WorldWideScience

Sample records for valley segment model

  1. Single-Molecule FISH Reveals Non-selective Packaging of Rift Valley Fever Virus Genome Segments.

    Directory of Open Access Journals (Sweden)

    Paul J Wichgers Schreur

    2016-08-01

    Full Text Available The bunyavirus genome comprises a small (S, medium (M, and large (L RNA segment of negative polarity. Although genome segmentation confers evolutionary advantages by enabling genome reassortment events with related viruses, genome segmentation also complicates genome replication and packaging. Accumulating evidence suggests that genomes of viruses with eight or more genome segments are incorporated into virions by highly selective processes. Remarkably, little is known about the genome packaging process of the tri-segmented bunyaviruses. Here, we evaluated, by single-molecule RNA fluorescence in situ hybridization (FISH, the intracellular spatio-temporal distribution and replication kinetics of the Rift Valley fever virus (RVFV genome and determined the segment composition of mature virions. The results reveal that the RVFV genome segments start to replicate near the site of infection before spreading and replicating throughout the cytoplasm followed by translocation to the virion assembly site at the Golgi network. Despite the average intracellular S, M and L genome segments approached a 1:1:1 ratio, major differences in genome segment ratios were observed among cells. We also observed a significant amount of cells lacking evidence of M-segment replication. Analysis of two-segmented replicons and four-segmented viruses subsequently confirmed the previous notion that Golgi recruitment is mediated by the Gn glycoprotein. The absence of colocalization of the different segments in the cytoplasm and the successful rescue of a tri-segmented variant with a codon shuffled M-segment suggested that inter-segment interactions are unlikely to drive the copackaging of the different segments into a single virion. The latter was confirmed by direct visualization of RNPs inside mature virions which showed that the majority of virions lack one or more genome segments. Altogether, this study suggests that RVFV genome packaging is a non-selective process.

  2. 3D GIS FOR FLOOD MODELLING IN RIVER VALLEYS

    Directory of Open Access Journals (Sweden)

    P. Tymkow

    2016-06-01

    Full Text Available The objective of this study is implementation of system architecture for collecting and analysing data as well as visualizing results for hydrodynamic modelling of flood flows in river valleys using remote sensing methods, tree-dimensional geometry of spatial objects and GPU multithread processing. The proposed solution includes: spatial data acquisition segment, data processing and transformation, mathematical modelling of flow phenomena and results visualization. Data acquisition segment was based on aerial laser scanning supplemented by images in visible range. Vector data creation was based on automatic and semiautomatic algorithms of DTM and 3D spatial features modelling. Algorithms for buildings and vegetation geometry modelling were proposed or adopted from literature. The implementation of the framework was designed as modular software using open specifications and partially reusing open source projects. The database structure for gathering and sharing vector data, including flood modelling results, was created using PostgreSQL. For the internal structure of feature classes of spatial objects in a database, the CityGML standard was used. For the hydrodynamic modelling the solutions of Navier-Stokes equations in two-dimensional version was implemented. Visualization of geospatial data and flow model results was transferred to the client side application. This gave the independence from server hardware platform. A real-world case in Poland, which is a part of Widawa River valley near Wroclaw city, was selected to demonstrate the applicability of proposed system.

  3. Four-segmented Rift Valley fever virus-based vaccines can be applied safely in ewes during pregnancy

    NARCIS (Netherlands)

    Wichgers Schreur, Paul J.; Keulen, van Lucien; Kant-Eenbergen, Jet; Kortekaas, Jeroen

    2017-01-01

    Rift Valley fever virus (RVFV) causes severe and recurrent outbreaks on the African continent and the Arabian Peninsula and continues to expand its habitat. This mosquito-borne virus, belonging to the genus Phlebovirus of the family Bunyaviridae contains a tri-segmented negative-strand RNA

  4. Hydrological Modelling the Middle Magdalena Valley (Colombia)

    Science.gov (United States)

    Arenas, M. C.; Duque, N.; Arboleda, P.; Guadagnini, A.; Riva, M.; Donado-Garzon, L. D.

    2017-12-01

    Hydrological distributed modeling is key point for a comprehensive assessment of the feedback between the dynamics of the hydrological cycle, climate conditions and land use. Such modeling results are markedly relevant in the fields of water resources management, natural hazards and oil and gas industry. Here, we employ TopModel (TOPography based hydrological MODEL) for the hydrological modeling of an area in the Middle Magdalena Valley (MMV), a tropical basin located in Colombia. This study is located over the intertropical convergence zone and is characterized by special meteorological conditions, with fast water fluxes over the year. It has been subject to significant land use changes, as a result of intense economical activities, i.e., and agriculture, energy and oil & gas production. The model employees a record of 12 years of daily precipitation and evapotranspiration data as inputs. Streamflow data monitored across the same time frame are used for model calibration. The latter is performed by considering data from 2000 to 2008. Model validation then relies on observations from 2009 to 2012. The robustness of our analyses is based on the Nash-Sutcliffe coefficient (values of this metric being 0.62 and 0.53, respectively for model calibration and validation). Our results reveal high water storage capacity in the soil, and a marked subsurface runoff, consistent with the characteristics of the soil types in the regions. A significant influence on runoff response of the basin to topographical factors represented in the model is evidenced. Our calibrated model provides relevant indications about recharge in the region, which is important to quantify the interaction between surface water and groundwater, specially during the dry season, which is more relevant in climate-change and climate-variability scenarios.

  5. Multi-scale Modelling of Segmentation

    DEFF Research Database (Denmark)

    Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri

    2016-01-01

    pieces. In a second experiment on non-real-time segmentation, musicians indicated boundaries and their strength for six examples. Kernel density estimation was used to develop multi-scale segmentation models. Contrary to previous research, no relationship was found between boundary strength and boundary......While listening to music, people often unwittingly break down musical pieces into constituent chunks such as verses and choruses. Music segmentation studies have suggested that some consensus regarding boundary perception exists, despite individual differences. However, neither the effects...

  6. Single-Molecule FISH Reveals Non-selective Packaging of Rift Valley Fever Virus Genome Segments

    NARCIS (Netherlands)

    Wichgers Schreur, Paul J.; Kortekaas, Jeroen

    2016-01-01

    The bunyavirus genome comprises a small (S), medium (M), and large (L) RNA segment of negative polarity. Although genome segmentation confers evolutionary advantages by enabling genome reassortment events with related viruses, genome segmentation also complicates genome replication and packaging.

  7. Air quality modeling in the Valley of Mexico: meteorology, emissions and forecasting

    Science.gov (United States)

    Garcia-Reynoso, A.; Jazcilevich, A. D.; Diaz-Nigenda, E.; Vazquez-Morales, W.; Torres-Jardon, R.; Ruiz-Suarez, G.; Tatarko, J.; Bornstein, R.

    2007-12-01

    The Valley of Mexico presents important challenges for air quality modeling: complex terrain, a great variety of anthropogenic and natural emissions sources, and high altitude and low latitude increasing the amount of radiation flux. The modeling group at the CCA-UNAM is using and merging state of the art models to study the different aspects that influence the air quality phenomenon in the Valley of Mexico. The air quality model MCCM that uses MM5 as its meteorological input has been a valuable tool to study important features of the complex and intricate atmospheric flows on the valley, such as local confluences and vertical fumigation. Air quality modeling has allowed studying the interaction between the atmospheres of the valleys surrounding the Valley of Mexico, prompting the location of measurement stations during the MILAGRO campaign. These measurements confirmed the modeling results and expanded our knowledge of the transport of pollutants between the Valleys of Cuernavaca, Puebla and Mexico. The urban landscape of Mexico City complicates meteorological modeling. Urban-MM5, a model that explicitly takes into account the influence of buildings, houses, streets, parks and anthropogenic heat, is being implemented. Preliminary results of urban-MM5 on a small area of the city have been obtained. The current emissions inventory uses traffic database that includes hourly vehicular activity in more than 11,000 street segments, includes 23 area emissions categories, more than 1,000 industrial sources and biogenic emissions. To improve mobile sources emissions a system consisting of a traffic model and a car simulator is underway. This system will allow for high time and space resolution and takes into account motor stress due to different driving regimes. An important source of emissions in the Valley of Mexico is erosion dust. The erosion model WEPS has been integrated with MM5 and preliminary results showing dust episodes over Mexico City have been obtained. A

  8. Eco-Hydrological Modelling of Stream Valleys

    DEFF Research Database (Denmark)

    Johansen, Ole

    a flow reduction in the order of 20 % in a natural spring, whereas no effect could be measured in neither short nor deep piezometers in the river valley 50 m from the spring. Problems of measuring effects of pumping are partly caused by disturbances from natural water level fluctuations. In this aspect...

  9. Charcterization of meadow ecosystems based on watershed and valley segment/reach scale characteristics [chapter 7

    Science.gov (United States)

    Wendy Trowbridge; Jeanne C. Chambers; Dru Germanoski; Mark L. Lord; Jerry R. Miller; David G. Jewett

    2011-01-01

    Great Basin riparian meadows are highly sensitive to both natural and anthropogenic disturbance. As detailed in earlier chapters, streams in the central Great Basin have a natural tendency to incise due to their geomorphic history (Miller and others 2001, 2004). Anthropogenic disturbances, including overgrazing by livestock, mining activities, and roads in the valley...

  10. Market Segmentation Using Bayesian Model Based Clustering

    NARCIS (Netherlands)

    Van Hattum, P.

    2009-01-01

    This dissertation deals with two basic problems in marketing, that are market segmentation, which is the grouping of persons who share common aspects, and market targeting, which is focusing your marketing efforts on one or more attractive market segments. For the grouping of persons who share

  11. Modeling of market segmentation for new IT product development

    Science.gov (United States)

    Nasiopoulos, Dimitrios K.; Sakas, Damianos P.; Vlachos, D. S.; Mavrogianni, Amanda

    2015-02-01

    Businesses from all Information Technology sectors use market segmentation[1] in their product development[2] and strategic planning[3]. Many studies have concluded that market segmentation is considered as the norm of modern marketing. With the rapid development of technology, customer needs are becoming increasingly diverse. These needs can no longer be satisfied by a mass marketing approach and follow one rule. IT Businesses can face with this diversity by pooling customers[4] with similar requirements and buying behavior and strength into segments. The result of the best choices about which segments are the most appropriate to serve can then be made, thus making the best of finite resources. Despite the attention which segmentation gathers and the resources that are invested in it, growing evidence suggests that businesses have problems operationalizing segmentation[5]. These problems take various forms. There may have been a rule that the segmentation process necessarily results in homogeneous groups of customers for whom appropriate marketing programs and procedures for dealing with them can be developed. Then the segmentation process, that a company follows, can fail. This increases concerns about what causes segmentation failure and how it might be overcome. To prevent the failure, we created a dynamic simulation model of market segmentation[6] based on the basic factors leading to this segmentation.

  12. Model-based segmentation and classification of trajectories (Extended abstract)

    NARCIS (Netherlands)

    Alewijnse, S.P.A.; Buchin, K.; Buchin, M.; Sijben, S.; Westenberg, M.A.

    2014-01-01

    We present efficient algorithms for segmenting and classifying a trajectory based on a parameterized movement model like the Brownian bridge movement model. Segmentation is the problem of subdividing a trajectory into parts such that each art is homogeneous in its movement characteristics. We

  13. Fast Appearance Modeling for Automatic Primary Video Object Segmentation.

    Science.gov (United States)

    Yang, Jiong; Price, Brian; Shen, Xiaohui; Lin, Zhe; Yuan, Junsong

    2016-02-01

    Automatic segmentation of the primary object in a video clip is a challenging problem as there is no prior knowledge of the primary object. Most existing techniques thus adapt an iterative approach for foreground and background appearance modeling, i.e., fix the appearance model while optimizing the segmentation and fix the segmentation while optimizing the appearance model. However, these approaches may rely on good initialization and can be easily trapped in local optimal. In addition, they are usually time consuming for analyzing videos. To address these limitations, we propose a novel and efficient appearance modeling technique for automatic primary video object segmentation in the Markov random field (MRF) framework. It embeds the appearance constraint as auxiliary nodes and edges in the MRF structure, and can optimize both the segmentation and appearance model parameters simultaneously in one graph cut. The extensive experimental evaluations validate the superiority of the proposed approach over the state-of-the-art methods, in both efficiency and effectiveness.

  14. Coupled Shape Model Segmentation in Pig Carcasses

    DEFF Research Database (Denmark)

    Hansen, Mads Fogtmann; Larsen, Rasmus; Ersbøll, Bjarne Kjær

    2006-01-01

    levels inside the outline as well as in a narrow band outside the outline. The maximum a posteriori estimate of the outline is found by gradient descent optimization. In order to segment a group of mutually dependent objects we propose 2 procedures, 1) the objects are found sequentially by conditioning...... the initialization of the next search from already found objects; 2) all objects are found simultaneously and a repelling force is introduced in order to avoid overlap between outlines in the solution. The methods are applied to segmentation of cross sections of muscles in slices of CT scans of pig backs for quality...

  15. An Epidemiological Model of Rift Valley Fever with Spatial Dynamics

    Directory of Open Access Journals (Sweden)

    Tianchan Niu

    2012-01-01

    Full Text Available As a category A agent in the Center for Disease Control bioterrorism list, Rift Valley fever (RVF is considered a major threat to the United States (USA. Should the pathogen be intentionally or unintentionally introduced to the continental USA, there is tremendous potential for economic damages due to loss of livestock, trade restrictions, and subsequent food supply chain disruptions. We have incorporated the effects of space into a mathematical model of RVF in order to study the dynamics of the pathogen spread as affected by the movement of humans, livestock, and mosquitoes. The model accounts for the horizontal transmission of Rift Valley fever virus (RVFV between two mosquito and one livestock species, and mother-to-offspring transmission of virus in one of the mosquito species. Space effects are introduced by dividing geographic space into smaller patches and considering the patch-to-patch movement of species. For each patch, a system of ordinary differential equations models fractions of populations susceptible to, incubating, infectious with, or immune to RVFV. The main contribution of this work is a methodology for analyzing the likelihood of pathogen establishment should an introduction occur into an area devoid of RVF. Examples are provided for general and specific cases to illustrate the methodology.

  16. The ASAC Flight Segment and Network Cost Models

    Science.gov (United States)

    Kaplan, Bruce J.; Lee, David A.; Retina, Nusrat; Wingrove, Earl R., III; Malone, Brett; Hall, Stephen G.; Houser, Scott A.

    1997-01-01

    To assist NASA in identifying research art, with the greatest potential for improving the air transportation system, two models were developed as part of its Aviation System Analysis Capability (ASAC). The ASAC Flight Segment Cost Model (FSCM) is used to predict aircraft trajectories, resource consumption, and variable operating costs for one or more flight segments. The Network Cost Model can either summarize the costs for a network of flight segments processed by the FSCM or can be used to independently estimate the variable operating costs of flying a fleet of equipment given the number of departures and average flight stage lengths.

  17. Device-Level Models Using Multi-Valley Effective Mass

    Science.gov (United States)

    Baczewski, Andrew D.; Frees, Adam; Gamble, John King; Gao, Xujiao; Jacobson, N. Tobias; Mitchell, John A.; Montaño, Inès; Muller, Richard P.; Nielsen, Erik

    2015-03-01

    Continued progress in quantum electronics depends critically on the availability of robust device-level modeling tools that capture a wide range of physics and effective mass theory (EMT) is one means of building such models. Recent developments in multi-valley EMT show quantitative agreement with more detailed atomistic tight-binding calculations of phosphorus donors in silicon (Gamble, et. al., arXiv:1408.3159). Leveraging existing PDE solvers, we are developing a framework in which this multi-valley EMT is coupled to an integrated device-level description of several experimentally active qubit technologies. Device-level simulations of quantum operations will be discussed, as well as the extraction of process matrices at this level of theory. The authors gratefully acknowledge support from the Sandia National Laboratories Truman Fellowship Program, which is funded by the Laboratory Directed Research and Development (LDRD) Program. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Security Administration under contract DE-AC04-94AL85000.

  18. Conceptual model of volcanism and volcanic hazards of the region of Ararat valley, Armenia

    Science.gov (United States)

    Meliksetian, Khachatur; Connor, Charles; Savov, Ivan; Connor, Laura; Navasardyan, Gevorg; Manucharyan, Davit; Ghukasyan, Yura; Gevorgyan, Hripsime

    2015-04-01

    Armenia and the adjacent volcanically active regions in Iran, Turkey and Georgia are located in the collision zone between the Arabian and Eurasian lithospheric plates. The majority of studies of regional collision related volcanism use the model proposed by Keskin, (2003) where volcanism is driven by Neo-Tethyan slab break-off. In Armenia, >500 Quaternary-Holocene volcanoes from the Gegham, Vardenis and Syunik volcanic fields are hosted within pull-apart structures formed by active faults and their segments (Karakhanyan et al., 2002), while tectonic position of the large in volume basalt-dacite Aragats volcano and periphery volcanic plateaus is different and its position away from major fault lines necessitates more complex volcano-tectonic setup. Our detailed volcanological, petrological and geochemical studies provide insight into the nature of such volcanic activity in the region of Ararat Valley. Most magmas, such as those erupted in Armenia are volatile-poor and erupt fairly hot. Here we report newly discovered tephra sequences in Ararat valley, that were erupted from historically active Ararat stratovolcano and provide evidence for explosive eruption of young, mid K2O calc-alkaline and volatile-rich (>4.6 wt% H2O; amph-bearing) magmas. Such young eruptions, in addition to the ignimbrite and lava flow hazards from Gegham and Aragats, present a threat to the >1.4 million people (~ ½ of the population of Armenia). We will report numerical simulations of potential volcanic hazards for the region of Ararat valley near Yerevan that will include including tephra fallout, lava flows and opening of new vents. Connor et al. (2012) J. Applied Volcanology 1:3, 1-19; Karakhanian et al. (2002), JVGR, 113, 319-344; Keskin, M. (2003) Geophys. Res. Lett. 30, 24, 8046.

  19. Optimal Goodwill Model with Consumer Recommendations and Market Segmentation

    OpenAIRE

    Bogusz, Dominika; Górajski, Mariusz

    2014-01-01

    We propose a new dynamic model of product goodwill where a product is sold in many market segments, and where the segments are indicated by the usage experience of consumers. The dynamics of product goodwill is described by a partial differential equation of the Lotka–Sharpe– McKendrick type. The main novelty of this model is that the product goodwill in a segment of new consumers depends not only on advertising effort, but also on consumer recommendations, for which we introduce a mathematic...

  20. A new level set model for cell image segmentation

    Science.gov (United States)

    Ma, Jing-Feng; Hou, Kai; Bao, Shang-Lian; Chen, Chun

    2011-02-01

    In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing.

  1. Attenuation of pathogenic Rift Valley fever virus strain through the chimeric S-segment encoding sandfly fever phlebovirus NSs or a dominant-negative PKR.

    Science.gov (United States)

    Nishiyama, Shoko; Slack, Olga A L; Lokugamage, Nandadeva; Hill, Terence E; Juelich, Terry L; Zhang, Lihong; Smith, Jennifer K; Perez, David; Gong, Bin; Freiberg, Alexander N; Ikegami, Tetsuro

    2016-11-16

    Rift Valley fever is a mosquito-borne zoonotic disease affecting ruminants and humans. Rift Valley fever virus (RVFV: family Bunyaviridae, genus Phlebovirus) causes abortions and fetal malformations in ruminants, and hemorrhagic fever, encephalitis, or retinitis in humans. The live-attenuated MP-12 vaccine is conditionally licensed for veterinary use in the US. However, this vaccine lacks a marker for the differentiation of vaccinated from infected animals (DIVA). NSs gene is dispensable for RVFV replication, and thus, rMP-12 strains lacking NSs gene is applicable to monitor vaccinated animals. However, the immunogenicity of MP-12 lacking NSs was not as high as parental MP-12. Thus, chimeric MP-12 strains encoding NSs from either Toscana virus (TOSV), sandfly fever Sicilian virus (SFSV) or Punta Toro virus Adames strain (PTA) were characterized previously. Although chimeric MP-12 strains are highly immunogenic, the attenuation through the S-segment remains unknown. Using pathogenic ZH501 strain, we aimed to demonstrate the attenuation of ZH501 strain through chimeric S-segment encoding either the NSs of TOSV, SFSV, PTA, or Punta Toro virus Balliet strain (PTB). In addition, we characterized rZH501 encoding a human dominant-negative PKR (PKRΔE7), which also enhances the immunogenicity of MP-12. Study done on mice revealed that attenuation of rZH501 occurred through the S-segment encoding either PKRΔE7 or SFSV NSs. However, rZH501 encoding either TOSV, PTA, or PTB NSs in the S-segment uniformly caused lethal encephalitis. Our results indicated that the S-segments encoding PKRΔE7 or SFSV NSs are attenuated and thus applicable toward next generation MP-12 vaccine candidates that encode a DIVA marker.

  2. A dynamic, climate-driven model of Rift Valley fever

    Directory of Open Access Journals (Sweden)

    Joseph Leedale

    2016-03-01

    Full Text Available Outbreaks of Rift Valley fever (RVF in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

  3. Muscles of mastication model-based MR image segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Ng, H.P. [NUS Graduate School for Integrative Sciences and Engineering, Singapore (Singapore); Agency for Science Technology and Research, Singapore (Singapore). Biomedical Imaging Lab.; Ong, S.H. [National Univ. of Singapore (Singapore). Dept. of Electrical and Computer Engineering; National Univ. of Singapore (Singapore). Div. of Bioengineering; Hu, Q.; Nowinski, W.L. [Agency for Science Technology and Research, Singapore (Singapore). Biomedical Imaging Lab.; Foong, K.W.C. [NUS Graduate School for Integrative Sciences and Engineering, Singapore (Singapore); National Univ. of Singapore (Singapore). Dept. of Preventive Dentistry; Goh, P.S. [National Univ. of Singapore (Singapore). Dept. of Diagnostic Radiology

    2006-11-15

    Objective: The muscles of mastication play a major role in the orodigestive system as the principal motive force for the mandible. An algorithm for segmenting these muscles from magnetic resonance (MR) images was developed and tested. Materials and methods: Anatomical information about the muscles of mastication in MR images is used to obtain the spatial relationships relating the muscle region of interest (ROI) and head ROI. A model-based technique that involves the spatial relationships between head and muscle ROIs as well as muscle templates is developed. In the segmentation stage, the muscle ROI is derived from the model. Within the muscle ROI, anisotropic diffusion is applied to smooth the texture, followed by thresholding to exclude bone and fat. The muscle template and morphological operators are employed to obtain an initial estimate of the muscle boundary, which then serves as the input contour to the gradient vector flow snake that iterates to the final segmentation. Results: The method was applied to segmentation of the masseter, lateral pterygoid and medial pterygoid in 75 images. The overlap indices (K) achieved are 91.4, 92.1 and 91.2%, respectively. Conclusion: A model-based method for segmenting the muscles of mastication from MR images was developed and tested. The results show good agreement between manual and automatic segmentations. (orig.)

  4. Muscles of mastication model-based MR image segmentation

    International Nuclear Information System (INIS)

    Ng, H.P.; Agency for Science Technology and Research, Singapore; Ong, S.H.; National Univ. of Singapore; Hu, Q.; Nowinski, W.L.; Foong, K.W.C.; National Univ. of Singapore; Goh, P.S.

    2006-01-01

    Objective: The muscles of mastication play a major role in the orodigestive system as the principal motive force for the mandible. An algorithm for segmenting these muscles from magnetic resonance (MR) images was developed and tested. Materials and methods: Anatomical information about the muscles of mastication in MR images is used to obtain the spatial relationships relating the muscle region of interest (ROI) and head ROI. A model-based technique that involves the spatial relationships between head and muscle ROIs as well as muscle templates is developed. In the segmentation stage, the muscle ROI is derived from the model. Within the muscle ROI, anisotropic diffusion is applied to smooth the texture, followed by thresholding to exclude bone and fat. The muscle template and morphological operators are employed to obtain an initial estimate of the muscle boundary, which then serves as the input contour to the gradient vector flow snake that iterates to the final segmentation. Results: The method was applied to segmentation of the masseter, lateral pterygoid and medial pterygoid in 75 images. The overlap indices (K) achieved are 91.4, 92.1 and 91.2%, respectively. Conclusion: A model-based method for segmenting the muscles of mastication from MR images was developed and tested. The results show good agreement between manual and automatic segmentations. (orig.)

  5. Electric Power Distribution System Model Simplification Using Segment Substitution

    Energy Technology Data Exchange (ETDEWEB)

    Reiman, Andrew P.; McDermott, Thomas E.; Akcakaya, Murat; Reed, Gregory F.

    2018-05-01

    Quasi-static time-series (QSTS) simulation is used to simulate the behavior of distribution systems over long periods of time (typically hours to years). The technique involves repeatedly solving the load-flow problem for a distribution system model and is useful for distributed energy resource (DER) planning. When a QSTS simulation has a small time step and a long duration, the computational burden of the simulation can be a barrier to integration into utility workflows. One way to relieve the computational burden is to simplify the system model. The segment substitution method of simplifying distribution system models introduced in this paper offers model bus reduction of up to 98% with a simplification error as low as 0.2% (0.002 pu voltage). In contrast to existing methods of distribution system model simplification, which rely on topological inspection and linearization, the segment substitution method uses black-box segment data and an assumed simplified topology.

  6. Electric Power Distribution System Model Simplification Using Segment Substitution

    International Nuclear Information System (INIS)

    Reiman, Andrew P.; McDermott, Thomas E.; Akcakaya, Murat; Reed, Gregory F.

    2017-01-01

    Quasi-static time-series (QSTS) simulation is used to simulate the behavior of distribution systems over long periods of time (typically hours to years). The technique involves repeatedly solving the load-flow problem for a distribution system model and is useful for distributed energy resource (DER) planning. When a QSTS simulation has a small time step and a long duration, the computational burden of the simulation can be a barrier to integration into utility workflows. One way to relieve the computational burden is to simplify the system model. The segment substitution method of simplifying distribution system models introduced in this paper offers model bus reduction of up to 98% with a simplification error as low as 0.2% (0.002 pu voltage). Finally, in contrast to existing methods of distribution system model simplification, which rely on topological inspection and linearization, the segment substitution method uses black-box segment data and an assumed simplified topology.

  7. Abdomen and spinal cord segmentation with augmented active shape models.

    Science.gov (United States)

    Xu, Zhoubing; Conrad, Benjamin N; Baucom, Rebeccah B; Smith, Seth A; Poulose, Benjamin K; Landman, Bennett A

    2016-07-01

    Active shape models (ASMs) have been widely used for extracting human anatomies in medical images given their capability for shape regularization of topology preservation. However, sensitivity to model initialization and local correspondence search often undermines their performances, especially around highly variable contexts in computed-tomography (CT) and magnetic resonance (MR) images. In this study, we propose an augmented ASM (AASM) by integrating the multiatlas label fusion (MALF) and level set (LS) techniques into the traditional ASM framework. Using AASM, landmark updates are optimized globally via a region-based LS evolution applied on the probability map generated from MALF. This augmentation effectively extends the searching range of correspondent landmarks while reducing sensitivity to the image contexts and improves the segmentation robustness. We propose the AASM framework as a two-dimensional segmentation technique targeting structures with one axis of regularity. We apply AASM approach to abdomen CT and spinal cord (SC) MR segmentation challenges. On 20 CT scans, the AASM segmentation of the whole abdominal wall enables the subcutaneous/visceral fat measurement, with high correlation to the measurement derived from manual segmentation. On 28 3T MR scans, AASM yields better performances than other state-of-the-art approaches in segmenting white/gray matter in SC.

  8. Main Battle Tank Flexible Gun Tube Disturbance Model: Three-Segment Model

    National Research Council Canada - National Science Library

    Sneck, Henry

    2002-01-01

    ... them. It was found that, contrary to the previously analyzed two degree-of-freedom segment model, the muzzle-end segment could be stabilized by the proper choice of transfer functions and elevation driveline response...

  9. The Consequences of Reconfiguring the Ambisense S Genome Segment of Rift Valley Fever Virus on Viral Replication in Mammalian and Mosquito Cells and for Genome Packaging

    Science.gov (United States)

    Elliott, Richard M.

    2014-01-01

    Rift Valley fever virus (RVFV, family Bunyaviridae) is a mosquito-borne pathogen of both livestock and humans, found primarily in Sub-Saharan Africa and the Arabian Peninsula. The viral genome comprises two negative-sense (L and M segments) and one ambisense (S segment) RNAs that encode seven proteins. The S segment encodes the nucleocapsid (N) protein in the negative-sense and a nonstructural (NSs) protein in the positive-sense, though NSs cannot be translated directly from the S segment but rather from a specific subgenomic mRNA. Using reverse genetics we generated a virus, designated rMP12:S-Swap, in which the N protein is expressed from the NSs locus and NSs from the N locus within the genomic S RNA. In cells infected with rMP12:S-Swap NSs is expressed at higher levels with respect to N than in cells infected with the parental rMP12 virus. Despite NSs being the main interferon antagonist and determinant of virulence, growth of rMP12:S-Swap was attenuated in mammalian cells and gave a small plaque phenotype. The increased abundance of the NSs protein did not lead to faster inhibition of host cell protein synthesis or host cell transcription in infected mammalian cells. In cultured mosquito cells, however, infection with rMP12:S-Swap resulted in cell death rather than establishment of persistence as seen with rMP12. Finally, altering the composition of the S segment led to a differential packaging ratio of genomic to antigenomic RNA into rMP12:S-Swap virions. Our results highlight the plasticity of the RVFV genome and provide a useful experimental tool to investigate further the packaging mechanism of the segmented genome. PMID:24550727

  10. A new level set model for cell image segmentation

    International Nuclear Information System (INIS)

    Ma Jing-Feng; Chen Chun; Hou Kai; Bao Shang-Lian

    2011-01-01

    In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing. (cross-disciplinary physics and related areas of science and technology)

  11. Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

    Czech Academy of Sciences Publication Activity Database

    Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

    2009-01-01

    Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

  12. Documentation of the Santa Clara Valley regional ground-water/surface-water flow model, Santa Clara Valley, California

    Science.gov (United States)

    Hanson, R.T.; Li, Zhen; Faunt, C.C.

    2004-01-01

    The Santa Clara Valley is a long, narrow trough extending about 35 miles southeast from the southern end of San Francisco Bay where the regional alluvial-aquifer system has been a major source of water. Intensive agricultural and urban development throughout the 20th century and related ground-water development resulted in ground-water-level declines of more than 200 feet and land subsidence of as much as 12.7 feet between the early 1900s and the mid-1960s. Since the 1960s, Santa Clara Valley Water District has imported surface water to meet growing demands and reduce dependence on ground-water supplies. This importation of water has resulted in a sustained recovery of the ground-water flow system. To help support effective management of the ground-water resources, a regional ground-water/surface-water flow model was developed. This model simulates the flow of ground water and surface water, changes in ground-water storage, and related effects such as land subsidence. A numerical ground-water/surface-water flow model of the Santa Clara Valley subbasin of the Santa Clara Valley was developed as part of a cooperative investigation with the Santa Clara Valley Water District. The model better defines the geohydrologic framework of the regional flow system and better delineates the supply and demand components that affect the inflows to and outflows from the regional ground-water flow system. Development of the model includes revisions to the previous ground-water flow model that upgraded the temporal and spatial discretization, added source-specific inflows and outflows, simulated additional flow features such as land subsidence and multi-aquifer wellbore flow, and extended the period of simulation through September 1999. The transient-state model was calibrated to historical surface-water and ground-water data for the period 197099 and to historical subsidence for the period 198399. The regional ground-water flow system consists of multiple aquifers that are grouped

  13. Analysis of overdeepened valleys using the digital elevation model of the bedrock surface of Northern Switzerland

    Energy Technology Data Exchange (ETDEWEB)

    Jordan, P.

    2010-11-15

    Based on surface and borehole information, together with pre-existing regional and local interpretations, a 7,150 square kilometre Raster Digital Elevation Model (DEM) of the bedrock surface of northern Switzerland was constructed using a 25 m cell size. This model represents a further important step in the understanding of Quaternary sediment distribution and is open to a broad field of application and analysis, including hydrogeological, geotechnical and geophysical studies as well as research in the field of Pleistocene landscape evolution. An analysis of the overdeepened valleys in the whole model area and, more specifically in the Reuss area, shows that, in most cases, overdeepening is restricted to the areas covered by the Last Glaciation Maximum (LGM). However, at various locations relatively narrow overdeepened valleys outreach the tongue basins and the LGM ice shield limits. Therefore, an earlier and further-reaching glacial event has probably contributed significantly to the overdeepening of these valleys. No significant overdeepening has been identified downstream of Boettstein (Aare) and Kaiserstuhl (Rhine), although the ice extended considerably further downstream, at least during the most extensive glaciation. Except for the bedrock between Brugg and Boettstein, no overdeepened valleys are found significantly north of the outcrop of Mesozoic limestone of the Folded and Tabular Jura. A detailed analysis of the Reuss area shows that the Lake and Suhre valleys are separated from the Emmen-Gisikon Reuss valley basin by a significant bedrock barrier. The individual bedrock valleys are divided into several sub-basins, indicating a multiphase evolution of the valleys. Some of the swells or barriers separating the sub-basins coincide with known late LGM retreat stages. In the Suhre valley, an old fluvial valley floor with restricted overdeepened sections is documented. (author)

  14. Stochastic Modelling as a Tool for Seismic Signals Segmentation

    Directory of Open Access Journals (Sweden)

    Daniel Kucharczyk

    2016-01-01

    Full Text Available In order to model nonstationary real-world processes one can find appropriate theoretical model with properties following the analyzed data. However in this case many trajectories of the analyzed process are required. Alternatively, one can extract parts of the signal that have homogenous structure via segmentation. The proper segmentation can lead to extraction of important features of analyzed phenomena that cannot be described without the segmentation. There is no one universal method that can be applied for all of the phenomena; thus novel methods should be invented for specific cases. They might address specific character of the signal in different domains (time, frequency, time-frequency, etc.. In this paper we propose two novel segmentation methods that take under consideration the stochastic properties of the analyzed signals in time domain. Our research is motivated by the analysis of vibration signals acquired in an underground mine. In such signals we observe seismic events which appear after the mining activity, like blasting, provoked relaxation of rock, and some unexpected events, like natural rock burst. The proposed segmentation procedures allow for extraction of such parts of the analyzed signals which are related to mentioned events.

  15. Modeling applications for precision agriculture in the California Central Valley

    Science.gov (United States)

    Marklein, A. R.; Riley, W. J.; Grant, R. F.; Mezbahuddin, S.; Mekonnen, Z. A.; Liu, Y.; Ying, S.

    2017-12-01

    Drought in California has increased the motivation to develop precision agriculture, which uses observations to make site-specific management decisions throughout the growing season. In agricultural systems that are prone to drought, these efforts often focus on irrigation efficiency. Recent improvements in soil sensor technology allow the monitoring of plant and soil status in real-time, which can then inform models aimed at improving irrigation management. But even on farms with resources to deploy soil sensors across the landscape, leveraging that sensor data to design an efficient irrigation scheme remains a challenge. We conduct a modeling experiment aimed at simulating precision agriculture to address several questions: (1) how, when, and where does irrigation lead to optimal yield? and (2) What are the impacts of different precision irrigation schemes on yields, soil organic carbon (SOC), and total water use? We use the ecosys model to simulate precision agriculture in a conventional tomato-corn rotation in the California Central Valley with varying soil water content thresholds for irrigation and soil water sensor depths. This model is ideal for our question because it includes explicit process-based functions for the plant growth, plant water use, soil hydrology, and SOC, and has been tested extensively in agricultural ecosystems. Low irrigation thresholds allows the soil to become drier before irrigating compared to high irrigation thresholds; as such, we found that the high irrigation thresholds use more irrigation over the course of the season, have higher yields, and have lower water use efficiency. The irrigation threshold did not affect SOC. Yields and water use are highest at sensor depths of 0.5 to 0.15 m, but water use efficiency was also lowest at these depths. We found SOC to be significantly affected by sensor depth, with the highest SOC at the shallowest sensor depths. These results will help regulate irrigation water while maintaining yield

  16. Fuzzy object models for newborn brain MR image segmentation

    Science.gov (United States)

    Kobashi, Syoji; Udupa, Jayaram K.

    2013-03-01

    Newborn brain MR image segmentation is a challenging problem because of variety of size, shape and MR signal although it is the fundamental study for quantitative radiology in brain MR images. Because of the large difference between the adult brain and the newborn brain, it is difficult to directly apply the conventional methods for the newborn brain. Inspired by the original fuzzy object model introduced by Udupa et al. at SPIE Medical Imaging 2011, called fuzzy shape object model (FSOM) here, this paper introduces fuzzy intensity object model (FIOM), and proposes a new image segmentation method which combines the FSOM and FIOM into fuzzy connected (FC) image segmentation. The fuzzy object models are built from training datasets in which the cerebral parenchyma is delineated by experts. After registering FSOM with the evaluating image, the proposed method roughly recognizes the cerebral parenchyma region based on a prior knowledge of location, shape, and the MR signal given by the registered FSOM and FIOM. Then, FC image segmentation delineates the cerebral parenchyma using the fuzzy object models. The proposed method has been evaluated using 9 newborn brain MR images using the leave-one-out strategy. The revised age was between -1 and 2 months. Quantitative evaluation using false positive volume fraction (FPVF) and false negative volume fraction (FNVF) has been conducted. Using the evaluation data, a FPVF of 0.75% and FNVF of 3.75% were achieved. More data collection and testing are underway.

  17. Selecting salient frames for spatiotemporal video modeling and segmentation.

    Science.gov (United States)

    Song, Xiaomu; Fan, Guoliang

    2007-12-01

    We propose a new statistical generative model for spatiotemporal video segmentation. The objective is to partition a video sequence into homogeneous segments that can be used as "building blocks" for semantic video segmentation. The baseline framework is a Gaussian mixture model (GMM)-based video modeling approach that involves a six-dimensional spatiotemporal feature space. Specifically, we introduce the concept of frame saliency to quantify the relevancy of a video frame to the GMM-based spatiotemporal video modeling. This helps us use a small set of salient frames to facilitate the model training by reducing data redundancy and irrelevance. A modified expectation maximization algorithm is developed for simultaneous GMM training and frame saliency estimation, and the frames with the highest saliency values are extracted to refine the GMM estimation for video segmentation. Moreover, it is interesting to find that frame saliency can imply some object behaviors. This makes the proposed method also applicable to other frame-related video analysis tasks, such as key-frame extraction, video skimming, etc. Experiments on real videos demonstrate the effectiveness and efficiency of the proposed method.

  18. VALDRIFT 1.0: A valley atmospheric dispersion model with deposition

    Energy Technology Data Exchange (ETDEWEB)

    Allwine, K.J.; Bian, X.; Whiteman, C.D.

    1995-05-01

    VALDRIFT version 1.0 is an atmospheric transport and diffusion model for use in well-defined mountain valleys. It is designed to determine the extent of ddft from aedal pesticide spraying activities, but can also be applied to estimate the transport and diffusion of various air pollutants in valleys. The model is phenomenological -- that is, the dominant meteorological processes goveming the behavior of the valley atmosphere are formulated explicitly in the model, albeit in a highly parameterized fashion. The key meteorological processes treated are: (1) nonsteady and nonhomogeneous along-valley winds and turbulent diffusivities, (2) convective boundary layer growth, (3) inversion descent, (4) noctumal temperature inversion breakup, and (5) subsidence. The model is applicable under relatively cloud-free, undisturbed synoptic conditions and is configured to operate through one diumal cycle for a single valley. The inputs required are the valley topographical characteristics, pesticide release rate as a function of time and space, along-valley wind speed as a function of time and space, temperature inversion characteristics at sunrise, and sensible heat flux as a function of time following sunrise. Default values are provided for certain inputs in the absence of detailed observations. The outputs are three-dimensional air concentration and ground-level deposition fields as a function of time.

  19. Evaporation estimation of rift valley lakes: comparison of models.

    Science.gov (United States)

    Melesse, Assefa M; Abtew, Wossenu; Dessalegne, Tibebe

    2009-01-01

    Evapotranspiration (ET) accounts for a substantial amount of the water flux in the arid and semi-arid regions of the World. Accurate estimation of ET has been a challenge for hydrologists, mainly because of the spatiotemporal variability of the environmental and physical parameters governing the latent heat flux. In addition, most available ET models depend on intensive meteorological information for ET estimation. Such data are not available at the desired spatial and temporal scales in less developed and remote parts of the world. This limitation has necessitated the development of simple models that are less data intensive and provide ET estimates with acceptable level of accuracy. Remote sensing approach can also be applied to large areas where meteorological data are not available and field scale data collection is costly, time consuming and difficult. In areas like the Rift Valley regions of Ethiopia, the applicability of the Simple Method (Abtew Method) of lake evaporation estimation and surface energy balance approach using remote sensing was studied. The Simple Method and a remote sensing-based lake evaporation estimates were compared to the Penman, Energy balance, Pan, Radiation and Complementary Relationship Lake Evaporation (CRLE) methods applied in the region. Results indicate a good correspondence of the models outputs to that of the above methods. Comparison of the 1986 and 2000 monthly lake ET from the Landsat images to the Simple and Penman Methods show that the remote sensing and surface energy balance approach is promising for large scale applications to understand the spatial variation of the latent heat flux.

  20. Evaporation Estimation of Rift Valley Lakes: Comparison of Models

    Directory of Open Access Journals (Sweden)

    Tibebe Dessalegne

    2009-12-01

    Full Text Available Evapotranspiration (ET accounts for a substantial amount of the water flux in the arid and semi-arid regions of the World. Accurate estimation of ET has been a challenge for hydrologists, mainly because of the spatiotemporal variability of the environmental and physical parameters governing the latent heat flux. In addition, most available ET models depend on intensive meteorological information for ET estimation. Such data are not available at the desired spatial and temporal scales in less developed and remote parts of the world. This limitation has necessitated the development of simple models that are less data intensive and provide ET estimates with acceptable level of accuracy. Remote sensing approach can also be applied to large areas where meteorological data are not available and field scale data collection is costly, time consuming and difficult. In areas like the Rift Valley regions of Ethiopia, the applicability of the Simple Method (Abtew Method of lake evaporation estimation and surface energy balance approach using remote sensing was studied. The Simple Method and a remote sensing-based lake evaporation estimates were compared to the Penman, Energy balance, Pan, Radiation and Complementary Relationship Lake Evaporation (CRLE methods applied in the region. Results indicate a good correspondence of the models outputs to that of the above methods. Comparison of the 1986 and 2000 monthly lake ET from the Landsat images to the Simple and Penman Methods show that the remote sensing and surface energy balance approach is promising for large scale applications to understand the spatial variation of the latent heat flux.

  1. Statistical shape model with random walks for inner ear segmentation

    DEFF Research Database (Denmark)

    Pujadas, Esmeralda Ruiz; Kjer, Hans Martin; Piella, Gemma

    2016-01-01

    is required. We propose a new framework for segmentation of micro-CT cochlear images using random walks combined with a statistical shape model (SSM). The SSM allows us to constrain the less contrasted areas and ensures valid inner ear shape outputs. Additionally, a topology preservation method is proposed...

  2. Combining segmentation and attention: a new foveal attention model

    Directory of Open Access Journals (Sweden)

    Rebeca eMarfil

    2014-08-01

    Full Text Available Artificial vision systems cannot process all the information that they receive from the world in real time because it is highly expensive and inefficient in terms of computational cost. Inspired by biological perception systems, articial attention models pursuit to select only the relevant part of the scene. Besides, it is well established that the units of attention on human vision are not merely spatial but closely related to perceptual objects (proto-objects. This implies a strong bidirectional relationship between segmentation and attention processes. Therefore, while the segmentation process is the responsible to extract the proto-objects from the scene, attention can guide segmentation, arising the concept of foveal attention. When the focus of attention is deployed from one visual unit to another, the rest of the scene is perceived but at a lower resolution that the focused object. The result is a multi-resolution visual perception in which the fovea, a dimple on the central retina, provides the highest resolution vision. In this paper, a bottom-up foveal attention model is presented. In this model the input image is a foveal image represented using a Cartesian Foveal Geometry (CFG, which encodes the field of view of the sensor as a fovea (placed in the focus of attention surrounded by a set of concentric rings with decreasing resolution. Then multirresolution perceptual segmentation is performed by building a foveal polygon using the Bounded Irregular Pyramid (BIP. Bottom-up attention is enclosed in the same structure, allowing to set the fovea over the most salient image proto-object. Saliency is computed as a linear combination of multiple low level features such us colour and intensity contrast, symmetry, orientation and roundness. Obtained results from natural images show that the performance of the combination of hierarchical foveal segmentation and saliency estimation is good in terms of accuracy and speed.

  3. Diurnal cycle of air pollution in the Kathmandu Valley, Nepal: 2. Modeling results

    Science.gov (United States)

    Panday, Arnico K.; Prinn, Ronald G.; SchäR, Christoph

    2009-11-01

    After completing a 9-month field experiment studying air pollution and meteorology in the Kathmandu Valley, Nepal, we set up the mesoscale meteorological model MM5 to simulate the Kathmandu Valley's meteorology with a horizontal resolution of up to 1 km. After testing the model against available data, we used it to address specific questions to understand the factors that control the observed diurnal cycle of air pollution in this urban basin in the Himalayas. We studied the dynamics of the basin's nocturnal cold air pool, its dissipation in the morning, and the subsequent growth and decay of the mixed layer over the valley. During mornings, we found behavior common to large basins, with upslope flows and basin-center subsidence removing the nocturnal cold air pool. During afternoons the circulation in the Kathmandu Valley exhibited patterns common to plateaus, with cooler denser air originating over lower regions west of Kathmandu arriving through mountain passes and spreading across the basin floor, thereby reducing the mixed layer depth. We also examined the pathways of pollutant ventilation out of the valley. The bulk of the pollution ventilation takes place during the afternoon, when strong westerly winds blow in through the western passes of the valley, and the pollutants are rapidly carried out through passes on the east and south sides of the valley. In the evening, pollutants first accumulate near the surface, but then are lifted slightly when katabatic flows converge underneath. The elevated polluted layers are mixed back down in the morning, contributing to the morning pollution peak. Later in the morning a fraction of the valley's pollutants travels up the slopes of the valley rim mountains before the westerly winds begin.

  4. Model instruments of effective segmentation of the fast food market

    Directory of Open Access Journals (Sweden)

    Mityaeva Tetyana L.

    2013-03-01

    Full Text Available The article presents results of optimisation step-type calculations of economic effectiveness of promotion of fast food with consideration of key parameters of assessment of efficiency of the marketing strategy of segmentation. The article justifies development of a mathematical model on the bases of 3D-presentations and three-dimensional system of management variables. The modern applied mathematical packages allow formation not only of one-dimensional and two-dimensional arrays and analyse links of variables, but also of three-dimensional, besides, the more links and parameters are taken into account, the more adequate and adaptive are results of modelling and, as a result, more informative and strategically valuable. The article shows modelling possibilities that allow taking into account strategies and reactions on formation of the marketing strategy under conditions of entering the fast food market segments.

  5. Simplified Model Surgery Technique for Segmental Maxillary Surgeries

    Directory of Open Access Journals (Sweden)

    Namit Nagar

    2011-01-01

    Full Text Available Model surgery is the dental cast version of cephalometric prediction of surgical results. Patients having vertical maxillary excess with prognathism invariably require Lefort I osteotomy with maxillary segmentation and maxillary first premolar extractions during surgery. Traditionally, model surgeries in these cases have been done by sawing the model through the first premolar interproximal area and removing that segment. This clinical innovation employed the use of X-ray film strips as separators in maxillary first premolar interproximal area. The method advocated is a time-saving procedure where no special clinical or laboratory tools, such as plaster saw (with accompanying plaster dust, were required and reusable separators were made from old and discarded X-ray films.

  6. Segmental Modification of the Mualem Model by Remolded Loess

    Directory of Open Access Journals (Sweden)

    Le-fan Wang

    2017-01-01

    Full Text Available The measured diffusion coefficient and soil-water characteristic curve (SWCC of remolded loess were used to modify the Mualem model for increasing its accuracy. The obtained results show that the goodness of fit between the Mualem model and the variable parameter-modified Mualem method comparing with the test results was not high. The saturation of 0.65 was introduced as the boundary to divide the curve of the measured diffusion coefficient into two segments. When the segmentation method combined with the variable parameter method was used to modify the Mualem model, the fitting correlation coefficient was increased to 0.921–0.998. The modified parameters Ko and L corresponding to remolded loess were calculated for different dry densities. Based on the exponential function between Ko and dry density and the linear relation between L and dry density, the segmentally modified Mualem model was established for remolded loess by considering variation in dry density. The results of the study can be used for directly determining the unsaturated infiltration coefficient and for indirectly determining the SWCC through diffusion coefficient.

  7. Three-body segment musculoskeletal model of the upper limb

    Directory of Open Access Journals (Sweden)

    Valdmanová L.

    2013-06-01

    Full Text Available The main aim is to create a computational three-body segment model of an upper limb of a human body for determination of muscle forces generated to keep a given loaded upper limb position. The model consists of three segments representing arm, forearm, hand and of all major muscles connected to the segments. Muscle origins and insertions determination corresponds to a real anatomy. Muscle behaviour is defined according to the Hill-type muscle model consisting of contractile and viscoelastic element. The upper limb is presented by a system of three rigid bars connected by rotational joints. The whole limb is fixed to the frame in the shoulder joint. A static balance problem is solved by principle of virtual work. The system of equation describing the musculoskeletal system is overdetermined because more muscles than necessary contribute to get the concrete upper limb position. Hence the mathematical problem is solved by an optimization method searching the least energetically-consuming solution. The upper limb computational model is verified by electromyography of the biceps brachii muscle.

  8. Color Texture Segmentation by Decomposition of Gaussian Mixture Model

    Czech Academy of Sciences Publication Activity Database

    Grim, Jiří; Somol, Petr; Haindl, Michal; Pudil, Pavel

    2006-01-01

    Roč. 19, č. 4225 (2006), s. 287-296 ISSN 0302-9743. [Iberoamerican Congress on Pattern Recognition. CIARP 2006 /11./. Cancun, 14.11.2006-17.11.2006] R&D Projects: GA AV ČR 1ET400750407; GA MŠk 1M0572; GA MŠk 2C06019 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : texture segmentation * gaussian mixture model * EM algorithm Subject RIV: IN - Informatics, Computer Science Impact factor: 0.402, year: 2005 http://library.utia.cas.cz/separaty/historie/grim-color texture segmentation by decomposition of gaussian mixture model.pdf

  9. Model instruments of effective segmentation of the fast food market

    OpenAIRE

    Mityaeva Tetyana L.

    2013-01-01

    The article presents results of optimisation step-type calculations of economic effectiveness of promotion of fast food with consideration of key parameters of assessment of efficiency of the marketing strategy of segmentation. The article justifies development of a mathematical model on the bases of 3D-presentations and three-dimensional system of management variables. The modern applied mathematical packages allow formation not only of one-dimensional and two-dimensional arrays and analyse ...

  10. Ultrasound Common Carotid Artery Segmentation Based on Active Shape Model

    Science.gov (United States)

    Yang, Xin; Jin, Jiaoying; Xu, Mengling; Wu, Huihui; He, Wanji; Yuchi, Ming; Ding, Mingyue

    2013-01-01

    Carotid atherosclerosis is a major reason of stroke, a leading cause of death and disability. In this paper, a segmentation method based on Active Shape Model (ASM) is developed and evaluated to outline common carotid artery (CCA) for carotid atherosclerosis computer-aided evaluation and diagnosis. The proposed method is used to segment both media-adventitia-boundary (MAB) and lumen-intima-boundary (LIB) on transverse views slices from three-dimensional ultrasound (3D US) images. The data set consists of sixty-eight, 17 × 2 × 2, 3D US volume data acquired from the left and right carotid arteries of seventeen patients (eight treated with 80 mg atorvastatin and nine with placebo), who had carotid stenosis of 60% or more, at baseline and after three months of treatment. Manually outlined boundaries by expert are adopted as the ground truth for evaluation. For the MAB and LIB segmentations, respectively, the algorithm yielded Dice Similarity Coefficient (DSC) of 94.4% ± 3.2% and 92.8% ± 3.3%, mean absolute distances (MAD) of 0.26 ± 0.18 mm and 0.33 ± 0.21 mm, and maximum absolute distances (MAXD) of 0.75 ± 0.46 mm and 0.84 ± 0.39 mm. It took 4.3 ± 0.5 mins to segment single 3D US images, while it took 11.7 ± 1.2 mins for manual segmentation. The method would promote the translation of carotid 3D US to clinical care for the monitoring of the atherosclerotic disease progression and regression. PMID:23533535

  11. Ultrasound Common Carotid Artery Segmentation Based on Active Shape Model

    Directory of Open Access Journals (Sweden)

    Xin Yang

    2013-01-01

    Full Text Available Carotid atherosclerosis is a major reason of stroke, a leading cause of death and disability. In this paper, a segmentation method based on Active Shape Model (ASM is developed and evaluated to outline common carotid artery (CCA for carotid atherosclerosis computer-aided evaluation and diagnosis. The proposed method is used to segment both media-adventitia-boundary (MAB and lumen-intima-boundary (LIB on transverse views slices from three-dimensional ultrasound (3D US images. The data set consists of sixty-eight, 17 × 2 × 2, 3D US volume data acquired from the left and right carotid arteries of seventeen patients (eight treated with 80 mg atorvastatin and nine with placebo, who had carotid stenosis of 60% or more, at baseline and after three months of treatment. Manually outlined boundaries by expert are adopted as the ground truth for evaluation. For the MAB and LIB segmentations, respectively, the algorithm yielded Dice Similarity Coefficient (DSC of 94.4% ± 3.2% and 92.8% ± 3.3%, mean absolute distances (MAD of 0.26 ± 0.18 mm and 0.33 ± 0.21 mm, and maximum absolute distances (MAXD of 0.75 ± 0.46 mm and 0.84 ± 0.39 mm. It took 4.3 ± 0.5 mins to segment single 3D US images, while it took 11.7 ± 1.2 mins for manual segmentation. The method would promote the translation of carotid 3D US to clinical care for the monitoring of the atherosclerotic disease progression and regression.

  12. Modeling Dissolved Solids in the Rincon Valley, New Mexico Using RiverWare

    Science.gov (United States)

    Abudu, S.; Ahn, S. R.; Sheng, Z.

    2017-12-01

    Simulating transport and storage of dissolved solids in surface water and underlying alluvial aquifer is essential to evaluate the impacts of surface water operations, groundwater pumping, and climate variability on the spatial and temporal variability of salinity in the Rio Grande Basin. In this study, we developed a monthly RiverWare water quantity and quality model to simulate the both concentration and loads of dissolved solids for the Rincon Valley, New Mexico from Caballo Reservoir to Leasburg Dam segment of the Rio Grande. The measured flows, concentration and loads of dissolved solids in the main stream and drains were used to develop RiveWare model using 1980-1988 data for calibration, and 1989-1995 data for validation. The transport of salt is tracked using discretized salt and post-process approaches. Flow and salt exchange between the surface water and adjacent groundwater objects is computed using "soil moisture salt with supplemental flow" method in the RiverWare. In the groundwater objects, the "layered salt" method is used to simulate concentration of the dissolved solids in the shallow groundwater storage. In addition, the estimated local inflows under different weather conditions by using a calibrated Soil Water Assessment Tool (SWAT) were fed into the RiverWare to refine the simulation of the flow and dissolved solids. The results show the salt concentration and loads increased at Leasburg Dam, which indicates the river collects salts from the agricultural return flow and the underlying aquifer. The RiverWare model with the local inflow fed by SWAT delivered the better quantification of temporal and spatial salt exchange patterns between the river and the underlying aquifer. The results from the proposed modeling approach can be used to refine the current mass-balance budgets for dissolved-solids transport in the Rio Grande, and provide guidelines for planning and decision-making to control salinity in arid river environment.

  13. Reliability of a Seven-Segment Foot Model with Medial and Lateral Midfoot and Forefoot Segments During Walking Gait.

    Science.gov (United States)

    Cobb, Stephen C; Joshi, Mukta N; Pomeroy, Robin L

    2016-12-01

    In-vitro and invasive in-vivo studies have reported relatively independent motion in the medial and lateral forefoot segments during gait. However, most current surface-based models have not defined medial and lateral forefoot or midfoot segments. The purpose of the current study was to determine the reliability of a 7-segment foot model that includes medial and lateral midfoot and forefoot segments during walking gait. Three-dimensional positions of marker clusters located on the leg and 6 foot segments were tracked as 10 participants completed 5 walking trials. To examine the reliability of the foot model, coefficients of multiple correlation (CMC) were calculated across the trials for each participant. Three-dimensional stance time series and range of motion (ROM) during stance were also calculated for each functional articulation. CMCs for all of the functional articulations were ≥ 0.80. Overall, the rearfoot complex (leg-calcaneus segments) was the most reliable articulation and the medial midfoot complex (calcaneus-navicular segments) was the least reliable. With respect to ROM, reliability was greatest for plantarflexion/dorsiflexion and least for abduction/adduction. Further, the stance ROM and time-series patterns results between the current study and previous invasive in-vivo studies that have assessed actual bone motion were generally consistent.

  14. A lung segmental model of chronic Pseudomonas infection in sheep.

    Directory of Open Access Journals (Sweden)

    David Collie

    Full Text Available Chronic lung infection with Pseudomonas aeruginosa is a major contributor to morbidity, mortality and premature death in cystic fibrosis. A new paradigm for managing such infections is needed, as are relevant and translatable animal models to identify and test concepts. We sought to improve on limitations associated with existing models of infection in small animals through developing a lung segmental model of chronic Pseudomonas infection in sheep.Using local lung instillation of P. aeruginosa suspended in agar beads we were able to demonstrate that such infection led to the development of a suppurative, necrotising and pyogranulomatous pneumonia centred on the instilled beads. No overt evidence of organ or systemic compromise was apparent in any animal during the course of infection. Infection persisted in the lungs of individual animals for as long as 66 days after initial instillation. Quantitative microbiology applied to bronchoalveolar lavage fluid derived from infected segments proved an insensitive index of the presence of significant infection in lung tissue (>10(4 cfu/g.The agar bead model of chronic P. aeruginosa lung infection in sheep is a relevant platform to investigate both the pathobiology of such infections as well as novel approaches to their diagnosis and therapy. Particular ethical benefits relate to the model in terms of refining existing approaches by compromising a smaller proportion of the lung with infection and facilitating longitudinal assessment by bronchoscopy, and also potentially reducing animal numbers through facilitating within-animal comparisons of differential therapeutic approaches.

  15. A lung segmental model of chronic Pseudomonas infection in sheep.

    Science.gov (United States)

    Collie, David; Govan, John; Wright, Steven; Thornton, Elisabeth; Tennant, Peter; Smith, Sionagh; Doherty, Catherine; McLachlan, Gerry

    2013-01-01

    Chronic lung infection with Pseudomonas aeruginosa is a major contributor to morbidity, mortality and premature death in cystic fibrosis. A new paradigm for managing such infections is needed, as are relevant and translatable animal models to identify and test concepts. We sought to improve on limitations associated with existing models of infection in small animals through developing a lung segmental model of chronic Pseudomonas infection in sheep. Using local lung instillation of P. aeruginosa suspended in agar beads we were able to demonstrate that such infection led to the development of a suppurative, necrotising and pyogranulomatous pneumonia centred on the instilled beads. No overt evidence of organ or systemic compromise was apparent in any animal during the course of infection. Infection persisted in the lungs of individual animals for as long as 66 days after initial instillation. Quantitative microbiology applied to bronchoalveolar lavage fluid derived from infected segments proved an insensitive index of the presence of significant infection in lung tissue (>10(4) cfu/g). The agar bead model of chronic P. aeruginosa lung infection in sheep is a relevant platform to investigate both the pathobiology of such infections as well as novel approaches to their diagnosis and therapy. Particular ethical benefits relate to the model in terms of refining existing approaches by compromising a smaller proportion of the lung with infection and facilitating longitudinal assessment by bronchoscopy, and also potentially reducing animal numbers through facilitating within-animal comparisons of differential therapeutic approaches.

  16. Modelling of subject specific based segmental dynamics of knee joint

    Science.gov (United States)

    Nasir, N. H. M.; Ibrahim, B. S. K. K.; Huq, M. S.; Ahmad, M. K. I.

    2017-09-01

    This study determines segmental dynamics parameters based on subject specific method. Five hemiplegic patients participated in the study, two men and three women. Their ages ranged from 50 to 60 years, weights from 60 to 70 kg and heights from 145 to 170 cm. Sample group included patients with different side of stroke. The parameters of the segmental dynamics resembling the knee joint functions measured via measurement of Winter and its model generated via the employment Kane's equation of motion. Inertial parameters in the form of the anthropometry can be identified and measured by employing Standard Human Dimension on the subjects who are in hemiplegia condition. The inertial parameters are the location of centre of mass (COM) at the length of the limb segment, inertia moment around the COM and masses of shank and foot to generate accurate motion equations. This investigation has also managed to dig out a few advantages of employing the table of anthropometry in movement biomechanics of Winter's and Kane's equation of motion. A general procedure is presented to yield accurate measurement of estimation for the inertial parameters for the joint of the knee of certain subjects with stroke history.

  17. Background based Gaussian mixture model lesion segmentation in PET

    Energy Technology Data Exchange (ETDEWEB)

    Soffientini, Chiara Dolores, E-mail: chiaradolores.soffientini@polimi.it; Baselli, Giuseppe [DEIB, Department of Electronics, Information, and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, Milan 20133 (Italy); De Bernardi, Elisabetta [Department of Medicine and Surgery, Tecnomed Foundation, University of Milano—Bicocca, Monza 20900 (Italy); Zito, Felicia; Castellani, Massimo [Nuclear Medicine Department, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, via Francesco Sforza 35, Milan 20122 (Italy)

    2016-05-15

    Purpose: Quantitative {sup 18}F-fluorodeoxyglucose positron emission tomography is limited by the uncertainty in lesion delineation due to poor SNR, low resolution, and partial volume effects, subsequently impacting oncological assessment, treatment planning, and follow-up. The present work develops and validates a segmentation algorithm based on statistical clustering. The introduction of constraints based on background features and contiguity priors is expected to improve robustness vs clinical image characteristics such as lesion dimension, noise, and contrast level. Methods: An eight-class Gaussian mixture model (GMM) clustering algorithm was modified by constraining the mean and variance parameters of four background classes according to the previous analysis of a lesion-free background volume of interest (background modeling). Hence, expectation maximization operated only on the four classes dedicated to lesion detection. To favor the segmentation of connected objects, a further variant was introduced by inserting priors relevant to the classification of neighbors. The algorithm was applied to simulated datasets and acquired phantom data. Feasibility and robustness toward initialization were assessed on a clinical dataset manually contoured by two expert clinicians. Comparisons were performed with respect to a standard eight-class GMM algorithm and to four different state-of-the-art methods in terms of volume error (VE), Dice index, classification error (CE), and Hausdorff distance (HD). Results: The proposed GMM segmentation with background modeling outperformed standard GMM and all the other tested methods. Medians of accuracy indexes were VE <3%, Dice >0.88, CE <0.25, and HD <1.2 in simulations; VE <23%, Dice >0.74, CE <0.43, and HD <1.77 in phantom data. Robustness toward image statistic changes (±15%) was shown by the low index changes: <26% for VE, <17% for Dice, and <15% for CE. Finally, robustness toward the user-dependent volume initialization was

  18. Predictive market segmentation model: An application of logistic regression model and CHAID procedure

    Directory of Open Access Journals (Sweden)

    Soldić-Aleksić Jasna

    2009-01-01

    Full Text Available Market segmentation presents one of the key concepts of the modern marketing. The main goal of market segmentation is focused on creating groups (segments of customers that have similar characteristics, needs, wishes and/or similar behavior regarding the purchase of concrete product/service. Companies can create specific marketing plan for each of these segments and therefore gain short or long term competitive advantage on the market. Depending on the concrete marketing goal, different segmentation schemes and techniques may be applied. This paper presents a predictive market segmentation model based on the application of logistic regression model and CHAID analysis. The logistic regression model was used for the purpose of variables selection (from the initial pool of eleven variables which are statistically significant for explaining the dependent variable. Selected variables were afterwards included in the CHAID procedure that generated the predictive market segmentation model. The model results are presented on the concrete empirical example in the following form: summary model results, CHAID tree, Gain chart, Index chart, risk and classification tables.

  19. Hydrological functioning of West-African inland valleys explored with a critical zone model

    Science.gov (United States)

    Hector, B.; Cohard, J. M.; Séguis, L.; Peugeot, C.; Galle, S.

    2017-12-01

    In west Africa, recurrent floods are still a major issue, and hydropower has been recognized as an important development pathway. Furthermore, inland valleys carry an important agronomic potential, which could meet the necessary increase of the crop production associated with the strong demographic rates of the region. This can lead to land cover and subsequent hydrologic changes. However, the hydrological role of the inland valleys in the humid, hard rock-dominated Sudanian area is not yet well understood, specifically for streamflow (Q) generation processes. We address both the questions of the hydrological functioning of inland valleys in the Sudanian area of West-Africa and the impact of land cover changes on these systems through deterministic sensitivity experiments using a physically-based critical zone model (ParFlow-CLM) applied on a synthetic catchment which comprises an inland valley. The conceptual lithological/pedological model for the catchment includes the main features of such a hydrological elementary unit derived from the literature and from a previously published model based on data from a highly instrumented elementary catchment. Model forcings and parameters are based on data from the AMMA-CATCH observation service and multiple field experiments. We found yearly water budgets were much more sensitive to vegetation distribution than lithology features of the inland valley (presence of the low permeability layer commonly found below the inland valley and the hydrodynamic properties of upstream and lateral areas). Yearly evapotranspiration budget between a fully tree-covered and an herbaceous-covered catchment increases between 6 and 21% of the precipitation of the year (depending on the tested cases) which reduces considerably the yearly streamflow budgets ( 30%). On the other hand, the lithology distribution has clear impacts on the spatial distribution of water storage dynamics.

  20. A Segmented Signal Progression Model for the Modern Streetcar System

    Directory of Open Access Journals (Sweden)

    Baojie Wang

    2015-01-01

    Full Text Available This paper is on the purpose of developing a segmented signal progression model for modern streetcar system. The new method is presented with the following features: (1 the control concept is based on the assumption of only one streetcar line operating along an arterial under a constant headway and no bandwidth demand for streetcar system signal progression; (2 the control unit is defined as a coordinated intersection group associated with several streetcar stations, and the control joints must be streetcar stations; (3 the objective function is built to ensure the two-way streetcar arrival times distributing within the available time of streetcar phase; (4 the available time of streetcar phase is determined by timing schemes, intersection structures, track locations, streetcar speeds, and vehicular accelerations; (5 the streetcar running speed is constant separately whether it is in upstream or downstream route; (6 the streetcar dwell time is preset according to historical data distribution or charging demand. The proposed method is experimentally examined in Hexi New City Streetcar Project in Nanjing, China. In the experimental results, the streetcar system operation and the progression impacts are shown to affect transit and vehicular traffic. The proposed model presents promising outcomes through the design of streetcar system segmented signal progression, in terms of ensuring high streetcar system efficiency and minimizing negative impacts on transit and vehicular traffic.

  1. Quantum Hall Valley Nematics: From Field Theories to Microscopic Models

    Science.gov (United States)

    Parameswaran, Siddharth

    The interplay between quantum Hall ordering and spontaneously broken ``internal'' symmetries in two-dimensional electron systems with spin or pseudospin degrees of freedom gives rise to a variety of interesting phenomena, including novel phases, phase transitions, and topological excitations. I will discuss a theory of broken-symmetry quantum Hall states, applicable to a class of multivalley systems, where the symmetry at issue is a point-group element that combines a spatial rotation with a permutation of valley indices. I will explore its ramifications for the phase diagram of a variety of experimental systems, such as AlAs and Si quantum wells and the surface states of bismuth. I will also discuss unconventional transport phenomena in these phases in the presence of quenched randomness, and the possible mechanisms of selection between degenerate broken-symmetry phases in clean systems. I acknowledge support from NSF DMR-1455366.

