals are increasingly found to combine local and distal interactions at the nucleotide level. Problems of interest include detection of regulatory regions, splice sites, exons, hypersensitive sites, and more. These problems naturally lend themselves to formulation as classification problems in machine learning. When classification is based on features extracted from the sequences under investigation, success is critically dependent on the chosen set of features.We present an algorithmic framework (EFFECT for automated detection of functional signals in biological sequences. We focus here on classification problems involving DNA sequences which state-of-the-art work in machine learning shows to be challenging and involve complex combinations of local and distal features. EFFECT uses a two-stage process to first construct a set of candidate sequence-based features and then select a most effective subset for the classification task at hand. Both stages make heavy use of evolutionary algorithms to efficiently guide the search towards informative features capable of discriminating between sequences that contain a particular functional signal and those that do not.To demonstrate its generality, EFFECT is applied to three separate problems of importance in DNA research: the recognition of hypersensitive sites, splice sites, and ALU sites. Comparisons with state-of-the-art algorithms show that the framework is both general and powerful. In addition, a detailed analysis of the constructed features shows that they contain valuable biological information about DNA architecture, allowing biologists and other researchers to directly inspect the features and potentially use the insights obtained to assist wet-laboratory studies on retainment or modification

Language Recognition Using Latent Dynamic Conditional Random Field Model with Phonological Features

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Sirinoot Boonsuk

2014-01-01

Full Text Available Spoken language recognition (SLR has been of increasing interest in multilingual speech recognition for identifying the languages of speech utterances. Most existing SLR approaches apply statistical modeling techniques with acoustic and phonotactic features. Among the popular approaches, the acoustic approach has become of greater interest than others because it does not require any prior language-specific knowledge. Previous research on the acoustic approach has shown less interest in applying linguistic knowledge; it was only used as supplementary features, while the current state-of-the-art system assumes independency among features. This paper proposes an SLR system based on the latent-dynamic conditional random field (LDCRF model using phonological features (PFs. We use PFs to represent acoustic characteristics and linguistic knowledge. The LDCRF model was employed to capture the dynamics of the PFs sequences for language classification. Baseline systems were conducted to evaluate the features and methods including Gaussian mixture model (GMM based systems using PFs, GMM using cepstral features, and the CRF model using PFs. Evaluated on the NIST LRE 2007 corpus, the proposed method showed an improvement over the baseline systems. Additionally, it showed comparable result with the acoustic system based on i-vector. This research demonstrates that utilizing PFs can enhance the performance.

Space moving target detection using time domain feature

Science.gov (United States)

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.

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

Science.gov (United States)

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

Visual search for features and conjunctions in development.

Science.gov (United States)

Lobaugh, N J; Cole, S; Rovet, J F

1998-12-01

Visual search performance was examined in three groups of children 7 to 12 years of age and in young adults. Colour and orientation feature searches and a conjunction search were conducted. Reaction time (RT) showed expected improvements in processing speed with age. Comparisons of RT's on target-present and target-absent trials were consistent with parallel search on the two feature conditions and with serial search in the conjunction condition. The RT results indicated searches for feature and conjunctions were treated similarly for children and adults. However, the youngest children missed more targets at the largest array sizes, most strikingly in conjunction search. Based on an analysis of speed/accuracy trade-offs, we suggest that low target-distractor discriminability leads to an undersampling of array elements, and is responsible for the high number of misses in the youngest children.

Enhanced Performance by Time-Frequency-Phase Feature for EEG-Based BCI Systems

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Baolei Xu

2014-01-01

Full Text Available We introduce a new motor parameter imagery paradigm using clench speed and clench force motor imagery. The time-frequency-phase features are extracted from mu rhythm and beta rhythms, and the features are optimized using three process methods: no-scaled feature using “MIFS” feature selection criterion, scaled feature using “MIFS” feature selection criterion, and scaled feature using “mRMR” feature selection criterion. Support vector machines (SVMs and extreme learning machines (ELMs are compared for classification between clench speed and clench force motor imagery using the optimized feature. Our results show that no significant difference in the classification rate between SVMs and ELMs is found. The scaled feature combinations can get higher classification accuracy than the no-scaled feature combinations at significant level of 0.01, and the “mRMR” feature selection criterion can get higher classification rate than the “MIFS” feature selection criterion at significant level of 0.01. The time-frequency-phase feature can improve the classification rate by about 20% more than the time-frequency feature, and the best classification rate between clench speed motor imagery and clench force motor imagery is 92%. In conclusion, the motor parameter imagery paradigm has the potential to increase the direct control commands for BCI control and the time-frequency-phase feature has the ability to improve BCI classification accuracy.

UNLABELED SELECTED SAMPLES IN FEATURE EXTRACTION FOR CLASSIFICATION OF HYPERSPECTRAL IMAGES WITH LIMITED TRAINING SAMPLES

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A. Kianisarkaleh

2015-12-01

Full Text Available Feature extraction plays a key role in hyperspectral images classification. Using unlabeled samples, often unlimitedly available, unsupervised and semisupervised feature extraction methods show better performance when limited number of training samples exists. This paper illustrates the importance of selecting appropriate unlabeled samples that used in feature extraction methods. Also proposes a new method for unlabeled samples selection using spectral and spatial information. The proposed method has four parts including: PCA, prior classification, posterior classification and sample selection. As hyperspectral image passes these parts, selected unlabeled samples can be used in arbitrary feature extraction methods. The effectiveness of the proposed unlabeled selected samples in unsupervised and semisupervised feature extraction is demonstrated using two real hyperspectral datasets. Results show that through selecting appropriate unlabeled samples, the proposed method can improve the performance of feature extraction methods and increase classification accuracy.

Hierarchical Feature Extraction With Local Neural Response for Image Recognition.

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Li, Hong; Wei, Yantao; Li, Luoqing; Chen, C L P

2013-04-01

In this paper, a hierarchical feature extraction method is proposed for image recognition. The key idea of the proposed method is to extract an effective feature, called local neural response (LNR), of the input image with nontrivial discrimination and invariance properties by alternating between local coding and maximum pooling operation. The local coding, which is carried out on the locally linear manifold, can extract the salient feature of image patches and leads to a sparse measure matrix on which maximum pooling is carried out. The maximum pooling operation builds the translation invariance into the model. We also show that other invariant properties, such as rotation and scaling, can be induced by the proposed model. In addition, a template selection algorithm is presented to reduce computational complexity and to improve the discrimination ability of the LNR. Experimental results show that our method is robust to local distortion and clutter compared with state-of-the-art algorithms.

Evolutionary Feature Selection for Big Data Classification: A MapReduce Approach

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Daniel Peralta

2015-01-01

Full Text Available Nowadays, many disciplines have to deal with big datasets that additionally involve a high number of features. Feature selection methods aim at eliminating noisy, redundant, or irrelevant features that may deteriorate the classification performance. However, traditional methods lack enough scalability to cope with datasets of millions of instances and extract successful results in a delimited time. This paper presents a feature selection algorithm based on evolutionary computation that uses the MapReduce paradigm to obtain subsets of features from big datasets. The algorithm decomposes the original dataset in blocks of instances to learn from them in the map phase; then, the reduce phase merges the obtained partial results into a final vector of feature weights, which allows a flexible application of the feature selection procedure using a threshold to determine the selected subset of features. The feature selection method is evaluated by using three well-known classifiers (SVM, Logistic Regression, and Naive Bayes implemented within the Spark framework to address big data problems. In the experiments, datasets up to 67 millions of instances and up to 2000 attributes have been managed, showing that this is a suitable framework to perform evolutionary feature selection, improving both the classification accuracy and its runtime when dealing with big data problems.

A graph-Laplacian-based feature extraction algorithm for neural spike sorting.

Science.gov (United States)

Ghanbari, Yasser; Spence, Larry; Papamichalis, Panos

2009-01-01

Analysis of extracellular neural spike recordings is highly dependent upon the accuracy of neural waveform classification, commonly referred to as spike sorting. Feature extraction is an important stage of this process because it can limit the quality of clustering which is performed in the feature space. This paper proposes a new feature extraction method (which we call Graph Laplacian Features, GLF) based on minimizing the graph Laplacian and maximizing the weighted variance. The algorithm is compared with Principal Components Analysis (PCA, the most commonly-used feature extraction method) using simulated neural data. The results show that the proposed algorithm produces more compact and well-separated clusters compared to PCA. As an added benefit, tentative cluster centers are output which can be used to initialize a subsequent clustering stage.

ON THE 10 μm SILICATE FEATURE IN ACTIVE GALACTIC NUCLEI

International Nuclear Information System (INIS)

Nikutta, Robert; Elitzur, Moshe; Lacy, Mark

2009-01-01

The 10 μm silicate feature observed with Spitzer in active galactic nuclei (AGNs) reveals some puzzling behavior. It (1) has been detected in emission in type 2 sources, (2) shows broad, flat-topped emission peaks shifted toward long wavelengths in several type 1 sources, and (3) is not seen in deep absorption in any source observed so far. We solve all three puzzles with our clumpy dust radiative transfer formalism. Addressing (1), we present the spectral energy distribution (SED) of SST1721+6012, the first type 2 quasar observed to show a clear 10 μm silicate feature in emission. Such emission arises in models of the AGN torus easily when its clumpy nature is taken into account. We constructed a large database of clumpy torus models and performed extensive fitting of the observed SED. We find that the cloud radial distribution varies as r -1.5 and the torus contains 2-4 clouds along radial equatorial rays, each with optical depth at visual ∼60-80. The source bolometric luminosity is ∼3 x 10 12 L sun . Our modeling suggests that ∼<35% of objects with tori sharing these characteristics and geometry would have their central engines obscured. This relatively low obscuration probability can explain the clear appearance of the 10 μm emission feature in SST1721+6012 together with its rarity among other QSO2. Investigating (2), we also fitted the SED of PG1211+143, one of the first type 1 QSOs with a 10 μm silicate feature detected in emission. Together with other similar sources, this QSO appears to display an unusually broadened feature whose peak is shifted toward longer wavelengths. Although this led to suggestions of non-standard dust chemistry in these sources, our analysis fits such SEDs with standard galactic dust; the apparent peak shifts arise from simple radiative transfer effects. Regarding (3), we find additionally that the distribution of silicate feature strengths among clumpy torus models closely resembles the observed distribution, and the

On the 10 μm Silicate Feature in Active Galactic Nuclei

Science.gov (United States)

Nikutta, Robert; Elitzur, Moshe; Lacy, Mark

2009-12-01

The 10 μm silicate feature observed with Spitzer in active galactic nuclei (AGNs) reveals some puzzling behavior. It (1) has been detected in emission in type 2 sources, (2) shows broad, flat-topped emission peaks shifted toward long wavelengths in several type 1 sources, and (3) is not seen in deep absorption in any source observed so far. We solve all three puzzles with our clumpy dust radiative transfer formalism. Addressing (1), we present the spectral energy distribution (SED) of SST1721+6012, the first type 2 quasar observed to show a clear 10 μm silicate feature in emission. Such emission arises in models of the AGN torus easily when its clumpy nature is taken into account. We constructed a large database of clumpy torus models and performed extensive fitting of the observed SED. We find that the cloud radial distribution varies as r -1.5 and the torus contains 2-4 clouds along radial equatorial rays, each with optical depth at visual ~60-80. The source bolometric luminosity is ~3 × 1012 Lsun. Our modeling suggests that lsim35% of objects with tori sharing these characteristics and geometry would have their central engines obscured. This relatively low obscuration probability can explain the clear appearance of the 10 μm emission feature in SST1721+6012 together with its rarity among other QSO2. Investigating (2), we also fitted the SED of PG1211+143, one of the first type 1 QSOs with a 10 μm silicate feature detected in emission. Together with other similar sources, this QSO appears to display an unusually broadened feature whose peak is shifted toward longer wavelengths. Although this led to suggestions of non-standard dust chemistry in these sources, our analysis fits such SEDs with standard galactic dust; the apparent peak shifts arise from simple radiative transfer effects. Regarding (3), we find additionally that the distribution of silicate feature strengths among clumpy torus models closely resembles the observed distribution, and the feature

Crystallization features of ternary reversible reciprocal systems

International Nuclear Information System (INIS)

Tomashik, V.N.; Shcherbak, L.P.; Fejchuk, P.I.; Grytsiv, V.I.

