WorldWideScience

Sample records for model key features

  1. Electronic Service Architecture Model Assessment of Conformity to Cloud Computing Key Features

    OpenAIRE

    Stipravietis, P; Žeiris, E; Ziema, M

    2013-01-01

    The research examines electronic service execution possibilities in cloud computing environment and the key features of cloud computing. It also offers a method which allows quantitatively assess the conformity of existing e-service architecture model to cloud computing key features.The method allows evaluating the amount of necessary transformations and their efficiency. The offered solution is verified using the business process administered by Motor Insurance Bureau...

  2. A step towards considering the spatial heterogeneity of urban key features in urban hydrology flood modelling

    Science.gov (United States)

    Leandro, J.; Schumann, A.; Pfister, A.

    2016-04-01

    Some of the major challenges in modelling rainfall-runoff in urbanised areas are the complex interaction between the sewer system and the overland surface, and the spatial heterogeneity of the urban key features. The former requires the sewer network and the system of surface flow paths to be solved simultaneously. The latter is still an unresolved issue because the heterogeneity of runoff formation requires high detailed information and includes a large variety of feature specific rainfall-runoff dynamics. This paper discloses a methodology for considering the variability of building types and the spatial heterogeneity of land surfaces. The former is achieved by developing a specific conceptual rainfall-runoff model and the latter by defining a fully distributed approach for infiltration processes in urban areas with limited storage capacity dependent on OpenStreetMaps (OSM). The model complexity is increased stepwise by adding components to an existing 2D overland flow model. The different steps are defined as modelling levels. The methodology is applied in a German case study. Results highlight that: (a) spatial heterogeneity of urban features has a medium to high impact on the estimated overland flood-depths, (b) the addition of multiple urban features have a higher cumulative effect due to the dynamic effects simulated by the model, (c) connecting the runoff from buildings to the sewer contributes to the non-linear effects observed on the overland flood-depths, and (d) OSM data is useful in identifying pounding areas (for which infiltration plays a decisive role) and permeable natural surface flow paths (which delay the flood propagation).

  3. Summary of the key features of seven biomathematical models of human fatigue and performance

    Science.gov (United States)

    Mallis, Melissa M.; Mejdal, Sig; Nguyen, Tammy T.; Dinges, David F.

    2004-01-01

    BACKGROUND: Biomathematical models that quantify the effects of circadian and sleep/wake processes on the regulation of alertness and performance have been developed in an effort to predict the magnitude and timing of fatigue-related responses in a variety of contexts (e.g., transmeridian travel, sustained operations, shift work). This paper summarizes key features of seven biomathematical models reviewed as part of the Fatigue and Performance Modeling Workshop held in Seattle, WA, on June 13-14, 2002. The Workshop was jointly sponsored by the National Aeronautics and Space Administration, U.S. Department of Defense, U.S. Army Medical Research and Materiel Command, Office of Naval Research, Air Force Office of Scientific Research, and U.S. Department of Transportation. METHODS: An invitation was sent to developers of seven biomathematical models that were commonly cited in scientific literature and/or supported by government funding. On acceptance of the invitation to attend the Workshop, developers were asked to complete a survey of the goals, capabilities, inputs, and outputs of their biomathematical models of alertness and performance. Data from the completed surveys were summarized and juxtaposed to provide a framework for comparing features of the seven models. RESULTS: Survey responses revealed that models varied greatly relative to their reported goals and capabilities. While all modelers reported that circadian factors were key components of their capabilities, they differed markedly with regard to the roles of sleep and work times as input factors for prediction: four of the seven models had work time as their sole input variable(s), while the other three models relied on various aspects of sleep timing for model input. Models also differed relative to outputs: five sought to predict results from laboratory experiments, field, and operational data, while two models were developed without regard to predicting laboratory experimental results. All modelers

  4. Empirical model of the composition of the Venus ionosphere Repeatable characteristics and key features not modeled

    Science.gov (United States)

    Taylor, H. A., Jr.; Mayr, H. G.; Niemann, H. B.; Larson, J.

    1985-01-01

    In-situ measurements of positive ion composition of the ionosphere of Venus are combined in an empirical model which is a key element for the Venus International Reference Atmosphere (VIRA) model. The ion data are obtained from the Pioneer Venus Orbiter Ion Mass Spectrometer (OIMS) which obtained daily measurements beginning in December 1978 and extending to July 1980 when the uncontrolled rise of satellite periapsis height precluded further measurements in the main body of the ionosphere. For this period, measurements of 12 ion species are sorted into altitude and local time bins with altitude extending from 150 to 1000 km. The model results exhibit the appreciable nightside ionosphere found at Venus, the dominance of atomic oxygen ions in the dayside upper ionosphere and the increase in prominence of atomic oxygen and deuterium ions on the nightside. Short term variations, such as the abrupt changes observed in the ionopause, cannot be represented in the model.

  5. Simple dynamical models capturing the key features of the Central Pacific El Niño.

    Science.gov (United States)

    Chen, Nan; Majda, Andrew J

    2016-10-18

    The Central Pacific El Niño (CP El Niño) has been frequently observed in recent decades. The phenomenon is characterized by an anomalous warm sea surface temperature (SST) confined to the central Pacific and has different teleconnections from the traditional El Niño. Here, simple models are developed and shown to capture the key mechanisms of the CP El Niño. The starting model involves coupled atmosphere-ocean processes that are deterministic, linear, and stable. Then, systematic strategies are developed for incorporating several major mechanisms of the CP El Niño into the coupled system. First, simple nonlinear zonal advection with no ad hoc parameterization of the background SST gradient is introduced that creates coupled nonlinear advective modes of the SST. Secondly, due to the recent multidecadal strengthening of the easterly trade wind, a stochastic parameterization of the wind bursts including a mean easterly trade wind anomaly is coupled to the simple atmosphere-ocean processes. Effective stochastic noise in the wind burst model facilitates the intermittent occurrence of the CP El Niño with realistic amplitude and duration. In addition to the anomalous warm SST in the central Pacific, other major features of the CP El Niño such as the rising branch of the anomalous Walker circulation being shifted to the central Pacific and the eastern Pacific cooling with a shallow thermocline are all captured by this simple coupled model. Importantly, the coupled model succeeds in simulating a series of CP El Niño that lasts for 5 y, which resembles the two CP El Niño episodes during 1990-1995 and 2002-2006.

  6. The Progressive BSSG Rat Model of Parkinson's: Recapitulating Multiple Key Features of the Human Disease.

    Science.gov (United States)

    Van Kampen, Jackalina M; Baranowski, David C; Robertson, Harold A; Shaw, Christopher A; Kay, Denis G

    2015-01-01

    The development of effective neuroprotective therapies for Parkinson's disease (PD) has been severely hindered by the notable lack of an appropriate animal model for preclinical screening. Indeed, most models currently available are either acute in nature or fail to recapitulate all characteristic features of the disease. Here, we present a novel progressive model of PD, with behavioural and cellular features that closely approximate those observed in patients. Chronic exposure to dietary phytosterol glucosides has been found to be neurotoxic. When fed to rats, β-sitosterol β-d-glucoside (BSSG) triggers the progressive development of parkinsonism, with clinical signs and histopathology beginning to appear following cessation of exposure to the neurotoxic insult and continuing to develop over several months. Here, we characterize the progressive nature of this model, its non-motor features, the anatomical spread of synucleinopathy, and response to levodopa administration. In Sprague Dawley rats, chronic BSSG feeding for 4 months triggered the progressive development of a parkinsonian phenotype and pathological events that evolved slowly over time, with neuronal loss beginning only after toxin exposure was terminated. At approximately 3 months following initiation of BSSG exposure, animals displayed the early emergence of an olfactory deficit, in the absence of significant dopaminergic nigral cell loss or locomotor deficits. Locomotor deficits developed gradually over time, initially appearing as locomotor asymmetry and developing into akinesia/bradykinesia, which was reversed by levodopa treatment. Late-stage cognitive impairment was observed in the form of spatial working memory deficits, as assessed by the radial arm maze. In addition to the progressive loss of TH+ cells in the substantia nigra, the appearance of proteinase K-resistant intracellular α-synuclein aggregates was also observed to develop progressively, appearing first in the olfactory bulb, then

  7. A study of key features of random atmospheric disturbance models for the approach flight phase

    Science.gov (United States)

    Heffley, R. K.

    1977-01-01

    An analysis and brief simulator experiment were performed to identify and classify important features of random turbulence for the landing approach flight phase. The analysis of various wind models was carried out within the context of the longitudinal closed-loop pilot/vehicle system. The analysis demonstrated the relative importance of atmospheric disturbance scale lengths, horizontal versus vertical gust components, decreasing altitude, and spectral forms of disturbances versus the pilot/vehicle system. Among certain competing wind models, the analysis predicted no significant difference in pilot performance. This was confirmed by a moving base simulator experiment which evaluated the two most extreme models. A number of conclusions were reached: attitude constrained equations do provide a simple but effective approach to describing the closed-loop pilot/vehicle. At low altitudes the horizontal gust component dominates pilot/vehicle performance.

  8. The Progressive BSSG Rat Model of Parkinson's: Recapitulating Multiple Key Features of the Human Disease.

    Directory of Open Access Journals (Sweden)

    Jackalina M Van Kampen

    Full Text Available The development of effective neuroprotective therapies for Parkinson's disease (PD has been severely hindered by the notable lack of an appropriate animal model for preclinical screening. Indeed, most models currently available are either acute in nature or fail to recapitulate all characteristic features of the disease. Here, we present a novel progressive model of PD, with behavioural and cellular features that closely approximate those observed in patients. Chronic exposure to dietary phytosterol glucosides has been found to be neurotoxic. When fed to rats, β-sitosterol β-d-glucoside (BSSG triggers the progressive development of parkinsonism, with clinical signs and histopathology beginning to appear following cessation of exposure to the neurotoxic insult and continuing to develop over several months. Here, we characterize the progressive nature of this model, its non-motor features, the anatomical spread of synucleinopathy, and response to levodopa administration. In Sprague Dawley rats, chronic BSSG feeding for 4 months triggered the progressive development of a parkinsonian phenotype and pathological events that evolved slowly over time, with neuronal loss beginning only after toxin exposure was terminated. At approximately 3 months following initiation of BSSG exposure, animals displayed the early emergence of an olfactory deficit, in the absence of significant dopaminergic nigral cell loss or locomotor deficits. Locomotor deficits developed gradually over time, initially appearing as locomotor asymmetry and developing into akinesia/bradykinesia, which was reversed by levodopa treatment. Late-stage cognitive impairment was observed in the form of spatial working memory deficits, as assessed by the radial arm maze. In addition to the progressive loss of TH+ cells in the substantia nigra, the appearance of proteinase K-resistant intracellular α-synuclein aggregates was also observed to develop progressively, appearing first in the

  9. A study of key features of the RAE atmospheric turbulence model

    Science.gov (United States)

    Jewell, W. F.; Heffley, R. K.

    1978-01-01

    A complex atmospheric turbulence model for use in aircraft simulation is analyzed in terms of its temporal, spectral, and statistical characteristics. First, a direct comparison was made between cases of the RAE model and the more conventional Dryden turbulence model. Next the control parameters of the RAE model were systematically varied and the effects noted. The RAE model was found to possess a high degree of flexibility in its characteristics, but the individual control parameters are cross-coupled in terms of their effect on various measures of intensity, bandwidth, and probability distribution.

  10. Key features of the IPSL ocean atmosphere model and its sensitivity to atmospheric resolution

    Energy Technology Data Exchange (ETDEWEB)

    Marti, Olivier; Braconnot, P.; Bellier, J.; Brockmann, P.; Caubel, A.; Noblet, N. de; Friedlingstein, P.; Idelkadi, A.; Kageyama, M. [Unite Mixte CEA-CNRS-UVSQ, IPSL/LSCE, Gif-sur-Yvette Cedex (France); Dufresne, J.L.; Bony, S.; Codron, F.; Fairhead, L.; Grandpeix, J.Y.; Hourdin, F.; Musat, I. [Unite Mixte CNRS-Ecole Polytechnique-ENS-UPCM, IPSL/LMD, Paris Cedex 05 (France); Benshila, R.; Guilyardi, E.; Levy, C.; Madec, G.; Mignot, J.; Talandier, C. [unite mixte CNRS-IRD-UPMC, IPLS/LOCEAN, Paris Cedex 05 (France); Cadule, P.; Denvil, S.; Foujols, M.A. [Institut Pierre Simon Laplace des Sciences de l' Environnement (IPSL), Paris Cedex 05 (France); Fichefet, T.; Goosse, H. [Universite Catholique de Louvain, Institut d' Astronomie et de Geophysique Georges Lemaitre, Louvain-la-Neuve (Belgium); Krinner, G. [Unite mixte CNRS-UJF Grenoble, LGGE, BP96, Saint-Martin-d' Heres (France); Swingedouw, D. [CNRS/CERFACS, Toulouse (France)

    2010-01-15

    This paper presents the major characteristics of the Institut Pierre Simon Laplace (IPSL) coupled ocean-atmosphere general circulation model. The model components and the coupling methodology are described, as well as the main characteristics of the climatology and interannual variability. The model results of the standard version used for IPCC climate projections, and for intercomparison projects like the Paleoclimate Modeling Intercomparison Project (PMIP 2) are compared to those with a higher resolution in the atmosphere. A focus on the North Atlantic and on the tropics is used to address the impact of the atmosphere resolution on processes and feedbacks. In the North Atlantic, the resolution change leads to an improved representation of the storm-tracks and the North Atlantic oscillation. The better representation of the wind structure increases the northward salt transports, the deep-water formation and the Atlantic meridional overturning circulation. In the tropics, the ocean-atmosphere dynamical coupling, or Bjerknes feedback, improves with the resolution. The amplitude of ENSO (El Nino-Southern oscillation) consequently increases, as the damping processes are left unchanged. (orig.)

  11. A Detailed Data-Driven Network Model of Prefrontal Cortex Reproduces Key Features of In Vivo Activity.

    Science.gov (United States)

    Hass, Joachim; Hertäg, Loreen; Durstewitz, Daniel

    2016-05-01

    The prefrontal cortex is centrally involved in a wide range of cognitive functions and their impairment in psychiatric disorders. Yet, the computational principles that govern the dynamics of prefrontal neural networks, and link their physiological, biochemical and anatomical properties to cognitive functions, are not well understood. Computational models can help to bridge the gap between these different levels of description, provided they are sufficiently constrained by experimental data and capable of predicting key properties of the intact cortex. Here, we present a detailed network model of the prefrontal cortex, based on a simple computationally efficient single neuron model (simpAdEx), with all parameters derived from in vitro electrophysiological and anatomical data. Without additional tuning, this model could be shown to quantitatively reproduce a wide range of measures from in vivo electrophysiological recordings, to a degree where simulated and experimentally observed activities were statistically indistinguishable. These measures include spike train statistics, membrane potential fluctuations, local field potentials, and the transmission of transient stimulus information across layers. We further demonstrate that model predictions are robust against moderate changes in key parameters, and that synaptic heterogeneity is a crucial ingredient to the quantitative reproduction of in vivo-like electrophysiological behavior. Thus, we have produced a physiologically highly valid, in a quantitative sense, yet computationally efficient PFC network model, which helped to identify key properties underlying spike time dynamics as observed in vivo, and can be harvested for in-depth investigation of the links between physiology and cognition.

  12. Image feature meaning for automatic key-frame extraction

    Science.gov (United States)

    Di Lecce, Vincenzo; Guerriero, Andrea

    2003-12-01

    Video abstraction and summarization, being request in several applications, has address a number of researches to automatic video analysis techniques. The processes for automatic video analysis are based on the recognition of short sequences of contiguous frames that describe the same scene, shots, and key frames representing the salient content of the shot. Since effective shot boundary detection techniques exist in the literature, in this paper we will focus our attention on key frames extraction techniques to identify the low level visual features of the frames that better represent the shot content. To evaluate the features performance, key frame automatically extracted using these features, are compared to human operator video annotations.

  13. Model Checking Feature Interactions

    DEFF Research Database (Denmark)

    Le Guilly, Thibaut; Olsen, Petur; Pedersen, Thomas;

    2015-01-01

    This paper presents an offline approach to analyzing feature interactions in embedded systems. The approach consists of a systematic process to gather the necessary information about system components and their models. The model is first specified in terms of predicates, before being refined to t...... to timed automata. The consistency of the model is verified at different development stages, and the correct linkage between the predicates and their semantic model is checked. The approach is illustrated on a use case from home automation....

  14. Key Features of the Manufacturing Vision Development Process

    DEFF Research Database (Denmark)

    Dukovska-Popovska, Iskra; Riis, Jens Ove; Boer, Harry

    2005-01-01

    This paper discusses the key features of the process of Manufacturing Vision Development, a process that enables companies to develop their future manufacturing concept. The basis for the process is a generic five-phase methodology (Riis and Johansen 2003) developed as a result of ten years...... of action research. The methodology recommends wide participation of people from different hierarchical and functional positions, who engage in a relatively short, playful and creative process and come up with a vision (concept) for the future manufacturing system in the company. Based on three case studies...... of companies going through the initial phases of the methodology, this research identified the key features of the Manufacturing Vision Development process. The paper elaborates the key features by defining them, discussing how and when they can appear, and how they influence the process....

  15. VIRTUAL KEY FORCE – A NEW FEATURE FOR KEYSTROKE

    Directory of Open Access Journals (Sweden)

    D. SHANMUGAPRIYA

    2011-10-01

    Full Text Available Securing the sensitive data and computer systems by allowing ease access to authenticated users and withstanding the attacks of imposters is one of the major challenges in the field of computer security. Traditionally, ID and password are most widely used method for authenticating the computer systems. But, this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary dttack, guessing, phishing and many more. Keystroke Dynamics is one of the famous and inexpensive behavioralbiometric technologies, which will try to identify the authenticity of a user when the user is working via a keyboard. There are many features that can be acquired using keystroke a feature. Force of Key type is one of the features which can be obtained using a special force sensitive keyboard which is expensive. The virtual keyforce is measured without using any special key board which also improves the accuracy when the feature is used for classification.

  16. Feature Technology in Product Modeling

    Institute of Scientific and Technical Information of China (English)

    ZHANG Xu; NING Ruxin

    2006-01-01

    A unified feature definition is proposed. Feature is form-concentrated, and can be used to model product functionalities, assembly relations, and part geometries. The feature model is given and a feature classification is introduced including functional, assembly, structural, and manufacturing features. A prototype modeling system is developed in Pro/ENGINEER that can define the assembly and user-defined form features.

  17. Unscrambling Key Features of TED as Open Educational Resources

    Institute of Scientific and Technical Information of China (English)

    汪静静; QIU; Cai-zhen

    2015-01-01

    TED is a particularly thriving branch in the campaign of Open Educational Resources,leading future educational revolution.What makes TED distinguished from other agents of open educational resources is worth studying.This paper studies key features of TED talks that help to explain why TED talks are so appealing,provide deeper look at TED and explore its value.

  18. Amyloid beta deposition and phosphorylated tau accumulation are key features in aged choroidal vessels in the complement factor H knock out model of retinal degeneration.

    Science.gov (United States)

    Aboelnour, Asmaa; Kam, Jaimie Hoh; Elnasharty, M A; Sayed-Ahmed, Ahmed; Jeffery, Glen

    2016-06-01

    Extra-cellular deposition including amyloid beta (Aβ) is a feature of retinal ageing. It has been documented for Bruch's membrane (BM) where Aβ is elevated in complement factor H knockout mice (Cfh(-/-)) proposed as a model for age related macular degeneration. However, arterial deposition in choroidal vessels prior to perfusion across BM has not been examined. Aβ is associated with tau phosphorylation and these are linked in blood vessels in Alzheimers Disease where they can drive perivascular pathology. Here we ask if Aβ, tau and phosphorylated tau are features of ageing in choroidal vessels in 12 month C57 BL/6 and Cfh(-/-) mice, using immune staining and Western blot analysis. Greater levels of Aβ and phosphorylated tau are found in choroidal vessels in Cfh(-/-) mice. Western blot revealed a 40% increase in Aβ in Cfh(-/-) over C57 BL/6 mice. Aβ deposits coat around 55% of the luminal wall in Cfh(-/-) compared to only about 40% in C57 BL/6. Total tau was similar in both groups, but phosphorylated tau increased by >100% in Cfh(-/-) compared to C57 BL/6 and covered >75% of the luminal wall compared to 50% in C57 BL/6. Hence, phosphorylated tau is a marked choroidal feature in this mouse model. Aβ deposition was clumped in Cfh(-/-) mice and likely to influence blood flow dynamics. Disturbed flow is associated with atherogenesis and may be related to the accumulation of membrane attack complex recently identified between choroidal vessels in those at high risk of macular degeneration due to complement factor H polymorphisms.

  19. A preclinical orthotopic model for glioblastoma recapitulates key features of human tumors and demonstrates sensitivity to a combination of MEK and PI3K pathway inhibitors.

    Science.gov (United States)

    El Meskini, Rajaa; Iacovelli, Anthony J; Kulaga, Alan; Gumprecht, Michelle; Martin, Philip L; Baran, Maureen; Householder, Deborah B; Van Dyke, Terry; Weaver Ohler, Zoë

    2015-01-01

    Current therapies for glioblastoma multiforme (GBM), the highest grade malignant brain tumor, are mostly ineffective, and better preclinical model systems are needed to increase the successful translation of drug discovery efforts into the clinic. Previous work describes a genetically engineered mouse (GEM) model that contains perturbations in the most frequently dysregulated networks in GBM (driven by RB, KRAS and/or PI3K signaling and PTEN) that induce development of Grade IV astrocytoma with properties of the human disease. Here, we developed and characterized an orthotopic mouse model derived from the GEM that retains the features of the GEM model in an immunocompetent background; however, this model is also tractable and efficient for preclinical evaluation of candidate therapeutic regimens. Orthotopic brain tumors are highly proliferative, invasive and vascular, and express histology markers characteristic of human GBM. Primary tumor cells were examined for sensitivity to chemotherapeutics and targeted drugs. PI3K and MAPK pathway inhibitors, when used as single agents, inhibited cell proliferation but did not result in significant apoptosis. However, in combination, these inhibitors resulted in a substantial increase in cell death. Moreover, these findings translated into the in vivo orthotopic model: PI3K or MAPK inhibitor treatment regimens resulted in incomplete pathway suppression and feedback loops, whereas dual treatment delayed tumor growth through increased apoptosis and decreased tumor cell proliferation. Analysis of downstream pathway components revealed a cooperative effect on target downregulation. These concordant results, together with the morphologic similarities to the human GBM disease characteristics of the model, validate it as a new platform for the evaluation of GBM treatment.

  20. On some key features of Ada : Language and programming environment

    Science.gov (United States)

    Wehrum, R. P.; Hoyer, W.; Dießl, G.

    1986-08-01

    The present paper focuses upon those aspects of the Ada language whose purpose is to support the discipline of software engineering. It illustrates the use of Ada features for various forms of abstraction, separate compilation, exception handling and tasking and highlights the importance of separating the definition of a module interface from its implementation. It demonstrates the use of the package concept to realize information hiding, data encapsulation and abstract data types. Some key aspects of Ada numerics are dealt with briefly. The paper continues by providing an overview of the Ada programming environments, their history and their relationship to the CAIS interface. Finally, the special importance of the interactive debugger within such an environment is presented.

  1. Using AI to understand key success features in evolving CTSAs.

    Science.gov (United States)

    Kusch, Jennifer D; Nelson, David A; Simpson, Deborah; Gerrits, Ronald; Glass, Laurie

    2013-08-01

    A vital role for Clinical and Translational Science Award (CTSA) evaluators is to first identify and then articulate the necessary change processes that support the research infrastructures and achieve synergies needed to improve health through research. The use of qualitative evaluation strategies to compliment quantitative tracking measures (e.g., number of grants/publications) is an essential but under-utilized approach in CTSA evaluations. The Clinical and Translational Science Institute of Southeast Wisconsin implemented a qualitative evaluation approach using appreciative inquiry (AI) that has revealed three critical features associated with CTSA infrastructure transformation success: developing open communication, creating opportunities for proactive collaboration, and ongoing attainment of milestones at the key function group level. These findings are consistent with Bolman & Deal's four interacting hallmarks of successful organizations: structural (infrastructure), political (power distribution; organizational politics), human resource (facilitating change among humans necessary for continued success), and symbolic (visions and aspirations). Data gathered through this longitudinal AI approach illuminates how these change features progress over time as CTSA funded organizations successfully create the multiinstitutional infrastructures to connect laboratory discoveries with the diagnosis and treatment of human disease.

  2. Effects of a Video Model to Teach Students with Moderate Intellectual Disability to Use Key Features of an iPhone

    Science.gov (United States)

    Walser, Kathryn; Ayres, Kevin; Foote, Erika

    2012-01-01

    This study evaluated the effects of video modeling on teaching three high school students with moderate intellectual disability to perform three activities on an iPhone 3GS. This study is a replication and extension of the Hammond, Whatley, Ayres, and Gast (2010) study in which researchers taught this same set of skills using a slightly different…

  3. Features of follicle-stimulating hormone-stimulated follicles in a sheep model: keys to elucidate embryo failure in assisted reproductive technique cycles.

    Science.gov (United States)

    Veiga-Lopez, Almudena; Dominguez, Veronica; Souza, Carlos J H; Garcia-Garcia, Rosa M; Ariznavarreta, Carmen; Tresguerres, Jesus A F; McNeilly, Alan S; Gonzalez-Bulnes, Antonio

    2008-05-01

    To evaluate the individual functionality of gonadotropin-stimulated preovulatory follicles, for understanding embryo failure in assisted reproductive technique cycles, in a sheep model. Observational, model study. Public research unit. Fifteen adult Manchega ewes. Synchronization of the estrous cycle with intravaginal progestagens and ovarian stimulation with FSH; evaluation of reproductive activity, plasma sampling, ovarian ultrasonography, and ovariectomies. Determination of estrus behavior, plasma and intrafollicular concentrations of E(2) and inhibin A, number and size of ovarian follicles, and developmental competence of oocytes. These results support the usefulness of serial measurements of plasma inhibin A for assessment of follicular growth during the FSH treatment, rather than of E(2) assays commonly used. Functionality of FSH-stimulated preovulatory follicles is clearly disturbed, as confirmed by a negative correlation between follicular size and intrafollicular concentrations of inhibin A and E(2) in preovulatory follicles after individual dissection; moreover, the ability of their oocytes to resume meiosis was diminished. Functionality of follicles in controlled ovarian stimulation (COS), and developmental competence of their oocytes, is disturbed by the high doses of gonadotropin supplied and finally determined by follicular sizes at starting FSH treatment.

  4. Preliminary safety analysis for key design features of KALIMER-600

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Y. B.; Chang, W. P.; Suk, S. D.; Ha, K. S.; Jeong, H. Y.; Heo, S

    2004-03-01

    KAERI is developing the conceptual design of a Liquid Metal Reactor, KALIMER-600 (Korea Advanced LIquid MEtal Reactor) under the Long-term Nuclear R and D Program. KALIMER-600 addresses key issues regarding future nuclear power plants such as plant safety, economics, proliferation, and waste. In this report, key safety design features are described and safety analyses results for typical ATWS accidents in the KALIMER design with breakeven core are presented. First, the basic approach to achieve the safety goal is introduced in Chapter 1, and the event categorization and acceptance criteria for the KALIMER-600 safety analysis are described in Chapter 2. In Chapter 3, results of inherent safety evaluations for the KALIMER-600 conceptual design are presented. The KALIMER-600 core and plant system are designed to assure benign performance during a selected set of events without either reactor control or protection system intervention. Safety analyses for the postulated Anticipated Transient Without Scram (ATWS) have been performed using the SSC-K code to investigate the KALIMER-600 system response to the events. They are categorized as Bounding Events (BEs) because of their low probability of occurrence. In Chapter 4, the analysis of flow blockage for KALIMER-600 with the MATRA-LMR-FB code, which has been developed for the internal flow blockage in a LMR subassembly. The cases with a blockage of 6-subchannel, 24-subchannel, and 54-subchannel are analyzed.The performance analysis of the KALIMER-600 containment and some evaluations for the behaviors during HCDA will be performed later.

  5. Genomic Feature Models

    DEFF Research Database (Denmark)

    Sørensen, Peter; Edwards, Stefan McKinnon; Rohde, Palle Duun

    Whole-genome sequences and multiple trait phenotypes from large numbers of individuals will soon be available in many populations. Well established statistical modeling approaches enable the genetic analyses of complex trait phenotypes while accounting for a variety of additive and non-additive g...... regions and gene ontologies) that provide better model fit and increase predictive ability of the statistical model for this trait....

  6. Fabled IBM Tank nears launch without key features

    CERN Multimedia

    2003-01-01

    "IBM is preparing to roll out the TotalStorage SAN File System, the ballyhooed, renamed, much delayed Storage Tank the company's been working on for ages, although it now appears some of its key capabilities won't appear until next year in a later version" (1 page).

  7. The idiopathic interstitial pneumonias: understanding key radiological features

    Energy Technology Data Exchange (ETDEWEB)

    Dixon, S. [Department of Radiology, Churchill Hospital, Old Road, Oxford OX3 7LJ (United Kingdom); Benamore, R., E-mail: Rachel.Benamore@orh.nhs.u [Department of Radiology, Churchill Hospital, Old Road, Oxford OX3 7LJ (United Kingdom)

    2010-10-15

    Many radiologists find it challenging to distinguish between the different interstitial idiopathic pneumonias (IIPs). The British Thoracic Society guidelines on interstitial lung disease (2008) recommend the formation of multidisciplinary meetings, with diagnoses made by combined radiological, pathological, and clinical findings. This review focuses on understanding typical and atypical radiological features on high-resolution computed tomography between the different IIPs, to help the radiologist determine when a confident diagnosis can be made and how to deal with uncertainty.

  8. Interactive Inconsistency Fixing in Feature Modeling

    Institute of Scientific and Technical Information of China (English)

    王波; 熊英飞; 胡振江; 赵海燕; 张伟; 梅宏

    2014-01-01

    Feature models have been widely adopted to reuse the requirements of a set of similar products in a domain. In feature models’ construction, one basic task is to ensure the consistency of feature models, which often involves detecting and fixing of inconsistencies in feature models. While many approaches have been proposed, most of them focus on detecting inconsistencies rather than fixing inconsistencies. In this paper, we propose a novel dynamic-priority based approach to interactively fixing inconsistencies in feature models, and report an implementation of a system that not only automatically recommends a solution to fixing inconsistencies but also supports domain analysts to gradually reach the desirable solution by dynamically adjusting priorities of constraints. The key technical contribution is, as far as we are aware, the first application of the constraint hierarchy theory to feature modeling, where the degree of domain analysts’ confidence on constraints is expressed by using priority and inconsistencies are resolved by deleting one or more lower-priority constraints. Two case studies demonstrate the usability and scalability (effciency) of our new approach.

  9. CHANGE MANAGEMENT IS A KEY FEATURE OF INNOVATIONAL PERSONNEL MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Buntovskiy S. Y.