  2. Dynamic Impact Analysis and Test of Concrete Overpack Segment Models

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Sang Hoon; Kim, Ki Young; Jeon, Je Eon; Seo, Ki Seog [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2011-10-15

    Concrete cask is an option for spent nuclear fuel interim storage which is used mainly in US. The concrete overpack of the cask provides radiation shielding as well as physical protection for inner canister against external mechanical shock. When the overpack undergoes a severe missile impact which might be caused by tornado or aircraft crash, it should sustain minimal level of structural integrity so that the radiation shielding and the retrievability of canister are maintained. Empirical formulas have been developed for the evaluation of concrete damage but those formulas can be used only for local damage evaluation and not for global damage evaluation. In this research, a series of numerical simulations and tests have been performed to evaluate the damage of two types of concrete overpack segment models under high speed missile impact. It is shown that appropriate modeling of material failure is crucial in this kind of analyses and finding the correct failure parameters may not be straightforward

  3. Name segmentation using hidden Markov models and its application in record linkage

    Directory of Open Access Journals (Sweden)

    Rita de Cassia Braga Gonçalves

    2014-10-01

    Full Text Available This study aimed to evaluate the use of hidden Markov models (HMM for the segmentation of person names and its influence on record linkage. A HMM was applied to the segmentation of patient’s and mother’s names in the databases of the Mortality Information System (SIM, Information Subsystem for High Complexity Procedures (APAC, and Hospital Information System (AIH. A sample of 200 patients from each database was segmented via HMM, and the results were compared to those from segmentation by the authors. The APAC-SIM and APAC-AIH databases were linked using three different segmentation strategies, one of which used HMM. Conformity of segmentation via HMM varied from 90.5% to 92.5%. The different segmentation strategies yielded similar results in the record linkage process. This study suggests that segmentation of Brazilian names via HMM is no more effective than traditional segmentation approaches in the linkage process.

  4. Analysis of a kinetic multi-segment foot model. Part I: Model repeatability and kinematic validity.

    Science.gov (United States)

    Bruening, Dustin A; Cooney, Kevin M; Buczek, Frank L

    2012-04-01

    Kinematic multi-segment foot models are still evolving, but have seen increased use in clinical and research settings. The addition of kinetics may increase knowledge of foot and ankle function as well as influence multi-segment foot model evolution; however, previous kinetic models are too complex for clinical use. In this study we present a three-segment kinetic foot model and thorough evaluation of model performance during normal gait. In this first of two companion papers, model reference frames and joint centers are analyzed for repeatability, joint translations are measured, segment rigidity characterized, and sample joint angles presented. Within-tester and between-tester repeatability were first assessed using 10 healthy pediatric participants, while kinematic parameters were subsequently measured on 17 additional healthy pediatric participants. Repeatability errors were generally low for all sagittal plane measures as well as transverse plane Hindfoot and Forefoot segments (median<3°), while the least repeatable orientations were the Hindfoot coronal plane and Hallux transverse plane. Joint translations were generally less than 2mm in any one direction, while segment rigidity analysis suggested rigid body behavior for the Shank and Hindfoot, with the Forefoot violating the rigid body assumptions in terminal stance/pre-swing. Joint excursions were consistent with previously published studies. Copyright © 2012 Elsevier B.V. All rights reserved.

  5. Extracting valley-ridge lines from point-cloud-based 3D fingerprint models.

    Science.gov (United States)

    Pang, Xufang; Song, Zhan; Xie, Wuyuan

    2013-01-01

    3D fingerprinting is an emerging technology with the distinct advantage of touchless operation. More important, 3D fingerprint models contain more biometric information than traditional 2D fingerprint images. However, current approaches to fingerprint feature detection usually must transform the 3D models to a 2D space through unwrapping or other methods, which might introduce distortions. A new approach directly extracts valley-ridge features from point-cloud-based 3D fingerprint models. It first applies the moving least-squares method to fit a local paraboloid surface and represent the local point cloud area. It then computes the local surface's curvatures and curvature tensors to facilitate detection of the potential valley and ridge points. The approach projects those points to the most likely valley-ridge lines, using statistical means such as covariance analysis and cross correlation. To finally extract the valley-ridge lines, it grows the polylines that approximate the projected feature points and removes the perturbations between the sampled points. Experiments with different 3D fingerprint models demonstrate this approach's feasibility and performance.

  6. Spatial risk modelling for water shortage and nitrate pollution in the lower Jordan valley

    International Nuclear Information System (INIS)

    Loibl, W.; Orthofer, R.

    2002-02-01

    This report summarizes the results of the spatial risk modeling activities (work package WP-4.4, 'GIS Risk Modeling') of the INCO-DC project 'Developing Sustainable Water Management in the Jordan Valley'. The project was funded by European Commission's INCO-DC research program. The main objective of the project was to develop the scientific basis for an integral management plan of water resources and their use in the Lower Jordan Valley. The outputs of the project were expected to allow a better understanding of the water management situation, and to provide a sound basis for a better future water management - not only separately in the three countries, but in the overall valley region. The risk modeling was done by the ARCS Seibersdorf research (ARCS), based on information and data provided by the regional partners from Israel (Hebrew University, Jerusalem, HUJ), Palestine (Applied Research Institute, Jerusalem, Bethlehem, ARIJ) and Jordan (EnviroConsult Office, Amman, ECO). The land use classification has been established through a cooperation between ARCS and the Yale University Center for Earth Observation (YUCEO). As a result of the work, the spatial patterns of agricultural and domestic water demand in the Lower Jordan Valley were established, and the spatial dimension of driving forces for water usage and water supply was analyzed. Furthermore, a conceptual model for nitrate leakage (established by HUJ) was translated into a GIS system, and the risks for nitrate pollution of groundwater were quantified. (author)

  7. Segment-based acoustic models for continuous speech recognition

    Science.gov (United States)

    Ostendorf, Mari; Rohlicek, J. R.

    1993-07-01

    This research aims to develop new and more accurate stochastic models for speaker-independent continuous speech recognition, by extending previous work in segment-based modeling and by introducing a new hierarchical approach to representing intra-utterance statistical dependencies. These techniques, which are more costly than traditional approaches because of the large search space associated with higher order models, are made feasible through rescoring a set of HMM-generated N-best sentence hypotheses. We expect these different modeling techniques to result in improved recognition performance over that achieved by current systems, which handle only frame-based observations and assume that these observations are independent given an underlying state sequence. In the fourth quarter of the project, we have completed the following: (1) ported our recognition system to the Wall Street Journal task, a standard task in the ARPA community; (2) developed an initial dependency-tree model of intra-utterance observation correlation; and (3) implemented baseline language model estimation software. Our initial results on the Wall Street Journal task are quite good and represent significantly improved performance over most HMM systems reporting on the Nov. 1992 5k vocabulary test set.

  8. Hydrodynamic modelling of extreme flood events in the Kashmir valley in India

    Science.gov (United States)

    Jain, Manoj; Parvaze, Sabah

    2017-04-01

    Floods are one of the most predominant, costly and deadly hazards of all natural vulnerabilities. Every year, floods exert a heavy toll on human life and property in many parts of the world. The prediction of river stages and discharge during flood extremes plays a vital role in planning structural and non-structural measures of flood management. The predictions are also valuable to prepare the flood inundation maps and river floodplain zoning. In the Kashmir Valley, floods occur mainly and very often in the Jhelum Basin mostly due to extreme precipitation events and rugged mountainous topography of the basin. These floods cause extreme damage to life and property in the valley from time to time. Excessive rainfall, particularly in higher sub-catchments causes the snow to melt resulting in excessive runoff downhill to the streams causing floods in the Kashmir Valley where Srinagar city is located. However, very few hydrological studies have been undertaken for the Jhelum Basin mainly due to non-availability of hydrological data due to very complex mountainous terrain. Therefore, the present study has been conducted to model the extreme flood events in the Jhelum Basin in Kashmir Valley. An integrated NAM and MIKE 11 HD model has been setup for Jhelum basin up to Ram Munshi Bagh gauging site and then four most extreme historical flood events in the time series has been analyzed separately including the most recent and most extreme flood event of 2014. In September 2014, the Kashmir Valley witnessed the most severe flood in the past 60 years due to catastrophic rainfall from 1st to 6th September wherein the valley received unprecedented rainfall of more than 650 mm in just 3 days breaking record of many decades. The MIKE 11 HD and NAM model has been calibrated using 21 years (1985-2005) data and validated using 9 years (2006-2014) data. The efficiency indices of the model for calibration and validation period is 0.749 and 0.792 respectively. The model simulated

  9. Integrated hydrologic model of Pajaro Valley, Santa Cruz and Monterey Counties, California

    Science.gov (United States)

    Hanson, Randall T.; Schmid, Wolfgang; Faunt, Claudia C.; Lear, Jonathan; Lockwood, Brian

    2014-01-01

    Increasing population, agricultural development (including shifts to more water-intensive crops), and climate variability are placing increasingly larger demands on available groundwater resources in the Pajaro Valley, one of the most productive agricultural regions in the world. This study provided a refined conceptual model, geohydrologic framework, and integrated hydrologic model of the Pajaro Valley. The goal of this study was to produce a model capable of being accurate at scales relevant to water management decisions that are being considered in the revision and updates to the Basin Management Plan (BMP). The Pajaro Valley Hydrologic Model (PVHM) was designed to reproduce the most important natural and human components of the hydrologic system and related climatic factors, permitting an accurate assessment of groundwater conditions and processes that can inform the new BMP and help to improve planning for long-term sustainability of water resources. Model development included a revision of the conceptual model of the flow system, reevaluation of the previous model transformed into MODFLOW, implementation of the new geohydrologic model and conceptual model, and calibration of the transient hydrologic model.

  10. Trend in Air Quality of Kathmandu Valley: A Satellite, Observation and Modelling Perspective

    Science.gov (United States)

    Mahapatra, P. S.; Praveen, P. S.; Adhikary, B.; Panday, A. K.; Putero, D.; Bonasoni, P.

    2016-12-01

    Kathmandu (floor area of 340 km2) in Nepal is considered to be a `hot spot' of urban air pollution in South Asia. Its structure as a flat basin surrounded by tall mountains provides a unique case study for analyzing pollution trapped by topography. Only a very small number of cities with similar features have been studied extensively including Mexico and Santiago-de-Chile. This study presents the trend in satellite derived Aerosol Optical Depth (AOD) from MODIS AQUA and TERRA (3x3km, Level 2) over Kathmandu from 2000 to 2015. Trend analysis of AOD shows 35% increase during the study period. Determination of the background pollution would reveal the contribution of only Kathmandu Valley for the observation period. For this, AOD at 1340m altitude outside Kathmandu, but nearby areas were considered as background. This analysis was further supported by investigating AOD at different heights around Kathmandu as well as determining AOD from CALIPSO vertical profiles. These analysis suggest that background AOD contributed 30% in winter and 60% in summer to Kathmandu Valley's observed AOD. Thereafter the background AOD was subtracted from total Kathmandu AOD to determine contribution of only Kathmandu Valley's AOD. Trend analysis of only Kathmandu Valley AOD (subtracting background AOD) suggested an increase of 50% during the study period. Further analysis of Kathmandu's visibility and AOD suggest profound role of background AOD on decreasing visibility. In-situ Black Carbon (BC) mass concentration measurements (BC being used as a proxy for surface observations) at two sites within Kathmandu valley have been analyzed. Kathmandu valley lacks long term trends of ambient air quality measurement data. Therefore, surface observations would be coupled with satellite measurements for understanding the urban air pollution scenario. Modelling studies to estimate the contribution of background pollution to Kathmandu's own pollution as well as the weekend effect on air quality will

  11. Fat segmentation on chest CT images via fuzzy models

    Science.gov (United States)

    Tong, Yubing; Udupa, Jayaram K.; Wu, Caiyun; Pednekar, Gargi; Subramanian, Janani Rajan; Lederer, David J.; Christie, Jason; Torigian, Drew A.

    2016-03-01

    Quantification of fat throughout the body is vital for the study of many diseases. In the thorax, it is important for lung transplant candidates since obesity and being underweight are contraindications to lung transplantation given their associations with increased mortality. Common approaches for thoracic fat segmentation are all interactive in nature, requiring significant manual effort to draw the interfaces between fat and muscle with low efficiency and questionable repeatability. The goal of this paper is to explore a practical way for the segmentation of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) components of chest fat based on a recently developed body-wide automatic anatomy recognition (AAR) methodology. The AAR approach involves 3 main steps: building a fuzzy anatomy model of the body region involving all its major representative objects, recognizing objects in any given test image, and delineating the objects. We made several modifications to these steps to develop an effective solution to delineate SAT/VAT components of fat. Two new objects representing interfaces of SAT and VAT regions with other tissues, SatIn and VatIn are defined, rather than using directly the SAT and VAT components as objects for constructing the models. A hierarchical arrangement of these new and other reference objects is built to facilitate their recognition in the hierarchical order. Subsequently, accurate delineations of the SAT/VAT components are derived from these objects. Unenhanced CT images from 40 lung transplant candidates were utilized in experimentally evaluating this new strategy. Mean object location error achieved was about 2 voxels and delineation error in terms of false positive and false negative volume fractions were, respectively, 0.07 and 0.1 for SAT and 0.04 and 0.2 for VAT.

  12. An innovation model of alumni relationship management: Alumni segmentation analysis

    Directory of Open Access Journals (Sweden)

    Natthawat Rattanamethawong

    2018-01-01

    Full Text Available The purpose of this study was to cluster alumni into segments to better understand the alumni's characteristics, lifestyles, types of behavior, and interests. A sample of 300 university alumni records was used to obtain their respective attribute values consisting of demographics, preferred communication channels, lifestyle, activities/interests, and expectation from university, needed information, donation willingness, and frequency of contact. The researcher used logistic regression and the k-mean clustering technique to analyze the data from the survey. Five segments could be derived from the analysis. Segment 3, the so-called “Mid Age Religious” contained the highest portion while segment 5, the so-called “Elaborate Cohort” had the least portion. Most of the population under these two segments was female. Differences were identified in age, marital status, education, occupation, position, income, experience, and field of work. The Elaborate Cohort segment represented young females having a bachelor degree, with low experience and low income, working for their first employer, and still enjoying being single. Another segment with similar values of attributes as the Elaborate Cohort was segment 1, the so-called “Activist Mainstreamer” whose field of work was computer technology. The segment called “Senior League” consisted of members older than 41 years like the Mid Age Religious segment, however all members were male. The last segment, the so-called “Passionate Learner” had members aged between 31 and 40 years. In conclusion, the results of this study can assist in formulating strategic marketing by alumni associations to satisfy and engage their alumni. Keywords: cluster, data mining, segmentation analysis, university alumni

  13. Correction tool for Active Shape Model based lumbar muscle segmentation.

    Science.gov (United States)

    Valenzuela, Waldo; Ferguson, Stephen J; Ignasiak, Dominika; Diserens, Gaelle; Vermathen, Peter; Boesch, Chris; Reyes, Mauricio

    2015-08-01

    In the clinical environment, accuracy and speed of the image segmentation process plays a key role in the analysis of pathological regions. Despite advances in anatomic image segmentation, time-effective correction tools are commonly needed to improve segmentation results. Therefore, these tools must provide faster corrections with a low number of interactions, and a user-independent solution. In this work we present a new interactive correction method for correcting the image segmentation. Given an initial segmentation and the original image, our tool provides a 2D/3D environment, that enables 3D shape correction through simple 2D interactions. Our scheme is based on direct manipulation of free form deformation adapted to a 2D environment. This approach enables an intuitive and natural correction of 3D segmentation results. The developed method has been implemented into a software tool and has been evaluated for the task of lumbar muscle segmentation from Magnetic Resonance Images. Experimental results show that full segmentation correction could be performed within an average correction time of 6±4 minutes and an average of 68±37 number of interactions, while maintaining the quality of the final segmentation result within an average Dice coefficient of 0.92±0.03.

  14. Segmenting Continuous Motions with Hidden Semi-markov Models and Gaussian Processes

    Directory of Open Access Journals (Sweden)

    Tomoaki Nakamura

    2017-12-01

    Full Text Available Humans divide perceived continuous information into segments to facilitate recognition. For example, humans can segment speech waves into recognizable morphemes. Analogously, continuous motions are segmented into recognizable unit actions. People can divide continuous information into segments without using explicit segment points. This capacity for unsupervised segmentation is also useful for robots, because it enables them to flexibly learn languages, gestures, and actions. In this paper, we propose a Gaussian process-hidden semi-Markov model (GP-HSMM that can divide continuous time series data into segments in an unsupervised manner. Our proposed method consists of a generative model based on the hidden semi-Markov model (HSMM, the emission distributions of which are Gaussian processes (GPs. Continuous time series data is generated by connecting segments generated by the GP. Segmentation can be achieved by using forward filtering-backward sampling to estimate the model's parameters, including the lengths and classes of the segments. In an experiment using the CMU motion capture dataset, we tested GP-HSMM with motion capture data containing simple exercise motions; the results of this experiment showed that the proposed GP-HSMM was comparable with other methods. We also conducted an experiment using karate motion capture data, which is more complex than exercise motion capture data; in this experiment, the segmentation accuracy of GP-HSMM was 0.92, which outperformed other methods.

  15. A clinically applicable six-segmented foot model.

    Science.gov (United States)

    De Mits, Sophie; Segers, Veerle; Woodburn, Jim; Elewaut, Dirk; De Clercq, Dirk; Roosen, Philip

    2012-04-01

    We describe a multi-segmented foot model comprising lower leg, rearfoot, midfoot, lateral forefoot, medial forefoot, and hallux for routine use in a clinical setting. The Ghent Foot Model describes the kinematic patterns of functional units of the foot, especially the midfoot, to investigate patient populations where midfoot deformation or dysfunction is an important feature, for example, rheumatoid arthritis patients. Data were obtained from surface markers by a 6 camera motion capture system at 500 Hz. Ten healthy subjects walked barefoot along a 12 m walkway at self-selected speed. Joint angles (rearfoot to shank, midfoot to rearfoot, lateral and medial forefoot to midfoot, and hallux to medial forefoot) in the sagittal, frontal, and transverse plane are reported according to anatomically based reference frames. These angles were calculated and reported during the foot rollover phases in stance, detected by synchronized plantar pressure measurements. Repeated measurements of each subject revealed low intra-subject variability, varying between 0.7° and 2.3° for the minimum values, between 0.5° and 2.1° for the maximum values, and between 0.8° and 5.8° for the ROM. The described movement patterns were repeatable and consistent with biomechanical and clinical knowledge. As such, the Ghent Foot model permits intersegment, in vivo motion measurement of the foot, which is crucial for both clinical and research applications. Copyright © 2011 Orthopaedic Research Society.

  16. Ground-Water Flow Model for the Spokane Valley-Rathdrum Prairie Aquifer, Spokane County, Washington, and Bonner and Kootenai Counties, Idaho

    Science.gov (United States)

    Hsieh, Paul A.; Barber, Michael E.; Contor, Bryce A.; Hossain, Md. Akram; Johnson, Gary S.; Jones, Joseph L.; Wylie, Allan H.

    2007-01-01

    approximately 326 square miles. For the most part, the model extent coincides with the 2005 revised extent of the Spokane Valley-Rathdrum Prairie aquifer as defined in a previous report. However, the model excludes Spirit and Hoodoo Valleys because of uncertainties about the ground-water flow directions in those valleys and the degree of hydraulic connection between the valleys and northern Rathdrum Prairie. The SVRP aquifer is considered to be a single hydrogeologic unit except in Hillyard Trough and the Little Spokane River Arm. In those areas, a continuous clay layer divides the aquifer into an upper, unconfined unit and a lower, confined unit. The model includes all known components of inflows to and outflows from the aquifer. Inflows to the SVRP aquifer include (1) recharge from precipitation, (2) inflows from tributary basins and adjacent uplands, (3) subsurface seepage and surface overflows from lakes that border the aquifer, (4) flow from losing segments of the Spokane River to the aquifer, (5) return percolation from irrigation, and (6) effluent from septic systems. Outflows from the SVRP aquifer include (1) ground-water withdrawals from wells, (2) flow from the aquifer to gaining segments of the Spokane River, (3) aquifer discharge to the Little Spokane River, and (4) subsurface outflow from the lower unit at the western limit of the model area near Long Lake. These inflow and outflow components are represented in the model by using MODFLOW-2000 packages. The parameter-estimation program PEST was used to calibrate the SVRP aquifer model. PEST implements a nonlinear least-squares regression method to estimate model parameters so that the differences between measured and simulated quantities are minimized with respect to an optimal criterion. Calibration data include 1,573 measurements of water levels and 313 measurements of streamflow gains and losses along segments of the Spokane and Little Spokane Rivers. Model parameters estimated during calib

  17. Statistical shape (ASM) and appearance (AAM) models for the segmentation of the cerebellum in fetal ultrasound

    Science.gov (United States)

    Reyes López, Misael; Arámbula Cosío, Fernando

    2017-11-01

    The cerebellum is an important structure to determine the gestational age of the fetus, moreover most of the abnormalities it presents are related to growth disorders. In this work, we present the results of the segmentation of the fetal cerebellum applying statistical shape and appearance models. Both models were tested on ultrasound images of the fetal brain taken from 23 pregnant women, between 18 and 24 gestational weeks. The accuracy results obtained on 11 ultrasound images show a mean Hausdorff distance of 6.08 mm between the manual segmentation and the segmentation using active shape model, and a mean Hausdorff distance of 7.54 mm between the manual segmentation and the segmentation using active appearance model. The reported results demonstrate that the active shape model is more robust in the segmentation of the fetal cerebellum in ultrasound images.

  18. A label field fusion bayesian model and its penalized maximum rand estimator for image segmentation.

    Science.gov (United States)

    Mignotte, Max

    2010-06-01

    This paper presents a novel segmentation approach based on a Markov random field (MRF) fusion model which aims at combining several segmentation results associated with simpler clustering models in order to achieve a more reliable and accurate segmentation result. The proposed fusion model is derived from the recently introduced probabilistic Rand measure for comparing one segmentation result to one or more manual segmentations of the same image. This non-parametric measure allows us to easily derive an appealing fusion model of label fields, easily expressed as a Gibbs distribution, or as a nonstationary MRF model defined on a complete graph. Concretely, this Gibbs energy model encodes the set of binary constraints, in terms of pairs of pixel labels, provided by each segmentation results to be fused. Combined with a prior distribution, this energy-based Gibbs model also allows for definition of an interesting penalized maximum probabilistic rand estimator with which the fusion of simple, quickly estimated, segmentation results appears as an interesting alternative to complex segmentation models existing in the literature. This fusion framework has been successfully applied on the Berkeley image database. The experiments reported in this paper demonstrate that the proposed method is efficient in terms of visual evaluation and quantitative performance measures and performs well compared to the best existing state-of-the-art segmentation methods recently proposed in the literature.

  19. Topoclimatic modeling for minimum temperature prediction at a regional scale in the Central Valley of Chile

    International Nuclear Information System (INIS)

    Santibáñez, F.; Morales, L.; Fuente, J. de la; Cellier, P.; Huete, A.

    1997-01-01

    Spring frost may strongly affect fruit production in the Central Valley of Chile. Minimum temperatures are spatially variable owing to topography and soil conditions. A methodology for forecasting minimum temperature at a regional scale in the Central Valley of Chile, integrating spatial variability of temperature under radiative frost conditions, has been developed. It uses simultaneously a model for forecasting minimum temperatures at a reference station using air temperature and humidity measured at 6 pm, and topoclimatic models, based on satellite infra-red imagery (NOAA/AVHRR) and a digital elevation model, to extend the prediction at a regional scale. The methodological developments were integrated in a geographic information system for geo referencing of a meteorological station with satellite imagery and modeled output. This approach proved to be a useful tool for short range (12 h) minimum temperature prediction by generating thermal images over the Central Valley of Chile. It may also be used as a tool for frost risk assessment, in order to adapt production to local climatological conditions. (author)

  20. Green River air quality model development: meteorological and tracer data, July/August 1982 field study in Brush Valley, Colorado

    Energy Technology Data Exchange (ETDEWEB)

    Whiteman, C.D.; Lee, R.N.; Orgill, M.M.; Zak, B.D.

    1984-06-01

    Meteorological and atmospheric tracer studies were conducted during a 3-week period in July and August of 1982 in the Brush Creek Valley of northwestern Colorado. The objective of the field experiments was to obtain data to evaluate a model, called VALMET, developed at PNL to predict dispersion of air pollutants released from an elevated stack located within a deep mountain valley in the post-sunrise temperature inversion breakup period. Three tracer experiments were conducted in the valley during the 2-week period. In these experiments, sulfur hexafluoride (SF/sub 6/) was released from a height of approximately 100 m, beginning before sunrise and continuing until the nocturnal down-valley winds reversed several hours after sunrise. Dispersion of the sulfur hexafluoride after release was evaluated by measuring SF/sub 6/ concentrations in ambient air samples taken from sampling devices operated within the valley up to about 8 km down valley from the source. An instrumented research aircraft was also used to measure concentrations in and above the valley. Tracer samples were collected using a network of radio-controlled bag sampling stations, two manually operated gas chromatographs, a continuous SF/sub 6/ monitor, and a vertical SF/sub 6/ profiler. In addition, basic meteorological data were collected during the tracer experiments. Frequent profiles of vertical wind and temperature structure were obtained with tethered balloons operated at the release site and at a site 7.7 km down the valley from the release site. 10 references, 63 figures, 50 tables.

  1. 3D Building Models Segmentation Based on K-Means++ Cluster Analysis

    Science.gov (United States)

    Zhang, C.; Mao, B.

    2016-10-01

    3D mesh model segmentation is drawing increasing attentions from digital geometry processing field in recent years. The original 3D mesh model need to be divided into separate meaningful parts or surface patches based on certain standards to support reconstruction, compressing, texture mapping, model retrieval and etc. Therefore, segmentation is a key problem for 3D mesh model segmentation. In this paper, we propose a method to segment Collada (a type of mesh model) 3D building models into meaningful parts using cluster analysis. Common clustering methods segment 3D mesh models by K-means, whose performance heavily depends on randomized initial seed points (i.e., centroid) and different randomized centroid can get quite different results. Therefore, we improved the existing method and used K-means++ clustering algorithm to solve this problem. Our experiments show that K-means++ improves both the speed and the accuracy of K-means, and achieve good and meaningful results.

  2. 3D BUILDING MODELS SEGMENTATION BASED ON K-MEANS++ CLUSTER ANALYSIS

    Directory of Open Access Journals (Sweden)

    C. Zhang

    2016-10-01

    Full Text Available 3D mesh model segmentation is drawing increasing attentions from digital geometry processing field in recent years. The original 3D mesh model need to be divided into separate meaningful parts or surface patches based on certain standards to support reconstruction, compressing, texture mapping, model retrieval and etc. Therefore, segmentation is a key problem for 3D mesh model segmentation. In this paper, we propose a method to segment Collada (a type of mesh model 3D building models into meaningful parts using cluster analysis. Common clustering methods segment 3D mesh models by K-means, whose performance heavily depends on randomized initial seed points (i.e., centroid and different randomized centroid can get quite different results. Therefore, we improved the existing method and used K-means++ clustering algorithm to solve this problem. Our experiments show that K-means++ improves both the speed and the accuracy of K-means, and achieve good and meaningful results.

  3. Establishing experimental model of human internal carotid artery siphon segment in canine common carotid artery

    International Nuclear Information System (INIS)

    Cui Xuee; Li Minghua; Wang Yongli; Cheng Yingsheng; Li Wenbin

    2005-01-01

    Objective: To study the feasibility of establishing experimental model of human internal carotid artery siphon segment in canine common carotid artery (CCA) by end-to-end anastomoses of one side common carotid artery segment with the other side common carotid artery. Methods: Surgical techniques were used to make siphon model in 8 canines. One side CCA was taken as the parent artery and anastomosing with the cut off contra-lateral CCA segment which has passed through within the S-shaped glass tube. Two weeks after the creation of models angiography showed the model siphons were patent. Results: Experimental models of human internal carotid artery siphon segment were successfully made in all 8 dogs. Conclusions: It is practically feasible to establish experimental canine common carotid artery models of siphon segment simulating human internal carotid artery. (authors)

  4. Linked statistical shape models for multi-modal segmentation: application to prostate CT-MR segmentation in radiotherapy planning

    Science.gov (United States)

    Chowdhury, Najeeb; Chappelow, Jonathan; Toth, Robert; Kim, Sung; Hahn, Stephen; Vapiwala, Neha; Lin, Haibo; Both, Stefan; Madabhushi, Anant

    2011-03-01

    We present a novel framework for building a linked statistical shape model (LSSM), a statistical shape model (SSM) that links the shape variation of a structure of interest (SOI) across multiple imaging modalities. This framework is particularly relevant in scenarios where accurate delineations of a SOI's boundary on one of the modalities may not be readily available, or difficult to obtain, for training a SSM. We apply the LSSM in the context of multi-modal prostate segmentation for radiotherapy planning, where we segment the prostate on MRI and CT simultaneously. Prostate capsule segmentation is a critical step in prostate radiotherapy planning, where dose plans have to be formulated on CT. Since accurate delineations of the prostate boundary are very difficult to obtain on CT, pre-treatment MRI is now beginning to be acquired at several medical centers. Delineation of the prostate on MRI is acknowledged as being significantly simpler to do compared to CT. Hence, our framework incorporates multi-modal registration of MRI and CT to map 2D boundary delineations of prostate (obtained from an expert radiation oncologist) on MR training images onto corresponding CT images. The delineations of the prostate capsule on MRI and CT allows for 3D reconstruction of the prostate shape which facilitates the building of the LSSM. We acquired 7 MRI-CT patient studies and used the leave-one-out strategy to train and evaluate our LSSM (fLSSM), built using expert ground truth delineations on MRI and MRI-CT fusion derived capsule delineations on CT. A unique attribute of our fLSSM is that it does not require expert delineations of the capsule on CT. In order to perform prostate MRI segmentation using the fLSSM, we employed a regionbased approach where we deformed the evolving prostate boundary to optimize a mutual information based cost criterion, which took into account region-based intensity statistics of the image being segmented. The final prostate segmentation was then

  5. A comparative empirical analysis of statistical models for evaluating highway segment crash frequency

    Directory of Open Access Journals (Sweden)

    Bismark R.D.K. Agbelie

    2016-08-01

    Full Text Available The present study conducted an empirical highway segment crash frequency analysis on the basis of fixed-parameters negative binomial and random-parameters negative binomial models. Using a 4-year data from a total of 158 highway segments, with a total of 11,168 crashes, the results from both models were presented, discussed, and compared. About 58% of the selected variables produced normally distributed parameters across highway segments, while the remaining produced fixed parameters. The presence of a noise barrier along a highway segment would increase mean annual crash frequency by 0.492 for 88.21% of the highway segments, and would decrease crash frequency for 11.79% of the remaining highway segments. Besides, the number of vertical curves per mile along a segment would increase mean annual crash frequency by 0.006 for 84.13% of the highway segments, and would decrease crash frequency for 15.87% of the remaining highway segments. Thus, constraining the parameters to be fixed across all highway segments would lead to an inaccurate conclusion. Although, the estimated parameters from both models showed consistency in direction, the magnitudes were significantly different. Out of the two models, the random-parameters negative binomial model was found to be statistically superior in evaluating highway segment crashes compared with the fixed-parameters negative binomial model. On average, the marginal effects from the fixed-parameters negative binomial model were observed to be significantly overestimated compared with those from the random-parameters negative binomial model.

  6. A Model for the Sounding Rocket Measurement on an Ionospheric E-F Valley at the Hainan Low Latitude Station

    International Nuclear Information System (INIS)

    Wang Zheng; Shi Jiankui; Guan Yibing; Liu Chao; Zhu Guangwu; Torkar Klaus; Fredrich Martin

    2014-01-01

    To understand the physics of an ionospheric E-F valley, a new overlapping three-Chapman-layer model is developed to interpret the sounding rocket measurement in the morning (sunrise) on May 7, 2011 at the Hainan low latitude ionospheric observation station (19.5°N, 109.1°E). From our model, the valley width, depth and height are 43.0 km, 62.9% and 121.0 km, respectively. From the sounding rocket observation, the valley width, depth and height are 42.2 km, 47.0% and 123.5 km, respectively. The model results are well consistent with the sounding rocket observation. The observed E-F valley at Hainan station is very wide and deep, and rapid development of the photochemical process in the ionosphere should be the underlying reason. (astrophysics and space plasma)

  7. Automatic segmentation for brain MR images via a convex optimized segmentation and bias field correction coupled model.

    Science.gov (United States)

    Chen, Yunjie; Zhao, Bo; Zhang, Jianwei; Zheng, Yuhui

    2014-09-01

    Accurate segmentation of magnetic resonance (MR) images remains challenging mainly due to the intensity inhomogeneity, which is also commonly known as bias field. Recently active contour models with geometric information constraint have been applied, however, most of them deal with the bias field by using a necessary pre-processing step before segmentation of MR data. This paper presents a novel automatic variational method, which can segment brain MR images meanwhile correcting the bias field when segmenting images with high intensity inhomogeneities. We first define a function for clustering the image pixels in a smaller neighborhood. The cluster centers in this objective function have a multiplicative factor that estimates the bias within the neighborhood. In order to reduce the effect of the noise, the local intensity variations are described by the Gaussian distributions with different means and variances. Then, the objective functions are integrated over the entire domain. In order to obtain the global optimal and make the results independent of the initialization of the algorithm, we reconstructed the energy function to be convex and calculated it by using the Split Bregman theory. A salient advantage of our method is that its result is independent of initialization, which allows robust and fully automated application. Our method is able to estimate the bias of quite general profiles, even in 7T MR images. Moreover, our model can also distinguish regions with similar intensity distribution with different variances. The proposed method has been rigorously validated with images acquired on variety of imaging modalities with promising results. Copyright © 2014 Elsevier Inc. All rights reserved.

  8. A model-based Bayesian framework for ECG beat segmentation

    International Nuclear Information System (INIS)

    Sayadi, O; Shamsollahi, M B

    2009-01-01

    The study of electrocardiogram (ECG) waveform amplitudes, timings and patterns has been the subject of intense research, for it provides a deep insight into the diagnostic features of the heart's functionality. In some recent works, a Bayesian filtering paradigm has been proposed for denoising and compression of ECG signals. In this paper, it is shown that this framework may be effectively used for ECG beat segmentation and extraction of fiducial points. Analytic expressions for the determination of points and intervals are derived and evaluated on various real ECG signals. Simulation results show that the method can contribute to and enhance the clinical ECG beat segmentation performance

  9. A conceptual geochemical model of the geothermal system at Surprise Valley, CA

    Science.gov (United States)

    Fowler, Andrew P. G.; Ferguson, Colin; Cantwell, Carolyn A.; Zierenberg, Robert A.; McClain, James; Spycher, Nicolas; Dobson, Patrick

    2018-03-01

    Characterizing the geothermal system at Surprise Valley (SV), northeastern California, is important for determining the sustainability of the energy resource, and mitigating hazards associated with hydrothermal eruptions that last occurred in 1951. Previous geochemical studies of the area attempted to reconcile different hot spring compositions on the western and eastern sides of the valley using scenarios of dilution, equilibration at low temperatures, surface evaporation, and differences in rock type along flow paths. These models were primarily supported using classical geothermometry methods, and generally assumed that fluids in the Lake City mud volcano area on the western side of the valley best reflect the composition of a deep geothermal fluid. In this contribution, we address controls on hot spring compositions using a different suite of geochemical tools, including optimized multicomponent geochemistry (GeoT) models, hot spring fluid major and trace element measurements, mineralogical observations, and stable isotope measurements of hot spring fluids and precipitated carbonates. We synthesize the results into a conceptual geochemical model of the Surprise Valley geothermal system, and show that high-temperature (quartz, Na/K, Na/K/Ca) classical geothermometers fail to predict maximum subsurface temperatures because fluids re-equilibrated at progressively lower temperatures during outflow, including in the Lake City area. We propose a model where hot spring fluids originate as a mixture between a deep thermal brine and modern meteoric fluids, with a seasonally variable mixing ratio. The deep brine has deuterium values at least 3 to 4‰ lighter than any known groundwater or high-elevation snow previously measured in and adjacent to SV, suggesting it was recharged during the Pleistocene when meteoric fluids had lower deuterium values. The deuterium values and compositional characteristics of the deep brine have only been identified in thermal springs and

  10. Snake Model Based on Improved Genetic Algorithm in Fingerprint Image Segmentation

    Directory of Open Access Journals (Sweden)

    Mingying Zhang

    2016-12-01

    Full Text Available Automatic fingerprint identification technology is a quite mature research field in biometric identification technology. As the preprocessing step in fingerprint identification, fingerprint segmentation can improve the accuracy of fingerprint feature extraction, and also reduce the time of fingerprint preprocessing, which has a great significance in improving the performance of the whole system. Based on the analysis of the commonly used methods of fingerprint segmentation, the existing segmentation algorithm is improved in this paper. The snake model is used to segment the fingerprint image. Additionally, it is improved by using the global optimization of the improved genetic algorithm. Experimental results show that the algorithm has obvious advantages both in the speed of image segmentation and in the segmentation effect.

  11. Segment-based Eyring-Wilson viscosity model for polymer solutions

    International Nuclear Information System (INIS)

    Sadeghi, Rahmat

    2005-01-01

    A theory-based model is presented for correlating viscosity of polymer solutions and is based on the segment-based Eyring mixture viscosity model as well as the segment-based Wilson model for describing deviations from ideality. The model has been applied to several polymer solutions and the results show that it is reliable both for correlation and prediction of the viscosity of polymer solutions at different molar masses and temperature of the polymer

  12. Range sections as rock models for intensity rock scene segmentation

    CSIR Research Space (South Africa)

    Mkwelo, S

    2007-11-01

    Full Text Available This paper presents another approach to segmenting a scene of rocks on a conveyor belt for the purposes of measuring rock size. Rock size estimation instruments are used to monitor, optimize and control milling and crushing in the mining industry...

  13. Contourlet-based active contour model for PET image segmentation

    NARCIS (Netherlands)

    Abdoli, M.; Dierckx, R. A. J. O.; Zaidi, H.

    Purpose: PET-guided radiation therapy treatment planning, clinical diagnosis, assessment of tumor growth, and therapy response rely on the accurate delineation of the tumor volume and quantification of tracer uptake. Most PET image segmentation techniques proposed thus far are suboptimal in the

  14. Simulation And Forecasting of Daily Pm10 Concentrations Using Autoregressive Models In Kagithane Creek Valley, Istanbul

    Science.gov (United States)

    Ağaç, Kübra; Koçak, Kasım; Deniz, Ali

    2015-04-01

    A time series approach using autoregressive model (AR), moving average model (MA) and seasonal autoregressive integrated moving average model (SARIMA) were used in this study to simulate and forecast daily PM10 concentrations in Kagithane Creek Valley, Istanbul. Hourly PM10 concentrations have been measured in Kagithane Creek Valley between 2010 and 2014 periods. Bosphorus divides the city in two parts as European and Asian parts. The historical part of the city takes place in Golden Horn. Our study area Kagithane Creek Valley is connected with this historical part. The study area is highly polluted because of its topographical structure and industrial activities. Also population density is extremely high in this site. The dispersion conditions are highly poor in this creek valley so it is necessary to calculate PM10 levels for air quality and human health. For given period there were some missing PM10 concentration values so to make an accurate calculations and to obtain exact results gap filling method was applied by Singular Spectrum Analysis (SSA). SSA is a new and efficient method for gap filling and it is an state-of-art modeling. SSA-MTM Toolkit was used for our study. SSA is considered as a noise reduction algorithm because it decomposes an original time series to trend (if exists), oscillatory and noise components by way of a singular value decomposition. The basic SSA algorithm has stages of decomposition and reconstruction. For given period daily and monthly PM10 concentrations were calculated and episodic periods are determined. Long term and short term PM10 concentrations were analyzed according to European Union (EU) standards. For simulation and forecasting of high level PM10 concentrations, meteorological data (wind speed, pressure and temperature) were used to see the relationship between daily PM10 concentrations. Fast Fourier Transformation (FFT) was also applied to the data to see the periodicity and according to these periods models were built

  15. Sustainability knowledge using “AKASA” model among architecture students from Klang Valley private universities, Malaysia.

    Science.gov (United States)

    Kuppusamy, Sivaraman; Faris Khamidi, Mohd; Sheng, Lee Xia; Salvi Mari, Tamil

    2017-12-01

    The study intend to investigate sustainability knowledge using “AKASA” model. This model comprises all the literacy level which is the awareness, knowledge, attitude, skills and action. 234 students from 5 selected private universities were surveyed using questionnaires. Students were specifically selected from year 2 and year 3 from private universities in Klang valley, Malaysia. The study intends to investigate the environmental literacy level specifically the knowledge variable. The parametric study was conducted with descriptive analysis and the results shows that the environmental knowledge is at high level compared to other environmental literacy variables among year 2, year 3 and combine year 2 and year 3.

  16. The Glasgow-Maastricht foot model, evaluation of a 26 segment kinematic model of the foot

    OpenAIRE

    Oosterwaal, Michiel; Carbes, Sylvain; Telfer, Scott; Woodburn, James; T?rholm, S?ren; Al-Munajjed, Amir A.; van Rhijn, Lodewijk; Meijer, Kenneth

    2016-01-01

    Background Accurately measuring of intrinsic foot kinematics using skin mounted markers is difficult, limited in part by the physical dimensions of the foot. Existing kinematic foot models solve this problem by combining multiple bones into idealized rigid segments. This study presents a novel foot model that allows the motion of the 26 bones to be individually estimated via a combination of partial joint constraints and coupling the motion of separate joints using kinematic rhythms. Methods ...

  17. Simultaneous Whole-Brain Segmentation and White Matter Lesion Detection Using Contrast-Adaptive Probabilistic Models

    DEFF Research Database (Denmark)

    Puonti, Oula; Van Leemput, Koen

    2016-01-01

    In this paper we propose a new generative model for simultaneous brain parcellation and white matter lesion segmentation from multi-contrast magnetic resonance images. The method combines an existing whole-brain segmentation technique with a novel spatial lesion model based on a convolutional...... restricted Boltzmann machine. Unlike current state-of-the-art lesion detection techniques based on discriminative modeling, the proposed method is not tuned to one specific scanner or imaging protocol, and simultaneously segments dozens of neuroanatomical structures. Experiments on a public benchmark dataset...... in multiple sclerosis indicate that the method’s lesion segmentation accuracy compares well to that of the current state-of-the-art in the field, while additionally providing robust whole-brain segmentations....

  18. A Composite Model of Wound Segmentation Based on Traditional Methods and Deep Neural Networks

    Directory of Open Access Journals (Sweden)

    Fangzhao Li

    2018-01-01

    Full Text Available Wound segmentation plays an important supporting role in the wound observation and wound healing. Current methods of image segmentation include those based on traditional process of image and those based on deep neural networks. The traditional methods use the artificial image features to complete the task without large amounts of labeled data. Meanwhile, the methods based on deep neural networks can extract the image features effectively without the artificial design, but lots of training data are required. Combined with the advantages of them, this paper presents a composite model of wound segmentation. The model uses the skin with wound detection algorithm we designed in the paper to highlight image features. Then, the preprocessed images are segmented by deep neural networks. And semantic corrections are applied to the segmentation results at last. The model shows a good performance in our experiment.

  19. Integrated 3D density modelling and segmentation of the Dead Sea Transform

    Science.gov (United States)

    Götze, H.-J.; El-Kelani, R.; Schmidt, S.; Rybakov, M.; Hassouneh, M.; Förster, H.-J.; Ebbing, J.

    2007-04-01

    A 3D interpretation of the newly compiled Bouguer anomaly in the area of the “Dead Sea Rift” is presented. A high-resolution 3D model constrained with the seismic results reveals the crustal thickness and density distribution beneath the Arava/Araba Valley (AV), the region between the Dead Sea and the Gulf of Aqaba/Elat. The Bouguer anomalies along the axial portion of the AV, as deduced from the modelling results, are mainly caused by deep-seated sedimentary basins ( D > 10 km). An inferred zone of intrusion coincides with the maximum gravity anomaly on the eastern flank of the AV. The intrusion is displaced at different sectors along the NNW-SSE direction. The zone of maximum crustal thinning (depth 30 km) is attained in the western sector at the Mediterranean. The southeastern plateau, on the other hand, shows by far the largest crustal thickness of the region (38-42 km). Linked to the left lateral movement of approx. 105 km at the boundary between the African and Arabian plate, and constrained with recent seismic data, a small asymmetric topography of the Moho beneath the Dead Sea Transform (DST) was modelled. The thickness and density of the crust suggest that the AV is underlain by continental crust. The deep basins, the relatively large intrusion and the asymmetric topography of the Moho lead to the conclusion that a small-scale asthenospheric upwelling could be responsible for the thinning of the crust and subsequent creation of the Dead Sea basin during the left lateral movement. A clear segmentation along the strike of the DST was obtained by curvature analysis: the northern part in the neighbourhood of the Dead Sea is characterised by high curvature of the residual gravity field. Flexural rigidity calculations result in very low values of effective elastic lithospheric thickness ( t e < 5 km). This points to decoupling of crust in the Dead Sea area. In the central, AV the curvature is less pronounced and t e increases to approximately 10 km

  20. Market segment derivation and profiling via a finite mixture model framework

    NARCIS (Netherlands)

    Wedel, M; Desarbo, WS

    The Marketing literature has shown how difficult it is to profile market segments derived with finite mixture models. especially using traditional descriptor variables (e.g., demographics). Such profiling is critical for the proper implementation of segmentation strategy. we propose a new finite

  1. Modelling the internal boundary layer over the lower fraser valley, British Columbia

    Energy Technology Data Exchange (ETDEWEB)

    Batchvarova, E. [National Inst. of Meteorology and Hydrology, Sofia (Bulgaria); Steyn, D. [Univ. of British Columbia, Dept. of Geography, Vancouver (Canada); Cai, X. [Univ. of Birmingham, School of Geography, Edgbaston (United Kingdom); Gryning, S.E. [Risoe National Lab., Roskilde (Denmark); Baldi, M. [Inst. for Atmospheric Physics, IFA-CNR, Rome (Italy)

    1997-10-01

    In this study we use the very extensive data-set on temporal and spatial structure of the internal boundary layer on the Lower Faser Valley, Canada, collected during the so-called Pacific `93 field campaign, to study the ability of the simple applied model by Gryning and Batchvarova (1996) and the CSU-RAMS meso-scale model summarised in Pielke et al. (1992) to describe the development and variability of the internal boundary layer depth during the course of a day. Given the complexity of topography, coastline and land-use in the Lower Fraser Valley region, both models perform remarkably well. The simple applied model performs extremely well, given its simplicity. It is clear that correct specification of spatially resolved surface sensible heat flux and wind field are crucial to the success of this model which can be operated at very fine spatial resolution. The 3D model performs extremely well, though it too must capture the local wind field correctly for complete success. Its limited horizontal resolution results in strongly smoothed internal boundary layer height fields. (LN)

  2. Unraveling Tropical Mountain Hydroclimatology by Coupling Autonomous Sensor Observations and Climate Modeling: Llanganuco Valley, Cordillera Blanca, Peru.

    Science.gov (United States)

    Hellstrom, R. A.; Fernandez, A.; Mark, B. G.; Covert, J. M.

    2015-12-01

    Northern Peru will face critical water resource issues in the near future as permanent ice retreats. Much of current global and regional climate research neglects the meteorological forcing of lapse rates and valley wind dynamics on critical components of the Peruvian Andes' water-cycle. In 2004 and 2005 we installed an autonomous sensor network (ASN) within the glacierized Llanganuco Valley, Cordillera Blanca (9°S), consisting of discrete, cost-effective, automatic temperature loggers located along the valley axis and anchored by two automatic weather stations. Comparisons of these embedded atmospheric measurements from the ASN and climate modeling (CM) by dynamical downscaling using the Weather Research and Forecasting (WRF) model elucidate distinct diurnal and seasonal characteristics of the mountain valley winds and lapse rates. Wind, temperature, humidity, and cloud simulations by WRF suggest that thermally driven valley winds converging with easterly flow aloft enhance late afternoon and evening cloud development which helps explain detected nocturnal precipitation maxima measured by the ASN. We attribute sustained evapotranspiration (ET), as estimated by the FAO-56 Penman-Monteith model, to an abundance of glacial melt-water during the dry season and strong pre-noon solar heating during the wet season. Furthermore, the extreme diurnal variability of along-valley-axis lapse rates and valley wind detected from ground observations and confirmed by dynamical downscaling demonstrate the importance of realistic scale parameterizations of the boundary layer to improve regional CM projections in mountainous regions. Our findings portray ET as an integral yet poorly represented process in Andean hydroclimatology. We show that coupling ASN and CM can improve understanding of multi-scale atmospheric and associated hydrological processes in mountain valleys.

  3. Label fusion based brain MR image segmentation via a latent selective model

    Science.gov (United States)

    Liu, Gang; Guo, Xiantang; Zhu, Kai; Liao, Hengxu

    2018-04-01

    Multi-atlas segmentation is an effective approach and increasingly popular for automatically labeling objects of interest in medical images. Recently, segmentation methods based on generative models and patch-based techniques have become the two principal branches of label fusion. However, these generative models and patch-based techniques are only loosely related, and the requirement for higher accuracy, faster segmentation, and robustness is always a great challenge. In this paper, we propose novel algorithm that combines the two branches using global weighted fusion strategy based on a patch latent selective model to perform segmentation of specific anatomical structures for human brain magnetic resonance (MR) images. In establishing this probabilistic model of label fusion between the target patch and patch dictionary, we explored the Kronecker delta function in the label prior, which is more suitable than other models, and designed a latent selective model as a membership prior to determine from which training patch the intensity and label of the target patch are generated at each spatial location. Because the image background is an equally important factor for segmentation, it is analyzed in label fusion procedure and we regard it as an isolated label to keep the same privilege between the background and the regions of interest. During label fusion with the global weighted fusion scheme, we use Bayesian inference and expectation maximization algorithm to estimate the labels of the target scan to produce the segmentation map. Experimental results indicate that the proposed algorithm is more accurate and robust than the other segmentation methods.

  4. Ecological niche modelling of Rift Valley fever virus vectors in Baringo, Kenya

    Directory of Open Access Journals (Sweden)

    Alfred O. Ochieng

    2016-11-01

    Full Text Available Background: Rift Valley fever (RVF is a vector-borne zoonotic disease that has an impact on human health and animal productivity. Here, we explore the use of vector presence modelling to predict the distribution of RVF vector species under climate change scenario to demonstrate the potential for geographic spread of Rift Valley fever virus (RVFV. Objectives: To evaluate the effect of climate change on RVF vector distribution in Baringo County, Kenya, with an aim of developing a risk map for spatial prediction of RVF outbreaks. Methodology: The study used data on vector presence and ecological niche modelling (MaxEnt algorithm to predict the effect of climatic change on habitat suitability and the spatial distribution of RVF vectors in Baringo County. Data on species occurrence were obtained from longitudinal sampling of adult mosquitoes and larvae in the study area. We used present (2000 and future (2050 Bioclim climate databases to model the vector distribution. Results: Model results predicted potential suitable areas with high success rates for Culex quinquefasciatus, Culex univitattus, Mansonia africana, and Mansonia uniformis. Under the present climatic conditions, the lowlands were found to be highly suitable for all the species. Future climatic conditions indicate an increase in the spatial distribution of Cx. quinquefasciatus and M. africana. Model performance was statistically significant. Conclusion: Soil types, precipitation in the driest quarter, precipitation seasonality, and isothermality showed the highest predictive potential for the four species.

  5. Application of a semi-automatic cartilage segmentation method for biomechanical modeling of the knee joint.

    Science.gov (United States)

    Liukkonen, Mimmi K; Mononen, Mika E; Tanska, Petri; Saarakkala, Simo; Nieminen, Miika T; Korhonen, Rami K

    2017-10-01

    Manual segmentation of articular cartilage from knee joint 3D magnetic resonance images (MRI) is a time consuming and laborious task. Thus, automatic methods are needed for faster and reproducible segmentations. In the present study, we developed a semi-automatic segmentation method based on radial intensity profiles to generate 3D geometries of knee joint cartilage which were then used in computational biomechanical models of the knee joint. Six healthy volunteers were imaged with a 3T MRI device and their knee cartilages were segmented both manually and semi-automatically. The values of cartilage thicknesses and volumes produced by these two methods were compared. Furthermore, the influences of possible geometrical differences on cartilage stresses and strains in the knee were evaluated with finite element modeling. The semi-automatic segmentation and 3D geometry construction of one knee joint (menisci, femoral and tibial cartilages) was approximately two times faster than with manual segmentation. Differences in cartilage thicknesses, volumes, contact pressures, stresses, and strains between segmentation methods in femoral and tibial cartilage were mostly insignificant (p > 0.05) and random, i.e. there were no systematic differences between the methods. In conclusion, the devised semi-automatic segmentation method is a quick and accurate way to determine cartilage geometries; it may become a valuable tool for biomechanical modeling applications with large patient groups.

  6. Inter-segment foot motion in girls using a three-dimensional multi-segment foot model.

    Science.gov (United States)

    Jang, Woo Young; Lee, Dong Yeon; Jung, Hae Woon; Lee, Doo Jae; Yoo, Won Joon; Choi, In Ho

    2018-05-06

    Several multi-segment foot models (MFMs) have been introduced for in vivo analyses of dynamic foot kinematics. However, the normal gait patterns of healthy children and adolescents remain uncharacterized. We sought to determine normal foot kinematics according to age in clinically normal female children and adolescents using a Foot 3D model. Fifty-eight girls (age 7-17 years) with normal function and without radiographic abnormalities were tested. Three representative strides from five separate trials were analyzed. Kinematic data of foot segment motion were tracked and evaluated using an MFM with a 15-marker set (Foot 3D model). As controls, 50 symptom-free female adults (20-35 years old) were analyzed. In the hindfoot kinematic analysis, plantar flexion motion in the pre-swing phase was significantly greater in girls aged 11 years or older than in girls aged foot progression angle showed mildly increased internal rotation in the loading response phase and the swing phase in girls aged foot motion in girls aged 11 years or older showed low-arch kinematic characteristics, whereas those in girls aged 11 years or older were more similar to the patterns in young adult women. Copyright © 2018 Elsevier B.V. All rights reserved.

  7. Evaluation of soft segment modeling on a context independent phoneme classification system

    International Nuclear Information System (INIS)

    Razzazi, F.; Sayadiyan, A.

    2007-01-01

    The geometric distribution of states duration is one of the main performance limiting assumptions of hidden Markov modeling of speech signals. Stochastic segment models, generally, and segmental HMM, specifically overcome this deficiency partly at the cost of more complexity in both training and recognition phases. In addition to this assumption, the gradual temporal changes of speech statistics has not been modeled in HMM. In this paper, a new duration modeling approach is presented. The main idea of the model is to consider the effect of adjacent segments on the probability density function estimation and evaluation of each acoustic segment. This idea not only makes the model robust against segmentation errors, but also it models gradual change from one segment to the next one with a minimum set of parameters. The proposed idea is analytically formulated and tested on a TIMIT based context independent phenomena classification system. During the test procedure, the phoneme classification of different phoneme classes was performed by applying various proposed recognition algorithms. The system was optimized and the results have been compared with a continuous density hidden Markov model (CDHMM) with similar computational complexity. The results show 8-10% improvement in phoneme recognition rate in comparison with standard continuous density hidden Markov model. This indicates improved compatibility of the proposed model with the speech nature. (author)

  8. The Illumination Model of the Valley Based on the Diffuse Reflect of Forest

    Directory of Open Access Journals (Sweden)

    He Guoliang

    2016-01-01

    Full Text Available In this paper, models are build to evaluate the impact of the forest on the valley’s illumination. Based on the assumes that all the light reach the ground comes from the diffuse reflection which comes from the sun directly and from the diffuse reflection of other points, One model is build to consider the impact of time and latitude on the direction of the sunlight. So we can get the direction of the sunlight at different time and latitude through the model. Besides, this paper develops a illumination model to evaluate the intensity of illumination of the ground. Combining the models above, this paper get a complete model which can not only evaluate the overall light intensity of the valley but also convert the light intensity to the intensity of illumination. Simulation of the intensity illumination of some basic terrains and finally gives a comprehensive results which is practical and close to the common sense.

  9. Targeting the robo-advice customer: the development of a psychographic segmentation model for financial advice robots

    NARCIS (Netherlands)

    van Thiel, D.; van Raaij, W.F.

    2017-01-01

    The purpose of this study is to develop the world’s first psychographic market segmentation model that supports personalization, customer education, customer activation, and customer engagement strategies with financial advice robots. As traditional segmentation models in consumer finance primarily

  10. Fena Valley Reservoir watershed and water-balance model updates and expansion of watershed modeling to southern Guam

    Science.gov (United States)

    Rosa, Sarah N.; Hay, Lauren E.

    2017-12-01

    In 2014, the U.S. Geological Survey, in cooperation with the U.S. Department of Defense’s Strategic Environmental Research and Development Program, initiated a project to evaluate the potential impacts of projected climate-change on Department of Defense installations that rely on Guam’s water resources. A major task of that project was to develop a watershed model of southern Guam and a water-balance model for the Fena Valley Reservoir. The southern Guam watershed model provides a physically based tool to estimate surface-water availability in southern Guam. The U.S. Geological Survey’s Precipitation Runoff Modeling System, PRMS-IV, was used to construct the watershed model. The PRMS-IV code simulates different parts of the hydrologic cycle based on a set of user-defined modules. The southern Guam watershed model was constructed by updating a watershed model for the Fena Valley watersheds, and expanding the modeled area to include all of southern Guam. The Fena Valley watershed model was combined with a previously developed, but recently updated and recalibrated Fena Valley Reservoir water-balance model.Two important surface-water resources for the U.S. Navy and the citizens of Guam were modeled in this study; the extended model now includes the Ugum River watershed and improves upon the previous model of the Fena Valley watersheds. Surface water from the Ugum River watershed is diverted and treated for drinking water, and the Fena Valley watersheds feed the largest surface-water reservoir on Guam. The southern Guam watershed model performed “very good,” according to the criteria of Moriasi and others (2007), in the Ugum River watershed above Talofofo Falls with monthly Nash-Sutcliffe efficiency statistic values of 0.97 for the calibration period and 0.93 for the verification period (a value of 1.0 represents perfect model fit). In the Fena Valley watershed, monthly simulated streamflow volumes from the watershed model compared reasonably well with the

  11. A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung.

    Science.gov (United States)

    Guo, Shengwen; Fei, Baowei

    2009-03-27

    We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 ± 0.33 pixels, while the error is 1.99 ± 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.

  12. Evaluation of prognostic models developed using standardised image features from different PET automated segmentation methods.

    Science.gov (United States)

    Parkinson, Craig; Foley, Kieran; Whybra, Philip; Hills, Robert; Roberts, Ashley; Marshall, Chris; Staffurth, John; Spezi, Emiliano

    2018-04-11

    Prognosis in oesophageal cancer (OC) is poor. The 5-year overall survival (OS) rate is approximately 15%. Personalised medicine is hoped to increase the 5- and 10-year OS rates. Quantitative analysis of PET is gaining substantial interest in prognostic research but requires the accurate definition of the metabolic tumour volume. This study compares prognostic models developed in the same patient cohort using individual PET segmentation algorithms and assesses the impact on patient risk stratification. Consecutive patients (n = 427) with biopsy-proven OC were included in final analysis. All patients were staged with PET/CT between September 2010 and July 2016. Nine automatic PET segmentation methods were studied. All tumour contours were subjectively analysed for accuracy, and segmentation methods with segmentation methods studied, clustering means (KM2), general clustering means (GCM3), adaptive thresholding (AT) and watershed thresholding (WT) methods were included for analysis. Known clinical prognostic factors (age, treatment and staging) were significant in all of the developed prognostic models. AT and KM2 segmentation methods developed identical prognostic models. Patient risk stratification was dependent on the segmentation method used to develop the prognostic model with up to 73 patients (17.1%) changing risk stratification group. Prognostic models incorporating quantitative image features are dependent on the method used to delineate the primary tumour. This has a subsequent effect on risk stratification, with patients changing groups depending on the image segmentation method used.

  13. A minimal path searching approach for active shape model (ASM)-based segmentation of the lung

    Science.gov (United States)

    Guo, Shengwen; Fei, Baowei

    2009-02-01

    We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 +/- 0.33 pixels, while the error is 1.99 +/- 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.

  14. Automated MRI segmentation for individualized modeling of current flow in the human head.

    Science.gov (United States)

    Huang, Yu; Dmochowski, Jacek P; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C

    2013-12-01

    High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of the brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images requires labor-intensive manual segmentation, even when utilizing available automated segmentation tools. Also, accurate placement of many high-density electrodes on an individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. A fully automated segmentation technique based on Statical Parametric Mapping 8, including an improved tissue probability map and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on four healthy subjects and seven stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets. The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly. Fully automated individualized modeling may now be feasible

  15. Validation of a model of left ventricular segmentation for interpretation of SPET myocardial perfusion images

    International Nuclear Information System (INIS)

    Aepfelbacher, F.C.; Johnson, R.B.; Schwartz, J.G.; Danias, P.G.; Chen, L.; Parker, R.A.; Parker, A.J.

    2001-01-01

    Several models of left ventricular segmentation have been developed that assume a standard coronary artery distribution, and are currently used for interpretation of single-photon emission tomography (SPET) myocardial perfusion imaging. This approach has the potential for incorrect assignment of myocardial segments to vascular territories, possibly over- or underestimating the number of vessels with significant coronary artery disease (CAD). We therefore sought to validate a 17-segment model of myocardial perfusion by comparing the predefined coronary territory assignment with the actual angiographically derived coronary distribution. We examined 135 patients who underwent both coronary angiography and stress SPET imaging within 30 days. Individualized coronary distribution was determined by review of the coronary angiograms and used to identify the coronary artery supplying each of the 17 myocardial segments of the model. The actual coronary distribution was used to assess the accuracy of the assumed coronary distribution of the model. The sensitivities and specificities of stress SPET for detection of CAD in individual coronary arteries and the classification regarding perceived number of diseased coronary arteries were also compared between the two coronary distributions (actual and assumed). The assumed coronary distribution corresponded to the actual coronary anatomy in all but one segment (3). The majority of patients (80%) had 14 or more concordant segments. Sensitivities and specificities of stress SPET for detection of CAD in the coronary territories were similar, with the exception of the RCA territory, for which specificity for detection of CAD was better for the angiographically derived coronary artery distribution than for the model. There was 95% agreement between assumed and angiographically derived coronary distributions in classification to single- versus multi-vessel CAD. Reassignment of a single segment (segment 3) from the LCX to the LAD

  16. Validation of a model of left ventricular segmentation for interpretation of SPET myocardial perfusion images

    Energy Technology Data Exchange (ETDEWEB)

    Aepfelbacher, F.C.; Johnson, R.B.; Schwartz, J.G.; Danias, P.G. [Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA (United States); Chen, L.; Parker, R.A. [Biometrics Center, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA (United States); Parker, A.J. [Nuclear Medicine Division, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA (United States)

    2001-11-01

    Several models of left ventricular segmentation have been developed that assume a standard coronary artery distribution, and are currently used for interpretation of single-photon emission tomography (SPET) myocardial perfusion imaging. This approach has the potential for incorrect assignment of myocardial segments to vascular territories, possibly over- or underestimating the number of vessels with significant coronary artery disease (CAD). We therefore sought to validate a 17-segment model of myocardial perfusion by comparing the predefined coronary territory assignment with the actual angiographically derived coronary distribution. We examined 135 patients who underwent both coronary angiography and stress SPET imaging within 30 days. Individualized coronary distribution was determined by review of the coronary angiograms and used to identify the coronary artery supplying each of the 17 myocardial segments of the model. The actual coronary distribution was used to assess the accuracy of the assumed coronary distribution of the model. The sensitivities and specificities of stress SPET for detection of CAD in individual coronary arteries and the classification regarding perceived number of diseased coronary arteries were also compared between the two coronary distributions (actual and assumed). The assumed coronary distribution corresponded to the actual coronary anatomy in all but one segment (3). The majority of patients (80%) had 14 or more concordant segments. Sensitivities and specificities of stress SPET for detection of CAD in the coronary territories were similar, with the exception of the RCA territory, for which specificity for detection of CAD was better for the angiographically derived coronary artery distribution than for the model. There was 95% agreement between assumed and angiographically derived coronary distributions in classification to single- versus multi-vessel CAD. Reassignment of a single segment (segment 3) from the LCX to the LAD

  17. The Glasgow-Maastricht foot model, evaluation of a 26 segment kinematic model of the foot.

    Science.gov (United States)

    Oosterwaal, Michiel; Carbes, Sylvain; Telfer, Scott; Woodburn, James; Tørholm, Søren; Al-Munajjed, Amir A; van Rhijn, Lodewijk; Meijer, Kenneth

    2016-01-01

    Accurately measuring of intrinsic foot kinematics using skin mounted markers is difficult, limited in part by the physical dimensions of the foot. Existing kinematic foot models solve this problem by combining multiple bones into idealized rigid segments. This study presents a novel foot model that allows the motion of the 26 bones to be individually estimated via a combination of partial joint constraints and coupling the motion of separate joints using kinematic rhythms. Segmented CT data from one healthy subject was used to create a template Glasgow-Maastricht foot model (GM-model). Following this, the template was scaled to produce subject-specific models for five additional healthy participants using a surface scan of the foot and ankle. Forty-three skin mounted markers, mainly positioned around the foot and ankle, were used to capture the stance phase of the right foot of the six healthy participants during walking. The GM-model was then applied to calculate the intrinsic foot kinematics. Distinct motion patterns where found for all joints. The variability in outcome depended on the location of the joint, with reasonable results for sagittal plane motions and poor results for transverse plane motions. The results of the GM-model were comparable with existing literature, including bone pin studies, with respect to the range of motion, motion pattern and timing of the motion in the studied joints. This novel model is the most complete kinematic model to date. Further evaluation of the model is warranted.

  18. Hydrologic models and analysis of water availability in Cuyama Valley, California

    Science.gov (United States)

    Hanson, R.T.; Flint, Lorraine E.; Faunt, Claudia C.; Gibbs, Dennis R.; Schmid, Wolfgang

    2014-01-01

    Changes in population, agricultural development practices (including shifts to more water-intensive crops), and climate variability are placing increasingly larger demands on available water resources, particularly groundwater, in the Cuyama Valley, one of the most productive agricultural regions in Santa Barbara County. The goal of this study was to produce a model capable of being accurate at scales relevant to water management decisions that could be considered in the evaluation of the sustainable water supply. The Cuyama Valley Hydrologic Model (CUVHM) was designed to simulate the most important natural and human components of the hydrologic system, including components dependent on variations in climate, thereby providing a reliable assessment of groundwater conditions and processes that can inform water users and help to improve planning for future conditions. Model development included a revision of the conceptual model of the flow system, construction of a precipitation-runoff model using the Basin Characterization Model (BCM), and construction of an integrated hydrologic flow model with MODFLOW-One-Water Hydrologic Flow Model (MF-OWHM). The hydrologic models were calibrated to historical conditions of water and land use and, then, used to assess the use and movement of water throughout the Valley. These tools provide a means to understand the evolution of water use in the Valley, its availability, and the limits of sustainability. The conceptual model identified inflows and outflows that include the movement and use of water in both natural and anthropogenic systems. The groundwater flow system is characterized by a layered geologic sedimentary sequence that—in combination with the effects of groundwater pumping, natural recharge, and the application of irrigation water at the land surface—displays vertical hydraulic-head gradients. Overall, most of the agricultural demand for water in the Cuyama Valley in the initial part of the growing season is

  19. Field Scale Groundwater Nitrate Loading Model for the Central Valley, California, 1945-Current

    Science.gov (United States)

    Harter, T.; Dzurella, K.; Bell, A.; Kourakos, G.