2006-01-01

Some features of the primary crystallization of phases in ternary reversible reciprocal system are considered and discussed. The diagonal join CdTe-GeSe of the CdTe + GeSe = CdSe + GeTe ternary reciprocal system is studied to show that the features in primary and secondary heating and cooling curves in such systems under fully equilibrium conditions are not reproduced upon consecutive heating and cooling sessions, because of the existence of different amounts of the reagents and the reaction products in the mixture; the temperatures of each transformation lie in a range. Those who experimentally investigate other ternary and more complex reversible reciprocal systems should take this fact into account [ru

Rehabilitation of the Ranger Mine Site

International Nuclear Information System (INIS)

East, J.; Uren, C.; Cull, R.; Curley, P.; Unger, C.

1989-01-01

Designs for long-lived waste rock piles in tropical Australia need to consider the climatic factors affecting erosion. Erosion trials on four plots at the Ranger waste rock dump demonstrate that some features of natural stable landforms such as slope morphogenetic variables and the size characteristics of aerial cover of resistive rock particles on the surface, can be sucessfully used in the design of the waste rock piles. Preliminary results indicate that the erosional stability of slopes can be enhanced by the use of concave surfaces. ills., diagrams

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

Science.gov (United States)

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.

Invariant features of spatial inequality in consumption: The case of India

Science.gov (United States)

Chatterjee, Arnab; Chakrabarti, Anindya S.; Ghosh, Asim; Chakraborti, Anirban; Nandi, Tushar K.

2016-01-01

We study the distributional features and inequality of consumption expenditure across India, for different states, castes, religion and urban-rural divide. We find that even though the aggregate measures of inequality are fairly diversified across states, the consumption distributions show near identical statistics, once properly normalized. This feature is seen to be robust with respect to variations in sociological and economic factors. We also show that state-wise inequality seems to be positively correlated with growth which is in accord with the traditional idea of Kuznets' curve. We present a brief model to account for the invariance found empirically and show that better but riskier technology draws can create a positive correlation between inequality and growth.

Collaborative Filtering Fusing Label Features Based on SDAE

DEFF Research Database (Denmark)

Huo, Huan; Liu, Xiufeng; Zheng, Deyuan

2017-01-01

problem, auxiliary information such as labels are utilized. Another approach of recommendation system is content-based model which can’t be directly integrated with CF-based model due to its inherent characteristics. Considering that deep learning algorithms are capable of extracting deep latent features......, this paper applies Stack Denoising Auto Encoder (SDAE) to content-based model and proposes LCF(Deep Learning for Collaborative Filtering) algorithm by combing CF-based model which fuses label features. Experiments on real-world data sets show that DLCF can largely overcome the sparsity problem...... and significantly improves the state of art approaches....

A Method to Measure the Bracelet Based on Feature Energy

Science.gov (United States)

Liu, Hongmin; Li, Lu; Wang, Zhiheng; Huo, Zhanqiang

2017-12-01

To measure the bracelet automatically, a novel method based on feature energy is proposed. Firstly, the morphological method is utilized to preprocess the image, and the contour consisting of a concentric circle is extracted. Then, a feature energy function, which is relevant to the distances from one pixel to the edge points, is defined taking into account the geometric properties of the concentric circle. The input image is subsequently transformed to the feature energy distribution map (FEDM) by computing the feature energy of each pixel. The center of the concentric circle is thus located by detecting the maximum on the FEDM; meanwhile, the radii of the concentric circle are determined according to the feature energy function of the center pixel. Finally, with the use of a calibration template, the internal diameter and thickness of the bracelet are measured. The experimental results show that the proposed method can measure the true sizes of the bracelet accurately with the simplicity, directness and robustness compared to the existing methods.

An Effective Combined Feature For Web Based Image Retrieval

Directory of Open Access Journals (Sweden)

H.M.R.B Herath

2015-08-01

Full Text Available Abstract Technology advances as well as the emergence of large scale multimedia applications and the revolution of the World Wide Web has changed the world into a digital age. Anybody can use their mobile phone to take a photo at any time anywhere and upload that image to ever growing image databases. Development of effective techniques for visual and multimedia retrieval systems is one of the most challenging and important directions of the future research. This paper proposes an effective combined feature for web based image retrieval. Frequently used colour and texture features are explored in order to develop a combined feature for this purpose. Widely used three colour features Colour moments Colour coherence vector and Colour Correlogram and three texture features Grey Level Co-occurrence matrix Tamura features and Gabor filter were analyzed for their performance. Precision and Recall were used to evaluate the performance of each of these techniques. By comparing precision and recall values the methods that performed best were taken and combined to form a hybrid feature. The developed combined feature was evaluated by developing a web based CBIR system. A web crawler was used to first crawl through Web sites and images found in those sites are downloaded and the combined feature representation technique was used to extract image features. The test results indicated that this web system can be used to index web images with the combined feature representation schema and to find similar images. Random image retrievals using the web system shows that the combined feature can be used to retrieve images belonging to the general image domain. Accuracy of the retrieval can be noted high for natural images like outdoor scenes images of flowers etc. Also images which have a similar colour and texture distribution were retrieved as similar even though the images were belonging to deferent semantic categories. This can be ideal for an artist who wants

Osteopetrosis: Some unusual radiological features with a short review

International Nuclear Information System (INIS)

Kolawole, T.M.; Hawass, N.D.; Patel, P.J.; Mahdi, A.H.

1988-01-01

The radiological features of 27 cases of osteopetrosis were analysed retrospectively. The common features of generalized sclerosis of bones; with metaphyses showing characteristic widening, multiple transverse striations, cortical thickening and medullary calcifications as well as fractures, are seen in most cases. In addition to these changes, a number of rare features of osteopetrosis are seen, viz: Medial and symmetrical metaphyseal cortical defects in the long bones (5 cases), excessive diaphyseal radiodense periosteal new bone formation (5 cases), bone-in-bone appearances (5 cases), and the presence of intracerebral and meningeal calcifications in 7 cases. The significance of these intracranial calcifications as a component of a particular autosomal recessive syndrome in which renal tubular acidosis and carbonic anhydrase II deficiency may coexist, is discussed. (orig.)

An object-oriented feature-based design system face-based detection of feature interactions

International Nuclear Information System (INIS)

Ariffin Abdul Razak

1999-01-01

This paper presents an object-oriented, feature-based design system which supports the integration of design and manufacture by ensuring that part descriptions fully account for any feature interactions. Manufacturing information is extracted from the feature descriptions in the form of volumes and Tool Access Directions, TADs. When features interact, both volumes and TADs are updated. This methodology has been demonstrated by developing a prototype system in which ACIS attributes are used to record feature information within the data structure of the solid model. The system implemented in the C++ programming language and embedded in a menu-driven X-windows user interface to the ACIS 3D Toolkit. (author)

Efficient Topological Localization Using Global and Local Feature Matching

Directory of Open Access Journals (Sweden)

Junqiu Wang

2013-03-01

Full Text Available We present an efficient vision-based global topological localization approach in which different image features are used in a coarse-to-fine matching framework. Orientation Adjacency Coherence Histogram (OACH, a novel image feature, is proposed to improve the coarse localization. The coarse localization results are taken as inputs for the fine localization which is carried out by matching Harris-Laplace interest points characterized by the SIFT descriptor. The computation of OACHs and interest points is efficient due to the fact that these features are computed in an integrated process. The matching of local features is improved by using approximate nearest neighbor searching technique. We have implemented and tested the localization system in real environments. The experimental results demonstrate that our approach is efficient and reliable in both indoor and outdoor environments. This work has also been compared with previous works. The comparison results show that our approach has better performance with higher correct ratio and lower computational complexity.

Dominant color and texture feature extraction for banknote discrimination

Science.gov (United States)

Wang, Junmin; Fan, Yangyu; Li, Ning

2017-07-01

Banknote discrimination with image recognition technology is significant in many applications. The traditional methods based on image recognition only recognize the banknote denomination without discriminating the counterfeit banknote. To solve this problem, we propose a systematical banknote discrimination approach with the dominant color and texture features. After capturing the visible and infrared images of the test banknote, we first implement the tilt correction based on the principal component analysis (PCA) algorithm. Second, we extract the dominant color feature of the visible banknote image to recognize the denomination. Third, we propose an adaptively weighted local binary pattern with "delta" tolerance algorithm to extract the texture features of the infrared banknote image. At last, we discriminate the genuine or counterfeit banknote by comparing the texture features between the test banknote and the benchmark banknote. The proposed approach is tested using 14,000 banknotes of six different denominations from Chinese yuan (CNY). The experimental results show 100% accuracy for denomination recognition and 99.92% accuracy for counterfeit banknote discrimination.

Construction Method of the Topographical Features Model for Underwater Terrain Navigation

Directory of Open Access Journals (Sweden)

Wang Lihui

2015-09-01

Full Text Available Terrain database is the reference basic for autonomous underwater vehicle (AUV to implement underwater terrain navigation (UTN functions, and is the important part of building topographical features model for UTN. To investigate the feasibility and correlation of a variety of terrain parameters as terrain navigation information metrics, this paper described and analyzed the underwater terrain features and topography parameters calculation method. Proposing a comprehensive evaluation method for terrain navigation information, and constructing an underwater navigation information analysis model, which is associated with topographic features. Simulation results show that the underwater terrain features, are associated with UTN information directly or indirectly, also affect the terrain matching capture probability and the positioning accuracy directly.

Combining Semantic and Acoustic Features for Valence and Arousal Recognition in Speech

DEFF Research Database (Denmark)

Karadogan, Seliz; Larsen, Jan

2012-01-01

The recognition of affect in speech has attracted a lot of interest recently; especially in the area of cognitive and computer sciences. Most of the previous studies focused on the recognition of basic emotions (such as happiness, sadness and anger) using categorical approach. Recently, the focus...... has been shifting towards dimensional affect recognition based on the idea that emotional states are not independent from one another but related in a systematic manner. In this paper, we design a continuous dimensional speech affect recognition model that combines acoustic and semantic features. We...... show that combining semantic and acoustic information for dimensional speech recognition improves the results. Moreover, we show that valence is better estimated using semantic features while arousal is better estimated using acoustic features....

Morphometric differences in debris flow and mixed flow fans in eastern Death Valley, CA

Science.gov (United States)

Wasklewicz, T. A.; Whitworth, J.

2004-12-01

Geomorphological features are best examined through direct measurement and parameterization of accurate topographic data. Fine-scale data are therefore required to produce a complete set of elevation data. Airborne Laser Swath Mapping (ALSM) data provide high-resolution data over large spatially continuous areas. The National Center for Advanced Laser Mapping (NCALM) collected ALSM data for an area along the eastern side of Death Valley extending from slightly north of Badwater to Mormon Point. The raw ALSM data were post-processed and delivered by NCALM in one-meter grid nodes that we converted to one-meter raster data sets. ALSM data are used to assess variations in the dimensions of surficial features found in 32 alluvial fans (21 debris flow and 11 mixed flow fans). Planimetric curvature of the fan surfaces is used to develop a topographic signature to distinguish debris flow from mixed flow fans. These two groups of fans are identified from field analysis of near vertical exposures along channels as well as surficial exposures at proximal, medial, and distal fan locations. One group of fans exhibited debris flow characteristics (DF), while the second group contained a mixture of fluid and debris flows (MF). Local planimetric curvature of the alluvial fan surfaces was derived from the one-meter DEM. The local curvature data were reclassified into concave and convex features. This sequence corresponds to two broad classes of fan features: channels and interfluves. Thirty random points were generated inside each fan polygon. The length of the nearest concave-convex (channel-interfluve) couplet was measured at each point and the percentage of convex and concave pixels in a 10m box centered on the random point was also recorded. Plots and statistical analyses of the data show clear indication that local planimetric curvature can be used as a topographic signature to distinguish between the varying formative processes in alluvial fans. Significant differences in the

Running of featureful primordial power spectra

Science.gov (United States)

Gariazzo, Stefano; Mena, Olga; Miralles, Victor; Ramírez, Héctor; Boubekeur, Lotfi

2017-06-01

Current measurements of the temperature and polarization anisotropy power spectra of the cosmic microwave background (CMB) seem to indicate that the naive expectation for the slow-roll hierarchy within the most simple inflationary paradigm may not be respected in nature. We show that a primordial power spectrum with localized features could in principle give rise to the observed slow-roll anarchy when fitted to a featureless power spectrum. From a model comparison perspective, and assuming that nature has chosen a featureless primordial power spectrum, we find that, while with mock Planck data there is only weak evidence against a model with localized features, upcoming CMB missions may provide compelling evidence against such a nonstandard primordial power spectrum. This evidence could be reinforced if a featureless primordial power spectrum is independently confirmed from bispectrum and/or galaxy clustering measurements.