    2016-04-01

    Full Text Available The article examines organizational and economic preconditions of the increasing of innovative activity of the personnel of a company in the modern conditions of managing. We have substantiated conclusions about the necessity and the importance of the development and the implementation of the corporate system of innovative-personnel management at the production level. We present specific proposals on the formation of the key system-oriented blocks, the basic elements of which in their totality and interconnection will contribute to efficient implementation of management decisions on innovative capacity of production through the change in labor behavior

  10. Defining Key Features of the Broad Autism Phenotype

    Science.gov (United States)

    Losh, Molly; Childress, Debra; Lam, Kristen; Piven, Joseph

    2009-01-01

    This study examined the frequency of personality, language, and social-behavioral characteristics believed to comprise the broad autism phenotype (BAP), across families differing in genetic liability to autism. We hypothesized that within this unique sample comprised of multiple-incidence autism families (MIAF), single-incidence autism families (SIAF), and control Down syndrome families (DWNS), a graded expression would be observed for the principal characteristics conferring genetic susceptibility to autism, in which such features would express most profoundly among parents from MIAFs, less strongly among SIAFs, and least of all among comparison parents from DWNS families, who should display population base rates. Analyses detected linear expression of traits in line with hypotheses, and further suggested differential intrafamilial expression across family types. In the vast majority of MIAFs both parents displayed BAP characteristics, whereas within SIAFs, it was equally likely that one, both, or neither parent show BAP features. The significance of these findings is discussed in relation to etiologic mechanisms in autism and relevance to molecular genetic studies. PMID:17948871

  11. Key features of Ebola hemorrhagic fever:a review

    Institute of Scientific and Technical Information of China (English)

    zulane; Lima; sousa

    2014-01-01

    The current outbreak of Ebola virus in West Africa has become a devastating problem.with a mortality rate around 51%;over 3132 deaths have been confirmed and even more arc expected in this case.The virus causes a characteristic disease known as hemorrhagic fever.Its symptoms range from nonspecific signs such as fever,lo more specific problems such as serious bleeding.Transmission occurs easily when a person comes in contact with contaminated fluids.Treatment is supportive because there are still no specific drugs for use.The present review focuses on the main features related to the Ebola virus,its transmission,pathogenesis,treatment and control forms.There is little in-depth knowledge about this disease,but its severily requires attention and information lo prevent a worse scenario than the current.

  12. Key features of Ebola hemorrhagic fever:a review

    Institute of Scientific and Technical Information of China (English)

    Zulane Lima Sousa

    2014-01-01

    The current outbreak of Ebola virus in West Africa has become a devastating problem, with a mortality rate around 51%; over 3132 deaths have been confirmed and even more are expected in this case. The virus causes a characteristic disease known as hemorrhagic fever. Its symptoms range from nonspecific signs such as fever, to more specific problems such as serious bleeding. Transmission occurs easily when a person comes in contact with contaminated fluids. Treatment is supportive because there are still no specific drugs for use. The present review focuses on the main features related to the Ebola virus, its transmission, pathogenesis, treatment and control forms. There is little in-depth knowledge about this disease, but its severity requires attention and information to prevent a worse scenario than the current.

  13. A Model of Hierarchical Key Assignment Scheme

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhigang; ZHAO Jing; XU Maozhi

    2006-01-01

    A model of the hierarchical key assignment scheme is approached in this paper, which can be used with any cryptography algorithm. Besides, the optimal dynamic control property of a hierarchical key assignment scheme will be defined in this paper. Also, our scheme model will meet this property.

  14. Key Features of Intertidal Food Webs That Support Migratory Shorebirds

    Science.gov (United States)

    Saint-Béat, Blanche; Dupuy, Christine; Bocher, Pierrick; Chalumeau, Julien; De Crignis, Margot; Fontaine, Camille; Guizien, Katell; Lavaud, Johann; Lefebvre, Sébastien; Montanié, Hélène; Mouget, Jean-Luc; Orvain, Francis; Pascal, Pierre-Yves; Quaintenne, Gwenaël; Radenac, Gilles; Richard, Pierre; Robin, Frédéric; Vézina, Alain F.; Niquil, Nathalie

    2013-01-01

    The migratory shorebirds of the East Atlantic flyway land in huge numbers during a migratory stopover or wintering on the French Atlantic coast. The Brouage bare mudflat (Marennes-Oléron Bay, NE Atlantic) is one of the major stopover sites in France. The particular structure and function of a food web affects the efficiency of carbon transfer. The structure and functioning of the Brouage food web is crucial for the conservation of species landing within this area because it provides sufficient food, which allows shorebirds to reach the north of Europe where they nest. The aim of this study was to describe and understand which food web characteristics support nutritional needs of birds. Two food-web models were constructed, based on in situ measurements that were made in February 2008 (the presence of birds) and July 2008 (absence of birds). To complete the models, allometric relationships and additional data from the literature were used. The missing flow values of the food web models were estimated by Monte Carlo Markov Chain – Linear Inverse Modelling. The flow solutions obtained were used to calculate the ecological network analysis indices, which estimate the emergent properties of the functioning of a food-web. The total activities of the Brouage ecosystem in February and July are significantly different. The specialisation of the trophic links within the ecosystem does not appear to differ between the two models. In spite of a large export of carbon from the primary producer and detritus in winter, the higher recycling leads to a similar retention of carbon for the two seasons. It can be concluded that in February, the higher activity of the ecosystem coupled with a higher cycling and a mean internal organization, ensure the sufficient feeding of the migratory shorebirds. PMID:24204666

  15. Preliminary safety analysis for key design features of KALIMER

    Energy Technology Data Exchange (ETDEWEB)

    Hahn, D. H.; Kwon, Y. M.; Chang, W. P.; Suk, S. D.; Lee, S. O.; Lee, Y. B.; Jeong, K. S

    2000-07-01

    KAERI is currently developing the conceptual design of a liquid metal reactor, KALIMER(Korea Advanced Liquid Metal Reactor) under the long-term nuclear R and D program. In this report, descriptions of the KALIMER safety design features and safety analyses results for selected ATWS accidents are presented. First, the basic approach to achieve the safety goal is introduced in chapter 1, and the safety evaluation procedure for the KALIMER design is described in chapter 2. It includes event selection, event categorization, description of design basis events, and beyond design basis events. In chapter 3, results of inherent safety evaluations for the KALIMER conceptual design are presented. The KALIMER core and plant system are designed to assure design performance during a selected set of events without either reactor control or protection system intervention. Safety analyses for the postulated anticipated transient without scram(ATWS) have been performed to investigate the KALIMER system response to the events. They are categorized as bounding events(BEs) because of their low probability of occurrence. In chapter 4, the design of the KALIMER containment dome and the results of its performance analysis are presented. The designs of the existing LMR containment and the KALIMER containment dome have been compared in this chapter. Procedure of the containment performance analysis and the analysis results are described along with the accident scenario and source terms. Finally, a simple methodology is introduced to investigate the core kinetics and hydraulic behavior during HCDA in chapter 5. Mathematical formulations have been developed in the framework of the modified bethe-tait method, and scoping analyses have been performed for the KALIMER core behavior during super-prompt critical excursions.

  16. Secured Cryptographic Key Generation From Multimodal Biometrics Feature Level Fusion Of Fingerprint And Iris

    CERN Document Server

    Jagadeesan, A

    2010-01-01

    Human users have a tough time remembering long cryptographic keys. Hence, researchers, for so long, have been examining ways to utilize biometric features of the user instead of a memorable password or passphrase, in an effort to generate strong and repeatable cryptographic keys. Our objective is to incorporate the volatility of the users biometric features into the generated key, so as to make the key unguessable to an attacker lacking significant knowledge of the users biometrics. We go one step further trying to incorporate multiple biometric modalities into cryptographic key generation so as to provide better security. In this article, we propose an efficient approach based on multimodal biometrics (Iris and fingerprint) for generation of secure cryptographic key. The proposed approach is composed of three modules namely, 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. Initially, the features, minutiae points and texture properties are extracted from...

  17. Secured Cryptographic Key Generation From Multimodal Biometrics: Feature Level Fusion of Fingerprint and Iris

    CERN Document Server

    Jagadeesan, A

    2010-01-01

    Human users have a tough time remembering long cryptographic keys. Hence, researchers, for so long, have been examining ways to utilize biometric features of the user instead of a memorable password or passphrase, in an effort to generate strong and repeatable cryptographic keys. Our objective is to incorporate the volatility of the user's biometric features into the generated key, so as to make the key unguessable to an attacker lacking significant knowledge of the user's biometrics. We go one step further trying to incorporate multiple biometric modalities into cryptographic key generation so as to provide better security. In this article, we propose an efficient approach based on multimodal biometrics (Iris and fingerprint) for generation of secure cryptographic key. The proposed approach is composed of three modules namely, 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. Initially, the features, minutiae points and texture properties are extracted fr...

  18. Aurones as histone deacetylase inhibitors: identification of key features.

    Science.gov (United States)

    Zwick, Vincent; Chatzivasileiou, Alkiviadis-Orfefs; Deschamps, Nathalie; Roussaki, Marina; Simões-Pires, Claudia A; Nurisso, Alessandra; Denis, Iza; Blanquart, Christophe; Martinet, Nadine; Carrupt, Pierre-Alain; Detsi, Anastasia; Cuendet, Muriel

    2014-12-01

    In this study, a total of 22 flavonoids were tested for their HDAC inhibitory activity using fluorimetric and BRET-based assays. Four aurones were found to be active in both assays and showed IC50 values below 20 μM in the enzymatic assay. Molecular modelling revealed that the presence of hydroxyl groups was responsible for good compound orientation within the isoenzyme catalytic site and zinc chelation.

  19. Key Features of the Deployed NPP/NPOESS Ground System

    Science.gov (United States)

    Heckmann, G.; Grant, K. D.; Mulligan, J. E.

    2010-12-01

    operations for NPP. C3S transitioned to operations at the NOAA Satellite Operations Facility (NSOF) in Suitland Maryland in August 2007 and IDPS transitioned in July 2009. Both segments were involved with several compatibility tests with the NPP Satellite at the Ball Aerospace Technology Corporation (BATC) factory. The compatibility tests involved the spacecraft bus, the four sensors (VIIRS, ATMS, CrIS and OMPS), and both ground segments flowing data between the NSOF and BATC factory and flowing data from the polar ground station (Svalbard) over high-speed links back to the NSOF and the two IDP locations (NESDIS & AFWA). This presentation will describe the NPP/NPOESS ground architecture features & enhancements for the NPOESS era. These will include C3S-provided space-to-ground connectivity, reliable and secure data delivery and insight & oversight of the total operation. For NPOESS the ground architecture is extended to provide additional ground receptor sites to reduce data product delivery times to users and delivery of additional sensor data products from sensors similar to NPP and more NPOESS sensors. This architecture is also extended from two Centrals (NESDIS & AFWA) to two additional Centrals (FNMOC & NAVO). IDPS acts as a buffer minimizing changes in how users request and receive data products.

  20. Component Composition Using Feature Models

    DEFF Research Database (Denmark)

    Eichberg, Michael; Klose, Karl; Mitschke, Ralf;

    2010-01-01

    In general, components provide and require services and two components are bound if the first component provides a service required by the second component. However, certain variability in services - w.r.t. how and which functionality is provided or required - cannot be described using standard...... interface description languages. If this variability is relevant when selecting a matching component then human interaction is required to decide which components can be bound. We propose to use feature models for making this variability explicit and (re-)enabling automatic component binding. In our...... approach, feature models are one part of service specifications. This enables to declaratively specify which service variant is provided by a component. By referring to a service's variation points, a component that requires a specific service can list the requirements on the desired variant. Using...

  1. Research on Digital Product Modeling Key Technologies of Digital Manufacturing

    Institute of Scientific and Technical Information of China (English)

    DING Guoping; ZHOU Zude; HU Yefa; ZHAO Liang

    2006-01-01

    With the globalization and diversification of the market and the rapid development of Information Technology (IT) and Artificial Intelligence (AI), the digital revolution of manufacturing is coming. One of the key technologies in digital manufacturing is product digital modeling. This paper firstly analyzes the information and features of the product digital model during each stage in the product whole lifecycle, then researches on the three critical technologies of digital modeling in digital manufacturing-product modeling, standard for the exchange of product model data and digital product data management. And the potential signification of the product digital model during the process of digital manufacturing is concluded-product digital model integrates primary features of each stage during the product whole lifecycle based on graphic features, applies STEP as data exchange mechanism, and establishes PDM system to manage the large amount, complicated and dynamic product data to implement the product digital model data exchange, sharing and integration.

  2. Key Features of Political Advertising as an Independent Type of Advertising Communication

    OpenAIRE

    Svetlana Anatolyevna Chubay

    2015-01-01

    To obtain the most complete understanding of the features of political advertising, the author characterizes its specific features allocated by modern researchers. The problem of defining the notion of political advertising is studied in detail. The analysis of definitions available in professional literature has allowed the author to identify a number of key features that characterize political advertising as an independent type of promotional activity. These features include belonging to th...

  3. From big data to rich data: The key features of athlete wheelchair mobility performance.

    Science.gov (United States)

    van der Slikke, R M A; Berger, M A M; Bregman, D J J; Veeger, H E J

    2016-10-03

    Quantitative assessment of an athlete׳s individual wheelchair mobility performance is one prerequisite needed to evaluate game performance, improve wheelchair settings and optimize training routines. Inertial Measurement Unit (IMU) based methods can be used to perform such quantitative assessment, providing a large number of kinematic data. The goal of this research was to reduce that large amount of data to a set of key features best describing wheelchair mobility performance in match play and present them in meaningful way for both scientists and athletes. To test the discriminative power, wheelchair mobility characteristics of athletes with different performance levels were compared. The wheelchair kinematics of 29 (inter-)national level athletes were measured during a match using three inertial sensors mounted on the wheelchair. Principal component analysis was used to reduce 22 kinematic outcomes to a set of six outcomes regarding linear and rotational movement; speed and acceleration; average and best performance. In addition, it was explored whether groups of athletes with known performance differences based on their impairment classification also differed with respect to these key outcomes using univariate general linear models. For all six key outcomes classification showed to be a significant factor (pperformance in match play. The key kinematic outcomes were displayed in an easy to interpret way, usable for athletes, coaches and scientists. This standardized representation enables comparison of different wheelchair sports regarding wheelchair mobility, but also evaluation at the level of an individual athlete. By this means, the tool could enhance further development of wheelchair sports in general.

  4. Key-Feature-Probleme zum Prüfen von prozeduralem Wissen: Ein Praxisleitfaden [Key Feature Problems for the assessment of procedural knowledge: a practical guide

    Directory of Open Access Journals (Sweden)

    Kopp, Veronika

    2006-08-01

    Full Text Available [english] After assigning the different examination formats to the diverse terms of Miller's pyramide of knowledge, this paper provides a short presentation of the key feature approach by giving the definition and an example for clarification. Afterwards, a practical guide to writing key feature problems is given consisting of the following steps: define the domain, choose a clinical situation, define the key features, develop a test case scenario, write questions, select a preferred response format, define the scoring key, and validation. Finally, we present the evaluation results of this practical guide. In sum, the participants were very pleased with it. The differences between the estimations of their knowledge before and after the workshop concerning key features were significant. The key feature approach is an innovative tool for assessing clinical decision-making skills, also for electronical examinations. Substituting the write-in format for the long-menu format allows an automatic data analysis. [german] Im vorliegenden Beitrag wird - nach der Zuordnung unterschiedlicher Prüfungsformen zu den verschiedenen Wissensarten der Wissenspyramide von Miller - der Key-Feature (KF Ansatz vorgestellt. Nachdem anhand der Definition und einem Beispiel erklärt wurde, was ein KF ist, wird im Anschluss eine Anleitung für die Erstellung eines KF-Problems gegeben. Diese besteht aus folgenden Schritten: Definition des Kontextes, Wahl der klinischen Situation, Identifikation der KFs des klinischen Problems, Schreiben des klinischen Szenarios (Fallvignette, Schreiben der einzelnen KF-Fragen, Auswahl des Antwortformates, Bewertungsverfahren und Inhaltsvalidierung. Am Ende werden die Ergebnisse einer Evaluation dieser Anleitung, die im Rahmen eines KF-Workshops gewonnen wurden, präsentiert. Die Teilnehmer waren mit dieser Workshopeinheit sehr zufrieden und gaben an, sehr viel gelernt zu haben. Die subjektive Einschätzung ihres Wissensstands vor und nach

  5. Human action classification using adaptive key frame interval for feature extraction

    Science.gov (United States)

    Lertniphonphan, Kanokphan; Aramvith, Supavadee; Chalidabhongse, Thanarat H.

    2016-01-01

    Human action classification based on the adaptive key frame interval (AKFI) feature extraction is presented. Since human movement periods are different, the action intervals that contain the intensive and compact motion information are considered in this work. We specify AKFI by analyzing an amount of motion through time. The key frame is defined to be the local minimum interframe motion, which is computed by using frame differencing between consecutive frames. Once key frames are detected, the features within a segmented period are encoded by adaptive motion history image and key pose history image. The action representation consists of the local orientation histogram of the features during AKFI. The experimental results on Weizmann dataset, KTH dataset, and UT Interaction dataset demonstrate that the features can effectively classify action and can classify irregular cases of walking compared to other well-known algorithms.

  6. Water Conservation Service Assessment and Its Spatiotemporal Features in National Key Ecological Function Zones

    Directory of Open Access Journals (Sweden)

    Jun Zhai

    2016-01-01

    Full Text Available In order to improve ecosystem service and protect nation ecology security, the government had designated lots of important ecosystem service protection areas, named national key ecological function zones (NKEFZ in China. Water conservation service had been assessed with the help of multisource remote sensing data, and spatiotemporal features were analyzed from 2000 to 2014 in these ecological services zones. By assuming precipitation scenario as the constant, contribution for water conservation from human activities and climate change was analyzed, and result shows that, because of vegetation restoration by human activities, evapotranspiration increased obviously with the increase of the vegetation coverage. This could reduce the water conservation. However, actual annual increase of water conservation mainly comes from the increase of precipitation. Our analysis revealed that the choice of evaluation model played a decisive role in the reason analysis, which would affect the development of ecological policy.

  7. Return of feature-based cost modeling

    Science.gov (United States)

    Creese, Robert C.; Patrawala, Taher B.

    1998-10-01

    Feature Based Cost Modeling is thought of as a relative new approach to cost modeling, but feature based cost modeling had considerable development in the 1950's. Considerable work was published in the 1950's by Boeing on cost for various casting processes--sand casting, die casting, investment casting and permanent mold casting--as a function of a single casting feature, casting volume. Additional approaches to feature based cost modeling have been made, and this work is a review of previous works and a proposed integrated model to feature based cost modeling.

  8. Soil fauna: key to new carbon models

    Science.gov (United States)

    Filser, Juliane; Faber, Jack H.; Tiunov, Alexei V.; Brussaard, Lijbert; Frouz, Jan; De Deyn, Gerlinde; Uvarov, Alexei V.; Berg, Matty P.; Lavelle, Patrick; Loreau, Michel; Wall, Diana H.; Querner, Pascal; Eijsackers, Herman; José Jiménez, Juan

    2016-11-01

    Soil organic matter (SOM) is key to maintaining soil fertility, mitigating climate change, combatting land degradation, and conserving above- and below-ground biodiversity and associated soil processes and ecosystem services. In order to derive management options for maintaining these essential services provided by soils, policy makers depend on robust, predictive models identifying key drivers of SOM dynamics. Existing SOM models and suggested guidelines for future SOM modelling are defined mostly in terms of plant residue quality and input and microbial decomposition, overlooking the significant regulation provided by soil fauna. The fauna controls almost any aspect of organic matter turnover, foremost by regulating the activity and functional composition of soil microorganisms and their physical-chemical connectivity with soil organic matter. We demonstrate a very strong impact of soil animals on carbon turnover, increasing or decreasing it by several dozen percent, sometimes even turning C sinks into C sources or vice versa. This is demonstrated not only for earthworms and other larger invertebrates but also for smaller fauna such as Collembola. We suggest that inclusion of soil animal activities (plant residue consumption and bioturbation altering the formation, depth, hydraulic properties and physical heterogeneity of soils) can fundamentally affect the predictive outcome of SOM models. Understanding direct and indirect impacts of soil fauna on nutrient availability, carbon sequestration, greenhouse gas emissions and plant growth is key to the understanding of SOM dynamics in the context of global carbon cycling models. We argue that explicit consideration of soil fauna is essential to make realistic modelling predictions on SOM dynamics and to detect expected non-linear responses of SOM dynamics to global change. We present a decision framework, to be further developed through the activities of KEYSOM, a European COST Action, for when mechanistic SOM models

  9. Classification Models for Symmetric Key Cryptosystem Identification

    Directory of Open Access Journals (Sweden)

    Shri Kant

    2012-01-01

    Full Text Available The present paper deals with the basic principle and theory behind prevalent classification models and their judicious application for symmetric key cryptosystem identification. These techniques have been implemented and verified on varieties of known and simulated data sets. After establishing the techniques the problems of cryptosystem identification have been addressed.Defence Science Journal, 2012, 62(1, pp.38-45, DOI:http://dx.doi.org/10.14429/dsj.62.1440

  10. Correlated Non-Parametric Latent Feature Models

    CERN Document Server

    Doshi-Velez, Finale

    2012-01-01

    We are often interested in explaining data through a set of hidden factors or features. When the number of hidden features is unknown, the Indian Buffet Process (IBP) is a nonparametric latent feature model that does not bound the number of active features in dataset. However, the IBP assumes that all latent features are uncorrelated, making it inadequate for many realworld problems. We introduce a framework for correlated nonparametric feature models, generalising the IBP. We use this framework to generate several specific models and demonstrate applications on realworld datasets.

  11. The role of key features in predator recognition by untrained birds.

    Science.gov (United States)

    Beránková, Jana; Veselý, Petr; Sýkorová, Jana; Fuchs, Roman

    2014-07-01

    The most important role in the recognition and categorization of predators (as well as other animals) is usually attributed to so-called key features. Under laboratory conditions, we tested the role of yellow eyes (specific for the genus Accipiter in European raptors) and hooked beak (common for all European birds of prey) in the recognition of the sparrowhawk (Accipiter nisus) by untrained great tits (Parus major) caught in the wild. Using wooden dummies, we interchanged either one of these potential key features or the body of the sparrowhawk (predator) and domestic pigeon (harmless bird). The tested tits showed three types of behaviour in the presence of the dummies: fear, interest without fear, and lack of interest. Eye interchange lowered fear of the sparrowhawk, but did not cause fear of the pigeon. Beak interchange did not lower fear of the sparrowhawk. Eye interchange caused increased interest in both species. Thus, a specific sparrowhawk feature is necessary for correct sparrowhawk dummy recognition but a general raptor feature is not. On the other hand, a specific sparrowhawk feature on a pigeon dummy is not enough to prompt sparrowhawk recognition. Thus, key features play an important, but not exclusive, role in predator recognition. An increased interest in some of the modified dummies implies that the tits have a general concept of a sparrowhawk. The individual variability in behaviour of tits is discussed.

  12. A multidimensional representation model of geographic features

    Science.gov (United States)

    Usery, E. Lynn; Timson, George; Coletti, Mark

    2016-01-28

    A multidimensional model of geographic features has been developed and implemented with data from The National Map of the U.S. Geological Survey. The model, programmed in C++ and implemented as a feature library, was tested with data from the National Hydrography Dataset demonstrating the capability to handle changes in feature attributes, such as increases in chlorine concentration in a stream, and feature geometry, such as the changing shoreline of barrier islands over time. Data can be entered directly, from a comma separated file, or features with attributes and relationships can be automatically populated in the model from data in the Spatial Data Transfer Standard format.

  13. Salient Key Features of Actual English Instructional Practices in Saudi Arabia

    Science.gov (United States)

    Al-Seghayer, Khalid

    2015-01-01

    This is a comprehensive review of the salient key features of the actual English instructional practices in Saudi Arabia. The goal of this work is to gain insights into the practices and pedagogic approaches to English as a foreign language (EFL) teaching currently employed in this country. In particular, we identify the following central features…

  14. Identifying Key Features of Student Performance in Educational Video Games and Simulations through Cluster Analysis

    Science.gov (United States)

    Kerr, Deirdre; Chung, Gregory K. W. K.

    2012-01-01

    The assessment cycle of "evidence-centered design" (ECD) provides a framework for treating an educational video game or simulation as an assessment. One of the main steps in the assessment cycle of ECD is the identification of the key features of student performance. While this process is relatively simple for multiple choice tests, when…

  15. A modified electronic key feature examination for undergraduate medical students: validation threats and opportunities.

    Science.gov (United States)

    Fischer, Martin R; Kopp, Veronika; Holzer, Matthias; Ruderich, Franz; Jünger, Jana

    2005-08-01

    The purpose of our study was the development and validation of a modified electronic key feature exam of clinical decision-making skills for undergraduate medical students. Therefore, the reliability of the test (15 items), the item difficulty level, the item-total correlations and correlations to other measures of knowledge (40 item MC-test and 580 items of German MC-National Licensing Exam, Part II) were calculated. Based on the guidelines provided by the Medical Council of Canada, a modified electronic key feature exam for internal medicine consisting of 15 key features (KFs) was developed for fifth year German medical students. Long menu (LM) and short menu (SM) question formats were used. Acceptance was assessed through a questionnaire. Thirty-seven students from four medical schools voluntarily participated in the study. The reliability of the key feature exam was 0.65 (Cronbach's alpha). The items' difficulty level scores were between 0.3 and 0.8 and the item-total correlations between 0.0 and 0.4. Correlations between the results of the KF exam and the other measures of knowledge were intermediate (r between 0.44 and 0.47) as well as the learners' level of acceptance. The modified electronic KF examination is a feasible and reliable evaluation tool that may be implemented for the assessment of clinical undergraduate training.

  16. Secure Biometric Key Generation Scheme for Cryptography using Combined Biometric Features of Fingerprint and Iris

    Directory of Open Access Journals (Sweden)

    Mr.P.Balakumar

    2011-09-01

    Full Text Available Exact and automatic recognition and authentication of users are a essential difficulty in all systems. Shared secrets like Personal Identification Numbers or Passwords and key devices such as Smart cards are not presently sufficient in few situations. What is required is a system that could authenticate that the person is actually the person. The biometrics is improving the capability to recognize the persons. The usage of biometrics system permits the recognition of a living person according to the physiological features or behavioral features to be recognized without human involvement. This leads to the world wide usage of biometrics to secure the system. The various biometrics used in securing system are fingerprint, iris, retina, etc. The construction of cryptographic key from biometrics is used generally to secure the system. The efficiency and the flexibility of the cryptographic make it suitable for securing purpose. In some times, biometrics can be stolen; this makes the attackers to access the system for any time. This problem is diminished in this paper by using two biometrics features. The biometrics used in this paper is fingerprint and iris. These two features are combined with the help of fusion algorithm. From the combined features, cryptographic key is generated. The experimental result shows that the proposed techniques results in better security than the existing techniques.

  17. A computational model for feature binding

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The "Binding Problem" is an important problem across many disciplines, including psychology, neuroscience, computational modeling, and even philosophy. In this work, we proposed a novel computational model, Bayesian Linking Field Model, for feature binding in visual perception, by combining the idea of noisy neuron model, Bayesian method, Linking Field Network and competitive mechanism. Simulation Experiments demonstrated that our model perfectly fulfilled the task of feature binding in visual perception and provided us some enlightening idea for future research.

  18. A computational model for feature binding

    Institute of Scientific and Technical Information of China (English)

    SHI ZhiWei; SHI ZhongZhi; LIU Xi; SHI ZhiPing

    2008-01-01

    The "Binding Problem" is an important problem across many disciplines, including psychology, neuroscience, computational modeling, and even philosophy. In this work, we proposed a novel computational model, Bayesian Linking Field Model, for feature binding in visual perception, by combining the idea of noisy neuron model, Bayesian method, Linking Field Network and competitive mechanism.Simulation Experiments demonstrated that our model perfectly fulfilled the task of feature binding in visual perception and provided us some enlightening idea for future research.

  19. Faceted interfaces: a key feature to quantitative understanding of transformation morphology

    Science.gov (United States)

    Zhang, Wen-Zheng; Gu, Xin-Fu; Dai, Fu-Zhi

    2016-09-01

    Faceted interfaces are a typical key feature of the morphology of many microstructures generated from solid-state phase transformations. Interpretation, prediction and simulation of this faceted morphology remain a challenge, especially for systems where irrational orientation relationships (ORs) between two phases and irrational interface orientations (IOs) are preferred. In terms of structural singularities, this work suggests an integrated framework, which possibly encompasses all candidates of faceted interfaces. The structural singularities are identified from a matching pattern, a dislocation structure and/or a ledge structure. The resultant singular interfaces have discrete IOs, described with low-index g's (rational orientations) and/or Δg's (either rational or irrational orientations). Various existing models are grouped according to their determined results regarding the OR and IO, and the links between the models are clarified in the integrated framework. Elimination of defect types as far as possible in a dominant singular interface often exerts a central restriction on the OR. An irrational IO is usually due to the elimination of dislocations in one direction, i.e., an O-line interface. Analytical methods using both three-dimensional and two-dimensional models for quantitative determinations of O-line interfaces are reviewed, and a detailed example showing the calculation for an irrational interface is given. The association between structural singularities and local energy minima is verified by atomistic calculations of interfacial energies in fcc/bcc alloys where it is found that the calculated equilibrium cross-sections are in a good agreement with observations from selected alloys.

  20. Genetic search feature selection for affective modeling

    DEFF Research Database (Denmark)

    Martínez, Héctor P.; Yannakakis, Georgios N.

    2010-01-01

    Automatic feature selection is a critical step towards the generation of successful computational models of affect. This paper presents a genetic search-based feature selection method which is developed as a global-search algorithm for improving the accuracy of the affective models built...

  1. Key Features of Political Advertising as an Independent Type of Advertising Communication

    Directory of Open Access Journals (Sweden)

    Svetlana Anatolyevna Chubay

    2015-09-01

    Full Text Available To obtain the most complete understanding of the features of political advertising, the author characterizes its specific features allocated by modern researchers. The problem of defining the notion of political advertising is studied in detail. The analysis of definitions available in professional literature has allowed the author to identify a number of key features that characterize political advertising as an independent type of promotional activity. These features include belonging to the forms of mass communication, implemented through different communication channels; the presence of characteristics typical of any advertising as a form of mass communication (strategies and concepts promoting the program, ideas; an integrated approach to the selection of communication channels, means and the methods of informing the addressers that focus on the audience; the formation of psychological attitude to voting; the image nature; the manipulative potential. It is shown that the influence is the primary function of political advertising – it determines the key characteristics common to this type of advertising. Political advertising, reflecting the essence of the political platform of certain political forces, setting up voters for their support, forming and introducing into the mass consciousness a definite idea of the character of these political forces, creates the desired psychological attitude to the voting. The analysis of definitions available in professional literature has allowed the author to formulate an operational definition of political advertising, which allowed to include the features that distinguish political advertising from other forms of political communication such as political PR which is traditionally mixed with political advertising.

  2. Genetic search feature selection for affective modeling

    DEFF Research Database (Denmark)

    Martínez, Héctor P.; Yannakakis, Georgios N.

    2010-01-01

    Automatic feature selection is a critical step towards the generation of successful computational models of affect. This paper presents a genetic search-based feature selection method which is developed as a global-search algorithm for improving the accuracy of the affective models built....... The method is tested and compared against sequential forward feature selection and random search in a dataset derived from a game survey experiment which contains bimodal input features (physiological and gameplay) and expressed pairwise preferences of affect. Results suggest that the proposed method...

  3. Global conservation outcomes depend on marine protected areas with five key features

    Science.gov (United States)

    Edgar, Graham J.; Stuart-Smith, Rick D.; Willis, Trevor J.; Kininmonth, Stuart; Baker, Susan C.; Banks, Stuart; Barrett, Neville S.; Becerro, Mikel A.; Bernard, Anthony T. F.; Berkhout, Just; Buxton, Colin D.; Campbell, Stuart J.; Cooper, Antonia T.; Davey, Marlene; Edgar, Sophie C.; Försterra, Günter; Galván, David E.; Irigoyen, Alejo J.; Kushner, David J.; Moura, Rodrigo; Parnell, P. Ed; Shears, Nick T.; Soler, German; Strain, Elisabeth M. A.; Thomson, Russell J.