    2015-12-01

    Anthropogenic groundwater nitrate contamination in the Central Valley aquifer system, California, is widespread, with over 40% of domestic wells in some counties exceeding drinking water standards. Sources of groundwater nitrate include leaky municipal wastewater systems, municipal wastewater recharge, onsite wastewater treatment (septic) systems, atmospheric nitrogen deposition, animal farming, application of organic waste materials (sludge, biosolids, animal manure) to agricultural lands, and synthetic fertilizer. At the site or field scale, nitrogen inputs to the landscape are balanced by plant nitrogen uptake and harvest, atmospheric nitrogen losses, surface runoff of nitrogen, soil nitrogen storage changes, and leaching to groundwater. Irrigated agriculture is a dominant player in the Central Valley nitrogen cycle: The largest nitrogen fluxes are synthetic fertilizer and animal manure applications to cropland, crop nitrogen uptake, and groundwater nitrogen losses. We construct a historic field/parcel scale groundwater nitrogen loading model distinguishing urban and residential areas, individual animal farming areas, leaky wastewater lagoons, and approximately 50 different categories of agricultural crops. For non-agricultural landuses, groundwater nitrate loading is based on reported leaching values, animal population, and human population. For cropland, groundwater nitrate loading is computed from mass balance, taking into account diverse and historically changing management practices between different crops. Groundwater nitrate loading is estimated for 1945 to current. Significant increases in groundwater nitrate loading are associated with the expansion of synthetic fertilizer use in the 1950s to 1970s. Nitrate loading from synthetic fertilizer use has stagnated over the past 20 years due to improvements in nutrient use efficiency. However, an unbroken 60 year exponential increase in dairy production until the late 2000s has significantly impacted the

  20. Fast and Sequence-Adaptive Whole-Brain Segmentation Using Parametric Bayesian Modeling

    DEFF Research Database (Denmark)

    Puonti, Oula; Iglesias, Juan Eugenio; Van Leemput, Koen

    2016-01-01

    the performance of a segmentation algorithm designed to meet these requirements, building upon generative parametric models previously used in tissue classification. The method is tested on four different datasets acquired with different scanners, field strengths and pulse sequences, demonstrating comparable...

  1. Whole vertebral bone segmentation method with a statistical intensity-shape model based approach

    Science.gov (United States)

    Hanaoka, Shouhei; Fritscher, Karl; Schuler, Benedikt; Masutani, Yoshitaka; Hayashi, Naoto; Ohtomo, Kuni; Schubert, Rainer

    2011-03-01

    An automatic segmentation algorithm for the vertebrae in human body CT images is presented. Especially we focused on constructing and utilizing 4 different statistical intensity-shape combined models for the cervical, upper / lower thoracic and lumbar vertebrae, respectively. For this purpose, two previously reported methods were combined: a deformable model-based initial segmentation method and a statistical shape-intensity model-based precise segmentation method. The former is used as a pre-processing to detect the position and orientation of each vertebra, which determines the initial condition for the latter precise segmentation method. The precise segmentation method needs prior knowledge on both the intensities and the shapes of the objects. After PCA analysis of such shape-intensity expressions obtained from training image sets, vertebrae were parametrically modeled as a linear combination of the principal component vectors. The segmentation of each target vertebra was performed as fitting of this parametric model to the target image by maximum a posteriori estimation, combined with the geodesic active contour method. In the experimental result by using 10 cases, the initial segmentation was successful in 6 cases and only partially failed in 4 cases (2 in the cervical area and 2 in the lumbo-sacral). In the precise segmentation, the mean error distances were 2.078, 1.416, 0.777, 0.939 mm for cervical, upper and lower thoracic, lumbar spines, respectively. In conclusion, our automatic segmentation algorithm for the vertebrae in human body CT images showed a fair performance for cervical, thoracic and lumbar vertebrae.

  2. Ultrastructural study of Rift Valley fever virus in the mouse model

    Energy Technology Data Exchange (ETDEWEB)

    Reed, Christopher; Steele, Keith E.; Honko, Anna; Shamblin, Joshua; Hensley, Lisa E. [United States Army Medical Research Institute of Infectious Diseases (USAMRIID), Fort Detrick, MD (United States); Smith, Darci R., E-mail: darci.smith1@us.army.mil [United States Army Medical Research Institute of Infectious Diseases (USAMRIID), Fort Detrick, MD (United States)

    2012-09-15

    Detailed ultrastructural studies of Rift Valley fever virus (RVFV) in the mouse model are needed to develop and characterize a small animal model of RVF for the evaluation of potential vaccines and therapeutics. In this study, the ultrastructural features of RVFV infection in the mouse model were analyzed. The main changes in the liver included the presence of viral particles in hepatocytes and hepatic stem cells accompanied by hepatocyte apoptosis. However, viral particles were observed rarely in the liver; in contrast, particles were extremely abundant in the CNS. Despite extensive lymphocytolysis, direct evidence of viral replication was not observed in the lymphoid tissue. These results correlate with the acute-onset hepatitis and delayed-onset encephalitis that are dominant features of severe human RVF, but suggest that host immune-mediated mechanisms contribute significantly to pathology. The results of this study expand our knowledge of RVFV-host interactions and further characterize the mouse model of RVF.

  3. Ultrastructural study of Rift Valley fever virus in the mouse model

    International Nuclear Information System (INIS)

    Reed, Christopher; Steele, Keith E.; Honko, Anna; Shamblin, Joshua; Hensley, Lisa E.; Smith, Darci R.

    2012-01-01

    Detailed ultrastructural studies of Rift Valley fever virus (RVFV) in the mouse model are needed to develop and characterize a small animal model of RVF for the evaluation of potential vaccines and therapeutics. In this study, the ultrastructural features of RVFV infection in the mouse model were analyzed. The main changes in the liver included the presence of viral particles in hepatocytes and hepatic stem cells accompanied by hepatocyte apoptosis. However, viral particles were observed rarely in the liver; in contrast, particles were extremely abundant in the CNS. Despite extensive lymphocytolysis, direct evidence of viral replication was not observed in the lymphoid tissue. These results correlate with the acute-onset hepatitis and delayed-onset encephalitis that are dominant features of severe human RVF, but suggest that host immune-mediated mechanisms contribute significantly to pathology. The results of this study expand our knowledge of RVFV–host interactions and further characterize the mouse model of RVF.

  4. Medical Image Segmentation by Combining Graph Cut and Oriented Active Appearance Models

    Science.gov (United States)

    Chen, Xinjian; Udupa, Jayaram K.; Bağcı, Ulaş; Zhuge, Ying; Yao, Jianhua

    2017-01-01

    In this paper, we propose a novel 3D segmentation method based on the effective combination of the active appearance model (AAM), live wire (LW), and graph cut (GC). The proposed method consists of three main parts: model building, initialization, and segmentation. In the model building part, we construct the AAM and train the LW cost function and GC parameters. In the initialization part, a novel algorithm is proposed for improving the conventional AAM matching method, which effectively combines the AAM and LW method, resulting in Oriented AAM (OAAM). A multi-object strategy is utilized to help in object initialization. We employ a pseudo-3D initialization strategy, and segment the organs slice by slice via multi-object OAAM method. For the segmentation part, a 3D shape constrained GC method is proposed. The object shape generated from the initialization step is integrated into the GC cost computation, and an iterative GC-OAAM method is used for object delineation. The proposed method was tested in segmenting the liver, kidneys, and spleen on a clinical CT dataset and also tested on the MICCAI 2007 grand challenge for liver segmentation training dataset. The results show the following: (a) An overall segmentation accuracy of true positive volume fraction (TPVF) > 94.3%, false positive volume fraction (FPVF) wordpress.com/research/. PMID:22311862

  5. Adaptive Breast Radiation Therapy Using Modeling of Tissue Mechanics: A Breast Tissue Segmentation Study

    International Nuclear Information System (INIS)

    Juneja, Prabhjot; Harris, Emma J.; Kirby, Anna M.; Evans, Philip M.

    2012-01-01

    Purpose: To validate and compare the accuracy of breast tissue segmentation methods applied to computed tomography (CT) scans used for radiation therapy planning and to study the effect of tissue distribution on the segmentation accuracy for the purpose of developing models for use in adaptive breast radiation therapy. Methods and Materials: Twenty-four patients receiving postlumpectomy radiation therapy for breast cancer underwent CT imaging in prone and supine positions. The whole-breast clinical target volume was outlined. Clinical target volumes were segmented into fibroglandular and fatty tissue using the following algorithms: physical density thresholding; interactive thresholding; fuzzy c-means with 3 classes (FCM3) and 4 classes (FCM4); and k-means. The segmentation algorithms were evaluated in 2 stages: first, an approach based on the assumption that the breast composition should be the same in both prone and supine position; and second, comparison of segmentation with tissue outlines from 3 experts using the Dice similarity coefficient (DSC). Breast datasets were grouped into nonsparse and sparse fibroglandular tissue distributions according to expert assessment and used to assess the accuracy of the segmentation methods and the agreement between experts. Results: Prone and supine breast composition analysis showed differences between the methods. Validation against expert outlines found significant differences (P<.001) between FCM3 and FCM4. Fuzzy c-means with 3 classes generated segmentation results (mean DSC = 0.70) closest to the experts' outlines. There was good agreement (mean DSC = 0.85) among experts for breast tissue outlining. Segmentation accuracy and expert agreement was significantly higher (P<.005) in the nonsparse group than in the sparse group. Conclusions: The FCM3 gave the most accurate segmentation of breast tissues on CT data and could therefore be used in adaptive radiation therapy-based on tissue modeling. Breast tissue segmentation

  6. A Modelling Framework for estimating Road Segment Based On-Board Vehicle Emissions

    International Nuclear Information System (INIS)

    Lin-Jun, Yu; Ya-Lan, Liu; Yu-Huan, Ren; Zhong-Ren, Peng; Meng, Liu Meng

    2014-01-01

    Traditional traffic emission inventory models aim to provide overall emissions at regional level which cannot meet planners' demand for detailed and accurate traffic emissions information at the road segment level. Therefore, a road segment-based emission model for estimating light duty vehicle emissions is proposed, where floating car technology is used to collect information of traffic condition of roads. The employed analysis framework consists of three major modules: the Average Speed and the Average Acceleration Module (ASAAM), the Traffic Flow Estimation Module (TFEM) and the Traffic Emission Module (TEM). The ASAAM is used to obtain the average speed and the average acceleration of the fleet on each road segment using FCD. The TFEM is designed to estimate the traffic flow of each road segment in a given period, based on the speed-flow relationship and traffic flow spatial distribution. Finally, the TEM estimates emissions from each road segment, based on the results of previous two modules. Hourly on-road light-duty vehicle emissions for each road segment in Shenzhen's traffic network are obtained using this analysis framework. The temporal-spatial distribution patterns of the pollutant emissions of road segments are also summarized. The results show high emission road segments cluster in several important regions in Shenzhen. Also, road segments emit more emissions during rush hours than other periods. The presented case study demonstrates that the proposed approach is feasible and easy-to-use to help planners make informed decisions by providing detailed road segment-based emission information

  7. Adaptive Breast Radiation Therapy Using Modeling of Tissue Mechanics: A Breast Tissue Segmentation Study

    Energy Technology Data Exchange (ETDEWEB)

    Juneja, Prabhjot, E-mail: Prabhjot.Juneja@icr.ac.uk [Joint Department of Physics, Institute of Cancer Research, Sutton (United Kingdom); Harris, Emma J. [Joint Department of Physics, Institute of Cancer Research, Sutton (United Kingdom); Kirby, Anna M. [Department of Academic Radiotherapy, Royal Marsden National Health Service Foundation Trust, Sutton (United Kingdom); Evans, Philip M. [Joint Department of Physics, Institute of Cancer Research, Sutton (United Kingdom)

    2012-11-01

    Purpose: To validate and compare the accuracy of breast tissue segmentation methods applied to computed tomography (CT) scans used for radiation therapy planning and to study the effect of tissue distribution on the segmentation accuracy for the purpose of developing models for use in adaptive breast radiation therapy. Methods and Materials: Twenty-four patients receiving postlumpectomy radiation therapy for breast cancer underwent CT imaging in prone and supine positions. The whole-breast clinical target volume was outlined. Clinical target volumes were segmented into fibroglandular and fatty tissue using the following algorithms: physical density thresholding; interactive thresholding; fuzzy c-means with 3 classes (FCM3) and 4 classes (FCM4); and k-means. The segmentation algorithms were evaluated in 2 stages: first, an approach based on the assumption that the breast composition should be the same in both prone and supine position; and second, comparison of segmentation with tissue outlines from 3 experts using the Dice similarity coefficient (DSC). Breast datasets were grouped into nonsparse and sparse fibroglandular tissue distributions according to expert assessment and used to assess the accuracy of the segmentation methods and the agreement between experts. Results: Prone and supine breast composition analysis showed differences between the methods. Validation against expert outlines found significant differences (P<.001) between FCM3 and FCM4. Fuzzy c-means with 3 classes generated segmentation results (mean DSC = 0.70) closest to the experts' outlines. There was good agreement (mean DSC = 0.85) among experts for breast tissue outlining. Segmentation accuracy and expert agreement was significantly higher (P<.005) in the nonsparse group than in the sparse group. Conclusions: The FCM3 gave the most accurate segmentation of breast tissues on CT data and could therefore be used in adaptive radiation therapy-based on tissue modeling. Breast tissue

  8. Expansion of the Kano model to identify relevant customer segments and functional requirements

    DEFF Research Database (Denmark)

    Atlason, Reynir Smari; Stefansson, Arnaldur Smari; Wietz, Miriam

    2017-01-01

    The Kano model of customer satisfaction has been widely used to analyse perceived needs of customers. The model provides product developers valuable information about if, and then how much a given functional requirement (FR) will impact customer satisfaction if implemented within a product, system...... or a service. A current limitation of the Kano model is that it does not allow developers to visualise which combined sets of FRs would provide the highest satisfaction between different customer segments. In this paper, a stepwise method to address this particular shortcoming is presented. First......, a traditional Kano analysis is conducted for the different segments of interest. Second, for each FR, relationship functions are integrated between x=0 and x=1. Third, integrals are inserted into a combination matrix crossing segments and FRs, where FRs with the highest sum across the chosen segments...

  9. Multi-valley effective mass theory for device-level modeling of open quantum dynamics

    Science.gov (United States)

    Jacobson, N. Tobias; Baczewski, Andrew D.; Frees, Adam; Gamble, John King; Montano, Ines; Moussa, Jonathan E.; Muller, Richard P.; Nielsen, Erik

    2015-03-01

    Simple models for semiconductor-based quantum information processors can provide useful qualitative descriptions of device behavior. However, as experimental implementations have matured, more specific guidance from theory has become necessary, particularly in the form of quantitatively reliable yet computationally efficient modeling. Besides modeling static device properties, improved characterization of noisy gate operations requires a more sophisticated description of device dynamics. Making use of recent developments in multi-valley effective mass theory, we discuss device-level simulations of the open system quantum dynamics of a qubit interacting with phonons and other noise sources. Sandia is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the US Department of Energy National Nuclear Security Administration under Contract No. DE-AC04-94AL85000.

  10. A joint model of word segmentation and meaning acquisition through cross-situational learning.

    Science.gov (United States)

    Räsänen, Okko; Rasilo, Heikki

    2015-10-01

    Human infants learn meanings for spoken words in complex interactions with other people, but the exact learning mechanisms are unknown. Among researchers, a widely studied learning mechanism is called cross-situational learning (XSL). In XSL, word meanings are learned when learners accumulate statistical information between spoken words and co-occurring objects or events, allowing the learner to overcome referential uncertainty after having sufficient experience with individually ambiguous scenarios. Existing models in this area have mainly assumed that the learner is capable of segmenting words from speech before grounding them to their referential meaning, while segmentation itself has been treated relatively independently of the meaning acquisition. In this article, we argue that XSL is not just a mechanism for word-to-meaning mapping, but that it provides strong cues for proto-lexical word segmentation. If a learner directly solves the correspondence problem between continuous speech input and the contextual referents being talked about, segmentation of the input into word-like units emerges as a by-product of the learning. We present a theoretical model for joint acquisition of proto-lexical segments and their meanings without assuming a priori knowledge of the language. We also investigate the behavior of the model using a computational implementation, making use of transition probability-based statistical learning. Results from simulations show that the model is not only capable of replicating behavioral data on word learning in artificial languages, but also shows effective learning of word segments and their meanings from continuous speech. Moreover, when augmented with a simple familiarity preference during learning, the model shows a good fit to human behavioral data in XSL tasks. These results support the idea of simultaneous segmentation and meaning acquisition and show that comprehensive models of early word segmentation should take referential word

  11. Importance of fishing as a segmentation variable in the application of a social worlds model

    Science.gov (United States)

    Gigliotti, Larry M.; Chase, Loren

    2017-01-01

    Market segmentation is useful to understanding and classifying the diverse range of outdoor recreation experiences sought by different recreationists. Although many different segmentation methodologies exist, many are complex and difficult to measure accurately during in-person intercepts, such as that of creel surveys. To address that gap in the literature, we propose a single-item measure of the importance of fishing as a surrogate to often overly- or needlesslycomplex segmentation techniques. The importance of fishing item is a measure of the value anglers place on the activity or a coarse quantification of how central the activity is to the respondent’s lifestyle (scale: 0 = not important, 1 = slightly, 2 = moderately, 3 = very, and 4 = fishing is my most important recreational activity). We suggest the importance scale may be a proxy measurement for segmenting anglers using the social worlds model as a theoretical framework. Vaske (1980) suggested that commitment to recreational activities may be best understood in relation to social group participation and the social worlds model provides a rich theoretical framework for understanding social group segments. Unruh (1983) identified four types of actor involvement in social worlds: strangers, tourists, regulars, and insiders, differentiated by four characteristics (orientation, experiences, relationships, and commitment). We evaluated the importance of fishing as a segmentation variable using data collected by a mixed-mode survey of South Dakota anglers fishing in 2010. We contend that this straightforward measurement may be useful for segmenting outdoor recreation activities when more complicated segmentation schemes are not suitable. Further, this index, when coupled with the social worlds model, provides a valuable framework for understanding the segments and making management decisions.

  12. Influence of the orographic roughness of glacier valleys across the Transantarctic Mountains in an atmospheric regional model

    Energy Technology Data Exchange (ETDEWEB)

    Jourdain, Nicolas C.; Gallee, Hubert [Laboratoire de Glaciologie et Geophysique de l' Environnement, Saint Martin d' Heres (France)

    2011-03-15

    Glacier valleys across the Transantarctic Mountains are not properly taken into account in climate models, because of their coarse resolution. Nonetheless, glacier valleys control katabatic winds in this region, and the latter are thought to affect the climate of the Ross Sea sector, frsater formation to snow mass balance. The purpose of this paper is to investigate the role of the production of turbulent kinetic energy by the subgrid-scale orography in the Transantarctic Mountains using a 20-km atmospheric regional model. A classical orographic roughness length parametrization is modified to produce either smooth or rough valleys. A one-year simulation shows that katabatic winds in the Transantarctic Mountains are strongly improved using smooth valleys rather than rough valleys. Pressure and temperature fields are affected by the representation of the orographic roughness, specifically in the Transantarctic Mountains and over the Ross Ice Shelf. A smooth representation of escarpment regions shows better agreement with automatic weather station observations than a rough representation. This work stresses the need to improve the representation of subgrid-scale orography to simulate realistic katabatic flows. This paper also provides a way of improving surface winds in an atmospheric model without increasing its resolution. (orig.)

  13. Model for bridging the translational "valleys of death" in spinal cord injury research

    Directory of Open Access Journals (Sweden)

    Barrable B

    2014-04-01

    Full Text Available Bill Barrable,1 Nancy Thorogood,1 Vanessa Noonan,1,2 Jocelyn Tomkinson,1 Phalgun Joshi,1 Ken Stephenson,1 John Barclay,1 Katharina Kovacs Burns3 1Rick Hansen Institute, 2Division of Spine, Department of Orthopaedics, University of British Columbia, Vancouver, BC, 3Health Sciences Council, University of Alberta, Edmonton, AB, Canada Abstract: To improve health care outcomes with cost-effective treatments and prevention initiatives, basic health research must be translated into clinical application and studied during implementation, a process commonly referred to as translational research. It is estimated that only 14% of health-related scientific discoveries enter into medical practice and that it takes an average of 17 years for them to do so. The transition from basic research to clinical knowledge and from clinical knowledge to practice or implementation is so fraught with obstacles that these transitions are often referred to as “valleys of death”. The Rick Hansen Institute has developed a unique praxis model for translational research in the field of spinal cord injury (SCI. The praxis model involves three components. The first is a coordinated program strategy of cure, care, consumer engagement, and commercialization. The second is a knowledge cycle that consists of four phases, ie, environmental scanning, knowledge generation and synthesis, knowledge validation, and implementation. The third is the provision of relevant resources and infrastructure to overcome obstacles in the “valleys of death”, ie, funding, clinical research operations, informatics, clinical research and best practice implementation, consumer engagement, collaborative networks, and strategic partnerships. This model, which is to be independently evaluated in 2018 to determine its strengths and limitations, has been used to advance treatments for pressure ulcers in SCI. The Rick Hansen Institute has developed an innovative solution to move knowledge into action by

  14. Toward combining thematic information with hierarchical multiscale segmentations using tree Markov random field model

    Science.gov (United States)

    Zhang, Xueliang; Xiao, Pengfeng; Feng, Xuezhi

    2017-09-01

    It has been a common idea to produce multiscale segmentations to represent the various geographic objects in high-spatial resolution remote sensing (HR) images. However, it remains a great challenge to automatically select the proper segmentation scale(s) just according to the image information. In this study, we propose a novel way of information fusion at object level by combining hierarchical multiscale segmentations with existed thematic information produced by classification or recognition. The tree Markov random field (T-MRF) model is designed for the multiscale combination framework, through which the object type is determined as close as the existed thematic information. At the same time, the object boundary is jointly determined by the thematic labels and the multiscale segments through the minimization of the energy function. The benefits of the proposed T-MRF combination model include: (1) reducing the dependence of segmentation scale selection when utilizing multiscale segmentations; (2) exploring the hierarchical context naturally imbedded in the multiscale segmentations. The HR images in both urban and rural areas are used in the experiments to show the effectiveness of the proposed combination framework on these two aspects.

  15. Model-Based Learning of Local Image Features for Unsupervised Texture Segmentation

    Science.gov (United States)

    Kiechle, Martin; Storath, Martin; Weinmann, Andreas; Kleinsteuber, Martin

    2018-04-01

    Features that capture well the textural patterns of a certain class of images are crucial for the performance of texture segmentation methods. The manual selection of features or designing new ones can be a tedious task. Therefore, it is desirable to automatically adapt the features to a certain image or class of images. Typically, this requires a large set of training images with similar textures and ground truth segmentation. In this work, we propose a framework to learn features for texture segmentation when no such training data is available. The cost function for our learning process is constructed to match a commonly used segmentation model, the piecewise constant Mumford-Shah model. This means that the features are learned such that they provide an approximately piecewise constant feature image with a small jump set. Based on this idea, we develop a two-stage algorithm which first learns suitable convolutional features and then performs a segmentation. We note that the features can be learned from a small set of images, from a single image, or even from image patches. The proposed method achieves a competitive rank in the Prague texture segmentation benchmark, and it is effective for segmenting histological images.

  16. Calibration of numerical models for small debris flows in Yosemite Valley, California, USA

    Directory of Open Access Journals (Sweden)

    P. Bertolo

    2005-01-01

    Full Text Available This study compares documented debris flow runout distances with numerical simulations in the Yosemite Valley of California, USA, where about 15% of historical events of slope instability can be classified as debris flows and debris slides (Wieczorek and Snyder, 2004. To model debris flows in the Yosemite Valley, we selected six streams with evidence of historical debris flows; three of the debris flow deposits have single channels, and the other three split their pattern in the fan area into two or more channels. From field observations all of the debris flows involved coarse material, with only very small clay content. We applied the one dimensional DAN (Dynamic ANalysis model (Hungr, 1995 and the two-dimensional FLO-2D model (O'Brien et al., 1993 to predict and compare the runout distance and the velocity of the debris flows observed in the study area. As a first step, we calibrated the parameters for the two softwares through the back analysis of three debris- flows channels using a trial-and-error procedure starting with values suggested in the literature. In the second step we applied the selected values to the other channels, in order to evaluate their predictive capabilities. After parameter calibration using three debris flows we obtained results similar to field observations We also obtained a good agreement between the two models for velocities. Both models are strongly influenced by topography: we used the 30 m cell size DTM available for the study area, that is probably not accurate enough for a highly detailed analysis, but it can be sufficient for a first screening.

  17. Cowichan Valley energy mapping and modelling. Report 6 - Findings and recommendations. Final report. [Vancouver Island, Canada

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2012-06-15

    This report is the final report in a series of six reports detailing the findings from the Cowichan Valley Energy Mapping and Modelling project that was carried out from April of 2011 to March of 2012 by Ea Energy Analyses in conjunction with Geographic Resource Analysis and Science (GRAS). The driving force behind the Integrated Energy Mapping and Analysis project was the identification and analysis of a suite of pathways that the Cowichan Valley Regional District (CVRD) can utilise to increase its energy resilience, as well as reduce energy consumption and GHG emissions, with a primary focus on the residential sector. Mapping and analysis undertaken will support provincial energy and GHG reduction targets, and the suite of pathways outlined will address a CVRD internal target that calls for 75% of the region's energy within the residential sector to come from locally sourced renewables by 2050. The target has been developed as a mechanism to meet resilience and climate action target. The maps and findings produced are to be integrated as part of a regional policy framework currently under development. The present report is the final report and presents a summary of the findings of project tasks 1-5 and provides a set of recommendations to the CVRD based on the work done and with an eye towards the next steps in the energy planning process of the CVRD. (LN)

  18. Updated comparison of groundwater flow model results and isotopic data in the Leon Valley, Mexico

    Science.gov (United States)

    Hernandez-Garcia, G. D.

    2015-12-01

    Northwest of Mexico City, the study area is located in the State of Guanajuato. Leon Valley has covered with groundwater its demand of water, estimated in 20.6 cubic meters per second. The constant increase of population and economic activities in the region, mainly in cities and automobile factories, has also a constant growth in water needs. Related extraction rate has produced an average decrease of approximately 1.0 m per year over the past two decades. This suggests that the present management of the groundwater should be checked. Management of groundwater in the study area involves the possibility of producing environmental impacts by extraction. This vital resource under stress becomes necessary studying its hydrogeological functioning to achieve scientific management of groundwater in the Valley. This research was based on the analysis and integration of existing information and the field generated by the authors. On the base of updated concepts like the geological structure of the area, the hydraulic parameters and the composition of deuterium-delta and delta-oxygen -18, this research has new results. This information has been fully analyzed by applying a groundwater flow model with particle tracking: the result has also a similar result in terms of travel time and paths derived from isotopic data.

  19. [Application of GVF snake model in segmentation of whole body bone SPECT image].

    Science.gov (United States)

    Zhu, Chunmei; Tian, Lianfang; Chen, Ping; Wang, Lifei; Ye, Guangchun; Mao, Zongyuan

    2008-02-01

    Limited by the imaging principle of whole body bone SPECT image, the gray value of bladder area is quite high, which affects the image's brightness, contrast and readability. In the meantime, the similarity between bladder area and focus makes it difficult for some images to be segmented automatically. In this paper, an improved Snake model, GVF Snake, is adopted to automatically segment bladder area, preparing for further processing of whole body bone SPECT images.

  20. Two-Segment Foot Model for the Biomechanical Analysis of Squat

    OpenAIRE

    Panero, E.; Gastaldi, L.; Rapp, W.

    2017-01-01

    Squat exercise is acquiring interest in many fields, due to its benefits in improving health and its biomechanical similarities to a wide range of sport motions and the recruitment of many body segments in a single maneuver. Several researches had examined considerable biomechanical aspects of lower limbs during squat, but not without limitations. The main goal of this study focuses on the analysis of the foot contribution during a partial body weight squat, using a two-segment foot model tha...

  1. Latent segmentation based count models: Analysis of bicycle safety in Montreal and Toronto.

    Science.gov (United States)

    Yasmin, Shamsunnahar; Eluru, Naveen

    2016-10-01

    The study contributes to literature on bicycle safety by building on the traditional count regression models to investigate factors affecting bicycle crashes at the Traffic Analysis Zone (TAZ) level. TAZ is a traffic related geographic entity which is most frequently used as spatial unit for macroscopic crash risk analysis. In conventional count models, the impact of exogenous factors is restricted to be the same across the entire region. However, it is possible that the influence of exogenous factors might vary across different TAZs. To accommodate for the potential variation in the impact of exogenous factors we formulate latent segmentation based count models. Specifically, we formulate and estimate latent segmentation based Poisson (LP) and latent segmentation based Negative Binomial (LNB) models to study bicycle crash counts. In our latent segmentation approach, we allow for more than two segments and also consider a large set of variables in segmentation and segment specific models. The formulated models are estimated using bicycle-motor vehicle crash data from the Island of Montreal and City of Toronto for the years 2006 through 2010. The TAZ level variables considered in our analysis include accessibility measures, exposure measures, sociodemographic characteristics, socioeconomic characteristics, road network characteristics and built environment. A policy analysis is also conducted to illustrate the applicability of the proposed model for planning purposes. This macro-level research would assist decision makers, transportation officials and community planners to make informed decisions to proactively improve bicycle safety - a prerequisite to promoting a culture of active transportation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Rift Valley Fever Risk Map Model and Seroprevalence in Selected Wild Ungulates and Camels from Kenya

    Science.gov (United States)

    Britch, Seth C.; Binepal, Yatinder S.; Ruder, Mark G.; Kariithi, Henry M.; Linthicum, Kenneth J.; Anyamba, Assaf; Small, Jennifer L.; Tucker, Compton J.; Ateya, Leonard O.; Oriko, Abuu A.; hide

    2013-01-01

    Since the first isolation of Rift Valley fever virus (RVFV) in the 1930s, there have been multiple epizootics and epidemics in animals and humans in sub-Saharan Africa. Prospective climate-based models have recently been developed that flag areas at risk of RVFV transmission in endemic regions based on key environmental indicators that precede Rift Valley fever (RVF) epizootics and epidemics. Although the timing and locations of human case data from the 2006-2007 RVF outbreak in Kenya have been compared to risk zones flagged by the model, seroprevalence of RVF antibodies in wildlife has not yet been analyzed in light of temporal and spatial predictions of RVF activity. Primarily wild ungulate serum samples from periods before, during, and after the 2006-2007 RVF epizootic were analyzed for the presence of RVFV IgM and/or IgG antibody. Results show an increase in RVF seropositivity from samples collected in 2007 (31.8%), compared to antibody prevalence observed from 2000-2006 (3.3%). After the epizootic, average RVF seropositivity diminished to 5% in samples collected from 2008-2009. Overlaying maps of modeled RVF risk assessments with sampling locations indicated positive RVF serology in several species of wild ungulate in or near areas flagged as being at risk for RVF. Our results establish the need to continue and expand sero-surveillance of wildlife species Kenya and elsewhere in the Horn of Africa to further calibrate and improve the RVF risk model, and better understand the dynamics of RVFV transmission.

  3. An Improved Random Walker with Bayes Model for Volumetric Medical Image Segmentation

    Directory of Open Access Journals (Sweden)

    Chunhua Dong

    2017-01-01

    Full Text Available Random walk (RW method has been widely used to segment the organ in the volumetric medical image. However, it leads to a very large-scale graph due to a number of nodes equal to a voxel number and inaccurate segmentation because of the unavailability of appropriate initial seed point setting. In addition, the classical RW algorithm was designed for a user to mark a few pixels with an arbitrary number of labels, regardless of the intensity and shape information of the organ. Hence, we propose a prior knowledge-based Bayes random walk framework to segment the volumetric medical image in a slice-by-slice manner. Our strategy is to employ the previous segmented slice to obtain the shape and intensity knowledge of the target organ for the adjacent slice. According to the prior knowledge, the object/background seed points can be dynamically updated for the adjacent slice by combining the narrow band threshold (NBT method and the organ model with a Gaussian process. Finally, a high-quality image segmentation result can be automatically achieved using Bayes RW algorithm. Comparing our method with conventional RW and state-of-the-art interactive segmentation methods, our results show an improvement in the accuracy for liver segmentation (p<0.001.

  4. Multi-atlas segmentation for abdominal organs with Gaussian mixture models

    Science.gov (United States)

    Burke, Ryan P.; Xu, Zhoubing; Lee, Christopher P.; Baucom, Rebeccah B.; Poulose, Benjamin K.; Abramson, Richard G.; Landman, Bennett A.

    2015-03-01

    Abdominal organ segmentation with clinically acquired computed tomography (CT) is drawing increasing interest in the medical imaging community. Gaussian mixture models (GMM) have been extensively used through medical segmentation, most notably in the brain for cerebrospinal fluid / gray matter / white matter differentiation. Because abdominal CT exhibit strong localized intensity characteristics, GMM have recently been incorporated in multi-stage abdominal segmentation algorithms. In the context of variable abdominal anatomy and rich algorithms, it is difficult to assess the marginal contribution of GMM. Herein, we characterize the efficacy of an a posteriori framework that integrates GMM of organ-wise intensity likelihood with spatial priors from multiple target-specific registered labels. In our study, we first manually labeled 100 CT images. Then, we assigned 40 images to use as training data for constructing target-specific spatial priors and intensity likelihoods. The remaining 60 images were evaluated as test targets for segmenting 12 abdominal organs. The overlap between the true and the automatic segmentations was measured by Dice similarity coefficient (DSC). A median improvement of 145% was achieved by integrating the GMM intensity likelihood against the specific spatial prior. The proposed framework opens the opportunities for abdominal organ segmentation by efficiently using both the spatial and appearance information from the atlases, and creates a benchmark for large-scale automatic abdominal segmentation.

  5. Brain Tumor Segmentation Using a Generative Model with an RBM Prior on Tumor Shape

    DEFF Research Database (Denmark)

    Agn, Mikael; Puonti, Oula; Rosenschöld, Per Munck af

    2016-01-01

    In this paper, we present a fully automated generative method for brain tumor segmentation in multi-modal magnetic resonance images. The method is based on the type of generative model often used for segmenting healthy brain tissues, where tissues are modeled by Gaussian mixture models combined...... the use of the intensity information in the training images. Experiments on public benchmark data of patients suffering from low- and high-grade gliomas show that the method performs well compared to current state-of-the-art methods, while not being tied to any specific imaging protocol....... with a spatial atlas-based tissue prior. We extend this basic model with a tumor prior, which uses convolutional restricted Boltzmann machines (cRBMs) to model the shape of both tumor core and complete tumor, which includes edema and core. The cRBMs are trained on expert segmentations of training images, without...

  6. Wireless Positioning Based on a Segment-Wise Linear Approach for Modeling the Target Trajectory

    DEFF Research Database (Denmark)

    Figueiras, Joao; Pedersen, Troels; Schwefel, Hans-Peter

    2008-01-01

    Positioning solutions in infrastructure-based wireless networks generally operate by exploiting the channel information of the links between the Wireless Devices and fixed networking Access Points. The major challenge of such solutions is the modeling of both the noise properties of the channel...... measurements and the user mobility patterns. One class of typical human being movement patterns is the segment-wise linear approach, which is studied in this paper. Current tracking solutions, such as the Constant Velocity model, hardly handle such segment-wise linear patterns. In this paper we propose...... a segment-wise linear model, called the Drifting Points model. The model results in an increased performance when compared with traditional solutions....

  7. Multi-object segmentation framework using deformable models for medical imaging analysis.

    Science.gov (United States)

    Namías, Rafael; D'Amato, Juan Pablo; Del Fresno, Mariana; Vénere, Marcelo; Pirró, Nicola; Bellemare, Marc-Emmanuel

    2016-08-01

    Segmenting structures of interest in medical images is an important step in different tasks such as visualization, quantitative analysis, simulation, and image-guided surgery, among several other clinical applications. Numerous segmentation methods have been developed in the past three decades for extraction of anatomical or functional structures on medical imaging. Deformable models, which include the active contour models or snakes, are among the most popular methods for image segmentation combining several desirable features such as inherent connectivity and smoothness. Even though different approaches have been proposed and significant work has been dedicated to the improvement of such algorithms, there are still challenging research directions as the simultaneous extraction of multiple objects and the integration of individual techniques. This paper presents a novel open-source framework called deformable model array (DMA) for the segmentation of multiple and complex structures of interest in different imaging modalities. While most active contour algorithms can extract one region at a time, DMA allows integrating several deformable models to deal with multiple segmentation scenarios. Moreover, it is possible to consider any existing explicit deformable model formulation and even to incorporate new active contour methods, allowing to select a suitable combination in different conditions. The framework also introduces a control module that coordinates the cooperative evolution of the snakes and is able to solve interaction issues toward the segmentation goal. Thus, DMA can implement complex object and multi-object segmentations in both 2D and 3D using the contextual information derived from the model interaction. These are important features for several medical image analysis tasks in which different but related objects need to be simultaneously extracted. Experimental results on both computed tomography and magnetic resonance imaging show that the proposed

  8. Segmentation of lung fields using Chan-Vese active contour model in chest radiographs

    Science.gov (United States)

    Sohn, Kiwon

    2011-03-01

    A CAD tool for chest radiographs consists of several procedures and the very first step is segmentation of lung fields. We develop a novel methodology for segmentation of lung fields in chest radiographs that can satisfy the following two requirements. First, we aim to develop a segmentation method that does not need a training stage with manual estimation of anatomical features in a large training dataset of images. Secondly, for the ease of implementation, it is desirable to apply a well established model that is widely used for various image-partitioning practices. The Chan-Vese active contour model, which is based on Mumford-Shah functional in the level set framework, is applied for segmentation of lung fields. With the use of this model, segmentation of lung fields can be carried out without detailed prior knowledge on the radiographic anatomy of the chest, yet in some chest radiographs, the trachea regions are unfavorably segmented out in addition to the lung field contours. To eliminate artifacts from the trachea, we locate the upper end of the trachea, find a vertical center line of the trachea and delineate it, and then brighten the trachea region to make it less distinctive. The segmentation process is finalized by subsequent morphological operations. We randomly select 30 images from the Japanese Society of Radiological Technology image database to test the proposed methodology and the results are shown. We hope our segmentation technique can help to promote of CAD tools, especially for emerging chest radiographic imaging techniques such as dual energy radiography and chest tomosynthesis.

  9. Groundwater-flow and land-subsidence model of Antelope Valley, California

    Science.gov (United States)

    Siade, Adam J.; Nishikawa, Tracy; Rewis, Diane L.; Martin, Peter; Phillips, Steven P.

    2014-01-01

    Antelope Valley, California, is a topographically closed basin in the western part of the Mojave Desert, about 50 miles northeast of Los Angeles. The Antelope Valley groundwater basin is about 940 square miles and is separated from the northern part of Antelope Valley by faults and low-lying hills. Prior to 1972, groundwater provided more than 90 percent of the total water supply in the valley; since 1972, it has provided between 50 and 90 percent. Most groundwater pumping in the valley occurs in the Antelope Valley groundwater basin, which includes the rapidly growing cities of Lancaster and Palmdale. Groundwater-level declines of more than 270 feet in some parts of the groundwater basin have resulted in an increase in pumping lifts, reduced well efficiency, and land subsidence of more than 6 feet in some areas. Future urban growth and limits on the supply of imported water may increase reliance on groundwater.

  10. A System Dynamics Modeling of Water Supply and Demand in Las Vegas Valley

    Science.gov (United States)

    Parajuli, R.; Kalra, A.; Mastino, L.; Velotta, M.; Ahmad, S.

    2017-12-01

    The rise in population and change in climate have posed the uncertainties in the balance between supply and demand of water. The current study deals with the water management issues in Las Vegas Valley (LVV) using Stella, a system dynamics modeling software, to model the feedback based relationship between supply and demand parameters. Population parameters were obtained from Center for Business and Economic Research while historical water demand and conservation practices were modeled as per the information provided by local authorities. The water surface elevation of Lake Mead, which is the prime source of water supply to the region, was modeled as the supply side whereas the water demand in LVV was modeled as the demand side. The study was done from the period of 1989 to 2049 with 1989 to 2012 as the historical one and the period from 2013 to 2049 as the future period. This study utilizes Coupled Model Intercomparison Project data sets (2013-2049) (CMIP3&5) to model different future climatic scenarios. The model simulates the past dynamics of supply and demand, and then forecasts the future water budget for the forecasted future population and future climatic conditions. The results can be utilized by the water authorities in understanding the future water status and hence plan suitable conservation policies to allocate future water budget and achieve sustainable water management.

  11. Modeling nitrate at domestic and public-supply well depths in the Central Valley, California

    Science.gov (United States)

    Nolan, Bernard T.; Gronberg, JoAnn M.; Faunt, Claudia C.; Eberts, Sandra M.; Belitz, Ken

    2014-01-01

    Aquifer vulnerability models were developed to map groundwater nitrate concentration at domestic and public-supply well depths in the Central Valley, California. We compared three modeling methods for ability to predict nitrate concentration >4 mg/L: logistic regression (LR), random forest classification (RFC), and random forest regression (RFR). All three models indicated processes of nitrogen fertilizer input at the land surface, transmission through coarse-textured, well-drained soils, and transport in the aquifer to the well screen. The total percent correct predictions were similar among the three models (69–82%), but RFR had greater sensitivity (84% for shallow wells and 51% for deep wells). The results suggest that RFR can better identify areas with high nitrate concentration but that LR and RFC may better describe bulk conditions in the aquifer. A unique aspect of the modeling approach was inclusion of outputs from previous, physically based hydrologic and textural models as predictor variables, which were important to the models. Vertical water fluxes in the aquifer and percent coarse material above the well screen were ranked moderately high-to-high in the RFR models, and the average vertical water flux during the irrigation season was highly significant (p < 0.0001) in logistic regression.

  12. Modeling nitrate at domestic and public-supply well depths in the Central Valley, California

    Science.gov (United States)

    Nolan, Bernard T.; Gronberg, JoAnn M.; Faunt, Claudia C.; Eberts, Sandra M.; Belitz, Ken

    2014-01-01

    Aquifer vulnerability models were developed to map groundwater nitrate concentration at domestic and public-supply well depths in the Central Valley, California. We compared three modeling methods for ability to predict nitrate concentration >4 mg/L: logistic regression (LR), random forest classification (RFC), and random forest regression (RFR). All three models indicated processes of nitrogen fertilizer input at the land surface, transmission through coarse-textured, well-drained soils, and transport in the aquifer to the well screen. The total percent correct predictions were similar among the three models (69–82%), but RFR had greater sensitivity (84% for shallow wells and 51% for deep wells). The results suggest that RFR can better identify areas with high nitrate concentration but that LR and RFC may better describe bulk conditions in the aquifer. A unique aspect of the modeling approach was inclusion of outputs from previous, physically based hydrologic and textural models as predictor variables, which were important to the models. Vertical water fluxes in the aquifer and percent coarse material above the well screen were ranked moderately high-to-high in the RFR models, and the average vertical water flux during the irrigation season was highly significant (p in logistic regression.

  13. A statistical learning framework for groundwater nitrate models of the Central Valley, California, USA

    Science.gov (United States)

    Nolan, Bernard T.; Fienen, Michael N.; Lorenz, David L.

    2015-01-01

    We used a statistical learning framework to evaluate the ability of three machine-learning methods to predict nitrate concentration in shallow groundwater of the Central Valley, California: boosted regression trees (BRT), artificial neural networks (ANN), and Bayesian networks (BN). Machine learning methods can learn complex patterns in the data but because of overfitting may not generalize well to new data. The statistical learning framework involves cross-validation (CV) training and testing data and a separate hold-out data set for model evaluation, with the goal of optimizing predictive performance by controlling for model overfit. The order of prediction performance according to both CV testing R2 and that for the hold-out data set was BRT > BN > ANN. For each method we identified two models based on CV testing results: that with maximum testing R2 and a version with R2 within one standard error of the maximum (the 1SE model). The former yielded CV training R2 values of 0.94–1.0. Cross-validation testing R2 values indicate predictive performance, and these were 0.22–0.39 for the maximum R2 models and 0.19–0.36 for the 1SE models. Evaluation with hold-out data suggested that the 1SE BRT and ANN models predicted better for an independent data set compared with the maximum R2 versions, which is relevant to extrapolation by mapping. Scatterplots of predicted vs. observed hold-out data obtained for final models helped identify prediction bias, which was fairly pronounced for ANN and BN. Lastly, the models were compared with multiple linear regression (MLR) and a previous random forest regression (RFR) model. Whereas BRT results were comparable to RFR, MLR had low hold-out R2 (0.07) and explained less than half the variation in the training data. Spatial patterns of predictions by the final, 1SE BRT model agreed reasonably well with previously observed patterns of nitrate occurrence in groundwater of the Central Valley.

  14. Refining the Subseafloor Circulation Model of the Middle Valley Hydrothermal System Using Fluid Geochemistry

    Science.gov (United States)

    Inderbitzen, K. E.; Wheat, C. G.; Baker, P. A.; Fisher, A. T.

    2014-12-01

    Currently, fluid circulation patterns and the evolution of rock/fluid compositions as circulation occurs in subseafloor hydrothermal systems are poorly constrained. Sedimented spreading centers provide a unique opportunity to study subsurface flow because sediment acts as an insulating blanket that traps heat from the cooling magma body and limits: (a) potential flow paths for seawater to recharge the aquifer in permeable upper basaltic basement and (b) points of altered fluid egress. This also allows for a range of thermal and geochemical gradients to exist near the sediment-water interface. Models of fluid circulation patterns in this type of hydrologic setting have been generated (eg. Stein and Fisher, 2001); however fluid chemistry datasets have not previously been used to test the model's viability. We address this issue by integrating the existing circulation model with fluid compositional data collected from sediment pore waters and high temperature hydrothermal vents located in Middle Valley on the Juan de Fuca Ridge. Middle Valley hosts a variety of hydrologic regimes: including areas of fluid recharge (Site 855), active venting (Site 858/1036; Dead Dog vent field), recent venting (Site 856/1035; Bent Hill Massive Sulfide deposit) and a section of heavily sedimented basement located between recharge and discharge sites (Site 857). We will present new results based on thermal and geochemical data from the area of active venting (Sites 858 and 1036), that was collected during Ocean Drilling Program Legs 139 and 169 and a subsequent heat flow/gravity coring effort. These results illuminate fine scale controls on secondary recharge and fluid flow within the sediment section at Site 858/1036. The current status of high temperature vents in this area (based on observations made in July, 2014) will also be outlined.

  15. Creation of voxel-based models for paediatric dosimetry from automatic segmentation methods

    International Nuclear Information System (INIS)

    Acosta, O.; Li, R.; Ourselin, S.; Caon, M.

    2006-01-01

    Full text: The first computational models representing human anatomy were mathematical phantoms, but still far from accurate representations of human body. These models have been used with radiation transport codes (Monte Carlo) to estimate organ doses from radiological procedures. Although new medical imaging techniques have recently allowed the construction of voxel-based models based on the real anatomy, few children models from individual CT or MRI data have been reported [1,3]. For pediatric dosimetry purposes, a large range of voxel models by ages is required since scaling the anatomy from existing models is not sufficiently accurate. The small number of models available arises from the small number of CT or MRI data sets of children available and the long amount of time required to segment the data sets. The existing models have been constructed by manual segmentation slice by slice and using simple thresholding techniques. In medical image segmentation, considerable difficulties appear when applying classical techniques like thresholding or simple edge detection. Until now, any evidence of more accurate or near-automatic methods used in construction of child voxel models exists. We aim to construct a range of pediatric voxel models, integrating automatic or semi-automatic 3D segmentation techniques. In this paper we present the first stage of this work using pediatric CT data.

  16. A statistical pixel intensity model for segmentation of confocal laser scanning microscopy images.

    Science.gov (United States)

    Calapez, Alexandre; Rosa, Agostinho

    2010-09-01

    Confocal laser scanning microscopy (CLSM) has been widely used in the life sciences for the characterization of cell processes because it allows the recording of the distribution of fluorescence-tagged macromolecules on a section of the living cell. It is in fact the cornerstone of many molecular transport and interaction quantification techniques where the identification of regions of interest through image segmentation is usually a required step. In many situations, because of the complexity of the recorded cellular structures or because of the amounts of data involved, image segmentation either is too difficult or inefficient to be done by hand and automated segmentation procedures have to be considered. Given the nature of CLSM images, statistical segmentation methodologies appear as natural candidates. In this work we propose a model to be used for statistical unsupervised CLSM image segmentation. The model is derived from the CLSM image formation mechanics and its performance is compared to the existing alternatives. Results show that it provides a much better description of the data on classes characterized by their mean intensity, making it suitable not only for segmentation methodologies with known number of classes but also for use with schemes aiming at the estimation of the number of classes through the application of cluster selection criteria.

  17. Dynamic thermal characteristics of heat pipe via segmented thermal resistance model for electric vehicle battery cooling

    Science.gov (United States)

    Liu, Feifei; Lan, Fengchong; Chen, Jiqing

    2016-07-01

    Heat pipe cooling for battery thermal management systems (BTMSs) in electric vehicles (EVs) is growing due to its advantages of high cooling efficiency, compact structure and flexible geometry. Considering the transient conduction, phase change and uncertain thermal conditions in a heat pipe, it is challenging to obtain the dynamic thermal characteristics accurately in such complex heat and mass transfer process. In this paper, a ;segmented; thermal resistance model of a heat pipe is proposed based on thermal circuit method. The equivalent conductivities of different segments, viz. the evaporator and condenser of pipe, are used to determine their own thermal parameters and conditions integrated into the thermal model of battery for a complete three-dimensional (3D) computational fluid dynamics (CFD) simulation. The proposed ;segmented; model shows more precise than the ;non-segmented; model by the comparison of simulated and experimental temperature distribution and variation of an ultra-thin micro heat pipe (UMHP) battery pack, and has less calculation error to obtain dynamic thermal behavior for exact thermal design, management and control of heat pipe BTMSs. Using the ;segmented; model, the cooling effect of the UMHP pack with different natural/forced convection and arrangements is predicted, and the results correspond well to the tests.

  18. Segmentation of kidney using C-V model and anatomy priors

    Science.gov (United States)

    Lu, Jinghua; Chen, Jie; Zhang, Juan; Yang, Wenjia

    2007-12-01

    This paper presents an approach for kidney segmentation on abdominal CT images as the first step of a virtual reality surgery system. Segmentation for medical images is often challenging because of the objects' complicated anatomical structures, various gray levels, and unclear edges. A coarse to fine approach has been applied in the kidney segmentation using Chan-Vese model (C-V model) and anatomy prior knowledge. In pre-processing stage, the candidate kidney regions are located. Then C-V model formulated by level set method is applied in these smaller ROI, which can reduce the calculation complexity to a certain extent. At last, after some mathematical morphology procedures, the specified kidney structures have been extracted interactively with prior knowledge. The satisfying results on abdominal CT series show that the proposed approach keeps all the advantages of C-V model and overcome its disadvantages.

  19. A new model for the determination of limb segment mass in children.

    Science.gov (United States)

    Kuemmerle-Deschner, J B; Hansmann, S; Rapp, H; Dannecker, G E

    2007-04-01

    The knowledge of limb segment masses is critical for the calculation of joint torques. Several methods for segment mass estimation have been described in the literature. They are either inaccurate or not applicable to the limb segments of children. Therefore, we developed a new cylinder brick model (CBM) to estimate segment mass in children. The aim of this study was to compare CBM and a model based on a polynomial regression equation (PRE) to volume measurement obtained by the water displacement method (WDM). We examined forearms, hands, lower legs, and feet of 121 children using CBM, PRE, and WDM. The differences between CBM and WDM or PRE and WDM were calculated and compared using a Bland-Altman plot of differences. Absolute limb segment mass measured by WDM ranged from 0.16+/-0.04 kg for hands in girls 5-6 years old, up to 2.72+/-1.03 kg for legs in girls 11-12 years old. The differences of normalised segment masses ranged from 0.0002+/-0.0021 to 0.0011+/-0.0036 for CBM-WDM and from 0.0023+/-0.0041 to 0.0127+/-0.036 for PRE-WDM (values are mean+/-2 S.D.). The CBM showed better agreement with WDM than PRE for all limb segments in girls and boys. CBM is accurate and superior to PRE for the estimation of individual limb segment mass of children. Therefore, CBM is a practical and useful tool for the analysis of kinetic parameters and the calculation of resulting forces to assess joint functionality in children.

  20. Automating the segmentation of medical images for the production of voxel tomographic computational models

    International Nuclear Information System (INIS)

    Caon, M.

    2001-01-01

    Radiation dosimetry for the diagnostic medical imaging procedures performed on humans requires anatomically accurate, computational models. These may be constructed from medical images as voxel-based tomographic models. However, they are time consuming to produce and as a consequence, there are few available. This paper discusses the emergence of semi-automatic segmentation techniques and describes an application (iRAD) written in Microsoft Visual Basic that allows the bitmap of a medical image to be segmented interactively and semi-automatically while displayed in Microsoft Excel. iRAD will decrease the time required to construct voxel models. Copyright (2001) Australasian College of Physical Scientists and Engineers in Medicine

  1. A network-based meta-population approach to model Rift Valley fever epidemics.

    Science.gov (United States)

    Xue, Ling; Scott, H Morgan; Cohnstaedt, Lee W; Scoglio, Caterina

    2012-08-07

    Rift Valley fever virus (RVFV) has been expanding its geographical distribution with important implications for both human and animal health. The emergence of Rift Valley fever (RVF) in the Middle East, and its continuing presence in many areas of Africa, has negatively impacted both medical and veterinary infrastructures and human morbidity, mortality, and economic endpoints. Furthermore, worldwide attention should be directed towards the broader infection dynamics of RVFV, because suitable host, vector and environmental conditions for additional epidemics likely exist on other continents; including Asia, Europe and the Americas. We propose a new compartmentalized model of RVF and the related ordinary differential equations to assess disease spread in both time and space; with the latter driven as a function of contact networks. Humans and livestock hosts and two species of vector mosquitoes are included in the model. The model is based on weighted contact networks, where nodes of the networks represent geographical regions and the weights represent the level of contact between regional pairings for each set of species. The inclusion of human, animal, and vector movements among regions is new to RVF modeling. The movement of the infected individuals is not only treated as a possibility, but also an actuality that can be incorporated into the model. We have tested, calibrated, and evaluated the model using data from the recent 2010 RVF outbreak in South Africa as a case study; mapping the epidemic spread within and among three South African provinces. An extensive set of simulation results shows the potential of the proposed approach for accurately modeling the RVF spreading process in additional regions of the world. The benefits of the proposed model are twofold: not only can the model differentiate the maximum number of infected individuals among different provinces, but also it can reproduce the different starting times of the outbreak in multiple locations

  2. A Variational Level Set Model Combined with FCMS for Image Clustering Segmentation

    Directory of Open Access Journals (Sweden)

    Liming Tang

    2014-01-01

    Full Text Available The fuzzy C means clustering algorithm with spatial constraint (FCMS is effective for image segmentation. However, it lacks essential smoothing constraints to the cluster boundaries and enough robustness to the noise. Samson et al. proposed a variational level set model for image clustering segmentation, which can get the smooth cluster boundaries and closed cluster regions due to the use of level set scheme. However it is very sensitive to the noise since it is actually a hard C means clustering model. In this paper, based on Samson’s work, we propose a new variational level set model combined with FCMS for image clustering segmentation. Compared with FCMS clustering, the proposed model can get smooth cluster boundaries and closed cluster regions due to the use of level set scheme. In addition, a block-based energy is incorporated into the energy functional, which enables the proposed model to be more robust to the noise than FCMS clustering and Samson’s model. Some experiments on the synthetic and real images are performed to assess the performance of the proposed model. Compared with some classical image segmentation models, the proposed model has a better performance for the images contaminated by different noise levels.

  3. Conditioning a segmented stem profile model for two diameter measurements

    Science.gov (United States)

    Raymond L. Czaplewski; Joe P. Mcclure

    1988-01-01

    The stem profile model of Max and Burkhart (1976) is conditioned for dbh and a second upper stem measurement. This model was applied to a loblolly pine data set using diameter outside bark at 5.3m (i.e., height of 17.3 foot Girard form class) as the second upper stem measurement, and then compared to the original, unconditioned model. Variance of residuals was reduced...

  4. Reconstructing late quaternary fluvial process controls in the upper aller valley (north Germany) by means of numerical modeling

    NARCIS (Netherlands)

    Veldkamp, A.; Berg, van den M.; Dijke, van J.J.; Berg van Saparoea, van den R.M.

    2002-01-01

    The morpho-genetic evolution of the upper Aller valley (Weser basin, North Germany) was reconstructed using geological and geomorphologic data integrated within a numerical process model framework (FLUVER-2). The current relief was shaped by Pre-Elsterian fluvial processes, Elsterian and Saalian ice

  5. Reconstructing Late Quaternary fluvial process controls in the upper Aller Valley (North Germany) by means of numerical modeling

    NARCIS (Netherlands)

    Veldkamp, A.; Berg, M.W. van den; Dijke, J.J. van; Berg van den; Saparoea, R.M. van

    2002-01-01

    The morpho-genetic evolution of the upper Aller valley (Weser basin, North Germany) was reconstructed using geological and geomorphologic data integrated within a numerical process model framework (FLUVER-2). The current relief was shaped by Pre-Elsterian fluvial processes, Elsterian and Saalian ice

  6. Spatiotemporal Segmentation and Modeling of the Mitral Valve in Real-Time 3D Echocardiographic Images.

    Science.gov (United States)

    Pouch, Alison M; Aly, Ahmed H; Lai, Eric K; Yushkevich, Natalie; Stoffers, Rutger H; Gorman, Joseph H; Cheung, Albert T; Gorman, Joseph H; Gorman, Robert C; Yushkevich, Paul A

    2017-09-01

    Transesophageal echocardiography is the primary imaging modality for preoperative assessment of mitral valves with ischemic mitral regurgitation (IMR). While there are well known echocardiographic insights into the 3D morphology of mitral valves with IMR, such as annular dilation and leaflet tethering, less is understood about how quantification of valve dynamics can inform surgical treatment of IMR or predict short-term recurrence of the disease. As a step towards filling this knowledge gap, we present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE). The framework integrates multi-atlas label fusion and template-based medial modeling to generate quantitatively descriptive models of valve dynamics. The novelty of this work is that temporal consistency in the rt-3DE segmentations is enforced during both the segmentation and modeling stages with the use of groupwise label fusion and Kalman filtering. The algorithm is evaluated on rt-3DE data series from 10 patients: five with normal mitral valve morphology and five with severe IMR. In these 10 data series that total 207 individual 3DE images, each 3DE segmentation is validated against manual tracing and temporal consistency between segmentations is demonstrated. The ultimate goal is to generate accurate and consistent representations of valve dynamics that can both visually and quantitatively provide insight into normal and pathological valve function.

  7. Analog model study of the ground-water basin of the Upper Coachella Valley, California

    Science.gov (United States)

    Tyley, Stephen J.

    1974-01-01

    An analog model of the ground-water basin of the upper Coachella Valley was constructed to determine the effects of imported water on ground-water levels. The model was considered verified when the ground-water levels generated by the model approximated the historical change in water levels of the ground-water basin caused by man's activities for the period 1986-67. The ground-water basin was almost unaffected by man's activities until about 1945 when ground-water development caused the water levels to begin to decline. The Palm Springs area has had the largest water-level decline, 75 feet since 1986, because of large pumpage, reduced natural inflow from the San Gorgonio Pass area, and diversions of natural inflows at Snow and Falls Creeks and Chino Canyon starting in 1945. The San Gorgonio Pass inflow had been reduced from about 18,000 acre-feet in 1986 to about 9,000 acre-feet by 1967 because of increased ground-water pumpage in the San Gorgonio Pass area, dewatering of the San Gorgonio Pass area that took place when the tunnel for the Metropolitan Water District of Southern California was drilled, and diversions of surface inflow at Snow and Falls Creeks. In addition, 1944-64 was a period of below-normal precipitation which, in part, contributed to the declines in water levels in the Coachella Valley. The Desert Hot Springs, Garnet Hill, and Mission Creek subbasins have had relatively little development; consequently, the water-level declines have been small, ranging from 5 to 15 feet since 1986. In the Point Happy area a decline of about 2 feet per year continued until 1949 when delivery of Colorado River water to the lower valley through the Coachella Canal was initiated. Since 1949 the water levels in the Point Happy area have been rising and by 1967 were above their 1986 levels. The Whitewater River subbasin includes the largest aquifer in the basin, having sustained ground-water pumpage of about 740,000 acre-feet from 1986 to 1967, and will probably

  8. A prosthesis-specific multi-link segment model of lower-limb amputee sprinting.

    Science.gov (United States)

    Rigney, Stacey M; Simmons, Anne; Kark, Lauren

    2016-10-03

    Lower-limb amputees commonly utilize non-articulating energy storage and return (ESAR) prostheses for high impact activities such as sprinting. Despite these prostheses lacking an articulating ankle joint, amputee gait analysis conventionally features a two-link segment model of the prosthetic foot. This paper investigated the effects of the selected link segment model׳s marker-set and geometry on a unilateral amputee sprinter׳s calculated lower-limb kinematics, kinetics and energetics. A total of five lower-limb models of the Ottobock ® 1E90 Sprinter were developed, including two conventional shank-foot models that each used a different version of the Plug-in-Gait (PiG) marker-set to test the effect of prosthesis ankle marker location. Two Hybrid prosthesis-specific models were then developed, also using the PiG marker-sets, with the anatomical shank and foot replaced by prosthesis-specific geometry separated into two segments. Finally, a Multi-link segment (MLS) model was developed, consisting of six segments for the prosthesis as defined by a custom marker-set. All full-body musculoskeletal models were tested using four trials of experimental marker trajectories within OpenSim 3.2 (Stanford, California, USA) to find the affected and unaffected hip, knee and ankle kinematics, kinetics and energetics. The geometry of the selected lower-limb prosthesis model was found to significantly affect all variables on the affected leg (p prosthesis-specific spatial, inertial and elastic properties from full-body models significantly affects the calculated amputee gait characteristics, and we therefore recommend the implementation of a MLS model. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Supervised variational model with statistical inference and its application in medical image segmentation.

    Science.gov (United States)

    Li, Changyang; Wang, Xiuying; Eberl, Stefan; Fulham, Michael; Yin, Yong; Dagan Feng, David

    2015-01-01

    Automated and general medical image segmentation can be challenging because the foreground and the background may have complicated and overlapping density distributions in medical imaging. Conventional region-based level set algorithms often assume piecewise constant or piecewise smooth for segments, which are implausible for general medical image segmentation. Furthermore, low contrast and noise make identification of the boundaries between foreground and background difficult for edge-based level set algorithms. Thus, to address these problems, we suggest a supervised variational level set segmentation model to harness the statistical region energy functional with a weighted probability approximation. Our approach models the region density distributions by using the mixture-of-mixtures Gaussian model to better approximate real intensity distributions and distinguish statistical intensity differences between foreground and background. The region-based statistical model in our algorithm can intuitively provide better performance on noisy images. We constructed a weighted probability map on graphs to incorporate spatial indications from user input with a contextual constraint based on the minimization of contextual graphs energy functional. We measured the performance of our approach on ten noisy synthetic images and 58 medical datasets with heterogeneous intensities and ill-defined boundaries and compared our technique to the Chan-Vese region-based level set model, the geodesic active contour model with distance regularization, and the random walker model. Our method consistently achieved the highest Dice similarity coefficient when compared to the other methods.

  10. Unsupervised Object Modeling and Segmentation with Symmetry Detection for Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Jui-Yuan Su

    2015-04-01

    Full Text Available In this paper we present a novel unsupervised approach to detecting and segmenting objects as well as their constituent symmetric parts in an image. Traditional unsupervised image segmentation is limited by two obvious deficiencies: the object detection accuracy degrades with the misaligned boundaries between the segmented regions and the target, and pre-learned models are required to group regions into meaningful objects. To tackle these difficulties, the proposed approach aims at incorporating the pair-wise detection of symmetric patches to achieve the goal of segmenting images into symmetric parts. The skeletons of these symmetric parts then provide estimates of the bounding boxes to locate the target objects. Finally, for each detected object, the graphcut-based segmentation algorithm is applied to find its contour. The proposed approach has significant advantages: no a priori object models are used, and multiple objects are detected. To verify the effectiveness of the approach based on the cues that a face part contains an oval shape and skin colors, human objects are extracted from among the detected objects. The detected human objects and their parts are finally tracked across video frames to capture the object part movements for learning the human activity models from video clips. Experimental results show that the proposed method gives good performance on publicly available datasets.

  11. A multi-cell, multi-scale model of vertebrate segmentation and somite formation.

    Directory of Open Access Journals (Sweden)

    Susan D Hester

    2011-10-01

    Full Text Available Somitogenesis, the formation of the body's primary segmental structure common to all vertebrate development, requires coordination between biological mechanisms at several scales. Explaining how these mechanisms interact across scales and how events are coordinated in space and time is necessary for a complete understanding of somitogenesis and its evolutionary flexibility. So far, mechanisms of somitogenesis have been studied independently. To test the consistency, integrability and combined explanatory power of current prevailing hypotheses, we built an integrated clock-and-wavefront model including submodels of the intracellular segmentation clock, intercellular segmentation-clock coupling via Delta/Notch signaling, an FGF8 determination front, delayed differentiation, clock-wavefront readout, and differential-cell-cell-adhesion-driven cell sorting. We identify inconsistencies between existing submodels and gaps in the current understanding of somitogenesis mechanisms, and propose novel submodels and extensions of existing submodels where necessary. For reasonable initial conditions, 2D simulations of our model robustly generate spatially and temporally regular somites, realistic dynamic morphologies and spontaneous emergence of anterior-traveling stripes of Lfng. We show that these traveling stripes are pseudo-waves rather than true propagating waves. Our model is flexible enough to generate interspecies-like variation in somite size in response to changes in the PSM growth rate and segmentation-clock period, and in the number and width of Lfng stripes in response to changes in the PSM growth rate, segmentation-clock period and PSM length.

  12. A multivariate model for predicting segmental body composition.

    Science.gov (United States)

    Tian, Simiao; Mioche, Laurence; Denis, Jean-Baptiste; Morio, Béatrice

    2013-12-01

    The aims of the present study were to propose a multivariate model for predicting simultaneously body, trunk and appendicular fat and lean masses from easily measured variables and to compare its predictive capacity with that of the available univariate models that predict body fat percentage (BF%). The dual-energy X-ray absorptiometry (DXA) dataset (52% men and 48% women) with White, Black and Hispanic ethnicities (1999-2004, National Health and Nutrition Examination Survey) was randomly divided into three sub-datasets: a training dataset (TRD), a test dataset (TED); a validation dataset (VAD), comprising 3835, 1917 and 1917 subjects. For each sex, several multivariate prediction models were fitted from the TRD using age, weight, height and possibly waist circumference. The most accurate model was selected from the TED and then applied to the VAD and a French DXA dataset (French DB) (526 men and 529 women) to assess the prediction accuracy in comparison with that of five published univariate models, for which adjusted formulas were re-estimated using the TRD. Waist circumference was found to improve the prediction accuracy, especially in men. For BF%, the standard error of prediction (SEP) values were 3.26 (3.75) % for men and 3.47 (3.95)% for women in the VAD (French DB), as good as those of the adjusted univariate models. Moreover, the SEP values for the prediction of body and appendicular lean masses ranged from 1.39 to 2.75 kg for both the sexes. The prediction accuracy was best for age < 65 years, BMI < 30 kg/m2 and the Hispanic ethnicity. The application of our multivariate model to large populations could be useful to address various public health issues.