An Incremental Classification Algorithm for Mining Data with Feature Space Heterogeneity

Directory of Open Access Journals (Sweden)

Yu Wang

2014-01-01

Full Text Available Feature space heterogeneity often exists in many real world data sets so that some features are of different importance for classification over different subsets. Moreover, the pattern of feature space heterogeneity might dynamically change over time as more and more data are accumulated. In this paper, we develop an incremental classification algorithm, Supervised Clustering for Classification with Feature Space Heterogeneity (SCCFSH, to address this problem. In our approach, supervised clustering is implemented to obtain a number of clusters such that samples in each cluster are from the same class. After the removal of outliers, relevance of features in each cluster is calculated based on their variations in this cluster. The feature relevance is incorporated into distance calculation for classification. The main advantage of SCCFSH lies in the fact that it is capable of solving a classification problem with feature space heterogeneity in an incremental way, which is favorable for online classification tasks with continuously changing data. Experimental results on a series of data sets and application to a database marketing problem show the efficiency and effectiveness of the proposed approach.

What goes through the gate? Exploring interference with visual feature binding.

Science.gov (United States)

Ueno, Taiji; Mate, Judit; Allen, Richard J; Hitch, Graham J; Baddeley, Alan D

2011-05-01

A series of experiments explored the mechanisms determining the encoding and storage of features and objects in visual working memory. We contrasted the effects of three types of visual suffix on cued recall of a display of colored shapes. The suffix was presented after the display and before the recall cue. The latter was either the color or shape of one of the objects and signaled recall of the object's other feature. In Experiments 1 and 2, we found a larger effect of 'plausible' suffixes comprising features (color and shape) drawn from the experimental set, relative to the effect of 'implausible' suffixes comprising features outside the experimental set. Experiment 3 extended this pattern by showing that 'semi-plausible' suffixes containing only one feature (either color or shape) from the experimental set had an equivalent effect to those with both features from the set. Reduction in accuracy was mainly due to an increase in recall of suffix features, rather than within-display confusions. The findings suggest a feature-based filtering process in visual working memory, with any stimuli that pass through this filter serving to directly overwrite existing object representations. Copyright © 2011 Elsevier Ltd. All rights reserved.

A review of feature detection and match algorithms for localization and mapping

Science.gov (United States)

Li, Shimiao

2017-09-01

Localization and mapping is an essential ability of a robot to keep track of its own location in an unknown environment. Among existing methods for this purpose, vision-based methods are more effective solutions for being accurate, inexpensive and versatile. Vision-based methods can generally be categorized as feature-based approaches and appearance-based approaches. The feature-based approaches prove higher performance in textured scenarios. However, their performance depend highly on the applied feature-detection algorithms. In this paper, we surveyed algorithms for feature detection, which is an essential step in achieving vision-based localization and mapping. In this pater, we present mathematical models of the algorithms one after another. To compare the performances of the algorithms, we conducted a series of experiments on their accuracy, speed, scale invariance and rotation invariance. The results of the experiments showed that ORB is the fastest algorithm in detecting and matching features, the speed of which is more than 10 times that of SURF and approximately 40 times that of SIFT. And SIFT, although with no advantage in terms of speed, shows the most correct matching pairs and proves its accuracy.

Simultaneous feature selection and classification via Minimax Probability Machine

Directory of Open Access Journals (Sweden)

Liming Yang

2010-12-01

Full Text Available This paper presents a novel method for simultaneous feature selection and classification by incorporating a robust L1-norm into the objective function of Minimax Probability Machine (MPM. A fractional programming framework is derived by using a bound on the misclassification error involving the mean and covariance of the data. Furthermore, the problems are solved by the Quadratic Interpolation method. Experiments show that our methods can select fewer features to improve the generalization compared to MPM, which illustrates the effectiveness of the proposed algorithms.

Sclerosing lobular hyperplasia of breast: cytomorphologic and histomorphologic features: a case report

Directory of Open Access Journals (Sweden)

Kapur Payal

2006-04-01

Full Text Available Abstract Background Mammary sclerosing lobular hyperplasia is an uncommon benign lesion of adolescent and young women. Fine-needle aspiration cytology of mammary sclerosing lobular hyperplasia is said to show characteristic features that include an absence of stromal fragments. Case presentation In this article, we describe a case of sclerosing lobular hyperplasia that occurred in the right breast of a 12-year-old girl. Fine-needle aspiration cytology showed some fibroadenoma-like features including the presence of stromal fragments, while branched tubular fragments were not seen. The diagnosis of sclerosing lobular hyperplasia was made on histologic examination that showed preserved acinar architecture with lobular hyperplasia and sclerosis of intralobular and interlobular stroma. Conclusion Fine-needle aspiration cytology features of mammary sclerosing lobular hyperplasia are not diagnostic and overlap with those of fibroadenoma; however, a distinction between the two benign entities is of no clinical significance. The definitive diagnosis of sclerosing lobular hyperplasia requires histopathologic evaluation.

Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search

Directory of Open Access Journals (Sweden)

Simon Fong

2013-01-01

Full Text Available Selecting the right set of features from data of high dimensionality for inducing an accurate classification model is a tough computational challenge. It is almost a NP-hard problem as the combinations of features escalate exponentially as the number of features increases. Unfortunately in data mining, as well as other engineering applications and bioinformatics, some data are described by a long array of features. Many feature subset selection algorithms have been proposed in the past, but not all of them are effective. Since it takes seemingly forever to use brute force in exhaustively trying every possible combination of features, stochastic optimization may be a solution. In this paper, we propose a new feature selection scheme called Swarm Search to find an optimal feature set by using metaheuristics. The advantage of Swarm Search is its flexibility in integrating any classifier into its fitness function and plugging in any metaheuristic algorithm to facilitate heuristic search. Simulation experiments are carried out by testing the Swarm Search over some high-dimensional datasets, with different classification algorithms and various metaheuristic algorithms. The comparative experiment results show that Swarm Search is able to attain relatively low error rates in classification without shrinking the size of the feature subset to its minimum.

Screening for Plant Features

NARCIS (Netherlands)

Heijden, van der G.W.A.M.; Polder, G.

2015-01-01

In this chapter, an overview of different plant features is given, from (sub)cellular to canopy level. A myriad of methods is available to measure these features using image analysis, and often, multiple methods can be used to measure the same feature. Several criteria are listed for choosing a

Thermokarst and thaw-related landscape dynamics -- an annotated bibliography with an emphasis on potential effects on habitat and wildlife

Science.gov (United States)

Jones, Benjamin M.; Amundson, Courtney L.; Koch, Joshua C.; Grosse, Guido

2013-01-01

, and heat and mass transfer processes. Typical Arctic thermokarst landforms include thermokarst lakes, collapsed pingos, sinkholes, and pits. Thermokarst is differentiated from thermal erosion, which refers to the erosion of the land surface by thermal and mechanical processes (Mackay, 1970; van Everdingen, 1998). Typical thermal erosional features include thermo-erosional gullies. Thermal abrasion is further differentiated from thermokarst and thermal erosion by association with the reworking of ocean, river, and lake bluffs (Are, 1988). Typical thermo-abrasion features include erosional niches at the base of bluffs. Thermal denudation is another distinct term that refers to the effect of incoming solar energy on the thaw of frozen slopes and permafrost bodies that subsequently become transported downhill by gravity (Shur and Osterkamp, 2007). Active layer detachment slides and thaw slumps are typical thermal denudation features. Shur and Osterkamp (2007) noted that these various transport processes may occur together with thermokarst or in instances that would not be considered thermokarst. This compilation of references regarding thermokarst and other thaw-related features is focused on the Arctic and the Subarctic. References were drawn from North America as well as Siberia. English-language literature mostly was targeted, with 167 references annotated in version 1.0; however, an additional 28 Russian-language references were taken from Shur and Osterkamp (2007) and are provided at the end of this document. This compilation may be missing key references and inevitably will become outdated soon after publication. We hope that this document, version 1.0, will serve as the foundation for a comprehensive compilation of thermokarst and permafrost-terrain stability references, and that it will be updated continually over the coming years.

Feature generation and representations for protein-protein interaction classification.

Science.gov (United States)

Lan, Man; Tan, Chew Lim; Su, Jian

2009-10-01

Automatic detecting protein-protein interaction (PPI) relevant articles is a crucial step for large-scale biological database curation. The previous work adopted POS tagging, shallow parsing and sentence splitting techniques, but they achieved worse performance than the simple bag-of-words representation. In this paper, we generated and investigated multiple types of feature representations in order to further improve the performance of PPI text classification task. Besides the traditional domain-independent bag-of-words approach and the term weighting methods, we also explored other domain-dependent features, i.e. protein-protein interaction trigger keywords, protein named entities and the advanced ways of incorporating Natural Language Processing (NLP) output. The integration of these multiple features has been evaluated on the BioCreAtIvE II corpus. The experimental results showed that both the advanced way of using NLP output and the integration of bag-of-words and NLP output improved the performance of text classification. Specifically, in comparison with the best performance achieved in the BioCreAtIvE II IAS, the feature-level and classifier-level integration of multiple features improved the performance of classification 2.71% and 3.95%, respectively.

Efficient feature for classification of eye movements using electrooculography signals

Directory of Open Access Journals (Sweden)

Phukpattaranont Pornchai

2016-01-01

Full Text Available Electrooculography (EOG signal is widely and successfully used to detect activities of human eye. The advantages of the EOG-based interface over other conventional interfaces have been presented in the last two decades; however, due to a lot of information in EOG signals, the extraction of useful features should be done before the classification task. In this study, an efficient feature extracted from two directional EOG signals: vertical and horizontal signals has been presented and evaluated. There are the maximum peak and valley amplitude values, the maximum peak and valley position values, and slope, which are derived from both vertical and horizontal signals. In the experiments, EOG signals obtained from five healthy subjects with ten directional eye movements were employed: up, down, right, left, up-right, up-left, down-right down-left clockwise and counterclockwise. The mean feature values and their standard deviations have been reported. The difference between the mean values of the proposed feature from different eye movements can be clearly seen. Using the scatter plot, the differences in features can be also clearly observed. Results show that classification accuracy can approach 100% with a simple distinction feature rule. The proposed features can be useful for various advanced human-computer interface applications in future researches.