    2014-02-01

    In line with global targets agreed under the Convention on Biological Diversity, the number of marine protected areas (MPAs) is increasing rapidly, yet socio-economic benefits generated by MPAs remain difficult to predict and under debate. MPAs often fail to reach their full potential as a consequence of factors such as illegal harvesting, regulations that legally allow detrimental harvesting, or emigration of animals outside boundaries because of continuous habitat or inadequate size of reserve. Here we show that the conservation benefits of 87 MPAs investigated worldwide increase exponentially with the accumulation of five key features: no take, well enforced, old (>10 years), large (>100km2), and isolated by deep water or sand. Using effective MPAs with four or five key features as an unfished standard, comparisons of underwater survey data from effective MPAs with predictions based on survey data from fished coasts indicate that total fish biomass has declined about two-thirds from historical baselines as a result of fishing. Effective MPAs also had twice as many large (>250mm total length) fish species per transect, five times more large fish biomass, and fourteen times more shark biomass than fished areas. Most (59%) of the MPAs studied had only one or two key features and were not ecologically distinguishable from fished sites. Our results show that global conservation targets based on area alone will not optimize protection of marine biodiversity. More emphasis is needed on better MPA design, durable management and compliance to ensure that MPAs achieve their desired conservation value.

  4. Featured Image: Modeling Supernova Remnants

    Science.gov (United States)

    Kohler, Susanna

    2016-05-01

    This image shows a computer simulation of the hydrodynamics within a supernova remnant. The mixing between the outer layers (where color represents the log of density) is caused by turbulence from the Rayleigh-Taylor instability, an effect that arises when the expanding core gas of the supernova is accelerated into denser shell gas. The past standard for supernova-evolution simulations was to perform them in one dimension and then, in post-processing, manually smooth out regions that undergo Rayleigh-Taylor turbulence (an intrinsically multidimensional effect). But in a recent study, Paul Duffell (University of California, Berkeley) has explored how a 1D model could be used to reproduce the multidimensional dynamics that occur in turbulence from this instability. For more information, check out the paper below!CitationPaul C. Duffell 2016 ApJ 821 76. doi:10.3847/0004-637X/821/2/76

  5. Cemento-osseous dysplasia of the jaw bones: key radiographic features.

    Science.gov (United States)

    Alsufyani, N A; Lam, E W N

    2011-03-01

    The purpose of this study is to assess possible diagnostic differences between general dentists (GPs) and oral and maxillofacial radiologists (RGs) in the identification of pathognomonic radiographic features of cemento-osseous dysplasia (COD) and its interpretation. Using a systematic objective survey instrument, 3 RGs and 3 GPs reviewed 50 image sets of COD and similarly appearing entities (dense bone island, cementoblastoma, cemento-ossifying fibroma, fibrous dysplasia, complex odontoma and sclerosing osteitis). Participants were asked to identify the presence or absence of radiographic features and then to make an interpretation of the images. RGs identified a well-defined border (odds ratio (OR) 6.67, P < 0.05); radiolucent periphery (OR 8.28, P < 0.005); bilateral occurrence (OR 10.23, P < 0.01); mixed radiolucent/radiopaque internal structure (OR 10.53, P < 0.01); the absence of non-concentric bony expansion (OR 7.63, P < 0.05); and the association with anterior and posterior teeth (OR 4.43, P < 0.05) as key features of COD. Consequently, RGs were able to correctly interpret 79.3% of COD cases. In contrast, GPs identified the absence of root resorption (OR 4.52, P < 0.05) and the association with anterior and posterior teeth (OR 3.22, P = 0.005) as the only key features of COD and were able to correctly interpret 38.7% of COD cases. There are statistically significant differences between RGs and GPs in the identification and interpretation of the radiographic features associated with COD (P < 0.001). We conclude that COD is radiographically discernable from other similarly appearing entities only if the characteristic radiographic features are correctly identified and then correctly interpreted.

  6. Preliminary safety analysis for key design features of KALIMER with breakeven core

    Energy Technology Data Exchange (ETDEWEB)

    Hahn, Do Hee; Kwon, Y. M.; Chang, W. P.; Suk, S. D.; Lee, Y. B.; Jeong, K. S

    2001-06-01

    KAERI is currently developing the conceptual design of a Liquid Metal Reactor, KALIMER (Korea Advanced Liquid MEtal Reactor) under the Long-term Nuclear R and D Program. KALIMER addresses key issues regarding future nuclear power plants such as plant safety, economics, proliferation, and waste. In this report, descriptions of safety design features and safety analyses results for selected ATWS accidents for the breakeven core KALIMER are presented. First, the basic approach to achieve the safety goal is introduced in Chapter 1, and the safety evaluation procedure for the KALIMER design is described in Chapter 2. It includes event selection, event categorization, description of design basis events, and beyond design basis events.In Chapter 3, results of inherent safety evaluations for the KALIMER conceptual design are presented. The KALIMER core and plant system are designed to assure benign performance during a selected set of events without either reactor control or protection system intervention. Safety analyses for the postulated anticipated transient without scram (ATWS) have been performed to investigate the KALIMER system response to the events. In Chapter 4, the design of the KALIMER containment dome and the results of its performance analyses are presented. The design of the existing containment and the KALIMER containment dome are compared in this chapter. Procedure of the containment performance analysis and the analysis results are described along with the accident scenario and source terms. Finally, a simple methodology is introduced to investigate the core energetics behavior during HCDA in Chapter 5. Sensitivity analyses have been performed for the KALIMER core behavior during super-prompt critical excursions, using mathematical formulations developed in the framework of the Modified Bethe-Tait method. Work energy potential was then calculated based on the isentropic fuel expansion model.

  7. Feature extraction for structural dynamics model validation

    Energy Technology Data Exchange (ETDEWEB)

    Hemez, Francois [Los Alamos National Laboratory; Farrar, Charles [Los Alamos National Laboratory; Park, Gyuhae [Los Alamos National Laboratory; Nishio, Mayuko [UNIV OF TOKYO; Worden, Keith [UNIV OF SHEFFIELD; Takeda, Nobuo [UNIV OF TOKYO

    2010-11-08

    This study focuses on defining and comparing response features that can be used for structural dynamics model validation studies. Features extracted from dynamic responses obtained analytically or experimentally, such as basic signal statistics, frequency spectra, and estimated time-series models, can be used to compare characteristics of structural system dynamics. By comparing those response features extracted from experimental data and numerical outputs, validation and uncertainty quantification of numerical model containing uncertain parameters can be realized. In this study, the applicability of some response features to model validation is first discussed using measured data from a simple test-bed structure and the associated numerical simulations of these experiments. issues that must be considered were sensitivity, dimensionality, type of response, and presence or absence of measurement noise in the response. Furthermore, we illustrate a comparison method of multivariate feature vectors for statistical model validation. Results show that the outlier detection technique using the Mahalanobis distance metric can be used as an effective and quantifiable technique for selecting appropriate model parameters. However, in this process, one must not only consider the sensitivity of the features being used, but also correlation of the parameters being compared.

  8. Modeling Course for Virtual University by Features

    Directory of Open Access Journals (Sweden)

    László Horváth

    2004-05-01

    Full Text Available Environments with large number of interrelated information uses several advanced concepts ascomputer description of different aspects of modeled objects in the form of feature basedmodels. In this case a set of features is defined then used for the purpose of modification of aninitial model to achieve a final model as a description of an instance of a well-defined complexobject from a real world environment. Utilization this approach and some relevant methodshave been investigated by the authors to establish course modeling in virtual universityenvironments. The main objective is definition generic model entities for courses and instancemodel entities for student course profiles. Course model entities describe virtual universityactivities. The modeling can be applied generally but it is being developed for the domain ofhigher education in virtual technologies. The paper introduces some virtual university relatedconcepts and the approach of the authors to virtual university. Following this feature drivenassociative model of virtual course developed by the authors is explained. Some issues aboutthe conceptualized application oriented virtual course features are discussed as a contributionto implementation of a virtual classroom model proposed by the authors. Finally, possibilitiesof integration of the university model with engineering modeling systems are discussed takinginto account present day virtual universities and possibilities to communicate with prospectivestudents both in professional design and home computer environments.

  9. KEY AREAS OF AIR-SEA INTERACTION IN GLOBAL OCEANS AND STUDY OF THE CLIMATOLOGICAL FEATURES

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Seven key areas of air-sea interaction in the global oceans are determined by comprehensive analysis of the global data of monthly mean sea surface temperature (SST), surface wind, temperature, humidity, sea surface sensible heat and latent heat fluxes. The time-lag correlation between SST and each atmospheric element in each key area are focally analyzed to expose the same and the different features of air-sea interaction in different key areas. The results show that the air-sea thermal interaction is strong in each area, SST, temperature and humidity can be fairly replaced with one another, particularly in the central eastern Pacific and the south India Ocean. The dynamic effect on SST is different in different areas and in the central western Pacific such effect is more important. The correlation between sensible heat, latent heat and SST is more significant in the eastern Pacific, the western Pacific and the two major monsoon areas - the northwestern Pacific and the south India Ocean. By analyzing the sustainable correlation probability of SST and every atmospheric element in each key area, we further know that the anomalies of which element, in which area and in which period are well sustained or easily destroyed. This is beneficial not only to prediction, but also to discussion of the physical mechanism of air-sea interaction.

  10. The Internationalization oh Higher Education in the U.S.: key features

    Directory of Open Access Journals (Sweden)

    Manolita Correia Lima

    2009-03-01

    Full Text Available One of the main features of the current process of internationalization of higher education is the increased mobility of academics, especially students in time of completion of his undergraduate studies. Based on literature and documentary research method on the subject, the article proposes an analysis of the key features of the geographical attraction exerted by the U.S. territory in relation to the flows of the current process of internationalization of higher education. The research concludes that this polarization that the country performs in global flows of students and scholars both contributes to the scientific-technological development of the country, and for the annual spend of massive amounts of dollars in the U.S. economy. In addition to the resources generated to pay for educational services rendered, the "client-students" still need to consume housing, food, entertainment, transportation, materials research etc.

  11. Discrete Feature Model (DFM) User Documentation

    Energy Technology Data Exchange (ETDEWEB)

    Geier, Joel (Clearwater Hardrock Consulting, Corvallis, OR (United States))

    2008-06-15

    This manual describes the Discrete-Feature Model (DFM) software package for modelling groundwater flow and solute transport in networks of discrete features. A discrete-feature conceptual model represents fractures and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which is usually treated as impermeable. This approximation may be valid for crystalline rocks such as granite or basalt, which have very low permeability if macroscopic fractures are excluded. A discrete feature is any entity that can conduct water and permit solute transport through bedrock, and can be reasonably represented as a piecewise-planar conductor. Examples of such entities may include individual natural fractures (joints or faults), fracture zones, and disturbed-zone features around tunnels (e.g. blasting-induced fractures or stress-concentration induced 'onion skin' fractures around underground openings). In a more abstract sense, the effectively discontinuous nature of pathways through fractured crystalline bedrock may be idealized as discrete, equivalent transmissive features that reproduce large-scale observations, even if the details of connective paths (and unconnected domains) are not precisely known. A discrete-feature model explicitly represents the fundamentally discontinuous and irregularly connected nature of systems of such systems, by constraining flow and transport to occur only within such features and their intersections. Pathways for flow and solute transport in this conceptualization are a consequence not just of the boundary conditions and hydrologic properties (as with continuum models), but also the irregularity of connections between conductive/transmissive features. The DFM software package described here is an extensible code for investigating problems of flow and transport in geological (natural or human-altered) systems that can be characterized effectively in terms of discrete features. With this

  12. Clafer: Unifying Class and Feature Modeling

    DEFF Research Database (Denmark)

    Bąk, Kacper; Diskin, Zinovy; Antkiewicz, Michal;

    2015-01-01

    of hierarchical models whereby properties can be arbitrarily nested in the presence of inheritance and feature modeling constructs. The semantics also enables building consistent automated reasoning support for the language: To date, we implemented three reasoners for Clafer based on Alloy, Z3 SMT, and Choco3 CSP...

  13. Feature Extraction for Structural Dynamics Model Validation

    Energy Technology Data Exchange (ETDEWEB)

    Farrar, Charles [Los Alamos National Laboratory; Nishio, Mayuko [Yokohama University; Hemez, Francois [Los Alamos National Laboratory; Stull, Chris [Los Alamos National Laboratory; Park, Gyuhae [Chonnam Univesity; Cornwell, Phil [Rose-Hulman Institute of Technology; Figueiredo, Eloi [Universidade Lusófona; Luscher, D. J. [Los Alamos National Laboratory; Worden, Keith [University of Sheffield

    2016-01-13

    As structural dynamics becomes increasingly non-modal, stochastic and nonlinear, finite element model-updating technology must adopt the broader notions of model validation and uncertainty quantification. For example, particular re-sampling procedures must be implemented to propagate uncertainty through a forward calculation, and non-modal features must be defined to analyze nonlinear data sets. The latter topic is the focus of this report, but first, some more general comments regarding the concept of model validation will be discussed.

  14. Philosophy and key features of 'Hodoyoshi' concept for optical remote sensing using 50kg class satellites

    Science.gov (United States)

    Enokuchi, A.; Takeyama, N.; Nakamura, Y.; Nojiri, Y.; Miyamura, N.; Iwasaki, A.; Nakasuka, S.

    2010-10-01

    Remote sensing missions have been conventionally performed by using satellite-onboard optical sensors with extraordinarily high reliability, on huge satellites. On the other hand, small satellites for remote-sensing missions have recently been developed intensely and operated all over the world. This paper gives a Japanese concept of the development of nano-satellites(10kg to 50kg) based on "Hodoyoshi" (Japanese word for "reasonable") reliability engineering aiming at cost-effective design of optical sensors, buses and satellites. The concept is named as "Hodoyoshi" concept. We focus on the philosophy and the key features of the concept. These are conveniently applicable to the development of optical sensors on nano-satellites. As major advantages, the optical sensors based on the "Hodoyoshi" concept are "flexible" in terms of selectability of wavelength bands, adaptability to the required ground sample distance, and optimal performance under a wide range of environmental temperatures. The first and second features mentioned above can be realized by dividing the functions of the optical sensor into modularized functional groups reasonably. The third feature becomes possible by adopting the athermal and apochromatic optics design. By utilizing these features, the development of the optical sensors become possible without exact information on the launcher or the orbit. Furthermore, this philosophy leads to truly quick delivery of nano-satellites for remote-sensing missions. On the basis of the concept, we are now developing nano-satellite technologies and five nano-satellites to realize the concept in a four-year-long governmentally funded project. In this paper, the specification of the optical sensor on the first satellite is also reported.

  15. REVERSE MODELING FOR CONIC BLENDING FEATURE

    Institute of Scientific and Technical Information of China (English)

    Fan Shuqian; Ke Yinglin

    2005-01-01

    A novel method to extract conic blending feature in reverse engineering is presented.Different from the methods to recover constant and variable radius blends from unorganized points, it contains not only novel segmentation and feature recognition techniques, but also bias corrected technique to capture more reliable distribution of feature parameters along the spine curve. The segmentation depending on point classification separates the points in the conic blend region from the input point cloud. The available feature parameters of the cross-sectional curves are extracted with the processes of slicing point clouds with planes, conic curve fitting, and parameters estimation and compensation. The extracted parameters and its distribution laws are refined according to statistic theory such as regression analysis and hypothesis test. The proposed method can accurately capture the original design intentions and conveniently guide the reverse modeling process. Application examples are presented to verify the high precision and stability of the proposed method.

  16. The Probabilistic Model of Keys Generation of QKD Systems

    CERN Document Server

    Golubchikov, Dmitry

    2010-01-01

    The probabilistic model of keys generation of QKD systems is proposed. The model includes all phases of keys generation starting from photons generation to states detection taking characteristics of fiber-optics components into account. The paper describes the tree of events of QKD systems. Equations are found for estimation of the effectiveness of the process of sifted keys generation as well as for bit-error probability and for the rate of private keys generation.

  17. Features and heterogeneities in growing network models

    Science.gov (United States)

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

    2012-06-01

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

  18. Key-feature questions for assessment of clinical reasoning: a literature review.

    Science.gov (United States)

    Hrynchak, Patricia; Takahashi, Susan Glover; Nayer, Marla

    2014-09-01

    Key-feature questions (KFQs) have been developed to assess clinical reasoning skills. The purpose of this paper is to review the published evidence on the reliability and validity of KFQs to assess clinical reasoning. A literature review was conducted by searching MEDLINE (1946-2012) and EMBASE (1980-2012) via OVID and ERIC. The following search terms were used: key feature; question or test or tests or testing or tested or exam; assess or evaluation, and case-based or case-specific. Articles not in English were eliminated. The literature search resulted in 560 articles. Duplicates were eliminated, as were articles that were not relevant; nine articles that contained reliability or validity data remained. A review of the references and of citations of these articles resulted in an additional 12 articles to give a total of 21 for this review. Format, language and scoring of KFQ examinations have been studied and modified to maximise reliability. Internal consistency reliability has been reported as being between 0.49 and 0.95. Face and content validity have been shown to be moderate to high. Construct validity has been shown to be good using vector thinking processes and novice versus expert paradigms, and to discriminate between teaching methods. The very modest correlations between KFQ examinations and more general knowledge-based examinations point to differing roles for each. Importantly, the results of KFQ examinations have been shown to successfully predict future physician performance, including patient outcomes. Although it is inaccurate to conclude that any testing format is universally reliable or valid, published research supports the use of examinations using KFQs to assess clinical reasoning. The review identifies areas of further study, including all categories of evidence. Investigation into how examinations using KFQs integrate with other methods in a system of assessment is needed. © 2014 John Wiley & Sons Ltd.

  19. Safety analysis for key design features of KALIMER-600 design concept

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Yong-Bum; Kwon, Y. M.; Kim, E. K.; Suk, S. D.; Chang, W. P.; Joeng, H. Y.; Ha, K. S.; Heo, S

    2005-03-01

    KAERI is developing the conceptual design of a Liquid Metal Reactor, KALIMER-600 (Korea Advanced LIquid MEtal Reactor) under the Long-term Nuclear R and D Program. KALIMER-600 addresses key issues regarding future nuclear power plants such as plant safety, economics, proliferation, and waste. In this report, key safety design features are described and safety analyses results for typical ATWS accidents, containment design basis accidents, and flow blockages in the KALIMER design are presented. First, the basic approach to achieve the safety goal and main design features of KALIMER-600 are introduced in Chapter 1, and the event categorization and acceptance criteria for the KALIMER-600 safety analysis are described in Chapter 2, In Chapter 3, results of inherent safety evaluations for the KALIMER-600 conceptual design are presented. The KALIMER-600 core and plant system are designed to assure benign performance during a selected set of events without either reactor control or protection system intervention. Safety analyses for the postulated anticipated transient without scram (ATWS) have been performed using the SSC-K code to investigate the KALIMER-600 system response to the events. The objectives of Chapter 4, are to assess the response of KALIMER-600 containment to the design basis accidents and to evaluate whether the consequences are acceptable or not in the aspect of structural integrity and the exposure dose rate. In Chapter 5, the analysis of flow blockage for KALIMER-600 with the MATRA-LMR-FB code, which has been developed for the internal flow blockage in a LMR subassembly, are described. The cases with a blockage of 6-subchannel, 24-subchannel, and 54-subchannel are analyzed.

  20. Model atmospheres - Tool for identifying interstellar features

    Science.gov (United States)

    Frisch, P. C.; Slojkowski, S. E.; Rodriguez-Bell, T.; York, D.

    1993-01-01

    Model atmosphere parameters are derived for 14 early A stars with rotation velocities, from optical spectra, in excess of 80 km/s. The models are compared with IUE observations of the stars in regions where interstellar lines are expected. In general, with the assumption of solar abundances, excellent fits are obtained in regions longward of 2580 A, and accurate interstellar equivalent widths can be derived using models to establish the continuum. The fits are poorer at shorter wavelengths, particularly at 2026-2062 A, where the stellar model parameters seem inadequate. Features indicating mass flows are evident in stars with known infrared excesses. In gamma TrA, variability in the Mg II lines is seen over the 5-year interval of these data, and also over timescales as short as 26 days. The present technique should be useful in systematic studies of episodic mass flows in A stars and for stellar abundance studies, as well as interstellar features.

  1. Key West, Florida Tsunami Forecast Grids for MOST Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Key West, Florida Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model. MOST...

  2. Qualitative research methods: key features and insights gained from use in infection prevention research.

    Science.gov (United States)

    Forman, Jane; Creswell, John W; Damschroder, Laura; Kowalski, Christine P; Krein, Sarah L

    2008-12-01

    Infection control professionals and hospital epidemiologists are accustomed to using quantitative research. Although quantitative studies are extremely important in the field of infection control and prevention, often they cannot help us explain why certain factors affect the use of infection control practices and identify the underlying mechanisms through which they do so. Qualitative research methods, which use open-ended techniques, such as interviews, to collect data and nonstatistical techniques to analyze it, provide detailed, diverse insights of individuals, useful quotes that bring a realism to applied research, and information about how different health care settings operate. Qualitative research can illuminate the processes underlying statistical correlations, inform the development of interventions, and show how interventions work to produce observed outcomes. This article describes the key features of qualitative research and the advantages that such features add to existing quantitative research approaches in the study of infection control. We address the goal of qualitative research, the nature of the research process, sampling, data collection and analysis, validity, generalizability of findings, and presentation of findings. Health services researchers are increasingly using qualitative methods to address practical problems by uncovering interacting influences in complex health care environments. Qualitative research methods, applied with expertise and rigor, can contribute important insights to infection prevention efforts.

  3. Key West, Florida Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  4. Discrete Event Simulation Modeling and Analysis of Key Leader Engagements

    Science.gov (United States)

    2012-06-01

    SIMULATION MODELING AND ANALYSIS OF KEY LEADER ENGAGEMENTS by Clifford C. Wakeman June 2012 Thesis Co-Advisors: Arnold H. Buss Susan...DATE June 2012 3. REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE Discrete Event Simulation Modeling and Analysis of Key...for public release; distribution is unlimited DISCRETE EVENT SIMULATION MODELING AND ANALYSIS OF KEY LEADER ENGAGEMENTS Clifford C. Wakeman

  5. Orthognathic model surgery with LEGO key-spacer.

    Science.gov (United States)

    Tsang, Alfred Chee-Ching; Lee, Alfred Siu Hong; Li, Wai Keung

    2013-12-01

    A new technique of model surgery using LEGO plates as key-spacers is described. This technique requires less time to set up compared with the conventional plaster model method. It also retains the preoperative setup with the same set of models. Movement of the segments can be measured and examined in detail with LEGO key-spacers.

  6. A Method for Model Checking Feature Interactions

    DEFF Research Database (Denmark)

    Pedersen, Thomas; Le Guilly, Thibaut; Ravn, Anders Peter;

    2015-01-01

    This paper presents a method to check for feature interactions in a system assembled from independently developed concurrent processes as found in many reactive systems. The method combines and refines existing definitions and adds a set of activities. The activities describe how to populate the ...... the definitions with models to ensure that all interactions are captured. The method is illustrated on a home automation example with model checking as analysis tool. In particular, the modelling formalism is timed automata and the analysis uses UPPAAL to find interactions....

  7. Features and heterogeneities in growing network models

    CERN Document Server

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

    2011-01-01

    Many complex networks from the World-Wide-Web to biological networks are growing taking into account the heterogeneous features of the nodes. The feature of a node might be a discrete quantity such as a classification of a URL document as personal page, thematic website, news, blog, search engine, social network, ect. or the classification of a gene in a functional module. Moreover the feature of a node can be a continuous variable such as the position of a node in the embedding space. In order to account for these properties, in this paper we provide a generalization of growing network models with preferential attachment that includes the effect of heterogeneous features of the nodes. The main effect of heterogeneity is the emergence of an "effective fitness" for each class of nodes, determining the rate at which nodes acquire new links. Beyond the degree distribution, in this paper we give a full characterization of the other relevant properties of the model. We evaluate the clustering coefficient and show ...

  8. Feature Matching in Time Series Modelling

    CERN Document Server

    Xia, Yingcun

    2011-01-01

    Using a time series model to mimic an observed time series has a long history. However, with regard to this objective, conventional estimation methods for discrete-time dynamical models are frequently found to be wanting. In the absence of a true model, we prefer an alternative approach to conventional model fitting that typically involves one-step-ahead prediction errors. Our primary aim is to match the joint probability distribution of the observable time series, including long-term features of the dynamics that underpin the data, such as cycles, long memory and others, rather than short-term prediction. For want of a better name, we call this specific aim {\\it feature matching}. The challenges of model mis-specification, measurement errors and the scarcity of data are forever present in real time series modelling. In this paper, by synthesizing earlier attempts into an extended-likelihood, we develop a systematic approach to empirical time series analysis to address these challenges and to aim at achieving...

  9. Hierarchical Geometric Constraint Model for Parametric Feature Based Modeling

    Institute of Scientific and Technical Information of China (English)

    高曙明; 彭群生

    1997-01-01

    A new geometric constraint model is described,which is hierarchical and suitable for parametric feature based modeling.In this model,different levels of geometric information are repesented to support various stages of a design process.An efficient approach to parametric feature based modeling is also presented,adopting the high level geometric constraint model.The low level geometric model such as B-reps can be derived automatically from the hig level geometric constraint model,enabling designers to perform their task of detailed design.

  10. Transverse beam splitting made operational: Key features of the multiturn extraction at the CERN Proton Synchrotron

    Directory of Open Access Journals (Sweden)

    A. Huschauer

    2017-06-01

    Full Text Available Following a successful commissioning period, the multiturn extraction (MTE at the CERN Proton Synchrotron (PS has been applied for the fixed-target physics programme at the Super Proton Synchrotron (SPS since September 2015. This exceptional extraction technique was proposed to replace the long-serving continuous transfer (CT extraction, which has the drawback of inducing high activation in the ring. MTE exploits the principles of nonlinear beam dynamics to perform loss-free beam splitting in the horizontal phase space. Over multiple turns, the resulting beamlets are then transferred to the downstream accelerator. The operational deployment of MTE was rendered possible by the full understanding and mitigation of different hardware limitations and by redesigning the extraction trajectories and nonlinear optics, which was required due to the installation of a dummy septum to reduce the activation of the magnetic extraction septum. This paper focuses on these key features including the use of the transverse damper and the septum shadowing, which allowed a transition from the MTE study to a mature operational extraction scheme.

  11. Safety Analysis for Key Design Features of KALIMER-600 Design Concept

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Yong Bum; Kwon, Y. M.; Kim, E. K.; Suk, S. D.; Chang, W. P.; Jeong, H. Y.; Ha, K. S

    2007-02-15

    This report contains the safety analyses of the KALIMER-600 conceptual design which KAERI has been developing under the Long-term Nuclear R and D Program. The analyses have been performed reflecting the design developments during the second year of the 4th design phase in the program. The specific presentations are the key design features with the safety principles for achieving the safety objectives, the event categorization and safety criteria, and results on the safety analyses for the DBAs and ATWS events, the containment performance, and the channel blockages. The safety analyses for both the DBAs and ATWS events have been performed using SSC-K version 1.3., and the results have shown the fulfillment of the safety criteria for DBAs with conservative assumptions. The safety margins as well as the inherent safety also have been confirmed for the ATWS events. For the containment performance analysis, ORIGEN-2.1 and CONTAIN-LMR have been used. In results, the structural integrity has been acceptable and the evaluated exposure dose rate has been complied with 10 CFR 100 and PAG limits. The analysis results for flow blockages of 6-subchannels, 24-subchannels, and 54- subchannels with the MATRA-LMR-FB code, have assured the integrity of subassemblies.

  12. Optical Emission Spectroscopy in PECVD Helps Modulate Key Features in Biofunctional Coatings for Medical Implants

    Science.gov (United States)

    Santos, Miguel; Michael, Praveesuda; Filipe, Elysse; Wise, Steven; Bilek, Marcela; University of Sydney Collaboration

    2015-09-01

    We explore the use of optical emission spectroscopy (OES) diagnostic tools as a process feedback control strategy in plasma-assisted deposition of biofunctional coatings. Hydrogenated carbon nitride coatings are deposited on medical-grade metallic substrates using radio-frequency (rf) discharges sustained in C2H2/N2/Ar gaseous mixtures. The discharge is generated by capacitively coupling the rf power (supplied at f = 13.56 MHz) to the plasma and the substrates are electrically biased using a pulse generator to provide microsecond square profiled pulses at voltages in the range |Vbias| = 250 V - 1000 V. Nitrogen content and CN bonding configurations in the coatings follow similar trends to those of CN radicals and nitrogen molecular ions in the discharge. OES is used as a non-intrusive diagnostic technique to identify a suitable window of process parameters and ultimately achieve biofunctional interfaces compatible with current clinical demands. Importantly, we demonstrate that key features of the coatings can be modulated and made suitable for blood and/or tissue contacting medical implants, such as coronary stents and orthopaedic implants. The coatings are mechanically robust, inherently non-thrombogenic and can be readily modified, enabling an easy functionalization through the immobilization of biological molecules in a bioactive conformation.

  13. Increasing AIP Macrocycle Size Reveals Key Features of agr Activation in Staphylococcus aureus.

    Science.gov (United States)

    Johnson, Jeffrey G; Wang, Boyuan; Debelouchina, Galia T; Novick, Richard P; Muir, Tom W

    2015-05-04

    The agr locus in the commensal human pathogen, Staphylococcus aureus, is a two-promoter regulon with allelic variability that produces a quorum-sensing circuit involved in regulating virulence within the bacterium. Secretion of unique autoinducing peptides (AIPs) and detection of their concentrations by AgrC, a transmembrane receptor histidine kinase, coordinates local bacterial population density with global changes in gene expression. The finding that staphylococcal virulence can be inhibited through antagonism of this quorum-sensing pathway has fueled tremendous interest in understanding the structure-activity relationships underlying the AIP-AgrC interaction. The defining structural feature of the AIP is a 16-membered, thiolactone-containing macrocycle. Surprisingly, the importance of ring size on agr activation or inhibition has not been explored. In this study, we address this deficiency through the synthesis and functional analysis of AIP analogues featuring enlarged and reduced macrocycles. Notably, this study is the first to interrogate AIP function by using both established cell-based reporter gene assays and newly developed in vitro AgrC-I binding and autophosphorylation activity assays. Based on our data, we present a model for robust agr activation involving a cooperative, three-points-of-contact interaction between the AIP macrocycle and AgrC.

  14. A Positive Deviance Approach to Understanding Key Features to Improving Diabetes Care in the Medical Home

    Science.gov (United States)

    Gabbay, Robert A.; Friedberg, Mark W.; Miller-Day, Michelle; Cronholm, Peter F.; Adelman, Alan; Schneider, Eric C.