  13. Design and implementation of segment oriented spatio-temporal model in urban panoramic maps

    Science.gov (United States)

    Li, Haiting; Fei, Lifan; Peng, Qingshan; Li, Yanhong

    2009-10-01

    Object-oriented spatio-temporal model is directed by human cognition that each object has what/where/when attributes. The precise and flexible structure of such models supports multi-semantics of space and time. This paper reviews current research of spatio-temporal models using object-oriented approach and proposed a new spatio-temporal model based on segmentation in order to resolve the updating problem of some special GIS system by taking advantages of object-oriented spatio-temporal model and adopting category theory. Category theory can be used as a unifying framework for specifying complex systems and it provides rules on how objects may be joined. It characterizes the segments of object through mappings between them. The segment-oriented spatio-temporal model designed for urban panoramic maps is described and implemented. We take points and polylines as objects in this model in the management of panoramic map data. For the randomness of routes which transportation vehicle adopts each time, road objects in this model are split into some segments by crossing points. The segments still remains polyline type, but the splitting makes it easier to update the panoramic data when new photos are captured. This model is capable of eliminating redundant data and accelerating data access when panoramas are unchanged. For evaluation purpose, the data types and operations are designed and implemented in PostgreSQL and the results of experiments come out to prove that this model is efficient and expedient in the application of urban panoramic maps.

  14. Attitudinal travel demand model for non-work trips of homogeneously constrained segments of a population

    Energy Technology Data Exchange (ETDEWEB)

    Recker, W.W.; Stevens, R.F.

    1977-06-01

    Market-segmentation techniques are used to capture effects of opportunity and availability constraints on urban residents' choice of mode for trips for major grocery shopping and for visiting friends and acquaintances. Attitudinal multinomial logit choice models are estimated for each market segment. Explanatory variables are individual's beliefs about attributes of four modal alternatives: bus, car, taxi and walking. Factor analysis is employed to identify latent dimensions of perception of the modal alternatives and to eliminate problems of multicollinearity in model estimation.

  15. Gallbladder Boundary Segmentation from Ultrasound Images Using Active Contour Model

    Science.gov (United States)

    Ciecholewski, Marcin

    Extracting the shape of the gallbladder from an ultrasonography (US) image allows superfluous information which is immaterial in the diagnostic process to be eliminated. In this project an active contour model was used to extract the shape of the gallbladder, both for cases free of lesions, and for those showing specific disease units, namely: lithiasis, polyps and changes in the shape of the organ, such as folds or turns of the gallbladder. The approximate shape of the gallbladder was found by applying the motion equation model. The tests conducted have shown that for the 220 US images of the gallbladder, the area error rate (AER) amounted to 18.15%.

  16. Integrated 3D density modelling and segmentation of the Dead Sea

    OpenAIRE

    H.-J. Götze; R. El-Kelani; Sebastian Schmidt; M. Rybakov; M. Hassouneh; Hans-Jürgen Förster; J. Ebbing; DESERT Group;  ;  ;  

    2007-01-01

    A 3D interpretation of the newly compiled Bouguer anomaly in the area of the '‘Dead Sea Rift’’ is presented. A high-resolution 3D model constrained with the seismic results reveals the crustal thickness and density distribution beneath the Arava/Araba Valley (AV), the region between the Dead Sea and the Gulf of Aqaba/Elat. The Bouguer anomalies along the axial portion of the AV, as deduced from the modelling results, are mainly caused by deep-seated sedimentary basins (D > 10 km). An inferred...

  17. Population growth and collapse in a multiagent model of the Kayenta Anasazi in Long House Valley.

    Science.gov (United States)

    Axtell, Robert L; Epstein, Joshua M; Dean, Jeffrey S; Gumerman, George J; Swedlund, Alan C; Harburger, Jason; Chakravarty, Shubha; Hammond, Ross; Parker, Jon; Parker, Miles

    2002-05-14

    Long House Valley in the Black Mesa area of northeastern Arizona (U.S.) was inhabited by the Kayenta Anasazi from about 1800 before Christ to about anno Domini 1300. These people were prehistoric ancestors of the modern Pueblo cultures of the Colorado Plateau. Paleoenvironmental research based on alluvial geomorphology, palynology, and dendroclimatology permits accurate quantitative reconstruction of annual fluctuations in potential agricultural production (kg of maize per hectare). The archaeological record of Anasazi farming groups from anno Domini 200-1300 provides information on a millennium of sociocultural stasis, variability, change, and adaptation. We report on a multiagent computational model of this society that closely reproduces the main features of its actual history, including population ebb and flow, changing spatial settlement patterns, and eventual rapid decline. The agents in the model are monoagriculturalists, who decide both where to situate their fields as well as the location of their settlements. Nutritional needs constrain fertility. Agent heterogeneity, difficult to model mathematically, is demonstrated to be crucial to the high fidelity of the model.

  18. A Hybrid 3D Colon Segmentation Method Using Modified Geometric Deformable Models

    Directory of Open Access Journals (Sweden)

    S. Falahieh Hamidpour

    2007-06-01

    Full Text Available Introduction: Nowadays virtual colonoscopy has become a reliable and efficient method of detecting primary stages of colon cancer such as polyp detection. One of the most important and crucial stages of virtual colonoscopy is colon segmentation because an incorrect segmentation may lead to a misdiagnosis.  Materials and Methods: In this work, a hybrid method based on Geometric Deformable Models (GDM in combination with an advanced region growing and thresholding methods is proposed. GDM are found to be an attractive tool for structural based image segmentation particularly for extracting the objects with complicated topology. There are two main parameters influencing the overall performance of GDM algorithm; the distance between the initial contour and the actual object’s contours and secondly the stopping term which controls the deformation. To overcome these limitations, a two stage hybrid based segmentation method is suggested to extract the rough but precise initial contours at the first stage of the segmentation. The extracted boundaries are smoothed and improved using a modified GDM algorithm by improving the stopping terms of the algorithm based on the gradient value of image voxels. Results: The proposed algorithm was implemented on forty data sets each containing 400-480 slices. The results show an improvement in the accuracy and smoothness of the extracted boundaries. The improvement obtained for the accuracy of segmentation is about 6% in comparison to the one achieved by the methods based on thresholding and region growing only. Discussion and Conclusion: The extracted contours using modified GDM are smoother and finer. The improvement achieved in this work on the performance of stopping function of GDM model together with applying two stage segmentation of boundaries have resulted in a great improvement on the computational efficiency of GDM algorithm while making smoother and finer colon borders.

  19. biomvRhsmm: Genomic Segmentation with Hidden Semi-Markov Model

    Directory of Open Access Journals (Sweden)

    Yang Du

    2014-01-01

    Full Text Available High-throughput technologies like tiling array and next-generation sequencing (NGS generate continuous homogeneous segments or signal peaks in the genome that represent transcripts and transcript variants (transcript mapping and quantification, regions of deletion and amplification (copy number variation, or regions characterized by particular common features like chromatin state or DNA methylation ratio (epigenetic modifications. However, the volume and output of data produced by these technologies present challenges in analysis. Here, a hidden semi-Markov model (HSMM is implemented and tailored to handle multiple genomic profile, to better facilitate genome annotation by assisting in the detection of transcripts, regulatory regions, and copy number variation by holistic microarray or NGS. With support for various data distributions, instead of limiting itself to one specific application, the proposed hidden semi-Markov model is designed to allow modeling options to accommodate different types of genomic data and to serve as a general segmentation engine. By incorporating genomic positions into the sojourn distribution of HSMM, with optional prior learning using annotation or previous studies, the modeling output is more biologically sensible. The proposed model has been compared with several other state-of-the-art segmentation models through simulation benchmarking, which shows that our efficient implementation achieves comparable or better sensitivity and specificity in genomic segmentation.

  20. Liver Segmentation Based on Snakes Model and Improved GrowCut Algorithm in Abdominal CT Image

    Directory of Open Access Journals (Sweden)

    Huiyan Jiang

    2013-01-01

    Full Text Available A novel method based on Snakes Model and GrowCut algorithm is proposed to segment liver region in abdominal CT images. First, according to the traditional GrowCut method, a pretreatment process using K-means algorithm is conducted to reduce the running time. Then, the segmentation result of our improved GrowCut approach is used as an initial contour for the future precise segmentation based on Snakes model. At last, several experiments are carried out to demonstrate the performance of our proposed approach and some comparisons are conducted between the traditional GrowCut algorithm. Experimental results show that the improved approach not only has a better robustness and precision but also is more efficient than the traditional GrowCut method.

  1. Tractography segmentation using a hierarchical Dirichlet processes mixture model.

    Science.gov (United States)

    Wang, Xiaogang; Grimson, W Eric L; Westin, Carl-Fredrik

    2011-01-01

    In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model. The number of clusters is automatically learned driven by data with a Dirichlet process (DP) prior instead of being manually specified. After the models of bundles have been learned from training data without supervision, they can be used as priors to cluster/classify fibers of new subjects for comparison across subjects. When clustering fibers of new subjects, new clusters can be created for structures not observed in the training data. Our approach does not require computing pairwise distances between fibers and can cluster a huge set of fibers across multiple subjects. We present results on several data sets, the largest of which has more than 120,000 fibers. Copyright © 2010 Elsevier Inc. All rights reserved.

  2. Fully automated segmentation of oncological PET volumes using a combined multiscale and statistical model

    International Nuclear Information System (INIS)

    Montgomery, David W. G.; Amira, Abbes; Zaidi, Habib

    2007-01-01

    The widespread application of positron emission tomography (PET) in clinical oncology has driven this imaging technology into a number of new research and clinical arenas. Increasing numbers of patient scans have led to an urgent need for efficient data handling and the development of new image analysis techniques to aid clinicians in the diagnosis of disease and planning of treatment. Automatic quantitative assessment of metabolic PET data is attractive and will certainly revolutionize the practice of functional imaging since it can lower variability across institutions and may enhance the consistency of image interpretation independent of reader experience. In this paper, a novel automated system for the segmentation of oncological PET data aiming at providing an accurate quantitative analysis tool is proposed. The initial step involves expectation maximization (EM)-based mixture modeling using a k-means clustering procedure, which varies voxel order for initialization. A multiscale Markov model is then used to refine this segmentation by modeling spatial correlations between neighboring image voxels. An experimental study using an anthropomorphic thorax phantom was conducted for quantitative evaluation of the performance of the proposed segmentation algorithm. The comparison of actual tumor volumes to the volumes calculated using different segmentation methodologies including standard k-means, spatial domain Markov Random Field Model (MRFM), and the new multiscale MRFM proposed in this paper showed that the latter dramatically reduces the relative error to less than 8% for small lesions (7 mm radii) and less than 3.5% for larger lesions (9 mm radii). The analysis of the resulting segmentations of clinical oncologic PET data seems to confirm that this methodology shows promise and can successfully segment patient lesions. For problematic images, this technique enables the identification of tumors situated very close to nearby high normal physiologic uptake. The

  3. The L0 Regularized Mumford-Shah Model for Bias Correction and Segmentation of Medical Images.

    Science.gov (United States)

    Duan, Yuping; Chang, Huibin; Huang, Weimin; Zhou, Jiayin; Lu, Zhongkang; Wu, Chunlin

    2015-11-01

    We propose a new variant of the Mumford-Shah model for simultaneous bias correction and segmentation of images with intensity inhomogeneity. First, based on the model of images with intensity inhomogeneity, we introduce an L0 gradient regularizer to model the true intensity and a smooth regularizer to model the bias field. In addition, we derive a new data fidelity using the local intensity properties to allow the bias field to be influenced by its neighborhood. Second, we use a two-stage segmentation method, where the fast alternating direction method is implemented in the first stage for the recovery of true intensity and bias field and a simple thresholding is used in the second stage for segmentation. Different from most of the existing methods for simultaneous bias correction and segmentation, we estimate the bias field and true intensity without fixing either the number of the regions or their values in advance. Our method has been validated on medical images of various modalities with intensity inhomogeneity. Compared with the state-of-art approaches and the well-known brain software tools, our model is fast, accurate, and robust with initializations.

  4. Models for positional signalling, the threefold subdivision of segments and the pigmentation pattern of molluscs.

    Science.gov (United States)

    Meinhardt, H

    1984-11-01

    Models of biological pattern formation are discussed. The regulatory features expected from the models are compared to those observed experimentally. It will be shown that: (i) Stable gradients appropriate to supply positional information can be produced by local autocatalysis and long-range inhibition. (ii) Spatially ordered sequences of differentiated cell states can emerge if these cell states mutually activate each other on long range but exclude each other locally. Segmentation results from the repetition of three such cell states, S, A and P (and not of only two, as is usually assumed). With a repetition of three states, each segment has a defined polarity. The confrontation of P cells and S cells lead to the formation of a segment border (...P/SAP/SAP/S...) while the A-P confrontation is a prerequisite for appendage formation. Mutations of Drosophila affecting larval segmentation are discussed in terms of this model. (iii) The two models for the generation of sequences of structures in space (positional information including interpretation versus mutual activation) lead to different predictions with respect to intercalary regeneration. This allows a distinction between the two models on the basis of experiments. (iv) The pigmentation patterns of certain molluscs emerge from a coupled oscillation of cells (that is, a lateral inhibition in time, instead of space). The oblique lines result from a chain of triggering events.

  5. Semiautomated four-dimensional computed tomography segmentation using deformable models

    International Nuclear Information System (INIS)

    Ragan, Dustin; Starkschall, George; McNutt, Todd; Kaus, Michael; Guerrero, Thomas; Stevens, Craig W.

    2005-01-01

    The purpose of this work is to demonstrate a proof of feasibility of the application of a commercial prototype deformable model algorithm to the problem of delineation of anatomic structures on four-dimensional (4D) computed tomography (CT) image data sets. We acquired a 4D CT image data set of a patient's thorax that consisted of three-dimensional (3D) image data sets from eight phases in the respiratory cycle. The contours of the right and left lungs, cord, heart, and esophagus were manually delineated on the end inspiration data set. An interactive deformable model algorithm, originally intended for deforming an atlas-based model surface to a 3D CT image data set, was applied in an automated fashion. Triangulations based on the contours generated on each phase were deformed to the CT data set on the succeeding phase to generate the contours on that phase. Deformation was propagated through the eight phases, and the contours obtained on the end inspiration data set were compared with the original manually delineated contours. Structures defined by high-density gradients, such as lungs, cord, and heart, were accurately reproduced, except in regions where other gradient boundaries may have confused the algorithm, such as near bronchi. The algorithm failed to accurately contour the esophagus, a soft-tissue structure completely surrounded by tissue of similar density, without manual interaction. This technique has the potential to facilitate contour delineation in 4D CT image data sets; and future evolution of the software is expected to improve the process

  6. Data-driven modeling to assess receptivity for Rift Valley Fever virus.

    Directory of Open Access Journals (Sweden)

    Christopher M Barker

    2013-11-01

    Full Text Available Rift Valley Fever virus (RVFV is an enzootic virus that causes extensive morbidity and mortality in domestic ruminants in Africa, and it has shown the potential to invade other areas such as the Arabian Peninsula. Here, we develop methods for linking mathematical models to real-world data that could be used for continent-scale risk assessment given adequate data on local host and vector populations. We have applied the methods to a well-studied agricultural region of California with [Formula: see text]1 million dairy cattle, abundant and competent mosquito vectors, and a permissive climate that has enabled consistent transmission of West Nile virus and historically other arboviruses. Our results suggest that RVFV outbreaks could occur from February-November, but would progress slowly during winter-early spring or early fall and be limited spatially to areas with early increases in vector abundance. Risk was greatest in summer, when the areas at risk broadened to include most of the dairy farms in the study region, indicating the potential for considerable economic losses if an introduction were to occur. To assess the threat that RVFV poses to North America, including what-if scenarios for introduction and control strategies, models such as this one should be an integral part of the process; however, modeling must be paralleled by efforts to address the numerous remaining gaps in data and knowledge for this system.

  7. Modeling the Thickness of Perennial Ice Covers on Stratified Lakes of the Taylor Valley, Antarctica

    Science.gov (United States)

    Obryk, M. K.; Doran, P. T.; Hicks, J. A.; McKay, C. P.; Priscu, J. C.

    2016-01-01

    A one-dimensional ice cover model was developed to predict and constrain drivers of long term ice thickness trends in chemically stratified lakes of Taylor Valley, Antarctica. The model is driven by surface radiative heat fluxes and heat fluxes from the underlying water column. The model successfully reproduced 16 years (between 1996 and 2012) of ice thickness changes for west lobe of Lake Bonney (average ice thickness = 3.53 m; RMSE = 0.09 m, n = 118) and Lake Fryxell (average ice thickness = 4.22 m; RMSE = 0.21 m, n = 128). Long-term ice thickness trends require coupling with the thermal structure of the water column. The heat stored within the temperature maximum of lakes exceeding a liquid water column depth of 20 m can either impede or facilitate ice thickness change depending on the predominant climatic trend (temperature cooling or warming). As such, shallow (< 20 m deep water columns) perennially ice-covered lakes without deep temperature maxima are more sensitive indicators of climate change. The long-term ice thickness trends are a result of surface energy flux and heat flux from the deep temperature maximum in the water column, the latter of which results from absorbed solar radiation.

  8. The water balance of the urban Salt Lake Valley: a multiple-box model validated by observations

    Science.gov (United States)

    Stwertka, C.; Strong, C.

    2012-12-01

    A main focus of the recently awarded National Science Foundation (NSF) EPSCoR Track-1 research project "innovative Urban Transitions and Arid-region Hydro-sustainability (iUTAH)" is to quantify the primary components of the water balance for the Wasatch region, and to evaluate their sensitivity to climate change and projected urban development. Building on the multiple-box model that we developed and validated for carbon dioxide (Strong et al 2011), mass balance equations for water in the atmosphere and surface are incorporated into the modeling framework. The model is used to determine how surface fluxes, ground-water transport, biological fluxes, and meteorological processes regulate water cycling within and around the urban Salt Lake Valley. The model is used to evaluate the hypotheses that increased water demand associated with urban growth in Salt Lake Valley will (1) elevate sensitivity to projected climate variability and (2) motivate more attentive management of urban water use and evaporative fluxes.

  9. Adapting Active Shape Models for 3D segmentation of tubular structures in medical images.

    Science.gov (United States)

    de Bruijne, Marleen; van Ginneken, Bram; Viergever, Max A; Niessen, Wiro J

    2003-07-01

    Active Shape Models (ASM) have proven to be an effective approach for image segmentation. In some applications, however, the linear model of gray level appearance around a contour that is used in ASM is not sufficient for accurate boundary localization. Furthermore, the statistical shape model may be too restricted if the training set is limited. This paper describes modifications to both the shape and the appearance model of the original ASM formulation. Shape model flexibility is increased, for tubular objects, by modeling the axis deformation independent of the cross-sectional deformation, and by adding supplementary cylindrical deformation modes. Furthermore, a novel appearance modeling scheme that effectively deals with a highly varying background is developed. In contrast with the conventional ASM approach, the new appearance model is trained on both boundary and non-boundary points, and the probability that a given point belongs to the boundary is estimated non-parametrically. The methods are evaluated on the complex task of segmenting thrombus in abdominal aortic aneurysms (AAA). Shape approximation errors were successfully reduced using the two shape model extensions. Segmentation using the new appearance model significantly outperformed the original ASM scheme; average volume errors are 5.1% and 45% respectively.

  10. Modeling the intraurban variation in nitrogen dioxide in urban areas in Kathmandu Valley, Nepal.

    Science.gov (United States)

    Gurung, Anobha; Levy, Jonathan I; Bell, Michelle L

    2017-05-01

    With growing urbanization, traffic has become one of the main sources of air pollution in Nepal. Understanding the impact of air pollution on health requires estimation of exposure. Land use regression (LUR) modeling is widely used to investigate intraurban variation in air pollution for Western cities, but LUR models are relatively scarce in developing countries. In this study, we developed LUR models to characterize intraurban variation of nitrogen dioxide (NO 2 ) in urban areas of Kathmandu Valley, Nepal, one of the fastest urbanizing areas in South Asia. Over the study area, 135 monitoring sites were selected using stratified random sampling based on building density and road density along with purposeful sampling. In 2014, four sampling campaigns were performed, one per season, for two weeks each. NO 2 was measured using duplicate Palmes tubes at 135 sites, with additional information on nitric oxide (NO), NO 2 , and nitrogen oxide (NOx) concentrations derived from Ogawa badges at 28 sites. Geographical variables (e.g., road network, land use, built area) were used as predictor variables in LUR modeling, considering buffers 25-400m around each monitoring site. Annual average NO 2 by site ranged from 5.7 to 120ppb for the study area, with higher concentrations in the Village Development Committees (VDCs) of Kathmandu and Lalitpur than in Kirtipur, Thimi, and Bhaktapur, and with variability present within each VDC. In the final LUR model, length of major road, built area, and industrial area were positively associated with NO 2 concentration while normalized difference vegetation index (NDVI) was negatively associated with NO 2 concentration (R 2 =0.51). Cross-validation of the results confirmed the reliability of the model. The combination of passive NO 2 sampling and LUR modeling techniques allowed for characterization of nitrogen dioxide patterns in a developing country setting, demonstrating spatial variability and high pollution levels. Copyright © 2017

  11. Incorporating Parameter Uncertainty in Bayesian Segmentation Models: Application to Hippocampal Subfield Volumetry

    DEFF Research Database (Denmark)

    Iglesias, J. E.; Sabuncu, M. R.; Van Leemput, Koen

    2012-01-01

    Many successful segmentation algorithms are based on Bayesian models in which prior anatomical knowledge is combined with the available image information. However, these methods typically have many free parameters that are estimated to obtain point estimates only, whereas a faithful Bayesian anal...

  12. Modelling the Success of Learning Management Systems: Application of Latent Class Segmentation Using FIMIX-PLS

    Science.gov (United States)

    Arenas-Gaitán, Jorge; Rondán-Cataluña, Francisco Javier; Ramírez-Correa, Patricio E.

    2018-01-01

    There is not a unique attitude towards the implementation of digital technology in educational sceneries. This paper aims to validate an adaptation of the DeLone and McLean information systems success model in the context of a learning management system. Furthermore, this study means to prove (1) the necessity of segmenting students in order to…

  13. A Hierarchical Building Segmentation in Digital Surface Models for 3D Reconstruction

    Directory of Open Access Journals (Sweden)

    Yiming Yan

    2017-01-01

    Full Text Available In this study, a hierarchical method for segmenting buildings in a digital surface model (DSM, which is used in a novel framework for 3D reconstruction, is proposed. Most 3D reconstructions of buildings are model-based. However, the limitations of these methods are overreliance on completeness of the offline-constructed models of buildings, and the completeness is not easily guaranteed since in modern cities buildings can be of a variety of types. Therefore, a model-free framework using high precision DSM and texture-images buildings was introduced. There are two key problems with this framework. The first one is how to accurately extract the buildings from the DSM. Most segmentation methods are limited by either the terrain factors or the difficult choice of parameter-settings. A level-set method are employed to roughly find the building regions in the DSM, and then a recently proposed ‘occlusions of random textures model’ are used to enhance the local segmentation of the buildings. The second problem is how to generate the facades of buildings. Synergizing with the corresponding texture-images, we propose a roof-contour guided interpolation of building facades. The 3D reconstruction results achieved by airborne-like images and satellites are compared. Experiments show that the segmentation method has good performance, and 3D reconstruction is easily performed by our framework, and better visualization results can be obtained by airborne-like images, which can be further replaced by UAV images.

  14. An explicit statistical model of learning lexical segmentation using multiple cues

    NARCIS (Netherlands)

    Çöltekin, Ça ̆grı; Nerbonne, John; Lenci, Alessandro; Padró, Muntsa; Poibeau, Thierry; Villavicencio, Aline

    2014-01-01

    This paper presents an unsupervised and incremental model of learning segmentation that combines multiple cues whose use by children and adults were attested by experimental studies. The cues we exploit in this study are predictability statistics, phonotactics, lexical stress and partial lexical

  15. Segmentation of heart sound recordings by a duration-dependent hidden Markov model

    International Nuclear Information System (INIS)

    Schmidt, S E; Graff, C; Toft, E; Struijk, J J; Holst-Hansen, C

    2010-01-01

    Digital stethoscopes offer new opportunities for computerized analysis of heart sounds. Segmentation of heart sound recordings into periods related to the first and second heart sound (S1 and S2) is fundamental in the analysis process. However, segmentation of heart sounds recorded with handheld stethoscopes in clinical environments is often complicated by background noise. A duration-dependent hidden Markov model (DHMM) is proposed for robust segmentation of heart sounds. The DHMM identifies the most likely sequence of physiological heart sounds, based on duration of the events, the amplitude of the signal envelope and a predefined model structure. The DHMM model was developed and tested with heart sounds recorded bedside with a commercially available handheld stethoscope from a population of patients referred for coronary arterioangiography. The DHMM identified 890 S1 and S2 sounds out of 901 which corresponds to 98.8% (CI: 97.8–99.3%) sensitivity in 73 test patients and 13 misplaced sounds out of 903 identified sounds which corresponds to 98.6% (CI: 97.6–99.1%) positive predictivity. These results indicate that the DHMM is an appropriate model of the heart cycle and suitable for segmentation of clinically recorded heart sounds

  16. Segmented Assimilation Theory and the Life Model: An Integrated Approach to Understanding Immigrants and Their Children

    Science.gov (United States)

    Piedra, Lissette M.; Engstrom, David W.

    2009-01-01

    The life model offers social workers a promising framework to use in assisting immigrant families. However, the complexities of adaptation to a new country may make it difficult for social workers to operate from a purely ecological approach. The authors use segmented assimilation theory to better account for the specificities of the immigrant…

  17. The commercial use of segmentation and predictive modeling techniques for database marketing in the Netherlands

    NARCIS (Netherlands)

    Verhoef, PC; Spring, PN; Hoekstra, JC; Leeflang, PSH

    Although the application of segmentation and predictive modeling is an important topic in the database marketing (DBM) literature, no study has yet investigated the extent of adoption of these techniques. We present the results of a Dutch survey involving 228 database marketing companies. We find

  18. Modeling of low-capillary number segmented flows in microchannels using OpenFOAM

    NARCIS (Netherlands)

    Hoang, D.A.; Van Steijn, V.; Portela, L.M.; Kreutzer, M.T.; Kleijn, C.R.

    2012-01-01

    Modeling of low-Capillary number segmented flows in microchannels is important for the design of microfluidic devices. We present numerical validations of microfluidic flow simulations using the volume-of-fluid (VOF) method as implemented in OpenFOAM. Two benchmark cases were investigated to ensure

  19. Model selection in Bayesian segmentation of multiple DNA alignments.

    Science.gov (United States)

    Oldmeadow, Christopher; Keith, Jonathan M

    2011-03-01

    The analysis of multiple sequence alignments is allowing researchers to glean valuable insights into evolution, as well as identify genomic regions that may be functional, or discover novel classes of functional elements. Understanding the distribution of conservation levels that constitutes the evolutionary landscape is crucial to distinguishing functional regions from non-functional. Recent evidence suggests that a binary classification of evolutionary rates is inappropriate for this purpose and finds only highly conserved functional elements. Given that the distribution of evolutionary rates is multi-modal, determining the number of modes is of paramount concern. Through simulation, we evaluate the performance of a number of information criterion approaches derived from MCMC simulations in determining the dimension of a model. We utilize a deviance information criterion (DIC) approximation that is more robust than the approximations from other information criteria, and show our information criteria approximations do not produce superfluous modes when estimating conservation distributions under a variety of circumstances. We analyse the distribution of conservation for a multiple alignment comprising four primate species and mouse, and repeat this on two additional multiple alignments of similar species. We find evidence of six distinct classes of evolutionary rates that appear to be robust to the species used. Source code and data are available at http://dl.dropbox.com/u/477240/changept.zip.

  20. Knee cartilage segmentation using active shape models and local binary patterns

    Science.gov (United States)

    González, Germán.; Escalante-Ramírez, Boris

    2014-05-01

    Segmentation of knee cartilage has been useful for opportune diagnosis and treatment of osteoarthritis (OA). This paper presents a semiautomatic segmentation technique based on Active Shape Models (ASM) combined with Local Binary Patterns (LBP) and its approaches to describe the surrounding texture of femoral cartilage. The proposed technique is tested on a 16-image database of different patients and it is validated through Leave- One-Out method. We compare different segmentation techniques: ASM-LBP, ASM-medianLBP, and ASM proposed by Cootes. The ASM-LBP approaches are tested with different ratios to decide which of them describes the cartilage texture better. The results show that ASM-medianLBP has better performance than ASM-LBP and ASM. Furthermore, we add a routine which improves the robustness versus two principal problems: oversegmentation and initialization.

  1. Channeler Ant Model: 3 D segmentation of medical images through ant colonies

    International Nuclear Information System (INIS)

    Fiorina, E.; Valzano, S.; Arteche Diaz, R.; Bosco, P.; Gargano, G.; Megna, R.; Oppedisano, C.; Massafra, A.

    2011-01-01

    In this paper the Channeler Ant Model (CAM) and some results of its application to the analysis of medical images are described. The CAM is an algorithm able to segment 3 D structures with different shapes, intensity and background. It makes use of virtual and colonies and exploits their natural capabilities to modify the environment and communicate with each other by pheromone deposition. Its performance has been validated with the segmentation of 3 D artificial objects and it has been already used successfully in lung nodules detection on Computer Tomography images. This work tries to evaluate the CAM as a candidate to solve the quantitative segmentation problem in Magnetic Resonance brain images: to evaluate the percentage of white matter, gray matter and cerebrospinal fluid in each voxel.

  2. Modeling the Impact of Climate Change on the Dynamics of Rift Valley Fever

    Directory of Open Access Journals (Sweden)

    Saul C. Mpeshe

    2014-01-01

    Full Text Available A deterministic SEIR model of rift valley fever (RVF with climate change parameters was considered to compute the basic reproduction number ℛ0 and investigate the impact of temperature and precipitation on ℛ0. To study the effect of model parameters to ℛ0, sensitivity and elasticity analysis of ℛ0 were performed. When temperature and precipitation effects are not considered, ℛ0 is more sensitive to the expected number of infected Aedes spp. due to one infected livestock and more elastic to the expected number of infected livestock due to one infected Aedes spp. When climatic data are used, ℛ0 is found to be more sensitive and elastic to the expected number of infected eggs laid by Aedes spp. via transovarial transmission, followed by the expected number of infected livestock due to one infected Aedes spp. and the expected number of infected Aedes spp. due to one infected livestock for both regions Arusha and Dodoma. These results call for attention to parameters regarding incubation period, the adequate contact rate of Aedes spp. and livestock, the infective periods of livestock and Aedes spp., and the vertical transmission in Aedes species.

  3. Modeling the Impact of Climate Change on the Dynamics of Rift Valley Fever

    Science.gov (United States)

    Mpeshe, Saul C.; Luboobi, Livingstone S.; Nkansah-Gyekye, Yaw

    2014-01-01

    A deterministic SEIR model of rift valley fever (RVF) with climate change parameters was considered to compute the basic reproduction number ℛ 0 and investigate the impact of temperature and precipitation on ℛ 0. To study the effect of model parameters to ℛ 0, sensitivity and elasticity analysis of ℛ 0 were performed. When temperature and precipitation effects are not considered, ℛ 0 is more sensitive to the expected number of infected Aedes spp. due to one infected livestock and more elastic to the expected number of infected livestock due to one infected Aedes spp. When climatic data are used, ℛ 0 is found to be more sensitive and elastic to the expected number of infected eggs laid by Aedes spp. via transovarial transmission, followed by the expected number of infected livestock due to one infected Aedes spp. and the expected number of infected Aedes spp. due to one infected livestock for both regions Arusha and Dodoma. These results call for attention to parameters regarding incubation period, the adequate contact rate of Aedes spp. and livestock, the infective periods of livestock and Aedes spp., and the vertical transmission in Aedes species. PMID:24795775

  4. Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa.

    Science.gov (United States)

    Redding, David W; Tiedt, Sonia; Lo Iacono, Gianni; Bett, Bernard; Jones, Kate E

    2017-07-19

    Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'. © 2017 The Authors.

  5. Targeting the robo-advice customer: the development of a psychographic segmentation model for financial advice robots

    OpenAIRE

    van Thiel, D.; van Raaij, W.F.

    2017-01-01

    The purpose of this study is to develop the world’s first psychographic market segmentation model that supports personalization, customer education, customer activation, and customer engagement strategies with financial advice robots. As traditional segmentation models in consumer finance primarily focus on externally observed demographics or economic criteria such as profession, age, income, or wealth, post-hoc psychographic segmentation further supports personalization in the digital adviso...

  6. Finite source modelling of magmatic unrest in Socorro, New Mexico, and Long Valley, California

    Science.gov (United States)

    Fialko, Yuri; Simons, Mark; Khazan, Yakov

    2001-07-01

    We investigate surface deformation associated with currently active crustal magma bodies in Socorro, New Mexico, and Long Valley, California, USA. We invert available geodetic data from these locations to constrain the overall geometry and dynamics of the inferred deformation sources at depth. Our best-fitting model for the Socorro magma body is a sill with a depth of 19km, an effective diameter of 70km and a rate of increase in the excess magma pressure of 0.6kPayr-1. We show that the corresponding volumetric inflation rate is ~6×10-3km3yr-1, which is considerably less than previously suggested. The measured inflation rate of the Socorro magma body may result from a steady influx of magma from a deep source, or a volume increase associated with melting of the magma chamber roof (i.e. crustal anatexis). In the latter case, the most recent major injection of mantle-derived melts into the middle crust beneath Socorro may have occurred within the last several tens to several hundreds of years. The Synthetic Interferometric Aperture Radar (InSAR) data collected in the area of the Long Valley caldera, CA, between June 1996 and July 1998 reveal an intracaldera uplift with a maximum amplitude of ~11cm and a volume of 3.5×10-2km3. Modelling of the InSAR data suggests that the observed deformation might be due to either a sill-like magma body at a depth of ~12km or a pluton-like magma body at a depth of ~8km beneath the resurgent dome. Assuming that the caldera fill deforms as an isotropic linear elastic solid, a joint inversion of the InSAR data and two-colour laser geodimeter data (which provide independent constraints on horizontal displacements at the surface) suggests that the inferred magma chamber is a steeply dipping prolate spheroid with a depth of 7-9km and an aspect ratio in excess of 2:1. Our results highlight the need for large radar look angles and multiple look directions in future InSAR missions.

  7. Landslide inventory and susceptibility modelling using geospatial tools, in Hunza-Nagar valley, northern Pakistan

    NARCIS (Netherlands)

    Bacha, Alam Sher; Shafique, Muhammad; van der Werff, H.M.A.

    2018-01-01

    A comprehensive landslide inventory and susceptibility maps are prerequisite for developing and implementing landslide mitigation strategies. Landslide susceptibility maps for the landslides prone regions in northern Pakistan are rarely available. The Hunza-Nagar valley in northern Pakistan is known

  8. The Utility of Cognitive Plausibility in Language Acquisition Modeling: Evidence From Word Segmentation.

    Science.gov (United States)

    Phillips, Lawrence; Pearl, Lisa

    2015-11-01

    The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's cognitive plausibility. We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition model can aim to be cognitively plausible in multiple ways. We discuss these cognitive plausibility checkpoints generally and then apply them to a case study in word segmentation, investigating a promising Bayesian segmentation strategy. We incorporate cognitive plausibility by using an age-appropriate unit of perceptual representation, evaluating the model output in terms of its utility, and incorporating cognitive constraints into the inference process. Our more cognitively plausible model shows a beneficial effect of cognitive constraints on segmentation performance. One interpretation of this effect is as a synergy between the naive theories of language structure that infants may have and the cognitive constraints that limit the fidelity of their inference processes, where less accurate inference approximations are better when the underlying assumptions about how words are generated are less accurate. More generally, these results highlight the utility of incorporating cognitive plausibility more fully into computational models of language acquisition. Copyright © 2015 Cognitive Science Society, Inc.

  9. Three-dimensional model-based object recognition and segmentation in cluttered scenes.

    Science.gov (United States)

    Mian, Ajmal S; Bennamoun, Mohammed; Owens, Robyn

    2006-10-01

    Viewpoint independent recognition of free-form objects and their segmentation in the presence of clutter and occlusions is a challenging task. We present a novel 3D model-based algorithm which performs this task automatically and efficiently. A 3D model of an object is automatically constructed offline from its multiple unordered range images (views). These views are converted into multidimensional table representations (which we refer to as tensors). Correspondences are automatically established between these views by simultaneously matching the tensors of a view with those of the remaining views using a hash table-based voting scheme. This results in a graph of relative transformations used to register the views before they are integrated into a seamless 3D model. These models and their tensor representations constitute the model library. During online recognition, a tensor from the scene is simultaneously matched with those in the library by casting votes. Similarity measures are calculated for the model tensors which receive the most votes. The model with the highest similarity is transformed to the scene and, if it aligns accurately with an object in the scene, that object is declared as recognized and is segmented. This process is repeated until the scene is completely segmented. Experiments were performed on real and synthetic data comprised of 55 models and 610 scenes and an overall recognition rate of 95 percent was achieved. Comparison with the spin images revealed that our algorithm is superior in terms of recognition rate and efficiency.

  10. Stochastic modeling of soundtrack for efficient segmentation and indexing of video

    Science.gov (United States)

    Naphade, Milind R.; Huang, Thomas S.

    1999-12-01

    Tools for efficient and intelligent management of digital content are essential for digital video data management. An extremely challenging research area in this context is that of multimedia analysis and understanding. The capabilities of audio analysis in particular for video data management are yet to be fully exploited. We present a novel scheme for indexing and segmentation of video by analyzing the audio track. This analysis is then applied to the segmentation and indexing of movies. We build models for some interesting events in the motion picture soundtrack. The models built include music, human speech and silence. We propose the use of hidden Markov models to model the dynamics of the soundtrack and detect audio-events. Using these models we segment and index the soundtrack. A practical problem in motion picture soundtracks is that the audio in the track is of a composite nature. This corresponds to the mixing of sounds from different sources. Speech in foreground and music in background are common examples. The coexistence of multiple individual audio sources forces us to model such events explicitly. Experiments reveal that explicit modeling gives better result than modeling individual audio events separately.

  11. Modeling vehicle interior noise exposure dose on freeways: Considering weaving segment designs and engine operation.

    Science.gov (United States)

    Li, Qing; Qiao, Fengxiang; Yu, Lei; Shi, Junqing

    2017-07-05

    Vehicle interior noise functions at the dominant frequencies of 500 Hz below and around 800 Hz, which fall into the bands that may impair hearing. Recent studies demonstrated that freeway commuters are chronically exposed to vehicle interior noise, bearing the risk of hearing impairment. The interior noise evaluation process is mostly conducted in a laboratory environment. The test results and the developed noise models may underestimate or ignore the noise effects from dynamic traffic and road conditions and configuration. However, the interior noise is highly associated with vehicle maneuvering. The vehicle maneuvering on a freeway weaving segment is more complex because of its nature of conflicting areas. This research is intended to explore the risk of the interior noise exposure on freeway weaving segments for freeway commuters and to improve the interior noise estimation by constructing a decision tree learning-based noise exposure dose (NED) model, considering weaving segment designs and engine operation. On-road driving tests were conducted on 12 subjects on State Highway 288 in Houston, Texas. On-board Diagnosis (OBD) II, a smartphone-based roughness app, and a digital sound meter were used to collect vehicle maneuvering and engine information, International Roughness Index, and interior noise levels, respectively. Eleven variables were obtainable from the driving tests, including the length and type of a weaving segment, serving as predictors. The importance of the predictors was estimated by their out-of-bag-permuted predictor delta errors. The hazardous exposure level of the interior noise on weaving segments was quantified to hazard quotient, NED, and daily noise exposure level, respectively. Results showed that the risk of hearing impairment on freeway is acceptable; the interior noise level is the most sensitive to the pavement roughness and is subject to freeway configuration and traffic conditions. The constructed NED model shows high predictive

  12. Ethiopian Central Rift Valley basin hydrologic modelling using HEC-HMS and ArcSWAT

    Science.gov (United States)

    Pascual-Ferrer, Jordi; Candela, Lucila; Pérez-Foguet, Agustí

    2013-04-01

    An Integrated Water Resources Management (IWRM) shall be applied to achieve a sustainable development, to increase population incomes without affecting lives of those who are highly dependent on the environment. First step should be to understand water dynamics at basin level, starting by modeling the basin water resources. For model implementation, a large number of data and parameters are required, but those are not always available, especially in some developing countries where different sources may have different data, there is lack of information on data collection, etc. The Ethiopian Central Rift Valley (CRV) is an endorheic basin covering an area of approximately 10,000 km2. For the period 1996-2005, the average annual volume of rainfall accounted for 9.1 Mm3, and evapotranspiration for 8 Mm3 (Jansen et al., 2007). From the environmental point of view, basin ecosystems are endangered due to human activities. Also, poverty is widespread all over the basin, with population mainly living from agriculture on a subsistence economy. Hence, there is an urgent need to set an IWRM, but datasets required for water dynamics simulation are not too reliable. In order to reduce uncertainty of numerical simulation, two semi-distributed open software hydrologic models were implemented: HEC-HMS and ArcSWAT. HEC-HMS was developed by the United States Army Corps of Engineers (USACoE) Hydrologic Engineering Center (HEC) to run precipitation-runoff simulations for a variety of applications in dendritic watershed systems. ArcSWAT includes the SWAT (Soil and Water Assessment Tool, Arnold et al., 1998) model developed for the USDA Agricultural Research Service into ArcGIS (ESRI®). SWAT was developed to assess the impact of land management practices on large complex watersheds with varying soils, land use and management conditions over long periods of time (Neitsch et al., 2005). According to this, ArcSWAT would be the best option for IWRM implementation in the basin. However

  13. Segmentation and intensity estimation of microarray images using a gamma-t mixture model.

    Science.gov (United States)

    Baek, Jangsun; Son, Young Sook; McLachlan, Geoffrey J

    2007-02-15

    We present a new approach to the analysis of images for complementary DNA microarray experiments. The image segmentation and intensity estimation are performed simultaneously by adopting a two-component mixture model. One component of this mixture corresponds to the distribution of the background intensity, while the other corresponds to the distribution of the foreground intensity. The intensity measurement is a bivariate vector consisting of red and green intensities. The background intensity component is modeled by the bivariate gamma distribution, whose marginal densities for the red and green intensities are independent three-parameter gamma distributions with different parameters. The foreground intensity component is taken to be the bivariate t distribution, with the constraint that the mean of the foreground is greater than that of the background for each of the two colors. The degrees of freedom of this t distribution are inferred from the data but they could be specified in advance to reduce the computation time. Also, the covariance matrix is not restricted to being diagonal and so it allows for nonzero correlation between R and G foreground intensities. This gamma-t mixture model is fitted by maximum likelihood via the EM algorithm. A final step is executed whereby nonparametric (kernel) smoothing is undertaken of the posterior probabilities of component membership. The main advantages of this approach are: (1) it enjoys the well-known strengths of a mixture model, namely flexibility and adaptability to the data; (2) it considers the segmentation and intensity simultaneously and not separately as in commonly used existing software, and it also works with the red and green intensities in a bivariate framework as opposed to their separate estimation via univariate methods; (3) the use of the three-parameter gamma distribution for the background red and green intensities provides a much better fit than the normal (log normal) or t distributions; (4) the

  14. Modelling and Optimization of Four-Segment Shielding Coils of Current Transformers.

    Science.gov (United States)

    Gao, Yucheng; Zhao, Wei; Wang, Qing; Qu, Kaifeng; Li, He; Shao, Haiming; Huang, Songling

    2017-05-26

    Applying shielding coils is a practical way to protect current transformers (CTs) for large-capacity generators from the intensive magnetic interference produced by adjacent bus-bars. The aim of this study is to build a simple analytical model for the shielding coils, from which the optimization of the shielding coils can be calculated effectively. Based on an existing stray flux model, a new analytical model for the leakage flux of partial coils is presented, and finite element method-based simulations are carried out to develop empirical equations for the core-pickup factors of the models. Using the flux models, a model of the common four-segment shielding coils is derived. Furthermore, a theoretical analysis is carried out on the optimal performance of the four-segment shielding coils in a typical six-bus-bars scenario. It turns out that the "all parallel" shielding coils with a 45° starting position have the best shielding performance, whereas the "separated loop" shielding coils with a 0° starting position feature the lowest heating value. Physical experiments were performed, which verified all the models and the conclusions proposed in the paper. In addition, for shielding coils with other than the four-segment configuration, the analysis process will generally be the same.

  15. Analysis of a kinetic multi-segment foot model part II: kinetics and clinical implications.

    Science.gov (United States)

    Bruening, Dustin A; Cooney, Kevin M; Buczek, Frank L

    2012-04-01

    Kinematic multi-segment foot models have seen increased use in clinical and research settings, but the addition of kinetics has been limited and hampered by measurement limitations and modeling assumptions. In this second of two companion papers, we complete the presentation and analysis of a three segment kinetic foot model by incorporating kinetic parameters and calculating joint moments and powers. The model was tested on 17 pediatric subjects (ages 7-18 years) during normal gait. Ground reaction forces were measured using two adjacent force platforms, requiring targeted walking and the creation of two sub-models to analyze ankle, midtarsal, and 1st metatarsophalangeal joints. Targeted walking resulted in only minimal kinematic and kinetic differences compared with walking at self selected speeds. Joint moments and powers were calculated and ensemble averages are presented as a normative database for comparison purposes. Ankle joint powers are shown to be overestimated when using a traditional single-segment foot model, as substantial angular velocities are attributed to the mid-tarsal joint. Power transfer is apparent between the 1st metatarsophalangeal and mid-tarsal joints in terminal stance/pre-swing. While the measurement approach presented here is limited to clinical populations with only minimal impairments, some elements of the model can also be incorporated into routine clinical gait analysis. Copyright © 2011 Elsevier B.V. All rights reserved.

  16. Modeling and analysis of passive dynamic bipedal walking with segmented feet and compliant joints

    Science.gov (United States)

    Huang, Yan; Wang, Qi-Ning; Gao, Yue; Xie, Guang-Ming

    2012-10-01

    Passive dynamic walking has been developed as a possible explanation for the efficiency of the human gait. This paper presents a passive dynamic walking model with segmented feet, which makes the bipedal walking gait more close to natural human-like gait. The proposed model extends the simplest walking model with the addition of flat feet and torsional spring based compliance on ankle joints and toe joints, to achieve stable walking on a slope driven by gravity. The push-off phase includes foot rotations around the toe joint and around the toe tip, which shows a great resemblance to human normal walking. This paper investigates the effects of the segmented foot structure on bipedal walking in simulations. The model achieves satisfactory walking results on even or uneven slopes.

  17. Binding and segmentation via a neural mass model trained with Hebbian and anti-Hebbian mechanisms.

    Science.gov (United States)

    Cona, Filippo; Zavaglia, Melissa; Ursino, Mauro

    2012-04-01

    Synchronization of neural activity in the gamma band, modulated by a slower theta rhythm, is assumed to play a significant role in binding and segmentation of multiple objects. In the present work, a recent neural mass model of a single cortical column is used to analyze the synaptic mechanisms which can warrant synchronization and desynchronization of cortical columns, during an autoassociation memory task. The model considers two distinct layers communicating via feedforward connections. The first layer receives the external input and works as an autoassociative network in the theta band, to recover a previously memorized object from incomplete information. The second realizes segmentation of different objects in the gamma band. To this end, units within both layers are connected with synapses trained on the basis of previous experience to store objects. The main model assumptions are: (i) recovery of incomplete objects is realized by excitatory synapses from pyramidal to pyramidal neurons in the same object; (ii) binding in the gamma range is realized by excitatory synapses from pyramidal neurons to fast inhibitory interneurons in the same object. These synapses (both at points i and ii) have a few ms dynamics and are trained with a Hebbian mechanism. (iii) Segmentation is realized with faster AMPA synapses, with rise times smaller than 1 ms, trained with an anti-Hebbian mechanism. Results show that the model, with the previous assumptions, can correctly reconstruct and segment three simultaneous objects, starting from incomplete knowledge. Segmentation of more objects is possible but requires an increased ratio between the theta and gamma periods.

  18. A two-stage method for microcalcification cluster segmentation in mammography by deformable models

    International Nuclear Information System (INIS)

    Arikidis, N.; Kazantzi, A.; Skiadopoulos, S.; Karahaliou, A.; Costaridou, L.; Vassiou, K.

    2015-01-01

    Purpose: Segmentation of microcalcification (MC) clusters in x-ray mammography is a difficult task for radiologists. Accurate segmentation is prerequisite for quantitative image analysis of MC clusters and subsequent feature extraction and classification in computer-aided diagnosis schemes. Methods: In this study, a two-stage semiautomated segmentation method of MC clusters is investigated. The first stage is targeted to accurate and time efficient segmentation of the majority of the particles of a MC cluster, by means of a level set method. The second stage is targeted to shape refinement of selected individual MCs, by means of an active contour model. Both methods are applied in the framework of a rich scale-space representation, provided by the wavelet transform at integer scales. Segmentation reliability of the proposed method in terms of inter and intraobserver agreements was evaluated in a case sample of 80 MC clusters originating from the digital database for screening mammography, corresponding to 4 morphology types (punctate: 22, fine linear branching: 16, pleomorphic: 18, and amorphous: 24) of MC clusters, assessing radiologists’ segmentations quantitatively by two distance metrics (Hausdorff distance—HDIST cluster , average of minimum distance—AMINDIST cluster ) and the area overlap measure (AOM cluster ). The effect of the proposed segmentation method on MC cluster characterization accuracy was evaluated in a case sample of 162 pleomorphic MC clusters (72 malignant and 90 benign). Ten MC cluster features, targeted to capture morphologic properties of individual MCs in a cluster (area, major length, perimeter, compactness, and spread), were extracted and a correlation-based feature selection method yielded a feature subset to feed in a support vector machine classifier. Classification performance of the MC cluster features was estimated by means of the area under receiver operating characteristic curve (Az ± Standard Error) utilizing tenfold cross

  19. Segmentation of Concealed Objects in Passive Millimeter-Wave Images Based on the Gaussian Mixture Model

    Science.gov (United States)

    Yu, Wangyang; Chen, Xiangguang; Wu, Lei

    2015-04-01

    Passive millimeter wave (PMMW) imaging has become one of the most effective means to detect the objects concealed under clothing. Due to the limitations of the available hardware and the inherent physical properties of PMMW imaging systems, images often exhibit poor contrast and low signal-to-noise ratios. Thus, it is difficult to achieve ideal results by using a general segmentation algorithm. In this paper, an advanced Gaussian Mixture Model (GMM) algorithm for the segmentation of concealed objects in PMMW images is presented. Our work is concerned with the fact that the GMM is a parametric statistical model, which is often used to characterize the statistical behavior of images. Our approach is three-fold: First, we remove the noise from the image using both a notch reject filter and a total variation filter. Next, we use an adaptive parameter initialization GMM algorithm (APIGMM) for simulating the histogram of images. The APIGMM provides an initial number of Gaussian components and start with more appropriate parameter. Bayesian decision is employed to separate the pixels of concealed objects from other areas. At last, the confidence interval (CI) method, alongside local gradient information, is used to extract the concealed objects. The proposed hybrid segmentation approach detects the concealed objects more accurately, even compared to two other state-of-the-art segmentation methods.

  20. Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.

    Science.gov (United States)

    Guo, Yu; Feng, Yuanming; Sun, Jian; Zhang, Ning; Lin, Wang; Sa, Yu; Wang, Ping

    2014-01-01

    The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.

  1. Automatic Lung Tumor Segmentation on PET/CT Images Using Fuzzy Markov Random Field Model

    Directory of Open Access Journals (Sweden)

    Yu Guo

    2014-01-01

    Full Text Available The combination of positron emission tomography (PET and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice’s similarity coefficient (DSC was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.

  2. A FAST SEGMENTATION ALGORITHM FOR C-V MODEL BASED ON EXPONENTIAL IMAGE SEQUENCE GENERATION

    Directory of Open Access Journals (Sweden)

    J. Hu

    2017-09-01

    Full Text Available For the island coastline segmentation, a fast segmentation algorithm for C-V model method based on exponential image sequence generation is proposed in this paper. The exponential multi-scale C-V model with level set inheritance and boundary inheritance is developed. The main research contributions are as follows: 1 the problems of the "holes" and "gaps" are solved when extraction coastline through the small scale shrinkage, low-pass filtering and area sorting of region. 2 the initial value of SDF (Signal Distance Function and the level set are given by Otsu segmentation based on the difference of reflection SAR on land and sea, which are finely close to the coastline. 3 the computational complexity of continuous transition are successfully reduced between the different scales by the SDF and of level set inheritance. Experiment results show that the method accelerates the acquisition of initial level set formation, shortens the time of the extraction of coastline, at the same time, removes the non-coastline body part and improves the identification precision of the main body coastline, which automates the process of coastline segmentation.

  3. a Fast Segmentation Algorithm for C-V Model Based on Exponential Image Sequence Generation

    Science.gov (United States)

    Hu, J.; Lu, L.; Xu, J.; Zhang, J.

    2017-09-01

    For the island coastline segmentation, a fast segmentation algorithm for C-V model method based on exponential image sequence generation is proposed in this paper. The exponential multi-scale C-V model with level set inheritance and boundary inheritance is developed. The main research contributions are as follows: 1) the problems of the "holes" and "gaps" are solved when extraction coastline through the small scale shrinkage, low-pass filtering and area sorting of region. 2) the initial value of SDF (Signal Distance Function) and the level set are given by Otsu segmentation based on the difference of reflection SAR on land and sea, which are finely close to the coastline. 3) the computational complexity of continuous transition are successfully reduced between the different scales by the SDF and of level set inheritance. Experiment results show that the method accelerates the acquisition of initial level set formation, shortens the time of the extraction of coastline, at the same time, removes the non-coastline body part and improves the identification precision of the main body coastline, which automates the process of coastline segmentation.

  4. Automatic and quantitative measurement of collagen gel contraction using model-guided segmentation

    Science.gov (United States)

    Chen, Hsin-Chen; Yang, Tai-Hua; Thoreson, Andrew R.; Zhao, Chunfeng; Amadio, Peter C.; Sun, Yung-Nien; Su, Fong-Chin; An, Kai-Nan

    2013-08-01

    Quantitative measurement of collagen gel contraction plays a critical role in the field of tissue engineering because it provides spatial-temporal assessment (e.g., changes of gel area and diameter during the contraction process) reflecting the cell behavior and tissue material properties. So far the assessment of collagen gels relies on manual segmentation, which is time-consuming and suffers from serious intra- and inter-observer variability. In this study, we propose an automatic method combining various image processing techniques to resolve these problems. The proposed method first detects the maximal feasible contraction range of circular references (e.g., culture dish) and avoids the interference of irrelevant objects in the given image. Then, a three-step color conversion strategy is applied to normalize and enhance the contrast between the gel and background. We subsequently introduce a deformable circular model which utilizes regional intensity contrast and circular shape constraint to locate the gel boundary. An adaptive weighting scheme was employed to coordinate the model behavior, so that the proposed system can overcome variations of gel boundary appearances at different contraction stages. Two measurements of collagen gels (i.e., area and diameter) can readily be obtained based on the segmentation results. Experimental results, including 120 gel images for accuracy validation, showed high agreement between the proposed method and manual segmentation with an average dice similarity coefficient larger than 0.95. The results also demonstrated obvious improvement in gel contours obtained by the proposed method over two popular, generic segmentation methods.

  5. Toward accurate tooth segmentation from computed tomography images using a hybrid level set model

    Energy Technology Data Exchange (ETDEWEB)

    Gan, Yangzhou; Zhao, Qunfei [Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240 (China); Xia, Zeyang, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn; Hu, Ying [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and The Chinese University of Hong Kong, Shenzhen 518055 (China); Xiong, Jing, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 510855 (China); Zhang, Jianwei [TAMS, Department of Informatics, University of Hamburg, Hamburg 22527 (Germany)

    2015-01-15

    Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm{sup 3}) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm{sup 3}, 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm{sup 3}, 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0

  6. Toward accurate tooth segmentation from computed tomography images using a hybrid level set model

    International Nuclear Information System (INIS)

    Gan, Yangzhou; Zhao, Qunfei; Xia, Zeyang; Hu, Ying; Xiong, Jing; Zhang, Jianwei

    2015-01-01

    Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm 3 ) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm 3 , 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm 3 , 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0.28 ± 0.03 mm

  7. Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation.

    Science.gov (United States)

    Wang, Shuo; Zhou, Mu; Liu, Zaiyi; Liu, Zhenyu; Gu, Dongsheng; Zang, Yali; Dong, Di; Gevaert, Olivier; Tian, Jie

    2017-08-01

    Accurate lung nodule segmentation from computed tomography (CT) images is of great importance for image-driven lung cancer analysis. However, the heterogeneity of lung nodules and the presence of similar visual characteristics between nodules and their surroundings make it difficult for robust nodule segmentation. In this study, we propose a data-driven model, termed the Central Focused Convolutional Neural Networks (CF-CNN), to segment lung nodules from heterogeneous CT images. Our approach combines two key insights: 1) the proposed model captures a diverse set of nodule-sensitive features from both 3-D and 2-D CT images simultaneously; 2) when classifying an image voxel, the effects of its neighbor voxels can vary according to their spatial locations. We describe this phenomenon by proposing a novel central pooling layer retaining much information on voxel patch center, followed by a multi-scale patch learning strategy. Moreover, we design a weighted sampling to facilitate the model training, where training samples are selected according to their degree of segmentation difficulty. The proposed method has been extensively evaluated on the public LIDC dataset including 893 nodules and an independent dataset with 74 nodules from Guangdong General Hospital (GDGH). We showed that CF-CNN achieved superior segmentation performance with average dice scores of 82.15% and 80.02% for the two datasets respectively. Moreover, we compared our results with the inter-radiologists consistency on LIDC dataset, showing a difference in average dice score of only 1.98%. Copyright © 2017. Published by Elsevier B.V.

  8. Medical image segmentation by combining graph cuts and oriented active appearance models.

    Science.gov (United States)

    Chen, Xinjian; Udupa, Jayaram K; Bagci, Ulas; Zhuge, Ying; Yao, Jianhua

    2012-04-01

    In this paper, we propose a novel method based on a strategic combination of the active appearance model (AAM), live wire (LW), and graph cuts (GCs) for abdominal 3-D organ segmentation. The proposed method consists of three main parts: model building, object recognition, and delineation. In the model building part, we construct the AAM and train the LW cost function and GC parameters. In the recognition part, a novel algorithm is proposed for improving the conventional AAM matching method, which effectively combines the AAM and LW methods, resulting in the oriented AAM (OAAM). A multiobject strategy is utilized to help in object initialization. We employ a pseudo-3-D initialization strategy and segment the organs slice by slice via a multiobject OAAM method. For the object delineation part, a 3-D shape-constrained GC method is proposed. The object shape generated from the initialization step is integrated into the GC cost computation, and an iterative GC-OAAM method is used for object delineation. The proposed method was tested in segmenting the liver, kidneys, and spleen on a clinical CT data set and also on the MICCAI 2007 Grand Challenge liver data set. The results show the following: 1) The overall segmentation accuracy of true positive volume fraction TPVF > 94.3% and false positive volume fraction can be achieved; 2) the initialization performance can be improved by combining the AAM and LW; 3) the multiobject strategy greatly facilitates initialization; 4) compared with the traditional 3-D AAM method, the pseudo-3-D OAAM method achieves comparable performance while running 12 times faster; and 5) the performance of the proposed method is comparable to state-of-the-art liver segmentation algorithm. The executable version of the 3-D shape-constrained GC method with a user interface can be downloaded from http://xinjianchen.wordpress.com/research/.

  9. Statistical analysis and modelling of weather radar beam propagation conditions in the Po Valley (Italy

    Directory of Open Access Journals (Sweden)

    A. Fornasiero

    2006-01-01

    Full Text Available Ground clutter caused by anomalous propagation (anaprop can affect seriously radar rain rate estimates, particularly in fully automatic radar processing systems, and, if not filtered, can produce frequent false alarms. A statistical study of anomalous propagation detected from two operational C-band radars in the northern Italian region of Emilia Romagna is discussed, paying particular attention to its diurnal and seasonal variability. The analysis shows a high incidence of anaprop in summer, mainly in the morning and evening, due to the humid and hot summer climate of the Po Valley, particularly in the coastal zone. Thereafter, a comparison between different techniques and datasets to retrieve the vertical profile of the refractive index gradient in the boundary layer is also presented. In particular, their capability to detect anomalous propagation conditions is compared. Furthermore, beam path trajectories are simulated using a multilayer ray-tracing model and the influence of the propagation conditions on the beam trajectory and shape is examined. High resolution radiosounding data are identified as the best available dataset to reproduce accurately the local propagation conditions, while lower resolution standard TEMP data suffers from interpolation degradation and Numerical Weather Prediction model data (Lokal Model are able to retrieve a tendency to superrefraction but not to detect ducting conditions. Observing the ray tracing of the centre, lower and upper limits of the radar antenna 3-dB half-power main beam lobe it is concluded that ducting layers produce a change in the measured volume and in the power distribution that can lead to an additional error in the reflectivity estimate and, subsequently, in the estimated rainfall rate.

  10. Generic method for automatic bladder segmentation on cone beam CT using a patient-specific bladder shape model

    International Nuclear Information System (INIS)

    Schoot, A. J. A. J. van de; Schooneveldt, G.; Wognum, S.; Stalpers, L. J. A.; Rasch, C. R. N.; Bel, A.; Hoogeman, M. S.; Chai, X.

    2014-01-01

    Purpose: The aim of this study is to develop and validate a generic method for automatic bladder segmentation on cone beam computed tomography (CBCT), independent of gender and treatment position (prone or supine), using only pretreatment imaging data. Methods: Data of 20 patients, treated for tumors in the pelvic region with the entire bladder visible on CT and CBCT, were divided into four equally sized groups based on gender and treatment position. The full and empty bladder contour, that can be acquired with pretreatment CT imaging, were used to generate a patient-specific bladder shape model. This model was used to guide the segmentation process on CBCT. To obtain the bladder segmentation, the reference bladder contour was deformed iteratively by maximizing the cross-correlation between directional grey value gradients over the reference and CBCT bladder edge. To overcome incorrect segmentations caused by CBCT image artifacts, automatic adaptations were implemented. Moreover, locally incorrect segmentations could be adapted manually. After each adapted segmentation, the bladder shape model was expanded and new shape patterns were calculated for following segmentations. All available CBCTs were used to validate the segmentation algorithm. The bladder segmentations were validated by comparison with the manual delineations and the segmentation performance was quantified using the Dice similarity coefficient (DSC), surface distance error (SDE) and SD of contour-to-contour distances. Also, bladder volumes obtained by manual delineations and segmentations were compared using a Bland-Altman error analysis. Results: The mean DSC, mean SDE, and mean SD of contour-to-contour distances between segmentations and manual delineations were 0.87, 0.27 cm and 0.22 cm (female, prone), 0.85, 0.28 cm and 0.22 cm (female, supine), 0.89, 0.21 cm and 0.17 cm (male, supine) and 0.88, 0.23 cm and 0.17 cm (male, prone), respectively. Manual local adaptations improved the segmentation

  11. Evaluating Hydrologic Transience in Watershed Delineation, Numerical Modeling and Solute Transport in the Great Basin. Clayton Valley, Nevada

    Science.gov (United States)

    Underdown, C. G.; Boutt, D. F.; Hynek, S. A.; Munk, L. A.

    2017-12-01

    Importance of transience in managed groundwater systems is generally determined by timeframe of management decisions. Watersheds with management times shorter than the aquifer (watershed) response time, or the time it takes a watershed to recover from a change in hydrologic state, would not include the new state and are treated as steady-state. However, these watersheds will experience transient response between hydrologic states. Watershed response time is a function of length. Therefore flat, regional watersheds characteristic of the Great Basin have long response times. Defining watershed extents as the area in which the water budget is balanced means inputs equal outputs. Steady-state budgets in the Great Basin have been balanced by extending watershed boundaries to include more area for recharge; however, the length and age of requisite flow paths are poorly constrained and often unrealistic. Inclusion of stored water in hydrologic budget calculations permits water balance within smaller contributing areas. As groundwater flow path lengths, depths, and locations differ between steady-state and transient systems, so do solute transport mechanisms. To observe how transience affects response time and solute transport, a refined (transient) version of the USGS steady-state groundwater flow model of the Great Basin is evaluated. This model is used to assess transient changes in contributing area for Clayton Valley, a lithium-brine producing endorheic basin in southwestern Nevada. Model runs of various recharge, discharge and storage bounds are created from conceptual models based upon historical climate data. Comparing results of the refined model to USGS groundwater observations allows for model validation and comparison against the USGS steady-state model. The transient contributing area to Clayton Valley is 85% smaller than that calculated from the steady-state solution, however several long flow paths important to both water and solute budgets at Clayton Valley

  12. Supplier segmentation model and multicriteria assessment for micro and small enterprise

    Directory of Open Access Journals (Sweden)

    Luiz Felipe de Oliveira Moura Santos

    2016-06-01

    Full Text Available The literature has presented many supplier segmentation models and multicriteria assessments; however, these models do not address the characteristics of micro and small enterprises (MSE, which have scarce resources and seek management tools with a large marginal contribution. The objective of this study is to propose a supplier segmentation model and assessment to address the requirements of MSE’s and to illustrate its practicability through a case study in a small furniture manufacturer. The results showed that the model’s direct benefits do not represent large marginal contributions, but the indirect benefits and the structuration process developed contribute to important consensual decisions and actions for the growth of these organizations.

  13. Ground water in Dale Valley, New York

    Science.gov (United States)

    Randall, Allan D.

    1979-01-01

    Dale Valley is a broad valley segment, enlarged by glacial erosion, at the headwaters of Little Tonawanda Creek near Warsaw , New York. A thin, shallow alluvial aquifer immediately underlies the valley floor but is little used. A deeper gravel aquifer, buried beneath many feet of lake deposits, is tapped by several industrial wells. A finite-difference digital model treated the deep aquifer as two-dimensional with recharge and discharge through a confining layer. It was calibrated by simulating (1) natural conditions, (2) an 18-day aquifer test, and (3) 91 days of well-field operation. Streamflow records and model simulations suggest that in moderately wet years such as 1974, a demand of 750 gallons per minute could be met by withdrawal from the creek and from the aquifer without excessive drawdown at production wells or existing domestic wells. With reasonable but unverified model adjustments to simulate an unusually dry year, the model predicts that a demand of 600 gallons per minute could be met from the same sources. Water high in chloride has migrated from bedrock into parts of the deep aquifer. Industrial pumpage, faults in the bedrock, and the natural flow system may be responsible. (Woodard-USGS)

  14. Tidal Simulations of an Incised-Valley Fluvial System with a Physics-Based Geologic Model

    Science.gov (United States)

    Ghayour, K.; Sun, T.

    2012-12-01

    Physics-based geologic modeling approaches use fluid flow in conjunction with sediment transport and deposition models to devise evolutionary geologic models that focus on underlying physical processes and attempt to resolve them at pertinent spatial and temporal scales. Physics-based models are particularly useful when the evolution of a depositional system is driven by the interplay of autogenic processes and their response to allogenic controls. This interplay can potentially create complex reservoir architectures with high permeability sedimentary bodies bounded by a hierarchy of shales that can effectively impede flow in the subsurface. The complex stratigraphy of tide-influenced fluvial systems is an example of such co-existing and interacting environments of deposition. The focus of this talk is a novel formulation of boundary conditions for hydrodynamics-driven models of sedimentary systems. In tidal simulations, a time-accurate boundary treatment is essential for proper imposition of tidal forcing and fluvial inlet conditions where the flow may be reversed at times within a tidal cycle. As such, the boundary treatment at the inlet has to accommodate for a smooth transition from inflow to outflow and vice-versa without creating numerical artifacts. Our numerical experimentations showed that boundary condition treatments based on a local (frozen) one-dimensional approach along the boundary normal which does not account for the variation of flow quantities in the tangential direction often lead to unsatisfactory results corrupted by numerical artifacts. In this talk, we propose a new boundary treatment that retains all spatial and temporal terms in the model and as such is capable to account for nonlinearities and sharp variations of model variables near boundaries. The proposed approach borrows heavily from the idea set forth by J. Sesterhenn1 for compressible Navier-Stokes equations. The methodology is successfully applied to a tide-influenced incised

  15. Superpixel Segmentation for Polsar Images with Local Iterative Clustering and Heterogeneous Statistical Model

    Science.gov (United States)

    Xiang, D.; Ni, W.; Zhang, H.; Wu, J.; Yan, W.; Su, Y.