Exploring the relationship between fractal features and bacterial essential genes

International Nuclear Information System (INIS)

Yu Yong-Ming; Yang Li-Cai; Zhao Lu-Lu; Liu Zhi-Ping; Zhou Qian

2016-01-01

Essential genes are indispensable for the survival of an organism in optimal conditions. Rapid and accurate identifications of new essential genes are of great theoretical and practical significance. Exploring features with predictive power is fundamental for this. Here, we calculate six fractal features from primary gene and protein sequences and then explore their relationship with gene essentiality by statistical analysis and machine learning-based methods. The models are applied to all the currently available identified genes in 27 bacteria from the database of essential genes (DEG). It is found that the fractal features of essential genes generally differ from those of non-essential genes. The fractal features are used to ascertain the parameters of two machine learning classifiers: Naïve Bayes and Random Forest. The area under the curve (AUC) of both classifiers show that each fractal feature is satisfactorily discriminative between essential genes and non-essential genes individually. And, although significant correlations exist among fractal features, gene essentiality can also be reliably predicted by various combinations of them. Thus, the fractal features analyzed in our study can be used not only to construct a good essentiality classifier alone, but also to be significant contributors for computational tools identifying essential genes. (paper)

Invariant Handwriting Features Useful in Cursive-Script Recognition

NARCIS (Netherlands)

Teulings, Hans-leo L; Schomaker, L R; Impedovo, S.

1994-01-01

A handwriting pattern is considered as a sequence of ballistic strokes. Replications of a pattern may be generated from a single, higher-level memory representation, acting as a motor program. Therefore, those stroke features which show the most invariant pattern are probably related to the

Effects of Feature Extraction and Classification Methods on Cyberbully Detection

OpenAIRE

ÖZEL, Selma Ayşe; SARAÇ, Esra

2016-01-01

Cyberbullying is defined as an aggressive, intentional action against a defenseless person by using the Internet, or other electronic contents. Researchers have found that many of the bullying cases have tragically ended in suicides; hence automatic detection of cyberbullying has become important. In this study we show the effects of feature extraction, feature selection, and classification methods that are used, on the performance of automatic detection of cyberbullying. To perform the exper...

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

Science.gov (United States)

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.

Remote Sensing Image Registration Using Multiple Image Features

Directory of Open Access Journals (Sweden)

Kun Yang

2017-06-01

Full Text Available Remote sensing image registration plays an important role in military and civilian fields, such as natural disaster damage assessment, military damage assessment and ground targets identification, etc. However, due to the ground relief variations and imaging viewpoint changes, non-rigid geometric distortion occurs between remote sensing images with different viewpoint, which further increases the difficulty of remote sensing image registration. To address the problem, we propose a multi-viewpoint remote sensing image registration method which contains the following contributions. (i A multiple features based finite mixture model is constructed for dealing with different types of image features. (ii Three features are combined and substituted into the mixture model to form a feature complementation, i.e., the Euclidean distance and shape context are used to measure the similarity of geometric structure, and the SIFT (scale-invariant feature transform distance which is endowed with the intensity information is used to measure the scale space extrema. (iii To prevent the ill-posed problem, a geometric constraint term is introduced into the L2E-based energy function for better behaving the non-rigid transformation. We evaluated the performances of the proposed method by three series of remote sensing images obtained from the unmanned aerial vehicle (UAV and Google Earth, and compared with five state-of-the-art methods where our method shows the best alignments in most cases.

Enhanced regulatory sequence prediction using gapped k-mer features.

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Ghandi, Mahmoud; Lee, Dongwon; Mohammad-Noori, Morteza; Beer, Michael A

2014-07-01

Oligomers of length k, or k-mers, are convenient and widely used features for modeling the properties and functions of DNA and protein sequences. However, k-mers suffer from the inherent limitation that if the parameter k is increased to resolve longer features, the probability of observing any specific k-mer becomes very small, and k-mer counts approach a binary variable, with most k-mers absent and a few present once. Thus, any statistical learning approach using k-mers as features becomes susceptible to noisy training set k-mer frequencies once k becomes large. To address this problem, we introduce alternative feature sets using gapped k-mers, a new classifier, gkm-SVM, and a general method for robust estimation of k-mer frequencies. To make the method applicable to large-scale genome wide applications, we develop an efficient tree data structure for computing the kernel matrix. We show that compared to our original kmer-SVM and alternative approaches, our gkm-SVM predicts functional genomic regulatory elements and tissue specific enhancers with significantly improved accuracy, increasing the precision by up to a factor of two. We then show that gkm-SVM consistently outperforms kmer-SVM on human ENCODE ChIP-seq datasets, and further demonstrate the general utility of our method using a Naïve-Bayes classifier. Although developed for regulatory sequence analysis, these methods can be applied to any sequence classification problem.

Enhanced regulatory sequence prediction using gapped k-mer features.

Directory of Open Access Journals (Sweden)

Mahmoud Ghandi

2014-07-01

Full Text Available Oligomers of length k, or k-mers, are convenient and widely used features for modeling the properties and functions of DNA and protein sequences. However, k-mers suffer from the inherent limitation that if the parameter k is increased to resolve longer features, the probability of observing any specific k-mer becomes very small, and k-mer counts approach a binary variable, with most k-mers absent and a few present once. Thus, any statistical learning approach using k-mers as features becomes susceptible to noisy training set k-mer frequencies once k becomes large. To address this problem, we introduce alternative feature sets using gapped k-mers, a new classifier, gkm-SVM, and a general method for robust estimation of k-mer frequencies. To make the method applicable to large-scale genome wide applications, we develop an efficient tree data structure for computing the kernel matrix. We show that compared to our original kmer-SVM and alternative approaches, our gkm-SVM predicts functional genomic regulatory elements and tissue specific enhancers with significantly improved accuracy, increasing the precision by up to a factor of two. We then show that gkm-SVM consistently outperforms kmer-SVM on human ENCODE ChIP-seq datasets, and further demonstrate the general utility of our method using a Naïve-Bayes classifier. Although developed for regulatory sequence analysis, these methods can be applied to any sequence classification problem.

Analyzing locomotion synthesis with feature-based motion graphs.

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Mahmudi, Mentar; Kallmann, Marcelo

2013-05-01

We propose feature-based motion graphs for realistic locomotion synthesis among obstacles. Among several advantages, feature-based motion graphs achieve improved results in search queries, eliminate the need of postprocessing for foot skating removal, and reduce the computational requirements in comparison to traditional motion graphs. Our contributions are threefold. First, we show that choosing transitions based on relevant features significantly reduces graph construction time and leads to improved search performances. Second, we employ a fast channel search method that confines the motion graph search to a free channel with guaranteed clearance among obstacles, achieving faster and improved results that avoid expensive collision checking. Lastly, we present a motion deformation model based on Inverse Kinematics applied over the transitions of a solution branch. Each transition is assigned a continuous deformation range that does not exceed the original transition cost threshold specified by the user for the graph construction. The obtained deformation improves the reachability of the feature-based motion graph and in turn also reduces the time spent during search. The results obtained by the proposed methods are evaluated and quantified, and they demonstrate significant improvements in comparison to traditional motion graph techniques.

Psychological features of attention in archery

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Ekaterina Yu. Korobeynikova

2017-06-01

Full Text Available The issue of attention is one of the leading in sports psychology. Quite often, athletes’ failures in competitions are ultimately connected with the attention processes, i.e. distraction, switching or loss of concentration. Simultaneously, each particular kind of sport is distinguished by a specific competitive situation and accordingly presents a number of requirements to athletes, including attention features. Archery is no exception. Thus, in shooting sports, concentration and stability of attention are often deemed as the most significant features of attention. The paper is devoted to the study of the attention dynamic properties in archers. Attention features of athletes were assessed depending on the sports major, gender, age, experience and level of competence. 65 archers from different regions of Russia took part in the study, including 34 males and 31 females, the average age being 16.29 ± 1.74. Experience ranges from 1 year to 8 years, average experience is 4.46 ± 1.93. The research results showed that archers are characterized by high indicators of stability of attention, and also high efficiency of solving attention problems. The professional success of archery was associated with the ability to distribute attention when necessary. At the same time, there were no significant differences in the features of attention for recurved and compound archers, which indicates the uniformity of tasks related to attention in the sporting practice of archers. Summing up, it is necessary to include skills in the distribution of attention in the program of psychological training of archers.

Feature Extraction and Fusion Using Deep Convolutional Neural Networks for Face Detection

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Xiaojun Lu

2017-01-01

Full Text Available This paper proposes a method that uses feature fusion to represent images better for face detection after feature extraction by deep convolutional neural network (DCNN. First, with Clarifai net and VGG Net-D (16 layers, we learn features from data, respectively; then we fuse features extracted from the two nets. To obtain more compact feature representation and mitigate computation complexity, we reduce the dimension of the fused features by PCA. Finally, we conduct face classification by SVM classifier for binary classification. In particular, we exploit offset max-pooling to extract features with sliding window densely, which leads to better matches of faces and detection windows; thus the detection result is more accurate. Experimental results show that our method can detect faces with severe occlusion and large variations in pose and scale. In particular, our method achieves 89.24% recall rate on FDDB and 97.19% average precision on AFW.

Discrimination of single features and conjunctions by children.

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Taylor, M J; Chevalier, H; Lobaugh, N J

2003-12-01

Stimuli that are discriminated by a conjunction of features can show more rapid early processing in adults. To determine how this facilitation effect develops, the processing of visual features and their conjunction was examined in 7-12-year-old children. The children completed a series of tasks in which they made a target-non-target judgement as a function of shape only, colour only or shape and colour features, while event-related potentials were recorded. To assess early stages of feature processing the posteriorly distributed P1 and N1 were analysed. Attentional effects were seen for both components. P1 had a shorter latency and P1 and N1 had larger amplitudes to targets than non-targets. Task effects were driven by the conjunction task. P1 amplitude was largest, while N1 amplitude was smallest for the conjunction targets. In contrast to larger left-sided N1 in adults, N1 had a symmetrical distribution in the children. N1 latency was shortest for the conjunction targets in the 9-10-year olds and 11-12-year olds, demonstrating facilitation in children, but which continued to develop over the pre-teen years. These data underline the sensitivity of early stages of processing to both top-down modulations and the parallel binding of non-spatial features in young children. Furthermore, facilitation effects, increased speed of processing when features need to be conjoined, mature in mid-childhood, arguing against a hierarchical model of visual processing, and supporting a rapid, integrated facilitative model.

Joint Concept Correlation and Feature-Concept Relevance Learning for Multilabel Classification.

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Zhao, Xiaowei; Ma, Zhigang; Li, Zhi; Li, Zhihui

2018-02-01

In recent years, multilabel classification has attracted significant attention in multimedia annotation. However, most of the multilabel classification methods focus only on the inherent correlations existing among multiple labels and concepts and ignore the relevance between features and the target concepts. To obtain more robust multilabel classification results, we propose a new multilabel classification method aiming to capture the correlations among multiple concepts by leveraging hypergraph that is proved to be beneficial for relational learning. Moreover, we consider mining feature-concept relevance, which is often overlooked by many multilabel learning algorithms. To better show the feature-concept relevance, we impose a sparsity constraint on the proposed method. We compare the proposed method with several other multilabel classification methods and evaluate the classification performance by mean average precision on several data sets. The experimental results show that the proposed method outperforms the state-of-the-art methods.

Adapting Local Features for Face Detection in Thermal Image

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Chao Ma

2017-11-01

Full Text Available A thermal camera captures the temperature distribution of a scene as a thermal image. In thermal images, facial appearances of different people under different lighting conditions are similar. This is because facial temperature distribution is generally constant and not affected by lighting condition. This similarity in face appearances is advantageous for face detection. To detect faces in thermal images, cascade classifiers with Haar-like features are generally used. However, there are few studies exploring the local features for face detection in thermal images. In this paper, we introduce two approaches relying on local features for face detection in thermal images. First, we create new feature types by extending Multi-Block LBP. We consider a margin around the reference and the generally constant distribution of facial temperature. In this way, we make the features more robust to image noise and more effective for face detection in thermal images. Second, we propose an AdaBoost-based training method to get cascade classifiers with multiple types of local features. These feature types have different advantages. In this way we enhance the description power of local features. We did a hold-out validation experiment and a field experiment. In the hold-out validation experiment, we captured a dataset from 20 participants, comprising 14 males and 6 females. For each participant, we captured 420 images with 10 variations in camera distance, 21 poses, and 2 appearances (participant with/without glasses. We compared the performance of cascade classifiers trained by different sets of the features. The experiment results showed that the proposed approaches effectively improve the performance of face detection in thermal images. In the field experiment, we compared the face detection performance in realistic scenes using thermal and RGB images, and gave discussion based on the results.