    2013-01-01

    PURPOSE The medical home has gained national attention as a model to reorganize primary care to improve health outcomes. Pennsylvania has undertaken one of the largest state-based, multipayer medical home pilot projects. We used a positive deviance approach to identify and compare factors driving the care models of practices showing the greatest and least improvement in diabetes care in a sample of 25 primary care practices in southeast Pennsylvania. METHODS We ranked practices into improvement quintiles on the basis of the average absolute percentage point improvement from baseline to 18 months in 3 registry-based measures of performance related to diabetes care: glycated hemoglobin concentration, blood pressure, and low-density lipoprotein cholesterol level. We then conducted surveys and key informant interviews with leaders and staff in the 5 most and least improved practices, and compared their responses. RESULTS The most improved/higher-performing practices tended to have greater structural capabilities (eg, electronic health records) than the least improved/lower-performing practices at baseline. Interviews revealed striking differences between the groups in terms of leadership styles and shared vision; sense, use, and development of teams; processes for monitoring progress and obtaining feedback; and presence of technologic and financial distractions. CONCLUSIONS Positive deviance analysis suggests that primary care practices’ baseline structural capabilities and abilities to buffer the stresses of change may be key facilitators of performance improvement in medical home transformations. Attention to the practices’ structural capabilities and factors shaping successful change, especially early in the process, will be necessary to improve the likelihood of successful medical home transformation and better care. PMID:23690393

  15. Chimeric Mice with Competent Hematopoietic Immunity Reproduce Key Features of Severe Lassa Fever.

    Directory of Open Access Journals (Sweden)

    Lisa Oestereich

    2016-05-01

    Full Text Available Lassa fever (LASF is a highly severe viral syndrome endemic to West African countries. Despite the annual high morbidity and mortality caused by LASF, very little is known about the pathophysiology of the disease. Basic research on LASF has been precluded due to the lack of relevant small animal models that reproduce the human disease. Immunocompetent laboratory mice are resistant to infection with Lassa virus (LASV and, to date, only immunodeficient mice, or mice expressing human HLA, have shown some degree of susceptibility to experimental infection. Here, transplantation of wild-type bone marrow cells into irradiated type I interferon receptor knockout mice (IFNAR-/- was used to generate chimeric mice that reproduced important features of severe LASF in humans. This included high lethality, liver damage, vascular leakage and systemic virus dissemination. In addition, this model indicated that T cell-mediated immunopathology was an important component of LASF pathogenesis that was directly correlated with vascular leakage. Our strategy allows easy generation of a suitable small animal model to test new vaccines and antivirals and to dissect the basic components of LASF pathophysiology.

  16. Chimeric Mice with Competent Hematopoietic Immunity Reproduce Key Features of Severe Lassa Fever.

    Science.gov (United States)

    Oestereich, Lisa; Lüdtke, Anja; Ruibal, Paula; Pallasch, Elisa; Kerber, Romy; Rieger, Toni; Wurr, Stephanie; Bockholt, Sabrina; Pérez-Girón, José V; Krasemann, Susanne; Günther, Stephan; Muñoz-Fontela, César

    2016-05-01

    Lassa fever (LASF) is a highly severe viral syndrome endemic to West African countries. Despite the annual high morbidity and mortality caused by LASF, very little is known about the pathophysiology of the disease. Basic research on LASF has been precluded due to the lack of relevant small animal models that reproduce the human disease. Immunocompetent laboratory mice are resistant to infection with Lassa virus (LASV) and, to date, only immunodeficient mice, or mice expressing human HLA, have shown some degree of susceptibility to experimental infection. Here, transplantation of wild-type bone marrow cells into irradiated type I interferon receptor knockout mice (IFNAR-/-) was used to generate chimeric mice that reproduced important features of severe LASF in humans. This included high lethality, liver damage, vascular leakage and systemic virus dissemination. In addition, this model indicated that T cell-mediated immunopathology was an important component of LASF pathogenesis that was directly correlated with vascular leakage. Our strategy allows easy generation of a suitable small animal model to test new vaccines and antivirals and to dissect the basic components of LASF pathophysiology.

  17. Safety analysis for key design features of KALIMER with breakeven core

    Energy Technology Data Exchange (ETDEWEB)

    Hahn, Do Hee; Kwon, Y. M.; Chang, W. P.; Suk, S. D.; Lee, Y. B.; Jeong, K. S

    2002-04-01

    KAERI is currently developing the conceptual design of a liquid metal reactor, KALIMER (Korea Advanced Liquid MEtal Reactor) under the Long-term nuclear R and D Program. In this report, key safety design features are described and safety analyses results for typical ATWS accidents in the KALIMER design with breakeven core are presented. First, the basic approach to achieve the safety goal is introduced in chapter 1, and the event categorization and acceptance criteria for the KALIMER safety analysis are described in chapter 2. In chapter 3, results of inherent safety evaluations for the KALIMER conceptual design are presented. Safety analyses for the postulated anticipated transient without scram (ATWS) have been performed using the SSC-K code to investigate the KALIMER system response to the events. They are categorized as Bounding Events (BEs) because of their low probability of occurrence. In chapter 4, the performance analysis results of the KALIMER containment dome are described along with the HCDA accident scenario and source terms. The major containment parameters of peak pressure and peak temperature have been calculated using the CONTAIN-LMR code. Radiological consequence has been evaluated by the MACCS code. Finally, a simple methodology is introduced to investigate the core energetics behavior during HCDA in chapter 5. Sensitivity analyses have been performed for the KALIMER core behavior during super-prompt critical excursions, using SCHAMBETA code developed in the framework of the modified bethe-tait method. Work energy potentials based arising from the sodium expansion as well as the isentropic fuel expansion are then calculated to evaluate the structural integrity of the reactor vessel, reactor internals and primary coolant system of KALIMER.

  18. Extracting Feature Model Changes from the Linux Kernel Using FMDiff

    NARCIS (Netherlands)

    Dintzner, N.J.R.; Van Deursen, A.; Pinzger, M.

    2014-01-01

    The Linux kernel feature model has been studied as an example of large scale evolving feature model and yet details of its evolution are not known. We present here a classification of feature changes occurring on the Linux kernel feature model, as well as a tool, FMDiff, designed to automatically ex

  19. Extracting Feature Model Changes from the Linux Kernel Using FMDiff

    NARCIS (Netherlands)

    Dintzner, N.J.R.; Van Deursen, A.; Pinzger, M.

    2014-01-01

    The Linux kernel feature model has been studied as an example of large scale evolving feature model and yet details of its evolution are not known. We present here a classification of feature changes occurring on the Linux kernel feature model, as well as a tool, FMDiff, designed to automatically

  20. New approach to spectral features modeling

    NARCIS (Netherlands)

    Brug, H. van; Scalia, P.S.

    2012-01-01

    The origin of spectral features, speckle effects, is explained, followed by a discussion on many aspects of spectral features generation. The next part gives an overview of means to limit the amplitude of the spectral features. This paper gives a discussion of all means to reduce the spectral featur

  1. An Active Model for Facial Feature Tracking

    Directory of Open Access Journals (Sweden)

    Jörgen Ahlberg

    2002-06-01

    Full Text Available We present a system for finding and tracking a face and extract global and local animation parameters from a video sequence. The system uses an initial colour processing step for finding a rough estimate of the position, size, and inplane rotation of the face, followed by a refinement step drived by an active model. The latter step refines the pre­vious estimate, and also extracts local animation parame­ters. The system is able to track the face and some facial features in near real-time, and can compress the result to a bitstream compliant to MPEG-4 face and body animation.

  2. Secret Key Generation for a Pairwise Independent Network Model

    CERN Document Server

    Nitinawarat, Sirin; Barg, Alexander; Narayan, Prakash; Reznik, Alex

    2010-01-01

    We consider secret key generation for a "pairwise independent network" model in which every pair of terminals observes correlated sources that are independent of sources observed by all other pairs of terminals. The terminals are then allowed to communicate publicly with all such communication being observed by all the terminals. The objective is to generate a secret key shared by a given subset of terminals at the largest rate possible, with the cooperation of any remaining terminals. Secrecy is required from an eavesdropper that has access to the public interterminal communication. A (single-letter) formula for secret key capacity brings out a natural connection between the problem of secret key generation and a combinatorial problem of maximal packing of Steiner trees in an associated multigraph. An explicit algorithm is proposed for secret key generation based on a maximal packing of Steiner trees in a multigraph; the corresponding maximum rate of Steiner tree packing is thus a lower bound for the secret ...

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

    Science.gov (United States)

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

    2008-01-01

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

  4. Improving Latino Children's Early Language and Literacy Development: Key Features of Early Childhood Education within Family Literacy Programmes

    Science.gov (United States)

    Jung, Youngok; Zuniga, Stephen; Howes, Carollee; Jeon, Hyun-Joo; Parrish, Deborah; Quick, Heather; Manship, Karen; Hauser, Alison

    2016-01-01

    Noting the lack of research on how early childhood education (ECE) programmes within family literacy programmes influence Latino children's early language and literacy development, this study examined key features of ECE programmes, specifically teacher-child interactions and child engagement in language and literacy activities and how these…

  5. Improving Latino Children's Early Language and Literacy Development: Key Features of Early Childhood Education within Family Literacy Programmes

    Science.gov (United States)

    Jung, Youngok; Zuniga, Stephen; Howes, Carollee; Jeon, Hyun-Joo; Parrish, Deborah; Quick, Heather; Manship, Karen; Hauser, Alison

    2016-01-01

    Noting the lack of research on how early childhood education (ECE) programmes within family literacy programmes influence Latino children's early language and literacy development, this study examined key features of ECE programmes, specifically teacher-child interactions and child engagement in language and literacy activities and how these…

  6. Model of key success factors for Business Intelligence implementation

    Directory of Open Access Journals (Sweden)

    Peter Mesaros

    2016-07-01

    Full Text Available New progressive technologies recorded growth in every area. Information-communication technologies facilitate the exchange of information and it facilitates management of everyday activities in enterprises. Specific modules (such as Business Intelligence facilitate decision-making. Several studies have demonstrated the positive impact of Business Intelligence to decision-making. The first step is to put in place the enterprise. The implementation process is influenced by many factors. This article discusses the issue of key success factors affecting to successful implementation of Business Intelligence. The article describes the key success factors for successful implementation and use of Business Intelligence based on multiple studies. The main objective of this study is to verify the effects and dependence of selected factors and proposes a model of key success factors for successful implementation of Business Intelligence. Key success factors and the proposed model are studied in Slovak enterprises.

  7. The queueing model for quantum key distribution network

    Institute of Scientific and Technical Information of China (English)

    Wen Hao; Han Zheng-Fu; Guo Guang-Can; Hong Pei-Lin

    2009-01-01

    This paper develops a QKD (quantum key distribution)-based queueing model to investigate the data delay on QKD link and network, especially that based on trusted relays. It shows the mean packet delay performance of the QKD system. Furthermore, it proposes a key buffering policy which could effectively improve the delay performance in practice. The results will be helpful for quality of service in practical QKD systems.

  8. Five features for modelling augmented reality

    OpenAIRE

    Liang, Sha; Roast, Chris

    2014-01-01

    Augmented reality is growing rapidly and supports people in differ-ent fields such as education, design, navigation and medicine. However, there is limited discussion about the characteristic features of augmented reality and what is meant by the term. This paper presents five different features: changea-bility, synchronicity and instant, antecedent, partial one to one and hidden reali-ty. The explanation of each of these features is given follow a consistent struc-ture. The benefits of gener...

  9. Study on Isomerous CAD Model Exchange Based on Feature

    Institute of Scientific and Technical Information of China (English)

    SHAO Xiaodong; CHEN Feng; XU Chenguang

    2006-01-01

    A model-exchange method based on feature between isomerous CAD systems is put forward in this paper. In this method, CAD model information is accessed at both feature and geometry levels and converted according to standard feature operation. The feature information including feature tree, dimensions and constraints, which will be lost in traditional data conversion, as well as geometry are converted completely from source CAD system to destination one. So the transferred model can be edited through feature operation, which cannot be implemented by general model-exchange interface.

  10. The Main Features and the Key Challenges of the Education System in Taiwan

    Science.gov (United States)

    Chien, Chiu-Kuei Chang; Lin, Lung-Chi; Chen, Chun-Fu

    2013-01-01

    Taiwan has undergone radical innovation of its educational system in the wake of political liberalization and democratization, with a request for a change in the idea which diverts from "de-centralization" to "individualization." The reforms have led to two main features of pluralism and generalization of education in our…

  11. Modeling, Simulation and Analysis of Public Key Infrastructure

    Science.gov (United States)

    Liu, Yuan-Kwei; Tuey, Richard; Ma, Paul (Technical Monitor)

    1998-01-01

    Security is an essential part of network communication. The advances in cryptography have provided solutions to many of the network security requirements. Public Key Infrastructure (PKI) is the foundation of the cryptography applications. The main objective of this research is to design a model to simulate a reliable, scalable, manageable, and high-performance public key infrastructure. We build a model to simulate the NASA public key infrastructure by using SimProcess and MatLab Software. The simulation is from top level all the way down to the computation needed for encryption, decryption, digital signature, and secure web server. The application of secure web server could be utilized in wireless communications. The results of the simulation are analyzed and confirmed by using queueing theory.

  12. Key feature identification from image profile segments using a high frequency sonar.

    OpenAIRE

    Ingold, Barry W.

    1992-01-01

    Approved for public release; distribution is unlimited. Many avenues have been explored to allow recognition of underwater objects by a sensing system on an Autonomous Underwater Vehicle (AUV). In particular, this research analyzes the precision with which a Tritech ST1000 high resolution imaging sonar system allows the extraction of linear features from its perceived environment. The linear extraction algorithm, as well as acceptance criteria for individual sonar returns are developed. Te...

  13. Key Elements of Effective Teaching in the Direct Teaching Model.

    Science.gov (United States)

    Bruning, Roger H.

    Summaries and outlines are presented of key elements in effective teaching identified in research studies by Kounin (1970), Brophy (1973), Brophy and Evertson (1976), Stallings (1974; l975), Berliner (1979), and Good and Grouws (1979). These elements are synthesized in a direct teaching model that delineates the characteristics of effective…

  14. Cloud Storage Vendors Wide Support and Security Key Features for Shifting Towards Business Perspective

    Directory of Open Access Journals (Sweden)

    T Prasath

    2014-02-01

    Full Text Available The emerging trends that suits well with the shifting terminologies of computational environment. The cloud computing plays the vital role in today’s business activities. The essential fact of computing rapid technological shift towards cloud.  The storage medium of cloud provides common public spacing, privatized infrastructure, and other platform supports are facilitated. Here in this paper a brief scrutiny  under gone on various cloud storage vendors. The various cloud storage vendors provides data storage, space availability, scaling, sharing, secure transmission between cloud storage medium. Here different vendors wide data storage mediums are discussed with their security features and data access managing capabilities are rendered.

  15. Neuroticism in Young Women with Fibromyalgia Links to Key Clinical Features

    Directory of Open Access Journals (Sweden)

    Katrina Malin

    2012-01-01

    Full Text Available Objective. We examined personality traits in young women with FM, in order to seek associations with key psychological processes and clinical symptoms. Methods. Twenty-seven women with FM and 29 age-matched female healthy controls [HC] completed a series of questionnaires examining FM symptoms, personality and psychological variables. Results. Significant differences between characteristic FM symptoms (sleep, pain, fatigue, and confusion as well as for the psychological variables of depression, anxiety, and stress were found between FM and HC (P<0.001. Neuroticism was the only subscale of the Big Five Inventory that showed a significant difference between the FM group and HC group [P<0.05]. Within the FM group, there was a significant association between the level of the neuroticism and each of pain, sleep, fatigue, and confusion, depression, anxiety, and stress (P<0.05–0.01. The association between the level of neuroticism and the level of stress was the strongest of all variables tested (P<0.001. Conclusion. The personality trait of neuroticism significantly associates with the key FM characteristics of pain, sleep, fatigue and confusion as well as the common co-morbidities of depression, anxiety and stress. Personality appears to be an important modulator of FM clinical symptoms.

  16. Cutaneous Manifestations in Dermatomyositis: Key Clinical and Serological Features-a Comprehensive Review.

    Science.gov (United States)

    Muro, Yoshinao; Sugiura, Kazumitsu; Akiyama, Masashi

    2016-12-01

    Dermatomyositis (DM) is a common idiopathic inflammatory myopathy. The pathogenesis is considered to be microangiopathy affecting skin and muscle. The cutaneous manifestations of DM are the most important aspect of this disease, and their correct evaluation is important for early diagnosis. The skin signs are various: Some are pathognomonic or highly characteristic, and others are compatible with DM. Recently, DM has been categorized into several disease subsets based on the various autoantibodies present in patients. Sometimes, characteristic cutaneous manifestations are strongly associated with the presence of specific autoantibodies. For example, anti-Mi-2 antibody is associated with the classic features of DM, including heliotrope rash, Gottron's papules, the V-neck sign, the shawl sign, cuticular overgrowth, and photosensitivity. Frequent cutaneous features in anti-transcriptional intermediary factor 1 gamma (TIF1γ)-positive patients are diffuse photoerythema, including "dusky red face," while skin ulcerations, palmar papules (inverse Gottron), diffuse hair loss, panniculitis, and oral pain and/or ulcers are sometimes associated with anti-melanoma differentiation-associated gene 5 product (MDA5) antibody. Here, we review important cutaneous manifestations seen in patients with DM, and we examine the relationship between the skin changes and myositis-associated autoantibodies. Correct evaluation of cutaneous manifestations and myositis-associated autoantibodies should help the clinician in the early diagnosis of DM, for a quick recognition of cutaneous signs that may be the symptom of onset before muscle inflammation.

  17. Evaporation of water droplets on "lock-and-key" structures with nanoscale features.

    Science.gov (United States)

    Zhu, Xiaolong; Zhang, Chi; Liu, Xiaohan; Hansen, Ole; Xiao, Sanshui; Mortensen, N A; Zi, Jian

    2012-06-26

    Highly ordered poly(dimethylsiloxane) microbowl arrays (MBAs) and microcap arrays (MCAs) with "lock-and-key" properties are successfully fabricated by self-assembly and electrochemical deposition. The wetting properties and evaporation dynamics of water droplets for both cases have been investigated. For the MBAs case, the wetting radius of the droplets remains unchanged until the portion of the droplet completely dries out at the end of the evaporation process. The pinning state extends for more than 99.5% of the total evaporation time, and the pinning-shrinking transition is essentially prevented whereas in the case of the MCAs the contact radius exhibits distinct stages during evaporation and the contact line retreats significantly in the middle of the evaporation process. We explain the phenomenon by a qualitative energy balance argument based on the different shrinkage types of the nanoscale-folded contact line.

  18. Hypertension Is a Key Feature of the Metabolic Syndrome in Subjects Aging with HIV

    DEFF Research Database (Denmark)

    Martin-Iguacel, Raquel; Negredo, Eugènia; Peck, Robert

    2016-01-01

    to predispose to these metabolic complications and to the excess risk of CVD observed in the HIV population. The metabolic syndrome (MS) represents a clustering of RF for CVD that includes abdominal obesity, hypertension, dyslipidemia and insulin resistance. Hypertension is a prevalent feature of the MS in HIV......With widespread and effective antiretroviral therapy, the life expectancy in the HIV population has dramatically improved over the last two decades. Consequently, as patients are aging with HIV, other age-related comorbidities, such as metabolic disturbances and cardiovascular disease (CVD), have......, in particular in the aging population, and constitutes an important RF for CVD. Physicians should screen their patients for metabolic and cardiovascular risk at the regular visits to reduce MS and the associated CVD risk among people aging with HIV, since many of RF are under-diagnosed and under...

  19. CONVERSE REASONING FOR FULL DEPRESSION-FEATURE MODEL AND PROCESS

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    A new approach, namely, "defining protrusion-feature with depression-parameter" is advanced, which focuses on the shortcomings of protrusion-feature alteration method; The full depression-feature model is built up, and a basic converse reasoning iterative algorithm for machining process is given.The detailed examination has been implemented on the feature-based modeling system for light industry product (QJFMS) and the converse reasoning on fixture-based machining process is achieved.

  20. Key metrics for HFIR HEU and LEU models

    Energy Technology Data Exchange (ETDEWEB)

    Ilas, Germina [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Betzler, Benjamin R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Chandler, David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Renfro, David G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Davidson, Eva E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2016-10-25

    This report compares key metrics for two fuel design models of the High Flux Isotope Reactor (HFIR). The first model represents the highly enriched uranium (HEU) fuel currently in use at HFIR, and the second model considers a low-enriched uranium (LEU) interim design fuel. Except for the fuel region, the two models are consistent, and both include an experiment loading that is representative of HFIR's current operation. The considered key metrics are the neutron flux at the cold source moderator vessel, the mass of 252Cf produced in the flux trap target region as function of cycle time, the fast neutron flux at locations of interest for material irradiation experiments, and the reactor cycle length. These key metrics are a small subset of the overall HFIR performance and safety metrics. They were defined as a means of capturing data essential for HFIR's primary missions, for use in optimization studies assessing the impact of HFIR's conversion from HEU fuel to different types of LEU fuel designs.

  1. Features in the Standard Model diphoton background

    CERN Document Server

    Bondarenko, Kyrylo; Ruchayskiy, Oleg; Shaposhnikov, Mikhail

    2016-01-01

    We argue that electromagnetic decays of energetic unflavoured neutral mesons, notably $\\eta$, mis-identified as single photons due to granularity of the electromagnetic calorimeter might create bump-like features in the diphoton invariant mass spectrum at different energies, including 750 GeV. We discuss what kind of additional analysis can exclude or confirm this hypothesis.

  2. A Method for Model Checking Feature Interactions

    DEFF Research Database (Denmark)

    Pedersen, Thomas; Le Guilly, Thibaut; Ravn, Anders Peter

    2015-01-01

    This paper presents a method to check for feature interactions in a system assembled from independently developed concurrent processes as found in many reactive systems. The method combines and refines existing definitions and adds a set of activities. The activities describe how to populate the ...

  3. CONSTRUCTION AND MODIFICATION OF FLEXIBLE FEATURE-BASED MODELS

    Institute of Scientific and Technical Information of China (English)

    1999-01-01

    A new approach is proposed to generate flexible featrure-based models (FFBM), which can be modified dynamically. BRep/CSFG/FRG hybrid scheme is used to describe FFBM, in which BRep explicitly defines the model, CSFG (Constructive solid-feature geometry) tree records the feature-based modelling procedure and FRG (Feature relation graph) reflects different knids of relationship among features. Topological operators with local retrievability are designed to implement feature addition, which is traced by topological operation list (TOL) in detail. As a result, FFBM can be modified directly in the system database. Related features' chain reactions and variable topologies are supported in design modification, after which the product information adhering on features will not be lost. Further, a feature can be modified as rapidly as it was added.

  4. Childhood Ataxia: Clinical Features, Pathogenesis, Key Unanswered Questions, and Future Directions

    Science.gov (United States)

    Ashley, Claire N.; Hoang, Kelly D.; Lynch, David R.; Perlman, Susan L.; Maria, Bernard L.

    2013-01-01

    Childhood ataxia is characterized by impaired balance and coordination primarily due to cerebellar dysfunction. Friedreich ataxia, a form of childhood ataxia, is the most common multisystem autosomal recessive disease. Most of these patients are homozygous for the GAA repeat expansion located on the first intron of the frataxin gene on chromosome 9. Mutations in the frataxin gene impair mitochondrial function, increase reactive oxygen species, and trigger redistribution of iron in the mitochondria and cytosol. Targeted therapies for Friedreich ataxia are undergoing testing. In addition, a centralized database, patient registry, and natural history study have been launched to support clinical trials in Friedreich ataxia. The 2011 Neurobiology of Disease in Children symposium, held in conjunction with the 40th annual Child Neurology Society meeting, aimed to (1) describe clinical features surrounding Friedreich ataxia, including cardiomyopathy and genetics; (2) discuss recent advances in the understanding of the pathogenesis of Friedreich ataxia and developments of clinical trials; (3) review new investigations of characteristic symptoms; (4) establish clinical and biochemical overlaps in neurodegenerative diseases and possible directions for future basic, translational, and clinical studies. PMID:22859693

  5. Occult sinusitis may be a key feature for non-controlled asthma in children.

    Science.gov (United States)

    Marseglia, G L; Caimmi, S; Marseglia, A; Pagella, F; Ciprandi, G; La Rosa, M; Leonardi, S; Miraglia Del Giudice, M; Caimmi, D

    2012-01-01

    Sinusitis is frequently associated with asthma. The diagnosis and management of patients with asthma associated with sinusitis are often challenging, though sometimes unsatisfactory. Detection and treatment of sinusitis in asthmatics may lead to a better control of asthma symptoms. Most of the studies regarding the relationship between sinusitis and asthma have been conducted in adults. The aim of the present study was to evaluate the presence of sinusal comorbidity in children with un-controlled asthma both clinically and through nasal endoscopy after the first 6 months of treatment. The present study included 294 consecutive asthmatic children (97 males, mean age 7.3 years). Asthma diagnosis, severity assessment and treatment were performed according to GINA guidelines. Twenty-one patients with non-controlled asthma presented with endoscopic features of sinusitis, but without any clinical sign or symptom. We defined such condition occult sinusitis. Not only overt sinusitis, but also occult sinusitis could be a significant comorbidity in asthmatic patients. For this reason, it may be beneficial to determine the presence of sinus inflammation in children with non-controlled asthma, even when they do not present clinical signs or symptoms of upper airways involvement.

  6. Key features of the X inactivation process are conserved between marsupials and eutherians.

    Science.gov (United States)

    Mahadevaiah, Shantha K; Royo, Helene; VandeBerg, John L; McCarrey, John R; Mackay, Sarah; Turner, James M A

    2009-09-15

    In female marsupials, X chromosome inactivation (XCI) is imprinted, affecting the paternal X chromosome. One model, supported by recent studies, proposes that XCI in marsupials is achieved through inheritance of an already silent X chromosome from the father, with XCI initiated by meiotic sex chromosome inactivation (MSCI). This model is appealing because marsupials have no Xist gene and the marsupial inactive X chromosome is epigenetically dissimilar to that of mice, apparently lacking repressive histone marks such as H3K27 trimethylation. A central prediction of the meiotic inactivation model of XCI is that silencing of genes on the X chromosome, initiated during male meiosis, is stably maintained during subsequent spermiogenesis. Here we characterize XCI in the male germline and female soma of the marsupial Monodelphis domestica. Contrary to the meiotic inactivation model, we find that X genes silenced by MSCI are reactivated after meiosis and are subsequently inactivated in the female. A reexamination of the female somatic inactive marsupial X chromosome reveals that it does share common properties with that of eutherians, including H3K27 trimethylation and targeting to the perinucleolar compartment. We conclude that aspects of the XCI process are more highly conserved in therian mammals than previously thought.

  7. Predicting establishment of non-native fishes in Greece: identifying key features

    Directory of Open Access Journals (Sweden)

    Christos Gkenas

    2015-11-01

    Full Text Available Non-native fishes are known to cause economic damage to human society and are considered a major threat to biodiversity loss in freshwater ecosystems. The growing concern about these impacts has driven to an investigation of the biological traits that facilitate the establishment of non-native fish. However, invalid assessment in choosing the appropriate statistical model can lead researchers to ambiguous conclusions. Here, we present a comprehensive comparison of traditional and alternative statistical methods for predicting fish invasions using logistic regression, classification trees, multicorrespondence analysis and random forest analysis to determine characteristics of successful and failed non-native fishes in Hellenic Peninsula through establishment. We defined fifteen categorical predictor variables with biological relevance and measures of human interest. Our study showed that accuracy differed according to the model and the number of factors considered. Among all the models tested, random forest and logistic regression performed best, although all approaches predicted non-native fish establishment with moderate to excellent results. Detailed evaluation among the models corresponded with differences in variables importance, with three biological variables (parental care, distance from nearest native source and maximum size and two variables of human interest (prior invasion success and propagule pressure being important in predicting establishment. The analyzed statistical methods presented have a high predictive power and can be used as a risk assessment tool to prevent future freshwater fish invasions in this region with an imperiled fish fauna.

  8. Key features of mcr-1-bearing plasmids from Escherichia coli isolated from humans and food.

    Science.gov (United States)

    Zurfluh, Katrin; Nüesch-Inderbinen, Magdalena; Klumpp, Jochen; Poirel, Laurent; Nordmann, Patrice; Stephan, Roger

    2017-01-01

    Mcr-1-harboring Enterobacteriaceae are reported worldwide since their first discovery in 2015. However, a limited number of studies are available that compared full-length plasmid sequences of human and animal origins. In this study, mcr-1-bearing plasmids from seven Escherichia coli isolates recovered from patients (n = 3), poultry meat (n = 2) and turkey meat (n = 2) in Switzerland were further analyzed and compared. Isolates were characterized by multilocus sequence typing (MLST). The mcr-1-bearing plasmids were transferred by transformation into reference strain E. coli DH5α and MCR-1-producing transformants were selected on LB-agar supplemented with 2 mg/L colistin. Purified plasmids were then sequenced and compared. MLST revealed six distinct STs, illustrating the high clonal diversity among mcr-1-positive E. coli isolates of different origins. Two different mcr-1-positive plasmids were identified from a single E. coli ST48 human isolate. All other isolates possessed a single mcr-1 harboring plasmid. Transferable IncI2 (size ca. 60-61 kb) and IncX4 (size ca. 33-35 kb) type plasmids each bearing mcr-1 were found associated with human and food isolates. None of the mcr-1-positive IncI2 and IncX4 plasmids possessed any additional resistance determinants. Surprisingly, all but one of the sequenced mcr-1-positive plasmids lacked the ISApl1 element, which is a key element mediating acquisition of mcr-1 into various plasmid backbones. There is strong evidence that the food chain may be an important transmission route for mcr-1-bearing plasmids. Our data suggest that some "epidemic" plasmids rather than specific E. coli clones might be responsible for the spread of the mcr-1 gene along the food chain.

  9. On the Use of Memory Models in Audio Features

    DEFF Research Database (Denmark)

    Jensen, Karl Kristoffer

    2011-01-01

    Audio feature estimation is potentially improved by including higher- level models. One such model is the Short Term Memory (STM) model. A new paradigm of audio feature estimation is obtained by adding the influence of notes in the STM. These notes are identified when the perceptual spectral flux...

  10. Cytoplasmic CUG RNA foci are insufficient to elicit key DM1 features.

    Directory of Open Access Journals (Sweden)

    Warunee Dansithong

    Full Text Available The genetic basis of myotonic dystrophy type I (DM1 is the expansion of a CTG tract located in the 3' untranslated region of DMPK. Expression of mutant RNAs encoding expanded CUG repeats plays a central role in the development of cardiac disease in DM1. Expanded CUG tracts form both nuclear and cytoplasmic aggregates, yet the relative significance of such aggregates in eliciting DM1 pathology is unclear. To test the pathophysiology of CUG repeat encoding RNAs, we developed and analyzed mice with cardiac-specific expression of a beta-galactosidase cassette in which a (CTG(400 repeat tract was positioned 3' of the termination codon and 5' of the bovine growth hormone polyadenylation signal. In these animals CUG aggregates form exclusively in the cytoplasm of cardiac cells. A key pathological consequence of expanded CUG repeat RNA expression in DM1 is aberrant RNA splicing. Abnormal splicing results from the functional inactivation of MBNL1, which is hypothesized to occur due to MBNL1 sequestration in CUG foci or from elevated levels of CUG-BP1. We therefore tested the ability of cytoplasmic CUG foci to elicit these changes. Aggregation of CUG RNAs within the cytoplasm results both in Mbnl1 sequestration and in approximately a two fold increase in both nuclear and cytoplasmic Cug-bp1 levels. Significantly, despite these changes RNA splice defects were not observed and functional analysis revealed only subtle cardiac dysfunction, characterized by conduction defects that primarily manifest under anesthesia. Using a human myoblast culture system we show that this transgene, when expressed at similar levels to a second transgene, which encodes expanded CTG tracts and facilitates both nuclear focus formation and aberrant splicing, does not elicit aberrant splicing. Thus the lack of toxicity of cytoplasmic CUG foci does not appear to be a consequence of low expression levels. Our results therefore demonstrate that the cellular location of CUG RNA

  11. Robust speech features representation based on computational auditory model

    Institute of Scientific and Technical Information of China (English)

    LU Xugang; JIA Chuan; DANG Jianwu

    2004-01-01

    A speech signal processing and features extracting method based on computational auditory model is proposed. The computational model is based on psychological, physiological knowledge and digital signal processing methods. In each stage of a hearing perception system, there is a corresponding computational model to simulate its function. Based on this model, speech features are extracted. In each stage, the features in different kinds of level are extracted. A further processing for primary auditory spectrum based on lateral inhibition is proposed to extract much more robust speech features. All these features can be regarded as the internal representations of speech stimulation in hearing system. The robust speech recognition experiments are conducted to test the robustness of the features. Results show that the representations based on the proposed computational auditory model are robust representations for speech signals.