    2017-09-01

    Superpixel segmentation has an advantage that can well preserve the target shape and details. In this research, an adaptive polarimetric SLIC (Pol-ASLIC) superpixel segmentation method is proposed. First, the spherically invariant random vector (SIRV) product model is adopted to estimate the normalized covariance matrix and texture for each pixel. A new edge detector is then utilized to extract PolSAR image edges for the initialization of central seeds. In the local iterative clustering, multiple cues including polarimetric, texture, and spatial information are considered to define the similarity measure. Moreover, a polarimetric homogeneity measurement is used to automatically determine the tradeoff factor, which can vary from homogeneous areas to heterogeneous areas. Finally, the SLIC superpixel segmentation scheme is applied to the airborne Experimental SAR and PiSAR L-band PolSAR data to demonstrate the effectiveness of this proposed segmentation approach. This proposed algorithm produces compact superpixels which can well adhere to image boundaries in both natural and urban areas. The detail information in heterogeneous areas can be well preserved.

  16. SUPERPIXEL SEGMENTATION FOR POLSAR IMAGES WITH LOCAL ITERATIVE CLUSTERING AND HETEROGENEOUS STATISTICAL MODEL

    Directory of Open Access Journals (Sweden)

    D. Xiang

    2017-09-01

    Full Text Available Superpixel segmentation has an advantage that can well preserve the target shape and details. In this research, an adaptive polarimetric SLIC (Pol-ASLIC superpixel segmentation method is proposed. First, the spherically invariant random vector (SIRV product model is adopted to estimate the normalized covariance matrix and texture for each pixel. A new edge detector is then utilized to extract PolSAR image edges for the initialization of central seeds. In the local iterative clustering, multiple cues including polarimetric, texture, and spatial information are considered to define the similarity measure. Moreover, a polarimetric homogeneity measurement is used to automatically determine the tradeoff factor, which can vary from homogeneous areas to heterogeneous areas. Finally, the SLIC superpixel segmentation scheme is applied to the airborne Experimental SAR and PiSAR L-band PolSAR data to demonstrate the effectiveness of this proposed segmentation approach. This proposed algorithm produces compact superpixels which can well adhere to image boundaries in both natural and urban areas. The detail information in heterogeneous areas can be well preserved.

  17. VOF Modeling and Analysis of the Segmented Flow in Y-Shaped Microchannels for Microreactor Systems

    Directory of Open Access Journals (Sweden)

    Xian Wang

    2013-01-01

    Full Text Available Microscaled devices receive great attention in microreactor systems for producing high renewable energy due to higher surface-to-volume, higher transport rates (heat or/and mass transfer rates, and other advantages over conventional-size reactors. In this paper, the two-phase liquid-liquid flow in a microchannel with various Y-shaped junctions has been studied numerically. Two kinds of immiscible liquids were injected into a microchannel from the Y-shaped junctions to generate the segment flow mode. The segment length was studied. The volume of fluid (VOF method was used to track the liquid-liquid interface and the piecewise-liner interface construction (PLIC technique was adopted to get a sharp interface. The interfacial tension was simulated with continuum surface force (CSF model and the wall adhesion boundary condition was taken into consideration. The simulated flow pattern presents consistence with our experimental one. The numerical results show that a segmented flow mode appears in the main channel. Under the same inlet velocities of two liquids, the segment lengths of the two liquids are the same and depend on the inclined angles of two lateral channels. The effect of inlet velocity is studied in a typical T-shaped microchannel. It is found that the ratio between the lengths of two liquids is almost equal to the ratio between their inlet velocities.

  18. Optical coherence tomography noise modeling and fundamental bounds on human retinal layer segmentation accuracy (Conference Presentation)

    Science.gov (United States)

    DuBose, Theodore B.; Milanfar, Peyman; Izatt, Joseph A.; Farsiu, Sina

    2016-03-01

    The human retina is composed of several layers, visible by in vivo optical coherence tomography (OCT) imaging. To enhance diagnostics of retinal diseases, several algorithms have been developed to automatically segment one or more of the boundaries of these layers. OCT images are corrupted by noise, which is frequently the result of the detector noise and speckle, a type of coherent noise resulting from the presence of several scatterers in each voxel. However, it is unknown what the empirical distribution of noise in each layer of the retina is, and how the magnitude and distribution of the noise affects the lower bounds of segmentation accuracy. Five healthy volunteers were imaged using a spectral domain OCT probe from Bioptigen, Inc, centered at 850nm with 4.6µm full width at half maximum axial resolution. Each volume was segmented by expert manual graders into nine layers. The histograms of intensities in each layer were then fit to seven possible noise distributions from the literature on speckle and image processing. Using these empirical noise distributions and empirical estimates of the intensity of each layer, the Cramer-Rao lower bound (CRLB), a measure of the variance of an estimator, was calculated for each boundary layer. Additionally, the optimum bias of a segmentation algorithm was calculated, and a corresponding biased CRLB was calculated, which represents the improved performance an algorithm can achieve by using prior knowledge, such as the smoothness and continuity of layer boundaries. Our general mathematical model can be easily adapted for virtually any OCT modality.

  19. Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

    Science.gov (United States)

    Li, X. L.; Zhao, Q. H.; Li, Y.

    2017-09-01

    Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

  20. SEGMENTATION OF 3D MODELS FOR CULTURAL HERITAGE STRUCTURAL ANALYSIS – SOME CRITICAL ISSUES

    Directory of Open Access Journals (Sweden)

    S. Gonizzi Barsanti

    2017-08-01

    Full Text Available Cultural Heritage documentation and preservation has become a fundamental concern in this historical period. 3D modelling offers a perfect aid to record ancient buildings and artefacts and can be used as a valid starting point for restoration, conservation and structural analysis, which can be performed by using Finite Element Methods (FEA. The models derived from reality-based techniques, made up of the exterior surfaces of the objects captured at high resolution, are - for this reason - made of millions of polygons. Such meshes are not directly usable in structural analysis packages and need to be properly pre-processed in order to be transformed in volumetric meshes suitable for FEA. In addition, dealing with ancient objects, a proper segmentation of 3D volumetric models is needed to analyse the behaviour of the structure with the most suitable level of detail for the different sections of the structure under analysis. Segmentation of 3D models is still an open issue, especially when dealing with ancient, complicated and geometrically complex objects that imply the presence of anomalies and gaps, due to environmental agents such as earthquakes, pollution, wind and rain, or human factors. The aims of this paper is to critically analyse some of the different methodologies and algorithms available to segment a 3D point cloud or a mesh, identifying difficulties and problems by showing examples on different structures.

  1. Study of Colour Model for Segmenting Mycobacterium Tuberculosis in Sputum Images

    Science.gov (United States)

    Kurniawardhani, A.; Kurniawan, R.; Muhimmah, I.; Kusumadewi, S.

    2018-03-01

    One of method to diagnose Tuberculosis (TB) disease is sputum test. The presence and number of Mycobacterium tuberculosis (MTB) in sputum are identified. The presence of MTB can be seen under light microscope. Before investigating through stained light microscope, the sputum samples are stained using Ziehl-Neelsen (ZN) stain technique. Because there is no standard procedure in staining, the appearance of sputum samples may vary either in background colour or contrast level. It increases the difficulty in segmentation stage of automatic MTB identification. Thus, this study investigated the colour models to look for colour channels of colour model that can segment MTB well in different stained conditions. The colour models will be investigated are each channel in RGB, HSV, CIELAB, YCbCr, and C-Y colour model and the clustering algorithm used is k-Means. The sputum image dataset used in this study is obtained from community health clinic in a district in Indonesia. The size of each image was set to 1600x1200 pixels which is having variation in number of MTB, background colour, and contrast level. The experiment result indicates that in all image conditions, blue, hue, Cr, and Ry colour channel can be used to segment MTB in one cluster well.

  2. Segmentation of 3d Models for Cultural Heritage Structural Analysis - Some Critical Issues

    Science.gov (United States)

    Gonizzi Barsanti, S.; Guidi, G.; De Luca, L.

    2017-08-01

    Cultural Heritage documentation and preservation has become a fundamental concern in this historical period. 3D modelling offers a perfect aid to record ancient buildings and artefacts and can be used as a valid starting point for restoration, conservation and structural analysis, which can be performed by using Finite Element Methods (FEA). The models derived from reality-based techniques, made up of the exterior surfaces of the objects captured at high resolution, are - for this reason - made of millions of polygons. Such meshes are not directly usable in structural analysis packages and need to be properly pre-processed in order to be transformed in volumetric meshes suitable for FEA. In addition, dealing with ancient objects, a proper segmentation of 3D volumetric models is needed to analyse the behaviour of the structure with the most suitable level of detail for the different sections of the structure under analysis. Segmentation of 3D models is still an open issue, especially when dealing with ancient, complicated and geometrically complex objects that imply the presence of anomalies and gaps, due to environmental agents such as earthquakes, pollution, wind and rain, or human factors. The aims of this paper is to critically analyse some of the different methodologies and algorithms available to segment a 3D point cloud or a mesh, identifying difficulties and problems by showing examples on different structures.

  3. A QFD-Based Mathematical Model for New Product Development Considering the Target Market Segment

    Directory of Open Access Journals (Sweden)

    Liang-Hsuan Chen

    2014-01-01

    Full Text Available Responding to customer needs is important for business success. Quality function deployment provides systematic procedures for converting customer needs into technical requirements to ensure maximum customer satisfaction. The existing literature mainly focuses on the achievement of maximum customer satisfaction under a budgetary limit via mathematical models. The market goal of the new product for the target market segment is usually ignored. In this study, the proposed approach thus considers the target customer satisfaction degree for the target market segment in the model by formulating the overall customer satisfaction as a function of the quality level. In addition, the proposed approach emphasizes the cost-effectiveness concept in the design stage via the achievement of the target customer satisfaction degree using the minimal total cost. A numerical example is used to demonstrate the applicability of the proposed approach and its characteristics are discussed.

  4. 3D Coupled Thermal-Hydraulic Model of the Lower Yarmouk Gorge, Jordan Rift Valley

    Science.gov (United States)

    Walther, M.; Magri, F.; Inbar, N.; Möller, P.; Raggad, M.; Rödiger, T.; Rosenthal, E.; Shentsis, I.; Siebert, C.; Volpi, G.

    2017-12-01

    It is supposed that the Lower Yarmouk Gorge (LYG), in the Jordan Rift Valley acts as the mixing zone of two crossing flow pathways: N-S from the Hermon Mountains and from the Ajlun Dome, and E-W from Jebel al Arab Mountain in Syria (also known as Huran Plateau or Yarmouk drainage basin). As a result, several springs can be found within the gorge. These are characterized by widespread temperatures (20 - 60 °C) which indicate that, beside the complex regional flow, also ascending thermal waters control the hydrologic behavior of the LYG. Previous simulations based on a conceptual simplified 3D model (Magri et al., 2016) showed that crossing flow paths result from the coexistence of convection, that can develop for example along NE-SW oriented faults within the gorge or in permeable aquifers below Maastrichtian aquiclude, and additional flow fields that are induced by the N-S topographic gradients. Here we present the first 3D hydrogeological model of the entire LYG that includes structural features based on actual logs and interpreted seismic lines from both Israeli and Jordanian territories. The model distinguishes seven units from upper Eocene to the Lower Triassic, accounting for major aquifers, aquicludes and deep-cutting faults. Recharges are implemented based on the numerical representation developed by Shentsis (1990) that considers relationships between mean annual rain and topographic elevation. The model reveals that topography-driven N-S and E-W flows strongly control the location of discharge areas while the anomalous spring temperature is not necessarily linked to the presence of fault convection. Local permeability anisotropy due to aquifers folding or facies changes are features sufficient for the rising of hot fluids. Shentsis, I., 1990. Mathematical models for long-term prediction of mountainous river runoff: methods, information and results, Hydrological Sciences Journal, 35:5, 487-500 Magri, F., Möller, S., Inbar, N., Möller, P., Raggad, M., R

  5. Modeled Perfluorooctanoic Acid (PFOA) Exposure and Liver Function in a Mid-Ohio Valley Community.

    Science.gov (United States)

    Darrow, Lyndsey A; Groth, Alyx C; Winquist, Andrea; Shin, Hyeong-Moo; Bartell, Scott M; Steenland, Kyle

    2016-08-01

    , Steenland K. 2016. Modeled perfluorooctanoic acid (PFOA) exposure and liver function in a Mid-Ohio Valley community. Environ Health Perspect 124:1227-1233; http://dx.doi.org/10.1289/ehp.1510391.

  6. Modeling the long-term fate of agricultural nitrate in groundwater in the San Joaquin Valley, California

    Science.gov (United States)

    Chapelle, Francis H.; Campbell, Bruce G.; Widdowson, Mark A.; Landon, Mathew K.

    2013-01-01

    (POC) are the primary electron donors driving active denitrification in groundwater. The purpose of this chapter is to use a numerical mass balance modeling approach to quantitatively compare sources of electron donors (DOC, POC) and electron acceptors (dissolved oxygen, nitrate, and ferric iron) in order to assess the potential for denitrification to attenuate nitrate migration in the Central Valley aquifer.

  7. A QFD-Based Mathematical Model for New Product Development Considering the Target Market Segment

    OpenAIRE

    Chen, Liang-Hsuan; Chen, Cheng-Nien

    2014-01-01

    Responding to customer needs is important for business success. Quality function deployment provides systematic procedures for converting customer needs into technical requirements to ensure maximum customer satisfaction. The existing literature mainly focuses on the achievement of maximum customer satisfaction under a budgetary limit via mathematical models. The market goal of the new product for the target market segment is usually ignored. In this study, the proposed approach thus consider...

  8. Filling Landsat ETM+ SLC-off gaps using a segmentation model approach

    Science.gov (United States)

    Maxwell, Susan

    2004-01-01

    The purpose of this article is to present a methodology for filling Landsat Scan Line Corrector (SLC)-off gaps with same-scene spectral data guided by a segmentation model. Failure of the SLC on the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) instrument resulted in a loss of approximately 25 percent of the spectral data. The missing data span across most of the image with scan gaps varying in size from two pixels near the center of the image to 14 pixels along the east and west edges. Even with the scan gaps, the radiometric and geometric qualities of the remaining portions of the image still meet design specifications and therefore contain useful information (see http:// landsat7.usgs.gov for additional information). The U.S. Geological Survey EROS Data Center (EDC) is evaluating several techniques to fill the gaps in SLC-off data to enhance the usability of the imagery (Howard and Lacasse 2004) (PE&RS, August 2004). The method presented here uses a segmentation model approach that allows for same-scene spectral data to be used to fill the gaps. The segment model is generated from a complete satellite image with no missing spectral data (e.g., Landsat 5, Landsat 7 SLCon, SPOT). The model is overlaid on the Landsat SLC-off image, and the missing data within the gaps are then estimated using SLC-off spectral data that intersect the segment boundary. A major advantage of this approach is that the gaps are filled using spectral data derived from the same SLC-off satellite image.

  9. ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation

    OpenAIRE

    Visin, Francesco; Ciccone, Marco; Romero, Adriana; Kastner, Kyle; Cho, Kyunghyun; Bengio, Yoshua; Matteucci, Matteo; Courville, Aaron

    2015-01-01

    We propose a structured prediction architecture, which exploits the local generic features extracted by Convolutional Neural Networks and the capacity of Recurrent Neural Networks (RNN) to retrieve distant dependencies. The proposed architecture, called ReSeg, is based on the recently introduced ReNet model for image classification. We modify and extend it to perform the more challenging task of semantic segmentation. Each ReNet layer is composed of four RNN that sweep the image horizontally ...

  10. Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images

    Science.gov (United States)

    Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong

    2017-12-01

    Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.

  11. Model-based segmentation of abdominal aortic aneurysms in CTA images

    Science.gov (United States)

    de Bruijne, Marleen; van Ginneken, Bram; Niessen, Wiro J.; Loog, Marco; Viergever, Max A.

    2003-05-01

    Segmentation of thrombus in abdominal aortic aneurysms is complicated by regions of low boundary contrast and by the presence of many neighboring structures in close proximity to the aneurysm wall. We present an automated method that is similar to the well known Active Shape Models (ASM), combining a three-dimensional shape model with a one-dimensional boundary appearance model. Our contribution is twofold: we developed a non-parametric appearance modeling scheme that effectively deals with a highly varying background, and we propose a way of generalizing models of curvilinear structures from small training sets. In contrast with the conventional ASM approach, the new appearance model trains on both true and false examples of boundary profiles. The probability that a given image profile belongs to the boundary is obtained using k nearest neighbor (kNN) probability density estimation. The performance of this scheme is compared to that of original ASMs, which minimize the Mahalanobis distance to the average true profile in the training set. The generalizability of the shape model is improved by modeling the objects axis deformation independent of its cross-sectional deformation. A leave-one-out experiment was performed on 23 datasets. Segmentation using the kNN appearance model significantly outperformed the original ASM scheme; average volume errors were 5.9% and 46% respectively.

  12. Integrated Modeling of Water Policy Futures in the Imperial-Mexicali Valleys

    Science.gov (United States)

    Kjelland, M. K.; Forster, C. B.; Grant, W. E.; Collins, K.

    2004-12-01

    Divided by an international border, the Imperial-Mexicali Valleys (IMVs) are linked by shared history, natural resources, culture and economy. This region is experiencing changes driven by policy makers both within and outside the IMVs. The largest external decision, the Colorado River Quantification Settlement Agreement (QSA) of 2003, opens the door to a laboratory for studying the consequences of a massive transfer of agricultural water to municipal users. Two irrigation districts, two urban water agencies and the State of California have agreed to a 75 year of more than 30 million acre-feet of Colorado River water from agricultural to urban use. Although Imperial Valley farmers will be compensated for water conservation and land fallowing, the economic, environmental and social consequences are unclear. Farmers who fallow will likely cause a greater impact on local businesses and government than those choosing on-field water conservation. Reduced agricultural water use causes reduced flow of irrigation runoff, at higher salinity than before, to the Salton Sea that, in turn, impacts the population dynamics of Ichthyan and Avian species at the Salton Sea. Municipal wastewater discharged into the New River by Mexicali, Mexico is also an important source of inflow to the Salton Sea that will be reduce by plans to reclaim the wastewater for various uses, including cooling water for two new power plants in the Mexicali. A restoration program is funded to produce a Sea with much reduced surface area. But this approach may, in turn, lead to increases in windblown dust from the dry lakebed that will contribute to an air basin already designated as a federal nonattainment area for particulate emissions. Additional water will be conserved by lining the All American and Coachella canals. But, eliminating seepage from the All American canal reduces groundwater recharge to aquifers used by Mexican farmers. A complex interplay of water-related issues must be accounted for if

  13. Two-Segment Foot Model for the Biomechanical Analysis of Squat.

    Science.gov (United States)

    Panero, E; Gastaldi, L; Rapp, W

    2017-01-01

    Squat exercise is acquiring interest in many fields, due to its benefits in improving health and its biomechanical similarities to a wide range of sport motions and the recruitment of many body segments in a single maneuver. Several researches had examined considerable biomechanical aspects of lower limbs during squat, but not without limitations. The main goal of this study focuses on the analysis of the foot contribution during a partial body weight squat, using a two-segment foot model that considers separately the forefoot and the hindfoot. The forefoot and hindfoot are articulated by the midtarsal joint. Five subjects performed a series of three trials, and results were averaged. Joint kinematics and dynamics were obtained using motion capture system, two force plates closed together, and inverse dynamics techniques. The midtarsal joint reached a dorsiflexion peak of 4°. Different strategies between subjects revealed 4° supination and 2.5° pronation of the forefoot. Vertical GRF showed 20% of body weight concentrated on the forefoot and 30% on the hindfoot. The percentages varied during motion, with a peak of 40% on the hindfoot and correspondently 10% on the forefoot, while the traditional model depicted the unique constant 50% value. Ankle peak of plantarflexion moment, power absorption, and power generation was consistent with values estimated by the one-segment model, without statistical significance.

  14. Kinematic repeatability of a multi-segment foot model for dance.

    Science.gov (United States)

    Carter, Sarah L; Sato, Nahoko; Hopper, Luke S

    2018-03-01

    The purpose of this study was to determine the intra and inter-assessor repeatability of a modified Rizzoli Foot Model for analysing the foot kinematics of ballet dancers. Six university-level ballet dancers performed the movements; parallel stance, turnout plié, turnout stance, turnout rise and flex-point-flex. The three-dimensional (3D) position of individual reflective markers and marker triads was used to model the movement of the dancers' tibia, entire foot, hindfoot, midfoot, forefoot and hallux. Intra and inter-assessor reliability demonstrated excellent (ICC ≥ 0.75) repeatability for the first metatarsophalangeal joint in the sagittal plane. Intra-assessor reliability demonstrated excellent (ICC ≥ 0.75) repeatability during flex-point-flex across all inter-segmental angles except for the tibia-hindfoot and hindfoot-midfoot frontal planes. Inter-assessor repeatability ranged from poor to excellent (0.5 > ICC ≥ 0.75) for the 3D segment rotations. The most repeatable measure was the tibia-foot dorsiflexion/plantar flexion articulation whereas the least repeatable measure was the hindfoot-midfoot adduction/abduction articulation. The variation found in the inter-assessor results is likely due to inconsistencies in marker placement. This 3D dance specific multi-segment foot model provides insight into which kinematic measures can be reliably used to ascertain in vivo technical errors and/or biomechanical abnormalities in a dancer's foot motion.

  15. Two-Segment Foot Model for the Biomechanical Analysis of Squat

    Directory of Open Access Journals (Sweden)

    E. Panero

    2017-01-01

    Full Text Available Squat exercise is acquiring interest in many fields, due to its benefits in improving health and its biomechanical similarities to a wide range of sport motions and the recruitment of many body segments in a single maneuver. Several researches had examined considerable biomechanical aspects of lower limbs during squat, but not without limitations. The main goal of this study focuses on the analysis of the foot contribution during a partial body weight squat, using a two-segment foot model that considers separately the forefoot and the hindfoot. The forefoot and hindfoot are articulated by the midtarsal joint. Five subjects performed a series of three trials, and results were averaged. Joint kinematics and dynamics were obtained using motion capture system, two force plates closed together, and inverse dynamics techniques. The midtarsal joint reached a dorsiflexion peak of 4°. Different strategies between subjects revealed 4° supination and 2.5° pronation of the forefoot. Vertical GRF showed 20% of body weight concentrated on the forefoot and 30% on the hindfoot. The percentages varied during motion, with a peak of 40% on the hindfoot and correspondently 10% on the forefoot, while the traditional model depicted the unique constant 50% value. Ankle peak of plantarflexion moment, power absorption, and power generation was consistent with values estimated by the one-segment model, without statistical significance.

  16. Image segmentation of overlapping leaves based on Chan–Vese model and Sobel operator

    Directory of Open Access Journals (Sweden)

    Zhibin Wang

    2018-03-01

    Full Text Available To improve the segmentation precision of overlapping crop leaves, this paper presents an effective image segmentation method based on the Chan–Vese model and Sobel operator. The approach consists of three stages. First, a feature that identifies hues with relatively high levels of green is used to extract the region of leaves and remove the background. Second, the Chan–Vese model and improved Sobel operator are implemented to extract the leaf contours and detect the edges, respectively. Third, a target leaf with a complex background and overlapping is extracted by combining the results obtained by the Chan–Vese model and Sobel operator. To verify the effectiveness of the proposed algorithm, a segmentation experiment was performed on 30 images of cucumber leaf. The mean error rate of the proposed method is 0.0428, which is a decrease of 6.54% compared with the mean error rate of the level set method. Experimental results show that the proposed method can accurately extract the target leaf from cucumber leaf images with complex backgrounds and overlapping regions.

  17. Distinct virulence of Rift Valley fever phlebovirus strains from different genetic lineages in a mouse model.

    Directory of Open Access Journals (Sweden)

    Tetsuro Ikegami

    Full Text Available Rift Valley fever phlebovirus (RVFV causes high rates of abortions and fetal malformations in ruminants, and hemorrhagic fever, encephalitis, or blindness in humans. Viral transmission occurs via mosquito vectors in endemic areas, which necessitates regular vaccination of susceptible livestock animals to prevent the RVF outbreaks. Although ZH501 strain has been used as a challenge strain for past vaccine efficacy studies, further characterization of other RVFV strains is important to optimize ruminant and nonhuman primate RVFV challenge models. This study aimed to characterize the virulence of wild-type RVFV strains belonging to different genetic lineages in outbred CD1 mice. Mice were intraperitoneally infected with 1x103 PFU of wild-type ZH501, Kenya 9800523, Kenya 90058, Saudi Arabia 200010911, OS1, OS7, SA75, Entebbe, or SA51 strains. Among them, mice infected with SA51, Entebbe, or OS7 strain showed rapid dissemination of virus in livers and peracute necrotic hepatitis at 2-3 dpi. Recombinant SA51 (rSA51 and Zinga (rZinga strains were recovered by reverse genetics, and their virulence was also tested in CD1 mice. The rSA51 strain reproduced peracute RVF disease in mice, whereas the rZinga strain showed a similar virulence with that of rZH501 strain. This study showed that RVFV strains in different genetic lineages display distinct virulence in outbred mice. Importantly, since wild-type RVFV strains contain defective-interfering RNA or various genetic subpopulations during passage from original viral isolations, recombinant RVFV strains generated by reverse genetics will be better suitable for reproducible challenge studies for vaccine development as well as pathological studies.

  18. Numerical modeling of Etla Valley aquifer, Oax., Mexico: Evolution and remediation scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Flores-Marquez, E. L; Martinez-Serrano, R. G; Chavez, R. E; Crusillo, Y [Instituto de Geofisica, Universidad Nacional Autonoma de Mexico, Mexico D.F. (Mexico); Jimenez, G [Facultad de Ingenieria, Benemerita Universidad Autonoma de Puebla, Puebla (Mexico); Camops-Enriquez, O [Instituto de Geofisica, Universidad Nacional Autonoma de Mexico, Mexico D.F. (Mexico)

    2008-01-15

    Short-term evolution (for 2001, 2005 and 2015) for the shallow aquifer of Etla Valley, Oaxaca, southern Mexico, was simulated based in a 3D hydrological model elaborated from the available geological, geophysical, geochemical, and hydrologic parameters. The numerical simulations were based on Visual MODFLOW code. These simulations indicate that, if the actual extraction regime is maintained, the drawdown of the potentiometric surface will get worse to the SE of the study area (i. e. beneath Oaxaca city). The prevailing aquifer flow direction favors the ground water pollution by fertilizers and leakage from the sewage network (dumped to the Atoyac river). According to the numerical simulation, remediation of this situation is possible if the wells located in the neighborhood of Oaxaca City are relocated at the recharge zones (i. e. at the feet from Sierra de Juarez). This remediation scenario will allow a recovery of the drawdown of the potentiometric surface. [Spanish] Se presenta un modelo geohidrologico evolutivo 3D a corto plazo (para los anos 2001, 2005 y 2015) del acuifero somero del Valle de Etla, Oaxaca, sureste de Mexico, basado en los parametros disponibles de geologia, geofisica, geoquimica e hidrologia. Las simulaciones numericas fueron realizadas en Visual MODFLOW. Estas simulaciones indican que, si el actual regimen de extraccion es mantenido, el abatimiento de la superficie potenciometrica puede ser mayor en el SE del area de estudio (i. e. cerca de la ciudad de Oaxaca). La contaminacion por fertilizantes y por las fugas de drenaje es favorecida por la direccion de flujo imperante en el acuifero (vaciandose en el rio Atoyac). De acuerdo a las simulaciones numericas, existe una posible remediacion de este proceso, relocalizando los pozos situados en la ciudad de Oaxaca en las zonas de recarga (i. e. en las faldas de la Sierra de Juarez). Este escenario de remediacion permitiria una recuperacion en el nivel de la superficie potenciometrica.

  19. Chagas’ disease: an emergent urban zoonosis. The Caracas Valley (Venezuela as an epidemiological model

    Directory of Open Access Journals (Sweden)

    Servio eUrdaneta-Morales

    2014-12-01

    Full Text Available The unprecedented emergence of important public health and veterinary zoonoses is usually a result of exponential population growth and globalization of human activities. I characterized Chagas´ disease as an emergent zoonosis in the Caracas Valley (Venezuela due to the following findings: the presence of reservoirs (Didelphis marsupialis, Rattus rattus and vectors (Panstrongylus geniculatus, P. rufotuberculatus infected with Trypanosoma cruzi in urbanized or marginalized areas; the elevated contact between P. geniculatus and humans detected by parasitological and molecular examinations of triatomine faeces demonstrated the possibility of transmission risks; a study of outbreaks of urban Chagas´ disease reported the first proven cases of oral transmission of T. cruzi to humans; the risk of transmission of glandular metacyclic stages from marsupials by experimental ocular and oral instillation; mice genitalia infected with T. cruzi contaminated blood resulted in the formation of amastigotes very close to the lumen suggesting that there may be a possibility of infection via their release into the urine and thence to the exterior; the ubiquitous histotropism and histopathology of T. cruzi was demonstrated using a mouse model; the presence of experimental T. cruzi pseudocysts in adipose, bone-cartilage and eye tissue indicated a potential risk for transplants. Socio-sanitary programs that include improvements in housing, vector control and access to medical treatment, as well as strategies aimed at combating social inequalities, poverty and underdevelopment should be undertaken in those areas where zoonoses are most prevalent. Disciplines such as Ecology, Epidemiology, Medical Entomology, Human and Veterinary Medicine, Environmental Studies, Public Health, Social and Political Studies, Immunology, Microbiology and Pharmacology, could all provide important contributions that aim to reduce the occurrence of factors governing the spread of emergent

  20. Modelling the effects of seasonality and socioeconomic impact on the transmission of Rift Valley fever virus

    Science.gov (United States)

    Xiao, Yanyu; Beier, John C.; Cantrell, Robert Stephen; Cosner, Chris; DeAngelis, Donald L.; Ruan, Shigui

    2015-01-01

    Rift Valley fever (RVF) is an important mosquito-borne viral zoonosis in Africa and the Middle East that causes human deaths and significant economic losses due to huge incidences of death and abortion among infected livestock. Outbreaks of RVF are sporadic and associated with both seasonal and socioeconomic effects. Here we propose an almost periodic three-patch model to investigate the transmission dynamics of RVF virus (RVFV) among ruminants with spatial movements. Our findings indicate that, in Northeastern Africa, human activities, including those associated with the Eid al Adha feast, along with a combination of climatic factors such as rainfall level and hydrological variations, contribute to the transmission and dispersal of the disease pathogen. Moreover, sporadic outbreaks may occur when the two events occur together: 1) abundant livestock are recruited into areas at risk from RVF due to the demand for the religious festival and 2) abundant numbers of mosquitoes emerge. These two factors have been shown to have impacts on the severity of RVF outbreaks. Our numerical results present the transmission dynamics of the disease pathogen over both short and long periods of time, particularly during the festival time. Further, we investigate the impact on patterns of disease outbreaks in each patch brought by festival- and seasonal-driven factors, such as the number of livestock imported daily, the animal transportation speed from patch to patch, and the death rate induced by ceremonial sacrifices. In addition, our simulations show that when the time for festival preparation starts earlier than usual, the risk of massive disease outbreaks rises, particularly in patch 3 (the place where the religious ceremony will be held).

  1. Comparison of energy fluxes at the land surface-atmosphere interface in an Alpine valley as simulated with different models

    Directory of Open Access Journals (Sweden)

    G. Grossi

    2003-01-01

    Full Text Available Within the framework of a research project coupling meteorological and hydrological models in mountainous areas a distributed Snow-Soil-Vegetation-Atmosphere Transfer model was developed and applied to simulate the energy fluxes at the land surface – atmosphere interface in an Alpine valley (Toce Valley - North Italy during selected flood events in the last decade. Energy fluxes simulated by the distributed energy transfer model were compared with those simulated by a limited area meteorological model for the event of June 1997 and the differences in the spatial and temporal distribution. The Snow/Soil-Vegetation-Atmosphere Transfer model was also applied to simulate the energy fluxes at the land surface-atmosphere interface for a single cell, assumed to be representative of the Siberia site (Toce Valley, where a micro-meteorological station was installed and operated for 2.5 months in autumn 1999. The Siberia site is very close to the Nosere site, where a standard meteorological station was measuring precipitation, air temperature and humidity, global and net radiation and wind speed during the same special observing period. Data recorded by the standard meteorological station were used to force the energy transfer model and simulate the point energy fluxes at the Siberia site, while turbulent fluxes observed at the Siberia site were used to derive the latent heat flux from the energy balance equation. Finally, the hourly evapotranspiration flux computed by this procedure was compared to the evapotranspiration flux simulated by the energy transfer model. Keywords: energy exchange processes, land surface-atmosphere interactions, turbulent fluxes

  2. A Guide for Using the Transient Ground-Water Flow Model of the Death Valley Regional Ground-Water Flow System, Nevada and California

    Energy Technology Data Exchange (ETDEWEB)

    Joan B. Blainey; Claudia C. Faunt, and Mary C. Hill

    2006-05-16

    This report is a guide for executing numerical simulations with the transient ground-water flow model of the Death Valley regional ground-water flow system, Nevada and California using the U.S. Geological Survey modular finite-difference ground-water flow model, MODFLOW-2000. Model inputs, including observations of hydraulic head, discharge, and boundary flows, are summarized. Modification of the DVRFS transient ground-water model is discussed for two common uses of the Death Valley regional ground-water flow system model: predictive pumping scenarios that extend beyond the end of the model simulation period (1998), and model simulations with only steady-state conditions.

  3. Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration

    Science.gov (United States)

    Sun, Kaioqiong; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Torigian, Drew A.

    2014-03-01

    This paper proposes a thoracic anatomy segmentation method based on hierarchical recognition and delineation guided by a built fuzzy model. Labeled binary samples for each organ are registered and aligned into a 3D fuzzy set representing the fuzzy shape model for the organ. The gray intensity distributions of the corresponding regions of the organ in the original image are recorded in the model. The hierarchical relation and mean location relation between different organs are also captured in the model. Following the hierarchical structure and location relation, the fuzzy shape model of different organs is registered to the given target image to achieve object recognition. A fuzzy connected delineation method is then used to obtain the final segmentation result of organs with seed points provided by recognition. The hierarchical structure and location relation integrated in the model provide the initial parameters for registration and make the recognition efficient and robust. The 3D fuzzy model combined with hierarchical affine registration ensures that accurate recognition can be obtained for both non-sparse and sparse organs. The results on real images are presented and shown to be better than a recently reported fuzzy model-based anatomy recognition strategy.

  4. Preliminary gravity and magnetic models across Midway Valley and Yucca Wash, Yucca Mountain, Nevada

    International Nuclear Information System (INIS)

    Ponce, D.A.; Langenheim, V.E.

    1994-01-01

    Detailed gravity and ground magnetic data collected along ten traverses across Midway Valley and Yucca Wash on the eastern flank of Yucca Mountain in southwest Nevada are interpreted. These data were collected as part of an effort to evaluate faulting in the vicinity of proposed surface facilities for a potential nuclear waste repository at Yucca Mountain. Geophysical data show that Midway Valley is bounded by large gravity and magnetic anomalies associated with the Bow Ridge and Paintbrush Canyon faults, on the west side of Exile Hill and on the west flank of Fran Ridge, respectively. In addition, Midway Valley itself is characterized by a number of small-amplitude anomalies that probably reflect small-scale faulting beneath Midway Valley. Gravity and magnetic data across the northwest trending Yucca Wash and the inferred Yucca Wash fault indicate no major vertical offsets greater than 100 m using a density contrast of 0.2 to 0.3 g/cm 3 along the proposed Yucca Wash fault. In addition, a broad magnetic high coincides with the approximate location of the hydrologic gradient and probably reflects moderately magnetic Topopah Spring Tuff or lavas in the Calico Hills Formation

  5. One-Step Dynamic Classifier Ensemble Model for Customer Value Segmentation with Missing Values

    Directory of Open Access Journals (Sweden)

    Jin Xiao

    2014-01-01

    Full Text Available Scientific customer value segmentation (CVS is the base of efficient customer relationship management, and customer credit scoring, fraud detection, and churn prediction all belong to CVS. In real CVS, the customer data usually include lots of missing values, which may affect the performance of CVS model greatly. This study proposes a one-step dynamic classifier ensemble model for missing values (ODCEM model. On the one hand, ODCEM integrates the preprocess of missing values and the classification modeling into one step; on the other hand, it utilizes multiple classifiers ensemble technology in constructing the classification models. The empirical results in credit scoring dataset “German” from UCI and the real customer churn prediction dataset “China churn” show that the ODCEM outperforms four commonly used “two-step” models and the ensemble based model LMF and can provide better decision support for market managers.

  6. Brain MR image segmentation based on an improved active contour model.

    Directory of Open Access Journals (Sweden)

    Xiangrui Meng

    Full Text Available It is often a difficult task to accurately segment brain magnetic resonance (MR images with intensity in-homogeneity and noise. This paper introduces a novel level set method for simultaneous brain MR image segmentation and intensity inhomogeneity correction. To reduce the effect of noise, novel anisotropic spatial information, which can preserve more details of edges and corners, is proposed by incorporating the inner relationships among the neighbor pixels. Then the proposed energy function uses the multivariate Student's t-distribution to fit the distribution of the intensities of each tissue. Furthermore, the proposed model utilizes Hidden Markov random fields to model the spatial correlation between neigh-boring pixels/voxels. The means of the multivariate Student's t-distribution can be adaptively estimated by multiplying a bias field to reduce the effect of intensity inhomogeneity. In the end, we reconstructed the energy function to be convex and calculated it by using the Split Bregman method, which allows our framework for random initialization, thereby allowing fully automated applications. Our method can obtain the final result in less than 1 second for 2D image with size 256 × 256 and less than 300 seconds for 3D image with size 256 × 256 × 171. The proposed method was compared to other state-of-the-art segmentation methods using both synthetic and clinical brain MR images and increased the accuracies of the results more than 3%.

  7. A Nonparametric Shape Prior Constrained Active Contour Model for Segmentation of Coronaries in CTA Images

    Directory of Open Access Journals (Sweden)

    Yin Wang

    2014-01-01

    Full Text Available We present a nonparametric shape constrained algorithm for segmentation of coronary arteries in computed tomography images within the framework of active contours. An adaptive scale selection scheme, based on the global histogram information of the image data, is employed to determine the appropriate window size for each point on the active contour, which improves the performance of the active contour model in the low contrast local image regions. The possible leakage, which cannot be identified by using intensity features alone, is reduced through the application of the proposed shape constraint, where the shape of circular sampled intensity profile is used to evaluate the likelihood of current segmentation being considered vascular structures. Experiments on both synthetic and clinical datasets have demonstrated the efficiency and robustness of the proposed method. The results on clinical datasets have shown that the proposed approach is capable of extracting more detailed coronary vessels with subvoxel accuracy.

  8. Unsupervised segmentation of lung fields in chest radiographs using multiresolution fractal feature vector and deformable models.

    Science.gov (United States)

    Lee, Wen-Li; Chang, Koyin; Hsieh, Kai-Sheng

    2016-09-01

    Segmenting lung fields in a chest radiograph is essential for automatically analyzing an image. We present an unsupervised method based on multiresolution fractal feature vector. The feature vector characterizes the lung field region effectively. A fuzzy c-means clustering algorithm is then applied to obtain a satisfactory initial contour. The final contour is obtained by deformable models. The results show the feasibility and high performance of the proposed method. Furthermore, based on the segmentation of lung fields, the cardiothoracic ratio (CTR) can be measured. The CTR is a simple index for evaluating cardiac hypertrophy. After identifying a suspicious symptom based on the estimated CTR, a physician can suggest that the patient undergoes additional extensive tests before a treatment plan is finalized.

  9. Infrared dim small target segmentation method based on ALI-PCNN model

    Science.gov (United States)

    Zhao, Shangnan; Song, Yong; Zhao, Yufei; Li, Yun; Li, Xu; Jiang, Yurong; Li, Lin

    2017-10-01

    Pulse Coupled Neural Network (PCNN) is improved by Adaptive Lateral Inhibition (ALI), while a method of infrared (IR) dim small target segmentation based on ALI-PCNN model is proposed in this paper. Firstly, the feeding input signal is modulated by lateral inhibition network to suppress background. Then, the linking input is modulated by ALI, and linking weight matrix is generated adaptively by calculating ALI coefficient of each pixel. Finally, the binary image is generated through the nonlinear modulation and the pulse generator in PCNN. The experimental results show that the segmentation effect as well as the values of contrast across region and uniformity across region of the proposed method are better than the OTSU method, maximum entropy method, the methods based on conventional PCNN and visual attention, and the proposed method has excellent performance in extracting IR dim small target from complex background.

  10. Advances in segmentation modeling for health communication and social marketing campaigns.

    Science.gov (United States)

    Albrecht, T L; Bryant, C

    1996-01-01

    Large-scale communication campaigns for health promotion and disease prevention involve analysis of audience demographic and psychographic factors for effective message targeting. A variety of segmentation modeling techniques, including tree-based methods such as Chi-squared Automatic Interaction Detection and logistic regression, are used to identify meaningful target groups within a large sample or population (N = 750-1,000+). Such groups are based on statistically significant combinations of factors (e.g., gender, marital status, and personality predispositions). The identification of groups or clusters facilitates message design in order to address the particular needs, attention patterns, and concerns of audience members within each group. We review current segmentation techniques, their contributions to conceptual development, and cost-effective decision making. Examples from a major study in which these strategies were used are provided from the Texas Women, Infants and Children Program's Comprehensive Social Marketing Program.

  11. A double-panel active segmented partition module using decoupled analog feedback controllers: numerical model.

    Science.gov (United States)

    Sagers, Jason D; Leishman, Timothy W; Blotter, Jonathan D

    2009-06-01

    Low-frequency sound transmission has long plagued the sound isolation performance of lightweight partitions. Over the past 2 decades, researchers have investigated actively controlled structures to prevent sound transmission from a source space into a receiving space. An approach using active segmented partitions (ASPs) seeks to improve low-frequency sound isolation capabilities. An ASP is a partition which has been mechanically and acoustically segmented into a number of small individually controlled modules. This paper provides a theoretical and numerical development of a single ASP module configuration, wherein each panel of the double-panel structure is independently actuated and controlled by an analog feedback controller. A numerical model is developed to estimate frequency response functions for the purpose of controller design, to understand the effects of acoustic coupling between the panels, to predict the transmission loss of the module in both passive and active states, and to demonstrate that the proposed ASP module will produce bidirectional sound isolation.

  12. Segmenting Bone Parts for Bone Age Assessment using Point Distribution Model and Contour Modelling

    Science.gov (United States)

    Kaur, Amandeep; Singh Mann, Kulwinder, Dr.

    2018-01-01

    Bone age assessment (BAA) is a task performed on radiographs by the pediatricians in hospitals to predict the final adult height, to diagnose growth disorders by monitoring skeletal development. For building an automatic bone age assessment system the step in routine is to do image pre-processing of the bone X-rays so that features row can be constructed. In this research paper, an enhanced point distribution algorithm using contours has been implemented for segmenting bone parts as per well-established procedure of bone age assessment that would be helpful in building feature row and later on; it would be helpful in construction of automatic bone age assessment system. Implementation of the segmentation algorithm shows high degree of accuracy in terms of recall and precision in segmenting bone parts from left hand X-Rays.

  13. A MULTI-RESOLUTION FUSION MODEL INCORPORATING COLOR AND ELEVATION FOR SEMANTIC SEGMENTATION

    Directory of Open Access Journals (Sweden)

    W. Zhang

    2017-05-01

    Full Text Available In recent years, the developments for Fully Convolutional Networks (FCN have led to great improvements for semantic segmentation in various applications including fused remote sensing data. There is, however, a lack of an in-depth study inside FCN models which would lead to an understanding of the contribution of individual layers to specific classes and their sensitivity to different types of input data. In this paper, we address this problem and propose a fusion model incorporating infrared imagery and Digital Surface Models (DSM for semantic segmentation. The goal is to utilize heterogeneous data more accurately and effectively in a single model instead of to assemble multiple models. First, the contribution and sensitivity of layers concerning the given classes are quantified by means of their recall in FCN. The contribution of different modalities on the pixel-wise prediction is then analyzed based on visualization. Finally, an optimized scheme for the fusion of layers with color and elevation information into a single FCN model is derived based on the analysis. Experiments are performed on the ISPRS Vaihingen 2D Semantic Labeling dataset. Comprehensive evaluations demonstrate the potential of the proposed approach.

  14. Analysis of the flexural mode response of a novel trimaran by segmented model test

    Directory of Open Access Journals (Sweden)

    Karim Akbari Vakilabadi

    Full Text Available A novel ship concept design is significantly an "adhoc" process. In the preliminary design stage of novel vessels, it is very important to be able to develop an initial estimate of the effects of stiffness and mass distribution on the longitudinal flexural natural frequencies due to different general arrangements in still water at zero speed to satisfy design specifications. For new emerging designs, this estimate has to be made based on a model test. The experiments should also be planned so that scales effects and other features that are not present in full scale case, are minimized. A model with a length of 1.5 meter has been selected. The model was cut into four segments longitudinally and connected by a backbone beam with three elastic hinges joining the four segments. Wet vibration tests were conducted on the model, showed significant influences on the flexural natural frequencies through variations in stiffness and different mass distributions. The whipping frequency was calculated with four degrees of freedom theoretical model to compare with the experimental results. The theoretical model shows a good agreement with the experimental results.

  15. Segmentation of laser range radar images using hidden Markov field models

    International Nuclear Information System (INIS)

    Pucar, P.

    1993-01-01

    Segmentation of images in the context of model based stochastic techniques is connected with high, very often unpracticle computational complexity. The objective with this thesis is to take the models used in model based image processing, simplify and use them in suboptimal, but not computationally demanding algorithms. Algorithms that are essentially one-dimensional, and their extensions to two dimensions are given. The model used in this thesis is the well known hidden Markov model. Estimation of the number of hidden states from observed data is a problem that is addressed. The state order estimation problem is of general interest and is not specifically connected to image processing. An investigation of three state order estimation techniques for hidden Markov models is given. 76 refs

  16. Parametric modelling and segmentation of vertebral bodies in 3D CT and MR spine images

    International Nuclear Information System (INIS)

    Štern, Darko; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž

    2011-01-01

    Accurate and objective evaluation of vertebral deformations is of significant importance in clinical diagnostics and therapy of pathological conditions affecting the spine. Although modern clinical practice is focused on three-dimensional (3D) computed tomography (CT) and magnetic resonance (MR) imaging techniques, the established methods for evaluation of vertebral deformations are limited to measuring deformations in two-dimensional (2D) x-ray images. In this paper, we propose a method for quantitative description of vertebral body deformations by efficient modelling and segmentation of vertebral bodies in 3D. The deformations are evaluated from the parameters of a 3D superquadric model, which is initialized as an elliptical cylinder and then gradually deformed by introducing transformations that yield a more detailed representation of the vertebral body shape. After modelling the vertebral body shape with 25 clinically meaningful parameters and the vertebral body pose with six rigid body parameters, the 3D model is aligned to the observed vertebral body in the 3D image. The performance of the method was evaluated on 75 vertebrae from CT and 75 vertebrae from T 2 -weighted MR spine images, extracted from the thoracolumbar part of normal and pathological spines. The results show that the proposed method can be used for 3D segmentation of vertebral bodies in CT and MR images, as the proposed 3D model is able to describe both normal and pathological vertebral body deformations. The method may therefore be used for initialization of whole vertebra segmentation or for quantitative measurement of vertebral body deformations.

  17. Pulmonary parenchyma segmentation in thin CT image sequences with spectral clustering and geodesic active contour model based on similarity

    Science.gov (United States)

    He, Nana; Zhang, Xiaolong; Zhao, Juanjuan; Zhao, Huilan; Qiang, Yan

    2017-07-01

    While the popular thin layer scanning technology of spiral CT has helped to improve diagnoses of lung diseases, the large volumes of scanning images produced by the technology also dramatically increase the load of physicians in lesion detection. Computer-aided diagnosis techniques like lesions segmentation in thin CT sequences have been developed to address this issue, but it remains a challenge to achieve high segmentation efficiency and accuracy without much involvement of human manual intervention. In this paper, we present our research on automated segmentation of lung parenchyma with an improved geodesic active contour model that is geodesic active contour model based on similarity (GACBS). Combining spectral clustering algorithm based on Nystrom (SCN) with GACBS, this algorithm first extracts key image slices, then uses these slices to generate an initial contour of pulmonary parenchyma of un-segmented slices with an interpolation algorithm, and finally segments lung parenchyma of un-segmented slices. Experimental results show that the segmentation results generated by our method are close to what manual segmentation can produce, with an average volume overlap ratio of 91.48%.

  18. Active surface model improvement by energy function optimization for 3D segmentation.

    Science.gov (United States)

    Azimifar, Zohreh; Mohaddesi, Mahsa

    2015-04-01

    This paper proposes an optimized and efficient active surface model by improving the energy functions, searching method, neighborhood definition and resampling criterion. Extracting an accurate surface of the desired object from a number of 3D images using active surface and deformable models plays an important role in computer vision especially medical image processing. Different powerful segmentation algorithms have been suggested to address the limitations associated with the model initialization, poor convergence to surface concavities and slow convergence rate. This paper proposes a method to improve one of the strongest and recent segmentation algorithms, namely the Decoupled Active Surface (DAS) method. We consider a gradient of wavelet edge extracted image and local phase coherence as external energy to extract more information from images and we use curvature integral as internal energy to focus on high curvature region extraction. Similarly, we use resampling of points and a line search for point selection to improve the accuracy of the algorithm. We further employ an estimation of the desired object as an initialization for the active surface model. A number of tests and experiments have been done and the results show the improvements with regards to the extracted surface accuracy and computational time of the presented algorithm compared with the best and recent active surface models. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. 3D hydrogeological model of the Lower Yarmouk Gorge, Jordan Rift Valley

    Science.gov (United States)

    Magri, Fabien; Inbar, Nimrod; Möller, Peter; Raggad, Marwan; Rödiger, Tino; Rosenthal, Eliahu; Shentsis, Izabela; Tzoufka, Kalliopi; Siebert, Christian

    2017-04-01

    The Lower Yarmouk Gorge (LYG) lies on the eastern margin of the lower Jordan Rift Valley (JRV), bounded to the south by the Ajlun and to the north by the Golan Heights. It allows the outflow of the Yarmouk drainage basin and flow into the Jordan River, a few kilometers south of Lake Tiberias. The main aquifer system of the LYG is built mostly of Cretaceous sandstones and carbonates confined by Maastrichtian aquiclude. Fissures allow hydraulic connections between the major water-bearing formations from Quaternary to Upper Cretaceous age. It is supposed that the gorge acts as the mixing zone of two crossing flow pathways: N-S from the Hermon Mountains and from the Ajlun Dome, and E-W from Jebel al Arab Mountain in Syria (also known as Huran Plateau or Yarmouk drainage basin). As a result, several springs can be found within the gorge. These are characterized by widespread temperatures (20 - 60 °C) which indicate that, beside the complex regional flow, also ascending thermal waters control the hydrologic behavior of the LYG. Previous simulations based on a conceptual simplified 3D model (Magri et al., 2016) showed that crossing flow paths result from the coexistence of convection, that can develop for example along NE-SW oriented faults within the gorge or in permeable aquifers below Maastrichtian aquiclude, and additional flow fields that are induced by the N-S topographic gradients. Here we present the first 3D hydrogeological model of the entire LYG that includes structural features based on actual logs and interpreted seismic lines from both Israeli and Jordanian territories. The model distinguishes seven units from upper Eocene to the Lower Triassic, accounting for major aquifers, aquicludes and deep-cutting faults. Recharges are implemented based on the numerical representation developed by Shentsis (1990) that considers relationships between mean annual rain and topographic elevation. The model reveals that topography-driven N-S and E-W flows strongly control

  20. Assessing Drought Impacts on Water Storage using GRACE Satellites and Regional Groundwater Modeling in the Central Valley of California

    Science.gov (United States)

    Scanlon, B. R.; Zhang, Z.; Save, H.; Faunt, C. C.; Dettinger, M. D.

    2015-12-01

    Increasing concerns about drought impacts on water resources in California underscores the need to better understand effects of drought on water storage and coping strategies. Here we use a new GRACE mascons solution with high spatial resolution (1 degree) developed at the Univ. of Texas Center for Space Research (CSR) and output from the most recent regional groundwater model developed by the U.S. Geological Survey to evaluate changes in water storage in response to recent droughts. We also extend the analysis of drought impacts on water storage back to the 1980s using modeling and monitoring data. The drought has been intensifying since 2012 with almost 50% of the state and 100% of the Central Valley under exceptional drought in 2015. Total water storage from GRACE data declined sharply during the current drought, similar to the rate of depletion during the previous drought in 2007 - 2009. However, only 45% average recovery between the two droughts results in a much greater cumulative impact of both droughts. The CSR GRACE Mascons data offer unprecedented spatial resolution with no leakage to the oceans and no requirement for signal restoration. Snow and reservoir storage declines contribute to the total water storage depletion estimated by GRACE with the residuals attributed to groundwater storage. Rates of groundwater storage depletion are consistent with the results of regional groundwater modeling in the Central Valley. Traditional approaches to coping with these climate extremes has focused on surface water reservoir storage; however, increasing conjunctive use of surface water and groundwater and storing excess water from wet periods in depleted aquifers is increasing in the Central Valley.

  1. Population growth and collapse in a multiagent model of the Kayenta Anasazi in Long House Valley

    OpenAIRE

    Axtell, Robert L.; Epstein, Joshua M.; Dean, Jeffrey S.; Gumerman, George J.; Swedlund, Alan C.; Harburger, Jason; Chakravarty, Shubha; Hammond, Ross; Parker, Jon; Parker, Miles

    2002-01-01

    Long House Valley in the Black Mesa area of northeastern Arizona (U.S.) was inhabited by the Kayenta Anasazi from about 1800 before Christ to about anno Domini 1300. These people were prehistoric ancestors of the modern Pueblo cultures of the Colorado Plateau. Paleoenvironmental research based on alluvial geomorphology, palynology, and dendroclimatology permits accurate quantitative reconstruction of annual fluctuations in potential agricultural production (kg of maize per hectare). The archa...

  2. Extraction of the mode shapes of a segmented ship model with a hydroelastic response

    Directory of Open Access Journals (Sweden)

    Yooil Kim

    2015-11-01

    Full Text Available The mode shapes of a segmented hull model towed in a model basin were predicted using both the Proper Orthogonal Decomposition (POD and cross random decrement technique. The proper orthogonal decomposition, which is also known as Karhunen-Loeve decomposition, is an emerging technology as a useful signal processing technique in structural dynamics. The technique is based on the fact that the eigenvectors of a spatial coherence matrix become the mode shapes of the system under free and randomly excited forced vibration conditions. Taking advantage of the sim-plicity of POD, efforts have been made to reveal the mode shapes of vibrating flexible hull under random wave ex-citation. First, the segmented hull model of a 400 K ore carrier with 3 flexible connections was towed in a model basin under different sea states and the time histories of the vertical bending moment at three different locations were meas-ured. The measured response time histories were processed using the proper orthogonal decomposition, eventually to obtain both the first and second vertical vibration modes of the flexible hull. A comparison of the obtained mode shapes with those obtained using the cross random decrement technique showed excellent correspondence between the two results.

  3. The dynamics of monolithic suspensions for advanced detectors: A 3-segment model

    Energy Technology Data Exchange (ETDEWEB)

    Piergiovanni, F; Campagna, E; Cesarini, E; Martelli, F; Vetrano, F; Vicere, A [Universita di Urbino, Via S.Chiara 27, 61029 Urbino (Italy); Lorenzini, M; Cagnoli, G; Losurdo, G, E-mail: piergiovanni@fi.infn.i [INFN, Istituto Nazionale di Fisica Nucleare, Sez. di Firenze, via G. Sansone 1, 50019 Sesto Fiorentino (Italy)

    2010-05-01

    In order to reduce the suspension thermal noise, the second generation GW interferometric detectors will employ monolithic suspensions in fused silica to hold the mirrors. The fibres are produced by melting and pulling apart a fused silica rod, obtaining a long thin wire with two thicker heads. The dynamics of such a fibre is in principle different from that of a cylindrical, regular fibre, because most of the deformation energy is stored in the neck region where the diameter is variable. This is an advantage, since adjusting the neck tapering, a thermoelastic noise cancellation effect can be obtained. Therefore, a careful study of the suspensions behavior is necessary to estimate the overall noise and to optimize the control strategy. To simplify the control design, a simple three segment model for the silica fibres has been developed, fully equivalent to the beam equation at low frequencies. The model, analytically proved for a regular cylindrical fibre, can be extended to a fibre with tapered necks, provided that the equivalent bending length is suitably measured. We developed a tool to measure the position of the bending point for each fibre, thus allowing to experimentally check the validity of the model. A numerical code has been written to solve the beam equation for wires with varying diameter. This code confirms the validity of the three segment model. Moreover, it is possible to extend the solution to higher frequencies thus computing the transfer function and the energy distribution of the suspension system and estimating the thermal noise contribution.

  4. An Evaluation of Mesoscale Model Predictions of Down-Valley and Canyon Flows and Their Consequences Using Doppler Lidar Measurements During VTMX 2000

    International Nuclear Information System (INIS)

    Fast, Jerome D.; Darby, Lisa S.

    2004-01-01

    A mesoscale model, a Lagrangian particle dispersion model, and extensive Doppler lidar wind measurements during the VTMX 2000 field campaign were used to examine converging flows over the Salt Lake Valley and their effect on vertical mixing of tracers at night and during the morning transition period. The simulated wind components were transformed into radial velocities to make a direct comparison with about 1.3 million Doppler lidar data points and critically evaluate, using correlation coefficients, the spatial variations in the simulated wind fields aloft. The mesoscale model captured reasonably well the general features of the observed circulations including the daytime up-valley flow, the nighttime slope, canyon, and down-valley flows, and the convergence of the flows over the valley. When there were errors in the simulated wind fields, they were usually associated with the timing, structure, or strength of specific flows. Simulated outflows from canyons along the Wasatch Mountains propagated over the valley and converged with the down-valley flow, but the advance and retreat of these simulated flows was often out of phase with the lidar measurements. While the flow reversal during the evening transition period produced rising motions over much of the valley atmosphere in the absence of significant ambient winds, average vertical velocities became close to zero as the down-valley flow developed. Still, vertical velocities between 5 and 15 cm s-1 occurred where down-slope, canyon and down-valley flows converged and vertical velocities greater than 50 cm s-1 were produced by hydraulic jumps at the base of the canyons. The presence of strong ambient winds resulted in smaller average rising motions during the evening transition period and larger average vertical velocities after that. A fraction of the tracer released at the surface was transported up to the height of the surrounding mountains; however, higher concentrations were produced aloft for evening s

  5. How sedimentation affects rift segment interaction during oblique extension: a 4D analogue modelling study

    Science.gov (United States)

    Zwaan, Frank; Schreurs, Guido; Adam, Jürgen

    2017-04-01

    During the early stages of rifting, rift segments may form along non-continuous and/or offset pre-existing weaknesses. It is important to understand how these initial rift segments interact and connect to form a continuous rift system. Previous modelling of rift interaction structures has shown the dominant influence of oblique extension, promoting rift segment linkage (e.g. Zwaan et al., 2016) and eventual continent break-up (Brune et al., 2012). However, these studies did not incorporate sedimentation, which can have important implications for rift evolution (e.g. Bialas and Buck, 2009). Here we present a series of analogue model experiments investigating the influence of sedimentation on rift interaction structures under oblique extension conditions. Our set-up involves a base of compressed foam and plexiglass that forces distributed extension in the overlying analogue materials when the model sidewalls move apart. A sand layer simulates the brittle upper crust and a viscous sand/silicone mixture the ductile lower crust. One of the underlying base plates can move laterally allowing oblique extension. Right-stepping offset and disconnected lines of silicone (seeds) on top of the basal viscous serve as inherited structures since the strong sand cover is locally thinner. We apply syn-rift sediments by filling in the developing rift and transfer zone basins with sand at fixed time steps. Models are run either with sedimentation or without to allow comparison. The first results suggest that the gross structures are similar with or without sedimentation. As seen by Zwaan et al. (2016), dextral oblique extension promotes rift linkage because rift propagation aligns itself perpendicular to the extension direction. This causes the rift segments to grow towards each other and to establish a continuous rift structure. However, the structures within the rift segments show quite different behaviour when sedimentation is applied. The extra sediment loading in the rift basin

  6. Apparel shopping behaviour – Part 2: Conceptual theoretical model, market segments, profiles and implications

    Directory of Open Access Journals (Sweden)

    R. Du Preez

    2003-10-01

    Full Text Available This article is based on the conceptual theoretical model developed in Part 1 of this series of articles. The objective of this research is to identify female apparel consumer market segments on the basis of differentiating lifestyles, shopping orientation, cultural consciousness, store patronage and demographics. These profiles are discussed in full and the implications thereof for retailers, marketers and researchers are highlighted. A new conceptual model is proposed and recommendations are made for further research. Opsomming Hierdie artikel word gebaseer op die konseptuele teoretiese model wat reeds in Deel 1 van hierdie artikelreeks ontwikkel is. Die doel van hierdie navorsing is om marksegmente van vroue klere-kopers te identifiseer na aanleiding van hulle lewenstyle, kooporiëntasie, kulturele bewustheid, winkelvoorkeurgedrag en demografie. Hierdie profiele word volledig beskryf en die implikasies van die verskillende profiele vir kleinhandelaars, bemarkers en navorsers word uitgelig. ’n Nuwe konseptuele model word voorgestel en aanbevelings vir verdere navorsing word gemaak.

  7. Modeled inundation limits of potential lahars from Mount Adams in the White Salmon River Valley, Washington

    Science.gov (United States)

    Griswold, Julia P.; Pierson, Thomas C.; Bard, Joseph A.

    2018-05-09

    inundation zones accompanying this report, shown in two different map perspectives, is intended to augment (not replace) the existing hazard maps for Mount Adams (W.E. Scott and others, 1995; Vallance, 1999). The maps in this report show potential areas of inundation by lahars of different initial volumes, which are determined by a computer model, LAHARZ (Iverson and others, 1998; Schilling, 1998). One map sheet presents LAHARZ-determined inundation areas on a normal plan-view shaded-relief map of the study area; the other gives an oblique perspective of the landscape with raised topography, as if one were viewing the landscape at an angle from an aircraft (Jenny and Patterson, 2007). LAHARZ was developed after the original hazard maps (based only on mapping of geologic deposits) were made. Predicted inundation zones on these maps provide an alternative approach to estimation of areas that could be inundated as lahars of different volumes pass through the valley. However, there is considerable uncertainty in the exact location of the hazard-zone boundaries shown on these maps, as well as on earlier maps.

  8. Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields.

    Science.gov (United States)

    Robinson, Sean; Guyon, Laurent; Nevalainen, Jaakko; Toriseva, Mervi; Åkerfelt, Malin; Nees, Matthias

    2015-01-01

    Organotypic, three dimensional (3D) cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs) and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs). The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy.

  9. Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields.

    Directory of Open Access Journals (Sweden)

    Sean Robinson

    Full Text Available Organotypic, three dimensional (3D cell culture models of epithelial tumour types such as prostate cancer recapitulate key aspects of the architecture and histology of solid cancers. Morphometric analysis of multicellular 3D organoids is particularly important when additional components such as the extracellular matrix and tumour microenvironment are included in the model. The complexity of such models has so far limited their successful implementation. There is a great need for automatic, accurate and robust image segmentation tools to facilitate the analysis of such biologically relevant 3D cell culture models. We present a segmentation method based on Markov random fields (MRFs and illustrate our method using 3D stack image data from an organotypic 3D model of prostate cancer cells co-cultured with cancer-associated fibroblasts (CAFs. The 3D segmentation output suggests that these cell types are in physical contact with each other within the model, which has important implications for tumour biology. Segmentation performance is quantified using ground truth labels and we show how each step of our method increases segmentation accuracy. We provide the ground truth labels along with the image data and code. Using independent image data we show that our segmentation method is also more generally applicable to other types of cellular microscopy and not only limited to fluorescence microscopy.

  10. Prostate segmentation in MRI using a convolutional neural network architecture and training strategy based on statistical shape models.

    Science.gov (United States)

    Karimi, Davood; Samei, Golnoosh; Kesch, Claudia; Nir, Guy; Salcudean, Septimiu E

    2018-05-15

    Most of the existing convolutional neural network (CNN)-based medical image segmentation methods are based on methods that have originally been developed for segmentation of natural images. Therefore, they largely ignore the differences between the two domains, such as the smaller degree of variability in the shape and appearance of the target volume and the smaller amounts of training data in medical applications. We propose a CNN-based method for prostate segmentation in MRI that employs statistical shape models to address these issues. Our CNN predicts the location of the prostate center and the parameters of the shape model, which determine the position of prostate surface keypoints. To train such a large model for segmentation of 3D images using small data (1) we adopt a stage-wise training strategy by first training the network to predict the prostate center and subsequently adding modules for predicting the parameters of the shape model and prostate rotation, (2) we propose a data augmentation method whereby the training images and their prostate surface keypoints are deformed according to the displacements computed based on the shape model, and (3) we employ various regularization techniques. Our proposed method achieves a Dice score of 0.88, which is obtained by using both elastic-net and spectral dropout for regularization. Compared with a standard CNN-based method, our method shows significantly better segmentation performance on the prostate base and apex. Our experiments also show that data augmentation using the shape model significantly improves the segmentation results. Prior knowledge about the shape of the target organ can improve the performance of CNN-based segmentation methods, especially where image features are not sufficient for a precise segmentation. Statistical shape models can also be employed to synthesize additional training data that can ease the training of large CNNs.

  11. Modeling The Evolution Of A Regional Aquifer System With The California Central Valley Groundwater-Surface Water Simulation Model (C2VSIM)

    Science.gov (United States)

    Brush, C. F.; Dogrul, E. C.; Kadir, T. N.; Moncrief, M. R.; Shultz, S.; Tonkin, M.; Wendell, D.

    2006-12-01

    The finite element application IWFM has been used to develop an integrated groundwater-surface water model for California's Central Valley, an area of ~50,000 km2, to simulate the evolution of the groundwater flow system and historical groundwater-surface water interactions on a monthly time step from October 1921 to September 2003. The Central Valley's hydrologic system changed significantly during this period. Prior to 1920, most surface water flowed unimpeded from source areas in the mountains surrounding the Central Valley through the Sacramento-San Joaquin Delta to the Pacific Ocean, and groundwater largely flowed from recharge areas on the valley rim to discharge as evapotransipration in extensive marshes along the valley's axis. Rapid agricultural development led to increases in groundwater pumping from ~0.5 km3/yr in the early 1920's to 13-18 km3/yr in the 1940's to 1970's, resulting in strong vertical head gradients, significant head declines throughout the valley, and subsidence of >0.3 m over an area of 13,000 km2. Construction of numerous dams and development of an extensive surface water delivery network after 1950 altered the surface water flow regime and reduced groundwater pumping to the current ~10 km3/yr, increasing net recharge and leading to local head gradient reversals and water level recoveries. A model calibrated to the range of historical flow regimes in the Central Valley will provide robust estimations of stream-groundwater interactions for a range of projected future scenarios. C2VSIM uses the IWFM application to simulate a 3-D finite element groundwater flow process dynamically coupled with 1-D land surface, stream flow, lake and unsaturated zone processes. The groundwater flow system is represented with three layers each having 1393 elements. Land surface processes are simulated using 21 subregions corresponding to California DWR water-supply planning areas. The surface-water network is simulated using 431 stream nodes representing 72

  12. Aircraft Segmentation in SAR Images Based on Improved Active Shape Model

    Science.gov (United States)

    Zhang, X.; Xiong, B.; Kuang, G.