Acoustic Features and Auditory Perceptions of the Cries of Newborns with Prenatal and Perinatal Complications.

Science.gov (United States)

Zeskind, Philip Sanford; Lester, Barry M.

1978-01-01

Describes two experiments which examined the relation between neonatal cry features and obstetric histories. Experiment 1 showed differences in pitch and durational features between the cries of high- and low-complication newborns. Experiment 2 showed differences in the cry ratings of the two groups on dimensions such as aversive, sick, urgent,…

Features for Exploiting Black-Box Optimization Problem Structure

DEFF Research Database (Denmark)

Tierney, Kevin; Malitsky, Yuri; Abell, Tinus

2013-01-01

landscape of BBO problems and show how an algorithm portfolio approach can exploit these general, problem indepen- dent features and outperform the utilization of any single minimization search strategy. We test our methodology on data from the GECCO Workshop on BBO Benchmarking 2012, which contains 21...

SU-D-207B-01: Radiomics Feature Reproducibility From Repeat CT Scans of Patients with Rectal Cancer

Energy Technology Data Exchange (ETDEWEB)

Hu, P; Wang, J; Zhong, H; Zhou, Z; Shen, L; Hu, W; Zhang, Z [Fudan University Shanghai Cancer Center, Shanghai, Shanghai (China)

2016-06-15

Purpose: To evaluate the reproducibility of radiomics features by repeating computed tomographic (CT) scans in rectal cancer. To choose stable radiomics features for rectal cancer. Methods: 40 rectal cancer patients were enrolled in this study, each of whom underwent two CT scans within average 8.7 days (5 days to 17 days), before any treatment was delivered. The rectal gross tumor volume (GTV) was distinguished and segmented by an experienced oncologist in both CTs. Totally, more than 2000 radiomics features were defined in this study, which were divided into four groups (I: GLCM, II: GLRLM III: Wavelet GLCM and IV: Wavelet GLRLM). For each group, five types of features were extracted (Max slice: features from the largest slice of target images, Max value: features from all slices of target images and choose the maximum value, Min value: minimum value of features for all slices, Average value: average value of features for all slices, Matrix sum: all slices of target images translate into GLCM and GLRLM matrices and superpose all matrices, then extract features from the superposed matrix). Meanwhile a LOG (Laplace of Gauss) filter with different parameters was applied to these images. Concordance correlation coefficients (CCC) and inter-class correlation coefficients (ICC) were calculated to assess the reproducibility. Results: 403 radiomics features were extracted from each type of patients’ medical images. Features of average type are the most reproducible. Different filters have little effect for radiomics features. For the average type features, 253 out of 403 features (62.8%) showed high reproducibility (ICC≥0.8), 133 out of 403 features (33.0%) showed medium reproducibility (0.8≥ICC≥0.5) and 17 out of 403 features (4.2%) showed low reproducibility (ICC≥0.5). Conclusion: The average type radiomics features are the most stable features in rectal cancer. Further analysis of these features of rectal cancer can be warranted for treatment monitoring and

Dissociation between Features and Feature Relations in Infant Memory: Effects of Memory Load.

Science.gov (United States)

Bhatt, Ramesh S.; Rovee-Collier, Carolyn

1997-01-01

Four experiments examined effects of the number of features and feature relations on learning and long-term memory in 3-month olds. Findings suggested that memory load size selectively constrained infants' long-term memory for relational information, suggesting that in infants, features and relations are psychologically distinct and that memory…

An adaptation study of internal and external features in facial representations.

Science.gov (United States)

Hills, Charlotte; Romano, Kali; Davies-Thompson, Jodie; Barton, Jason J S

2014-07-01

Prior work suggests that internal features contribute more than external features to face processing. Whether this asymmetry is also true of the mental representations of faces is not known. We used face adaptation to determine whether the internal and external features of faces contribute differently to the representation of facial identity, whether this was affected by familiarity, and whether the results differed if the features were presented in isolation or as part of a whole face. In a first experiment, subjects performed a study of identity adaptation for famous and novel faces, in which the adapting stimuli were whole faces, the internal features alone, or the external features alone. In a second experiment, the same faces were used, but the adapting internal and external features were superimposed on whole faces that were ambiguous to identity. The first experiment showed larger aftereffects for unfamiliar faces, and greater aftereffects from internal than from external features, and the latter was true for both familiar and unfamiliar faces. When internal and external features were presented in a whole-face context in the second experiment, aftereffects from either internal or external features was less than that from the whole face, and did not differ from each other. While we reproduce the greater importance of internal features when presented in isolation, we find this is equally true for familiar and unfamiliar faces. The dominant influence of internal features is reduced when integrated into a whole-face context, suggesting another facet of expert face processing. Copyright © 2014 Elsevier B.V. All rights reserved.

Common Features in Electronic Structure of the Oxypnictide Superconductors from Photoemission Spectroscopy

International Nuclear Information System (INIS)

Xiao-Wen, Jia; Hai-Yun, Liu; Wen-Tao, Zhang; Lin, Zhao; Jian-Qiao, Meng; Guo-Dong, Liu; Xiao-Li, Dong; Zhi-An, Ren; Wei, Yi; Guang-Can, Che; Zhong-Xian, Zhao; Gang, Wu; Rong-Hua, Liu; Xian-Hui, Chen; Gen-Fu, Chen; Nan-Lin, Wang; Yong, Zhu; Xiao-Yang, Wang; Gui-Ling, Wang; Yong, Zhou

2008-01-01

High resolution photoemission measurements are carried out on non-superconducting LaFeAsO parent compound and various superconducting RFeAs(O 1-x F x ) (R=La, Ce and Pr) compounds. It is found that the parent LaFeAsO compound shows a metallic character. By extensive measurements, several common features are identified in the electronic structure of these Fe-based compounds: (1) 0.2 eV feature in the valence band, (2) a universal 13-16 meV feature, (3) near Ef spectral weight suppression with decreasing temperature. These universal features can provide important information about band structure, superconducting gap and pseudogap in these Fe-based materials

Task-induced frequency modulation features for brain-computer interfacing.

Science.gov (United States)

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

2017-10-01

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. 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. 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. 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.

Task-induced frequency modulation features for brain-computer interfacing

Science.gov (United States)

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.

FAST DISCRETE CURVELET TRANSFORM BASED ANISOTROPIC FEATURE EXTRACTION FOR IRIS RECOGNITION

Directory of Open Access Journals (Sweden)

Amol D. Rahulkar

2010-11-01

Full Text Available The feature extraction plays a very important role in iris recognition. Recent researches on multiscale analysis provide good opportunity to extract more accurate information for iris recognition. In this work, a new directional iris texture features based on 2-D Fast Discrete Curvelet Transform (FDCT is proposed. The proposed approach divides the normalized iris image into six sub-images and the curvelet transform is applied independently on each sub-image. The anisotropic feature vector for each sub-image is derived using the directional energies of the curvelet coefficients. These six feature vectors are combined to create the resultant feature vector. During recognition, the nearest neighbor classifier based on Euclidean distance has been used for authentication. The effectiveness of the proposed approach has been tested on two different databases namely UBIRIS and MMU1. Experimental results show the superiority of the proposed approach.

Design and Realization of Music Retrieval System Based on Feature Content

Directory of Open Access Journals (Sweden)

Li Lei

2015-01-01

Full Text Available As computer technology develops rapidly, retrieval systems have also undergone great changes. People are no longer contented with singular retrieval means, but are trying many other ways to retrieve feature content. When it comes to music, however, the complexity of sound is still preventing its retrieval from moving further forward. To solve this problem, systematic analysis and study is carried out on music retrieval system based on feature content. A music retrieval system model based on feature content consisting of technical approaches for processing and retrieving of extraction symbols of music feature content is built and realized. An SML model is proposed and tested on two different types of song sets. The result shows good performance of the system. Besides, the shortfalls of the model are also noted and the future prospects of the music retrieval system based on feature content are outlined.

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

Science.gov (United States)

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.

Non-negative matrix factorization in texture feature for classification of dementia with MRI data

Science.gov (United States)

Sarwinda, D.; Bustamam, A.; Ardaneswari, G.

2017-07-01

This paper investigates applications of non-negative matrix factorization as feature selection method to select the features from gray level co-occurrence matrix. The proposed approach is used to classify dementia using MRI data. In this study, texture analysis using gray level co-occurrence matrix is done to feature extraction. In the feature extraction process of MRI data, we found seven features from gray level co-occurrence matrix. Non-negative matrix factorization selected three features that influence of all features produced by feature extractions. A Naïve Bayes classifier is adapted to classify dementia, i.e. Alzheimer's disease, Mild Cognitive Impairment (MCI) and normal control. The experimental results show that non-negative factorization as feature selection method able to achieve an accuracy of 96.4% for classification of Alzheimer's and normal control. The proposed method also compared with other features selection methods i.e. Principal Component Analysis (PCA).

Sonographic features of lethal multiple pterygium syndrome at 14 weeks.

Science.gov (United States)

Chen, Min; Chan, Gavin Shueng Wai; Lee, Chin Peng; Tang, Mary Hoi Yin

2005-06-01

Lethal multiple pterygium syndrome is a rare inherited disorder. Previous reports suggest that the diagnosis may be based on prenatal sonographic demonstration of severe limb flexion, absence of fetal motion, and a large cystic hygroma in the second and third trimesters. We present the sonographic features and postmortem features of a fetus with lethal multiple pterygium syndrome at 13 weeks of gestation, which shows that the condition can possibly be diagnosed in the first trimester of pregnancy.

Case study of the gradient features of in situ concrete

Directory of Open Access Journals (Sweden)

Pengkun Hou

2014-01-01

Full Text Available The recognition of gradient features of the properties of in situ concrete is important for the interpretation/prediction of service life. In this work, the gradient features: water absorption, porosity, mineralogy, morphology and micromechanical properties were studied on two in situ road concretes (15 and 5 years old, respectively by weighing, MIP, XRD, IR, SEM/EDS and micro-indentation techniques. Results showed that a coarsening trend of the pores of the concrete leads to a gradual increase of liquid transport property from inside to outside. Although the carbonation of the exposed surface results in a compact microstructure of the paste, its combined action with calcium-leaching leads to a comparable porosity of different concrete layers. Moreover, the combining factors result in three morphological features, i.e. a porous and granular exposed-layer, a fibrous and porous subexposed-layer and a compact inner-layer. Micro-indentation test results showed that a hard layer that moves inward with aging exists due to the alterations of the mineralogy, the pore and the gel structure.

Image Mosaic Method Based on SIFT Features of Line Segment

Directory of Open Access Journals (Sweden)

Jun Zhu

2014-01-01

Full Text Available This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling.

Perceptual grouping and attention in visual search for features and for objects.

Science.gov (United States)

Treisman, A

1982-04-01

This article explores the effects of perceptual grouping on search for targets defined by separate features or by conjunction of features. Treisman and Gelade proposed a feature-integration theory of attention, which claims that in the absence of prior knowledge, the separable features of objects are correctly combined only when focused attention is directed to each item in turn. If items are preattentively grouped, however, attention may be directed to groups rather than to single items whenever no recombination of features within a group could generate an illusory target. This prediction is confirmed: In search for conjunctions, subjects appear to scan serially between groups rather than items. The scanning rate shows little effect of the spatial density of distractors, suggesting that it reflects serial fixations of attention rather than eye movements. Search for features, on the other hand, appears to independent of perceptual grouping, suggesting that features are detected preattentively. A conjunction target can be camouflaged at the preattentive level by placing it at the boundary between two adjacent groups, each of which shares one of its features. This suggests that preattentive grouping creates separate feature maps within each separable dimension rather than one global configuration.