  12. Aeroheating model advancements featuring electroless metallic plating

    Science.gov (United States)

    Stalmach, C. J., Jr.; Goodrich, W. D.

    1976-01-01

    Discussed are advancements in wind tunnel model construction methods and hypersonic test data demonstrating the methods. The general objective was to develop model fabrication methods for improved heat transfer measuring capability at less model cost. A plated slab model approach was evaluated with cast models containing constantan wires that formed single-wire-to-plate surface thermocouple junctions with a seamless skin of electroless nickel alloy. The surface of a space shuttle orbiter model was selectively plated with scaled tiles to simulate, with high fidelity, the probable misalignments of the heatshield tiles on a flight vehicle. Initial, Mach 8 heating results indicated a minor effect of tile misalignment roughness on boundary layer transition, implying a possible relaxation of heatshield manufacturing tolerances. Some loss of the plated tiles was experienced when the model was tested at high heating rates.

  13. Automatically extracting sheet-metal features from solid model

    Institute of Scientific and Technical Information of China (English)

    刘志坚; 李建军; 王义林; 李材元; 肖祥芷

    2004-01-01

    With the development of modern industry,sheet-metal parts in mass production have been widely applied in mechanical,communication,electronics,and light industries in recent decades; but the advances in sheet-metal part design and manufacturing remain too slow compared with the increasing importance of sheet-metal parts in modern industry. This paper proposes a method for automatically extracting features from an arbitrary solid model of sheet-metal parts; whose characteristics are used for classification and graph-based representation of the sheet-metal features to extract the features embodied in a sheet-metal part. The extracting feature process can be divided for valid checking of the model geometry,feature matching,and feature relationship. Since the extracted features include abundant geometry and engineering information,they will be effective for downstream application such as feature rebuilding and stamping process planning.

  14. Automatically extracting sheet-metal features from solid model

    Institute of Scientific and Technical Information of China (English)

    刘志坚; 李建军; 王义林; 李材元; 肖祥芷

    2004-01-01

    With the development of modern industry, sheet-metal parts in mass production have been widely applied in mechanical, communication, electronics, and light industries in recent decades; but the advances in sheet-metal part design and manufacturing remain too slow compared with the increasing importance of sheet-metal parts in modern industry. This paper proposes a method for automatically extracting features from an arbitrary solid model of sheet-metal parts; whose characteristics are used for classification and graph-based representation of the sheet-metal features to extract the features embodied in a sheet-metal part. The extracting feature process can be divided for valid checking of the model geometry, feature matching, and feature relationship. Since the extracted features include abundant geometry and engineering information, they will be effective for downstream application such as feature rebuilding and stamping process planning.

  15. Selection of key terrain attributes for SOC model

    DEFF Research Database (Denmark)

    Greve, Mogens Humlekrog; Adhikari, Kabindra; Chellasamy, Menaka

    was selected, total 2,514,820 data mining models were constructed by 71 differences grid from 12m to 2304m and 22 attributes, 21 attributes derived by DTM and the original elevation. Relative importance and usage of each attributes in every model were calculated. Comprehensive impact rates of each attribute...... (standh) are the first three key terrain attributes in 5-attributes-model in all resolutions, the rest 2 of 5 attributes are Normal High (NormalH) and Valley Depth (Vall_depth) at the resolution finer than 40m, and Elevation and Channel Base (Chnl_base) coarser than 40m. The models at pixels size at 88m......As an important component of the global carbon pool, soil organic carbon (SOC) plays an important role in the global carbon cycle. SOC pool is the basic information to carry out global warming research, and needs to sustainable use of land resources. Digital terrain attributes are often use...

  16. Key management and encryption under the bounded storage model.

    Energy Technology Data Exchange (ETDEWEB)

    Draelos, Timothy John; Neumann, William Douglas; Lanzone, Andrew J.; Anderson, William Erik

    2005-11-01

    There are several engineering obstacles that need to be solved before key management and encryption under the bounded storage model can be realized. One of the critical obstacles hindering its adoption is the construction of a scheme that achieves reliable communication in the event that timing synchronization errors occur. One of the main accomplishments of this project was the development of a new scheme that solves this problem. We show in general that there exist message encoding techniques under the bounded storage model that provide an arbitrarily small probability of transmission error. We compute the maximum capacity of this channel using the unsynchronized key-expansion as side-channel information at the decoder and provide tight lower bounds for a particular class of key-expansion functions that are pseudo-invariant to timing errors. Using our results in combination with Dziembowski et al. [11] encryption scheme we can construct a scheme that solves the timing synchronization error problem. In addition to this work we conducted a detailed case study of current and future storage technologies. We analyzed the cost, capacity, and storage data rate of various technologies, so that precise security parameters can be developed for bounded storage encryption schemes. This will provide an invaluable tool for developing these schemes in practice.

  17. Development of Groundwater Modeling Capacity in Mongolia: Keys to Success

    Science.gov (United States)

    Anderson, M. T.; Valder, J. F.; Carter, J. M.

    2015-12-01

    Ulaanbaatar, the capital city of Mongolia, is totally dependent on groundwater for its municipal and industrial water supply. Water is drawn from a network of shallow wells in an alluvial aquifer along the Tuul River. Evidence, however, suggests that current water use and especially the projected water demand from a rapidly growing urban population, is not sustainable from existing water sources. In response, the Mongolia Ministry of Environment and the Mongolian Fresh Water Institute requested technical assistance on groundwater modeling through the U.S. Army Corps of Engineers to the U.S. Geological Survey (USGS). Scientists from the USGS-SD Water Science Center provided a workshop to Mongolian water experts on basic principles of groundwater modeling using MODFLOW. The purpose of the workshop was to bring together representatives from the Government of Mongolia, local universities, technical experts, and other key stakeholders to build in-country capacity in hydrogeology and groundwater modeling. A preliminary steady-state groundwater flow model was developed to simulate groundwater conditions in the Tuul River Basin and for use in water use decision-making. The model consisted of 2 layers, 226 rows, and 260 columns with uniform 500 meter grid spacing. The upper model layer represented the alluvial aquifer and the lower layer represented the underlying bedrock, which includes areas characterized by permafrost. Estimated groundwater withdrawal was 180 m3/day, and estimated recharge was 114 mm/yr. The model will be modified and updated by Mongolian scientists as more data are available. Ultimately the model will be used to assist managers in developing a sustainable water supply, for current use and changing climate scenarios. A key to success was developing in-country technical capacity and partnerships with the Mongolian University of Science and Technology, Mongolian Freshwater Institute, a non-profit organization, UNESCO, and the government of Mongolia.

  18. Negative symptoms as key features of depression among cannabis users: a preliminary report.

    Science.gov (United States)

    Bersani, G; Bersani, F S; Caroti, E; Russo, P; Albano, G; Valeriani, G; Imperatori, C; Minichino, A; Manuali, G; Corazza, O

    2016-01-01

    Cannabis use is frequent among depressed patients and may lead to the so-called "amotivational syndrome", which combines symptoms of affective flattening and loss of emotional reactivity (i.e. the so-called "negative" symptomatology). The aim of this study was to investigate the negative symptomatology in depressed patients with concomitant cannabis use disorders (CUDs) in comparison with depressed patients without CUDs. Fifty-one patients with a diagnosis of Major Depressive Disorder (MDD) and concomitant CUD and fifty-one MDD patients were enrolled in the study. The 21-Item Hamilton Depression Rating Scale (HDRS) and the negative symptoms subscales of the Positive and Negative Syndrome Scale (PANSS) were used to assess depressive and negative symptomatology. Patients with cannabis use disorders presented significantly more severe negative symptoms in comparison with patients without cannabis use (15.18 ± 2.25 vs 13.75 ± 2.44; t100 = 3.25 p = 0.002). A deeper knowledge of the "negative" psychopathological profile of MDD patients who use cannabis may lead to novel etiopathogenetic models of MDD and to more appropriate treatment approaches.

  19. Full feature data model for spatial information network integration

    Institute of Scientific and Technical Information of China (English)

    DENG Ji-qiu; BAO Guang-shu

    2006-01-01

    In allusion to the difficulty of integrating data with different models in integrating spatial information,the characteristics of raster structure, vector structure and mixed model were analyzed, and a hierarchical vectorraster integrative full feature model was put forward by integrating the advantage of vector and raster model and using the object-oriented method. The data structures of the four basic features, i.e. point, line, surface and solid,were described. An application was analyzed and described, and the characteristics of this model were described. In this model, all objects in the real world are divided into and described as features with hierarchy, and all the data are organized in vector. This model can describe data based on feature, field, network and other models, and avoid the disadvantage of inability to integrate data based on different models and perform spatial analysis on them in spatial information integration.

  20. Control of canine rabies in developing countries: key features and animal welfare implications.

    Science.gov (United States)

    Aréchiga Ceballos, N; Karunaratna, D; Aguilar Setién, A

    2014-04-01

    Over 90% of human deaths from rabies worldwide are caused by dog bites. Mass vaccination, along with the effective control of dog populations, has been used successfully in industrialised countries to control this disease. A lower success rate in developing countries is due to a number of factors, including vaccination campaigns that do not cover a sufficient number of animals or reach all communities, and a wide biodiversity that increases the number of reservoirs of the rabies virus. Educational programmes are needed, which focus on the commitment involved when acquiring a domestic animal, stating clearly what is required to provide it with a good quality of life. New technologies developed in the industrialised world will not always be successful in less developed countries. Approaches must be adapted to the particular conditions in each country, taking cultural and socio-economic issues into account. Authorities must promote research on dog population dynamics, the development of non-invasive methods to control dog populations and the most efficient, stable and low-cost options for vaccination. Under the One Health model, it is hoped that dog-transmitted human rabies will be accorded high priority as a zoonosis by human health authorities, international authorities and donor agencies to support ambitious eradication goals, particularly those being set in South-East Asia. Well-designed and adequately resourced vaccination programmes, based on the World Organisation for Animal Health (OIE) guidelines, will have significant animal welfare benefits, due to the availability of improved vaccines (in terms of efficacy, duration of immunity, ease of administration and lower cost), advances in dog population management and the more widespread implementation of the OIE Guidelines on Stray Dog Control. Animal welfare benefits include not only the elimination of pain and suffering caused by the clinical disease itself, but also the avoidance of the indirect impact of

  1. Music Genre Classification using the multivariate AR feature integration model

    DEFF Research Database (Denmark)

    Ahrendt, Peter; Meng, Anders

    2005-01-01

    informative decisions about musical genre. For the MIREX music genre contest several authors derive long time features based either on statistical moments and/or temporal structure in the short time features. In our contribution we model a segment (1.2 s) of short time features (texture) using a multivariate......Music genre classification systems are normally build as a feature extraction module followed by a classifier. The features are often short-time features with time frames of 10-30ms, although several characteristics of music require larger time scales. Thus, larger time frames are needed to take...... autoregressive model. Other authors have applied simpler statistical models such as the mean-variance model, which also has been included in several of this years MIREX submissions, see e.g. Tzanetakis (2005); Burred (2005); Bergstra et al. (2005); Lidy and Rauber (2005)....

  2. Effects of a supplementary final year curriculum on students' clinical reasoning skills as assessed by key-feature examination.

    Science.gov (United States)

    Nikendei, C; Mennin, S; Weyrich, P; Kraus, B; Zipfel, S; Schrauth, M; Jünger, J

    2009-09-01

    The final year of medical education is considered crucial in making students 'fit for purpose'. Studies have shown that many students leave medical school without having experienced sufficient preparation for their upcoming professional life. The aim of this study was to examine the effectiveness of a supplementary internal medicine final year curriculum on clinical reasoning skills. Final year internal medicine students from two universities participated in the study which was based on a static-group design. The experimental group (n = 49) took part in a final year student curriculum with interactive case-based seminars and skills training sessions. The comparison group (n = 25) did not receive any additional training beyond working on the ward. Clinical reasoning skills were assessed using a key-feature pre-post test. Prior to their clinical rotation, the two groups did not differ in the key-feature examination (p skills training sessions are effective and significantly improve the clinical reasoning skills of final year students in internal medicine. Further study is warranted and should look to examine the effectiveness of a final year student curriculum on other performance measures.

  3. A Multiobjective Sparse Feature Learning Model for Deep Neural Networks.

    Science.gov (United States)

    Gong, Maoguo; Liu, Jia; Li, Hao; Cai, Qing; Su, Linzhi

    2015-12-01

    Hierarchical deep neural networks are currently popular learning models for imitating the hierarchical architecture of human brain. Single-layer feature extractors are the bricks to build deep networks. Sparse feature learning models are popular models that can learn useful representations. But most of those models need a user-defined constant to control the sparsity of representations. In this paper, we propose a multiobjective sparse feature learning model based on the autoencoder. The parameters of the model are learnt by optimizing two objectives, reconstruction error and the sparsity of hidden units simultaneously to find a reasonable compromise between them automatically. We design a multiobjective induced learning procedure for this model based on a multiobjective evolutionary algorithm. In the experiments, we demonstrate that the learning procedure is effective, and the proposed multiobjective model can learn useful sparse features.

  4. Analysing the Linux kernel feature model changes using FMDiff

    NARCIS (Netherlands)

    Dintzner, N.J.R.; Van Deursen, A.; Pinzger, M.

    2015-01-01

    Evolving a large scale, highly variable system is a challenging task. For such a system, evolution operations often require to update consistently both their implementation and its feature model. In this context, the evolution of the feature model closely follows the evolution of the system. The pur

  5. Key features of human episodic recollection in the cross-episode retrieval of rat hippocampus representations of space.

    Directory of Open Access Journals (Sweden)

    Eduard Kelemen

    2013-07-01

    Full Text Available Neurophysiological studies focus on memory retrieval as a reproduction of what was experienced and have established that neural discharge is replayed to express memory. However, cognitive psychology has established that recollection is not a verbatim replay of stored information. Recollection is constructive, the product of memory retrieval cues, the information stored in memory, and the subject's state of mind. We discovered key features of constructive recollection embedded in the rat CA1 ensemble discharge during an active avoidance task. Rats learned two task variants, one with the arena stable, the other with it rotating; each variant defined a distinct behavioral episode. During the rotating episode, the ensemble discharge of CA1 principal neurons was dynamically organized to concurrently represent space in two distinct codes. The code for spatial reference frame switched rapidly between representing the rat's current location in either the stationary spatial frame of the room or the rotating frame of the arena. The code for task variant switched less frequently between a representation of the current rotating episode and the stable episode from the rat's past. The characteristics and interplay of these two hippocampal codes revealed three key properties of constructive recollection. (1 Although the ensemble representations of the stable and rotating episodes were distinct, ensemble discharge during rotation occasionally resembled the stable condition, demonstrating cross-episode retrieval of the representation of the remote, stable episode. (2 This cross-episode retrieval at the level of the code for task variant was more likely when the rotating arena was about to match its orientation in the stable episode. (3 The likelihood of cross-episode retrieval was influenced by preretrieval information that was signaled at the level of the code for spatial reference frame. Thus key features of episodic recollection manifest in rat hippocampal

  6. Feature Analysis for Modeling Game Content Quality

    DEFF Research Database (Denmark)

    Shaker, Noor; Yannakakis, Georgios N.; Togelius, Julian

    2011-01-01

    ’ preferences, and by defining the smallest game session size for which the model can still predict reported emotion with acceptable accuracy. Neuroevolutionary preference learning is used to approximate the function from game content to reported emotional preferences. The experiments are based on a modified...

  7. Are animal models relevant to key aspects of human parturition?

    Science.gov (United States)

    Mitchell, Bryan F; Taggart, Michael J

    2009-09-01

    Preterm birth remains the most serious complication of pregnancy and is associated with increased rates of infant death or permanent neurodevelopmental disability. Our understanding of the regulation of parturition remains inadequate. The scientific literature, largely derived from rodent animal models, suggests two major mechanisms regulating the timing of parturition: the withdrawal of the steroid hormone progesterone and a proinflammatory response by the immune system. However, available evidence strongly suggests that parturition in the human has significantly different regulators and mediators from those in most of the animal models. Our objectives are to critically review the data and concepts that have arisen from use of animal models for parturition and to rationalize the use of a new model. Many animal models have contributed to advances in our understanding of the regulation of parturition. However, we suggest that those animals dependent on progesterone withdrawal to initiate parturition clearly have a limitation to their translation to the human. In such models, a linear sequence of events (e.g., luteolysis, progesterone withdrawal, uterine activation, parturition) gives rise to the concept of a "trigger" mechanism. Conversely, we propose that human parturition may arise from the concomitant maturation of several systems in parallel. We have termed this novel concept "modular accumulation of physiological systems" (MAPS). We also emphasize the urgency to determine the precise role of the immune system in the process of parturition in situations other than intrauterine infection. Finally, we accentuate the need to develop a nonprimate animal model whose physiology is more relevant to human parturition. We suggest that the guinea pig displays several key physiological characteristics of gestation that more closely resemble human pregnancy than do currently favored animal models. We conclude that the application of novel concepts and new models are

  8. Feature Analysis for Modeling Game Content Quality

    DEFF Research Database (Denmark)

    Shaker, Noor; Yannakakis, Georgios N.; Togelius, Julian

    2011-01-01

    entertainment for individual game players is to tailor player experience in real-time via automatic game content generation. Modeling the relationship between game content and player preferences or affective states is an important step towards this type of game personalization. In this paper we...... analyse the relationship between level design parameters of platform games and player experience. We introduce a method to extract the most useful information about game content from short game sessions by investigating the size of game session that yields the highest accuracy in predicting players......’ preferences, and by defining the smallest game session size for which the model can still predict reported emotion with acceptable accuracy. Neuroevolutionary preference learning is used to approximate the function from game content to reported emotional preferences. The experiments are based on a modified...

  9. Individual discriminative face recognition models based on subsets of features

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Gomez, David Delgado; Ersbøll, Bjarne Kjær

    2007-01-01

    of the face recognition problem. The elastic net model is able to select a subset of features with low computational effort compared to other state-of-the-art feature selection methods. Furthermore, the fact that the number of features usually is larger than the number of images in the data base makes feature...... selection techniques such as forward selection or lasso regression become inadequate. In the experimental section, the performance of the elastic net model is compared with geometrical and color based algorithms widely used in face recognition such as Procrustes nearest neighbor, Eigenfaces, or Fisher...

  10. An adaptive multi-feature segmentation model for infrared image

    Science.gov (United States)

    Zhang, Tingting; Han, Jin; Zhang, Yi; Bai, Lianfa

    2016-04-01

    Active contour models (ACM) have been extensively applied to image segmentation, conventional region-based active contour models only utilize global or local single feature information to minimize the energy functional to drive the contour evolution. Considering the limitations of original ACMs, an adaptive multi-feature segmentation model is proposed to handle infrared images with blurred boundaries and low contrast. In the proposed model, several essential local statistic features are introduced to construct a multi-feature signed pressure function (MFSPF). In addition, we draw upon the adaptive weight coefficient to modify the level set formulation, which is formed by integrating MFSPF with local statistic features and signed pressure function with global information. Experimental results demonstrate that the proposed method can make up for the inadequacy of the original method and get desirable results in segmenting infrared images.

  11. Data publication and dissemination of interactive keys under the open access model

    Directory of Open Access Journals (Sweden)

    Lyubomir Penev

    2009-09-01

    Full Text Available The concepts of publication, citation and dissemination of interactive keys and other online keys are discussed and illustrated by a sample paper published in the present issue (doi: 10.3897/zookeys.21.271. The present model is based on previous experience with several existing examples of publishing online keys. However, this model also suggests ways to publish, cite, preserve, disseminate and reuse the original data files to the benefit of the authors, future workers, and society in general. To be regarded as a ''formal scientific publication,'' an online key should satisfy the same criteria of peer review, registration, persistence, bibliographic description, etc., as conventional publications. Keys can be published in a form of either ''static'\\''dynamic'' publications. We define a ''static'' publication as a discrete unit of information preserved in a persistent and unchangeable way on the publisher’s Web site and/or on paper and consequently in conventional/electronic libraries and archives. This contrasts with the nature of the Internet, which allows and tends to encourage updating and improvement on a continuing basis. We call ''dynamic'' a publication of an interactive key on a Web site where its contents can be continuously updated. ''Dynamic'' publications meet some of the criteria of a ''formal scientific publication'' (identification, citation and location, while they lack other important features of it (persistence, archiving, indexing, science metric and citation metric services. Dynamic Web-based interactive keys may benefit from publishing the first version of their underlying datasets in a form of “formal scientific publication”. We define here the minimum set of data files to be published for several different platforms (Intkey, Lucid2, Lucid3, MX to ensure both (1 priority, identification, location and citation of the firstly published work and (2 future use and re-use of the keys.

  12. Secret Key and Private Key Constructions for Simple Multiterminal Source Models

    CERN Document Server

    Ye, Chunxuan

    2010-01-01

    We propose an approach for constructing secret and private keys based on the long-known Slepian-Wolf code, due to Wyner, for correlated sources connected by a virtual additive noise channel. Our work is motivated by results of Csisz\\'ar and Narayan which highlight innate connections between secrecy generation by multiple terminals that observe correlated source signals and Slepian-Wolf near-lossless data compression. Explicit procedures for such constructions and their substantiation are provided. The performance of low density parity check channel codes in devising a new class of secret keys is examined.

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

    Science.gov (United States)

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

    2016-10-01

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

  14. Steady progression of osteoarthritic features in the canine groove model

    NARCIS (Netherlands)

    Marijnissen, A.C.A.; Roermund, P.M. van; Verzijl, N.; Tekoppele, J.M.; Bijlsma, J.W.J.; Lafeber, F.P.J.G.

    2002-01-01

    Objective: Recently we described a canine model of osteoarthritis (OA), the groove model with features of OA at 10 weeks after induction, identical to those seen in the canine anterior cruciate ligament transection (ACLT) model. This new model depends on cartilage damage accompanied by transient int

  15. Steady progression of osteoarthritic features in the canine groove model

    NARCIS (Netherlands)

    Marijnissen, A.C.A.; Roermund, P.M. van; Verzijl, N.; Tekoppele, J.M.; Bijlsma, J.W.J.; Lafeber, F.P.J.G.

    2002-01-01

    Objective: Recently we described a canine model of osteoarthritis (OA), the groove model with features of OA at 10 weeks after induction, identical to those seen in the canine anterior cruciate ligament transection (ACLT) model. This new model depends on cartilage damage accompanied by transient int

  16. Key performance indicators in hospital based on balanced scorecard model

    Directory of Open Access Journals (Sweden)

    Hamed Rahimi

    2017-01-01

    Full Text Available Introduction: Performance measurement is receiving increasing verification all over the world. Nowadays in a lot of organizations, irrespective of their type or size, performance evaluation is the main concern and a key issue for top administrators. The purpose of this study is to organize suitable key performance indicators (KPIs for hospitals’ performance evaluation based on the balanced scorecard (BSC. Method: This is a mixed method study. In order to identify the hospital’s performance indicators (HPI, first related literature was reviewed and then the experts’ panel and Delphi method were used. In this study, two rounds were needed for the desired level of consensus. The experts rated the importance of the indicators, on a five-point Likert scale. In the consensus calculation, the consensus percentage was calculated by classifying the values 1-3 as not important (0 and 4-5 to (1 as important. Simple additive weighting technique was used to rank the indicators and select hospital’s KPIs. The data were analyzed by Excel 2010 software. Results: About 218 indicators were obtained from a review of selected literature. Through internal expert panel, 77 indicators were selected. Finally, 22 were selected for KPIs of hospitals. Ten indicators were selected in internal process perspective and 5, 4, and 3 indicators in finance, learning and growth, and customer, respectively. Conclusion: This model can be a useful tool for evaluating and comparing the performance of hospitals. However, this model is flexible and can be adjusted according to differences in the target hospitals. This study can be beneficial for hospital administrators and it can help them to change their perspective about performance evaluation.

  17. Modeling Suspicious Email Detection using Enhanced Feature Selection

    OpenAIRE

    2013-01-01

    The paper presents a suspicious email detection model which incorporates enhanced feature selection. In the paper we proposed the use of feature selection strategies along with classification technique for terrorists email detection. The presented model focuses on the evaluation of machine learning algorithms such as decision tree (ID3), logistic regression, Na\\"ive Bayes (NB), and Support Vector Machine (SVM) for detecting emails containing suspicious content. In the literature, various algo...

  18. Key engineering features of the ITER-FEAT magnet system and implications for the R&D programme

    Science.gov (United States)

    Huguet, M.; ITER Joint Central Team; ITER Home Teams

    2001-10-01

    The magnet design of the new ITER-FEAT machine comprises 18 toroidal field (TF) coils, a central solenoid (CS), 6 poloidal field coils and correction coils. A key driver of this new design is the requirement to generate and control plasmas with a relatively high elongation (κ95 = 1.7) and a relatively high triangularity (δ95 = 0.35). This has led to a design where the CS is vertically segmented and self-standing and the TF coils are wedged along their inboard legs. Another important design driver is the requirement to achieve a high operational reliability of the magnets, and this has resulted in several unconventional designs, and in particular the use of conductors supported in radial plates for the winding pack of the TF coils. A key mechanical issue is the cyclic loading of the TF coil cases due to the out-of-plane loads which result from the interaction of the TF coil current and the poloidal field. These loads are resisted by a combination of shear keys and `pre-compression' rings able to provide a centripetal preload at assembly. The fatigue life of the CS conductor jacket is another issue, as it determines the CS performance in terms of the flux generation. Two jacket materials and designs are under study. Since 1993, the ITER magnet R&D programme has been focused on the manufacture and testing of a CS and a TF model coil. During its testing, the CS model coil has successfully achieved all its performance targets in DC and AC operations. The manufacture of the TF model coil is complete. The manufacture of segments of the full scale TF coil case is another important and successful part of this programme and is near completion. New R&D effort is now being initiated to cover specific aspects of the ITER-FEAT design.

  19. A Co-modeling Method Based on Component Features for Mechatronic Devices in Aero-engines

    Science.gov (United States)

    Wang, Bin; Zhao, Haocen; Ye, Zhifeng

    2017-08-01

    Data-fused and user-friendly design of aero-engine accessories is required because of their structural complexity and stringent reliability. This paper gives an overview of a typical aero-engine control system and the development process of key mechatronic devices used. Several essential aspects of modeling and simulation in the process are investigated. Considering the limitations of a single theoretic model, feature-based co-modeling methodology is suggested to satisfy the design requirements and compensate for diversity of component sub-models for these devices. As an example, a stepper motor controlled Fuel Metering Unit (FMU) is modeled in view of the component physical features using two different software tools. An interface is suggested to integrate the single discipline models into the synthesized one. Performance simulation of this device using the co-model and parameter optimization for its key components are discussed. Comparison between delivery testing and the simulation shows that the co-model for the FMU has a high accuracy and the absolute superiority over a single model. Together with its compatible interface with the engine mathematical model, the feature-based co-modeling methodology is proven to be an effective technical measure in the development process of the device.

  20. Selecting Optimal Subset of Features for Student Performance Model

    Directory of Open Access Journals (Sweden)

    Hany M. Harb

    2012-09-01

    Full Text Available Educational data mining (EDM is a new growing research area and the essence of data mining concepts are used in the educational field for the purpose of extracting useful information on the student behavior in the learning process. Classification methods like decision trees, rule mining, and Bayesian network, can be applied on the educational data for predicting the student behavior like performance in an examination. This prediction may help in student evaluation. As the feature selection influences the predictive accuracy of any performance model, it is essential to study elaborately the effectiveness of student performance model in connection with feature selection techniques. The main objective of this work is to achieve high predictive performance by adopting various feature selection techniques to increase the predictive accuracy with least number of features. The outcomes show a reduction in computational time and constructional cost in both training and classification phases of the student performance model.

  1. Whispered speaker identification based on feature and model hybrid compensation

    Institute of Scientific and Technical Information of China (English)

    GU Xiaojiang; ZHAO Heming; Lu Gang

    2012-01-01

    In order to increase short time whispered speaker recognition rate in variable chan- nel conditions, the hybrid compensation in model and feature domains was proposed. This method is based on joint factor analysis in training model stage. It extracts speaker factor and eliminates channel factor by estimating training speech speaker and channel spaces. Then in the test stage, the test speech channel factor is projected into feature space to engage in feature compensation, so it can remove channel information both in model and feature domains in order to improve recognition rate. The experiment result shows that the hybrid compensation can obtain the similar recognition rate in the three different training channel conditions and this method is more effective than joint factor analysis in the test of short whispered speech.

  2. Spatial uncertainty model for visual features using a Kinect™ sensor.

    Science.gov (United States)

    Park, Jae-Han; Shin, Yong-Deuk; Bae, Ji-Hun; Baeg, Moon-Hong

    2012-01-01

    This study proposes a mathematical uncertainty model for the spatial measurement of visual features using Kinect™ sensors. This model can provide qualitative and quantitative analysis for the utilization of Kinect™ sensors as 3D perception sensors. In order to achieve this objective, we derived the propagation relationship of the uncertainties between the disparity image space and the real Cartesian space with the mapping function between the two spaces. Using this propagation relationship, we obtained the mathematical model for the covariance matrix of the measurement error, which represents the uncertainty for spatial position of visual features from Kinect™ sensors. In order to derive the quantitative model of spatial uncertainty for visual features, we estimated the covariance matrix in the disparity image space using collected visual feature data. Further, we computed the spatial uncertainty information by applying the covariance matrix in the disparity image space and the calibrated sensor parameters to the proposed mathematical model. This spatial uncertainty model was verified by comparing the uncertainty ellipsoids for spatial covariance matrices and the distribution of scattered matching visual features. We expect that this spatial uncertainty model and its analyses will be useful in various Kinect™ sensor applications.

  3. Spatial Uncertainty Model for Visual Features Using a Kinect™ Sensor

    Directory of Open Access Journals (Sweden)

    Jae-Han Park

    2012-06-01

    Full Text Available This study proposes a mathematical uncertainty model for the spatial measurement of visual features using Kinect™ sensors. This model can provide qualitative and quantitative analysis for the utilization of Kinect™ sensors as 3D perception sensors. In order to achieve this objective, we derived the propagation relationship of the uncertainties between the disparity image space and the real Cartesian space with the mapping function between the two spaces. Using this propagation relationship, we obtained the mathematical model for the covariance matrix of the measurement error, which represents the uncertainty for spatial position of visual features from Kinect™ sensors. In order to derive the quantitative model of spatial uncertainty for visual features, we estimated the covariance matrix in the disparity image space using collected visual feature data. Further, we computed the spatial uncertainty information by applying the covariance matrix in the disparity image space and the calibrated sensor parameters to the proposed mathematical model. This spatial uncertainty model was verified by comparing the uncertainty ellipsoids for spatial covariance matrices and the distribution of scattered matching visual features. We expect that this spatial uncertainty model and its analyses will be useful in various Kinect™ sensor applications.

  4. Towards the maturity model for feature oriented domain analysis

    Directory of Open Access Journals (Sweden)

    Muhammad Javed

    2014-09-01

    Full Text Available Assessing the quality of a model has always been a challenge for researchers in academia and industry. The quality of a feature model is a prime factor because it is used in the development of products. A degraded feature model leads the development of low quality products. Few efforts have been made on improving the quality of feature models. This paper is an effort to present our ongoing work i.e. development of FODA (Feature Oriented Domain Analysis maturity model which will help to evaluate the quality of a given feature model. In this paper, we provide the quality levels along with their descriptions. The proposed model consists of four levels starting from level 0 to level 3. Design of each level is based on the severity of errors, whereas severity of errors decreases from level 0 to level 3. We elaborate each level with the help of examples. We borrowed all examples from the material published by the research community of Software Product Lines (SPL for the application of our framework.