    2018-04-01

    In SAR image interpretation, aircrafts are the important targets arousing much attention. However, it is far from easy to segment an aircraft from the background completely and precisely in SAR images. Because of the complex structure, different kinds of electromagnetic scattering take place on the aircraft surfaces. As a result, aircraft targets usually appear to be inhomogeneous and disconnected. It is a good idea to extract an aircraft target by the active shape model (ASM), since combination of the geometric information controls variations of the shape during the contour evolution. However, linear dimensionality reduction, used in classic ACM, makes the model rigid. It brings much trouble to segment different types of aircrafts. Aiming at this problem, an improved ACM based on ISOMAP is proposed in this paper. ISOMAP algorithm is used to extract the shape information of the training set and make the model flexible enough to deal with different aircrafts. The experiments based on real SAR data shows that the proposed method achieves obvious improvement in accuracy.

  13. Engraftment of Prevascularized, Tissue Engineered Constructs in a Novel Rabbit Segmental Bone Defect Model

    Directory of Open Access Journals (Sweden)

    Alexandre Kaempfen

    2015-06-01

    Full Text Available The gold standard treatment of large segmental bone defects is autologous bone transfer, which suffers from low availability and additional morbidity. Tissue engineered bone able to engraft orthotopically and a suitable animal model for pre-clinical testing are direly needed. This study aimed to evaluate engraftment of tissue-engineered bone with different prevascularization strategies in a novel segmental defect model in the rabbit humerus. Decellularized bone matrix (Tutobone seeded with bone marrow mesenchymal stromal cells was used directly orthotopically or combined with a vessel and inserted immediately (1-step or only after six weeks of subcutaneous “incubation” (2-step. After 12 weeks, histological and radiological assessment was performed. Variable callus formation was observed. No bone formation or remodeling of the graft through TRAP positive osteoclasts could be detected. Instead, a variable amount of necrotic tissue formed. Although necrotic area correlated significantly with amount of vessels and the 2-step strategy had significantly more vessels than the 1-step strategy, no significant reduction of necrotic area was found. In conclusion, the animal model developed here represents a highly challenging situation, for which a suitable engineered bone graft with better prevascularization, better resorbability and higher osteogenicity has yet to be developed.

  14. Recreation Value of Water to Wetlands in the San Joaquin Valley: Linked Multinomial Logit and Count Data Trip Frequency Models

    Science.gov (United States)

    Creel, Michael; Loomis, John

    1992-10-01

    The recreational benefits from providing increased quantities of water to wildlife and fisheries habitats is estimated using linked multinomial logit site selection models and count data trip frequency models. The study encompasses waterfowl hunting, fishing and wildlife viewing at 14 recreational resources in the San Joaquin Valley, including the National Wildlife Refuges, the State Wildlife Management Areas, and six river destinations. The economic benefits of increasing water supplies to wildlife refuges were also examined by using the estimated models to predict changing patterns of site selection and overall participation due to increases in water allocations. Estimates of the dollar value per acre foot of water are calculated for increases in water to refuges. The resulting model is a flexible and useful tool for estimating the economic benefits of alternative water allocation policies for wildlife habitat and rivers.

  15. Monte Carlo simulation of THz radiation from GaAs p-i-n diodes under high electric fields using an extended valley model

    International Nuclear Information System (INIS)

    Dinh Nhu Thao

    2008-01-01

    We have applied a self-consistent ensemble Monte Carlo simulation procedure using an extended valley model to consider the THz radiation from GaAs p-i-n diodes under high electric fields. The present calculation has shown an important improvement of the numerical results when using this model instead of the usual valley model. It has been shown the importance of the full band-structure in the simulation of processes in semiconductors, especially under the influence of high electric fields. (author)

  16. Three-dimensional electrical resistivity model of the hydrothermal system in Long Valley Caldera, California, from magnetotellurics

    Science.gov (United States)

    Peacock, Jared R.; Mangan, Margaret T.; McPhee, Darcy K.; Wannamaker, Phil E.

    2016-01-01

    Though shallow flow of hydrothermal fluids in Long Valley Caldera, California, has been well studied, neither the hydrothermal source reservoir nor heat source has been well characterized. Here a grid of magnetotelluric data were collected around the Long Valley volcanic system and modeled in 3-D. The preferred electrical resistivity model suggests that the source reservoir is a narrow east-west elongated body 4 km below the west moat. The heat source could be a zone of 2–5% partial melt 8 km below Deer Mountain. Additionally, a collection of hypersaline fluids, not connected to the shallow hydrothermal system, is found 3 km below the medial graben, which could originate from a zone of 5–10% partial melt 8 km below the south moat. Below Mammoth Mountain is a 3 km thick isolated body containing fluids and gases originating from an 8 km deep zone of 5–10% basaltic partial melt.

  17. Reprint of Solution of Ambrosio-Tortorelli model for image segmentation by generalized relaxation method

    Science.gov (United States)

    D'Ambra, Pasqua; Tartaglione, Gaetano

    2015-04-01

    Image segmentation addresses the problem to partition a given image into its constituent objects and then to identify the boundaries of the objects. This problem can be formulated in terms of a variational model aimed to find optimal approximations of a bounded function by piecewise-smooth functions, minimizing a given functional. The corresponding Euler-Lagrange equations are a set of two coupled elliptic partial differential equations with varying coefficients. Numerical solution of the above system often relies on alternating minimization techniques involving descent methods coupled with explicit or semi-implicit finite-difference discretization schemes, which are slowly convergent and poorly scalable with respect to image size. In this work we focus on generalized relaxation methods also coupled with multigrid linear solvers, when a finite-difference discretization is applied to the Euler-Lagrange equations of Ambrosio-Tortorelli model. We show that non-linear Gauss-Seidel, accelerated by inner linear iterations, is an effective method for large-scale image analysis as those arising from high-throughput screening platforms for stem cells targeted differentiation, where one of the main goal is segmentation of thousand of images to analyze cell colonies morphology.

  18. Solution of Ambrosio-Tortorelli model for image segmentation by generalized relaxation method

    Science.gov (United States)

    D'Ambra, Pasqua; Tartaglione, Gaetano

    2015-03-01

    Image segmentation addresses the problem to partition a given image into its constituent objects and then to identify the boundaries of the objects. This problem can be formulated in terms of a variational model aimed to find optimal approximations of a bounded function by piecewise-smooth functions, minimizing a given functional. The corresponding Euler-Lagrange equations are a set of two coupled elliptic partial differential equations with varying coefficients. Numerical solution of the above system often relies on alternating minimization techniques involving descent methods coupled with explicit or semi-implicit finite-difference discretization schemes, which are slowly convergent and poorly scalable with respect to image size. In this work we focus on generalized relaxation methods also coupled with multigrid linear solvers, when a finite-difference discretization is applied to the Euler-Lagrange equations of Ambrosio-Tortorelli model. We show that non-linear Gauss-Seidel, accelerated by inner linear iterations, is an effective method for large-scale image analysis as those arising from high-throughput screening platforms for stem cells targeted differentiation, where one of the main goal is segmentation of thousand of images to analyze cell colonies morphology.

  19. A novel model for product bundling and direct marketing in e-commerce based on market segmentation

    Directory of Open Access Journals (Sweden)

    Arash Beheshtian-Ardakani

    2018-01-01

    Full Text Available Nowadays, companies offer product bundles with special discounts in order to sell more products. However, it is important to note that customers show different levels of loyalties to companies, and each segment of the market has unique features, which influences the customers’ buying patterns. The primary purpose of this paper is to propose a novel model for product bundling in e-commerce websites by using market segmentation variables and customer loyalty analysis. RFM model is employed to calculate customer loyalty. Subsequently, the customers are grouped based on their loyalty levels. Each group is then divided into different segments based on market segmentation variables. The product bundles are determined for each market segment via clustering algorithms. Apriori algorithm is also used to determine the association rules for each product bundle. Classification models are applied in order to determine which product bundle should be recommended to each customer. The results demonstrate that the silhouette coefficient, support, confidence, and accuracy values are higher when both customer loyalty level and market segmentation variables are used in product bundling. Accordingly, the proposed model increases the chance of success in direct marketing and recommending product bundles to customers.

  20. MESH-TO-BIM: FROM SEGMENTED MESH ELEMENTS TO BIM MODEL WITH LIMITED PARAMETERS

    Directory of Open Access Journals (Sweden)

    X. Yang

    2018-05-01

    Full Text Available Building Information Modelling (BIM technique has been widely utilized in heritage documentation and comes to a general term Historical/Heritage BIM (HBIM. The current HBIM project mostly employs the scan-to-BIM process to manually create the geometric model from the point cloud. This paper explains how it is possible to shape from the mesh geometry with reduced human involvement during the modelling process. Aiming at unbuilt heritage, two case studies are handled in this study, including a ruined Roman stone architectural and a severely damaged abbey. The pipeline consists of solid element modelling based on documentation data using Autodesk Revit, a common BIM platform, and the successive modelling from these geometric primitives using Autodesk Dynamo, a visual programming built-in plugin tool in Revit. The BIM-based reconstruction enriches the classic visual model from computer graphics approaches with measurement, semantic and additional information. Dynamo is used to develop a semi-automated function to reduce the manual process, which builds the final BIM model from segmented parametric elements directly. The level of detail (LoD of the final models is dramatically relevant with the manual involvement in the element creation. The proposed outline also presents two potential issues in the ongoing work: combining the ontology semantics with the parametric BIM model, and introducing the proposed pipeline into the as-built HBIM process.

  1. Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting

    Energy Technology Data Exchange (ETDEWEB)

    Ross, James C., E-mail: jross@bwh.harvard.edu [Channing Laboratory, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Surgical Planning Lab, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Laboratory of Mathematics in Imaging, Brigham and Women' s Hospital, Boston, Massachusetts 02126 (United States); Kindlmann, Gordon L. [Computer Science Department and Computation Institute, University of Chicago, Chicago, Illinois 60637 (United States); Okajima, Yuka; Hatabu, Hiroto [Department of Radiology, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Díaz, Alejandro A. [Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 and Department of Pulmonary Diseases, Pontificia Universidad Católica de Chile, Santiago (Chile); Silverman, Edwin K. [Channing Laboratory, Brigham and Women' s Hospital, Boston, Massachusetts 02215 and Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 (United States); Washko, George R. [Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 (United States); Dy, Jennifer [ECE Department, Northeastern University, Boston, Massachusetts 02115 (United States); Estépar, Raúl San José [Department of Radiology, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Surgical Planning Lab, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Laboratory of Mathematics in Imaging, Brigham and Women' s Hospital, Boston, Massachusetts 02126 (United States)

    2013-12-15

    Purpose: Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. Methods: The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. Results: The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. Conclusions: The

  2. Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting

    International Nuclear Information System (INIS)

    Ross, James C.; Kindlmann, Gordon L.; Okajima, Yuka; Hatabu, Hiroto; Díaz, Alejandro A.; Silverman, Edwin K.; Washko, George R.; Dy, Jennifer; Estépar, Raúl San José

    2013-01-01

    Purpose: Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. Methods: The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. Results: The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. Conclusions: The proposed

  3. Spatial modeling of rat bites and prediction of rat infestation in Peshawar valley using binomial kriging with logistic regression.

    Science.gov (United States)

    Ali, Asad; Zaidi, Farrah; Fatima, Syeda Hira; Adnan, Muhammad; Ullah, Saleem

    2018-03-24

    In this study, we propose to develop a geostatistical computational framework to model the distribution of rat bite infestation of epidemic proportion in Peshawar valley, Pakistan. Two species Rattus norvegicus and Rattus rattus are suspected to spread the infestation. The framework combines strengths of maximum entropy algorithm and binomial kriging with logistic regression to spatially model the distribution of infestation and to determine the individual role of environmental predictors in modeling the distribution trends. Our results demonstrate the significance of a number of social and environmental factors in rat infestations such as (I) high human population density; (II) greater dispersal ability of rodents due to the availability of better connectivity routes such as roads, and (III) temperature and precipitation influencing rodent fecundity and life cycle.

  4. Valley Fever

    Science.gov (United States)

    ... valley fever. These fungi are commonly found in soil in specific regions. The fungi's spores can be stirred into the air by ... species have a complex life cycle. In the soil, they grow as a mold with long filaments that break off into airborne ...

  5. 3D medical image segmentation based on a continuous modelling of the volume

    International Nuclear Information System (INIS)

    Marque, I.

    1990-12-01

    Several medical imaging/techniques, including Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) provide 3D information of the human body by means of a stack of parallel cross-sectional images. But a more sophisticated edge detection step has to be performed when the object under study is not well defined by its characteristic density or when an analytical knowledge of the surface of the object is useful for later processings. A new method for medical image segmentation has been developed: it uses the stability and differentiability properties of a continuous modelling of the 3D data. The idea is to build a system of Ordinary Differential Equations which the stable manifold is the surface of the object we are looking for. This technique has been applied to classical edge detection operators: threshold following, laplacian, gradient maximum in its direction. It can be used in 2D as well as in 3D and has been extended to seek particular points of the surface, such as local extrema. The major advantages of this method are as follows: the segmentation and boundary following steps are performed simultaneously, an analytical representation of the surface is obtained straightforwardly and complex objects in which branching problems may occur can be described automatically. Simulations on noisy synthetic images have induced a quantization step to test the sensitiveness to noise of our method with respect to each operator, and to study the influence of all the parameters. Last, this method has been applied to numerous real clinical exams: skull or femur images provided by CT, MR images of a cerebral tumor and of the ventricular system. These results show the reliability and the efficiency of this new method of segmentation [fr

  6. Registration-based segmentation with articulated model from multipostural magnetic resonance images for hand bone motion animation.

    Science.gov (United States)

    Chen, Hsin-Chen; Jou, I-Ming; Wang, Chien-Kuo; Su, Fong-Chin; Sun, Yung-Nien

    2010-06-01

    The quantitative measurements of hand bones, including volume, surface, orientation, and position are essential in investigating hand kinematics. Moreover, within the measurement stage, bone segmentation is the most important step due to its certain influences on measuring accuracy. Since hand bones are small and tubular in shape, magnetic resonance (MR) imaging is prone to artifacts such as nonuniform intensity and fuzzy boundaries. Thus, greater detail is required for improving segmentation accuracy. The authors then propose using a novel registration-based method on an articulated hand model to segment hand bones from multipostural MR images. The proposed method consists of the model construction and registration-based segmentation stages. Given a reference postural image, the first stage requires construction of a drivable reference model characterized by hand bone shapes, intensity patterns, and articulated joint mechanism. By applying the reference model to the second stage, the authors initially design a model-based registration pursuant to intensity distribution similarity, MR bone intensity properties, and constraints of model geometry to align the reference model to target bone regions of the given postural image. The authors then refine the resulting surface to improve the superimposition between the registered reference model and target bone boundaries. For each subject, given a reference postural image, the proposed method can automatically segment all hand bones from all other postural images. Compared to the ground truth from two experts, the resulting surface image had an average margin of error within 1 mm (mm) only. In addition, the proposed method showed good agreement on the overlap of bone segmentations by dice similarity coefficient and also demonstrated better segmentation results than conventional methods. The proposed registration-based segmentation method can successfully overcome drawbacks caused by inherent artifacts in MR images and

  7. Model-based segmentation of short-axis MR cardiac images

    NARCIS (Netherlands)

    Spreeuwers, Lieuwe Jan; Breeuwer, M.

    Reliable automatic segmentation of MR cardiac images is still an important problem in medical image processing. Although image data quality has improved considerably during the last years, this segmentation is still considered a difficult problem. Manual segmentation is hardly an option as this is

  8. Automatic Cell Segmentation in Fluorescence Images of Confluent Cell Monolayers Using Multi-object Geometric Deformable Model.

    Science.gov (United States)

    Yang, Zhen; Bogovic, John A; Carass, Aaron; Ye, Mao; Searson, Peter C; Prince, Jerry L

    2013-03-13

    With the rapid development of microscopy for cell imaging, there is a strong and growing demand for image analysis software to quantitatively study cell morphology. Automatic cell segmentation is an important step in image analysis. Despite substantial progress, there is still a need to improve the accuracy, efficiency, and adaptability to different cell morphologies. In this paper, we propose a fully automatic method for segmenting cells in fluorescence images of confluent cell monolayers. This method addresses several challenges through a combination of ideas. 1) It realizes a fully automatic segmentation process by first detecting the cell nuclei as initial seeds and then using a multi-object geometric deformable model (MGDM) for final segmentation. 2) To deal with different defects in the fluorescence images, the cell junctions are enhanced by applying an order-statistic filter and principal curvature based image operator. 3) The final segmentation using MGDM promotes robust and accurate segmentation results, and guarantees no overlaps and gaps between neighboring cells. The automatic segmentation results are compared with manually delineated cells, and the average Dice coefficient over all distinguishable cells is 0.88.

  9. Segmentation of expiratory and inspiratory sounds in baby cry audio recordings using hidden Markov models.

    Science.gov (United States)

    Aucouturier, Jean-Julien; Nonaka, Yulri; Katahira, Kentaro; Okanoya, Kazuo

    2011-11-01

    The paper describes an application of machine learning techniques to identify expiratory and inspiration phases from the audio recording of human baby cries. Crying episodes were recorded from 14 infants, spanning four vocalization contexts in their first 12 months of age; recordings from three individuals were annotated manually to identify expiratory and inspiratory sounds and used as training examples to segment automatically the recordings of the other 11 individuals. The proposed algorithm uses a hidden Markov model architecture, in which state likelihoods are estimated either with Gaussian mixture models or by converting the classification decisions of a support vector machine. The algorithm yields up to 95% classification precision (86% average), and its ability generalizes over different babies, different ages, and vocalization contexts. The technique offers an opportunity to quantify expiration duration, count the crying rate, and other time-related characteristics of baby crying for screening, diagnosis, and research purposes over large populations of infants.

  10. Customer segmentation model based on value generation for marketing strategies formulation

    Directory of Open Access Journals (Sweden)

    Alvaro Julio Cuadros

    2014-01-01

    Full Text Available When deciding in which segment to invest or how to distribute the marketing budget, managers generally take risks in making decisions without considering the real impact every client or segment has over organizational profits. In this paper, a segmentation framework is proposed that considers, firstly, the calculation of customer lifetime value, the current value, and client loyalty, and then the building of client segments by self-organized maps. The effectiveness of the proposed method is demonstrated with an empirical study in a cane sugar mill where a total of 9 segments of interest were identified for decision making.

  11. Graph-based unsupervised segmentation algorithm for cultured neuronal networks' structure characterization and modeling.

    Science.gov (United States)

    de Santos-Sierra, Daniel; Sendiña-Nadal, Irene; Leyva, Inmaculada; Almendral, Juan A; Ayali, Amir; Anava, Sarit; Sánchez-Ávila, Carmen; Boccaletti, Stefano

    2015-06-01

    Large scale phase-contrast images taken at high resolution through the life of a cultured neuronal network are analyzed by a graph-based unsupervised segmentation algorithm with a very low computational cost, scaling linearly with the image size. The processing automatically retrieves the whole network structure, an object whose mathematical representation is a matrix in which nodes are identified neurons or neurons' clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocytochemistry techniques, our non invasive measures entitle us to perform a longitudinal analysis during the maturation of a single culture. Such an analysis furnishes the way of individuating the main physical processes underlying the self-organization of the neurons' ensemble into a complex network, and drives the formulation of a phenomenological model yet able to describe qualitatively the overall scenario observed during the culture growth. © 2014 International Society for Advancement of Cytometry.

  12. TWO NOVEL ACM (ACTIVE CONTOUR MODEL) METHODS FOR INTRAVASCULAR ULTRASOUND IMAGE SEGMENTATION

    International Nuclear Information System (INIS)

    Chen, Chi Hau; Potdat, Labhesh; Chittineni, Rakesh

    2010-01-01

    One of the attractive image segmentation methods is the Active Contour Model (ACM) which has been widely used in medical imaging as it always produces sub-regions with continuous boundaries. Intravascular ultrasound (IVUS) is a catheter based medical imaging technique which is used for quantitative assessment of atherosclerotic disease. Two methods of ACM realizations are presented in this paper. The gradient descent flow based on minimizing energy functional can be used for segmentation of IVUS images. However this local operation alone may not be adequate to work with the complex IVUS images. The first method presented consists of basically combining the local geodesic active contours and global region-based active contours. The advantage of combining the local and global operations is to allow curves deforming under the energy to find only significant local minima and delineate object borders despite noise, poor edge information and heterogeneous intensity profiles. Results for this algorithm are compared to standard techniques to demonstrate the method's robustness and accuracy. In the second method, the energy function is appropriately modified and minimized using a Hopfield neural network. Proper modifications in the definition of the bias of the neurons have been introduced to incorporate image characteristics. The method overcomes distortions in the expected image pattern, such as due to the presence of calcium, and employs a specialized structure of the neural network and boundary correction schemes which are based on a priori knowledge about the vessel geometry. The presented method is very fast and has been evaluated using sequences of IVUS frames.

  13. Automated segmentation and geometrical modeling of the tricuspid aortic valve in 3D echocardiographic images.

    Science.gov (United States)

    Pouch, Alison M; Wang, Hongzhi; Takabe, Manabu; Jackson, Benjamin M; Sehgal, Chandra M; Gorman, Joseph H; Gorman, Robert C; Yushkevich, Paul A

    2013-01-01

    The aortic valve has been described with variable anatomical definitions, and the consistency of 2D manual measurement of valve dimensions in medical image data has been questionable. Given the importance of image-based morphological assessment in the diagnosis and surgical treatment of aortic valve disease, there is considerable need to develop a standardized framework for 3D valve segmentation and shape representation. Towards this goal, this work integrates template-based medial modeling and multi-atlas label fusion techniques to automatically delineate and quantitatively describe aortic leaflet geometry in 3D echocardiographic (3DE) images, a challenging task that has been explored only to a limited extent. The method makes use of expert knowledge of aortic leaflet image appearance, generates segmentations with consistent topology, and establishes a shape-based coordinate system on the aortic leaflets that enables standardized automated measurements. In this study, the algorithm is evaluated on 11 3DE images of normal human aortic leaflets acquired at mid systole. The clinical relevance of the method is its ability to capture leaflet geometry in 3DE image data with minimal user interaction while producing consistent measurements of 3D aortic leaflet geometry.

  14. PRINCIPLES AND MODELS OF CONSUMER SEGMENTATION IN THE BANKING PRODUCTS AND SERVICES MARKET

    Directory of Open Access Journals (Sweden)

    Andrey V. Tsarev

    2015-01-01

    Full Text Available The process of segmenting consumers ofbanking products and services connects withconducting marketing research. In the processof customer segmentation it is necessary to identify the factors that affect them. Identifi cation of competitive and consumer factors, in particular, is necessary for marketing decision making andthe development of the segment coverage strategy to reach a segment at all stages of planningmarketing activities and evaluating its effectiveness. After determining the basic segments on macro and micro levels the segment coveragestrategies are developed that should be based onthe results of the segmentation map construction.Banking institutions that implement informationtechnology to facilitate collecting and processingcustomer data, such as CRM-systems, receivemore opportunities to identify the client and provide a competitive position in the market.

  15. Research on Scenic Spot’s Sustainable Development Based on a SD Model: A Case Study of the Jiuzhai Valley

    Directory of Open Access Journals (Sweden)

    Zhixue Liao

    2014-07-01

    Full Text Available In the field of tourism, the development of tourist attractions is playing an increasingly crucial role in tourism economy, regional economy and national economy. However, the eco-environment has been damaged while tourism industry develops rapidly. Thus, to solve the contradiction between tourism development and eco-environment protection is the key to achieving sustainable development of tourism. This paper builds a SD model, which is based on the analysis of the economic subsystem and environment subsystem, to promote sustainable development. In order to show the effectiveness of the model, Jiuzhai Valley is taken as the research object and a decisive basis is provided for the path adjustment of sustainable development in tourist scenic.

  16. Evaluation of segmentation algorithms for generation of patient models in radiofrequency hyperthermia

    International Nuclear Information System (INIS)

    Wust, P.; Gellermann, J.; Beier, J.; Tilly, W.; Troeger, J.; Felix, R.; Wegner, S.; Oswald, H.; Stalling, D.; Hege, H.C.; Deuflhard, P.

    1998-01-01

    Time-efficient and easy-to-use segmentation algorithms (contour generation) are a precondition for various applications in radiation oncology, especially for planning purposes in hyperthermia. We have developed the three following algorithms for contour generation and implemented them in an editor of the HyperPlan hyperthermia planning system. Firstly, a manual contour input with numerous correction and editing options. Secondly, a volume growing algorithm with adjustable threshold range and minimal region size. Thirdly, a watershed transformation in two and three dimensions. In addition, the region input function of the Helax commercial radiation therapy planning system was available for comparison. All four approaches were applied under routine conditions to two-dimensional computed tomographic slices of the superior thoracic aperture, mid-chest, upper abdomen, mid-abdomen, pelvis and thigh; they were also applied to a 3D CT sequence of 72 slices using the three-dimensional extension of the algorithms. Time to generate the contours and their quality with respect to a reference model were determined. Manual input for a complete patient model required approximately 5 to 6 h for 72 CT slices (4.5 min/slice). If slight irregularities at object boundaries are accepted, this time can be reduced to 3.5 min/slice using the volume growing algorithm. However, generating a tetrahedron mesh from such a contour sequence for hyperthermia planning (the basis for finite-element algorithms) requires a significant amount of postediting. With the watershed algorithm extended to three dimensions, processing time can be further reduced to 3 min/slice while achieving satisfactory contour quality. Therefore, this method is currently regarded as offering some potential for efficient automated model generation in hyperthermia. In summary, the 3D volume growing algorithm and watershed transformation are both suitable for segmentation of even low-contrast objects. However, they are not

  17. Beyond Retinal Layers: A Deep Voting Model for Automated Geographic Atrophy Segmentation in SD-OCT Images.

    Science.gov (United States)

    Ji, Zexuan; Chen, Qiang; Niu, Sijie; Leng, Theodore; Rubin, Daniel L

    2018-01-01

    To automatically and accurately segment geographic atrophy (GA) in spectral-domain optical coherence tomography (SD-OCT) images by constructing a voting system with deep neural networks without the use of retinal layer segmentation. An automatic GA segmentation method for SD-OCT images based on the deep network was constructed. The structure of the deep network was composed of five layers, including one input layer, three hidden layers, and one output layer. During the training phase, the labeled A-scans with 1024 features were directly fed into the network as the input layer to obtain the deep representations. Then a soft-max classifier was trained to determine the label of each individual pixel. Finally, a voting decision strategy was used to refine the segmentation results among 10 trained models. Two image data sets with GA were used to evaluate the model. For the first dataset, our algorithm obtained a mean overlap ratio (OR) 86.94% ± 8.75%, absolute area difference (AAD) 11.49% ± 11.50%, and correlation coefficients (CC) 0.9857; for the second dataset, the mean OR, AAD, and CC of the proposed method were 81.66% ± 10.93%, 8.30% ± 9.09%, and 0.9952, respectively. The proposed algorithm was capable of improving over 5% and 10% segmentation accuracy, respectively, when compared with several state-of-the-art algorithms on two data sets. Without retinal layer segmentation, the proposed algorithm could produce higher segmentation accuracy and was more stable when compared with state-of-the-art methods that relied on retinal layer segmentation results. Our model may provide reliable GA segmentations from SD-OCT images and be useful in the clinical diagnosis of advanced nonexudative AMD. Based on the deep neural networks, this study presents an accurate GA segmentation method for SD-OCT images without using any retinal layer segmentation results, and may contribute to improved understanding of advanced nonexudative AMD.

  18. Segmented Spiral Waves and Anti-phase Synchronization in a Model System with Two Identical Time-Delayed Coupled Layers

    International Nuclear Information System (INIS)

    Yuan Guoyong; Yang Shiping; Wang Guangrui; Chen Shigang

    2008-01-01

    In this paper, we consider a model system with two identical time-delayed coupled layers. Synchronization and anti-phase synchronization are exhibited in the reactive system without diffusion term. New segmented spiral waves, which are constituted by many thin trips, are found in each layer of two identical time-delayed coupled layers, and are different from the segmented spiral waves in a water-in-oil aerosol sodium bis(2-ethylhexyl) sulfosuccinate (AOT) micro-emulsion (ME) (BZ-AOT system), which consists of many small segments. 'Anti-phase spiral wave synchronization' can be realized between the first layer and the second one. For different excitable parameters, we also give the minimum values of the coupling strength to generate segmented spiral waves and the tip orbits of spiral waves in the whole bilayer.

  19. A model of late quaternary landscape development in the Delaware Valley, New Jersey and Pennsylvania

    Science.gov (United States)

    Ridge, J.C.; Evenson, E.B.; Sevon, W.D.

    1992-01-01

    In the Delaware Valley of New Jersey and eastern Pennsylvania the late Quaternary history of colluviation, fluvial adjustment, and soil formation is based on the ages of pre-Wisconsinan soils and glacial deposits which are indicated by feld relationships and inferred from mid-latitude climate changes indicated by marine oxygen-isotope records. The area is divided into four terranes characterized by sandstone, gneiss, slate and carbonate rocks. Since the last pre-Wisconsinan glaciation (> 130 ka, inferred to be late Illinoian), each terrane responded differently to chemical and mechanical weathering. During the Sangamon interglacial stage (??? 130-75 ka) in situ weathering is inferred to have occurred at rates greater than transportation of material which resulted in the formation of deep, highly weathered soil and saprolite, and dissolution of carbonate rocks. Cold climatic conditions during the Wisconsinan, on the other hand, induced erosion of the landscape at rates faster than soil development. Upland erosion during the Wisconsinan removed pre-Wisconsinan soil and glacial sediment and bedrock to produce muddy to blocky colluvium, gre??zes lite??es, and alluvial fans on footslopes. Fluvial gravel and overlying colluvium in the Delaware Valley, both buried by late Wisconsinan outwash, are inferred to represent episodes of early and middle Wisconsinan (??? 75-25 ka) upland erosion and river aggradiation followed by river degradation and colluvium deposition. Early-middle Wisconsinan colluvium is more voluminous than later colluvium despite colder, possibly permafrost conditions during the late Wisconsinan ??? 25-10 ka). Extensive colluviation during the early and middle Wisconsinan resulted from a longer (50 kyr), generally cold interval of erosion with a greater availability of easily eroded pre-Wisconsinan surficial materials on uplands than during the late Wisconsinan. After recession of late Wisconsinan ice from its terminal position, soil formation and

  20. Knowledge, transparency, and refutability in groundwater models, an example from the Death Valley regional groundwater flow system

    Science.gov (United States)

    Hill, Mary C.; Faunt, Claudia C.; Belcher, Wayne; Sweetkind, Donald; Tiedeman, Claire; Kavetski, Dmitri

    2013-01-01

    This work demonstrates how available knowledge can be used to build more transparent and refutable computer models of groundwater systems. The Death Valley regional groundwater flow system, which surrounds a proposed site for a high level nuclear waste repository of the United States of America, and the Nevada National Security Site (NNSS), where nuclear weapons were tested, is used to explore model adequacy, identify parameters important to (and informed by) observations, and identify existing old and potential new observations important to predictions. Model development is pursued using a set of fundamental questions addressed with carefully designed metrics. Critical methods include using a hydrogeologic model, managing model nonlinearity by designing models that are robust while maintaining realism, using error-based weighting to combine disparate types of data, and identifying important and unimportant parameters and observations and optimizing parameter values with computationally frugal schemes. The frugal schemes employed in this study require relatively few (10–1000 s), parallelizable model runs. This is beneficial because models able to approximate the complex site geology defensibly tend to have high computational cost. The issue of model defensibility is particularly important given the contentious political issues involved.

  1. Speaker segmentation and clustering

    OpenAIRE

    Kotti, M; Moschou, V; Kotropoulos, C

    2008-01-01

    07.08.13 KB. Ok to add the accepted version to Spiral, Elsevier says ok whlile mandate not enforced. This survey focuses on two challenging speech processing topics, namely: speaker segmentation and speaker clustering. Speaker segmentation aims at finding speaker change points in an audio stream, whereas speaker clustering aims at grouping speech segments based on speaker characteristics. Model-based, metric-based, and hybrid speaker segmentation algorithms are reviewed. Concerning speaker...

  2. Death Valley regional ground-water flow system, Nevada and California -- hydrogeologic framework and transient ground-water flow model

    Science.gov (United States)

    Belcher, Wayne R.

    2004-01-01

    A numerical three-dimensional (3D) transient ground-water flow model of the Death Valley region was developed by the U.S. Geological Survey for the U.S. Department of Energy programs at the Nevada Test Site and at Yucca Mountain, Nevada. Decades of study of aspects of the ground-water flow system and previous less extensive ground-water flow models were incorporated and reevaluated together with new data to provide greater detail for the complex, digital model. A 3D digital hydrogeologic framework model (HFM) was developed from digital elevation models, geologic maps, borehole information, geologic and hydrogeologic cross sections, and other 3D models to represent the geometry of the hydrogeologic units (HGUs). Structural features, such as faults and fractures, that affect ground-water flow also were added. The HFM represents Precambrian and Paleozoic crystalline and sedimentary rocks, Mesozoic sedimentary rocks, Mesozoic to Cenozoic intrusive rocks, Cenozoic volcanic tuffs and lavas, and late Cenozoic sedimentary deposits of the Death Valley Regional Ground-Water Flow System (DVRFS) region in 27 HGUs. Information from a series of investigations was compiled to conceptualize and quantify hydrologic components of the ground-water flow system within the DVRFS model domain and to provide hydraulic-property and head-observation data used in the calibration of the transient-flow model. These studies reevaluated natural ground-water discharge occurring through evapotranspiration and spring flow; the history of ground-water pumping from 1913 through 1998; ground-water recharge simulated as net infiltration; model boundary inflows and outflows based on regional hydraulic gradients and water budgets of surrounding areas; hydraulic conductivity and its relation to depth; and water levels appropriate for regional simulation of prepumped and pumped conditions within the DVRFS model domain. Simulation results appropriate for the regional extent and scale of the model were

  3. Construction of Korean male tomographic model segmented from PET-CT data

    International Nuclear Information System (INIS)

    Lee, Choon Sik; Park, Sang Kyun; Lee, Jai Ki

    2004-01-01

    Tomographic human models provide currently the most realistic representation of human anatomy for radiation dosimetry calculation. Most of the models have been constructed by using computed tomographic (CT) or magnetic resonance (MR) images obtained from a single individual. Each scan has its inherent advantages and disadvantages. CT scan gives a considerable radiation dose to a subject, and MR scan takes too long time to get clear images of an immobile subject. An emerging source of medical images for the construction of tomographic models is PET-CT, which is performed when looking for cancer. In this study, a tomographic model of Korean adult male was developed by processing whole-body CT images of a PET-CT-scanned healthy volunteer. The 343 slices of the CT images were semi-automatically segmented layer by layer using a graphic software and screen digitizer. The 3rd Korean tomographic model, named KRMAN-2, consisting of 300x150x344 voxels of a size of 2x2x5mm 3 , was constructed. Examples of application to Monte Carlo radiation dosimetry calculation in idealized whole-body irradiations were given and discussed

  4. Numerical Predictions of Sonic Boom Signatures for a Straight Line Segmented Leading Edge Model

    Science.gov (United States)

    Elmiligui, Alaa A.; Wilcox, Floyd J.; Cliff, Susan; Thomas, Scott

    2012-01-01

    A sonic boom wind tunnel test was conducted on a straight-line segmented leading edge (SLSLE) model in the NASA Langley 4- by 4- Foot Unitary Plan Wind Tunnel (UPWT). The purpose of the test was to determine whether accurate sonic boom measurements could be obtained while continuously moving the SLSLE model past a conical pressure probe. Sonic boom signatures were also obtained using the conventional move-pause data acquisition method for comparison. The continuous data acquisition approach allows for accurate signatures approximately 15 times faster than a move-pause technique. These successful results provide an incentive for future testing with greatly increased efficiency using the continuous model translation technique with the single probe to measure sonic boom signatures. Two widely used NASA codes, USM3D (Navier-Stokes) and CART3D-AERO (Euler, adjoint-based adaptive mesh), were used to compute off-body sonic boom pressure signatures of the SLSLE model at several different altitudes below the model at Mach 2.0. The computed pressure signatures compared well with wind tunnel data. The effect of the different altitude for signature extraction was evaluated by extrapolating the near field signatures to the ground and comparing pressure signatures and sonic boom loudness levels.

  5. Generic and robust method for automatic segmentation of PET images using an active contour model

    Energy Technology Data Exchange (ETDEWEB)

    Zhuang, Mingzan [Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, 9700 RB Groningen (Netherlands)

    2016-08-15

    Purpose: Although positron emission tomography (PET) images have shown potential to improve the accuracy of targeting in radiation therapy planning and assessment of response to treatment, the boundaries of tumors are not easily distinguishable from surrounding normal tissue owing to the low spatial resolution and inherent noisy characteristics of PET images. The objective of this study is to develop a generic and robust method for automatic delineation of tumor volumes using an active contour model and to evaluate its performance using phantom and clinical studies. Methods: MASAC, a method for automatic segmentation using an active contour model, incorporates the histogram fuzzy C-means clustering, and localized and textural information to constrain the active contour to detect boundaries in an accurate and robust manner. Moreover, the lattice Boltzmann method is used as an alternative approach for solving the level set equation to make it faster and suitable for parallel programming. Twenty simulated phantom studies and 16 clinical studies, including six cases of pharyngolaryngeal squamous cell carcinoma and ten cases of nonsmall cell lung cancer, were included to evaluate its performance. Besides, the proposed method was also compared with the contourlet-based active contour algorithm (CAC) and Schaefer’s thresholding method (ST). The relative volume error (RE), Dice similarity coefficient (DSC), and classification error (CE) metrics were used to analyze the results quantitatively. Results: For the simulated phantom studies (PSs), MASAC and CAC provide similar segmentations of the different lesions, while ST fails to achieve reliable results. For the clinical datasets (2 cases with connected high-uptake regions excluded) (CSs), CAC provides for the lowest mean RE (−8.38% ± 27.49%), while MASAC achieves the best mean DSC (0.71 ± 0.09) and mean CE (53.92% ± 12.65%), respectively. MASAC could reliably quantify different types of lesions assessed in this work

  6. Segmentation process significantly influences the accuracy of 3D surface models derived from cone beam computed tomography

    International Nuclear Information System (INIS)

    Fourie, Zacharias; Damstra, Janalt; Schepers, Rutger H.; Gerrits, Peter O.; Ren Yijin

    2012-01-01

    Aims: To assess the accuracy of surface models derived from 3D cone beam computed tomography (CBCT) with two different segmentation protocols. Materials and methods: Seven fresh-frozen cadaver heads were used. There was no conflict of interests in this study. CBCT scans were made of the heads and 3D surface models were created of the mandible using two different segmentation protocols. The one series of 3D models was segmented by a commercial software company, while the other series was done by an experienced 3D clinician. The heads were then macerated following a standard process. A high resolution laser surface scanner was used to make a 3D model of the macerated mandibles, which acted as the reference 3D model or “gold standard”. The 3D models generated from the two rendering protocols were compared with the “gold standard” using a point-based rigid registration algorithm to superimpose the three 3D models. The linear difference at 25 anatomic and cephalometric landmarks between the laser surface scan and the 3D models generate from the two rendering protocols was measured repeatedly in two sessions with one week interval. Results: The agreement between the repeated measurement was excellent (ICC = 0.923–1.000). The mean deviation from the gold standard by the 3D models generated from the CS group was 0.330 mm ± 0.427, while the mean deviation from the Clinician's rendering was 0.763 mm ± 0.392. The surface models segmented by both CS and DS protocols tend to be larger than those of the reference models. In the DS group, the biggest mean differences with the LSS models were found at the points ConLatR (CI: 0.83–1.23), ConMedR (CI: −3.16 to 2.25), CoLatL (CI: −0.68 to 2.23), Spine (CI: 1.19–2.28), ConAntL (CI: 0.84–1.69), ConSupR (CI: −1.12 to 1.47) and RetMolR (CI: 0.84–1.80). Conclusion: The Commercially segmented models resembled the reality more closely than the Doctor's segmented models. If 3D models are needed for surgical drilling

  7. A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA

    Science.gov (United States)

    Ransom, Katherine M.; Nolan, Bernard T.; Traum, Jonathan A.; Faunt, Claudia; Bell, Andrew M.; Gronberg, Jo Ann M.; Wheeler, David C.; Zamora, Celia; Jurgens, Bryant; Schwarz, Gregory E.; Belitz, Kenneth; Eberts, Sandra; Kourakos, George; Harter, Thomas

    2017-01-01

    Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500 m below ground surface. A database of 145 predictor variables representing well characteristics, historical and current field and landscape-scale nitrogen mass balances, historical and current land use, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The boosted regression tree (BRT) method was used to screen and rank variables to predict nitrate concentration at the depths of domestic and public well supplies. The novel approach included as predictor variables outputs from existing physically based models of the Central Valley. The top five most important predictor variables included two oxidation/reduction variables (probability of manganese concentration to exceed 50 ppb and probability of dissolved oxygen concentration to be below 0.5 ppm), field-scale adjusted unsaturated zone nitrogen input for the 1975 time period, average difference between precipitation and evapotranspiration during the years 1971–2000, and 1992 total landscape nitrogen input. Twenty-five variables were selected for the final model for log-transformed nitrate. In general, increasing probability of anoxic conditions and increasing precipitation relative to potential evapotranspiration had a corresponding decrease in nitrate concentration predictions. Conversely, increasing 1975 unsaturated zone nitrogen leaching flux and 1992 total landscape nitrogen input had an increasing relative

  8. Death Valley regional groundwater flow system, Nevada and California-Hydrogeologic framework and transient groundwater flow model

    Science.gov (United States)

    Belcher, Wayne R.; Sweetkind, Donald S.

    2010-01-01

    A numerical three-dimensional (3D) transient groundwater flow model of the Death Valley region was developed by the U.S. Geological Survey for the U.S. Department of Energy programs at the Nevada Test Site and at Yucca Mountain, Nevada. Decades of study of aspects of the groundwater flow system and previous less extensive groundwater flow models were incorporated and reevaluated together with new data to provide greater detail for the complex, digital model. A 3D digital hydrogeologic framework model (HFM) was developed from digital elevation models, geologic maps, borehole information, geologic and hydrogeologic cross sections, and other 3D models to represent the geometry of the hydrogeologic units (HGUs). Structural features, such as faults and fractures, that affect groundwater flow also were added. The HFM represents Precambrian and Paleozoic crystalline and sedimentary rocks, Mesozoic sedimentary rocks, Mesozoic to Cenozoic intrusive rocks, Cenozoic volcanic tuffs and lavas, and late Cenozoic sedimentary deposits of the Death Valley regional groundwater flow system (DVRFS) region in 27 HGUs. Information from a series of investigations was compiled to conceptualize and quantify hydrologic components of the groundwater flow system within the DVRFS model domain and to provide hydraulic-property and head-observation data used in the calibration of the transient-flow model. These studies reevaluated natural groundwater discharge occurring through evapotranspiration (ET) and spring flow; the history of groundwater pumping from 1913 through 1998; groundwater recharge simulated as net infiltration; model boundary inflows and outflows based on regional hydraulic gradients and water budgets of surrounding areas; hydraulic conductivity and its relation to depth; and water levels appropriate for regional simulation of prepumped and pumped conditions within the DVRFS model domain. Simulation results appropriate for the regional extent and scale of the model were provided

  9. Estimating Hourly Beam and Diffuse Solar Radiation in an Alpine Valley: A Critical Assessment of Decomposition Models

    Directory of Open Access Journals (Sweden)

    Lavinia Laiti

    2018-03-01

    Full Text Available Accurate solar radiation estimates in Alpine areas represent a challenging task, because of the strong variability arising from orographic effects and mountain weather phenomena. These factors, together with the scarcity of observations in elevated areas, often cause large modelling uncertainties. In the present paper, estimates of hourly mean diffuse fraction values from global radiation data, provided by a number (13 of decomposition models (chosen among the most widely tested in the literature, are evaluated and compared with observations collected near the city of Bolzano, in the Adige Valley (Italian Alps. In addition, the physical factors influencing diffuse fraction values in such a complex orographic context are explored. The average accuracy of the models were found to be around 27% and 14% for diffuse and beam radiation respectively, the largest errors being observed under clear sky and partly cloudy conditions, respectively. The best performances were provided by the more complex models, i.e., those including a predictor specifically explaining the radiation components’ variability associated with scattered clouds. Yet, these models return non-negligible biases. In contrast, the local calibration of a single-equation logistical model with five predictors allows perfectly unbiased estimates, as accurate as those of the best-performing models (20% and 12% for diffuse and beam radiation, respectively, but at much smaller computational costs.

  10. Modeling the drug transport in the anterior segment of the eye.

    Science.gov (United States)

    Avtar, Ram; Tandon, Deepti

    2008-10-02

    The aim of the present work is the development of a simple mathematical model for the time course concentration profile of topically administered drugs in the anterior chamber aqueous humor and investigation of the effects of various model parameters on the aqueous humor concentration of lipophilic and hydrophilic drugs. A simple pharmacokinetic model for the transient drug transport in the anterior segment has been developed by using the conservation of mass in the precorneal tear film, Fick's law of diffusion and Michaelis-Menten kinetics of drug metabolism in cornea, and the conservation of mass in the anterior chamber. An analytical solution describing the drug concentration in the anterior chamber has been obtained. The model predicts that an increase in the drug metabolic (consumption) rate in the corneal epithelium reduces the drug concentration in the anterior chamber for both lipophilic and hydrophilic molecules. A decrease in the clearance rate and distribution volume of the drug in the anterior chamber raises the aqueous humor concentration significantly. It is also observed that decay rate of drug concentration in the anterior chamber is higher for lipophilic molecules than that for hydrophilic molecules. The bioavailability of drugs applied topically to the eye may be improved by a rise in the precorneal tear volume, diffusion coefficient in corneal epithelium and distribution coefficient across the endothelium anterior chamber interface, and by reducing the drug metabolism, drug clearance rate and distribution volume in anterior chamber.

  11. Distribution of macular xanthophylls between domains in a model of photoreceptor outer segment membranes.

    Science.gov (United States)

    Wisniewska, Anna; Subczynski, Witold K

    2006-10-15

    A model of photoreceptor outer segment (POS) membranes has been proposed, consisting of an equimolar ternary mixture of 1-palmitoyl-2-docosahexaenoylphosphatidylcholine/distearoylphosphatidylcholine/cholesterol. It was shown that, as in membranes made from the raft-forming mixture, in the model of POS membranes, two domains are formed: the raft domain (detergent resistant membranes, DRM), and the bulk domain (detergent soluble membranes, DSM). Saturation-recovery EPR discrimination by oxygen transport method also demonstrated the presence of two domains in this model system in situ at a wide range of temperatures (10-55 degrees C), showing additionally that neither lutein nor zeaxanthin at 1 mol% affect the formation of these domains. These membrane domains have been separated using cold Triton X-100 extraction from a model of POS membranes containing 1 mol% of either lutein or zeaxanthin. The results indicated that the macular xanthophylls lutein and zeaxanthin are substantially excluded from DRM and remain concentrated in DSM, a domain enriched in highly unsaturated docosahexaenoyl acid which is abundant in retina membranes. The concentration of xanthophylls in DRM and DSM calculated as the mol ratio of either xanthophyll to total lipid (phospholipid+cholesterol) was 0.0028 and 0.0391, respectively. Thus, xanthophylls are about 14 times more concentrated in DSM than in DRM. No significant difference in the distribution of lutein and zeaxanthin was found. The obtained results suggest that in POS membranes macular xanthophylls should also be concentrated in domains enriched in polyunsaturated chains.

  12. Modelling a real-world buried valley system with vertical non-stationarity using multiple-point statistics

    DEFF Research Database (Denmark)

    He, Xiulan; Sonnenborg, Torben; Jørgensen, Flemming

    2017-01-01

    -stationary geological system characterized by a network of connected buried valleys that incise deeply into layered Miocene sediments (case study in Denmark). The results show that, based on fragmented information of the formation boundaries, the MPS partition method is able to simulate a non-stationary system......Stationarity has traditionally been a requirement of geostatistical simulations. A common way to deal with non-stationarity is to divide the system into stationary sub-regions and subsequently merge the realizations for each region. Recently, the so-called partition approach that has...... the flexibility to model non-stationary systems directly was developed for multiple-point statistics simulation (MPS). The objective of this study is to apply the MPS partition method with conventional borehole logs and high-resolution airborne electromagnetic (AEM) data, for simulation of a real-world non...

  13. GC-ASM: Synergistic Integration of Graph-Cut and Active Shape Model Strategies for Medical Image Segmentation.

    Science.gov (United States)

    Chen, Xinjian; Udupa, Jayaram K; Alavi, Abass; Torigian, Drew A

    2013-05-01

    Image segmentation methods may be classified into two categories: purely image based and model based. Each of these two classes has its own advantages and disadvantages. In this paper, we propose a novel synergistic combination of the image based graph-cut (GC) method with the model based ASM method to arrive at the GC-ASM method for medical image segmentation. A multi-object GC cost function is proposed which effectively integrates the ASM shape information into the GC framework. The proposed method consists of two phases: model building and segmentation. In the model building phase, the ASM model is built and the parameters of the GC are estimated. The segmentation phase consists of two main steps: initialization (recognition) and delineation. For initialization, an automatic method is proposed which estimates the pose (translation, orientation, and scale) of the model, and obtains a rough segmentation result which also provides the shape information for the GC method. For delineation, an iterative GC-ASM algorithm is proposed which performs finer delineation based on the initialization results. The proposed methods are implemented to operate on 2D images and evaluated on clinical chest CT, abdominal CT, and foot MRI data sets. The results show the following: (a) An overall delineation accuracy of TPVF > 96%, FPVF ASM for different objects, modalities, and body regions. (b) GC-ASM improves over ASM in its accuracy and precision to search region. (c) GC-ASM requires far fewer landmarks (about 1/3 of ASM) than ASM. (d) GC-ASM achieves full automation in the segmentation step compared to GC which requires seed specification and improves on the accuracy of GC. (e) One disadvantage of GC-ASM is its increased computational expense owing to the iterative nature of the algorithm.

  14. Accuracy of open-source software segmentation and paper-based printed three-dimensional models.

    Science.gov (United States)

    Szymor, Piotr; Kozakiewicz, Marcin; Olszewski, Raphael

    2016-02-01

    In this study, we aimed to verify the accuracy of models created with the help of open-source Slicer 3.6.3 software (Surgical Planning Lab, Harvard Medical School, Harvard University, Boston, MA, USA) and the Mcor Matrix 300 paper-based 3D printer. Our study focused on the accuracy of recreating the walls of the right orbit of a cadaveric skull. Cone beam computed tomography (CBCT) of the skull was performed (0.25-mm pixel size, 0.5-mm slice thickness). Acquired DICOM data were imported into Slicer 3.6.3 software, where segmentation was performed. A virtual model was created and saved as an .STL file and imported into Netfabb Studio professional 4.9.5 software. Three different virtual models were created by cutting the original file along three different planes (coronal, sagittal, and axial). All models were printed with a Selective Deposition Lamination Technology Matrix 300 3D printer using 80 gsm A4 paper. The models were printed so that their cutting plane was parallel to the paper sheets creating the model. Each model (coronal, sagittal, and axial) consisted of three separate parts (∼200 sheets of paper each) that were glued together to form a final model. The skull and created models were scanned with a three-dimensional (3D) optical scanner (Breuckmann smart SCAN) and were saved as .STL files. Comparisons of the orbital walls of the skull, the virtual model, and each of the three paper models were carried out with GOM Inspect 7.5SR1 software. Deviations measured between the models analysed were presented in the form of a colour-labelled map and covered with an evenly distributed network of points automatically generated by the software. An average of 804.43 ± 19.39 points for each measurement was created. Differences measured in each point were exported as a .csv file. The results were statistically analysed using Statistica 10, with statistical significance set at p paper-based Mcor Matrix 300 3D printer is comparable to those of other commonly used

  15. Medical Image Segmentation for Mobile Electronic Patient Charts Using Numerical Modeling of IoT

    Directory of Open Access Journals (Sweden)

    Seung-Hoon Chae

    2014-01-01

    Full Text Available Internet of Things (IoT brings telemedicine a new chance. This enables the specialist to consult the patient’s condition despite the fact that they are in different places. Medical image segmentation is needed for analysis, storage, and protection of medical image in telemedicine. Therefore, a variety of methods have been researched for fast and accurate medical image segmentation. Performing segmentation in various organs, the accurate judgment of the region is needed in medical image. However, the removal of region occurs by the lack of information to determine the region in a small region. In this paper, we researched how to reconstruct segmentation region in a small region in order to improve the segmentation results. We generated predicted segmentation of slices using volume data with linear equation and proposed improvement method for small regions using the predicted segmentation. In order to verify the performance of the proposed method, lung region by chest CT images was segmented. As a result of experiments, volume data segmentation accuracy rose from 0.978 to 0.981 and from 0.281 to 0.187 with a standard deviation improvement confirmed.

  16. Automated brain structure segmentation based on atlas registration and appearance models

    DEFF Research Database (Denmark)

    van der Lijn, Fedde; de Bruijne, Marleen; Klein, Stefan

    2012-01-01

    Accurate automated brain structure segmentation methods facilitate the analysis of large-scale neuroimaging studies. This work describes a novel method for brain structure segmentation in magnetic resonance images that combines information about a structure’s location and appearance. The spatial...... with different magnetic resonance sequences, in which the hippocampus and cerebellum were segmented by an expert. Furthermore, the method is compared to two other segmentation techniques that were applied to the same data. Results show that the atlas- and appearance-based method produces accurate results...

  17. 3D statistical shape models incorporating 3D random forest regression voting for robust CT liver segmentation

    Science.gov (United States)

    Norajitra, Tobias; Meinzer, Hans-Peter; Maier-Hein, Klaus H.

    2015-03-01

    During image segmentation, 3D Statistical Shape Models (SSM) usually conduct a limited search for target landmarks within one-dimensional search profiles perpendicular to the model surface. In addition, landmark appearance is modeled only locally based on linear profiles and weak learners, altogether leading to segmentation errors from landmark ambiguities and limited search coverage. We present a new method for 3D SSM segmentation based on 3D Random Forest Regression Voting. For each surface landmark, a Random Regression Forest is trained that learns a 3D spatial displacement function between the according reference landmark and a set of surrounding sample points, based on an infinite set of non-local randomized 3D Haar-like features. Landmark search is then conducted omni-directionally within 3D search spaces, where voxelwise forest predictions on landmark position contribute to a common voting map which reflects the overall position estimate. Segmentation experiments were conducted on a set of 45 CT volumes of the human liver, of which 40 images were randomly chosen for training and 5 for testing. Without parameter optimization, using a simple candidate selection and a single resolution approach, excellent results were achieved, while faster convergence and better concavity segmentation were observed, altogether underlining the potential of our approach in terms of increased robustness from distinct landmark detection and from better search coverage.

  18. Towards continuum models of lateral rupture propagation in a segmented megathrust

    Science.gov (United States)

    Pranger, C. C.; van Dinther, Y.; Le Pourhiet, L.; May, D.; Gerya, T.

    2015-12-01

    At subduction megathrusts, propagation of large ruptures may be confined between the up-dip and down-dip limits of the seismogenic zone. This opens a primary role for lateral rupture dimensions to control the magnitude and severity of megathrust earthquakes. The goal of this study is to improve our understanding of the ways in which the inherent variability of the subduction interface may influence the degree of interseismic locking, and the propensity of a rupture to propagate over regions of variable slip potential. We focus in particular on the roughness of the incoming seafloor, which we expect to be of primary importance. The global absence of a historic record sufficiently long to base risk assessment on, makes us rely on numerical modelling as a way to extend our understanding of the spatio-temporal occurrence of earthquakes. However, the complex interaction of the subduction stress environment, the variability of the subduction interface, and the structure and deformation of the crustal wedge has made it very difficult to construct comprehensive numerical models of megathrust segmentation. We intend to develop and exploit the power of a plastic 3D continuum representation of the subduction megathrust, as well as off-megathrust faulting to model the long-term tectonic build-up of stresses, and their sudden seismic release. The sheer size of the 3D problem, and the time scales covering those of tectonics as well as seismology, force us to explore efficient and accurate physical and numerical techniques. So far, we have focused our efforts on developing a staggered grid finite difference code that makes use of the PETSc library for massively parallel computing. The code incorporates a newly developed automatic discretization algorithm, which enables it to handle a wide variety of equations with relative ease. What remains now is combining the physics that act on the different spatial and temporal scales. To this end we explore new constitutive models that

  19. Towards three-dimensional continuum models of self-consistent along-strike megathrust segmentation

    Science.gov (United States)

    Pranger, Casper; van Dinther, Ylona; May, Dave; Le Pourhiet, Laetitia; Gerya, Taras

    2016-04-01

    At subduction megathrusts, propagation of large ruptures may be confined between the up-dip and down-dip limits of the seismogenic zone. This opens a primary role for lateral rupture dimensions to control the magnitude and severity of megathrust earthquakes. The goal of this study is to improve our understanding of the ways in which the inherent variability of the subduction interface may influence the degree of interseismic locking, and the propensity of a rupture to propagate over regions of variable slip potential. The global absence of a historic record sufficiently long to base risk assessment on, makes us rely on numerical modelling as a way to extend our understanding of the spatio-temporal occurrence of earthquakes. However, the complex interaction of the subduction stress environment, the variability of the subduction interface, and the structure and deformation of the crustal wedge has made it very difficult to construct comprehensive numerical models of megathrust segmentation. We develop and exploit the power of a plastic 3D continuum representation of the subduction megathrust, as well as off-megathrust faulting to model the long-term tectonic build-up of stresses, and their sudden seismic release. The sheer size of the 3D problem, and the time scales covering those of tectonics as well as seismology, force us to explore efficient and accurate physical and numerical techniques. We thus focused our efforts on developing a staggered grid finite difference code that makes use of the PETSc library for massively parallel computing. The code incorporates a newly developed automatic discretization algorithm, which enables it to handle a wide variety of equations with relative ease. The different physical and numerical ingredients - like attenuating visco-elasto-plastic materials, frictional weakening and inertially driven seismic release, and adaptive time marching schemes - most of which have been implemented and benchmarked individually - are now combined

  20. A proposal of conceptual model for Pertuso Spring discharge evaluation in the Upper Valley of Aniene River

    Directory of Open Access Journals (Sweden)

    Giuseppe Sappa

    2016-10-01

    Full Text Available The Upper Aniene River basin is part of a large karst aquifer, which interacts with the river, and represents the most important water resource in the southeast part of Latium Region, Central Italy, used for drinking, agriculture and hydroelectric supplies. This work provides hydrogeochemical data and their interpretations for 1 spring and 2 cross section of Aniene River, monitored from July 2014 to December 2015, in the Upper Valley of Aniene River, to identify flow paths and hydrogeochemical processes governing groundwater-surface water interactions in this region. These activities deal with the Environmental Monitoring Plan made for the catchment work project of the Pertuso Spring, in the Upper Valley of Aniene River, which is going to be exploited to supply an important drinking water network in the South part of Rome district. Discharge measurements and hydrogeochemical data were analyzed to develop a conceptual model of aquifer-river interaction, with the aim of achieving proper management and protection of this important hydrogeological system. All groundwater samples are characterized as Ca-HCO3 type. Geochemical modeling and saturation index computation of the water samples show that groundwater and surface water chemistry in the study area was evolved through the interaction with carbonate minerals. All groundwater samples were undersaturated with respect to calcite and dolomite, however some of the Aniene River samples were saturated with respect to dolomite. The analysis of Mg2+/Ca2+ ratios indicates that the dissolution of carbonate minerals is important for groundwater and surface water chemistry, depending on the hydrological processes, which control the groundwater residence time and chemical equilibria in the aquifer.

  1. 3-D Velocity Model of the Coachella Valley, Southern California Based on Explosive Shots from the Salton Seismic Imaging Project

    Science.gov (United States)

    Persaud, P.; Stock, J. M.; Fuis, G. S.; Hole, J. A.; Goldman, M.; Scheirer, D. S.

    2014-12-01

    We have analyzed explosive shot data from the 2011 Salton Seismic Imaging Project (SSIP) across a 2-D seismic array and 5 profiles in the Coachella Valley to produce a 3-D P-wave velocity model that will be used in calculations of strong ground shaking. Accurate maps of seismicity and active faults rely both on detailed geological field mapping and a suitable velocity model to accurately locate earthquakes. Adjoint tomography of an older version of the SCEC 3-D velocity model shows that crustal heterogeneities strongly influence seismic wave propagation from moderate earthquakes (Tape et al., 2010). These authors improve the crustal model and subsequently simulate the details of ground motion at periods of 2 s and longer for hundreds of ray paths. Even with improvements such as the above, the current SCEC velocity model for the Salton Trough does not provide a match of the timing or waveforms of the horizontal S-wave motions, which Wei et al. (2013) interpret as caused by inaccuracies in the shallow velocity structure. They effectively demonstrate that the inclusion of shallow basin structure improves the fit in both travel times and waveforms. Our velocity model benefits from the inclusion of known location and times of a subset of 126 shots detonated over a 3-week period during the SSIP. This results in an improved velocity model particularly in the shallow crust. In addition, one of the main challenges in developing 3-D velocity models is an uneven stations-source distribution. To better overcome this challenge, we also include the first arrival times of the SSIP shots at the more widely spaced Southern California Seismic Network (SCSN) in our inversion, since the layout of the SSIP is complementary to the SCSN. References: Tape, C., et al., 2010, Seismic tomography of the Southern California crust based on spectral-element and adjoint methods: Geophysical Journal International, v. 180, no. 1, p. 433-462. Wei, S., et al., 2013, Complementary slip distributions

  2. Resistivity structure of Sumatran Fault (Aceh segment) derived from 1-D magnetotelluric modeling

    Science.gov (United States)

    Nurhasan, Sutarno, D.; Bachtiar, H.; Sugiyanto, D.; Ogawa, Y.; Kimata, F.; Fitriani, D.

    2012-06-01

    Sumatran Fault Zone is the most active fault in Indonesia as a result of strike-slip component of Indo-Australian oblique convergence. With the length of 1900 km, Sumatran fault was divided into 20 segments starting from the southernmost Sumatra Island having small slip rate and increasing to the north end of Sumatra Island. There are several geophysical methods to analyze fault structure depending on physical parameter used in these methods, such as seismology, geodesy and electromagnetic. Magnetotelluric method which is one of geophysical methods has been widely used in mapping and sounding resistivity distribution because it does not only has the ability for detecting contras resistivity but also has a penetration range up to hundreds of kilometers. Magnetotelluric survey was carried out in Aceh region with the 12 total sites crossing Sumatran Fault on Aceh and Seulimeum segments. Two components of electric and magnetic fields were recorded during 10 hours in average with the frequency range from 320 Hz to 0,01 Hz. Analysis of the pseudosection of phase and apparent resistivity exhibit vertical low phase flanked on the west and east by high phase describing the existence of resistivity contras in this region. Having rotated the data to N45°E direction, interpretation of the result has been performed using three different methods of 1D MT modeling i.e. Bostick inversion, 1D MT inversion of TM data, and 1D MT inversion of the impedance determinant. By comparison, we concluded that the use of TM data only and the impedance determinant in 1D inversion yield the more reliable resistivity structure of the fault compare to other methods. Based on this result, it has been shown clearly that Sumatra Fault is characterized by vertical contras resistivity indicating the existence of Aceh and Seulimeum faults which has a good agreement with the geological data.

  3. Optimizing Likelihood Models for Particle Trajectory Segmentation in Multi-State Systems.

    Science.gov (United States)

    Young, Dylan Christopher; Scrimgeour, Jan

    2018-06-19

    Particle tracking offers significant insight into the molecular mechanics that govern the behav- ior of living cells. The analysis of molecular trajectories that transition between different motive states, such as diffusive, driven and tethered modes, is of considerable importance, with even single trajectories containing significant amounts of information about a molecule's environment and its interactions with cellular structures. Hidden Markov models (HMM) have been widely adopted to perform the segmentation of such complex tracks. In this paper, we show that extensive analysis of hidden Markov model outputs using data derived from multi-state Brownian dynamics simulations can be used both for the optimization of the likelihood models used to describe the states of the system and for characterization of the technique's failure mechanisms. This analysis was made pos- sible by the implementation of parallelized adaptive direct search algorithm on a Nvidia graphics processing unit. This approach provides critical information for the visualization of HMM failure and successful design of particle tracking experiments where trajectories contain multiple mobile states. © 2018 IOP Publishing Ltd.

  4. Proposal for a model for competitiveness analysis in environmental sustainability in automotive segment companies

    Directory of Open Access Journals (Sweden)

    Luís Henrique Rodrigues

    2018-06-01

    Full Text Available The competitive landscape for companies has been changing over time, featuring an increase in competitiveness in cost, quality, reliability, agility and more recently by a concern for environmental and social factors. This work aims to propose an exploratory analysis model to evaluate companies’ sustainability competitiveness. The model proposes the grouping of companies into clusters, ranking them according to the adoption of lean manufacturing practices, environmental management and human resources, and allocating them into quadrants according to the higher or lower production of waste in their manufacturing processes. The adherence to the model is made with a sample of automotive segment companies (auto parts and motor vehicle manufacturers. The work is classified as one of a practical nature, exploratory, qualitative, and using the survey method. The conclusion that 37.5% of auto parts companies are grouped into clusters that lead to the reduction of waste, with practices in lean manufacturing and environmental management which adjust to competitive factors in the sustainability of motor vehicle manufacturers, is noteworthy.

  5. New variational image decomposition model for simultaneously denoising and segmenting optical coherence tomography images

    International Nuclear Information System (INIS)

    Duan, Jinming; Bai, Li; Tench, Christopher; Gottlob, Irene; Proudlock, Frank

    2015-01-01

    Optical coherence tomography (OCT) imaging plays an important role in clinical diagnosis and monitoring of diseases of the human retina. Automated analysis of optical coherence tomography images is a challenging task as the images are inherently noisy. In this paper, a novel variational image decomposition model is proposed to decompose an OCT image into three components: the first component is the original image but with the noise completely removed; the second contains the set of edges representing the retinal layer boundaries present in the image; and the third is an image of noise, or in image decomposition terms, the texture, or oscillatory patterns of the original image. In addition, a fast Fourier transform based split Bregman algorithm is developed to improve computational efficiency of solving the proposed model. Extensive experiments are conducted on both synthesised and real OCT images to demonstrate that the proposed model outperforms the state-of-the-art speckle noise reduction methods and leads to accurate retinal layer segmentation. (paper)

  6. Automatic bladder segmentation on CBCT for multiple plan ART of bladder cancer using a patient-specific bladder model

    Energy Technology Data Exchange (ETDEWEB)

    Xiangfei, Chai; Hulshof, Maarten; Bel, Arjan [Department of Radiotherapy, Academic medical Center, University of Amsterdam, 1105 AZ, Amsterdam (Netherlands); Van Herk, Marcel; Betgen, Anja [Department of Radiotherapy, The Netherlands Cancer Institute/Antoni van Leeuwenhoek Hospital, 1066 CX, Amsterdam (Netherlands)

    2012-06-21

    In multiple plan adaptive radiotherapy (ART) strategies of bladder cancer, a library of plans corresponding to different bladder volumes is created based on images acquired in early treatment sessions. Subsequently, the plan for the smallest PTV safely covering the bladder on cone-beam CT (CBCT) is selected as the plan of the day. The aim of this study is to develop an automatic bladder segmentation approach suitable for CBCT scans and test its ability to select the appropriate plan from the library of plans for such an ART procedure. Twenty-three bladder cancer patients with a planning CT and on average 11.6 CBCT scans were included in our study. For each patient, all CBCT scans were matched to the planning CT on bony anatomy. Bladder contours were manually delineated for each planning CT (for model building) and CBCT (for model building and validation). The automatic segmentation method consisted of two steps. A patient-specific bladder deformation model was built from the training data set of each patient (the planning CT and the first five CBCT scans). Then, the model was applied to automatically segment bladders in the validation data of the same patient (the remaining CBCT scans). Principal component analysis (PCA) was applied to the training data to model patient-specific bladder deformation patterns. The number of PCA modes for each patient was chosen such that the bladder shapes in the training set could be represented by such number of PCA modes with less than 0.1 cm mean residual error. The automatic segmentation started from the bladder shape of a reference CBCT, which was adjusted by changing the weight of each PCA mode. As a result, the segmentation contour was deformed consistently with the training set to fit the bladder in the validation image. A cost function was defined by the absolute difference between the directional gradient field of reference CBCT sampled on the corresponding bladder contour and the directional gradient field of validation

  7. Automatic bladder segmentation on CBCT for multiple plan ART of bladder cancer using a patient-specific bladder model

    International Nuclear Information System (INIS)

    Chai Xiangfei; Hulshof, Maarten; Bel, Arjan; Van Herk, Marcel; Betgen, Anja

    2012-01-01

    In multiple plan adaptive radiotherapy (ART) strategies of bladder cancer, a library of plans corresponding to different bladder volumes is created based on images acquired in early treatment sessions. Subsequently, the plan for the smallest PTV safely covering the bladder on cone-beam CT (CBCT) is selected as the plan of the day. The aim of this study is to develop an automatic bladder segmentation approach suitable for CBCT scans and test its ability to select the appropriate plan from the library of plans for such an ART procedure. Twenty-three bladder cancer patients with a planning CT and on average 11.6 CBCT scans were included in our study. For each patient, all CBCT scans were matched to the planning CT on bony anatomy. Bladder contours were manually delineated for each planning CT (for model building) and CBCT (for model building and validation). The automatic segmentation method consisted of two steps. A patient-specific bladder deformation model was built from the training data set of each patient (the planning CT and the first five CBCT scans). Then, the model was applied to automatically segment bladders in the validation data of the same patient (the remaining CBCT scans). Principal component analysis (PCA) was applied to the training data to model patient-specific bladder deformation patterns. The number of PCA modes for each patient was chosen such that the bladder shapes in the training set could be represented by such number of PCA modes with less than 0.1 cm mean residual error. The automatic segmentation started from the bladder shape of a reference CBCT, which was adjusted by changing the weight of each PCA mode. As a result, the segmentation contour was deformed consistently with the training set to fit the bladder in the validation image. A cost function was defined by the absolute difference between the directional gradient field of reference CBCT sampled on the corresponding bladder contour and the directional gradient field of validation

  8. A landscape scale valley confinement algorithm: Delineating unconfined valley bottoms for geomorphic, aquatic, and riparian applications

    Science.gov (United States)

    David E. Nagel; John M. Buffington; Sharon L. Parkes; Seth Wenger; Jaime R. Goode

    2014-01-01

    Valley confinement is an important landscape characteristic linked to aquatic habitat, riparian diversity, and geomorphic processes. This report describes a GIS program called the Valley Confinement Algorithm (VCA), which identifies unconfined valleys in montane landscapes. The algorithm uses nationally available digital elevation models (DEMs) at 10-30 m resolution to...