Doubly sparse factor models for unifying feature transformation and feature selection

International Nuclear Information System (INIS)

Katahira, Kentaro; Okanoya, Kazuo; Okada, Masato; Matsumoto, Narihisa; Sugase-Miyamoto, Yasuko

2010-01-01

A number of unsupervised learning methods for high-dimensional data are largely divided into two groups based on their procedures, i.e., (1) feature selection, which discards irrelevant dimensions of the data, and (2) feature transformation, which constructs new variables by transforming and mixing over all dimensions. We propose a method that both selects and transforms features in a common Bayesian inference procedure. Our method imposes a doubly automatic relevance determination (ARD) prior on the factor loading matrix. We propose a variational Bayesian inference for our model and demonstrate the performance of our method on both synthetic and real data.

Doubly sparse factor models for unifying feature transformation and feature selection

Energy Technology Data Exchange (ETDEWEB)

Katahira, Kentaro; Okanoya, Kazuo; Okada, Masato [ERATO, Okanoya Emotional Information Project, Japan Science Technology Agency, Saitama (Japan); Matsumoto, Narihisa; Sugase-Miyamoto, Yasuko, E-mail: okada@k.u-tokyo.ac.j [Human Technology Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki (Japan)

2010-06-01

A number of unsupervised learning methods for high-dimensional data are largely divided into two groups based on their procedures, i.e., (1) feature selection, which discards irrelevant dimensions of the data, and (2) feature transformation, which constructs new variables by transforming and mixing over all dimensions. We propose a method that both selects and transforms features in a common Bayesian inference procedure. Our method imposes a doubly automatic relevance determination (ARD) prior on the factor loading matrix. We propose a variational Bayesian inference for our model and demonstrate the performance of our method on both synthetic and real data.

Men and women show similar survival outcome in stage IV breast cancer.

Science.gov (United States)

Wu, San-Gang; Zhang, Wen-Wen; Liao, Xu-Lin; Sun, Jia-Yuan; Li, Feng-Yan; Su, Jing-Jun; He, Zhen-Yu

2017-08-01

To evaluate the clinicopathological features, patterns of distant metastases, and survival outcome between stage IV male breast cancer (MBC) and female breast cancer (FBC). Patients diagnosed with stage IV MBC and FBC between 2010 and 2013 were included using the Surveillance, Epidemiology, and End Results program. Univariate and multivariate Cox regression analyses were used to analyze risk factors for overall survival (OS). A total of 4997 patients were identified, including 60 MBC and 4937 FBC. Compared with FBC, patients with MBC were associated with a significantly higher rate of estrogen receptor-positive, progesterone receptor-positive, unmarried, lung metastases, and a lower frequency of liver metastases. Univariate and multivariate analyses showed no significant difference in OS between MBC and FBC. In the propensity score-matched population, there was also no difference in survival between MBC and FBC. Multivariate analysis of MBC showed that OS was longer for patients aged 50-69 years and with estrogen receptor-positive disease. There was no significant difference in survival outcome between stage IV MBC and FBC, but significant differences in clinicopathological features and patterns of metastases between the genders. Copyright © 2017 Elsevier Ltd. All rights reserved.

Graphemes Sharing Phonetic Features Tend to Induce Similar Synesthetic Colors.

Science.gov (United States)

Kang, Mi-Jeong; Kim, Yeseul; Shin, Ji-Young; Kim, Chai-Youn

2017-01-01

Individuals with grapheme-color synesthesia experience idiosyncratic colors when viewing achromatic letters or digits. Despite large individual differences in grapheme-color association, synesthetes tend to associate graphemes sharing a perceptual feature with similar synesthetic colors. Sound has been suggested as one such feature. In the present study, we investigated whether graphemes of which representative phonemes have similar phonetic features tend to be associated with analogous synesthetic colors. We tested five Korean multilingual synesthetes on a color-matching task using graphemes from Korean, English, and Japanese orthography. We then compared the similarity of synesthetic colors induced by those characters sharing a phonetic feature. Results showed that graphemes associated with the same phonetic feature tend to induce synesthetic color in both within- and cross-script analyses. Moreover, this tendency was consistent for graphemes that are not transliterable into each other as well as graphemes that are. These results suggest that it is the perceptual-i.e., phonetic-properties associated with graphemes, not just conceptual associations such as transliteration, that determine synesthetic color.

Graphemes Sharing Phonetic Features Tend to Induce Similar Synesthetic Colors

Science.gov (United States)

Kang, Mi-Jeong; Kim, Yeseul; Shin, Ji-Young; Kim, Chai-Youn

2017-01-01

Individuals with grapheme-color synesthesia experience idiosyncratic colors when viewing achromatic letters or digits. Despite large individual differences in grapheme-color association, synesthetes tend to associate graphemes sharing a perceptual feature with similar synesthetic colors. Sound has been suggested as one such feature. In the present study, we investigated whether graphemes of which representative phonemes have similar phonetic features tend to be associated with analogous synesthetic colors. We tested five Korean multilingual synesthetes on a color-matching task using graphemes from Korean, English, and Japanese orthography. We then compared the similarity of synesthetic colors induced by those characters sharing a phonetic feature. Results showed that graphemes associated with the same phonetic feature tend to induce synesthetic color in both within- and cross-script analyses. Moreover, this tendency was consistent for graphemes that are not transliterable into each other as well as graphemes that are. These results suggest that it is the perceptual—i.e., phonetic—properties associated with graphemes, not just conceptual associations such as transliteration, that determine synesthetic color. PMID:28348537

Feature Import Vector Machine: A General Classifier with Flexible Feature Selection.

Science.gov (United States)

Ghosh, Samiran; Wang, Yazhen

2015-02-01

The support vector machine (SVM) and other reproducing kernel Hilbert space (RKHS) based classifier systems are drawing much attention recently due to its robustness and generalization capability. General theme here is to construct classifiers based on the training data in a high dimensional space by using all available dimensions. The SVM achieves huge data compression by selecting only few observations which lie close to the boundary of the classifier function. However when the number of observations are not very large (small n ) but the number of dimensions/features are large (large p ), then it is not necessary that all available features are of equal importance in the classification context. Possible selection of an useful fraction of the available features may result in huge data compression. In this paper we propose an algorithmic approach by means of which such an optimal set of features could be selected. In short, we reverse the traditional sequential observation selection strategy of SVM to that of sequential feature selection. To achieve this we have modified the solution proposed by Zhu and Hastie (2005) in the context of import vector machine (IVM), to select an optimal sub-dimensional model to build the final classifier with sufficient accuracy.

Longitudinal Study of Sensory Features in Children with Autism Spectrum Disorder

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Lucia Perez Repetto

2017-01-01

Full Text Available Background. Between 45 and 95% of children with Autism Spectrum Disorder (ASD present sensory features that affect their daily functioning. However, the data in the scientific literature are not conclusive regarding the evolution of sensory features in children with ASD. The main objective of this study was to analyze the sensory features of children within the age of 3-4 (T1 when they received their ASD diagnosis and two years later (T2 when they started school. Methods. We conducted a prospective cohort study to assess sensory features in 34 children with ASD over time. The data were collected using a standardized assessment tool, the Sensory Profile. Results. Our analyses show that sensory features in children with ASD are stable from the age of three to six years. The stability of sensory scores is independent of correction by covariates, such as cognitive level and autism severity scores. Conclusions. Children with ASD have sensory features that persist from the time of diagnosis at the age of 3 to 4 years to school age. This persistence of sensory features from an early age underscores the need to support these children and their parents. Sensory features should be detected early and managed to improve functional and psychosocial outcomes.

Obscene Video Recognition Using Fuzzy SVM and New Sets of Features

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Alireza Behrad

2013-02-01

Full Text Available In this paper, a novel approach for identifying normal and obscene videos is proposed. In order to classify different episodes of a video independently and discard the need to process all frames, first, key frames are extracted and skin regions are detected for groups of video frames starting with key frames. In the second step, three different features including 1- structural features based on single frame information, 2- features based on spatiotemporal volume and 3-motion-based features, are extracted for each episode of video. The PCA-LDA method is then applied to reduce the size of structural features and select more distinctive features. For the final step, we use fuzzy or a Weighted Support Vector Machine (WSVM classifier to identify video episodes. We also employ a multilayer Kohonen network as an initial clustering algorithm to increase the ability to discriminate between the extracted features into two classes of videos. Features based on motion and periodicity characteristics increase the efficiency of the proposed algorithm in videos with bad illumination and skin colour variation. The proposed method is evaluated using 1100 videos in different environmental and illumination conditions. The experimental results show a correct recognition rate of 94.2% for the proposed algorithm.

Critical product features' identification using an opinion analyzer.

Science.gov (United States)

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.

Learning in data-limited multimodal scenarios: Scandent decision forests and tree-based features.

Science.gov (United States)

Hor, Soheil; Moradi, Mehdi

2016-12-01

Incomplete and inconsistent datasets often pose difficulties in multimodal studies. We introduce the concept of scandent decision trees to tackle these difficulties. Scandent trees are decision trees that optimally mimic the partitioning of the data determined by another decision tree, and crucially, use only a subset of the feature set. We show how scandent trees can be used to enhance the performance of decision forests trained on a small number of multimodal samples when we have access to larger datasets with vastly incomplete feature sets. Additionally, we introduce the concept of tree-based feature transforms in the decision forest paradigm. When combined with scandent trees, the tree-based feature transforms enable us to train a classifier on a rich multimodal dataset, and use it to classify samples with only a subset of features of the training data. Using this methodology, we build a model trained on MRI and PET images of the ADNI dataset, and then test it on cases with only MRI data. We show that this is significantly more effective in staging of cognitive impairments compared to a similar decision forest model trained and tested on MRI only, or one that uses other kinds of feature transform applied to the MRI data. Copyright © 2016. Published by Elsevier B.V.

ATLAS event featuring two charm jets and missing energy

CERN Multimedia

ATLAS Collaboration

2012-01-01

Proton collision event in the ATLAS detector featuring two tagged charm jets and missing transverse energy. The zoomed view in the bottom right panel shows a displaced vertex of one of the c-tagged jets (marked in blue).

Clinical features of emergency department patients with depression ...

African Journals Online (AJOL)

Clinical features of emergency department patients with depression who had attempted to commit suicide by poisoning. ... MDD patients. Conclusion: In poisoning patients with MDD, physicians in the ED must consider that they have a higher tendency to show suicidal behavior and to have ingested multiple types of drugs.

A method for real-time implementation of HOG feature extraction

Science.gov (United States)

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.

[INVITED] Evaluation of process observation features for laser metal welding

Science.gov (United States)

Tenner, Felix; Klämpfl, Florian; Nagulin, Konstantin Yu.; Schmidt, Michael

2016-06-01

In the present study we show how fast the fluid dynamics change when changing the laser power for different feed rates during laser metal welding. By the use of two high-speed cameras and a data acquisition system we conclude how fast we have to image the process to measure the fluid dynamics with a very high certainty. Our experiments show that not all process features which can be measured during laser welding do represent the process behavior similarly well. Despite the good visibility of the vapor plume the monitoring of its movement is less suitable as an input signal for a closed-loop control. The features measured inside the keyhole show a good correlation with changes of process parameters. Due to its low noise, the area of the keyhole opening is well suited as an input signal for a closed-loop control of the process.

Novel Feature Modelling the Prediction and Detection of sEMG Muscle Fatigue towards an Automated Wearable System

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Mohamed R. Al-Mulla

2010-05-01

Full Text Available Surface Electromyography (sEMG activity of the biceps muscle was recorded from ten subjects performing isometric contraction until fatigue. A novel feature (1D spectro_std was used to extract the feature that modeled three classes of fatigue, which enabled the prediction and detection of fatigue. Initial results of class separation were encouraging, discriminating between the three classes of fatigue, a longitudinal classification on Non-Fatigue and Transition-to-Fatigue shows 81.58% correct classification with accuracy 0.74 of correct predictions while the longitudinal classification on Transition-to-Fatigue and Fatigue showed lower average correct classification of 66.51% with a positive classification accuracy 0.73 of correct prediction. Comparison of the 1D spectro_std with other sEMG fatigue features on the same dataset show a significant improvement in classification, where results show a significant 20.58% (p < 0.01 improvement when using the 1D spectro_std to classify Non-Fatigue and Transition-to-Fatigue. In classifying Transition-to-Fatigue and Fatigue results also show a significant improvement over the other features giving 8.14% (p < 0.05 on average of all compared features.