  5. A System-Level Throughput Model for Quantum Key Distribution

    Science.gov (United States)

    2015-09-17

    quantum mechanics to generate and distribute shared secret keying material. QKD systems generate and distribute key by progressing through a number of...communicate a seed to prime random number generation to construct a very large matrix used in the calculation of Privacy Amplification. We assume that... generate a desired number of final key bits. RQ7: What are the implications of altering the amount of Alice’s memory allocated for Quantum Exchange

  6. Automatic Extraction of Three Dimensional Prismatic Machining Features from CAD Model

    Directory of Open Access Journals (Sweden)

    B.V. Sudheer Kumar

    2011-12-01

    Full Text Available Machining features recognition provides the necessary platform for the computer aided process planning (CAPP and plays a key role in the integration of computer aided design (CAD and computer aided manufacturing (CAM. This paper presents a new methodology for extracting features from the geometrical data of the CAD Model present in the form of Virtual Reality Modeling Language (VRML files. First, the point cloud is separated into the available number of horizontal cross sections. Each cross section consists of a 2D point cloud. Then, a collection of points represented by a set of feature points is derived for each slice, describing the cross section accurately, and providing the basis for a feature-extraction. These extracted manufacturing features, gives the necessary information regarding the manufacturing activities tomanufacture the part. Software in Microsoft Visual C++ environment is developed to recognize the features, where geometric information of the part isextracted from the CAD model. By using this data, anoutput file i.e., text file is generated, which gives all the machinable features present in the part. This process has been tested on various parts and successfully extracted all the features

  7. Modeling multiple visual words assignment for bag-of-features based medical image retrieval

    KAUST Repository

    Wang, Jim Jing-Yan

    2012-01-01

    In this paper, we investigate the bag-of-features based medical image retrieval methods, which represent an image as a collection of local features, such as image patch and key points with SIFT descriptor. To improve the bag-of-features method, we first model the assignment of local descriptor as contribution functions, and then propose a new multiple assignment strategy. By assuming the local feature can be reconstructed by its neighboring visual words in vocabulary, we solve the reconstruction weights as a QP problem and then use the solved weights as contribution functions, which results in a new assignment method called the QP assignment. We carry our experiments on ImageCLEFmed datasets. Experiments\\' results show that our proposed method exceeds the performances of traditional solutions and works well for the bag-of-features based medical image retrieval tasks.

  8. Adaptability Feature's Concept, Modeling and Application in Product Design

    Institute of Scientific and Technical Information of China (English)

    BaiYuewei; ChenZhuoning; WeiShuangyu; BinHongzan

    2003-01-01

    The current 3D CAD/CAM system, both research prototypes and commercial systems, based on traditional feature modeling are always hampered by the problems in their complicated modeling and difficult maintaining. This paper introduces a new method for modeling parts by using adaptability feature (AF), by which the consistent relationship among parts and assemblies can be maintained in whole design process. In addition, the design process, can be speeded, time-to-market shortened, and product quality improved. Some essential issues of the strategy are discussed. A system, KMCAD3D, by taking advantages of AF has been developed. It is shown that the method discussed is a feasible and effective way to improve current feature modeling technology.

  9. Detecting feature interactions in Web services with model checking techniques

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    As a platform-independent software system, a Web service is designed to offer interoperability among diverse and heterogeneous applications.With the introduction of service composition in the Web service creation, various message interactions among the atomic services result in a problem resembling the feature interaction problem in the telecommunication area.This article defines the problem as feature interaction in Web services and proposes a model checking-based detection method.In the method, the Web service description is translated to the Promela language - the input language of the model checker simple promela interpreter (SPIN), and the specific properties, expressed as linear temporal logic (LTL) formulas, are formulated according to our classification of feature interaction.Then, SPIN is used to check these specific properties to detect the feature interaction in Web services.

  10. Confirming the key role of Ar+ ion bombardment in growth feature of nanostructured carbon materials by PECVD.

    Science.gov (United States)

    Liu, Yulin; Lin, Jinghuang; Jia, Henan; Chen, Shulin; Qi, J; Qu, Chaoqun; Cao, Jian; Feng, Jicai; Fei, Weidong

    2017-09-20

    In order to confirm the key role of plasma etching in growth feature of nanostructured carbon materials (NCMs), here we reported a novel strategy to in-situ create different states of plasma etching conditions in plasma enhanced chemical vapor deposition (PECVD) by separating catalyst film from substrate. Different plasma-related environments on either side of the catalyst film were created simultaneously for achieving multi-layered structural NCMs. Results showed that plasma etching is observed crucial and complex for the growth of NCMs. The effect of plasma etching has both positive and negative sides on carbon nanotubes (CNTs). On one hand, plasma etching can break up the structure of CNTs and thus thin CNTs cannot be obtained. On the other hand, plasma etching can remove the redundant carbon on surface of large catalyst particles, contributing to catalyzing thick CNTs. As a result, the diameter of CNTs depends on the state of plasma etching. For vertically oriented few-layer graphene (VFG), plasma etching is an essential asset and strong plasma etching can even change the CNTs into VFG. Therefore, specific multi-layered structural NCMs can be obtained by PECVD combining plasma etching with catalyst separation method, which is promising in many fields. © 2017 IOP Publishing Ltd.

  11. Active Shape Models Using Scale Invariant Feature Transform

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A new active shape models (ASMs) was presented, which is driven by scale invariant feature transform (SIFT) local descriptor instead of normalizing first order derivative profiles in the original formulation, to segment lung fields from chest radiographs. The modified SIFT local descriptor, more distinctive than the general intensity and gradient features, is used to characterize the image features in the vicinity of each pixel at each resolution level during the segmentation optimization procedure. Experimental results show that the proposed method is more robust and accurate than the original ASMs in terms of an average overlap percentage and average contour distance in segmenting the lung fields from an available public database.

  12. The Saturnian ribbon feature: A baroclinically unstable model

    Science.gov (United States)

    Godfrey, D.

    1986-01-01

    Using measurements made by the Voyager spacecraft, an oscillatory feature in the northern midlatitudes of Saturn is examined. Measurements made by the imaging and infrared instruments are used to estimate its horizontal wavelength and vertical extent. Some of these characteristics suggest that the feature could be due to baroclinic instability. A numerical model is described of such an instability with parameters based upon the Voyager observations, and using the lower boundary condition developed by Gierasch et al for the Jovian planets.

  13. A feature fusion based forecasting model for financial time series.

    Science.gov (United States)

    Guo, Zhiqiang; Wang, Huaiqing; Liu, Quan; Yang, Jie

    2014-01-01

    Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models.

  14. A feature fusion based forecasting model for financial time series.

    Directory of Open Access Journals (Sweden)

    Zhiqiang Guo

    Full Text Available Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models.

  15. Features of Functioning the Integrated Building Thermal Model

    Directory of Open Access Journals (Sweden)

    Morozov Maxim N.

    2017-01-01

    Full Text Available A model of the building heating system, consisting of energy source, a distributed automatic control system, elements of individual heating unit and heating system is designed. Application Simulink of mathematical package Matlab is selected as a platform for the model. There are the specialized application Simscape libraries in aggregate with a wide range of Matlab mathematical tools allow to apply the “acausal” modeling concept. Implementation the “physical” representation of the object model gave improving the accuracy of the models. Principle of operation and features of the functioning of the thermal model is described. The investigations of building cooling dynamics were carried out.

  16. Unified Saliency Detection Model Using Color and Texture Features.

    Science.gov (United States)

    Zhang, Libo; Yang, Lin; Luo, Tiejian

    2016-01-01

    Saliency detection attracted attention of many researchers and had become a very active area of research. Recently, many saliency detection models have been proposed and achieved excellent performance in various fields. However, most of these models only consider low-level features. This paper proposes a novel saliency detection model using both color and texture features and incorporating higher-level priors. The SLIC superpixel algorithm is applied to form an over-segmentation of the image. Color saliency map and texture saliency map are calculated based on the region contrast method and adaptive weight. Higher-level priors including location prior and color prior are incorporated into the model to achieve a better performance and full resolution saliency map is obtained by using the up-sampling method. Experimental results on three datasets demonstrate that the proposed saliency detection model outperforms the state-of-the-art models.

  17. Enhanced HMAX model with feedforward feature learning for multiclass categorization

    Directory of Open Access Journals (Sweden)

    Yinlin eLi

    2015-10-01

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

  18. Goal-directed learning of features and forward models.

    Science.gov (United States)

    Saeb, Sohrab; Weber, Cornelius; Triesch, Jochen

    2009-01-01

    The brain is able to perform actions based on an adequate internal representation of the world, where task-irrelevant features are ignored and incomplete sensory data are estimated. Traditionally, it is assumed that such abstract state representations are obtained purely from the statistics of sensory input for example by unsupervised learning methods. However, more recent findings suggest an influence of the dopaminergic system, which can be modeled by a reinforcement learning approach. Standard reinforcement learning algorithms act on a single layer network connecting the state space to the action space. Here, we involve in a feature detection stage and a memory layer, which together, construct the state space for a learning agent. The memory layer consists of the state activation at the previous time step as well as the previously chosen action. We present a temporal difference based learning rule for training the weights from these additional inputs to the state layer. As a result, the performance of the network is maintained both, in the presence of task-irrelevant features, and at randomly occurring time steps during which the input is invisible. Interestingly, a goal-directed forward model emerges from the memory weights, which only covers the state-action pairs that are relevant to the task. The model presents a link between reinforcement learning, feature detection and forward models and may help to explain how reward systems recruit cortical circuits for goal-directed feature detection and prediction.

  19. Attentional spreading to task-irrelevant object features: experimental support and a 3-step model of attention for object-based selection and feature-based processing modulation.

    Science.gov (United States)

    Wegener, Detlef; Galashan, Fingal Orlando; Aurich, Maike Kathrin; Kreiter, Andreas Kurt

    2014-01-01

    Directing attention to a specific feature of an object has been linked to different forms of attentional modulation. Object-based attention theory founds on the finding that even task-irrelevant features at the selected object are subject to attentional modulation, while feature-based attention theory proposes a global processing benefit for the selected feature even at other objects. Most studies investigated either the one or the other form of attention, leaving open the possibility that both object- and feature-specific attentional effects do occur at the same time and may just represent two sides of a single attention system. We here investigate this issue by testing attentional spreading within and across objects, using reaction time (RT) measurements to changes of attended and unattended features on both attended and unattended objects. We asked subjects to report color and speed changes occurring on one of two overlapping random dot patterns (RDPs), presented at the center of gaze. The key property of the stimulation was that only one of the features (e.g., motion direction) was unique for each object, whereas the other feature (e.g., color) was shared by both. The results of two experiments show that co-selection of unattended features even occurs when those features have no means for selecting the object. At the same time, they demonstrate that this processing benefit is not restricted to the selected object but spreads to the task-irrelevant one. We conceptualize these findings by a 3-step model of attention that assumes a task-dependent top-down gain, object-specific feature selection based on task- and binding characteristics, and a global feature-specific processing enhancement. The model allows for the unification of a vast amount of experimental results into a single model, and makes various experimentally testable predictions for the interaction of object- and feature-specific processes.

  20. Attentional spreading to task-irrelevant object features: Experimental support and a 3-step model of attention for object-based selection and feature-based processing modulation

    Directory of Open Access Journals (Sweden)

    Detlef eWegener

    2014-06-01

    Full Text Available Directing attention to a specific feature of an object has been linked to different forms of attentional modulation. Object-based attention theory founds on the finding that even task-irrelevant features at the selected object are subject to attentional modulation, while feature-based attention theory proposes a global processing benefit for the selected feature even at other objects. Most studies investigated either the one or the other form of attention, leaving open the possibility that both object- and feature-specific attentional effects do occur at the same time and may just represent two sides of a single attention system. We here investigate this issue by testing attentional spreading within and across objects, using reaction time measurements to changes of attended and unattended features on both attended and unattended objects. We asked subjects to report color and speed changes occurring on one of two overlapping random dot patterns, presented at the center of gaze. The key property of the stimulation was that only one of the features (e.g. motion direction was unique for each object, whereas the other feature (e.g. color was shared by both. The results of two experiments show that co-selection of unattended features even occurs when those features have no means for selecting the object. At the same time, they demonstrate that this processing benefit is not restricted to the selected object but spreads to the task-irrelevant one. We conceptualize these findings by a 3-step model of attention that assumes a task-dependent top-down gain, object-specific feature selection based on task- and binding characteristics, and a global feature-specific processing enhancement. The model allows for the unification of a vast amount of experimental results into a single model, and makes various experimentally testable predictions for the interaction of object- and feature-specific processes.

  1. Ensemble feature selection integrating elitist roles and quantum game model

    Institute of Scientific and Technical Information of China (English)

    Weiping Ding; Jiandong Wang; Zhijin Guan; Quan Shi

    2015-01-01

    To accelerate the selection process of feature subsets in the rough set theory (RST), an ensemble elitist roles based quantum game (EERQG) algorithm is proposed for feature selec-tion. Firstly, the multilevel elitist roles based dynamics equilibrium strategy is established, and both immigration and emigration of elitists are able to be self-adaptive to balance between exploration and exploitation for feature selection. Secondly, the utility matrix of trust margins is introduced to the model of multilevel elitist roles to enhance various elitist roles’ performance of searching the optimal feature subsets, and the win-win utility solutions for feature selec-tion can be attained. Meanwhile, a novel ensemble quantum game strategy is designed as an intriguing exhibiting structure to perfect the dynamics equilibrium of multilevel elitist roles. Final y, the en-semble manner of multilevel elitist roles is employed to achieve the global minimal feature subset, which wil greatly improve the fea-sibility and effectiveness. Experiment results show the proposed EERQG algorithm has superiority compared to the existing feature selection algorithms.

  2. Modeling neuron selectivity over simple midlevel features for image classification.

    Science.gov (United States)

    Shu Kong; Zhuolin Jiang; Qiang Yang

    2015-08-01

    We now know that good mid-level features can greatly enhance the performance of image classification, but how to efficiently learn the image features is still an open question. In this paper, we present an efficient unsupervised midlevel feature learning approach (MidFea), which only involves simple operations, such as k-means clustering, convolution, pooling, vector quantization, and random projection. We show this simple feature can also achieve good performance in traditional classification task. To further boost the performance, we model the neuron selectivity (NS) principle by building an additional layer over the midlevel features prior to the classifier. The NS-layer learns category-specific neurons in a supervised manner with both bottom-up inference and top-down analysis, and thus supports fast inference for a query image. Through extensive experiments, we demonstrate that this higher level NS-layer notably improves the classification accuracy with our simple MidFea, achieving comparable performances for face recognition, gender classification, age estimation, and object categorization. In particular, our approach runs faster in inference by an order of magnitude than sparse coding-based feature learning methods. As a conclusion, we argue that not only do carefully learned features (MidFea) bring improved performance, but also a sophisticated mechanism (NS-layer) at higher level boosts the performance further.

  3. Solving Topological and Geometrical Constraints in Bridge Feature Model

    Institute of Scientific and Technical Information of China (English)

    PENG Weibing; SONG Liangliang; PAN Guoshuai

    2008-01-01

    The capacity that computer can solve more complex design problem was gradually increased.Bridge designs need a breakthrough in the current development limitations, and then become more intelli-gent and integrated. This paper proposes a new parametric and feature-based computer aided design (CAD) models which can represent families of bridge objects, includes knowledge representation, three-dimensional geometric topology relationships. The realization of a family member is found by solving first the geometdc constraints, and then the topological constraints. From the geometric solution, constraint equations are constructed. Topology solution is developed by feature dependencies graph between bridge objects. Finally, feature parameters are proposed to drive bridge design with feature parameters. Results from our implementation show that the method can help to facilitate bridge design.

  4. Analysis of expressed genes of the bacterium 'Candidatus phytoplasma Mali' highlights key features of virulence and metabolism.

    Directory of Open Access Journals (Sweden)

    Christin Siewert

    Full Text Available 'Candidatus Phytoplasma mali' is a phytopathogenic bacterium of the family Acholeplasmataceae assigned to the class Mollicutes. This causative agent of the apple proliferation colonizes in Malus domestica the sieve tubes of the plant phloem resulting in a range of symptoms such as witches'--broom formation, reduced vigor and affecting size and quality of the crop. The disease is responsible for strong economical losses in Europe. Although the genome sequence of the pathogen is available, there is only limited information on expression of selected genes and metabolic key features that have not been examined on the transcriptomic or proteomic level so far. This situation is similar to many other phytoplasmas. In the work presented here, RNA-Seq and mass spectrometry shotgun techniques were applied on tissue samples from Nicotiana occidentalis infected by 'Ca. P. mali' strain AT providing insights into transcriptome and proteome of the pathogen. Data analysis highlights expression of 208 genes including 14 proteins located in the terminal inverted repeats of the linear chromosome. Beside a high portion of house keeping genes, the recently discussed chaperone GroES/GroEL is expressed. Furthermore, gene expression involved in formation of a type IVB and of the Sec-dependent secretion system was identified as well as the highly expressed putative pathogenicity-related SAP11-like effector protein. Metabolism of phytoplasmas depends on the uptake of spermidine/putescine, amino acids, co-factors, carbohydrates and in particular malate/citrate. The expression of these transporters was confirmed and the analysis of the carbohydrate cycle supports the suggested alternative energy-providing pathway for phytoplasmas releasing acetate and providing ATP. The phylogenetic analyses of malate dehydrogenase and acetate kinase in phytoplasmas show a closer relatedness to the Firmicutes in comparison to Mycoplasma species indicating an early divergence of the

  5. Bayesian latent feature modeling for modeling bipartite networks with overlapping groups

    DEFF Research Database (Denmark)

    Jørgensen, Philip H.; Mørup, Morten; Schmidt, Mikkel Nørgaard;

    2016-01-01

    Bi-partite networks are commonly modelled using latent class or latent feature models. Whereas the existing latent class models admit marginalization of parameters specifying the strength of interaction between groups, existing latent feature models do not admit analytical marginalization...... of the parameters accounting for the interaction strength within the feature representation. We propose a new binary latent feature model that admits analytical marginalization of interaction strengths such that model inference reduces to assigning nodes to latent features. We propose a constraint inspired...... to the infinite relational model and the infinite Bernoulli mixture model. We find that the model provides a new latent feature representation of structure while in link-prediction performing close to existing models. Our current extension of the notion of communities and collapsed inference to binary latent...

  6. Preferential Attachment Model with Degree Bound and its Application to Key Predistribution in WSN

    CERN Document Server

    Ruj, Sushmita

    2016-01-01

    Preferential attachment models have been widely studied in complex networks, because they can explain the formation of many networks like social networks, citation networks, power grids, and biological networks, to name a few. Motivated by the application of key predistribution in wireless sensor networks (WSN), we initiate the study of preferential attachment with degree bound. Our paper has two important contributions to two different areas. The first is a contribution in the study of complex networks. We propose preferential attachment model with degree bound for the first time. In the normal preferential attachment model, the degree distribution follows a power law, with many nodes of low degree and a few nodes of high degree. In our scheme, the nodes can have a maximum degree $d_{\\max}$, where $d_{\\max}$ is an integer chosen according to the application. The second is in the security of wireless sensor networks. We propose a new key predistribution scheme based on the above model. The important features ...

  7. The changing model of big pharma: impact of key trends.

    Science.gov (United States)

    Gautam, Ajay; Pan, Xiaogang

    2016-03-01

    Recent years have seen exciting breakthroughs in biomedical sciences that are producing truly novel therapeutics for unmet patient needs. However, the pharmaceutical industry is also facing significant barriers in the form of pricing and reimbursement, continued patent expirations and challenging market dynamics. In this article, we have analyzed data from the 1995-2015 period, on key aspects such as revenue distribution, research units, portfolio mix and emerging markets to identify four key trends that help to understand the change in strategic focus, realignment of R&D footprint, the shift from primary care toward specialty drugs and biologics and the growth of emerging markets as major revenue drivers for big pharma.

  8. Toward Designing a Quantum Key Distribution Network Simulation Model

    Directory of Open Access Journals (Sweden)

    Miralem Mehic

    2016-01-01

    Full Text Available As research in quantum key distribution network technologies grows larger and more complex, the need for highly accurate and scalable simulation technologies becomes important to assess the practical feasibility and foresee difficulties in the practical implementation of theoretical achievements. In this paper, we described the design of simplified simulation environment of the quantum key distribution network with multiple links and nodes. In such simulation environment, we analyzed several routing protocols in terms of the number of sent routing packets, goodput and Packet Delivery Ratio of data traffic flow using NS-3 simulator.

  9. Advancing Affect Modeling via Preference Learning and Unsupervised Feature Extraction

    DEFF Research Database (Denmark)

    Martínez, Héctor Pérez

    over the other examined methods. The second challenge addressed in this thesis refers to the extraction of relevant information from physiological modalities. Deep learning is proposed as an automatic approach to extract input features for models of affect from physiological signals. Experiments...... difficulties, ordinal reports such as rankings and ratings can yield more reliable affect annotations than alternative tools. This thesis explores preference learning methods to automatically learn computational models from ordinal annotations of affect. In particular, an extensive collection of training...... the complexity of hand-crafting feature extractors that combine information across dissimilar modalities of input. Frequent sequence mining is presented as a method to learn feature extractors that fuse physiological and contextual information. This method is evaluated in a game-based dataset and compared...

  10. 3D facial geometric features for constrained local model

    NARCIS (Netherlands)

    Cheng, Shiyang; Zafeiriou, Stefanos; Asthana, Akshay; Pantic, Maja

    2014-01-01

    We propose a 3D Constrained Local Model framework for deformable face alignment in depth image. Our framework exploits the intrinsic 3D geometric information in depth data by utilizing robust histogram-based 3D geometric features that are based on normal vectors. In addition, we demonstrate the fusi

  11. Observational evidence for various models of Moving Magnetic Features

    Science.gov (United States)

    Lee, Jeongwoo W.

    1992-01-01

    New measurements of Moving Magnetic Features (MMFs) based on the observations of the active region NOAA 5612 made at Big Bear Solar Observatory (BBSO) on August 2, 1989 are presented. The existing theoretical models are checked against the new observations, and the origin of MMFs conjectured from the deduced observational constraints is discussed.

  12. Automatic computational models of acoustical category features: Talking versus singing

    Science.gov (United States)

    Gerhard, David

    2003-10-01

    The automatic discrimination between acoustical categories has been an increasingly interesting problem in the fields of computer listening, multimedia databases, and music information retrieval. A system is presented which automatically generates classification models, given a set of destination classes and a set of a priori labeled acoustic events. Computational models are created using comparative probability density estimations. For the specific example presented, the destination classes are talking and singing. Individual feature models are evaluated using two measures: The Kologorov-Smirnov distance measures feature separation, and accuracy is measured using absolute and relative metrics. The system automatically segments the event set into a user-defined number (n) of development subsets, and runs a development cycle for each set, generating n separate systems, each of which is evaluated using the above metrics to improve overall system accuracy and to reduce inherent data skew from any one development subset. Multiple features for the same acoustical categories are then compared for underlying feature overlap using cross-correlation. Advantages of automated computational models include improved system development and testing, shortened development cycle, and automation of common system evaluation tasks. Numerical results are presented relating to the talking/singing classification problem.

  13. A model for explaining some features of shuttle glow

    Science.gov (United States)

    Peters, P. N.

    1985-01-01

    A solid state model is proposed which hopefully removes some of the objections to excited atoms being sources for light emanating from surfaces. Glow features are discussed in terms of excited oxygen atoms impinged on the surface, although other species could be treated similarly. Band formation, excited lifetime shortening and glow color are discussed in terms of this model. The model's inability to explain glow emanating above surfaces indicates a necessity for other mechanisms to satisfy this requirements. Several ways of testing the model are described.

  14. Where's the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network.

    Science.gov (United States)

    Hartmann, Christoph; Lazar, Andreea; Nessler, Bernhard; Triesch, Jochen

    2015-12-01

    Even in the absence of sensory stimulation the brain is spontaneously active. This background "noise" seems to be the dominant cause of the notoriously high trial-to-trial variability of neural recordings. Recent experimental observations have extended our knowledge of trial-to-trial variability and spontaneous activity in several directions: 1. Trial-to-trial variability systematically decreases following the onset of a sensory stimulus or the start of a motor act. 2. Spontaneous activity states in sensory cortex outline the region of evoked sensory responses. 3. Across development, spontaneous activity aligns itself with typical evoked activity patterns. 4. The spontaneous brain activity prior to the presentation of an ambiguous stimulus predicts how the stimulus will be interpreted. At present it is unclear how these observations relate to each other and how they arise in cortical circuits. Here we demonstrate that all of these phenomena can be accounted for by a deterministic self-organizing recurrent neural network model (SORN), which learns a predictive model of its sensory environment. The SORN comprises recurrently coupled populations of excitatory and inhibitory threshold units and learns via a combination of spike-timing dependent plasticity (STDP) and homeostatic plasticity mechanisms. Similar to balanced network architectures, units in the network show irregular activity and variable responses to inputs. Additionally, however, the SORN exhibits sequence learning abilities matching recent findings from visual cortex and the network's spontaneous activity reproduces the experimental findings mentioned above. Intriguingly, the network's behaviour is reminiscent of sampling-based probabilistic inference, suggesting that correlates of sampling-based inference can develop from the interaction of STDP and homeostasis in deterministic networks. We conclude that key observations on spontaneous brain activity and the variability of neural responses can be

  15. Analysis of the key influence factors on brand of higher education organizations. Feature of the fashion industry

    Directory of Open Access Journals (Sweden)

    I.A. Hardabkhadze

    2013-03-01

    Full Text Available The aim of this article is the search of rational suite of factors which have a significant impact on various aspects of the educational institution, and the development model of brand management system which is based on these factors.To achieve this aim the following tasks were formulated and solved:the analysis of main factors that adequately describe activities of the university was fulfilled;the suite of factors of influene on the state of the university brand, was selected from the lists of main factors which present its functioning;the approach of estimation brand current status which is the multi-component model was presented;the vision of brand management on the basis of balanced indicators which include necessary value was described;the features of the brand educational services were identified in the field of the fashion design.The results of the analysis. First the multi-component model of balanced brand management of the higher institution was proposed. For the creation of the model the factors that have the greatest impact on the brand were used. These factors must describe the different directions of educational institutions functioning process as fully as possible and must have minimal interaction with each other.The suite of main factors that characterize the functioning of a modern university can be represented by the variety of options. As one of the direction model uses the consolidated rating, based on the materials of the international agency Webometrics and rating tables from Ukrainian agencies which represented by the Rating of Ukrainian higher educational institutions from The money Journal and Summary rating of Ukrainian universities Compass 2012. Another direction is represented by the Scientific-methodical and professional base. Technological facilities of equipping. In the third direction is used complex factor Activity of team. Distributed management strategy. Cultural, social and living factors.Chosen strategy of

  16. Feature Solution in the Process of Parameterizing Port Model

    Institute of Scientific and Technical Information of China (English)

    彭禹; 郝志勇; 孙秀永; 刘东航; 付鲁华

    2004-01-01

    Aimed at attaining to an integrated and effective pattern to guide the port design process, this paper puts forward a new conception of feature solution, which is based on the parameterized feature modeling. With this solution, the overall pert pre-design process can be conducted in a virtual pattern. Moreover, to evaluate the advantages of the new design pattern, an application of port system has been involved in this paper; and in the process of application a computational fluid dynamic analysis is concerned. An ideal effect of cleanness,high efficiency and high precision has been achieved.

  17. Regional profiles of the candidate tau PET ligand 18F-AV-1451 recapitulate key features of Braak histopathological stages.

    Science.gov (United States)

    Schwarz, Adam J; Yu, Peng; Miller, Bradley B; Shcherbinin, Sergey; Dickson, James; Navitsky, Michael; Joshi, Abhinay D; Devous, Michael D; Mintun, Mark S

    2016-05-01

    SEE THAL AND VANDENBERGHE DOI101093/BRAIN/AWW057 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Post-mortem Braak staging of neurofibrillary tau tangle topographical distribution is one of the core neuropathological criteria for the diagnosis of Alzheimer's disease. The recent development of positron emission tomography tracers targeting neurofibrillary tangles has enabled the distribution of tau pathology to be imaged in living subjects. Methods for extraction of classic Braak staging from in vivo imaging of neurofibrillary tau tangles have not yet been explored. Standardized uptake value ratio images were calculated from 80-100 minute (18)F-AV-1451 (also known as T807) positron emission tomography scans obtained from n = 14 young reference subjects (age 21-39 years, Mini-Mental State Examination 29-30) and n = 173 older test subjects (age 50-95 years) comprising amyloid negative cognitively normal (n = 42), clinically-diagnosed mild cognitive impairment (amyloid positive, n = 47, and amyloid negative, n = 40) and Alzheimer's disease (amyloid positive, n = 28, and amyloid negative, n = 16). We defined seven regions of interest in anterior temporal lobe and occipital lobe sections corresponding closely to those used as decision points in Braak staging. An algorithm based on the Braak histological staging procedure was applied to estimate Braak stages directly from the region of interest profiles in each subject. Quantitative region-based analysis of (18)F-AV-1451 images yielded region of interest and voxel level profiles that mirrored key features of neuropathological tau progression including profiles consistent with Braak stages 0 through VI. A simple set of decision rules enabled plausible Braak stages corresponding to stereotypical progression patterns to be objectively estimated in 149 (86%) of test subjects. An additional 12 (7%) subjects presented with predefined variant profiles (relative sparing of the hippocampus and/or occipital lobe). The estimated Braak

  18. Powerline Communications Channel Modelling Methodology Based on Statistical Features

    CERN Document Server

    Tan, Bo

    2012-01-01

    This paper proposes a new channel modelling method for powerline communications networks based on the multipath profile in the time domain. The new channel model is developed to be applied in a range of Powerline Communications (PLC) research topics such as impulse noise modelling, deployment and coverage studies, and communications theory analysis. To develop the methodology, channels are categorised according to their propagation distance and power delay profile. The statistical multipath parameters such as path arrival time, magnitude and interval for each category are analyzed to build the model. Each generated channel based on the proposed statistical model represents a different realisation of a PLC network. Simulation results in similar the time and frequency domains show that the proposed statistical modelling method, which integrates the impact of network topology presents the PLC channel features as the underlying transmission line theory model. Furthermore, two potential application scenarios are d...

  19. Gravity Model for Topological Features on a Cylindrical Manifold

    Directory of Open Access Journals (Sweden)

    Bayak I.

    2008-04-01

    Full Text Available A model aimed at understanding quantum gravity in terms of Birkhoff's approach is discussed. The geometry of this model is constructed by using a winding map of Minkowski space into a $R^3 x S^{1}$-cylinder. The basic field of this model is a field of unit vectors defined through the velocity field of a flow wrapping the cylinder. The degeneration of some parts of the flow into circles (topological features results in inhomogeneities and gives rise to a scalar field, analogous to the gravitational field. The geometry and dynamics of this field are briefly discussed. We treat the intersections between the topological features and the observer's 3-space as matter particles and argue that these entities are likely to possess some quantum properties.

  20. Gravity Model for Topological Features on a Cylindrical Manifold

    Directory of Open Access Journals (Sweden)

    Bayak I.

    2008-04-01

    Full Text Available A model aimed at understanding quantum gravity in terms of Birkho’s approach is discussed. The geometry of this model is constructed by using a winding map of Minkowski space into a R3 S1 -cylinder. The basic field of this model is a field of unit vectors defined through the velocity field of a flow wrapping the cylinder. The degeneration of some parts of the flow into circles (topological features results in in- homogeneities and gives rise to a scalar field, analogous to the gravitational field. The geometry and dynamics of this field are briefly discussed. We treat the intersections be- tween the topological features and the observer’s 3-space as matter particles and argue that these entities are likely to possess some quantum properties.