  9. Spread and Control of Rift Valley Fever virus after accidental introduction in the Netherlands: a modelling study.

    NARCIS (Netherlands)

    Fischer, E.A.J.; Boender, G.J.; Koeijer, de A.A.; Nodelijk, G.; Roermund, van H.J.W.

    2011-01-01

    Rift Valley Fever (RVF) is a zoonotic vector-borne infection and causes a potentially severe disease in both humans and young animals. The Ministry of Economic Affairs, Agriculture and Innovation (EL&I) is interested in the risk of an outbreak of Rift Valley Fever virus (RVFV) for the

  10. A Combined Random Forests and Active Contour Model Approach for Fully Automatic Segmentation of the Left Atrium in Volumetric MRI

    Directory of Open Access Journals (Sweden)

    Chao Ma

    2017-01-01

    Full Text Available Segmentation of the left atrium (LA from cardiac magnetic resonance imaging (MRI datasets is of great importance for image guided atrial fibrillation ablation, LA fibrosis quantification, and cardiac biophysical modelling. However, automated LA segmentation from cardiac MRI is challenging due to limited image resolution, considerable variability in anatomical structures across subjects, and dynamic motion of the heart. In this work, we propose a combined random forests (RFs and active contour model (ACM approach for fully automatic segmentation of the LA from cardiac volumetric MRI. Specifically, we employ the RFs within an autocontext scheme to effectively integrate contextual and appearance information from multisource images together for LA shape inferring. The inferred shape is then incorporated into a volume-scalable ACM for further improving the segmentation accuracy. We validated the proposed method on the cardiac volumetric MRI datasets from the STACOM 2013 and HVSMR 2016 databases and showed that it outperforms other latest automated LA segmentation methods. Validation metrics, average Dice coefficient (DC and average surface-to-surface distance (S2S, were computed as 0.9227±0.0598 and 1.14±1.205 mm, versus those of 0.6222–0.878 and 1.34–8.72 mm, obtained by other methods, respectively.

  11. Segmentation of solid subregion of high grade gliomas in MRI images based on active contour model (ACM)

    Science.gov (United States)

    Seow, P.; Win, M. T.; Wong, J. H. D.; Abdullah, N. A.; Ramli, N.

    2016-03-01

    Gliomas are tumours arising from the interstitial tissue of the brain which are heterogeneous, infiltrative and possess ill-defined borders. Tumour subregions (e.g. solid enhancing part, edema and necrosis) are often used for tumour characterisation. Tumour demarcation into substructures facilitates glioma staging and provides essential information. Manual segmentation had several drawbacks that include laborious, time consuming, subjected to intra and inter-rater variability and hindered by diversity in the appearance of tumour tissues. In this work, active contour model (ACM) was used to segment the solid enhancing subregion of the tumour. 2D brain image acquisition data using 3T MRI fast spoiled gradient echo sequence in post gadolinium of four histologically proven high-grade glioma patients were obtained. Preprocessing of the images which includes subtraction and skull stripping were performed and then followed by ACM segmentation. The results of the automatic segmentation method were compared against the manual delineation of the tumour by a trainee radiologist. Both results were further validated by an experienced neuroradiologist and a brief quantitative evaluations (pixel area and difference ratio) were performed. Preliminary results of the clinical data showed the potential of ACM model in the application of fast and large scale tumour segmentation in medical imaging.

  12. Segmentation of solid subregion of high grade gliomas in MRI images based on active contour model (ACM)

    International Nuclear Information System (INIS)

    Seow, P; Win, M T; Wong, J H D; Ramli, N; Abdullah, N A

    2016-01-01

    Gliomas are tumours arising from the interstitial tissue of the brain which are heterogeneous, infiltrative and possess ill-defined borders. Tumour subregions (e.g. solid enhancing part, edema and necrosis) are often used for tumour characterisation. Tumour demarcation into substructures facilitates glioma staging and provides essential information. Manual segmentation had several drawbacks that include laborious, time consuming, subjected to intra and inter-rater variability and hindered by diversity in the appearance of tumour tissues. In this work, active contour model (ACM) was used to segment the solid enhancing subregion of the tumour. 2D brain image acquisition data using 3T MRI fast spoiled gradient echo sequence in post gadolinium of four histologically proven high-grade glioma patients were obtained. Preprocessing of the images which includes subtraction and skull stripping were performed and then followed by ACM segmentation. The results of the automatic segmentation method were compared against the manual delineation of the tumour by a trainee radiologist. Both results were further validated by an experienced neuroradiologist and a brief quantitative evaluations (pixel area and difference ratio) were performed. Preliminary results of the clinical data showed the potential of ACM model in the application of fast and large scale tumour segmentation in medical imaging. (paper)

  13. Assessing potential effects of changes in water use with a numerical groundwater-flow model of Carson Valley, Douglas County, Nevada, and Alpine County, California

    Science.gov (United States)

    Yager, Richard M.; Maurer, Douglas K.; Mayers, C.J.

    2012-01-01

    margins. A groundwater-flow model of Quaternary and Tertiary sediments in Carson Valley was developed using MODFLOW and calibrated to simulate historical conditions from water years 1971 through 2005. The 35-year transient simulation represented quarterly changes in precipitation, streamflow, pumping and irrigation. Inflows to the groundwater system simulated in the model include mountain-front recharge from watersheds in the Carson Range and Pine Nut Mountains, valley recharge from precipitation and land application of wastewater, agricultural recharge from irrigation, and septic-tank discharge. Outflows from the groundwater system simulated in the model include evapotranspiration from the water table and groundwater withdrawals for municipal, domestic, irrigation and other water supplies. The exchange of water between groundwater, the Carson River, and the irrigation system was represented with a version of the Streamflow Routing (SFR) package that was modified to apply diversions from the irrigation network to irrigated areas as recharge. The groundwater-flow model was calibrated through nonlinear regression with UCODE to measured water levels and streamflow to estimate values of hydraulic conductivity, recharge and streambed hydraulic-conductivity that were represented by 18 optimized parameters. The aquifer system was simulated as confined to facilitate numerical convergence, and the hydraulic conductivity of the top active model layers that intersect the water table was multiplied by a factor to account for partial saturation. Storage values representative of specific yield were specified in parts of model layers where unconfined conditions are assumed to occur. The median transmissivity (T) values (11,000 and 800 ft2/d for the fluvial and alluvial-fan sediments, respectively) are both within the third quartile of T values estimated from specific-capacity data, but T values for Tertiary sediments are larger than the third quartile estimated from specific

  14. CT-based patient modeling for head and neck hyperthermia treatment planning: manual versus automatic normal-tissue-segmentation.

    Science.gov (United States)

    Verhaart, René F; Fortunati, Valerio; Verduijn, Gerda M; van Walsum, Theo; Veenland, Jifke F; Paulides, Margarethus M

    2014-04-01

    Clinical trials have shown that hyperthermia, as adjuvant to radiotherapy and/or chemotherapy, improves treatment of patients with locally advanced or recurrent head and neck (H&N) carcinoma. Hyperthermia treatment planning (HTP) guided H&N hyperthermia is being investigated, which requires patient specific 3D patient models derived from Computed Tomography (CT)-images. To decide whether a recently developed automatic-segmentation algorithm can be introduced in the clinic, we compared the impact of manual- and automatic normal-tissue-segmentation variations on HTP quality. CT images of seven patients were segmented automatically and manually by four observers, to study inter-observer and intra-observer geometrical variation. To determine the impact of this variation on HTP quality, HTP was performed using the automatic and manual segmentation of each observer, for each patient. This impact was compared to other sources of patient model uncertainties, i.e. varying gridsizes and dielectric tissue properties. Despite geometrical variations, manual and automatic generated 3D patient models resulted in an equal, i.e. 1%, variation in HTP quality. This variation was minor with respect to the total of other sources of patient model uncertainties, i.e. 11.7%. Automatically generated 3D patient models can be introduced in the clinic for H&N HTP. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  15. CT-based patient modeling for head and neck hyperthermia treatment planning: Manual versus automatic normal-tissue-segmentation

    International Nuclear Information System (INIS)

    Verhaart, René F.; Fortunati, Valerio; Verduijn, Gerda M.; Walsum, Theo van; Veenland, Jifke F.; Paulides, Margarethus M.

    2014-01-01

    Background and purpose: Clinical trials have shown that hyperthermia, as adjuvant to radiotherapy and/or chemotherapy, improves treatment of patients with locally advanced or recurrent head and neck (H and N) carcinoma. Hyperthermia treatment planning (HTP) guided H and N hyperthermia is being investigated, which requires patient specific 3D patient models derived from Computed Tomography (CT)-images. To decide whether a recently developed automatic-segmentation algorithm can be introduced in the clinic, we compared the impact of manual- and automatic normal-tissue-segmentation variations on HTP quality. Material and methods: CT images of seven patients were segmented automatically and manually by four observers, to study inter-observer and intra-observer geometrical variation. To determine the impact of this variation on HTP quality, HTP was performed using the automatic and manual segmentation of each observer, for each patient. This impact was compared to other sources of patient model uncertainties, i.e. varying gridsizes and dielectric tissue properties. Results: Despite geometrical variations, manual and automatic generated 3D patient models resulted in an equal, i.e. 1%, variation in HTP quality. This variation was minor with respect to the total of other sources of patient model uncertainties, i.e. 11.7%. Conclusions: Automatically generated 3D patient models can be introduced in the clinic for H and N HTP

  16. Time series segmentation: a new approach based on Genetic Algorithm and Hidden Markov Model

    Science.gov (United States)

    Toreti, A.; Kuglitsch, F. G.; Xoplaki, E.; Luterbacher, J.

    2009-04-01

    The subdivision of a time series into homogeneous segments has been performed using various methods applied to different disciplines. In climatology, for example, it is accompanied by the well-known homogenization problem and the detection of artificial change points. In this context, we present a new method (GAMM) based on Hidden Markov Model (HMM) and Genetic Algorithm (GA), applicable to series of independent observations (and easily adaptable to autoregressive processes). A left-to-right hidden Markov model, estimating the parameters and the best-state sequence, respectively, with the Baum-Welch and Viterbi algorithms, was applied. In order to avoid the well-known dependence of the Baum-Welch algorithm on the initial condition, a Genetic Algorithm was developed. This algorithm is characterized by mutation, elitism and a crossover procedure implemented with some restrictive rules. Moreover the function to be minimized was derived following the approach of Kehagias (2004), i.e. it is the so-called complete log-likelihood. The number of states was determined applying a two-fold cross-validation procedure (Celeux and Durand, 2008). Being aware that the last issue is complex, and it influences all the analysis, a Multi Response Permutation Procedure (MRPP; Mielke et al., 1981) was inserted. It tests the model with K+1 states (where K is the state number of the best model) if its likelihood is close to K-state model. Finally, an evaluation of the GAMM performances, applied as a break detection method in the field of climate time series homogenization, is shown. 1. G. Celeux and J.B. Durand, Comput Stat 2008. 2. A. Kehagias, Stoch Envir Res 2004. 3. P.W. Mielke, K.J. Berry, G.W. Brier, Monthly Wea Rev 1981.

  17. An accelerated life test model for harmonic drives under a segmental stress history and its parameter optimization

    Directory of Open Access Journals (Sweden)

    Zhang Chao

    2015-12-01

    Full Text Available Harmonic drives have various distinctive advantages and are widely used in space drive mechanisms. Accelerated life test (ALT is commonly conducted to shorten test time and reduce associated costs. An appropriate ALT model is needed to predict the lifetime of harmonic drives with ALT data. However, harmonic drives which are used in space usually work under a segmental stress history, and traditional ALT models can hardly be used in this situation. This paper proposes a dedicated ALT model for harmonic drives applied in space systems. A comprehensive ALT model is established and genetic algorithm (GA is adopted to obtain optimal parameters in the model using the Manson fatigue damage rule to describe the fatigue failure process and a cumulative damage method to calculate and accumulate the damage caused by each segment in the stress history. An ALT of harmonic drives was carried out and experimental results show that this model is acceptable and effective.

  18. Human effects on the hydrologic system of the Verde Valley, central Arizona, 1910–2005 and 2005–2110, using a regional groundwater flow model

    Science.gov (United States)

    Garner, Bradley D.; Pool, D.R.; Tillman, Fred D.; Forbes, Brandon T.

    2013-01-01

    Water budgets were developed for the Verde Valley of central Arizona in order to evaluate the degree to which human stresses have affected the hydrologic system and might affect it in the future. The Verde Valley is a portion of central Arizona wherein concerns have been raised about water availability, particularly perennial base flow of the Verde River. The Northern Arizona Regional Groundwater Flow Model (NARGFM) was used to generate the water budgets and was run in several configurations for the 1910–2005 and 2005–2110 time periods. The resultant water budgets were subtracted from one another in order to quantify the relative changes that were attributable solely to human stresses; human stresses included groundwater withdrawals and incidental and artificial recharge but did not include, for example, human effects on the global climate. Three hypothetical and varied conditions of human stresses were developed and applied to the model for the 2005–2110 period. On the basis of this analysis, human stresses during 1910–2005 were found to have already affected the hydrologic system of the Verde Valley, and human stresses will continue to affect the hydrologic system during 2005–2110. Riparian evapotranspiration decreased and underflow into the Verde Valley increased because of human stresses, and net groundwater discharge to the Verde River in the Verde Valley decreased for the 1910–2005 model runs. The model also showed that base flow at the upstream end of the study area, as of 2005, was about 4,900 acre-feet per year less than it would have been in the absence of human stresses. At the downstream end of the Verde Valley, base flow had been reduced by about 10,000 acre-feet per year by the year 2005 because of human stresses. For the 2005–2110 period, the model showed that base flow at the downstream end of the Verde Valley may decrease by an additional 5,400 to 8,600 acre-feet per year because of past, ongoing, and hypothetical future human

  19. Evaluation of the groundwater flow model for southern Utah and Goshen Valleys, Utah, updated to conditions through 2011, with new projections and groundwater management simulations

    Science.gov (United States)

    Brooks, Lynette E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the Southern Utah Valley Municipal Water Association, updated an existing USGS model of southern Utah and Goshen Valleys for hydrologic and climatic conditions from 1991 to 2011 and used the model for projection and groundwater management simulations. All model files used in the transient model were updated to be compatible with MODFLOW-2005 and with the additional stress periods. The well and recharge files had the most extensive changes. Discharge to pumping wells in southern Utah and Goshen Valleys was estimated and simulated on an annual basis from 1991 to 2011. Recharge estimates for 1991 to 2011 were included in the updated model by using precipitation, streamflow, canal diversions, and irrigation groundwater withdrawals for each year. The model was evaluated to determine how well it simulates groundwater conditions during recent increased withdrawals and drought, and to determine if the model is adequate for use in future planning. In southern Utah Valley, the magnitude and direction of annual water-level fluctuation simulated by the updated model reasonably match measured water-level changes, but they do not simulate as much decline as was measured in some locations from 2000 to 2002. Both the rapid increase in groundwater withdrawals and the total groundwater withdrawals in southern Utah Valley during this period exceed the variations and magnitudes simulated during the 1949 to 1990 calibration period. It is possible that hydraulic properties may be locally incorrect or that changes, such as land use or irrigation diversions, occurred that are not simulated. In the northern part of Goshen Valley, simulated water-level changes reasonably match measured changes. Farther south, however, simulated declines are much less than measured declines. Land-use changes indicate that groundwater withdrawals in Goshen Valley are possibly greater than estimated and simulated. It is also possible that irrigation

  20. Model-based segmentation in orbital volume measurement with cone beam computed tomography and evaluation against current concepts.

    Science.gov (United States)

    Wagner, Maximilian E H; Gellrich, Nils-Claudius; Friese, Karl-Ingo; Becker, Matthias; Wolter, Franz-Erich; Lichtenstein, Juergen T; Stoetzer, Marcus; Rana, Majeed; Essig, Harald

    2016-01-01

    Objective determination of the orbital volume is important in the diagnostic process and in evaluating the efficacy of medical and/or surgical treatment of orbital diseases. Tools designed to measure orbital volume with computed tomography (CT) often cannot be used with cone beam CT (CBCT) because of inferior tissue representation, although CBCT has the benefit of greater availability and lower patient radiation exposure. Therefore, a model-based segmentation technique is presented as a new method for measuring orbital volume and compared to alternative techniques. Both eyes from thirty subjects with no known orbital pathology who had undergone CBCT as a part of routine care were evaluated (n = 60 eyes). Orbital volume was measured with manual, atlas-based, and model-based segmentation methods. Volume measurements, volume determination time, and usability were compared between the three methods. Differences in means were tested for statistical significance using two-tailed Student's t tests. Neither atlas-based (26.63 ± 3.15 mm(3)) nor model-based (26.87 ± 2.99 mm(3)) measurements were significantly different from manual volume measurements (26.65 ± 4.0 mm(3)). However, the time required to determine orbital volume was significantly longer for manual measurements (10.24 ± 1.21 min) than for atlas-based (6.96 ± 2.62 min, p < 0.001) or model-based (5.73 ± 1.12 min, p < 0.001) measurements. All three orbital volume measurement methods examined can accurately measure orbital volume, although atlas-based and model-based methods seem to be more user-friendly and less time-consuming. The new model-based technique achieves fully automated segmentation results, whereas all atlas-based segmentations at least required manipulations to the anterior closing. Additionally, model-based segmentation can provide reliable orbital volume measurements when CT image quality is poor.

  1. Semiautomatic segmentation of aortic valve from sequenced ultrasound image using a novel shape-constraint GCV model

    International Nuclear Information System (INIS)

    Guo, Yiting; Dong, Bin; Wang, Bing; Xie, Hongzhi; Zhang, Shuyang; Gu, Lixu

    2014-01-01

    Purpose: Effective and accurate segmentation of the aortic valve (AV) from sequenced ultrasound (US) images remains a technical challenge because of intrinsic factors of ultrasound images that impact the quality and the continuous changes of shape and position of segmented objects. In this paper, a novel shape-constraint gradient Chan-Vese (GCV) model is proposed for segmenting the AV from time serial echocardiography. Methods: The GCV model is derived by incorporating the energy of the gradient vector flow into a CV model framework, where the gradient vector energy term is introduced by calculating the deviation angle between the inward normal force of the evolution contour and the gradient vector force. The flow force enlarges the capture range and enhances the blurred boundaries of objects. This is achieved by adding a circle-like contour (constructed using the AV structure region as a constraint shape) as an energy item to the GCV model through the shape comparison function. This shape-constrained energy can enhance the image constraint force by effectively connecting separate gaps of the object edge as well as driving the evolution contour to quickly approach the ideal object. Because of the slight movement of the AV in adjacent frames, the initial constraint shape is defined by users, with the other constraint shapes being derived from the segmentation results of adjacent sequence frames after morphological filtering. The AV is segmented from the US images by minimizing the proposed energy function. Results: To evaluate the performance of the proposed method, five assessment parameters were used to compare it with manual delineations performed by radiologists (gold standards). Three hundred and fifteen images acquired from nine groups were analyzed in the experiment. The area-metric overlap error rate was 6.89% ± 2.88%, the relative area difference rate 3.94% ± 2.63%, the average symmetric contour distance 1.08 ± 0.43 mm, the root mean square symmetric

  2. Semiautomatic segmentation of aortic valve from sequenced ultrasound image using a novel shape-constraint GCV model

    Energy Technology Data Exchange (ETDEWEB)

    Guo, Yiting [Multi-disciplinary Research Center, Hebei University, Baoding 071000 (China); Dong, Bin [Hebei University Affiliated Hospital, Hebei Baoding 071000 (China); Wang, Bing [College of Mathematics and Computer Science, Hebei University, Baoding 071000 (China); Xie, Hongzhi, E-mail: xiehongzhi@medmail.com.cn, E-mail: gulixu@sjtu.edu.cn; Zhang, Shuyang [Department of Cardiovascular, Peking Union Medical College Hospital, Beijing 100005 (China); Gu, Lixu, E-mail: xiehongzhi@medmail.com.cn, E-mail: gulixu@sjtu.edu.cn [Multi-disciplinary Research Center, Hebei University, Baoding 071000, China and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030 (China)

    2014-07-15

    Purpose: Effective and accurate segmentation of the aortic valve (AV) from sequenced ultrasound (US) images remains a technical challenge because of intrinsic factors of ultrasound images that impact the quality and the continuous changes of shape and position of segmented objects. In this paper, a novel shape-constraint gradient Chan-Vese (GCV) model is proposed for segmenting the AV from time serial echocardiography. Methods: The GCV model is derived by incorporating the energy of the gradient vector flow into a CV model framework, where the gradient vector energy term is introduced by calculating the deviation angle between the inward normal force of the evolution contour and the gradient vector force. The flow force enlarges the capture range and enhances the blurred boundaries of objects. This is achieved by adding a circle-like contour (constructed using the AV structure region as a constraint shape) as an energy item to the GCV model through the shape comparison function. This shape-constrained energy can enhance the image constraint force by effectively connecting separate gaps of the object edge as well as driving the evolution contour to quickly approach the ideal object. Because of the slight movement of the AV in adjacent frames, the initial constraint shape is defined by users, with the other constraint shapes being derived from the segmentation results of adjacent sequence frames after morphological filtering. The AV is segmented from the US images by minimizing the proposed energy function. Results: To evaluate the performance of the proposed method, five assessment parameters were used to compare it with manual delineations performed by radiologists (gold standards). Three hundred and fifteen images acquired from nine groups were analyzed in the experiment. The area-metric overlap error rate was 6.89% ± 2.88%, the relative area difference rate 3.94% ± 2.63%, the average symmetric contour distance 1.08 ± 0.43 mm, the root mean square symmetric

  3. Modeling and segmentation of intra-cochlear anatomy in conventional CT

    Science.gov (United States)

    Noble, Jack H.; Rutherford, Robert B.; Labadie, Robert F.; Majdani, Omid; Dawant, Benoit M.

    2010-03-01

    Cochlear implant surgery is a procedure performed to treat profound hearing loss. Since the cochlea is not visible in surgery, the physician uses anatomical landmarks to estimate the pose of the cochlea. Research has indicated that implanting the electrode in a particular cavity of the cochlea, the scala tympani, results in better hearing restoration. The success of the scala tympani implantation is largely dependent on the point of entry and angle of electrode insertion. Errors can occur due to the imprecise nature of landmark-based, manual navigation as well as inter-patient variations between scala tympani and the anatomical landmarks. In this work, we use point distribution models of the intra-cochlear anatomy to study the inter-patient variations between the cochlea and the typical anatomic landmarks, and we implement an active shape model technique to automatically localize intra-cochlear anatomy in conventional CT images, where intra-cochlear structures are not visible. This fully automatic segmentation could aid the surgeon to choose the point of entry and angle of approach to maximize the likelihood of scala tympani insertion, resulting in more substantial hearing restoration.

  4. Repeatability of a 3D multi-segment foot model protocol in presence of foot deformities.

    Science.gov (United States)

    Deschamps, Kevin; Staes, Filip; Bruyninckx, Herman; Busschots, Ellen; Matricali, Giovanni A; Spaepen, Pieter; Meyer, Christophe; Desloovere, Kaat

    2012-07-01

    Repeatability studies on 3D multi-segment foot models (3DMFMs) have mainly considered healthy participants which contrasts with the widespread application of these models to evaluate foot pathologies. The current study aimed at establishing the repeatability of the 3DMFM described by Leardini et al. in presence of foot deformities. Foot kinematics of eight adult participants were analyzed using a repeated-measures design including two therapists with different levels of experience. The inter-trial variability was higher compared to the kinematics of healthy subjects. Consideration of relative angles resulted in the lowest inter-session variability. The absolute 3D rotations between the Sha-Cal and Cal-Met seem to have the lowest variability in both therapists. A general trend towards higher σ(sess)/σ(trial) ratios was observed when the midfoot was involved. The current study indicates that not only relative 3D rotations and planar angles can be measured consistently in patients, also a number of absolute parameters can be consistently measured serving as basis for the decision making process. Copyright © 2012 Elsevier B.V. All rights reserved.

  5. New structural/tectonical model and its implication on hydrological thinking and groundwater management - the Lake Tiberias, Jordan Rift Valley

    Science.gov (United States)

    Inbar, Nimrod; Magri, Fabien; Yellin-Dror, Annat; Rosenthal, Eliahu; Möller, Peter; Siebert, Christian; Guttman, Josef

    2014-05-01

    Lake Tiberias is a fresh water lake located at the Kinneret basin which is approximately 30 km long and 10 km wide. It comprises a link in the chain of pull-apart basins that characterizes the structure of the conspicuous Jordan Rift Valley (JRV). The basin surface is about 200 m below mean sea level (msl) and basin-fill attains a thickness of up to 8 km. Until recently, studies focused mainly on the upper strata of basin fill. Consequently, a complete three dimensional geological model, including clear view of the tectonic framework at the Kinneret Basin was incomplete. This situation imposes great difficulty in understanding the local hydrological system and as consequence enforce constrains on groundwater management of the regional aquifers that flows towards the lake. A recently proposed structural/tectonical model (Inbar, 2012) enables revaluation of several geohydrological aspects at Sea of Galilee and its surroundings and a new hydrological model based on those findings aims to clarify those aspects with relation to groundwater management. The deep-seated stratigraphical units were seismically studied at the Kinnarot Valley (southern part of Kinneret basin) where sufficient information is available (Inbar, 2012). This study shows the subsidence and northwestward tilting of the basin floor (pre-rift formations) and the flow of thick Late Miocene salt accumulation accordingly. Furthermore, shallower seismic data, collected at the lake itself, shows a suspected salt dome close to the western boundary fault of the basin (Resnikov et al., 2004). Salt flow is now suggested to be a substantial factor in the tectonic play. At the lake surroundings there are several springs and boreholes where brine immerges from an estimated depth of about 2-3 kilometers. Significant differences in brine characteristics raised questions regarding the location of brine traps, flow mechanism and the mixture process between the fresh water and the brine. However, the effect of the

  6. A new background distribution-based active contour model for three-dimensional lesion segmentation in breast DCE-MRI

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Hui; Liu, Yiping; Qiu, Tianshuang [Department of Biomedical Engineering, Dalian University of Technology, Dalian 116024 (China); Zhao, Zuowei, E-mail: liuhui@dlut.edu.cn [Second Affiliated Hospital, Dalian Medical University, Dalian 116027 (China); Zhang, Lina [Department of Radiology, First Affiliated Hospital, Dalian Medical University, Dalian 116027 (China)

    2014-08-15

    Purpose: To develop and evaluate a computerized semiautomatic segmentation method for accurate extraction of three-dimensional lesions from dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) of the breast. Methods: The authors propose a new background distribution-based active contour model using level set (BDACMLS) to segment lesions in breast DCE-MRIs. The method starts with manual selection of a region of interest (ROI) that contains the entire lesion in a single slice where the lesion is enhanced. Then the lesion volume from the volume data of interest, which is captured automatically, is separated. The core idea of BDACMLS is a new signed pressure function which is based solely on the intensity distribution combined with pathophysiological basis. To compare the algorithm results, two experienced radiologists delineated all lesions jointly to obtain the ground truth. In addition, results generated by other different methods based on level set (LS) are also compared with the authors’ method. Finally, the performance of the proposed method is evaluated by several region-based metrics such as the overlap ratio. Results: Forty-two studies with 46 lesions that contain 29 benign and 17 malignant lesions are evaluated. The dataset includes various typical pathologies of the breast such as invasive ductal carcinoma, ductal carcinomain situ, scar carcinoma, phyllodes tumor, breast cysts, fibroadenoma, etc. The overlap ratio for BDACMLS with respect to manual segmentation is 79.55% ± 12.60% (mean ± s.d.). Conclusions: A new active contour model method has been developed and shown to successfully segment breast DCE-MRI three-dimensional lesions. The results from this model correspond more closely to manual segmentation, solve the weak-edge-passed problem, and improve the robustness in segmenting different lesions.

  7. A generative model for segmentation of tumor and organs-at-risk for radiation therapy planning of glioblastoma patients

    DEFF Research Database (Denmark)

    Agn, Mikael; Law, Ian; Munck Af Rosenschöld, Per

    2016-01-01

    to model tumor shape. The method is not tuned to any specific imaging protocol and can simultaneously segment the gross tumor volume, peritumoral edema and healthy tissue structures relevant for radiotherapy planning. We validate the method on a manually delineated clinical data set of glioblastoma...

  8. Semiautomatic bladder segmentation on CBCT using a population-based model for multiple-plan ART of bladder cancer

    NARCIS (Netherlands)

    Chai, Xiangfei; van Herk, Marcel; Betgen, Anja; Hulshof, Maarten; Bel, Arjan

    2012-01-01

    The aim of this study is to develop a novel semiautomatic bladder segmentation approach for selecting the appropriate plan from the library of plans for a multiple-plan adaptive radiotherapy (ART) procedure. A population-based statistical bladder model was first built from a training data set (95

  9. Segmentation process significantly influences the accuracy of 3D surface models derived from cone beam computed tomography

    NARCIS (Netherlands)

    Fourie, Zacharias; Damstra, Janalt; Schepers, Rutger H; Gerrits, Pieter; Ren, Yijin

    AIMS: To assess the accuracy of surface models derived from 3D cone beam computed tomography (CBCT) with two different segmentation protocols. MATERIALS AND METHODS: Seven fresh-frozen cadaver heads were used. There was no conflict of interests in this study. CBCT scans were made of the heads and 3D

  10. A refined model of Quaternary valley downcutting emphasizing the interplay between tectonically triggered regressive erosion and climatic cyclicity

    Science.gov (United States)

    Demoulin, A.; Beckers, A.; Rixhon, G.; Braucher, R.; Bourlès, D.; Siame, L.

    2012-04-01

    While climatic models of valley downcutting discuss the origin of terrace staircases in valleys of middle Europe within the frame of alternating cold and temperate periods of the Quaternary, other models, starting from a base level fall imposed by an initial tectonic signal, describe the response of the drainage network mainly as the propagation of an erosion wave from the place of base level fall (the margin of the uplifted region) toward the headwaters, the two types of model being rarely confronted. In the Ardennes (West Europe), cosmogenic 10Be and 26Al ages have recently been calculated for the abandonment of the Younger Main Terrace (YMT) level (Rixhon et al., 2011), a prominent feature at mid-height of the valleysides marking the starting point of the mid-Pleistocene phase of deep river incision in the massif. These ages show that the terrace has been abandoned diachronically as the result of a migrating erosion wave that started at 0.73 Ma in the Meuse catchment just north of the massif, soon entered the latter, and is still visible in the current long profiles of the Ardennian Ourthe tributaries as knickpoints disturbing their upper reaches. At first glance, these new findings are incompatible with the common belief that the terraces of the Ardennian rivers were generated by a climatically triggered stepwise general incision of the river profiles. However, several details of the terrace staircases (larger than average vertical spacing between the YMT and the next younger terrace, varying number of post-YMT terraces in trunk stream, tributaries and subtributaries) show that a combination of the climatic and tectonic models of river incision is able to satisfactorily account for all available data. The cosmogenic ages of the YMT also point out a particular behaviour of the migrating knickpoints, which apparently propagated on average more slowly in the main rivers than in the tributaries, in contradiction with the relation that makes knickpoint celerity

  11. Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model

    Energy Technology Data Exchange (ETDEWEB)

    He, Baochun; Huang, Cheng; Zhou, Shoujun; Hu, Qingmao; Jia, Fucang, E-mail: fc.jia@siat.ac.cn [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055 (China); Sharp, Gregory [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts 02114 (United States); Fang, Chihua; Fan, Yingfang [Department of Hepatology (I), Zhujiang Hospital, Southern Medical University, Guangzhou 510280 (China)

    2016-05-15

    Purpose: A robust, automatic, and rapid method for liver delineation is urgently needed for the diagnosis and treatment of liver disorders. Until now, the high variability in liver shape, local image artifacts, and the presence of tumors have complicated the development of automatic 3D liver segmentation. In this study, an automatic three-level AdaBoost-guided active shape model (ASM) is proposed for the segmentation of the liver based on enhanced computed tomography images in a robust and fast manner, with an emphasis on the detection of tumors. Methods: The AdaBoost voxel classifier and AdaBoost profile classifier were used to automatically guide three-level active shape modeling. In the first level of model initialization, fast automatic liver segmentation by an AdaBoost voxel classifier method is proposed. A shape model is then initialized by registration with the resulting rough segmentation. In the second level of active shape model fitting, a prior model based on the two-class AdaBoost profile classifier is proposed to identify the optimal surface. In the third level, a deformable simplex mesh with profile probability and curvature constraint as the external force is used to refine the shape fitting result. In total, three registration methods—3D similarity registration, probability atlas B-spline, and their proposed deformable closest point registration—are used to establish shape correspondence. Results: The proposed method was evaluated using three public challenge datasets: 3Dircadb1, SLIVER07, and Visceral Anatomy3. The results showed that our approach performs with promising efficiency, with an average of 35 s, and accuracy, with an average Dice similarity coefficient (DSC) of 0.94 ± 0.02, 0.96 ± 0.01, and 0.94 ± 0.02 for the 3Dircadb1, SLIVER07, and Anatomy3 training datasets, respectively. The DSC of the SLIVER07 testing and Anatomy3 unseen testing datasets were 0.964 and 0.933, respectively. Conclusions: The proposed automatic approach

  12. Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model.

    Science.gov (United States)

    He, Baochun; Huang, Cheng; Sharp, Gregory; Zhou, Shoujun; Hu, Qingmao; Fang, Chihua; Fan, Yingfang; Jia, Fucang

    2016-05-01

    A robust, automatic, and rapid method for liver delineation is urgently needed for the diagnosis and treatment of liver disorders. Until now, the high variability in liver shape, local image artifacts, and the presence of tumors have complicated the development of automatic 3D liver segmentation. In this study, an automatic three-level AdaBoost-guided active shape model (ASM) is proposed for the segmentation of the liver based on enhanced computed tomography images in a robust and fast manner, with an emphasis on the detection of tumors. The AdaBoost voxel classifier and AdaBoost profile classifier were used to automatically guide three-level active shape modeling. In the first level of model initialization, fast automatic liver segmentation by an AdaBoost voxel classifier method is proposed. A shape model is then initialized by registration with the resulting rough segmentation. In the second level of active shape model fitting, a prior model based on the two-class AdaBoost profile classifier is proposed to identify the optimal surface. In the third level, a deformable simplex mesh with profile probability and curvature constraint as the external force is used to refine the shape fitting result. In total, three registration methods-3D similarity registration, probability atlas B-spline, and their proposed deformable closest point registration-are used to establish shape correspondence. The proposed method was evaluated using three public challenge datasets: 3Dircadb1, SLIVER07, and Visceral Anatomy3. The results showed that our approach performs with promising efficiency, with an average of 35 s, and accuracy, with an average Dice similarity coefficient (DSC) of 0.94 ± 0.02, 0.96 ± 0.01, and 0.94 ± 0.02 for the 3Dircadb1, SLIVER07, and Anatomy3 training datasets, respectively. The DSC of the SLIVER07 testing and Anatomy3 unseen testing datasets were 0.964 and 0.933, respectively. The proposed automatic approach achieves robust, accurate, and fast liver

  13. Three-dimensional geological modelling of anthropogenic deposits at small urban sites: a case study from Sheepcote Valley, Brighton, UK.

    Science.gov (United States)

    Tame, C; Cundy, A B; Royse, K R; Smith, M; Moles, N R

    2013-11-15

    Improvements in computing speed and capacity and the increasing collection and digitisation of geological data now allow geoscientists to produce meaningful 3D spatial models of the shallow subsurface in many large urban areas, to predict ground conditions and reduce risk and uncertainty in urban planning. It is not yet clear how useful this 3D modelling approach is at smaller urban scales, where poorly characterised anthropogenic deposits (artificial/made ground and fill) form the dominant subsurface material and where the availability of borehole and other geological data is less comprehensive. This is important as it is these smaller urban sites, with complex site history, which frequently form the focus of urban regeneration and redevelopment schemes. This paper examines the extent to which the 3D modelling approach previously utilised at large urban scales can be extended to smaller less well-characterised urban sites, using a historic landfill site in Sheepcote Valley, Brighton, UK as a case study. Two 3D models were generated and compared using GSI3D™ software, one using borehole data only, one combining borehole data with local geological maps and results from a desk study (involving collation of available site data, including ground contour plans). These models clearly delimit the overall subsurface geology at the site, and allow visualisation and modelling of the anthropogenic deposits present. Shallow geophysical data collected from the site partially validate the 3D modelled data, and can improve GSI3D™ outputs where boundaries of anthropogenic deposits may not be clearly defined by surface, contour or borehole data. Attribution of geotechnical and geochemical properties to the 3D model is problematic without intrusive investigations and sampling. However, combining available borehole data, shallow geophysical methods and site histories may allow attribution of generic fill properties, and consequent reduction of urban development risk and

  14. Automatic lung segmentation in functional SPECT images using active shape models trained on reference lung shapes from CT.

    Science.gov (United States)

    Cheimariotis, Grigorios-Aris; Al-Mashat, Mariam; Haris, Kostas; Aletras, Anthony H; Jögi, Jonas; Bajc, Marika; Maglaveras, Nicolaos; Heiberg, Einar

    2018-02-01

    Image segmentation is an essential step in quantifying the extent of reduced or absent lung function. The aim of this study is to develop and validate a new tool for automatic segmentation of lungs in ventilation and perfusion SPECT images and compare automatic and manual SPECT lung segmentations with reference computed tomography (CT) volumes. A total of 77 subjects (69 patients with obstructive lung disease, and 8 subjects without apparent perfusion of ventilation loss) performed low-dose CT followed by ventilation/perfusion (V/P) SPECT examination in a hybrid gamma camera system. In the training phase, lung shapes from the 57 anatomical low-dose CT images were used to construct two active shape models (right lung and left lung) which were then used for image segmentation. The algorithm was validated in 20 patients, comparing its results to reference delineation of corresponding CT images, and by comparing automatic segmentation to manual delineations in SPECT images. The Dice coefficient between automatic SPECT delineations and manual SPECT delineations were 0.83 ± 0.04% for the right and 0.82 ± 0.05% for the left lung. There was statistically significant difference between reference volumes from CT and automatic delineations for the right (R = 0.53, p = 0.02) and left lung (R = 0.69, p automatic quantification of wide range of measurements.

  15. Modeling of phonon heat transfer in spherical segment of silica aerogel grains

    Energy Technology Data Exchange (ETDEWEB)

    Han, Ya-Fen; Xia, Xin-Lin, E-mail: xiaxl@hit.edu.cn; Tan, He-Ping, E-mail: tanheping@hit.edu.cn; Liu, Hai-Dong

    2013-07-01

    Phonon heat transfer in spherical segment of nano silica aerogel grains is investigated by the lattice Boltzmann method (LBM). For various sizes of grains, the temperature distribution and the thermal conductivity are obtained by the numerical simulation, in which the size effects of the gap surface are also considered. The results indicate that the temperature distribution in the silica aerogel grain depends strongly on the size. Both the decreases in the diameter of spherical segment and the ratio of the diameter of gap surface to the diameter of spherical segment reduce its effective thermal conductivity obviously. In addition, the phonon scattering at the boundary surfaces becomes more prominent when grain size decreases.

  16. Modeling of phonon heat transfer in spherical segment of silica aerogel grains

    International Nuclear Information System (INIS)

    Han, Ya-Fen; Xia, Xin-Lin; Tan, He-Ping; Liu, Hai-Dong

    2013-01-01

    Phonon heat transfer in spherical segment of nano silica aerogel grains is investigated by the lattice Boltzmann method (LBM). For various sizes of grains, the temperature distribution and the thermal conductivity are obtained by the numerical simulation, in which the size effects of the gap surface are also considered. The results indicate that the temperature distribution in the silica aerogel grain depends strongly on the size. Both the decreases in the diameter of spherical segment and the ratio of the diameter of gap surface to the diameter of spherical segment reduce its effective thermal conductivity obviously. In addition, the phonon scattering at the boundary surfaces becomes more prominent when grain size decreases

  17. The use of the greater trochanter marker in the thigh segment model: Implications for hip and knee frontal and transverse plane motion

    Directory of Open Access Journals (Sweden)

    Valentina Graci

    2016-03-01

    Conclusion: Hip and knee kinematics differed across different segment definitions including or excluding the greater trochanter marker, especially in the transverse plane. Therefore when considering whether to include the greater trochanter in the thigh segment model when using a surface markers to calculate 3D kinematics for movement assessment, it is important to have a clear understanding of the effect of different marker sets and segment models in use.

  18. Validation and sensitivity tests on improved parametrizations of a land surface process model (LSPM) in the Po Valley

    International Nuclear Information System (INIS)

    Cassardo, C.; Carena, E.; Longhetto, A.

    1998-01-01

    The Land Surface Process Model (LSPM) has been improved with respect to the 1. version of 1994. The modifications have involved the parametrizations of the radiation terms and of turbulent heat fluxes. A parametrization of runoff has also been developed, in order to close the hydrologic balance. This 2. version of LSPM has been validated against experimental data gathered at Mottarone (Verbania, Northern Italy) during a field experiment. The results of this validation show that this new version is able to apportionate the energy into sensible and latent heat fluxes. LSPM has also been submitted to a series of sensitivity tests in order to investigate the hydrological part of the model. The physical quantities selected in these sensitivity experiments have been the initial soil moisture content and the rainfall intensity. In each experiment, the model has been forced by using the observations carried out at the synoptic stations of San Pietro Capofiume (Po Valley, Italy). The observed characteristics of soil and vegetation (not involved in the sensitivity tests) have been used as initial and boundary conditions. The results of the simulation show that LSPM can reproduce well the energy, heat and water budgets and their behaviours with varying the selected parameters. A careful analysis of the LSPM output shows also the importance to identify the effective soil type

  19. Dynamic modeling of organophosphate pesticide load in surface water in the northern San Joaquin Valley watershed of California

    Energy Technology Data Exchange (ETDEWEB)

    Luo Yuzhou [Department of Land, Air and Water Resources, University of California, Davis, CA 95616 (United States); Institute of Watershed Science and Environmental Ecology, Wenzhou Medical College, Wenzhou, 325000 (China); Zhang Xuyang [Department of Land, Air and Water Resources, University of California, Davis, CA 95616 (United States); Liu Xingmei [Department of Land, Air and Water Resources, University of California, Davis, CA 95616 (United States); Institute of Soil, Water and Environmental Science, Zhejiang University, Hangzhou 310029 (China); Ficklin, Darren [Department of Land, Air and Water Resources, University of California, Davis, CA 95616 (United States); Zhang Minghua [Department of Land, Air and Water Resources, University of California, Davis, CA 95616 (United States); Institute of Watershed Science and Environmental Ecology, Wenzhou Medical College, Wenzhou, 325000 (China)], E-mail: mhzhang@ucdavis.edu

    2008-12-15

    The hydrology, sediment, and pesticide transport components of the Soil and Water Assessment Tool (SWAT) were evaluated on the northern San Joaquin Valley watershed of California. The Nash-Sutcliffe coefficients for monthly stream flow and sediment load ranged from 0.49 to 0.99 over the watershed during the study period of 1992-2005. The calibrated SWAT model was applied to simulate fate and transport processes of two organophosphate pesticides of diazinon and chlorpyrifos at watershed scale. The model generated satisfactory predictions of dissolved pesticide loads relative to the monitoring data. The model also showed great success in capturing spatial patterns of dissolved diazinon and chlorpyrifos loads according to the soil properties and landscape morphology over the large agricultural watershed. This study indicated that curve number was the major factor influencing the hydrology while pesticide fate and transport were mainly affected by surface runoff and pesticide application and in the study area. - Major factors governing the instream loads of organophosphate pesticides are magnitude and timing of surface runoff and pesticide application.

  20. Dynamic modeling of organophosphate pesticide load in surface water in the northern San Joaquin Valley watershed of California

    International Nuclear Information System (INIS)

    Luo Yuzhou; Zhang Xuyang; Liu Xingmei; Ficklin, Darren; Zhang Minghua

    2008-01-01

    The hydrology, sediment, and pesticide transport components of the Soil and Water Assessment Tool (SWAT) were evaluated on the northern San Joaquin Valley watershed of California. The Nash-Sutcliffe coefficients for monthly stream flow and sediment load ranged from 0.49 to 0.99 over the watershed during the study period of 1992-2005. The calibrated SWAT model was applied to simulate fate and transport processes of two organophosphate pesticides of diazinon and chlorpyrifos at watershed scale. The model generated satisfactory predictions of dissolved pesticide loads relative to the monitoring data. The model also showed great success in capturing spatial patterns of dissolved diazinon and chlorpyrifos loads according to the soil properties and landscape morphology over the large agricultural watershed. This study indicated that curve number was the major factor influencing the hydrology while pesticide fate and transport were mainly affected by surface runoff and pesticide application and in the study area. - Major factors governing the instream loads of organophosphate pesticides are magnitude and timing of surface runoff and pesticide application

  1. Quantitative assessment of the flow pattern in the southern Arava Valley (Israel) by environmental tracers and a mixing cell model

    Science.gov (United States)

    Adar, E. M.; Rosenthal, E.; Issar, A. S.; Batelaan, O.

    1992-08-01

    This paper demonstrates the implementation of a novel mathematical model to quantify subsurface inflows from various sources into the arid alluvial basin of the southern Arava Valley divided between Israel and Jordan. The model is based on spatial distribution of environmental tracers and is aimed for use on basins with complex hydrogeological structure and/or with scarce physical hydrologic information. However, a sufficient qualified number of wells and springs are required to allow water sampling for chemical and isotopic analyses. Environmental tracers are used in a multivariable cluster analysis to define potential sources of recharge, and also to delimit homogeneous mixing compartments within the modeled aquifer. Six mixing cells were identified based on 13 constituents. A quantitative assessment of 11 significant subsurface inflows was obtained. Results revealed that the total recharge into the southern Arava basin is around 12.52 × 10 6m3year-1. The major source of inflow into the alluvial aquifer is from the Nubian sandstone aquifer which comprises 65-75% of the total recharge. Only 19-24% of the recharge, but the most important source of fresh water, originates over the eastern Jordanian mountains and alluvial fans.

  2. Hydrology and model of North Fork Solomon River Valley, Kirwin Dam to Waconda Lake, north-central Kansas

    Science.gov (United States)

    Jorgensen, Donald G.; Stullken, Lloyd E.

    1981-01-01

    The alluvial valley of the North Fork Solomon River is an important agricultural area. Reservoir releases diverted below Kirwin Dam are the principal source of irrigation water. During the 1970'S, severe water shortages occurred in Kirwin Reservoir and other nearby reservoirs as a result of an extended drought. Some evidence indicates that surface-water shortages may have been the result of a change in the rainfall-runoff relationship. Examination of the rainfall-runoff relationship shows no apparent trend from 1951 to 1968, but annual records from 1969 to 1976 indicate that deficient rainfall occurred during 6 of the 8 years. Ground water from the alluvial aquifer underlying the river valley also is used extensively for irrigation. Utilization of ground water for irrigation greatly increased from about 200 acre-feet in 1955 to about 12,300 acre-feet in 1976. Part of the surface water diverted for irrigation has percolated downward into the aquifer raising the ground-water level. Ground-water storage in the aquifer increased from 230,000 acre-feet in 1946 to 275,000 acre-feet in 1976-77. A digital model was used to simulate the steady-state conditions in the aquifer prior to closure of Kirwin Dam. Model results indicated that precipitation was the major source of recharge to the aquifer. The effective recharge, or gain from precipitation minus evapotranspiration, was about 11,700 acre-feet per year. The major element of discharge from the aquifer was leakage to the river. The simulated net leakage (leakage to the river minus leakage from the river) was about 11,500 acre-feet per year. The simulated value is consistent with the estimated gain in base flow of the river within the area modeled. Measurements of seepage used to determine gain and loss to the stream were made twice during 1976. Based on these measurements and on base-flow periods identified from hydrographs, it was estimated that the ground-water discharge to the stream has increased about 4,000 acre

  3. Spectrum recovery method based on sparse representation for segmented multi-Gaussian model

    Science.gov (United States)

    Teng, Yidan; Zhang, Ye; Ti, Chunli; Su, Nan

    2016-09-01

    Hyperspectral images can realize crackajack features discriminability for supplying diagnostic characteristics with high spectral resolution. However, various degradations may generate negative influence on the spectral information, including water absorption, bands-continuous noise. On the other hand, the huge data volume and strong redundancy among spectrums produced intense demand on compressing HSIs in spectral dimension, which also leads to the loss of spectral information. The reconstruction of spectral diagnostic characteristics has irreplaceable significance for the subsequent application of HSIs. This paper introduces a spectrum restoration method for HSIs making use of segmented multi-Gaussian model (SMGM) and sparse representation. A SMGM is established to indicating the unsymmetrical spectral absorption and reflection characteristics, meanwhile, its rationality and sparse property are discussed. With the application of compressed sensing (CS) theory, we implement sparse representation to the SMGM. Then, the degraded and compressed HSIs can be reconstructed utilizing the uninjured or key bands. Finally, we take low rank matrix recovery (LRMR) algorithm for post processing to restore the spatial details. The proposed method was tested on the spectral data captured on the ground with artificial water absorption condition and an AVIRIS-HSI data set. The experimental results in terms of qualitative and quantitative assessments demonstrate that the effectiveness on recovering the spectral information from both degradations and loss compression. The spectral diagnostic characteristics and the spatial geometry feature are well preserved.

  4. Contaminant fate and transport in the Venice Lagoon: results from a multi-segment multimedia model.

    Science.gov (United States)

    Sommerfreund, J K; Gandhi, N; Diamond, M L; Mugnai, C; Frignani, M; Capodaglio, G; Gerino, M; Bellucci, L G; Giuliani, S

    2010-03-01

    Contaminant loadings to the Venice Lagoon peaked from 1950s-1980s and although they have since declined, contaminant concentrations remain elevated in sediment and seafood. In order to identify the relative importance of contaminant sources, inter-media exchange and removal pathways, a modified 10-segment fugacity/aquivalence-based model was developed for octachlorodibenzodioxin/furan (OCDD/F), PCB-180, Pb and Cu in the Venice Lagoon. Results showed that in-place pollution nearby the industrial area, current industrial discharges, and tributary loadings were the main sources of contaminants to the lagoon, with negligible contributions from the atmosphere. The fate of these contaminants was governed by sediment-water exchange with simultaneous advective transport by water circulation. Contaminants circulated amongst the northern and central basins with a small fraction reaching the far southern basin and the Chioggia inlet. As a consequence, we estimated limited contaminant transfer to the Adriatic Sea, trapping the majority of contaminants in the sediment in this "average" circulation scenario which does not account for periodic flooding events. (c) 2009 Elsevier Inc. All rights reserved.

  5. Use of a three-dimensional model for the analysis of the ground-water flow system in Parker Valley, Arizona and California

    Science.gov (United States)

    Tucci, Patrick

    1982-01-01

    A three-dimensional, finite-difference model was used to simulate ground-water flow conditions in Parker Valley. The study evaluated present knowledge and concepts of the ground-water system and the ability of the model to represent the system. Modeling assumptions and generalized physical parameters that were used may have transfer value in the construction and calibration of models of other basins along the lower Colorado River. The aquifer was simulated in two layers to represent the three-dimensional system. Ground-water conditions were simulated for 1940-41, the mid-1960's, and 1980. Overall model results generally compared favorably with available field information. The model results showed that for 1940-41 the Colorado River was a losing stream through out Parker Valley. Infiltration of surface water from the river was the major source of recharge. The dominant mechanism of discharge was evapotranspiration by phreatophytes. Agricultural development between 1941 and the mid-1960 's resulted in significant changes to the ground-water system. Model results for conditions in the mid-1960 's showed that the Colorado River had become a gaining stream in the northern part of the valley as a result of higher water levels. The rise in water levels was caused by infiltration of applied irrigation water. Diminished water-level gradients from the river in the rest of the valley reduced the amount of infiltration of surface water from the river. Models results for conditions in 1980 showed that ground-water level rises of several feet caused further reduction in the amount of surface-water infiltration from the river. (USGS)

  6. Modal Damping Ratio and Optimal Elastic Moduli of Human Body Segments for Anthropometric Vibratory Model of Standing Subjects.

    Science.gov (United States)

    Gupta, Manoj; Gupta, T C

    2017-10-01

    The present study aims to accurately estimate inertial, physical, and dynamic parameters of human body vibratory model consistent with physical structure of the human body that also replicates its dynamic response. A 13 degree-of-freedom (DOF) lumped parameter model for standing person subjected to support excitation is established. Model parameters are determined from anthropometric measurements, uniform mass density, elastic modulus of individual body segments, and modal damping ratios. Elastic moduli of ellipsoidal body segments are initially estimated by comparing stiffness of spring elements, calculated from a detailed scheme, and values available in literature for same. These values are further optimized by minimizing difference between theoretically calculated platform-to-head transmissibility ratio (TR) and experimental measurements. Modal damping ratios are estimated from experimental transmissibility response using two dominant peaks in the frequency range of 0-25 Hz. From comparison between dynamic response determined form modal analysis and experimental results, a set of elastic moduli for different segments of human body and a novel scheme to determine modal damping ratios from TR plots, are established. Acceptable match between transmissibility values calculated from the vibratory model and experimental measurements for 50th percentile U.S. male, except at very low frequencies, establishes the human body model developed. Also, reasonable agreement obtained between theoretical response curve and experimental response envelop for average Indian male, affirms the technique used for constructing vibratory model of a standing person. Present work attempts to develop effective technique for constructing subject specific damped vibratory model based on its physical measurements.

  7. Simplified segmented human models for whole body and localised SAR evaluation of 20 MHz to 6 GHz electromagnetic field exposures

    International Nuclear Information System (INIS)

    Wu, T.; Shao, Q.; Yang, L.

    2013-01-01

    The digital human model is a key element in evaluating the electromagnetic field (EMF) exposure. This paper proposes the application of simplified segmented human models for EMF exposure compliance evaluation with the whole body and the localised limits. The method is based on the fact that most of the EMF power absorption is concentrated in several major tissues. Two kinds of human models were simply (the proposed method) and precisely segmented from two sets of whole body magnetic resonance imaging (MRI) scanned images. The whole body average-specific absorption rate (WBA-SAR) and the peak localised SAR averaging over 10 g tissues for the two kinds of models are calculated for various exposure configurations. The results confirmed the efficiency and the validity of the proposed method. The application as evaluating the MRI radiofrequency EMF exposure is also discussed in the paper. (authors)

  8. Ecological niche modeling and land cover risk areas for rift valley fever vector, culex tritaeniorhynchus giles in Jazan, Saudi Arabia.

    Science.gov (United States)

    Sallam, Mohamed F; Al Ahmed, Azzam M; Abdel-Dayem, Mahmoud S; Abdullah, Mohamed A R

    2013-01-01

    The mosquito, Culex tritaeniorhynchus Giles is a prevalent and confirmed Rift Valley Fever virus (RVFV) vector. This vector, in association with Aedimorphus arabiensis (Patton), was responsible for causing the outbreak of 2000 in Jazan Province, Saudi Arabia. Larval occurrence records and a total of 19 bioclimatic and three topographic layers imported from Worldclim Database were used to predict the larval suitable breeding habitats for this vector in Jazan Province using ArcGIS ver.10 and MaxEnt modeling program. Also, a supervised land cover classification from SPOT5 imagery was developed to assess the land cover distribution within the suitable predicted habitats. Eleven bioclimatic and slope attributes were found to be the significant predictors for this larval suitable breeding habitat. Precipitation and temperature were strong predictors of mosquito distribution. Among six land cover classes, the linear regression model (LM) indicated wet muddy substrate is significantly associated with high-very high suitable predicted habitats (R(2) = 73.7%, Presearchers.

  9. Ground-water flow and transport modeling of the NRC-licensed waste disposal facility, West Valley, New York

    International Nuclear Information System (INIS)

    Kool, J.B.; Wu, Y.S.

    1991-10-01

    This report describes a simulation study of groundwater flow and radionuclide transport from disposal at the NRC licensed waste disposal facility in West Valley, New York. A transient, precipitation driven, flow model of the near-surface fractured till layer and underlying unweathered till was developed and calibrated against observed inflow data into a recently constructed interceptor trench for the period March--May 1990. The results suggest that lateral flow through the upper, fractured till layer may be more significant than indicated by previous, steady state flow modeling studies. A conclusive assessment of the actual magnitude of lateral flow through the fractured till could however not be made. A primary factor contributing to this uncertainty is the unknown contribution of vertical infiltration through the interceptor trench cap to the total trench inflow. The second part of the investigation involved simulation of the migration of Sr-90, Cs-137 and Pu-239 from the one of the fuel hull disposal pits. A first-order radionuclide leach rate with rate coefficient of 10 -6 /day was assumed to describe radionuclide release into the disposal pit. The simulations indicated that for wastes buried below the fractured till zone, no significant migration would occur. However, under the assumed conditions, significant lateral migration could occur for radionuclides present in the upper, fractured till zone. 23 refs., 68 figs., 12 tabs

  10. Evaluating model structure adequacy: The case of the Maggia Valley groundwater system, southern Switzerland

    Science.gov (United States)

    Hill, Mary C.; L. Foglia,; S. W. Mehl,; P. Burlando,

    2013-01-01

    Model adequacy is evaluated with alternative models rated using model selection criteria (AICc, BIC, and KIC) and three other statistics. Model selection criteria are tested with cross-validation experiments and insights for using alternative models to evaluate model structural adequacy are provided. The study is conducted using the computer codes UCODE_2005 and MMA (MultiModel Analysis). One recharge alternative is simulated using the TOPKAPI hydrological model. The predictions evaluated include eight heads and three flows located where ecological consequences and model precision are of concern. Cross-validation is used to obtain measures of prediction accuracy. Sixty-four models were designed deterministically and differ in representation of river, recharge, bedrock topography, and hydraulic conductivity. Results include: (1) What may seem like inconsequential choices in model construction may be important to predictions. Analysis of predictions from alternative models is advised. (2) None of the model selection criteria consistently identified models with more accurate predictions. This is a disturbing result that suggests to reconsider the utility of model selection criteria, and/or the cross-validation measures used in this work to measure model accuracy. (3) KIC displayed poor performance for the present regression problems; theoretical considerations suggest that difficulties are associated with wide variations in the sensitivity term of KIC resulting from the models being nonlinear and the problems being ill-posed due to parameter correlations and insensitivity. The other criteria performed somewhat better, and similarly to each other. (4) Quantities with high leverage are more difficult to predict. The results are expected to be generally applicable to models of environmental systems.

  11. Measurements and Modeling of Turbulent Fluxes during Persistent Cold Air Pool Events in Salt Lake Valley, Utah

    Science.gov (United States)

    Ivey, C. E.; Sun, X.; Holmes, H.

    2017-12-01

    Land surface processes are important in meteorology and climate research since they control the partitioning of surface energy and water exchange at the earth's surface. The surface layer is coupled to the planetary boundary layer (PBL) by surface fluxes, which serve as sinks or sources of energy, moisture, momentum, and atmospheric pollutants. Quantifying the surface heat and momentum fluxes at the land-atmosphere interface, especially for different surface land cover types, is important because they can further influence the atmospheric dynamics, vertical mixing, and transport processes that impact local, regional, and global climate. A cold air pool (CAP) forms when a topographic depression (i.e., valley) fills with cold air, where the air in the stagnant layer is colder than the air aloft. Insufficient surface heating, which is not able to sufficiently erode the temperature inversion that forms during the nighttime stable boundary layer, can lead to the formation of persistent CAPs during wintertime. These persistent CAPs can last for days, or even weeks, and are associated with increased air pollution concentrations. Thus, realistic simulations of the land-atmosphere exchange are meaningful to achieve improved predictions of the accumulation, transport, and dispersion of air pollution concentrations. The focus of this presentation is on observations and modeling results using turbulence data collected in Salt Lake Valley, Utah during the 2010-2011 wintertime Persistent Cold Air Pool Study (PCAPS). Turbulent fluxes and the surface energy balance over seven land use types are quantified. The urban site has an energy balance ratio (EBR) larger than one (1.276). Negative Bowen ratio (-0.070) is found at the cropland site. In addition to turbulence observations, half-hourly WRF simulated net radiation, latent heat, sensible heat, ground heat fluxes during one persistent CAP event are evaluated using the PCAPS observations. The results show that sensible and latent

  12. A participatory modelling approach to define farm-scale effects of reclaimed wastewater irrigation in the Lockyer Valley, Australia

    NARCIS (Netherlands)

    Opstal, van J.D.; Huibers, F.P.; Cresswell, R.G.

    2012-01-01

    The Lockyer Valley is an important agricultural area experiencing water insecurity, which causes a decrease in agricultural production. Regional authorities are initiating a wastewater reclamation project conveying treated municipal wastewater to water users, including potentially the Lockyer

  13. Systematic Mapping and Statistical Analyses of Valley Landform and Vegetation Asymmetries Across Hydroclimatic Gradients

    Science.gov (United States)

    Poulos, M. J.; Pierce, J. L.; McNamara, J. P.; Flores, A. N.; Benner, S. G.

    2015-12-01

    Terrain aspect alters the spatial distribution of insolation across topography, driving eco-pedo-hydro-geomorphic feedbacks that can alter landform evolution and result in valley asymmetries for a suite of land surface characteristics (e.g. slope length and steepness, vegetation, soil properties, and drainage development). Asymmetric valleys serve as natural laboratories for studying how landscapes respond to climate perturbation. In the semi-arid montane granodioritic terrain of the Idaho batholith, Northern Rocky Mountains, USA, prior works indicate that reduced insolation on northern (pole-facing) aspects prolongs snow pack persistence, and is associated with thicker, finer-grained soils, that retain more water, prolong the growing season, support coniferous forest rather than sagebrush steppe ecosystems, stabilize slopes at steeper angles, and produce sparser drainage networks. We hypothesize that the primary drivers of valley asymmetry development are changes in the pedon-scale water-balance that coalesce to alter catchment-scale runoff and drainage development, and ultimately cause the divide between north and south-facing land surfaces to migrate northward. We explore this conceptual framework by coupling land surface analyses with statistical modeling to assess relationships and the relative importance of land surface characteristics. Throughout the Idaho batholith, we systematically mapped and tabulated various statistical measures of landforms, land cover, and hydroclimate within discrete valley segments (n=~10,000). We developed a random forest based statistical model to predict valley slope asymmetry based upon numerous measures (n>300) of landscape asymmetries. Preliminary results suggest that drainages are tightly coupled with hillslopes throughout the region, with drainage-network slope being one of the strongest predictors of land-surface-averaged slope asymmetry. When slope-related statistics are excluded, due to possible autocorrelation, valley

  14. Simulation modelling of population dynamics of mosquito vectors for rift valley Fever virus in a disease epidemic setting.

    Directory of Open Access Journals (Sweden)

    Clement N Mweya

    Full Text Available Rift Valley Fever (RVF is weather dependent arboviral infection of livestock and humans. Population dynamics of mosquito vectors is associated with disease epidemics. In our study, we use daily temperature and rainfall as model inputs to simulate dynamics of mosquito vectors population in relation to disease epidemics.Time-varying distributed delays (TVDD and multi-way functional response equations were implemented to simulate mosquito vectors and hosts developmental stages and to establish interactions between stages and phases of mosquito vectors in relation to vertebrate hosts for infection introduction in compartmental phases. An open-source modelling platforms, Universal Simulator and Qt integrated development environment were used to develop models in C++ programming language. Developed models include source codes for mosquito fecundity, host fecundity, water level, mosquito infection, host infection, interactions, and egg time. Extensible Markup Language (XML files were used as recipes to integrate source codes in Qt creator with Universal Simulator plug-in. We observed that Floodwater Aedines and Culicine population continued to fluctuate with temperature and water level over simulation period while controlled by availability of host for blood feeding. Infection in the system was introduced by floodwater Aedines. Culicines pick infection from infected host once to amplify disease epidemic. Simulated mosquito population show sudden unusual increase between December 1997 and January 1998 a similar period when RVF outbreak occurred in Ngorongoro district.Findings presented here provide new opportunities for weather-driven RVF epidemic simulation modelling. This is an ideal approach for understanding disease transmission dynamics towards epidemics prediction, prevention and control. This approach can be used as an alternative source for generation of calibrated RVF epidemics data in different settings.

  15. Simulation modelling of population dynamics of mosquito vectors for rift valley Fever virus in a disease epidemic setting.

    Science.gov (United States)

    Mweya, Clement N; Holst, Niels; Mboera, Leonard E G; Kimera, Sharadhuli I

    2014-01-01

    Rift Valley Fever (RVF) is weather dependent arboviral infection of livestock and humans. Population dynamics of mosquito vectors is associated with disease epidemics. In our study, we use daily temperature and rainfall as model inputs to simulate dynamics of mosquito vectors population in relation to disease epidemics. Time-varying distributed delays (TVDD) and multi-way functional response equations were implemented to simulate mosquito vectors and hosts developmental stages and to establish interactions between stages and phases of mosquito vectors in relation to vertebrate hosts for infection introduction in compartmental phases. An open-source modelling platforms, Universal Simulator and Qt integrated development environment were used to develop models in C++ programming language. Developed models include source codes for mosquito fecundity, host fecundity, water level, mosquito infection, host infection, interactions, and egg time. Extensible Markup Language (XML) files were used as recipes to integrate source codes in Qt creator with Universal Simulator plug-in. We observed that Floodwater Aedines and Culicine population continued to fluctuate with temperature and water level over simulation period while controlled by availability of host for blood feeding. Infection in the system was introduced by floodwater Aedines. Culicines pick infection from infected host once to amplify disease epidemic. Simulated mosquito population show sudden unusual increase between December 1997 and January 1998 a similar period when RVF outbreak occurred in Ngorongoro district. Findings presented here provide new opportunities for weather-driven RVF epidemic simulation modelling. This is an ideal approach for understanding disease transmission dynamics towards epidemics prediction, prevention and control. This approach can be used as an alternative source for generation of calibrated RVF epidemics data in different settings.