Erosive processes in Macau/Serra oil field, on the basis of coastal hydrodynamic and in the beaches profiles, Macau/RN, NE, Brazil; Processos erosivos no Campo Petrolifero de Macau/Serra, com base na hidrodinamica costeira e nos perfis praiais, Macau/RN, NE do Brasil

Energy Technology Data Exchange (ETDEWEB)

Chaves, Marcelo dos Santos [Rio Grande do Norte Univ., Natal, RN (Brazil). Programa de Pos-graduacao em Geodinamica e Geofisica]. E-mail: marceloschaves@bol.com.br; Vital, Helenice [Rio Grande do Norte Univ., Natal, RN (Brazil). Dept. de Geologia]|[Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq), Brasilia, DF (Brazil); Silveira, Iracema M. [Museu Camara Cascudo, Natal, RN (Brazil); Santos, Daniel A.S. [Rio Grande do Norte Univ., Natal, RN (Brazil). Dept. de Geologia

2003-07-01

In order to understand the causes of erosion before the construction of protective structures on erosional beaches of northeastern Brazil where the Macau/Serra oil field (Potiguar Basin) are installed, environmental studies based mainly on in situ measurements of hydrodynamic and beaches profiles data were undertaken as part of MARPETRO project (FINEP/CTPETRO/PETROBRAS). The data were collected monthly during a period of 24 months (October 2000 to September 2002), always in the spring tides. The beach profiles analysis show an intensive surface erosion rate, as observed by the decrease of the berm scarp in the profile 03, which retreat more than 17 meters in this period. Hydrodynamic data indicate a decrease in the period of erosion x deposition, as verified in the overlap of the topographic profiles. The results show that due to the high environmental sensibility of the area, which has a negative natural impacts while the human interference just accentuate the erosional processes. (author)

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

Science.gov (United States)

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

An expert botanical feature extraction technique based on phenetic features for identifying plant species.

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Hoshang Kolivand

Full Text Available In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost.

An expert botanical feature extraction technique based on phenetic features for identifying plant species

Science.gov (United States)

Fern, Bong Mei; Rahim, Mohd Shafry Mohd; Sulong, Ghazali; Baker, Thar; Tully, David

2018-01-01

In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost. PMID:29420568

Binding of intrinsic and extrinsic features in working memory.

Science.gov (United States)

Ecker, Ullrich K H; Maybery, Murray; Zimmer, Hubert D

2013-02-01

There is ongoing debate concerning the mechanisms of feature binding in working memory. In particular, there is controversy regarding the extent to which these binding processes are automatic. The present article demonstrates that binding mechanisms differ depending on whether the to-be-integrated features are perceived as forming a coherent object. We presented a series of experiments that investigated the binding of color and shape, whereby color was either an intrinsic feature of the shape or an extrinsic feature of the shape's background. Results show that intrinsic color affected shape recognition, even when it was incidentally studied and irrelevant for the recognition task. In contrast, extrinsic color did not affect shape recognition, even when the association of color and shape was encoded and retrievable on demand. This strongly suggests that binding of intrinsic intra-item information but not extrinsic contextual information is obligatory in visual working memory. We highlight links to perception as well as implicit and explicit long-term memory, which suggest that the intrinsic-extrinsic dimension is a principle relevant to multiple domains of human cognition. 2013 APA, all rights reserved

A feature-based approach to modeling protein-DNA interactions.

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Eilon Sharon

Full Text Available Transcription factor (TF binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position specific scoring matrix (PSSM, which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. Here, we present feature motif models (FMMs, a novel probabilistic method for modeling TF-DNA interactions, based on log-linear models. Our approach uses sequence features to represent TF binding specificities, where each feature may span multiple positions. We develop the mathematical formulation of our model and devise an algorithm for learning its structural features from binding site data. We also developed a discriminative motif finder, which discovers de novo FMMs that are enriched in target sets of sequences compared to background sets. We evaluate our approach on synthetic data and on the widely used TF chromatin immunoprecipitation (ChIP dataset of Harbison et al. We then apply our algorithm to high-throughput TF ChIP data from mouse and human, reveal sequence features that are present in the binding specificities of mouse and human TFs, and show that FMMs explain TF binding significantly better than PSSMs. Our FMM learning and motif finder software are available at http://genie.weizmann.ac.il/.

Prediction of protein modification sites of pyrrolidone carboxylic acid using mRMR feature selection and analysis.

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Lu-Lu Zheng

Full Text Available Pyrrolidone carboxylic acid (PCA is formed during a common post-translational modification (PTM of extracellular and multi-pass membrane proteins. In this study, we developed a new predictor to predict the modification sites of PCA based on maximum relevance minimum redundancy (mRMR and incremental feature selection (IFS. We incorporated 727 features that belonged to 7 kinds of protein properties to predict the modification sites, including sequence conservation, residual disorder, amino acid factor, secondary structure and solvent accessibility, gain/loss of amino acid during evolution, propensity of amino acid to be conserved at protein-protein interface and protein surface, and deviation of side chain carbon atom number. Among these 727 features, 244 features were selected by mRMR and IFS as the optimized features for the prediction, with which the prediction model achieved a maximum of MCC of 0.7812. Feature analysis showed that all feature types contributed to the modification process. Further site-specific feature analysis showed that the features derived from PCA's surrounding sites contributed more to the determination of PCA sites than other sites. The detailed feature analysis in this paper might provide important clues for understanding the mechanism of the PCA formation and guide relevant experimental validations.

Evaluating the Stability of Feature Selectors that Optimize Feature Subset Cardinality

Czech Academy of Sciences Publication Activity Database

Somol, Petr; Novovičová, Jana

2008-01-01

Roč. 2008, č. 5342 (2008), s. 956-966 ISSN 0302-9743. [Joint IAPR International Workshops SSPR 2008 and SPR 2008. Orlando , 04.12.2008-06.12.2008] R&D Projects: GA AV ČR 1ET400750407; GA MŠk 1M0572; GA ČR GA102/07/1594 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Feature selection * stability * relative weighted consistency measure * sequential search * floating search Subject RIV: IN - Informatics, Computer Science http://library.utia.cas.cz/separaty/2008/RO/somol-evaluating the stability of feature selectors that optimize feature subset cardinality.pdf

Infrared face recognition based on LBP histogram and KW feature selection

Science.gov (United States)

Xie, Zhihua

2014-07-01

The conventional LBP-based feature as represented by the local binary pattern (LBP) histogram still has room for performance improvements. This paper focuses on the dimension reduction of LBP micro-patterns and proposes an improved infrared face recognition method based on LBP histogram representation. To extract the local robust features in infrared face images, LBP is chosen to get the composition of micro-patterns of sub-blocks. Based on statistical test theory, Kruskal-Wallis (KW) feature selection method is proposed to get the LBP patterns which are suitable for infrared face recognition. The experimental results show combination of LBP and KW features selection improves the performance of infrared face recognition, the proposed method outperforms the traditional methods based on LBP histogram, discrete cosine transform(DCT) or principal component analysis(PCA).

Leaf traits show different relationships with shade tolerance in moist versus dry tropical forests

NARCIS (Netherlands)

Poorter, L.

2009-01-01

¿ Shade tolerance is the central paradigm for understanding forest succession and dynamics, but there is considerable debate as to what the salient features of shade tolerance are, whether adult leaves show similar shade adaptations to seedling leaves, and whether the same leaf adaptations are found

Robust Image Hashing Using Radon Transform and Invariant Features

Directory of Open Access Journals (Sweden)

Y.L. Liu

2016-09-01

Full Text Available A robust image hashing method based on radon transform and invariant features is proposed for image authentication, image retrieval, and image detection. Specifically, an input image is firstly converted into a counterpart with a normalized size. Then the invariant centroid algorithm is applied to obtain the invariant feature point and the surrounding circular area, and the radon transform is employed to acquire the mapping coefficient matrix of the area. Finally, the hashing sequence is generated by combining the feature vectors and the invariant moments calculated from the coefficient matrix. Experimental results show that this method not only can resist against the normal image processing operations, but also some geometric distortions. Comparisons of receiver operating characteristic (ROC curve indicate that the proposed method outperforms some existing methods in classification between perceptual robustness and discrimination.

Adaptive Colour Feature Identification in Image for Object Tracking

Directory of Open Access Journals (Sweden)

Feng Su

2012-01-01

Full Text Available Identification and tracking of a moving object using computer vision techniques is important in robotic surveillance. In this paper, an adaptive colour filtering method is introduced for identifying and tracking a moving object appearing in image sequences. This filter is capable of automatically identifying the most salient colour feature of the moving object in the image and using this for a robot to track the object. The method enables the selected colour feature to adapt to surrounding condition when it is changed. A method of determining the region of interest of the moving target is also developed for the adaptive colour filter to extract colour information. Experimental results show that by using a camera mounted on a robot, the proposed methods can perform robustly in tracking a randomly moving object using adaptively selected colour features in a crowded environment.

Estimating Human Physical States from Chronological Gait Features Acquired with RFID Technology

Directory of Open Access Journals (Sweden)

Yoshihiro UEMURA

2015-11-01

Full Text Available This paper proposes a method to estimate the state of the user to provide proactive hospitality from features of their gait pattern acquired with a Radio Frequency Identifier (RFID system. This method uses RFID readers on each shoe, as well as RFID tags installed on the floor. The ID of each tag is organized as a map, to show the precise position of the user. The reader and tags communicate while the user is walking. We extract feature components which represents gait patterns. Two-way ANOVA test and correlation analysis are conducted to find significant features. We classify the state of the user from these components with the Naȉve Bayes, the Support Vector Machine, and the Random Forest. Compared with each combination of the analysis and the machine learning method, the most efficient way is found to identify the state of the user. The experimental results show that different state of users can be classified appropriately. Finally, variable importance and the feasibility of proposed method are discussed to show potential implications of the proposed approach.

RESEARCH ON FEATURE POINTS EXTRACTION METHOD FOR BINARY MULTISCALE AND ROTATION INVARIANT LOCAL FEATURE DESCRIPTOR

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Hongwei Ying

2014-08-01

Full Text Available An extreme point of scale space extraction method for binary multiscale and rotation invariant local feature descriptor is studied in this paper in order to obtain a robust and fast method for local image feature descriptor. Classic local feature description algorithms often select neighborhood information of feature points which are extremes of image scale space, obtained by constructing the image pyramid using certain signal transform method. But build the image pyramid always consumes a large amount of computing and storage resources, is not conducive to the actual applications development. This paper presents a dual multiscale FAST algorithm, it does not need to build the image pyramid, but can extract feature points of scale extreme quickly. Feature points extracted by proposed method have the characteristic of multiscale and rotation Invariant and are fit to construct the local feature descriptor.

Structural features that predict real-value fluctuations of globular proteins.

Science.gov (United States)

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2012-05-01

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics (MD) trajectories of nonhomologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real value of residue fluctuations using the support vector regression (SVR). It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in MD trajectories. Moreover, SVR that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson's correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed in predictions by the Gaussian network model (GNM). An advantage of the developed method over the GNMs is that the former predicts the real value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. Copyright © 2012 Wiley Periodicals, Inc.

Analysis of iris surface features in populations of diverse ancestry

Science.gov (United States)

Edwards, Melissa; Cha, David; Krithika, S.; Johnson, Monique; Parra, Esteban J.