  1. Landmine detection using discrete hidden Markov models with Gabor features

    Science.gov (United States)

    Frigui, Hichem; Missaoui, Oualid; Gader, Paul

    2007-04-01

    We propose a general method for detecting landmine signatures in vehicle mounted ground penetrating radar (GPR) using discrete hidden Markov models and Gabor wavelet features. Observation vectors are constructed based on the expansion of the signature's B-scan using a bank of scale and orientation selective Gabor filters. This expansion provides localized frequency description that gets encoded in the observation sequence. These observations do not impose an explicit structure on the mine model, and are used to naturally model the time-varying signatures produced by the interaction of the GPR and the landmines as the vehicle moves. The proposed method is evaluated on real data collected by a GPR mounted on a moving vehicle at three different geographical locations that include several lanes. The model parameters are optimized using the BaumWelch algorithm, and lane-based cross-validation, in which each mine lane is in turn treated as a test set with the rest of the lanes used for training, is used to train and test the model. Preliminary results show that observations encoded with Gabor wavelet features perform better than observation encoded with gradient-based edge features.

  2. Auditory-model based robust feature selection for speech recognition.

    Science.gov (United States)

    Koniaris, Christos; Kuropatwinski, Marcin; Kleijn, W Bastiaan

    2010-02-01

    It is shown that robust dimension-reduction of a feature set for speech recognition can be based on a model of the human auditory system. Whereas conventional methods optimize classification performance, the proposed method exploits knowledge implicit in the auditory periphery, inheriting its robustness. Features are selected to maximize the similarity of the Euclidean geometry of the feature domain and the perceptual domain. Recognition experiments using mel-frequency cepstral coefficients (MFCCs) confirm the effectiveness of the approach, which does not require labeled training data. For noisy data the method outperforms commonly used discriminant-analysis based dimension-reduction methods that rely on labeling. The results indicate that selecting MFCCs in their natural order results in subsets with good performance.

  3. Formal Modeling and Verification of Interlocking Systems Featuring Sequential Release

    DEFF Research Database (Denmark)

    Vu, Linh Hong; Haxthausen, Anne Elisabeth; Peleska, Jan

    2015-01-01

    In this paper, we present a method and an associated tool suite for formal verification of the new ETCS level 2 based Danish railway interlocking systems. We have made a generic and reconfigurable model of the system behavior and generic high-level safety properties. This model accommodates...... sequential release – a feature in the new Danish interlocking systems. The generic model and safety properties can be instantiated with interlocking configuration data, resulting in a concrete model in the form of a Kripke structure, and in high-level safety properties expressed as state invariants. Using...... SMT based bounded model checking (BMC) and inductive reasoning, we are able to verify the properties for model instances corresponding to railway networks of industrial size. Experiments also show that BMC is efficient for finding bugs in the railway interlocking designs....

  4. Formal Modeling and Verification of Interlocking Systems Featuring Sequential Release

    DEFF Research Database (Denmark)

    Vu, Linh Hong; Haxthausen, Anne Elisabeth; Peleska, Jan

    2014-01-01

    In this paper, we present a method and an associated tool suite for formal verification of the new ETCS level 2 based Danish railway interlocking systems. We have made a generic and reconfigurable model of the system behavior and generic high-level safety properties. This model accommodates...... sequential release - a feature in the new Danish interlocking systems. The generic model and safety properties can be instantiated with interlocking configuration data, resulting in a concrete model in the form of a Kripke structure, and in high-level safety properties expressed as state invariants. Using...... SMT based bounded model checking (BMC) and inductive reasoning, we are able to verify the properties for model instances corresponding to railway networks of industrial size. Experiments also show that BMC is efficient for finding bugs in the railway interlocking designs....

  5. Exploring key factors in online shopping with a hybrid model.

    Science.gov (United States)

    Chen, Hsiao-Ming; Wu, Chia-Huei; Tsai, Sang-Bing; Yu, Jian; Wang, Jiangtao; Zheng, Yuxiang

    2016-01-01

    Nowadays, the web increasingly influences retail sales. An in-depth analysis of consumer decision-making in the context of e-business has become an important issue for internet vendors. However, factors affecting e-business are complicated and intertwined. To stimulate online sales, understanding key influential factors and causal relationships among the factors is important. To gain more insights into this issue, this paper introduces a hybrid method, which combines the Decision Making Trial and Evaluation Laboratory (DEMATEL) with the analytic network process, called DANP method, to find out the driving factors that influence the online business mostly. By DEMATEL approach the causal graph showed that "online service" dimension has the highest degree of direct impact on other dimensions; thus, the internet vendor is suggested to made strong efforts on service quality throughout the online shopping process. In addition, the study adopted DANP to measure the importance of key factors, among which "transaction security" proves to be the most important criterion. Hence, transaction security should be treated with top priority to boost the online businesses. From our study with DANP approach, the comprehensive information can be visually detected so that the decision makers can spotlight on the root causes to develop effectual actions.

  6. The SWISS-MODEL Repository—new features and functionality

    Science.gov (United States)

    Bienert, Stefan; Waterhouse, Andrew; de Beer, Tjaart A. P.; Tauriello, Gerardo; Studer, Gabriel; Bordoli, Lorenza; Schwede, Torsten

    2017-01-01

    SWISS-MODEL Repository (SMR) is a database of annotated 3D protein structure models generated by the automated SWISS-MODEL homology modeling pipeline. It currently holds >400 000 high quality models covering almost 20% of Swiss-Prot/UniProtKB entries. In this manuscript, we provide an update of features and functionalities which have been implemented recently. We address improvements in target coverage, model quality estimates, functional annotations and improved in-page visualization. We also introduce a new update concept which includes regular updates of an expanded set of core organism models and UniProtKB-based targets, complemented by user-driven on-demand update of individual models. With the new release of the modeling pipeline, SMR has implemented a REST-API and adopted an open licencing model for accessing model coordinates, thus enabling bulk download for groups of targets fostering re-use of models in other contexts. SMR can be accessed at https://swissmodel.expasy.org/repository. PMID:27899672

  7. Our energy-Ca2+ signaling deficits hypothesis and its explanatory potential for key features of Alzheimer’s disease

    Directory of Open Access Journals (Sweden)

    Ming eChen

    2014-12-01

    Full Text Available Alzheimer’s disease (AD has not been explained by any current theories, so new hypotheses are urgently needed. We proposed that energy and Ca2+ signaling deficits are perhaps the earliest modifiable defects in brain aging underlying memory decline and tau deposits (by means of inactivating Ca2+-dependent protease calpain. Consistent with this hypothesis, we now notice that at least eight other known calpain substrates have also been reported to accumulate in aging and AD. Thus, protein accumulation or aggregation is not an accidental or random event, but occurs naturally and selectively to a peculiar family of proteins, corroborating the proposed changes of calpain. Why are only calpain substrates accumulated and how can they stay for decades in the brain without being attacked by many other non-specific proteases there? We believe that these long-lasting puzzles can be explained by calpain’s unique properties, especially its unusual specificity and exclusivity in substrate recognition, which can protect the substrates from other proteases’ attacks after calpain inactivation. Interestingly, the energy-Ca2+ deficits model, in essence, may also explain tau phosphorylation (by calcineurin inactivation and the formation of amyloid plaques. Our studies suggest that α-secretase is an energy-/Ca2+-dual dependent protease and is also the primary determinant for Aβ levels. Finally we discuss why β- and γ-secretases, the current enthusiastic study focuses, are unlikely to be responsible for Aβ genesis or be positively identified by biological laws. Overall, the study suggests that our hypothesis can coherently explain several basic AD features, thus pointing to a new strategy for AD prevention.

  8. Evidence on Features of a DSGE Business Cycle Model from Bayesian Model Averaging

    NARCIS (Netherlands)

    R.W. Strachan (Rodney); H.K. van Dijk (Herman)

    2012-01-01

    textabstractThe empirical support for features of a Dynamic Stochastic General Equilibrium model with two technology shocks is valuated using Bayesian model averaging over vector autoregressions. The model features include equilibria, restrictions on long-run responses, a structural break of unknown

  9. Key Elements of the Tutorial Support Management Model

    Science.gov (United States)

    Lynch, Grace; Paasuke, Philip

    2011-01-01

    In response to an exponential growth in enrolments the "Tutorial Support Management" (TSM) model has been adopted by Open Universities Australia (OUA) after a two-year project on the provision of online tutor support in first year, online undergraduate units. The essential focus of the TSM model was the development of a systemic approach…

  10. Hidden Markov models for prediction of protein features

    DEFF Research Database (Denmark)

    Bystroff, Christopher; Krogh, Anders

    2008-01-01

    Hidden Markov Models (HMMs) are an extremely versatile statistical representation that can be used to model any set of one-dimensional discrete symbol data. HMMs can model protein sequences in many ways, depending on what features of the protein are represented by the Markov states. For protein...... structure prediction, states have been chosen to represent either homologous sequence positions, local or secondary structure types, or transmembrane locality. The resulting models can be used to predict common ancestry, secondary or local structure, or membrane topology by applying one of the two standard...... algorithms for comparing a sequence to a model. In this chapter, we review those algorithms and discuss how HMMs have been constructed and refined for the purpose of protein structure prediction....

  11. Feature Analysis and Modeling of the Network Community Structure

    Institute of Scientific and Technical Information of China (English)

    袁超; 柴毅; 魏善碧

    2012-01-01

    Community structure has an important influence on the structural and dynamic characteristics of the complex systems.So it has attracted a large number of researchers.However,due to its complexity,the mechanism of action of the community structure is still not clear to this day.In this paper,some features of the community structure have been discussed.And a constraint model of the community has been deduced.This model is effective to identify the communities.And especially,it is effective to identify the overlapping nodes between the communities.Then a community detection algorithm,which has linear time complexity,is proposed based on this constraint model,a proposed node similarity model and the Modularity Q.Through some experiments on a series of real-world and synthetic networks,the high performances of the algorithm and the constraint model have been illustrated.

  12. Combining Spatial and Telemetric Features for Learning Animal Movement Models

    CERN Document Server

    Kapicioglu, Berk; Wikelski, Martin; Broderick, Tamara

    2012-01-01

    We introduce a new graphical model for tracking radio-tagged animals and learning their movement patterns. The model provides a principled way to combine radio telemetry data with an arbitrary set of userdefined, spatial features. We describe an efficient stochastic gradient algorithm for fitting model parameters to data and demonstrate its effectiveness via asymptotic analysis and synthetic experiments. We also apply our model to real datasets, and show that it outperforms the most popular radio telemetry software package used in ecology. We conclude that integration of different data sources under a single statistical framework, coupled with appropriate parameter and state estimation procedures, produces both accurate location estimates and an interpretable statistical model of animal movement.

  13. Multiple linear regression model for predicting biomass digestibility from structural features.

    Science.gov (United States)

    Zhu, Li; O'Dwyer, Jonathan P; Chang, Vincent S; Granda, Cesar B; Holtzapple, Mark T

    2010-07-01

    A total of 147 model lignocellulose samples with a broad spectrum of structural features (lignin contents, acetyl contents, and crystallinity indices) were hydrolyzed with a wide range of cellulase loadings during 1-, 6-, and 72-h hydrolysis periods. Carbohydrate conversions at 1, 6, and 72 h were linearly proportional to the logarithm of cellulase loadings from approximately 10% to 90% conversion, indicating that the simplified HCH-1 model is valid for predicting lignocellulose digestibility. The HCH-1 model is a modified Michaelis-Menton model that accounts for the fraction of insoluble substrate available to bind with enzyme. The slopes and intercepts of a simplified HCH-1 model were correlated with structural features using multiple linear regression (MLR) models. The agreement between the measured and predicted 1-, 6-, and 72-h slopes and intercepts of glucan, xylan, and total sugar hydrolyses indicate that lignin content, acetyl content, and cellulose crystallinity are key factors that determine biomass digestibility. The 1-, 6-, and 72-h glucan, xylan, and total sugar conversions predicted from structural features using MLR models and the simplified HCH-1 model fit satisfactorily with the measured data (R(2) approximately 1.0). The parameter selection suggests that lignin content and cellulose crystallinity more strongly affect on digestibility than acetyl content. Cellulose crystallinity has greater influence during short hydrolysis periods whereas lignin content has more influence during longer hydrolysis periods. Cellulose crystallinity shows more influence on glucan hydrolysis whereas lignin content affects xylan hydrolysis to a greater extent.

  14. Crossing the dividing surface of transition state theory. IV. Dynamical regularity and dimensionality reduction as key features of reactive trajectories

    Science.gov (United States)

    Lorquet, J. C.

    2017-04-01

    The atom-diatom interaction is studied by classical mechanics using Jacobi coordinates (R, r, θ). Reactivity criteria that go beyond the simple requirement of transition state theory (i.e., PR* > 0) are derived in terms of specific initial conditions. Trajectories that exactly fulfill these conditions cross the conventional dividing surface used in transition state theory (i.e., the plane in configuration space passing through a saddle point of the potential energy surface and perpendicular to the reaction coordinate) only once. Furthermore, they are observed to be strikingly similar and to form a tightly packed bundle of perfectly collimated trajectories in the two-dimensional (R, r) configuration space, although their angular motion is highly specific for each one. Particular attention is paid to symmetrical transition states (i.e., either collinear or T-shaped with C2v symmetry) for which decoupling between angular and radial coordinates is observed, as a result of selection rules that reduce to zero Coriolis couplings between modes that belong to different irreducible representations. Liapunov exponents are equal to zero and Hamilton's characteristic function is planar in that part of configuration space that is visited by reactive trajectories. Detailed consideration is given to the concept of average reactive trajectory, which starts right from the saddle point and which is shown to be free of curvature-induced Coriolis coupling. The reaction path Hamiltonian model, together with a symmetry-based separation of the angular degree of freedom, provides an appropriate framework that leads to the formulation of an effective two-dimensional Hamiltonian. The success of the adiabatic approximation in this model is due to the symmetry of the transition state, not to a separation of time scales. Adjacent trajectories, i.e., those that do not exactly fulfill the reactivity conditions have similar characteristics, but the quality of the approximation is lower. At higher

  15. Key Challenges and Potential Urban Modelling Opportunities in ...

    African Journals Online (AJOL)

    Chris Wray

    monitoring and guiding urban spatial planning and development. ... and social system functions, urban modelling has evolved from simple ... careful long-term planning aligned with the national vision and other strategic perspectives' (GPC,.

  16. Machine learning methods enable predictive modeling of antibody feature:function relationships in RV144 vaccinees.

    Directory of Open Access Journals (Sweden)

    Ickwon Choi

    2015-04-01

    Full Text Available The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release. We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates.

  17. THE IDENTITY FEATURES OF THE INTERVENTION MODEL OF EDUCATIONAL INSPECTION IN ANDALUSIA

    Directory of Open Access Journals (Sweden)

    Pedro Ángel Luna Ariza

    2014-06-01

    Full Text Available It is hard to imagine Inspectorate of Education in Andalusia without an intervention model approved and stable oriented to improve students achievement. Dedication to the IFC (Key Factors Intervention and its supervision in schools and classrooms of Andalusia is a differentiating factor . It is an intervention model that goes beyond the simple verification of standars compliance, where the visit and report are the main tools of the inspector. The main features of its identity are the number of methodological elements, as contrasted data analysis, which provides a systemic view of the school organization and other functional aspects , such as open level, open reference and teamwork.

  18. Culture Models to Define Key Mediators of Cancer Matrix Remodeling

    Directory of Open Access Journals (Sweden)

    Emily Suzanne Fuller

    2014-03-01

    Full Text Available High grade serous epithelial ovarian cancer (HG-SOC is one of the most devastating gynecological cancers affecting women worldwide, with a poor survival rate despite clinical treatment advances. HG-SOC commonly metastasizes within the peritoneal cavity, primarily to the mesothelial cells of the omentum which regulate an extracellular matrix (ECM rich in collagens type I, III and IV along with laminin, vitronectin and fibronectin. Cancer cells depend on their ability to penetrate and invade secondary tissue sites to spread, however a detailed understanding of the molecular mechanisms underlying these processes remain largely unknown. Given the high metastatic potential of HG-SOC and the associated poor clinical outcome, it is extremely important to identify the pathways and the components of which that are responsible for the progression of this disease. In-vitro methods of recapitulating human disease processes are the critical first step in such investigations. In this context, establishment of an in-vitro ‘tumor-like’ microenvironment, such as 3D culture, to study early disease and metastasis of human HG-SOC is an important and highly insightful method. In recent years many such methods have been established to investigate the adhesion and invasion of human ovarian cancer cell lines. The aim of this review is to summarize recent developments in ovarian cancer culture systems and their use to investigate clinically relevant findings concerning the key players in driving human HG-SOC.

  19. Efficient and Robust Feature Model for Visual Tracking

    Institute of Scientific and Technical Information of China (English)

    WANG Lu; ZHUO Qing; WANG Wenyuan

    2009-01-01

    Long duration visual tracking of targets is quite challenging for computer vision, because the envi-ronments may be cluttered and distracting. Illumination variations and partial occlusions are two main diffi-culties in real world visual tracking. Existing methods based on hostile appearance information cannot solve these problems effectively. This paper proposes a feature-based dynamic tracking approach that can track objects with partial occlusions and varying illumination. The method represents the tracked object by an in-variant feature model. During the tracking, a new pyramid matching algorithm was used to match the object template with the observations to determine the observation likelihood. This matching is quite efficient in calculation and the spatial constraints among these features are also embedded. Instead of complicated op-timization methods, the whole model is incorporated into a Bayesian filtering framework. The experiments on real world sequences demonstrate that the method can track objects accurately and robustly even with illu-mination variations and partial occlusions.

  20. Full-field feature profile models in process control

    Science.gov (United States)

    Zavecz, Terrence E.

    2005-05-01

    Most process window analysis applications are capable of deriving the functional focus-dose workspace available to any set of device specifications. Previous work in this area has concentrated on calculating the superpositioned optimum operating points of various combinations of feature orientations or feature types. These studies invariably result in an average performance calculation that is biased by the impact of the substrate, reticle and exposure tool contributed perturbations. Many SEM's and optical metrology tools now provide full-feature profile information for multiple points in the exposure field. The inclusion of field spatial information into the process window analysis results in a calculation of greater accuracy and process understanding because now the capabilities of each exposure tool can be individually modeled and optimized. Such an analysis provides the added benefit that after the exposure tool is characterized, it's process perturbations can be removed from the analysis to provide greater understanding of the true process performance. Process window variables are shown to vary significantly across the exposure field of the scanner. Evaluating the depth-of-focus and optimum focus-dose at each point in the exposure field yields additional information on the imaging response of the reticle and scan-linearity of the exposure tool's reticle stage. The optimal focus response of the reticle is then removed from a full wafer exposure and the results are modeled to obtain a true process response and performance.

  1. Accessing key steps of human tumor progression in vivo by using an avian embryo model

    Science.gov (United States)

    Hagedorn, Martin; Javerzat, Sophie; Gilges, Delphine; Meyre, Aurélie; de Lafarge, Benjamin; Eichmann, Anne; Bikfalvi, Andreas

    2005-02-01

    Experimental in vivo tumor models are essential for comprehending the dynamic process of human cancer progression, identifying therapeutic targets, and evaluating antitumor drugs. However, current rodent models are limited by high costs, long experimental duration, variability, restricted accessibility to the tumor, and major ethical concerns. To avoid these shortcomings, we investigated whether tumor growth on the chick chorio-allantoic membrane after human glioblastoma cell grafting would replicate characteristics of the human disease. Avascular tumors consistently formed within 2 days, then progressed through vascular endothelial growth factor receptor 2-dependent angiogenesis, associated with hemorrhage, necrosis, and peritumoral edema. Blocking of vascular endothelial growth factor receptor 2 and platelet-derived growth factor receptor signaling pathways by using small-molecule receptor tyrosine kinase inhibitors abrogated tumor development. Gene regulation during the angiogenic switch was analyzed by oligonucleotide microarrays. Defined sample selection for gene profiling permitted identification of regulated genes whose functions are associated mainly with tumor vascularization and growth. Furthermore, expression of known tumor progression genes identified in the screen (IL-6 and cysteine-rich angiogenic inducer 61) as well as potential regulators (lumican and F-box-only 6) follow similar patterns in patient glioma. The model reliably simulates key features of human glioma growth in a few days and thus could considerably increase the speed and efficacy of research on human tumor progression and preclinical drug screening. angiogenesis | animal model alternatives | glioblastoma

  2. Spermatozoa scattering by a microchannel feature: an elastohydrodynamic model

    CERN Document Server

    Montenegro-Johnson, Thomas; Smith, David J

    2014-01-01

    Sperm traverse their microenvironment through viscous fluid by propagating flagellar waves; the waveform emerges as a consequence of elastic structure, internal active moments, and low Reynolds number fluid dynamics. Engineered microchannels have recently been proposed as a method of sorting and manipulating motile cells; the interaction of cells with these artificial environments therefore warrants investigation. A numerical method is presented for the geometrically nonlinear elastohydrodynamic interaction of active swimmers with domain features. This method is employed to examine hydrodynamic scattering by a model microchannel backstep feature. Scattering is shown to depend on backstep height and the relative strength of viscous and elastic forces in the flagellum. In a 'high viscosity' parameter regime corresponding to human sperm in cervical mucus analogue, this hydrodynamic contribution to scattering is comparable in magnitude to recent data on contact effects, being of the order of 5-10 degrees. Scatter...

  3. Music genre classification via likelihood fusion from multiple feature models

    Science.gov (United States)

    Shiu, Yu; Kuo, C.-C. J.

    2005-01-01

    Music genre provides an efficient way to index songs in a music database, and can be used as an effective means to retrieval music of a similar type, i.e. content-based music retrieval. A new two-stage scheme for music genre classification is proposed in this work. At the first stage, we examine a couple of different features, construct their corresponding parametric models (e.g. GMM and HMM) and compute their likelihood functions to yield soft classification results. In particular, the timbre, rhythm and temporal variation features are considered. Then, at the second stage, these soft classification results are integrated to result in a hard decision for final music genre classification. Experimental results are given to demonstrate the performance of the proposed scheme.

  4. Modeling photoacoustic spectral features of micron-sized particles.

    Science.gov (United States)

    Strohm, Eric M; Gorelikov, Ivan; Matsuura, Naomi; Kolios, Michael C

    2014-10-07

    The photoacoustic signal generated from particles when irradiated by light is determined by attributes of the particle such as the size, speed of sound, morphology and the optical absorption coefficient. Unique features such as periodically varying minima and maxima are observed throughout the photoacoustic signal power spectrum, where the periodicity depends on these physical attributes. The frequency content of the photoacoustic signals can be used to obtain the physical attributes of unknown particles by comparison to analytical solutions of homogeneous symmetric geometric structures, such as spheres. However, analytical solutions do not exist for irregularly shaped particles, inhomogeneous particles or particles near structures. A finite element model (FEM) was used to simulate photoacoustic wave propagation from four different particle configurations: a homogeneous particle suspended in water, a homogeneous particle on a reflecting boundary, an inhomogeneous particle with an absorbing shell and non-absorbing core, and an irregularly shaped particle such as a red blood cell. Biocompatible perfluorocarbon droplets, 3-5 μm in diameter containing optically absorbing nanoparticles were used as the representative ideal particles, as they are spherical, homogeneous, optically translucent, and have known physical properties. The photoacoustic spectrum of micron-sized single droplets in suspension and on a reflecting boundary were measured over the frequency range of 100-500 MHz and compared directly to analytical models and the FEM. Good agreement between the analytical model, FEM and measured values were observed for a droplet in suspension, where the spectral minima agreed to within a 3.3 MHz standard deviation. For a droplet on a reflecting boundary, spectral features were correctly reproduced using the FEM but not the analytical model. The photoacoustic spectra from other common particle configurations such as particle with an absorbing shell and a

  5. Modeling photoacoustic spectral features of micron-sized particles

    Science.gov (United States)

    Strohm, Eric M.; Gorelikov, Ivan; Matsuura, Naomi; Kolios, Michael C.

    2014-10-01

    The photoacoustic signal generated from particles when irradiated by light is determined by attributes of the particle such as the size, speed of sound, morphology and the optical absorption coefficient. Unique features such as periodically varying minima and maxima are observed throughout the photoacoustic signal power spectrum, where the periodicity depends on these physical attributes. The frequency content of the photoacoustic signals can be used to obtain the physical attributes of unknown particles by comparison to analytical solutions of homogeneous symmetric geometric structures, such as spheres. However, analytical solutions do not exist for irregularly shaped particles, inhomogeneous particles or particles near structures. A finite element model (FEM) was used to simulate photoacoustic wave propagation from four different particle configurations: a homogeneous particle suspended in water, a homogeneous particle on a reflecting boundary, an inhomogeneous particle with an absorbing shell and non-absorbing core, and an irregularly shaped particle such as a red blood cell. Biocompatible perfluorocarbon droplets, 3-5 μm in diameter containing optically absorbing nanoparticles were used as the representative ideal particles, as they are spherical, homogeneous, optically translucent, and have known physical properties. The photoacoustic spectrum of micron-sized single droplets in suspension and on a reflecting boundary were measured over the frequency range of 100-500 MHz and compared directly to analytical models and the FEM. Good agreement between the analytical model, FEM and measured values were observed for a droplet in suspension, where the spectral minima agreed to within a 3.3 MHz standard deviation. For a droplet on a reflecting boundary, spectral features were correctly reproduced using the FEM but not the analytical model. The photoacoustic spectra from other common particle configurations such as particle with an absorbing shell and a

  6. The shell model approach: Key to hadron structure

    Energy Technology Data Exchange (ETDEWEB)

    Lipkin, H.J. (Weizmann Inst. of Science, Rehovoth (Israel). Dept. of Nuclear Physics)

    1989-08-14

    A shell model approach leads to a simple constituent quark model for hadron structure in which mesons and baryons consist only of constituent quarks. Hadron masses are the sums of the constituent quark effective masses and a hyperfine interaction inversely proportional to the product of these same masses. Hadron masses and magnetic moments are related by the assumption that the same effective mass parameter appears in the additive mass term, the hyperfine interaction, and the quark magnetic moment, both in mesons and baryons. The analysis pinpoints the physical assumptions needed for each relation and gives two new mass relations. Application to weak decays and recent polarized EMC data confirms conclusions previously obtained that the current quark contribution to the spin structure of the proton vanishes, but without need for the questionable assumption of SU(3) symmetry relating hyperon decays and proton structure. SU(3) symmetry breaking is clarified. 24 refs.

  7. Scattering as a key to improved room acoustic computer modelling

    DEFF Research Database (Denmark)

    Rindel, Jens Holger; Christensen, Claus Lynge

    1996-01-01

    It has been known for a long time that surface scattering plays a very important role in room acoustics. With room acoustic computer models like ODEON it is possible to study the influence of scattering coefficients, which can be assigned to the surfaces of the room. In the latest version...... of the program an additional effect has been modelled, namely the attenuation of sound due to diffraction, which is particularly pronounced for small surfaces, low frequencies and long reflecting paths. The present paper describes a parameter study of how to optimize the choice of the number of rays...... room acoustic parameters. Results from two different halls have shown that a relative low number of rays are sufficient for reliable and stable calculation results. The optimum value of the transition order is two or three. The inclusion of diffraction effect leads to clearly improved results....

  8. A model for revocation forecasting in public-key infrastructures

    OpenAIRE

    Hernández Gañan, Carlos; Mata Diaz, Jorge; Muñoz Tapia, José Luis; Esparza Martín, Óscar; Alins Delgado, Juan José

    2015-01-01

    One of the hardest tasks of a certification infrastructure is to manage revocation. This process consists in collecting and making the revocation status of certificates available to users. Research on this topic has focused on the trade-offs that different revocation mechanisms offer. Much less effort has been conducted to understand and model real-world revocation processes. For this reason, in this paper, we present a novel analysis of real-world collected revocation data and we propose a r...

  9. Improving permafrost distribution modelling using feature selection algorithms

    Science.gov (United States)

    Deluigi, Nicola; Lambiel, Christophe; Kanevski, Mikhail

    2016-04-01

    The availability of an increasing number of spatial data on the occurrence of mountain permafrost allows the employment of machine learning (ML) classification algorithms for modelling the distribution of the phenomenon. One of the major problems when dealing with high-dimensional dataset is the number of input features (variables) involved. Application of ML classification algorithms to this large number of variables leads to the risk of overfitting, with the consequence of a poor generalization/prediction. For this reason, applying feature selection (FS) techniques helps simplifying the amount of factors required and improves the knowledge on adopted features and their relation with the studied phenomenon. Moreover, taking away irrelevant or redundant variables from the dataset effectively improves the quality of the ML prediction. This research deals with a comparative analysis of permafrost distribution models supported by FS variable importance assessment. The input dataset (dimension = 20-25, 10 m spatial resolution) was constructed using landcover maps, climate data and DEM derived variables (altitude, aspect, slope, terrain curvature, solar radiation, etc.). It was completed with permafrost evidences (geophysical and thermal data and rock glacier inventories) that serve as training permafrost data. Used FS algorithms informed about variables that appeared less statistically important for permafrost presence/absence. Three different algorithms were compared: Information Gain (IG), Correlation-based Feature Selection (CFS) and Random Forest (RF). IG is a filter technique that evaluates the worth of a predictor by measuring the information gain with respect to the permafrost presence/absence. Conversely, CFS is a wrapper technique that evaluates the worth of a subset of predictors by considering the individual predictive ability of each variable along with the degree of redundancy between them. Finally, RF is a ML algorithm that performs FS as part of its

  10. Monitor key parameters of winter wheat using Crop model

    Science.gov (United States)

    Jibo, Yue; Haikuan, Feng; Xiudong, Qi

    2016-11-01

    Estimation of biomass, canopy cover and yield is very important to agricultural decision Precision Farming. During the winter wheat growing season of 2013/2014, field measurements were conducted at Yangling District, Shaanxi Province at the jointing stage, heading stage and filling stage. AquaCrop model and Particle swarm optimization algorithm was used to find the global optimal simulation when the intermediate variable was the biomass. Through the simulation for each of the experimental data, biomass, canopy coverage and soil moisture were verification by ground measurements. Based on 8 sets of data, the simulation accuracy was calculated. The RMSE, nRMSE, MAE and R2 between simulation and measured biomass were 1.06 ton/ha, 11.92%, 0.90 ton/ha and 0.92. The RMSE, nRMSE, MAE and R2 between simulation and measured canopy cover were 8.92%, 9.84%, 7.84% and 0.66, respectively. The simulation results show that the AquaCrop model can help the decision making of winter wheat field in arid areas.