  16. Statistical modeling of the abundance of vectors of West African Rift Valley fever in Barkédji, Senegal.

    Directory of Open Access Journals (Sweden)

    Cheikh Talla

    Full Text Available Rift Valley fever is an emerging mosquito-borne disease that represents a threat to human and animal health. The exophilic and exophagic behavior of the two main vector in West Africa (Aedes vexans and Culex poicilipes, adverse events post-vaccination, and lack of treatment, render ineffective the disease control. Therefore it is essential to develop an information system that facilitates decision-making and the implementation of adaptation strategies. In East Africa, RVF outbreaks are linked with abnormally high rainfall, and can be predicted up to 5 months in advance by modeling approaches using climatic and environmental parameters. However, the application of these models in West Africa remains unsatisfactory due to a lack of data for animal and human cases and differences in the dynamics of the disease emergence and the vector species involved in transmission. Models have been proposed for West Africa but they were restricted to rainfall impact analysis without a spatial dimension. In this study, we developed a mixed Bayesian statistical model to evaluate the effects of climatic and ecological determinants on the spatiotemporal dynamics of the two main vectors. Adult mosquito abundance data were generated from July to December every fortnight in 2005-2006 at 79 sites, including temporary ponds, bare soils, shrubby savannah, wooded savannah, steppes, and villages in the Barkédji area. The results demonstrate the importance of environmental factors and weather conditions for predicting mosquito abundance. The rainfall and minimum temperature were positively correlated with the abundance of Cx. poicilipes, whereas the maximum temperature had negative effects. The rainfall was negatively correlated with the abundance of Ae. vexans. After combining land cover classes, weather conditions, and vector abundance, our model was used to predict the areas and periods with the highest risks of vector pressure. This information could support decision

  17. Spatial Heterogeneity of Habitat Suitability for Rift Valley Fever Occurrence in Tanzania: An Ecological Niche Modelling Approach

    Science.gov (United States)

    Sindato, Calvin; Stevens, Kim B.; Karimuribo, Esron D.; Mboera, Leonard E. G.; Paweska, Janusz T.; Pfeiffer, Dirk U.

    2016-01-01

    Background Despite the long history of Rift Valley fever (RVF) in Tanzania, extent of its suitable habitat in the country remains unclear. In this study we investigated potential effects of temperature, precipitation, elevation, soil type, livestock density, rainfall pattern, proximity to wild animals, protected areas and forest on the habitat suitability for RVF occurrence in Tanzania. Materials and Methods Presence-only records of 193 RVF outbreak locations from 1930 to 2007 together with potential predictor variables were used to model and map the suitable habitats for RVF occurrence using ecological niche modelling. Ground-truthing of the model outputs was conducted by comparing the levels of RVF virus specific antibodies in cattle, sheep and goats sampled from locations in Tanzania that presented different predicted habitat suitability values. Principal Findings Habitat suitability values for RVF occurrence were higher in the northern and central-eastern regions of Tanzania than the rest of the regions in the country. Soil type and precipitation of the wettest quarter contributed equally to habitat suitability (32.4% each), followed by livestock density (25.9%) and rainfall pattern (9.3%). Ground-truthing of model outputs revealed that the odds of an animal being seropositive for RVFV when sampled from areas predicted to be most suitable for RVF occurrence were twice the odds of an animal sampled from areas least suitable for RVF occurrence (95% CI: 1.43, 2.76, p < 0.001). Conclusion/Significance The regions in the northern and central-eastern Tanzania were more suitable for RVF occurrence than the rest of the regions in the country. The modelled suitable habitat is characterised by impermeable soils, moderate precipitation in the wettest quarter, high livestock density and a bimodal rainfall pattern. The findings of this study should provide guidance for the design of appropriate RVF surveillance, prevention and control strategies which target areas with

  18. The spherical segmented Langmuir probe in a flowing thermal plasma: numerical model of the current collection

    Directory of Open Access Journals (Sweden)

    E. Séran

    2005-07-01

    Full Text Available The segmented Langmuir probe (SLP has been recently proposed by one of the authors (Lebreton, 2002 as an instrument to derive the bulk velocity of terrestrial or planetary plasmas, in addition to the electron density and temperature that are routinely measured by Langmuir probes. It is part of the scientific payload on the DEMETER micro-satellite developed by CNES. The basic concept of this probe is to measure the current distribution over the surface using independent collectors under the form of small spherical caps and to use the angular anisotropy of these currents to obtain the plasma bulk velocity in the probe reference frame. In order to determine the SLP capabilities, we have developed a numerical PIC (Particles In Cell model which provides a tool to compute the distribution of the current collected by a spherical probe. Our model is based on the simultaneous determination of the charge densities in the probe sheath and on the probe surface, from which the potential distribution in the sheath region can be obtained. This method is well adapted to the SLP problem and has some advantages since it provides a natural control of the charge neutrality inside the simulation box, allows independent mesh sizes in the sheath and on the probe surface, and can be applied to complex surfaces. We present in this paper initial results obtained for plasma conditions corresponding to a Debye length equal to the probe radius. These plasma conditions are observed along the Demeter orbit. The model results are found to be in very good agreement with those published by Laframboise (1966 for a spherical probe in a thermal non-flowing plasma. This demonstrates the adequacy of the computation method and of the adjustable numerical parameters (size of the numerical box and mesh, time step, number of macro-particles, etc. for the considered plasma-probe configuration. We also present the results obtained in the case of plasma flowing with mesothermal conditions

  19. The spherical segmented Langmuir probe in a flowing thermal plasma: numerical model of the current collection

    Directory of Open Access Journals (Sweden)

    E. Séran

    2005-07-01

    Full Text Available The segmented Langmuir probe (SLP has been recently proposed by one of the authors (Lebreton, 2002 as an instrument to derive the bulk velocity of terrestrial or planetary plasmas, in addition to the electron density and temperature that are routinely measured by Langmuir probes. It is part of the scientific payload on the DEMETER micro-satellite developed by CNES. The basic concept of this probe is to measure the current distribution over the surface using independent collectors under the form of small spherical caps and to use the angular anisotropy of these currents to obtain the plasma bulk velocity in the probe reference frame. In order to determine the SLP capabilities, we have developed a numerical PIC (Particles In Cell model which provides a tool to compute the distribution of the current collected by a spherical probe. Our model is based on the simultaneous determination of the charge densities in the probe sheath and on the probe surface, from which the potential distribution in the sheath region can be obtained. This method is well adapted to the SLP problem and has some advantages since it provides a natural control of the charge neutrality inside the simulation box, allows independent mesh sizes in the sheath and on the probe surface, and can be applied to complex surfaces. We present in this paper initial results obtained for plasma conditions corresponding to a Debye length equal to the probe radius. These plasma conditions are observed along the Demeter orbit. The model results are found to be in very good agreement with those published by Laframboise (1966 for a spherical probe in a thermal non-flowing plasma. This demonstrates the adequacy of the computation method and of the adjustable numerical parameters (size of the numerical box and mesh, time step, number of macro-particles, etc. for the considered plasma-probe configuration. We also present the results obtained in the case of plasma flowing with mesothermal conditions

  20. Variability of indicator values for ozone production sensitivity: a model study in Switzerland and San Joaquin Valley (California)

    International Nuclear Information System (INIS)

    Andreani-Aksoyoglu, S.; Keller, J.; Prevot, A.S.H.; Chenghsuan Lu; Chang, J.S.

    2001-01-01

    The threshold values of indicator species and ratios delineating the transition between NO x and VOC sensitivity of ozone formation are assumed to be universal by various investigators. However, our previous studies suggested that threshold values might vary according to the locations and conditions. In this study, threshold values derived from various model simulations at two different locations (the area of Switzerland by UAM Model and San Joaquin Valley of Central California by SAQM Model) are examined using a new approach for defining NO x and VOC sensitive regimes. Possible definitions for the distinction of NO x and VOC sensitive ozone production regimes are given. The dependence of the threshold values for indicators and indicator ratios such as NO y , O 3 /NO z , HCHO/NO y , and H 2 O 2 /HNO 3 on the definition of NO x and VOC sensitivity is discussed. Then the variations of threshold values under low emission conditions and in two different days are examined in both areas to check whether the models respond consistently to changes in environmental conditions. In both cases, threshold values are shifted similarly when emissions are reduced. Changes in the wind fields and aging of the photochemical oxidants seem to cause the day-to-day variation of the threshold values. O 3 /NO z and HCHO/NO y indicators are predicted to be unsatisfactory to separate the NO x and VOC sensitive regimes. Although NO y and H 2 O 2 /HNO 3 provide a good separation of the two regimes, threshold values are affected by changes in the environmental conditions studied in this work. (author)

  1. Cowichan Valley energy mapping and modelling. Report 3 - Analysis of potentially applicable distributed energy opportunities. Final report. [Vancouver Island, Canada

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2012-06-15

    The driving force behind the Integrated Energy Mapping and Analysis project was the identification and analysis of a suite of pathways that the Cowichan Valley Regional District (CVRD) can utilise to increase its energy resilience, as well as reduce energy consumption and GHG emissions, with a primary focus on the residential sector. Mapping and analysis undertaken will support provincial energy and GHG reduction targets, and the suite of pathways outlined will address a CVRD internal target that calls for 75% of the region's energy within the residential sector to come from locally sourced renewables by 2050. The target has been developed as a mechanism to meet resilience and climate action target. The maps and findings produced are to be integrated as part of a regional policy framework currently under development. The third task built upon the findings of the previous two and undertook an analysis of potentially applicable distributed energy opportunities. These opportunities were analysed given a number of different parameters, which were decided upon in consultation with the CVRD. The primary output of this task was a series of cost figures for the various technologies, thus allowing comparison on a cents/kWh basis. All of the cost figures from this task have been entered into a tailor made Excel model. This 'technology cost' model is linked to the Excel scenario model utilised in task 4. As a result, as technology costs change, they can be updated accordingly and be reflected in the scenarios. Please note, that the technologies considered at present in the technology cost model are well-proven technologies, available in the market today, even though the output is being used for an analysis of development until 2050. Task 3 results are detailed in this report and both presents an initial screening for various local renewable energies, and provides the CVRD with the means of evaluating the costs and benefits of local energy productions versus

  2. Color Image Segmentation Based on Different Color Space Models Using Automatic GrabCut

    Directory of Open Access Journals (Sweden)

    Dina Khattab

    2014-01-01

    Full Text Available This paper presents a comparative study using different color spaces to evaluate the performance of color image segmentation using the automatic GrabCut technique. GrabCut is considered as one of the semiautomatic image segmentation techniques, since it requires user interaction for the initialization of the segmentation process. The automation of the GrabCut technique is proposed as a modification of the original semiautomatic one in order to eliminate the user interaction. The automatic GrabCut utilizes the unsupervised Orchard and Bouman clustering technique for the initialization phase. Comparisons with the original GrabCut show the efficiency of the proposed automatic technique in terms of segmentation, quality, and accuracy. As no explicit color space is recommended for every segmentation problem, automatic GrabCut is applied with RGB, HSV, CMY, XYZ, and YUV color spaces. The comparative study and experimental results using different color images show that RGB color space is the best color space representation for the set of the images used.

  3. A hybrid machine learning model to estimate nitrate contamination of production zone groundwater in the Central Valley, California

    Science.gov (United States)

    Ransom, K.; Nolan, B. T.; Faunt, C. C.; Bell, A.; Gronberg, J.; Traum, J.; Wheeler, D. C.; Rosecrans, C.; Belitz, K.; Eberts, S.; Harter, T.

    2016-12-01

    A hybrid, non-linear, machine learning statistical model was developed within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500 m below ground surface in the Central Valley, California. A database of 213 predictor variables representing well characteristics, historical and current field and county scale nitrogen mass balance, historical and current landuse, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6,000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The machine learning method, gradient boosting machine (GBM) was used to screen predictor variables and rank them in order of importance in relation to the groundwater nitrate measurements. The top five most important predictor variables included oxidation/reduction characteristics, historical field scale nitrogen mass balance, climate, and depth to 60 year old water. Twenty-two variables were selected for the final model and final model errors for log-transformed hold-out data were R squared of 0.45 and root mean square error (RMSE) of 1.124. Modeled mean groundwater age was tested separately for error improvement in the model and when included decreased model RMSE by 0.5% compared to the same model without age and by 0.20% compared to the model with all 213 variables. 1D and 2D partial plots were examined to determine how variables behave individually and interact in the model. Some variables behaved as expected: log nitrate decreased with increasing probability of anoxic conditions and depth to 60 year old water, generally decreased with increasing natural landuse surrounding wells and increasing mean groundwater age, generally increased with increased minimum depth to high water table and with increased base flow index value. Other variables exhibited much more erratic or noisy behavior in

  4. Exact analytical modeling of magnetic vector potential in surface inset permanent magnet DC machines considering magnet segmentation

    Science.gov (United States)

    Jabbari, Ali

    2018-01-01

    Surface inset permanent magnet DC machine can be used as an alternative in automation systems due to their high efficiency and robustness. Magnet segmentation is a common technique in order to mitigate pulsating torque components in permanent magnet machines. An accurate computation of air-gap magnetic field distribution is necessary in order to calculate machine performance. An exact analytical method for magnetic vector potential calculation in surface inset permanent magnet machines considering magnet segmentation has been proposed in this paper. The analytical method is based on the resolution of Laplace and Poisson equations as well as Maxwell equation in polar coordinate by using sub-domain method. One of the main contributions of the paper is to derive an expression for the magnetic vector potential in the segmented PM region by using hyperbolic functions. The developed method is applied on the performance computation of two prototype surface inset magnet segmented motors with open circuit and on load conditions. The results of these models are validated through FEM method.

  5. Automatic optimal filament segmentation with sub-pixel accuracy using generalized linear models and B-spline level-sets.

    Science.gov (United States)

    Xiao, Xun; Geyer, Veikko F; Bowne-Anderson, Hugo; Howard, Jonathon; Sbalzarini, Ivo F

    2016-08-01

    Biological filaments, such as actin filaments, microtubules, and cilia, are often imaged using different light-microscopy techniques. Reconstructing the filament curve from the acquired images constitutes the filament segmentation problem. Since filaments have lower dimensionality than the image itself, there is an inherent trade-off between tracing the filament with sub-pixel accuracy and avoiding noise artifacts. Here, we present a globally optimal filament segmentation method based on B-spline vector level-sets and a generalized linear model for the pixel intensity statistics. We show that the resulting optimization problem is convex and can hence be solved with global optimality. We introduce a simple and efficient algorithm to compute such optimal filament segmentations, and provide an open-source implementation as an ImageJ/Fiji plugin. We further derive an information-theoretic lower bound on the filament segmentation error, quantifying how well an algorithm could possibly do given the information in the image. We show that our algorithm asymptotically reaches this bound in the spline coefficients. We validate our method in comprehensive benchmarks, compare with other methods, and show applications from fluorescence, phase-contrast, and dark-field microscopy. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  6. Distinguishing between Rural and Urban Road Segment Traffic Safety Based on Zero-Inflated Negative Binomial Regression Models

    Directory of Open Access Journals (Sweden)

    Xuedong Yan

    2012-01-01

    Full Text Available In this study, the traffic crash rate, total crash frequency, and injury and fatal crash frequency were taken into consideration for distinguishing between rural and urban road segment safety. The GIS-based crash data during four and half years in Pikes Peak Area, US were applied for the analyses. The comparative statistical results show that the crash rates in rural segments are consistently lower than urban segments. Further, the regression results based on Zero-Inflated Negative Binomial (ZINB regression models indicate that the urban areas have a higher crash risk in terms of both total crash frequency and injury and fatal crash frequency, compared to rural areas. Additionally, it is found that crash frequencies increase as traffic volume and segment length increase, though the higher traffic volume lower the likelihood of severe crash occurrence; compared to 2-lane roads, the 4-lane roads have lower crash frequencies but have a higher probability of severe crash occurrence; and better road facilities with higher free flow speed can benefit from high standard design feature thus resulting in a lower total crash frequency, but they cannot mitigate the severe crash risk.

  7. Myocardial segmentation based on coronary anatomy using coronary computed tomography angiography: Development and validation in a pig model

    Energy Technology Data Exchange (ETDEWEB)

    Chung, Mi Sun [Chung-Ang University College of Medicine, Department of Radiology, Chung-Ang University Hospital, Seoul (Korea, Republic of); Yang, Dong Hyun; Seo, Joon Beom; Kang, Joon-Won; Lim, Tae-Hwan [Asan Medical Center, University of Ulsan College of Medicine, Department of Radiology and Research Institute of Radiology, Seoul (Korea, Republic of); Kim, Young-Hak; Kang, Soo-Jin; Jung, Joonho [Asan Medical Center, University of Ulsan College of Medicine, Heart Institute, Seoul (Korea, Republic of); Kim, Namkug [Asan Medical Center, University of Ulsan College of Medicine, Department of Convergence Medicine, Seoul (Korea, Republic of); Heo, Seung-Ho [Asan Medical Center, University of Ulsan College of Medicine, Asan institute for Life Science, Seoul (Korea, Republic of); Baek, Seunghee [Asan Medical Center, University of Ulsan College of Medicine, Department of Clinical Epidemiology and Biostatistics, Seoul (Korea, Republic of); Choi, Byoung Wook [Yonsei University, Department of Diagnostic Radiology, College of Medicine, Seoul (Korea, Republic of)

    2017-10-15

    To validate a method for performing myocardial segmentation based on coronary anatomy using coronary CT angiography (CCTA). Coronary artery-based myocardial segmentation (CAMS) was developed for use with CCTA. To validate and compare this method with the conventional American Heart Association (AHA) classification, a single coronary occlusion model was prepared and validated using six pigs. The unstained occluded coronary territories of the specimens and corresponding arterial territories from CAMS and AHA segmentations were compared using slice-by-slice matching and 100 virtual myocardial columns. CAMS more precisely predicted ischaemic area than the AHA method, as indicated by 95% versus 76% (p < 0.001) of the percentage of matched columns (defined as percentage of matched columns of segmentation method divided by number of unstained columns in the specimen). According to the subgroup analyses, CAMS demonstrated a higher percentage of matched columns than the AHA method in the left anterior descending artery (100% vs. 77%; p < 0.001) and mid- (99% vs. 83%; p = 0.046) and apical-level territories of the left ventricle (90% vs. 52%; p = 0.011). CAMS is a feasible method for identifying the corresponding myocardial territories of the coronary arteries using CCTA. (orig.)

  8. Modelling the Effects of Sea-level, Climate Change, Geology, and Tectonism on the Morphology of the Amazon River Valley and its Floodplain

    Science.gov (United States)

    Aalto, R. E.; Cremon, E.; Dunne, T.

    2017-12-01

    How continental-scale rivers respond to climate, geology, and sea level change is not well represented in morphodynamic models. Large rivers respond to influences less apparent in the form and deposits of smaller streams, as the huge scales require long time periods for changes in form and behavior. Tectonic deformation and excavation of resistant deposits can affect low gradient continental-scale rivers, thereby changing flow pathways, channel slope and sinuosity, along-stream patterns of sediment transport capacity, channel patterns, floodplain construction, and valley topography. Nowhere are such scales of morphodynamic response grander than the Amazon River, as described in papers by L.A.K. Mertes. Field-based understanding has improved over the intervening decades, but mechanistic models are needed to simulate and synthesize key morphodynamic components relevant to the construction of large river valleys, with a focus on the Amazon. The Landscape-Linked Environmental Model (LLEM) utilizes novel massively parallel computer architectures to simulate multiple-direction flow, sediment transport, deposition, and incision for exceptionally large (30-80 million nodes per compute unit) lowland dispersal systems. LLEM represents key fluvial processes such as bed and bar deposition, lateral and vertical erosion/incision, levee and floodplain construction, floodplain hydrology, `badlands dissection' of weak sedimentary deposits during falling sea level, tectonic and glacial-isostatic deformation, and provides a 3D record of created stratigraphy and underlying bedrock. We used LLEM to simulate the development of the main valley of the Amazon over the last million years, exploring the propagation of incision waves and system dissection during glacial lowstands, followed by rapid valley filling and extreme lateral mobility of channels during interglacials. We present metrics, videos, and 3D fly-throughs characterizing how system development responds to key assumptions

  9. Water quality modeling of the Medellin river in the Aburrá Valley

    OpenAIRE

    Giraldo-B., Lina Claudia; Palacio, Carlos Alberto; Molina, Rubén; Agudelo, Rubén Alberto

    2015-01-01

    Water quality modeling intends to represent a water body in order to assess their status and project the effects of different measures taken for their protection. This paper presents the results obtained from the Qual2kw model implementation in the first 50 kilometers of the Aburrá-Medellín River, in their most critical conditions of water quality, which correspond to low flow rates. After the model calibration, three recovery scenarios (short-term, medium-term and long-term) were evaluated. ...

  10. Geochemical tracing and hydrogeochemical modelling of water-rock interactions during salinization of alluvial groundwater (Upper Rhine Valley, France)

    Energy Technology Data Exchange (ETDEWEB)

    Lucas, Y., E-mail: yann.lucas@eost.u-strasbg.fr [Universite de Strasbourg et CNRS, Laboratoire d' Hydrologie et de Geochimie de Strasbourg, Ecole et Observatoire des Sciences de la Terre, 1, rue Blessig, 67084 Strasbourg Cedex (France); Schmitt, A.D., E-mail: anne-desiree.schmitt@univ-fcomte.fr [Universite de Strasbourg et CNRS, Laboratoire d' Hydrologie et de Geochimie de Strasbourg, Ecole et Observatoire des Sciences de la Terre, 1, rue Blessig, 67084 Strasbourg Cedex (France)] [Universite de Franche-Comte et CNRS-UMR 6249, Chrono-Environnement, 16, Route de Gray, 25030 Besancon Cedex (France); Chabaux, F., E-mail: francois.chabaux@eost.u-strasbg.fr [Universite de Strasbourg et CNRS, Laboratoire d' Hydrologie et de Geochimie de Strasbourg, Ecole et Observatoire des Sciences de la Terre, 1, rue Blessig, 67084 Strasbourg Cedex (France); Clement, A.; Fritz, B. [Universite de Strasbourg et CNRS, Laboratoire d' Hydrologie et de Geochimie de Strasbourg, Ecole et Observatoire des Sciences de la Terre, 1, rue Blessig, 67084 Strasbourg Cedex (France); Elsass, Ph. [BRGM, GEODERIS, 1, rue Claude Chappe, 57070 Metz (France); Durand, S. [Universite de Strasbourg et CNRS, Laboratoire d' Hydrologie et de Geochimie de Strasbourg, Ecole et Observatoire des Sciences de la Terre, 1, rue Blessig, 67084 Strasbourg Cedex (France)

    2010-11-15

    Research highlights: {yields} Major and trace elements along with strontium and uranium isotopic ratios show that groundwater geochemical characteristics along the saline plumes cannot reflect a conservative mixing. {yields} A coupled hydrogeochemical model demonstrates that cationic exchange between alkalis from polluted waters and alkaline-earth elements from montmorillonite present in the host rock of the aquifer is the primary process. {yields} The model requires only a small amount of montmorillonite. {yields} It is necessary to consider the pollution history to explain the important chloride, sodium and calcium concentration modifications. {yields} The model shows that the rapidity of the cationic exchange reactions insures a reversibility of the cation fixation on clays in the aquifer. - Abstract: In the southern Upper Rhine Valley, groundwater has undergone intensive saline pollution caused by the infiltration of mining brines, a consequence of potash extraction carried out during the 20th century. Major and trace elements along with Sr and U isotopic ratios show that groundwater geochemical characteristics along the saline plumes cannot reflect conservative mixing between saline waters resulting from the dissolution of waste heaps and one or more unpolluted end-members. The results imply the occurrence of interactions between host rocks and polluted waters, and they suggest that cationic exchange mechanisms are the primary controlling process. A coupled hydrogeochemical model has been developed with the numerical code KIRMAT, which demonstrates that cationic exchange between alkalis from polluted waters and alkaline-earth elements from montmorillonite present in the host rock of the aquifer is the primary process controlling the geochemical evolution of the groundwater. The model requires only a small amount of montmorillonite (between 0.75% and 2.25%), which is in agreement with the observed mineralogical composition of the aquifer. The model also proves

  11. Automatic brain matter segmentation of computed tomography images using a statistical model: A tool to gain working time!

    Science.gov (United States)

    Bertè, Francesco; Lamponi, Giuseppe; Bramanti, Placido; Calabrò, Rocco S

    2015-10-01

    Brain computed tomography (CT) is useful diagnostic tool for the evaluation of several neurological disorders due to its accuracy, reliability, safety and wide availability. In this field, a potentially interesting research topic is the automatic segmentation and recognition of medical regions of interest (ROIs). Herein, we propose a novel automated method, based on the use of the active appearance model (AAM) for the segmentation of brain matter in CT images to assist radiologists in the evaluation of the images. The method described, that was applied to 54 CT images coming from a sample of outpatients affected by cognitive impairment, enabled us to obtain the generation of a model overlapping with the original image with quite good precision. Since CT neuroimaging is in widespread use for detecting neurological disease, including neurodegenerative conditions, the development of automated tools enabling technicians and physicians to reduce working time and reach a more accurate diagnosis is needed. © The Author(s) 2015.

  12. Identifying Generalizable Image Segmentation Parameters for Urban Land Cover Mapping through Meta-Analysis and Regression Tree Modeling

    Directory of Open Access Journals (Sweden)

    Brian A. Johnson

    2018-01-01

    Full Text Available The advent of very high resolution (VHR satellite imagery and the development of Geographic Object-Based Image Analysis (GEOBIA have led to many new opportunities for fine-scale land cover mapping, especially in urban areas. Image segmentation is an important step in the GEOBIA framework, so great time/effort is often spent to ensure that computer-generated image segments closely match real-world objects of interest. In the remote sensing community, segmentation is frequently performed using the multiresolution segmentation (MRS algorithm, which is tuned through three user-defined parameters (the scale, shape/color, and compactness/smoothness parameters. The scale parameter (SP is the most important parameter and governs the average size of generated image segments. Existing automatic methods to determine suitable SPs for segmentation are scene-specific and often computationally intensive, so an approach to estimating appropriate SPs that is generalizable (i.e., not scene-specific could speed up the GEOBIA workflow considerably. In this study, we attempted to identify generalizable SPs for five common urban land cover types (buildings, vegetation, roads, bare soil, and water through meta-analysis and nonlinear regression tree (RT modeling. First, we performed a literature search of recent studies that employed GEOBIA for urban land cover mapping and extracted the MRS parameters used, the image properties (i.e., spatial and radiometric resolutions, and the land cover classes mapped. Using this data extracted from the literature, we constructed RT models for each land cover class to predict suitable SP values based on the: image spatial resolution, image radiometric resolution, shape/color parameter, and compactness/smoothness parameter. Based on a visual and quantitative analysis of results, we found that for all land cover classes except water, relatively accurate SPs could be identified using our RT modeling results. The main advantage of our

  13. Landslide Susceptibility Evaluation on agricultural terraces of DOURO VALLEY (PORTUGAL), using physically based mathematical models.

    Science.gov (United States)

    Faria, Ana; Bateira, Carlos; Laura, Soares; Fernandes, Joana; Gonçalves, José; Marques, Fernando

    2016-04-01

    The work focuses the evaluation of landslide susceptibility in Douro Region agricultural terraces, supported by dry stone walls and earth embankments, using two physically based models. The applied models, SHALSTAB (Montgomery et al.,1994; Dietrich et al., 1995) and SINMAP (PACK et al., 2005), combine an infinite slope stability model with a steady state hydrological model, and both use the following geophysical parameters: cohesion, friction angle, specific weight and soil thickness. The definition of the contributing areas is different in both models. The D∞ methodology used by SINMAP model suggests a great influence of the terraces morphology, providing a much more diffuse flow on the internal flow modelling. The MD8 used in SHALSTAB promotes an important degree of flow concentration, representing an internal flow based on preferential paths of the runoff as the areas more susceptible to saturation processes. The model validation is made through the contingency matrix method (Fawcett, 2006; Raia et al., 2014) and implies the confrontation with the inventory of past landslides. The True Positive Rate shows that SHALSTAB classifies 77% of the landslides on the high susceptibility areas, while SINMAP reaches 90%. The SINMAP has a False Positive Rate (represents the percentage of the slipped area that is classified as unstable but without landslides) of 83% and the SHALSTAB has 67%. The reliability (analyzes the areas that were correctly classified on the total area) of SHALSTAB is better (33% against 18% of SINMAP). Relative to Precision (refers to the ratio of the slipped area correctly classified over the whole area classified as unstable) SHALSTAB has better results (0.00298 against 0.00283 of SINMAP). It was elaborate the index TPR/FPR and better results obtained by SHALSTAB (1.14 against 1.09 of SINMAP). SHALSTAB shows a better performance in the definition of susceptibility most prone areas to instability processes. One of the reasons for the difference of

  14. Strategic implication of a segmentation and positioning model for the South African gold narrow reef mining market.

    OpenAIRE

    2012-01-01

    M.Comm. Many variables exist that influence buyer behaviour in the narrow reef gold mining market. Since some variables are real but subjective in nature, such as the opinion and charisma of mine managers or influential individuals, it is difficult to quantify and analyse them. The question is ? Which variables, 8 quantifiable or not, are more dominant in shaping buyer behaviour and how should they be prioritised? What is needed is a logical segmentation model which reflects true buyer beh...

  15. Generalization of Figure-Ground Segmentation from Binocular to Monocular Vision in an Embodied Biological Brain Model

    Science.gov (United States)

    2011-08-01

    figure and ground the luminance cue breaks down and gestalt contours can fail to pop out. In this case we rely on color, which, having weak stereopsis...REPORT Generalization of Figure - Ground Segmentation from Monocular to Binocular Vision in an Embodied Biological Brain Model 14. ABSTRACT 16. SECURITY...U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 15. SUBJECT TERMS figure - ground , neural network, object

  16. Using Magnetics and Topography to Model Fault Splays of the Hilton Creek Fault System within the Long Valley Caldera

    Science.gov (United States)

    De Cristofaro, J. L.; Polet, J.

    2017-12-01

    The Hilton Creek Fault (HCF) is a range-bounding extensional fault that forms the eastern escarpment of California's Sierra Nevada mountain range, near the town of Mammoth Lakes. The fault is well mapped along its main trace to the south of the Long Valley Caldera (LVC), but the location and nature of its northern terminus is poorly constrained. The fault terminates as a series of left-stepping splays within the LVC, an area of active volcanism that most notably erupted 760 ka, and currently experiences continuous geothermal activity and sporadic earthquake swarms. The timing of the most recent motion on these fault splays is debated, as is the threat posed by this section of the Hilton Creek Fault. The Third Uniform California Earthquake Rupture Forecast (UCERF3) model depicts the HCF as a single strand projecting up to 12km into the LVC. However, Bailey (1989) and Hill and Montgomery-Brown (2015) have argued against this model, suggesting that extensional faulting within the Caldera has been accommodated by the ongoing volcanic uplift and thus the intracaldera section of the HCF has not experienced motion since 760ka.We intend to map the intracaldera fault splays and model their subsurface characteristics to better assess their rupture history and potential. This will be accomplished using high-resolution topography and subsurface geophysical methods, including ground-based magnetics. Preliminary work was performed using high-precision Nikon Nivo 5.C total stations to generate elevation profiles and a backpack mounted GEM GS-19 proton precession magnetometer. The initial results reveal a correlation between magnetic anomalies and topography. East-West topographic profiles show terrace-like steps, sub-meter in height, which correlate to changes in the magnetic data. Continued study of the magnetic data using Oasis Montaj 3D modeling software is planned. Additionally, we intend to prepare a high-resolution terrain model using structure-from-motion techniques

  17. Geological model for Boulder 1 at Station 2, South Massif, Valley of Taurus-Littrow

    Science.gov (United States)

    Schmitt, H. H.

    1975-01-01

    A possible geological model for the origin and history of the materials that make up Boulder 1 is proposed on the basis of firm and probable regional, local, and boulder geological constraints. These constraints are described in detail, unresolved questions are considered, and a model is presented which appears to satisfy all the firm constraints and most of the probable constraints. According to this model, the crystallization of plagioclase and other ANT-suite phases now present in the boulder as clasts and matrix materials took place during the melted-shell stage of lunar history; the original rocks were greatly modified during the cratered-highland stage; and the events that determined the major characteristics of the boulder occurred during the large-basin stage.

  18. Evaluating and Improving the SAMA (Segmentation Analysis and Market Assessment) Recruiting Model

    Science.gov (United States)

    2015-06-01

    53  APPENDIX B. SAMPLE VBA CONSOLIDATION CODE .............................................55  APPENDIX C. DATA...Assessment SSE Sum of Squared Errors TS Tactical Segment USAREC United States Army Recruiting Command VBA Visual Basic for Applications VIF...this research is the lack of access to SAMA calculations since it is a real- time system available exclusively to USAREC personnel. However, we

  19. Effective Segmentation of University Alumni: Mining Contribution Data with Finite-Mixture Models

    Science.gov (United States)

    Durango-Cohen, Elizabeth J.; Balasubramanian, Siva K.

    2015-01-01

    Having an effective segmentation strategy is key to the viability of any organization. This is particularly true for colleges, universities, and other nonprofit organizations--who have seen sharp declines in private contributions, endowment income, and government grants in the past few years, and face fierce competition for donor dollars…

  20. A Theoretical Model of Segmented Youth Labor Markets and the School to Work Transition.

    Science.gov (United States)

    Vrooman, John

    Recurring evidence that workers with similar skills do not necessarily earn the same wages led to the formulation of an alternative to the conventional market theory, namely, the segmented market theory. This theory posits that certain skills are distributed not among prospective employees but among jobs, in relation to the technology of those…

  1. Of clocks and waves, stripes and shapes : evo-devo models of sequential segmentation

    NARCIS (Netherlands)

    Vroomans, R.M.A.

    2017-01-01

    Segments are repeated elements along the main body axis of many animals, such as the rings of earthworms and myriapods or the vertebrae of mammals. These structures are produced very early in development. Typically, they are produced one by one from a posterior growth zone that starts just behind

  2. Validation of Point Clouds Segmentation Algorithms Through Their Application to Several Case Studies for Indoor Building Modelling

    Science.gov (United States)

    Macher, H.; Landes, T.; Grussenmeyer, P.

    2016-06-01

    Laser scanners are widely used for the modelling of existing buildings and particularly in the creation process of as-built BIM (Building Information Modelling). However, the generation of as-built BIM from point clouds involves mainly manual steps and it is consequently time consuming and error-prone. Along the path to automation, a three steps segmentation approach has been developed. This approach is composed of two phases: a segmentation into sub-spaces namely floors and rooms and a plane segmentation combined with the identification of building elements. In order to assess and validate the developed approach, different case studies are considered. Indeed, it is essential to apply algorithms to several datasets and not to develop algorithms with a unique dataset which could influence the development with its particularities. Indoor point clouds of different types of buildings will be used as input for the developed algorithms, going from an individual house of almost one hundred square meters to larger buildings of several thousand square meters. Datasets provide various space configurations and present numerous different occluding objects as for example desks, computer equipments, home furnishings and even wine barrels. For each dataset, the results will be illustrated. The analysis of the results will provide an insight into the transferability of the developed approach for the indoor modelling of several types of buildings.

  3. Predicting Rift Valley Fever Inter-epidemic Activities and Outbreak Patterns: Insights from a Stochastic Host-Vector Model.

    Directory of Open Access Journals (Sweden)

    Sansao A Pedro

    2016-12-01

    Full Text Available Rift Valley fever (RVF outbreaks are recurrent, occurring at irregular intervals of up to 15 years at least in East Africa. Between outbreaks disease inter-epidemic activities exist and occur at low levels and are maintained by female Aedes mcintoshi mosquitoes which transmit the virus to their eggs leading to disease persistence during unfavourable seasons. Here we formulate and analyse a full stochastic host-vector model with two routes of transmission: vertical and horizontal. By applying branching process theory we establish novel relationships between the basic reproduction number, R0, vertical transmission and the invasion and extinction probabilities. Optimum climatic conditions and presence of mosquitoes have not fully explained the irregular oscillatory behaviour of RVF outbreaks. Using our model without seasonality and applying van Kampen system-size expansion techniques, we provide an analytical expression for the spectrum of stochastic fluctuations, revealing how outbreaks multi-year periodicity varies with the vertical transmission. Our theory predicts complex fluctuations with a dominant period of 1 to 10 years which essentially depends on the efficiency of vertical transmission. Our predictions are then compared to temporal patterns of disease outbreaks in Tanzania, Kenya and South Africa. Our analyses show that interaction between nonlinearity, stochasticity and vertical transmission provides a simple but plausible explanation for the irregular oscillatory nature of RVF outbreaks. Therefore, we argue that while rainfall might be the major determinant for the onset and switch-off of an outbreak, the occurrence of a particular outbreak is also a result of a build up phenomena that is correlated to vertical transmission efficiency.

  4. EPA Region 1 - Valley Depth in Meters

    Science.gov (United States)

    Raster of the Depth in meters of EPA-delimited Valleys in Region 1.Valleys (areas that are lower than their neighbors) were extracted from a Digital Elevation Model (USGS, 30m) by finding the local average elevation, subtracting the actual elevation from the average, and selecting areas where the actual elevation was below the average. The landscape was sampled at seven scales (circles of 1, 2, 4, 7, 11, 16, and 22 km radius) to take into account the diversity of valley shapes and sizes. Areas selected in at least four scales were designated as valleys.

  5. A regional model simulation of the 1991 severe precipitation event over the Yangtze-Huai River Valley. Part 2: Model bias

    Energy Technology Data Exchange (ETDEWEB)

    Gong, W.; Wang, W.C.

    2000-01-01

    This is the second part of a study investigating the 1991 severe precipitation event over the Uangtze-Huai River valley (YHRV) in China using both observations and regional model simulations. While Part 1 reported on the Mei-yu front and its association with large-scale circulation, this study documents the biases associated with the treatment of the lateral boundary in the regional model. Two aspects of the biases were studied: the driving field, which provides large-scale boundary forcing, and the coupling scheme, which specified how the forcing is adopted by the model. The former bias is defined as model uncertainty because it is not related to the model itself, while the latter bias (as well as those biases attributed to other sources) is referred to as model error. These two aspects were examined by analyzing the regional model simulations of the 1991 summer severe precipitation event over YHRV using different driving fields (ECMWF-TOGA objective analysis, ECMWF reanalysis, and NCEP-NCAR reanalysis) and coupling scheme (distribution function of the nudging coefficient and width of the buffer zone). Spectral analysis was also used to study the frequency distribution of the bias.

  6. A multi-segment foot model based on anatomically registered technical coordinate systems: method repeatability in pediatric feet.

    Science.gov (United States)

    Saraswat, Prabhav; MacWilliams, Bruce A; Davis, Roy B

    2012-04-01

    Several multi-segment foot models to measure the motion of intrinsic joints of the foot have been reported. Use of these models in clinical decision making is limited due to lack of rigorous validation including inter-clinician, and inter-lab variability measures. A model with thoroughly quantified variability may significantly improve the confidence in the results of such foot models. This study proposes a new clinical foot model with the underlying strategy of using separate anatomic and technical marker configurations and coordinate systems. Anatomical landmark and coordinate system identification is determined during a static subject calibration. Technical markers are located at optimal sites for dynamic motion tracking. The model is comprised of the tibia and three foot segments (hindfoot, forefoot and hallux) and inter-segmental joint angles are computed in three planes. Data collection was carried out on pediatric subjects at two sites (Site 1: n=10 subjects by two clinicians and Site 2: five subjects by one clinician). A plaster mold method was used to quantify static intra-clinician and inter-clinician marker placement variability by allowing direct comparisons of marker data between sessions for each subject. Intra-clinician and inter-clinician joint angle variability were less than 4°. For dynamic walking kinematics, intra-clinician, inter-clinician and inter-laboratory variability were less than 6° for the ankle and forefoot, but slightly higher for the hallux. Inter-trial variability accounted for 2-4° of the total dynamic variability. Results indicate the proposed foot model reduces the effects of marker placement variability on computed foot kinematics during walking compared to similar measures in previous models. Copyright © 2011 Elsevier B.V. All rights reserved.

  7. Modelling atmospheric circulations for the study of Alpine valleys pollution; Modelisation des circulations atmospheriques pour l'etude de la pollution des vallees alpines

    Energy Technology Data Exchange (ETDEWEB)

    Brulfert, G

    2004-11-15

    Local weather phenomena observed in alpine valleys frequently lead to the accumulation of emitted anthropogenic airborne species in the low layers of the atmosphere. The development of a numerical model allows reproducing the chemical evolution of air mass during POVA intensive period of observations. In Chamonix and Maurienne valley, computations of photochemical indicators (NO{sub y}, O{sub 3}/NO{sub z}, H{sub 2}O{sub 2}/HNO{sub 3}) prove the ozone regime to be control by volatile organic compounds. Moreover simulation highlighted that the major part of this secondary pollutant is regionally produced. The development of an indicator who localised ozone production sites can help to define abatement scenarios. The chemical mechanism RACM allows describing the evolution of many species. It is possible to conclude that in winter road traffic and heating are the main sources of volatile organic compounds. (author)

  8. Modelling atmospheric circulations for the study of Alpine valleys pollution; Modelisation des circulations atmospheriques pour l'etude de la pollution des vallees alpines

    Energy Technology Data Exchange (ETDEWEB)

    Brulfert, G.

    2004-11-15

    Local weather phenomena observed in alpine valleys frequently lead to the accumulation of emitted anthropogenic airborne species in the low layers of the atmosphere. The development of a numerical model allows reproducing the chemical evolution of air mass during POVA intensive period of observations. In Chamonix and Maurienne valley, computations of photochemical indicators (NO{sub y}, O{sub 3}/NO{sub z}, H{sub 2}O{sub 2}/HNO{sub 3}) prove the ozone regime to be control by volatile organic compounds. Moreover simulation highlighted that the major part of this secondary pollutant is regionally produced. The development of an indicator who localised ozone production sites can help to define abatement scenarios. The chemical mechanism RACM allows describing the evolution of many species. It is possible to conclude that in winter road traffic and heating are the main sources of volatile organic compounds. (author)

  9. Research on analytical model and design formulas of permanent magnetic bearings based on Halbach array with arbitrary segmented magnetized angle

    International Nuclear Information System (INIS)

    Wang, Nianxian; Wang, Dongxiong; Chen, Kuisheng; Wu, Huachun

    2016-01-01

    The bearing capacity of permanent magnetic bearings can be improved efficiently by using the Halbach array magnetization. However, the research on analytical model of Halbach array PMBs with arbitrary segmented magnetized angle has not been developed. The application of Halbach array PMBs has been limited by the absence of the analytical model and design formulas. In this research, the Halbach array PMBs with arbitrary segmented magnetized angle has been studied. The magnetization model of bearings is established. The magnetic field distribution model of the permanent magnet array is established by using the scalar magnetic potential model. On the basis of this, the bearing force model and the bearing stiffness model of the PMBs are established based on the virtual displacement method. The influence of the pair of magnetic rings in one cycle and the structure parameters of PMBs on the maximal bearing capacity and support stiffness characteristics are studied. The reference factors for the design process of PMBs have been given. Finally, the theoretical model and the conclusions are verified by the finite element analysis.

  10. Multi-criteria media mix decision model for advertising multiple product with segment specific and mass media

    Directory of Open Access Journals (Sweden)

    Sugandha Aggarwal

    2014-12-01

    Full Text Available Judicious media planning decisions are crucial for successful advertising of products. Media planners extensively use mathematical models supplemented with market research and expert opinion to devise the media plans. Media planning models discussed in the literature largely focus on single products with limited studies related to the multi-product media planning. In this paper we propose a media planning model to allocate limited advertising budget among multiple products advertised in a segmented market and determine the number of advertisements to be given in different media. The proposed model is formulated considering both segment specific and mass media vehicles to maximize the total advertising reach for each product. The model also incorporates the cross product effect of advertising of one product on the other. The proposed formulation is a multi-objective linear integer programming model and interactive linear integer goal programming is discussed to solve the model. A real life case study is presented to illustrate the application of the proposed model.

  11. Flow prediction models using macroclimatic variables and multivariate statistical techniques in the Cauca River Valley

    International Nuclear Information System (INIS)

    Carvajal Escobar Yesid; Munoz, Flor Matilde

    2007-01-01

    The project this centred in the revision of the state of the art of the ocean-atmospheric phenomena that you affect the Colombian hydrology especially The Phenomenon Enos that causes a socioeconomic impact of first order in our country, it has not been sufficiently studied; therefore it is important to approach the thematic one, including the variable macroclimates associated to the Enos in the analyses of water planning. The analyses include revision of statistical techniques of analysis of consistency of hydrological data with the objective of conforming a database of monthly flow of the river reliable and homogeneous Cauca. Statistical methods are used (Analysis of data multivariante) specifically The analysis of principal components to involve them in the development of models of prediction of flows monthly means in the river Cauca involving the Lineal focus as they are the model autoregressive AR, ARX and Armax and the focus non lineal Net Artificial Network.

  12. Automated and simultaneous fovea center localization and macula segmentation using the new dynamic identification and classification of edges model

    Science.gov (United States)

    Onal, Sinan; Chen, Xin; Satamraju, Veeresh; Balasooriya, Maduka; Dabil-Karacal, Humeyra

    2016-01-01

    Abstract. Detecting the position of retinal structures, including the fovea center and macula, in retinal images plays a key role in diagnosing eye diseases such as optic nerve hypoplasia, amblyopia, diabetic retinopathy, and macular edema. However, current detection methods are unreliable for infants or certain ethnic populations. Thus, a methodology is proposed here that may be useful for infants and across ethnicities that automatically localizes the fovea center and segments the macula on digital fundus images. First, dark structures and bright artifacts are removed from the input image using preprocessing operations, and the resulting image is transformed to polar space. Second, the fovea center is identified, and the macula region is segmented using the proposed dynamic identification and classification of edges (DICE) model. The performance of the method was evaluated using 1200 fundus images obtained from the relatively large, diverse, and publicly available Messidor database. In 96.1% of these 1200 cases, the distance between the fovea center identified manually by ophthalmologists and automatically using the proposed method remained within 0 to 8 pixels. The dice similarity index comparing the manually obtained results with those of the model for macula segmentation was 96.12% for these 1200 cases. Thus, the proposed method displayed a high degree of accuracy. The methodology using the DICE model is unique and advantageous over previously reported methods because it simultaneously determines the fovea center and segments the macula region without using any structural information, such as optic disc or blood vessel location, and it may prove useful for all populations, including infants. PMID:27660803

  13. Development of Hydrological Model of Klang River Valley for flood forecasting

    Science.gov (United States)

    Mohammad, M.; Andras, B.

    2012-12-01

    This study is to review the impact of climate change and land used on flooding through the Klang River and to compare the changes in the existing river system in Klang River Basin with the Storm water Management and Road Tunnel (SMART) which is now already operating in the city centre of Kuala Lumpur. Klang River Basin is the most urbanized region in Malaysia. More than half of the basin has been urbanized on the land that is prone to flooding. Numerous flood mitigation projects and studies have been carried out to enhance the existing flood forecasting and mitigation project. The objective of this study is to develop a hydrological model for flood forecasting in Klang Basin Malaysia. Hydrological modelling generally requires large set of input data and this is more often a challenge for a developing country. Due to this limitation, the Tropical Rainfall Measuring Mission (TRMM) rainfall measurement, initiated by the US space agency NASA and Japanese space agency JAXA was used in this study. TRMM data was transformed and corrected by quantile to quantile transformation. However, transforming the data based on ground measurement doesn't make any significant improvement and the statistical comparison shows only 10% difference. The conceptual HYMOD model was used in this study and calibrated using ROPE algorithm. But, using the whole time series of the observation period in this area resulted in insufficient performance. The depth function which used in ROPE algorithm are then used to identified and calibrated using only unusual event to observed the improvement and efficiency of the model.

  14. Modeling anthropogenic and natural fire ignitions in an inner-alpine valley

    Directory of Open Access Journals (Sweden)

    G. Vacchiano

    2018-03-01

    Full Text Available Modeling and assessing the factors that drive forest fire ignitions is critical for fire prevention and sustainable ecosystem management. In southern Europe, the anthropogenic component of wildland fire ignitions is especially relevant. In the Alps, however, the role of fire as a component of disturbance regimes in forest and grassland ecosystems is poorly known. The aim of this work is to model the probability of fire ignition for an Alpine region in Italy using a regional wildfire archive (1995–2009 and MaxEnt modeling. We analyzed separately (i winter forest fires, (ii winter fires on grasslands and fallow land, and (iii summer fires. Predictors were related to morphology, climate, and land use; distance from infrastructures, number of farms, and number of grazing animals were used as proxies for the anthropogenic component. Collinearity among predictors was reduced by a principal component analysis. Regarding ignitions, 30 % occurred in agricultural areas and 24 % in forests. Ignitions peaked in the late winter–early spring. Negligence from agrosilvicultural activities was the main cause of ignition (64 %; lightning accounted for 9 % of causes across the study time frame, but increased from 6 to 10 % between the first and second period of analysis. Models for all groups of fire had a high goodness of fit (AUC 0.90–0.95. Temperature was proportional to the probability of ignition, and precipitation was inversely proportional. Proximity from infrastructures had an effect only on winter fires, while the density of grazing animals had a remarkably different effect on summer (positive correlation and winter (negative fires. Implications are discussed regarding climate change, fire regime changes, and silvicultural prevention. Such a spatially explicit approach allows us to carry out spatially targeted fire management strategies and may assist in developing better fire management plans.

  15. Modeling anthropogenic and natural fire ignitions in an inner-alpine valley

    Science.gov (United States)

    Vacchiano, Giorgio; Foderi, Cristiano; Berretti, Roberta; Marchi, Enrico; Motta, Renzo

    2018-03-01

    Modeling and assessing the factors that drive forest fire ignitions is critical for fire prevention and sustainable ecosystem management. In southern Europe, the anthropogenic component of wildland fire ignitions is especially relevant. In the Alps, however, the role of fire as a component of disturbance regimes in forest and grassland ecosystems is poorly known. The aim of this work is to model the probability of fire ignition for an Alpine region in Italy using a regional wildfire archive (1995-2009) and MaxEnt modeling. We analyzed separately (i) winter forest fires, (ii) winter fires on grasslands and fallow land, and (iii) summer fires. Predictors were related to morphology, climate, and land use; distance from infrastructures, number of farms, and number of grazing animals were used as proxies for the anthropogenic component. Collinearity among predictors was reduced by a principal component analysis. Regarding ignitions, 30 % occurred in agricultural areas and 24 % in forests. Ignitions peaked in the late winter-early spring. Negligence from agrosilvicultural activities was the main cause of ignition (64 %); lightning accounted for 9 % of causes across the study time frame, but increased from 6 to 10 % between the first and second period of analysis. Models for all groups of fire had a high goodness of fit (AUC 0.90-0.95). Temperature was proportional to the probability of ignition, and precipitation was inversely proportional. Proximity from infrastructures had an effect only on winter fires, while the density of grazing animals had a remarkably different effect on summer (positive correlation) and winter (negative) fires. Implications are discussed regarding climate change, fire regime changes, and silvicultural prevention. Such a spatially explicit approach allows us to carry out spatially targeted fire management strategies and may assist in developing better fire management plans.

  16. Conceptual Modeling for Adaptive Environmental Assessment and Management in the Barycz Valley, Lower Silesia, Poland

    Directory of Open Access Journals (Sweden)

    Jakub Kronenberg

    2005-08-01

    Full Text Available The complexity of interactions in socio-ecological systems makes it very difficult to plan and implement policies successfully. Traditional environmental management and assessment techniques produce unsatisfactory results because they often ignore facets of system structure that underlie complexity: delays, feedbacks, and non-linearities. Assuming that causes are linked in a linear chain, they concentrate on technological developments (“hard path” as the only solutions to environmental problems. Adaptive Management is recognized as a promising alternative approach directly addressing links between social and ecological systems and involving stakeholders in the analysis and decision process. This “soft path” requires special tools to facilitate collaboration between “experts” and stakeholders in analyzing complex situations and prioritizing policies and actions. We have applied conceptual modeling to increase communication, understanding and commitment in the project of seven NGOs “Sustainable Regional Development in the Odra Catchment”. The main goal was to help our NGO partners to facilitate their efforts related to developing sustainable policies and practices to respond to large-scale challenges (EU accession, global changes in climate and economy to their natural, economic and socio-cultural heritages. Among the variety of sustainability issues explored by these NGOs, two (extensive agricultural practices and “green” local products were examined by using Adaptive Management (AM as a framework that would link analysis, discussion, research, actions and monitoring. Within the AM framework the project coordinators used tools of systems analysis (Mental Model Mapping to facilitate discussions in which NGO professionals and local stakeholders could graphically diagram and study their understanding of what factors interacted and

  17. A deformable-model approach to semi-automatic segmentation of CT images demonstrated by application to the spinal canal

    International Nuclear Information System (INIS)

    Burnett, Stuart S.C.; Starkschall, George; Stevens, Craig W.; Liao Zhongxing

    2004-01-01

    Because of the importance of accurately defining the target in radiation treatment planning, we have developed a deformable-template algorithm for the semi-automatic delineation of normal tissue structures on computed tomography (CT) images. We illustrate the method by applying it to the spinal canal. Segmentation is performed in three steps: (a) partial delineation of the anatomic structure is obtained by wavelet-based edge detection; (b) a deformable-model template is fitted to the edge set by chamfer matching; and (c) the template is relaxed away from its original shape into its final position. Appropriately chosen ranges for the model parameters limit the deformations of the template, accounting for interpatient variability. Our approach differs from those used in other deformable models in that it does not inherently require the modeling of forces. Instead, the spinal canal was modeled using Fourier descriptors derived from four sets of manually drawn contours. Segmentation was carried out, without manual intervention, on five CT data sets and the algorithm's performance was judged subjectively by two radiation oncologists. Two assessments were considered: in the first, segmentation on a random selection of 100 axial CT images was compared with the corresponding contours drawn manually by one of six dosimetrists, also chosen randomly; in the second assessment, the segmentation of each image in the five evaluable CT sets (a total of 557 axial images) was rated as either successful, unsuccessful, or requiring further editing. Contours generated by the algorithm were more likely than manually drawn contours to be considered acceptable by the oncologists. The mean proportions of acceptable contours were 93% (automatic) and 69% (manual). Automatic delineation of the spinal canal was deemed to be successful on 91% of the images, unsuccessful on 2% of the images, and requiring further editing on 7% of the images. Our deformable template algorithm thus gives a robust

  18. Composition models for the viscosity and chemical durability of West Valley related nuclear waste glasses

    International Nuclear Information System (INIS)

    Feng, X.; Saad, E.E.; Freeborn, W.P.; Macedo, P.B.; Pegg, I.L.; Sassoon, R.E.; Barkatt, A.; Finger, S.M.

    1988-01-01

    There are two important criteria that must be satisfied by a nuclear waste glass durability and processability. The chemical composition of the glass must be such that it does not dissolve or erode appreciably faster than the decay of the radioactive materials embedded in it. The second criterion, processability, means that the glass must melt with ease, must be easily pourable, and must not crystallize appreciably. This paper summarizes the development of simple models for predicting the durability and viscosity of nuclear waste glasses from their composition

  19. Nematic-isotropic transition in some lattice models for rigid cores having semiflexible tails: segmental Lennard-Jones interactions

    International Nuclear Information System (INIS)

    Dowell, F.

    1983-01-01

    Two average-environment simple cubic lattice models: a refined model and a simple model, both having site-site (segmental) pair Lennard-Jones (LJ) interactions: for molecules composed of rigid cores having semiflexible tails are presented. The calculated values of the following properties at the nematic-isotropic transition for rigid rods of varying length are compared with relevant experimental data for PAA (p-azoxyanisole, or 4,4'-dimethoxyazoxybenzene): temperature, core orientational order parameter, nematic density and volume, relative density change, and relative entropy change. The temperature change as a function of volume change at constant order parameter is also discussed. In general, both LJ models give considerably better quantitative agreement with experiment, especially for the temperature and the relative density change, than do the earlier lattice models with hard repulsions, with or without constant segmental pair interaction energies. In most aspects, these LJ models give good quantitative agreement with experiment. These LJ models elucidate the importance of realistic intermolecular potentials, especially the role of soft repulsions, in describing an order-disorder transition between two condensed phases

  20. The Statistical Segment Length of DNA: Opportunities for Biomechanical Modeling in Polymer Physics and Next-Generation Genomics.

    Science.gov (United States)

    Dorfman, Kevin D

    2018-02-01

    The development of bright bisintercalating dyes for deoxyribonucleic acid (DNA) in the 1990s, most notably YOYO-1, revolutionized the field of polymer physics in the ensuing years. These dyes, in conjunction with modern molecular biology techniques, permit the facile observation of polymer dynamics via fluorescence microscopy and thus direct tests of different theories of polymer dynamics. At the same time, they have played a key role in advancing an emerging next-generation method known as genome mapping in nanochannels. The effect of intercalation on the bending energy of DNA as embodied by a change in its statistical segment length (or, alternatively, its persistence length) has been the subject of significant controversy. The precise value of the statistical segment length is critical for the proper interpretation of polymer physics experiments and controls the phenomena underlying the aforementioned genomics technology. In this perspective, we briefly review the model of DNA as a wormlike chain and a trio of methods (light scattering, optical or magnetic tweezers, and atomic force microscopy (AFM)) that have been used to determine the statistical segment length of DNA. We then outline the disagreement in the literature over the role of bisintercalation on the bending energy of DNA, and how a multiscale biomechanical approach could provide an important model for this scientifically and technologically relevant problem.

  1. Simulation of net infiltration and potential recharge using a distributed-parameter watershed model of the Death Valley region, Nevada and California

    Science.gov (United States)

    Hevesi, Joseph A.; Flint, Alan L.; Flint, Lorraine E.

    2003-01-01

    This report presents the development and application of the distributed-parameter watershed model, INFILv3, for estimating the temporal and spatial distribution of net infiltration and potential recharge in the Death Valley region, Nevada and California. The estimates of net infiltration quantify the downward drainage of water across the lower boundary of the root zone and are used to indicate potential recharge under variable climate conditions and drainage basin characteristics. Spatial variability in recharge in the Death Valley region likely is high owing to large differences in precipitation, potential evapotranspiration, bedrock permeability, soil thickness, vegetation characteristics, and contributions to recharge along active stream channels. The quantity and spatial distribution of recharge representing the effects of variable climatic conditions and drainage basin characteristics on recharge are needed to reduce uncertainty in modeling ground-water flow. The U.S. Geological Survey, in cooperation with the Department of Energy, developed a regional saturated-zone ground-water flow model of the Death Valley regional ground-water flow system to help evaluate the current hydrogeologic system and the potential effects of natural or human-induced changes. Although previous estimates of recharge have been made for most areas of the Death Valley region, including the area defined by the boundary of the Death Valley regional ground-water flow system, the uncertainty of these estimates is high, and the spatial and temporal variability of the recharge in these basins has not been quantified. To estimate the magnitude and distribution of potential recharge in response to variable climate and spatially varying drainage basin characteristics, the INFILv3 model uses a daily water-balance model of the root zone with a primarily deterministic representation of the processes controlling net infiltration and potential recharge. The daily water balance includes precipitation

  2. Structural Evolution of the East Sierra Valley System (Owens Valley and Vicinity, California: A Geologic and Geophysical Synthesis

    Directory of Open Access Journals (Sweden)

    Richard J. Blakely

    2013-04-01

    Full Text Available The tectonically active East Sierra Valley System (ESVS, which comprises the westernmost part of the Walker Lane-Eastern California Shear Zone, marks the boundary between the highly extended Basin and Range Province and the largely coherent Sierra Nevada-Great Valley microplate (SN-GVm, which is moving relatively NW. The recent history of the ESVS is characterized by oblique extension partitioned between NNW-striking normal and strike-slip faults oriented at an angle to the more northwesterly relative motion of the SN-GVm. Spatially variable extension and right-lateral shear have resulted in a longitudinally segmented valley system composed of diverse geomorphic and structural elements, including a discontinuous series of deep basins detected through analysis of isostatic gravity anomalies. Extension in the ESVS probably began in the middle Miocene in response to initial westward movement of the SN-GVm relative to the Colorado Plateau. At ca. 3–3.5 Ma, the SN-GVm became structurally separated from blocks directly to the east, resulting in significant basin-forming deformation in the ESVS. We propose a structural model that links high-angle normal faulting in the ESVS with coeval low-angle detachment faulting in adjacent areas to the east.

  3. Structural evolution of the east Sierra Valley system (Owens Valley and vicinity), California: a geologic and geophysical synthesis

    Science.gov (United States)

    Stevens, Calvin H.; Stone, Paul; Blakely, Richard J.

    2013-01-01

    The tectonically active East Sierra Valley System (ESVS), which comprises the westernmost part of the Walker Lane-Eastern California Shear Zone, marks the boundary between the highly extended Basin and Range Province and the largely coherent Sierra Nevada-Great Valley microplate (SN-GVm), which is moving relatively NW. The recent history of the ESVS is characterized by oblique extension partitioned between NNW-striking normal and strike-slip faults oriented at an angle to the more northwesterly relative motion of the SN-GVm. Spatially variable extension and right-lateral shear have resulted in a longitudinally segmented valley system composed of diverse geomorphic and structural elements, including a discontinuous series of deep basins detected through analysis of isostatic gravity anomalies. Extension in the ESVS probably began in the middle Miocene in response to initial westward movement of the SN-GVm relative to the Colorado Plateau. At ca. 3-3.5 Ma, the SN-GVm became structurally separated from blocks directly to the east, resulting in significant basin-forming deformation in the ESVS. We propose a structural model that links high-angle normal faulting in the ESVS with coeval low-angle detachment faulting in adjacent areas to the east.

  4. CT and MRI assessment and characterization using segmentation and 3D modeling techniques: applications to muscle, bone and brain

    Directory of Open Access Journals (Sweden)

    Paolo Gargiulo

    2014-03-01

    Full Text Available This paper reviews the novel use of CT and MRI data and image processing tools to segment and reconstruct tissue images in 3D to determine characteristics of muscle, bone and brain.This to study and simulate the structural changes occurring in healthy and pathological conditions as well as in response to clinical treatments. Here we report the application of this methodology to evaluate and quantify: 1. progression of atrophy in human muscle subsequent to permanent lower motor neuron (LMN denervation, 2. muscle recovery as induced by functional electrical stimulation (FES, 3. bone quality in patients undergoing total hip replacement and 4. to model the electrical activity of the brain. Study 1: CT data and segmentation techniques were used to quantify changes in muscle density and composition by associating the Hounsfield unit values of muscle, adipose and fibrous connective tissue with different colors. This method was employed to monitor patients who have permanent muscle LMN denervation in the lower extremities under two different conditions: permanent LMN denervated not electrically stimulated and stimulated. Study 2: CT data and segmentation techniques were employed, however, in this work we assessed bone and muscle conditions in the pre-operative CT scans of patients scheduled to undergo total hip replacement. In this work, the overall anatomical structure, the bone mineral density (BMD and compactness of quadriceps muscles and proximal femoral was computed to provide a more complete view for surgeons when deciding which implant technology to use. Further, a Finite element analysis provided a map of the strains around the proximal femur socket when solicited by typical stresses caused by an implant press fitting. Study 3 describes a method to model the electrical behavior of human brain using segmented MR images. The aim of the work is to use these models to predict the electrical activity of the human brain under normal and pathological

  5. Segmental trisomy of chromosome 17: a mouse model of human aneuploidy syndromes

    Czech Academy of Sciences Publication Activity Database

    Vacík, Tomáš; Ort, Michael; Gregorová, Soňa; Strnad, P.; Conte, N.; Bradley, A.; Blatný, Radek; Bureš, Jan; Forejt, Jiří

    2005-01-01

    Roč. 102, č. 12 (2005), s. 4500-4505 ISSN 0027-8424 R&D Projects: GA ČR(CZ) GA309/03/0715 Grant - others:Howard Hughes Medical Institute(US) 55000306 Institutional research plan: CEZ:AV0Z5011922; CEZ:AV0Z50110509 Keywords : dosage-sensitive genes * Down's syndrome * mouse segmental trisomy Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 10.231, year: 2005

  6. Segmental trisomy of mouse chromosome 17: introducing an alternative model of Down syndrome

    Czech Academy of Sciences Publication Activity Database

    Forejt, Jiří; Vacík, Tomáš; Gregorová, Soňa

    2003-01-01

    Roč. 4, - (2003), s. 647-652 ISSN 1531-6912 R&D Projects: GA MŠk LN00A079; GA ČR GV204/98/K015 Grant - others:HHMI(US) 555000306 Institutional research plan: CEZ:AV0Z5052915 Keywords : segmental aneuploidy * Down ´s syndrome * gene dosage Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 1.297, year: 2003

  7. Segmentation of vessels cluttered with cells using a physics based model.

    Science.gov (United States)

    Schmugge, Stephen J; Keller, Steve; Nguyen, Nhat; Souvenir, Richard; Huynh, Toan; Clemens, Mark; Shin, Min C

    2008-01-01

    Segmentation of vessels in biomedical images is important as it can provide insight into analysis of vascular morphology, topology and is required for kinetic analysis of flow velocity and vessel permeability. Intravital microscopy is a powerful tool as it enables in vivo imaging of both vasculature and circulating cells. However, the analysis of vasculature in those images is difficult due to the presence of cells and their image gradient. In this paper, we provide a novel method of segmenting vessels with a high level of cell related clutter. A set of virtual point pairs ("vessel probes") are moved reacting to forces including Vessel Vector Flow (VVF) and Vessel Boundary Vector Flow (VBVF) forces. Incorporating the cell detection, the VVF force attracts the probes toward the vessel, while the VBVF force attracts the virtual points of the probes to localize the vessel boundary without being distracted by the image features of the cells. The vessel probes are moved according to Newtonian Physics reacting to the net of forces applied on them. We demonstrate the results on a set of five real in vivo images of liver vasculature cluttered by white blood cells. When compared against the ground truth prepared by the technician, the Root Mean Squared Error (RMSE) of segmentation with VVF and VBVF was 55% lower than the method without VVF and VBVF.

  8. Numerical model for the thermal-hydraulic solution of shell-and-U-tubes heat exchanger with segmental baffles

    International Nuclear Information System (INIS)

    Baptista Filho, Benedito Dias

    1979-01-01

    A numerical model has been developed to calculate the flow, pressure and temperature distribution of steady-state |for the tube and shell-side fluids in a shell-and-U-tubes heat exchanger with segmental baffles. It was based on the Subchannel Analysis Method- The model, checked with experimental results from one heat exchanger, predicted with good accuracy outlet temperatures for both fluids. The method, implemented ' in a computer program of low cost and easy application, can be used in the design and performance evaluation of commercial units.(author)

  9. Active Segmentation.

    Science.gov (United States)

    Mishra, Ajay; Aloimonos, Yiannis

    2009-01-01

    The human visual system observes and understands a scene/image by making a series of fixations. Every fixation point lies inside a particular region of arbitrary shape and size in the scene which can either be an object or just a part of it. We define as a basic segmentation problem the task of segmenting that region containing the fixation point. Segmenting the region containing the fixation is equivalent to finding the enclosing contour- a connected set of boundary edge fragments in the edge map of the scene - around the fixation. This enclosing contour should be a depth boundary.We present here a novel algorithm that finds this bounding contour and achieves the segmentation of one object, given the fixation. The proposed segmentation framework combines monocular cues (color/intensity/texture) with stereo and/or motion, in a cue independent manner. The semantic robots of the immediate future will be able to use this algorithm to automatically find objects in any environment. The capability of automatically segmenting objects in their visual field can bring the visual processing to the next level. Our approach is different from current approaches. While existing work attempts to segment the whole scene at once into many areas, we segment only one image region, specifically the one containing the fixation point. Experiments with real imagery collected by our active robot and from the known databases 1 demonstrate the promise of the approach.