2016-01-01

There are many textural elements that can be found in the human eye, including Fuchs’ crypts, Wolfflin nodules, pigment spots, contraction furrows and conjunctival melanosis. Although iris surface features have been well-studied in populations of European ancestry, the worldwide distribution of these traits is poorly understood. In this paper, we develop a new method of characterizing iris features from photographs of the iris. We then apply this method to a diverse sample of East Asian, European and South Asian ancestry. All five iris features showed significant differences in frequency between the three populations, indicating that iris features are largely population dependent. Although none of the features were correlated with each other in the East and South Asian groups, Fuchs’ crypts were significantly correlated with contraction furrows and pigment spots and contraction furrows were significantly associated with pigment spots in the European group. The genetic marker SEMA3A rs10235789 was significantly associated with Fuchs’ crypt grade in the European, East Asian and South Asian samples and a borderline association between TRAF3IP1 rs3739070 and contraction furrow grade was found in the European sample. The study of iris surface features in diverse populations may provide valuable information of forensic, biomedical and ophthalmological interest. PMID:26909168

Feature-based attention in early vision for the modulation of figure–ground segregation

Directory of Open Access Journals (Sweden)

Nobuhiko eWagatsuma

2013-03-01

Full Text Available We investigated psychophysically whether feature-based attention modulates the perception of figure–ground (F–G segregation and, based on the results, we investigated computationally the neural mechanisms underlying attention modulation. In the psychophysical experiments, the attention of participants was drawn to a specific motion direction and they were then asked to judge the side of figure in an ambiguous figure with surfaces consisting of distinct motion directions. The results of these experiments showed that the surface consisting of the attended direction of motion was more frequently observed as figure, with a degree comparable to that of spatial attention (Wagatsuma, Shimizu, and Sakai, 2008. These experiments also showed that perception was dependent on the distribution of feature contrast, specifically the motion direction differences. These results led us to hypothesize that feature-based attention functions in a framework similar to that of spatial attention. We proposed a V1–V2 model in which feature-based attention modulates the contrast of low-level feature in V1, and this modulation of contrast changes directly the surround modulation of border-ownership-selective cells in V2; thus, perception of F–G is biased. The model exhibited good agreement with human perception in the magnitude of attention modulation and its invariance among stimuli. These results indicate that early-level features that are modified by feature-based attention alter subsequent processing along afferent pathway, and that such modification could even change the perception of object.

Feature-Based Attention in Early Vision for the Modulation of Figure–Ground Segregation

Science.gov (United States)

Wagatsuma, Nobuhiko; Oki, Megumi; Sakai, Ko

2013-01-01

We investigated psychophysically whether feature-based attention modulates the perception of figure–ground (F–G) segregation and, based on the results, we investigated computationally the neural mechanisms underlying attention modulation. In the psychophysical experiments, the attention of participants was drawn to a specific motion direction and they were then asked to judge the side of figure in an ambiguous figure with surfaces consisting of distinct motion directions. The results of these experiments showed that the surface consisting of the attended direction of motion was more frequently observed as figure, with a degree comparable to that of spatial attention (Wagatsuma et al., 2008). These experiments also showed that perception was dependent on the distribution of feature contrast, specifically the motion direction differences. These results led us to hypothesize that feature-based attention functions in a framework similar to that of spatial attention. We proposed a V1–V2 model in which feature-based attention modulates the contrast of low-level feature in V1, and this modulation of contrast changes directly the surround modulation of border-ownership-selective cells in V2; thus, perception of F–G is biased. The model exhibited good agreement with human perception in the magnitude of attention modulation and its invariance among stimuli. These results indicate that early-level features that are modified by feature-based attention alter subsequent processing along afferent pathway, and that such modification could even change the perception of object. PMID:23515841

Feature-based attention in early vision for the modulation of figure-ground segregation.

Science.gov (United States)

Wagatsuma, Nobuhiko; Oki, Megumi; Sakai, Ko

2013-01-01

We investigated psychophysically whether feature-based attention modulates the perception of figure-ground (F-G) segregation and, based on the results, we investigated computationally the neural mechanisms underlying attention modulation. In the psychophysical experiments, the attention of participants was drawn to a specific motion direction and they were then asked to judge the side of figure in an ambiguous figure with surfaces consisting of distinct motion directions. The results of these experiments showed that the surface consisting of the attended direction of motion was more frequently observed as figure, with a degree comparable to that of spatial attention (Wagatsuma et al., 2008). These experiments also showed that perception was dependent on the distribution of feature contrast, specifically the motion direction differences. These results led us to hypothesize that feature-based attention functions in a framework similar to that of spatial attention. We proposed a V1-V2 model in which feature-based attention modulates the contrast of low-level feature in V1, and this modulation of contrast changes directly the surround modulation of border-ownership-selective cells in V2; thus, perception of F-G is biased. The model exhibited good agreement with human perception in the magnitude of attention modulation and its invariance among stimuli. These results indicate that early-level features that are modified by feature-based attention alter subsequent processing along afferent pathway, and that such modification could even change the perception of object.

A DYNAMIC FEATURE SELECTION METHOD FOR DOCUMENT RANKING WITH RELEVANCE FEEDBACK APPROACH

Directory of Open Access Journals (Sweden)

K. Latha

2010-07-01

Full Text Available Ranking search results is essential for information retrieval and Web search. Search engines need to not only return highly relevant results, but also be fast to satisfy users. As a result, not all available features can be used for ranking, and in fact only a small percentage of these features can be used. Thus, it is crucial to have a feature selection mechanism that can find a subset of features that both meets latency requirements and achieves high relevance. In this paper we describe a 0/1 knapsack procedure for automatically selecting features to use within Generalization model for Document Ranking. We propose an approach for Relevance Feedback using Expectation Maximization method and evaluate the algorithm on the TREC Collection for describing classes of feedback textual information retrieval features. Experimental results, evaluated on standard TREC-9 part of the OHSUMED collections, show that our feature selection algorithm produces models that are either significantly more effective than, or equally effective as, models such as Markov Random Field model, Correlation Co-efficient and Count Difference method

Mid-Infrared Emission Features in the ISM: Feature-to-Features Flux Ratios

Science.gov (United States)

Lu, N. Y.

1998-01-01

Using a limited, but representative sample of sources in the ISM of our Galaxy with published spectra from the Infrared Space Observatory, we analyze flux ratios between the major mid-IR emission features (EFs) centered around 6.2, 7.7, 8.6 and 11.3 mu, respectively.

FEATUREOUS: AN INTEGRATED ENVIRONMENT FOR FEATURE-CENTRIC ANALYSIS AND MODIFICATION OF OBJECT-ORIENTED SOFTWARE

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2011-01-01

The decentralized nature of collaborations between objects in object-oriented software makes it difficult to understand the implementations of user-observable program features and their respective interdependencies. As feature-centric program understanding and modification are essential during...... software maintenance and evolution, this situation needs to change. In this paper, we present Featureous, an integrated development environment built on top of the NetBeans IDE that facilitates feature-centric analysis of object-oriented software. Our integrated development environment encompasses...... a lightweight feature location mechanism, a number of reusable analytical views, and necessary APIs for supporting future extensions. The base of the integrated development environment is a conceptual framework comprising of three complementary dimensions of comprehension: perspective, abstraction...

Radiographic features of paediatric pneumocystis pneumonia - a historical perspective

International Nuclear Information System (INIS)

Pitcher, R.D.; Zar, H.J.

2008-01-01

Aim: To determine differences between the plain radiographic features of paediatric pneumocystis pneumonia (PCP) recorded before the emergence of human immunodeficiency virus (HIV) in 1982 and those documented in the HIV era. To establish differences in the radiographic features of PCP documented in HIV-infected children in developed and developing countries. Method: A Medline search of articles was conducted from 1950 to 2006, using the terms 'pneumocystis pneumonia in children' and 'chest radiographic features' or 'bilateral opacification' or 'lobar consolidation' or 'asymmetrical opacification' or 'pneumatocoeles' or 'cavities' or 'pneumothorax' or 'pneumomediastinum' or 'pleural effusion' or 'mediastinal adenopathy' or 'nodules' or 'normal chest radiography'. Appropriate articles were retrieved, radiological data extracted, reference lists examined and hand searches of referenced articles conducted. Results: Diffuse bilateral 'ground-glass' or alveolar pulmonary opacification, which may show some asymmetry, has been consistently documented as the commonest radiographic finding in childhood PCP throughout the period under review. The less common radiological features of PCP in children are similar to those in adults. In developed countries, PCP-related pulmonary air cysts have been reported at an earlier age in HIV-infected children, compared with uninfected children. PCP-related air cysts, pneumothorax, and pneumomediastinum have been reported in children in developed but not in developing countries. Conclusion: The radiological features of paediatric PCP documented before the HIV epidemic are similar to those recorded in the HIV era. Further study of the determinants of the uncommon radiographic features in children is warranted

EVENT-MARKETING – FEATURES OF APPLICATION IN MODERN TOURISM

Directory of Open Access Journals (Sweden)

Oksana Vlasenko

2016-03-01

Full Text Available In the article analyzed the modern features of the development and using of event- marketing. Showed the conditions of the essence and characteristics of event management, its principles and methods of application. Characterized the features and importance of tourism and the benefits of application of event marketing as a promising method of indirect marketing communications. Used examples of practical application of event marketing activity. Determined correlation of event management and marketing and its subordination to the event marketing purposes. Key words: tourism, event-tourism, event-management, event-marketing, socio-cultural sphere. JEL: M 31

Feature Screening for Ultrahigh Dimensional Categorical Data with Applications.

Science.gov (United States)

Huang, Danyang; Li, Runze; Wang, Hansheng

2014-01-01

Ultrahigh dimensional data with both categorical responses and categorical covariates are frequently encountered in the analysis of big data, for which feature screening has become an indispensable statistical tool. We propose a Pearson chi-square based feature screening procedure for categorical response with ultrahigh dimensional categorical covariates. The proposed procedure can be directly applied for detection of important interaction effects. We further show that the proposed procedure possesses screening consistency property in the terminology of Fan and Lv (2008). We investigate the finite sample performance of the proposed procedure by Monte Carlo simulation studies, and illustrate the proposed method by two empirical datasets.

HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features.

Science.gov (United States)

Zaman, Rianon; Chowdhury, Shahana Yasmin; Rashid, Mahmood A; Sharma, Alok; Dehzangi, Abdollah; Shatabda, Swakkhar

2017-01-01

DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM) as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.

HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features

Directory of Open Access Journals (Sweden)

Rianon Zaman

2017-01-01

Full Text Available DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.

Mass photosynthesis and distribution of photo assimilates of winter wheat varieties with different maturity feature

International Nuclear Information System (INIS)

Wang Fahong; Zhao Junshi

1996-01-01

The mass photosynthesis rate and distribution of photoassimilates of winter wheat varieties with different maturity feature were studied using GXH-305 portable CO 2 infrared ray analyzer. The mass photosynthesis rate of winter wheat varieties with better maturity feature showed little difference from the varieties with general maturity feature during the early stage of grain filling phase. However, the mass photosynthesis rate of the former was significantly higher than that of the later during the middle and late stage of grain filling. The study with 14 CO 2 -tracing method showed that the relative activity in different organs of varieties with better maturity feature was significantly higher than that of varieties with worse maturity feature during the later growth stage of winter wheat. The rate of photoassimilates distribution in stalk and root system of winter wheat varieties with better maturity was higher than that in the others organs. The physiological mechanism of difference of grain yield and plant decay in varieties with different maturity feature were also discussed

Clustering-based Feature Learning on Variable Stars

Science.gov (United States)

Mackenzie, Cristóbal; Pichara, Karim; Protopapas, Pavlos

2016-04-01

The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline.

CLUSTERING-BASED FEATURE LEARNING ON VARIABLE STARS

International Nuclear Information System (INIS)

Mackenzie, Cristóbal; Pichara, Karim; Protopapas, Pavlos

2016-01-01

The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline

CLUSTERING-BASED FEATURE LEARNING ON VARIABLE STARS

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