  11. Global Deep Convection Models of Saturn's Atmospheric Features

    Science.gov (United States)

    Heimpel, Moritz; Cuff, Keith; Gastine, Thomas; Wicht, Johannes

    2016-04-01

    The Cassini mission, along with previous missions and ground-based observations, has revealed a rich variety of atmospheric phenomena and time variability on Saturn. Some examples of dynamical features are: zonal flows with multiple jet streams, turbulent tilted shear flows that seem to power the jets, the north polar hexagon, the south polar cyclone, large anticyclones in "storm alley", numerous convective storms (white spots) of various sizes, and the 2010/2011 great storm, which destroyed an array of vortices dubbed the "string of pearls". Here we use the anelastic dynamo code MagIC, in non-magnetic mode, to study rotating convection in a spherical shell. The thickness of the shell is set to approximate the depth of the low electrical conductivity deep atmosphere of Saturn, and the convective forcing is set to yield zonal flows of similar velocity (Rossby number) to those of Saturn. Internal heating and the outer entropy boundary conditions allow simple modelling of atmospheric layers with neutral stability or stable stratification. In these simulations we can identify several saturnian and jovian atmospheric features, with some variations. We find that large anticyclonic vortices tend to form in the first anticyclonic shear zones away from the equatorial jet. Cyclones form at the poles, and polar polygonal jet streams, comparable to Saturn's hexagon, may or may not form, depending on the model conditions. Strings of small scale vortical structures arise as convective plumes near boundaries of shear zones. They typically precede larger scale convective storms that spawn propagating shear flow disturbances and anticyclonic vortices, which tend to drift across anticyclonic shear zones, toward the equator (opposite the drift direction of Saturn's 2010/2011 storm). Our model results indicate that many identifiable dynamical atmospheric features seen on Jupiter and Saturn arise from deep convection, shaped by planetary rotation, underlying and interacting with stably

  12. Feature and Statistical Model Development in Structural Health Monitoring

    Science.gov (United States)

    Kim, Inho

    All structures suffer wear and tear because of impact, excessive load, fatigue, corrosion, etc. in addition to inherent defects during their manufacturing processes and their exposure to various environmental effects. These structural degradations are often imperceptible, but they can severely affect the structural performance of a component, thereby severely decreasing its service life. Although previous studies of Structural Health Monitoring (SHM) have revealed extensive prior knowledge on the parts of SHM processes, such as the operational evaluation, data processing, and feature extraction, few studies have been conducted from a systematical perspective, the statistical model development. The first part of this dissertation, the characteristics of inverse scattering problems, such as ill-posedness and nonlinearity, reviews ultrasonic guided wave-based structural health monitoring problems. The distinctive features and the selection of the domain analysis are investigated by analytically searching the conditions of the uniqueness solutions for ill-posedness and are validated experimentally. Based on the distinctive features, a novel wave packet tracing (WPT) method for damage localization and size quantification is presented. This method involves creating time-space representations of the guided Lamb waves (GLWs), collected at a series of locations, with a spatially dense distribution along paths at pre-selected angles with respect to the direction, normal to the direction of wave propagation. The fringe patterns due to wave dispersion, which depends on the phase velocity, are selected as the primary features that carry information, regarding the wave propagation and scattering. The following part of this dissertation presents a novel damage-localization framework, using a fully automated process. In order to construct the statistical model for autonomous damage localization deep-learning techniques, such as restricted Boltzmann machine and deep belief network

  13. Rock thermal conductivity as key parameter for geothermal numerical models

    Science.gov (United States)

    Di Sipio, Eloisa; Chiesa, Sergio; Destro, Elisa; Galgaro, Antonio; Giaretta, Aurelio; Gola, Gianluca; Manzella, Adele

    2013-04-01

    The geothermal energy applications are undergoing a rapid development. However, there are still several challenges in the successful exploitation of geothermal energy resources. In particular, a special effort is required to characterize the thermal properties of the ground along with the implementation of efficient thermal energy transfer technologies. This paper focuses on understanding the quantitative contribution that geosciences can receive from the characterization of rock thermal conductivity. The thermal conductivity of materials is one of the main input parameters in geothermal modeling since it directly controls the steady state temperature field. An evaluation of this thermal property is required in several fields, such as Thermo-Hydro-Mechanical multiphysics analysis of frozen soils, designing ground source heat pumps plant, modeling the deep geothermal reservoirs structure, assessing the geothermal potential of subsoil. Aim of this study is to provide original rock thermal conductivity values useful for the evaluation of both low and high enthalpy resources at regional or local scale. To overcome the existing lack of thermal conductivity data of sedimentary, igneous and metamorphic rocks, a series of laboratory measurements has been performed on several samples, collected in outcrop, representative of the main lithologies of the regions included in the VIGOR Project (southern Italy). Thermal properties tests were carried out both in dry and wet conditions, using a C-Therm TCi device, operating following the Modified Transient Plane Source method.Measurements were made at standard laboratory conditions on samples both water saturated and dehydrated with a fan-forced drying oven at 70 ° C for 24 hr, for preserving the mineral assemblage and preventing the change of effective porosity. Subsequently, the samples have been stored in an air-conditioned room while bulk density, solid volume and porosity were detected. The measured thermal conductivity

  14. Feature and Meta-Models in Clafer: Mixed, Specialized, and Coupled

    DEFF Research Database (Denmark)

    Bąk, Kacper; Czarnecki, Krzysztof; Wasowski, Andrzej

    2011-01-01

    We present Clafer, a meta-modeling language with first-class support for feature modeling. We designed Clafer as a concise notation for meta-models, feature models, mixtures of meta- and feature models (such as components with options), and models that couple feature models and meta-models via co...... models concisely and show that Clafer meets its design objectives using a sample product line. We evaluated Clafer and how it lends itself to analysis on sample feature models, meta-models, and model templates of an E-Commerce platform....

  15. Simulation and Projection of Blocking Highs in Key Regions of the Eurasia by CMIP5 Models

    Science.gov (United States)

    Li, Y.

    2016-12-01

    Previous studies generally hold viewpoint that CMIP5 models underestimate blocking frequency and predict decreasing trend of blockings in 21st century in North Hemisphere (NH). However, regional blocking has its own features, which is different from blockings in NH as a whole. Focusing on three key regions in Eurasia-Ural, Baikal, and Okhotsk where blockings significantly influence weather and climate of East Asia, historical simulations were analyzed to evaluate the performance of the CMIP5 models, and possible changes in the first half 21st century were then predicted using the RCP 4.5 and RCP 8.5 pathways. Comparison with NCEP/NCAR reanalysis (NNR) data revealed that instantaneous blocking frequencies are underestimated in the Ural and Baikal in the whole year and in Okhotsk in summer, but are overestimated in Okhotsk in winter. Overall, the CMIP5 models could largely reproduce character of instantaneous blocking frequency in the Eurasia, with a better performance in winter than in summer. Blocking episodes frequency in the Ural and Baikal is underestimated by most the 13 CMIP5 models, especially the short duration blocking episodes, and simulated superiorly in winter to in summer. However, modeled blocking episodes frequency is near to observed value in summer but overestimated in winter in Okhotsk. Model projections of instantaneous blocking frequency for the first half 21st century (2016-2065) shows that the RCP 4.5 projection yields a significant increasing frequency during January-May, decreasing frequency during June-August, and a little increasing frequency during September- December. The RCP 8.5 projection presents similar case to RCP 4.5 projection, but indicating more remarkable decreasing trend. Blocking episodes frequency of the multi-model ensemble mean obviously decreases in the Ural and Baikal (especially blocking episodes with short duration) and increase a little in Okhotsk in the first half 21st century. For blocking episodes with long duration

  16. Feature selection and survival modeling in The Cancer Genome Atlas

    Directory of Open Access Journals (Sweden)

    Kim H

    2013-09-01

    Full Text Available Hyunsoo Kim,1 Markus Bredel2 1Department of Pathology, The University of Alabama at Birmingham, Birmingham, AL, USA; 2Department of Radiation Oncology, and Comprehensive Cancer Center, The University of Alabama at Birmingham, Birmingham, AL, USA Purpose: Personalized medicine is predicated on the concept of identifying subgroups of a common disease for better treatment. Identifying biomarkers that predict disease subtypes has been a major focus of biomedical science. In the era of genome-wide profiling, there is controversy as to the optimal number of genes as an input of a feature selection algorithm for survival modeling. Patients and methods: The expression profiles and outcomes of 544 patients were retrieved from The Cancer Genome Atlas. We compared four different survival prediction methods: (1 1-nearest neighbor (1-NN survival prediction method; (2 random patient selection method and a Cox-based regression method with nested cross-validation; (3 least absolute shrinkage and selection operator (LASSO optimization using whole-genome gene expression profiles; or (4 gene expression profiles of cancer pathway genes. Results: The 1-NN method performed better than the random patient selection method in terms of survival predictions, although it does not include a feature selection step. The Cox-based regression method with LASSO optimization using whole-genome gene expression data demonstrated higher survival prediction power than the 1-NN method, but was outperformed by the same method when using gene expression profiles of cancer pathway genes alone. Conclusion: The 1-NN survival prediction method may require more patients for better performance, even when omitting censored data. Using preexisting biological knowledge for survival prediction is reasonable as a means to understand the biological system of a cancer, unless the analysis goal is to identify completely unknown genes relevant to cancer biology. Keywords: brain, feature selection

  17. Key Elements of the User-Friendly, GFDL SKYHI General Circulation Model

    Directory of Open Access Journals (Sweden)

    Richard S. Hemler

    2000-01-01

    Full Text Available Over the past seven years, the portability of the GFDL SKYHI general circulation model has greatly increased. Modifications to the source code have allowed SKYHI to be run on the GFDL Cray Research PVP machines, the TMC CM-5 machine at Los Alamos National Laboratory, and more recently on the GFDL 40-processor Cray Research T3E system. At the same time, changes have been made to the model to make it more usable and flexible. Because of the reduction of the human resources available to manage and analyze scientific experiments, it is no longer acceptable to consider only the optimization of computer resources when producing a research code; one must also consider the availability and cost of the people necessary to maintain, modify and use the model as an investigative tool, and include these factors in defining the form of the model code. The new SKYHI model attempts to strike a balance between the optimization of the use of machine resources (CPU time, memory, disc and the optimal use of human resources (ability to understand code, ability to modify code, ability to perturb code to do experiments, ability to run code on different platforms. Two of the key features that make the new SKYHI code more usable and flexible are the archiving package and the user variable block. The archiving package is used to manage the writing of all archive files, which contain data for later analysis. The model-supplied user variable block allows the easy inclusion of any new variables needed for particular experiments.

  18. Image Watermarking Using Visual Perception Model and Statistical Features

    Directory of Open Access Journals (Sweden)

    Mrs.C.Akila

    2010-06-01

    Full Text Available This paper presents an effective method for the image watermarking using visual perception model based on statistical features in the low frequency domain. In the image watermarking community watermark resistance to geometric attacks is an important issue. Most countermeasures proposed in the literature usually focus on the problem of global affine transforms such as rotation, scaling and translation (RST, but few are resistant to challenging cropping and random bending attacks (RBAs. Normally in the case of watermarking there may be an occurrence of distortion in the form of artifacts. A visual perception model is proposed to quantify the localized tolerance to noise for arbitrary imagery which achieves the reduction of artifacts. As a result, the watermarking system provides a satisfactory performance for those content-preserving geometric deformations and image processing operations, including JPEG ompression, low pass filtering, cropping and RBAs.

  19. Performance modeling of a feature-aided tracker

    Science.gov (United States)

    Goley, G. Steven; Nolan, Adam R.

    2012-06-01

    In order to provide actionable intelligence in a layered sensing paradigm, exploitation algorithms should produce a confidence estimate in addition to the inference variable. This article presents a methodology and results of one such algorithm for feature-aided tracking of vehicles in wide area motion imagery. To perform experiments a synthetic environment was developed, which provided explicit knowledge of ground truth, tracker prediction accuracy, and control of operating conditions. This synthetic environment leveraged physics-based modeling simulations to re-create both traffic flow, reflectance of vehicles, obscuration and shadowing. With the ability to control operating conditions as well as the availability of ground truth, several experiments were conducted to test both the tracker and expected performance. The results show that the performance model produces a meaningful estimate of the tracker performance over the subset of operating conditions.

  20. Feature selection versus feature compression in the building of calibration models from FTIR-spectrophotometry datasets.

    Science.gov (United States)

    Vergara, Alexander; Llobet, Eduard

    2012-01-15

    Undoubtedly, FTIR-spectrophotometry has become a standard in chemical industry for monitoring, on-the-fly, the different concentrations of reagents and by-products. However, representing chemical samples by FTIR spectra, which spectra are characterized by hundreds if not thousands of variables, conveys their own set of particular challenges because they necessitate to be analyzed in a high-dimensional feature space, where many of these features are likely to be highly correlated and many others surely affected by noise. Therefore, identifying a subset of features that preserves the classifier/regressor performance seems imperative prior any attempt to build an appropriate pattern recognition method. In this context, we investigate the benefit of utilizing two different dimensionality reduction methods, namely the minimum Redundancy-Maximum Relevance (mRMR) feature selection scheme and a new self-organized map (SOM) based feature compression, coupled to regression methods to quantitatively analyze two-component liquid samples utilizing FTIR spectrophotometry. Since these methods give us the possibility of selecting a small subset of relevant features from FTIR spectra preserving the statistical characteristics of the target variable being analyzed, we claim that expressing the FTIR spectra by these dimensionality-reduced set of features may be beneficial. We demonstrate the utility of these novel feature selection schemes in quantifying the distinct analytes within their binary mixtures utilizing a FTIR-spectrophotometer.

  1. Structured Reporting of Magnetic Resonance Enterography for Pediatric Crohn's Disease: Effect on Key Feature Reporting and Subjective Assessment of Disease by Referring Physicians.

    Science.gov (United States)

    Wildman-Tobriner, Benjamin; Allen, Brian C; Davis, Joseph T; Miller, Chad M; Schooler, Gary R; McGreal, Nancy M; Quevedo, Reinaldo; Thacker, Julie K; Jaffe, Tracy A

    To objectively compare the content of structured reports (SR) vs nonstructured reports (NSR) for magnetic resonance enterography (MRE) of pediatric patients with Crohn's disease, and to evaluate referring clinicians' subjective assessment of reports. This institutional review board-approved, Health Insurance Portability and Accountability Act-compliant retrospective study included 25 pediatric subjects (15 male, 10 female; mean age = 14 years [range: 9-18 years]) with Crohn's disease imaged with MRE. Three radiologists independently interpreted all examinations using both NSR and SR, separated by 4 weeks. Reports were assessed for documentation of the presence or absence of 15 key reporting features. A total of 30 reports (15 NSR [5 per reader] and 15 SR [5 per reader]) were randomly selected for review by 3 referring physicians, who subjectively evaluated the reports independently. NSR documented the presence or absence of 7.7 ± 2.5 key features, whereas SR documented 14.0 ± 0.8 features (P < 0.001). SR resulted in increased documentation of 12 of 15 features including stricture (P < 0.001), fistula (P < 0.001), fluid collection (P = 0.003), and perianal disease (P < 0.001). Referring physicians preferred SR regarding ease of information extraction, clarity of anatomy, and ability to identify disease phenotype (P < 0.01 for each). The use of structured reporting in describing pediatric Crohn's disease, MRE resulted in significantly increased reporting of key features. Referring clinicians also demonstrated a subjective preference for SR. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. BUILDING ROBUST APPEARANCE MODELS USING ON-LINE FEATURE SELECTION

    Energy Technology Data Exchange (ETDEWEB)

    PORTER, REID B. [Los Alamos National Laboratory; LOVELAND, ROHAN [Los Alamos National Laboratory; ROSTEN, ED [Los Alamos National Laboratory

    2007-01-29

    In many tracking applications, adapting the target appearance model over time can improve performance. This approach is most popular in high frame rate video applications where latent variables, related to the objects appearance (e.g., orientation and pose), vary slowly from one frame to the next. In these cases the appearance model and the tracking system are tightly integrated, and latent variables are often included as part of the tracking system's dynamic model. In this paper we describe our efforts to track cars in low frame rate data (1 frame/second) acquired from a highly unstable airborne platform. Due to the low frame rate, and poor image quality, the appearance of a particular vehicle varies greatly from one frame to the next. This leads us to a different problem: how can we build the best appearance model from all instances of a vehicle we have seen so far. The best appearance model should maximize the future performance of the tracking system, and maximize the chances of reacquiring the vehicle once it leaves the field of view. We propose an online feature selection approach to this problem and investigate the performance and computational trade-offs with a real-world dataset.

  3. Defining key features of the broad autism phenotype: a comparison across parents of multiple- and single-incidence autism families.

    Science.gov (United States)

    Losh, Molly; Childress, Debra; Lam, Kristen; Piven, Joseph

    2008-06-01

    This study examined the frequency of personality, language, and social-behavioral characteristics believed to comprise the broad autism phenotype (BAP), across families differing in genetic liability to autism. We hypothesized that within this unique sample comprised of multiple-incidence autism families (MIAF), single-incidence autism families (SIAF), and control Down syndrome families (DWNS), a graded expression would be observed for the principal characteristics conferring genetic susceptibility to autism, in which such features would express most profoundly among parents from MIAFs, less strongly among SIAFs, and least of all among comparison parents from DWNS families, who should display population base rates. Analyses detected linear expression of traits in line with hypotheses, and further suggested differential intrafamilial expression across family types. In the vast majority of MIAFs both parents displayed BAP characteristics, whereas within SIAFs, it was equally likely that one, both, or neither parent show BAP features. The significance of these findings is discussed in relation to etiologic mechanisms in autism and relevance to molecular genetic studies.

  4. Keys to the House: Unlocking Residential Savings With Program Models for Home Energy Upgrades

    Energy Technology Data Exchange (ETDEWEB)

    Grevatt, Jim [Energy Futures Group (United States); Hoffman, Ian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hoffmeyer, Dale [US Department of Energy, Washington, DC (United States)

    2017-07-05

    After more than 40 years of effort, energy efficiency program administrators and associated contractors still find it challenging to penetrate the home retrofit market, especially at levels commensurate with state and federal goals for energy savings and emissions reductions. Residential retrofit programs further have not coalesced around a reliably successful model. They still vary in design, implementation and performance, and they remain among the more difficult and costly options for acquiring savings in the residential sector. If programs are to contribute fully to meeting resource and policy objectives, administrators need to understand what program elements are key to acquiring residential savings as cost effectively as possible. To that end, the U.S. Department of Energy (DOE) sponsored a comprehensive review and analysis of home energy upgrade programs with proven track records, focusing on those with robustly verified savings and constituting good examples for replication. The study team reviewed evaluations for the period 2010 to 2014 for 134 programs that are funded by customers of investor-owned utilities. All are programs that promote multi-measure retrofits or major system upgrades. We paid particular attention to useful design and implementation features, costs, and savings for nearly 30 programs with rigorous evaluations of performance. This meta-analysis describes program models and implementation strategies for (1) direct install retrofits; (2) heating, ventilating and air-conditioning (HVAC) replacement and early retirement; and (3) comprehensive, whole-home retrofits. We analyze costs and impacts of these program models, in terms of both energy savings and emissions avoided. These program models can be useful guides as states consider expanding their strategies for acquiring energy savings as a resource and for emissions reductions. We also discuss the challenges of using evaluations to create program models that can be confidently applied in

  5. From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

    Science.gov (United States)

    Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

    2016-02-01

    This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the

  6. Weighted Feature Significance: A Simple, Interpretable Model of Compound Toxicity Based on the Statistical Enrichment of Structural Features

    OpenAIRE

    Huang, Ruili; Southall, Noel; Xia, Menghang; Cho, Ming-Hsuang; Jadhav, Ajit; Nguyen, Dac-Trung; Inglese, James; Tice, Raymond R.; Austin, Christopher P.

    2009-01-01

    In support of the U.S. Tox21 program, we have developed a simple and chemically intuitive model we call weighted feature significance (WFS) to predict the toxicological activity of compounds, based on the statistical enrichment of structural features in toxic compounds. We trained and tested the model on the following: (1) data from quantitative high–throughput screening cytotoxicity and caspase activation assays conducted at the National Institutes of Health Chemical Genomics Center, (2) dat...

  7. Fiber modeling and clustering based on neuroanatomical features.

    Science.gov (United States)

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

    2011-01-01

    DTI tractography allows unprecedented understanding of brain neural connectivity in-vivo by capturing water diffusion patterns in brain white-matter microstructures. However, tractography algorithms often output hundreds of thousands of fibers, rendering the computation needed for subsequent data analysis intractable. A remedy is to group the fibers into bundles using fiber clustering techniques. Most existing fiber clustering methods, however, rely on fiber geometrical information only by viewing fibers as curves in the 3D Euclidean space. The important neuroanatomical aspect of the fibers is mostly ignored. In this paper, neuroanatomical information is encapsulated in a feature vector called the associativity vector, which functions as the "fingerprint" for each fiber and depicts the connectivity of the fiber with respect to individual anatomies. Using the associativity vectors of fibers, we model the fibers as observations sampled from multivariate Gaussian mixtures in the feature space. An expectation-maximization clustering approach is then employed to group the fibers into 16 major bundles. Experimental results indicate that the proposed method groups the fibers into anatomically meaningful bundles, which are highly consistent across subjects.

  8. Multi-scale salient feature extraction on mesh models

    KAUST Repository

    Yang, Yongliang

    2012-01-01

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

  9. Chromatin extrusion explains key features of loop and domain formation in wild-type and engineered genomes

    Science.gov (United States)

    Sanborn, Adrian; Rao, Suhas; Huang, Su-Chen; Durand, Neva; Huntley, Miriam; Jewett, Andrew; Bochkov, Ivan; Chinnappan, Dharmaraj; Cutkosky, Ashok; Li, Jian; Geeting, Kristopher; McKenna, Doug; Stamenova, Elena; Gnirke, Andreas; Melnikov, Alexandre; Lander, Eric; Aiden, Erez

    Our recent kilobase-resolution genome-wide maps of DNA self-contacts demonstrated that mammalian genomes are organized into domains and loops demarcated by the DNA-binding protein CTCF. Here, we combine these maps with new Hi-C, microscopy, and genome-editing experiments to study the physical structure of chromatin fibers, domains, and loops. We find that domains are inconsistent with equilibrium and fractal models. Instead, we use physical simulations to study two models of genome folding. In one, intermonomer attraction during condensation leads to formation of an anisotropic ``tension globule.'' In the other, CTCF and cohesin act together to extrude unknotted loops. Both models are consistent with the observed domains and loops. However, the extrusion model explains a far wider array of observations, such as why the CTCF-binding motifs at pairs of loop anchors lie in the convergent orientation. Finally, we perform 13 genome-editing experiments examining the effect of altering CTCF-binding sites on chromatin folding. The extrusion model predicts in silico the experimental maps using only CTCF-binding sites. Thus, we show that it is possible to disrupt, restore, and move loops and domains using targeted mutations as small as a single base pair.

  10. Data publication and dissemination of interactive keys under the open access model

    Science.gov (United States)

    The concepts of publication, citation and dissemination of interactive keys and other online keys are discussed and illustrated by a sample paper published in the present issue (doi: 10.3897/zookeys.21.271). The present model is based on previous experience with several existing examples of publishi...

  11. Feature extraction and models for speech: An overview

    Science.gov (United States)

    Schroeder, Manfred

    2002-11-01

    Modeling of speech has a long history, beginning with Count von Kempelens 1770 mechanical speaking machine. Even then human vowel production was seen as resulting from a source (the vocal chords) driving a physically separate resonator (the vocal tract). Homer Dudley's 1928 frequency-channel vocoder and many of its descendants are based on the same successful source-filter paradigm. For linguistic studies as well as practical applications in speech recognition, compression, and synthesis (see M. R. Schroeder, Computer Speech), the extant models require the (often difficult) extraction of numerous parameters such as the fundamental and formant frequencies and various linguistic distinctive features. Some of these difficulties were obviated by the introduction of linear predictive coding (LPC) in 1967 in which the filter part is an all-pole filter, reflecting the fact that for non-nasalized vowels the vocal tract is well approximated by an all-pole transfer function. In the now ubiquitous code-excited linear prediction (CELP), the source-part is replaced by a code book which (together with a perceptual error criterion) permits speech compression to very low bit rates at high speech quality for the Internet and cell phones.

  12. Feature network models for proximity data : statistical inference, model selection, network representations and links with related models

    NARCIS (Netherlands)

    Frank, Laurence Emmanuelle

    2006-01-01

    Feature Network Models (FNM) are graphical structures that represent proximity data in a discrete space with the use of features. A statistical inference theory is introduced, based on the additivity properties of networks and the linear regression framework. Considering features as predictor variab

  13. A New Skeleton Feature Extraction Method for Terrain Model Using Profile Recognition and Morphological Simplification

    Directory of Open Access Journals (Sweden)

    Huijie Zhang

    2013-01-01

    Full Text Available It is always difficul to reserve rings and main truck lines in the real engineering of feature extraction for terrain model. In this paper, a new skeleton feature extraction method is proposed to solve these problems, which put forward a simplification algorithm based on morphological theory to eliminate the noise points of the target points produced by classical profile recognition. As well all know, noise point is the key factor to influence the accuracy and efficiency of feature extraction. Our method connected the optimized feature points subset after morphological simplification; therefore, the efficiency of ring process and pruning has been improved markedly, and the accuracy has been enhanced without the negative effect of noisy points. An outbranching concept is defined, and the related algorithms are proposed to extract sufficient long trucks, which is capable of being consistent with real terrain skeleton. All of algorithms are conducted on many real experimental data, including GTOPO30 and benchmark data provided by PPA to verify the performance and accuracy of our method. The results showed that our method precedes PPA as a whole.

  14. Rate Regions of Secret Key Sharing in a New Source Model

    CERN Document Server

    Salimi, Somayeh; Aref, Mohammad Reza

    2010-01-01

    A source model for secret key generation between terminals is considered. Two users, namely users 1 and 2, at one side communicate with another user, namely user 3, at the other side via a public channel where three users can observe i.i.d. outputs of correlated sources. Each of users 1 and 2 intends to share a secret key with user 3 where user 1 acts as a wiretapper for user 2 and vice versa. In this model, two situations are considered: communication from users 1 and 2 to user 3 (the forward key strategy) and from user 3 to users 1 and 2 (the backward key strategy). In both situations, the goal is sharing a secret key between user 1 and user 3 while leaking no effective information about that key to user 2, and simultaneously, sharing another secret key between user 2 and user 3 while leaking no effective information about the latter key to user 1. This model is motivated by wireless communications when considering user 3 as a base station and users 1 and 2 as network users. In this paper, for both the forw...

  15. Analysis of the key influence factors on brand of higher education organizations. Feature of the fashion industry

    OpenAIRE

    I.A. Hardabkhadze

    2013-01-01

    The aim of this article is the search of rational suite of factors which have a significant impact on various aspects of the educational institution, and the development model of brand management system which is based on these factors.To achieve this aim the following tasks were formulated and solved:the analysis of main factors that adequately describe activities of the university was fulfilled;the suite of factors of influene on the state of the university brand, was selected from the lists...

  16. Self-interacting fields - key feature of the Standard Model of physics Exhibition LEPFest 2000

    CERN Multimedia

    2000-01-01

    The messengers of the weak interaction -W and Z particles -were discovered at CERN in 1983.After this breakthrough, LEP mass produced W and Z particles so physicists could study them and make careful measurements.These preci- sion studies have shown that W and Z particles behave very differently to photons,messengers of the electromagnetic interaction.Once emitted by an electrically charged particle, a photon has to terminate its mission at another electrically charged particle.Photons do not mingle with each other.W and Z particles,on the other hand,do.The LEP experiments were the first to see this intermingling of messenger particles.

  17. Abbreviation of larval development and extension of brood care as key features of the evolution of freshwater Decapoda.

    Science.gov (United States)

    Vogt, Günter

    2013-02-01

    The transition from marine to freshwater habitats is one of the major steps in the evolution of life. In the decapod crustaceans, four groups have colonized fresh water at different geological times since the Triassic, the freshwater shrimps, freshwater crayfish, freshwater crabs and freshwater anomurans. Some families have even colonized terrestrial habitats via the freshwater route or directly via the sea shore. Since none of these taxa has ever reinvaded its environment of origin the Decapoda appear particularly suitable to investigate life-history adaptations to fresh water. Evolutionary comparison of marine, freshwater and terrestrial decapods suggests that the reduction of egg number, abbreviation of larval development, extension of brood care and lecithotrophy of the first posthatching life stages are key adaptations to fresh water. Marine decapods usually have high numbers of small eggs and develop through a prolonged planktonic larval cycle, whereas the production of small numbers of large eggs, direct development and extended brood care until the juvenile stage is the rule in freshwater crayfish, primary freshwater crabs and aeglid anomurans. The amphidromous freshwater shrimp and freshwater crab species and all terrestrial decapods that invaded land via the sea shore have retained ocean-type planktonic development. Abbreviation of larval development and extension of brood care are interpreted as adaptations to the particularly strong variations of hydrodynamic parameters, physico-chemical factors and phytoplankton availability in freshwater habitats. These life-history changes increase fitness of the offspring and are obviously favoured by natural selection, explaining their multiple origins in fresh water. There is no evidence for their early evolution in the marine ancestors of the extant freshwater groups and a preadaptive role for the conquest of fresh water. The costs of the shift from relative r- to K-strategy in freshwater decapods are traded

  18. A Regional Model Study of Synoptic Features Over West Africa

    Science.gov (United States)

    Druyan, Leonard M.; Fulakeza, Matthew; Lonergan, Patrick; Saloum, Mahaman; Hansen, James E. (Technical Monitor)

    2001-01-01

    Synoptic weather features over West Africa were studied in simulations by the regional simulation model (RM) at the NASA/Goddard Institute for Space Studies. These pioneering simulations represent the beginning of an effort to adapt regional models for weather and climate prediction over West Africa. The RM uses a cartesian grid with 50 km horizontal resolution and fifteen vertical levels. An ensemble of four simulations was forced with lateral boundary conditions from ECMWF global analyses for the period 8-22 August 1988. The simulated mid-tropospheric circulation includes the skillful development and movement of several African wave disturbances. Wavelet analysis of mid-tropospheric winds detected a dominant periodicity of about 4 days and a secondary periodicity of 5-8 days. Spatial distributions of RM precipitation and precipitation time series were validated against daily rain gauge measurements and ISCCP satellite infrared cloud imagery. The time-space distribution of simulated precipitation was made more realistic by combining the ECMWR initial conditions with a 24-hr spin-up of the moisture field and also by damping high frequency gravity waves by dynamic initialization. Model precipitation "forecasts" over the Central Sahel were correlated with observations for about three days, but reinitializing with observed data on day 5 resulted in a dramatic improvement in the precipitation validation over the remaining 9 days. Results imply that information via the lateral boundary conditions is not always sufficient to minimize departures between simulated and actual precipitation patterns for more than several days. In addition, there was some evidence that the new initialization may increase the simulations' sensitivity to the quality of lateral boundary conditions.

  19. Norepinephrine transporter variant A457P knock-in mice display key features of human postural orthostatic tachycardia syndrome

    Directory of Open Access Journals (Sweden)

    Jana K. Shirey-Rice

    2013-07-01

    Postural orthostatic tachycardia syndrome (POTS is a common autonomic disorder of largely unknown etiology that presents with sustained tachycardia on standing, syncope and elevated norepinephrine spillover. Some individuals with POTS experience anxiety, depression and cognitive dysfunction. Previously, we identified a mutation, A457P, in the norepinephrine (NE; also known as noradrenaline transporter (NET; encoded by SLC6A2 in POTS patients. NET is expressed at presynaptic sites in NE neurons and plays a crucial role in regulating NE signaling and homeostasis through NE reuptake into noradrenergic nerve terminals. Our in vitro studies demonstrate that A457P reduces both NET surface trafficking and NE transport and exerts a dominant-negative impact on wild-type NET proteins. Here we report the generation and characterization of NET A457P mice, demonstrating the ability of A457P to drive the POTS phenotype and behaviors that are consistent with reported comorbidities. Mice carrying one A457P allele (NET+/P exhibited reduced brain and sympathetic NE transport levels compared with wild-type (NET+/+ mice, whereas transport activity in mice carrying two A457P alleles (NETP/P was nearly abolished. NET+/P and NETP/P mice exhibited elevations in plasma and urine NE levels, reduced 3,4-dihydroxyphenylglycol (DHPG, and reduced DHPG:NE ratios, consistent with a decrease in sympathetic nerve terminal NE reuptake. Radiotelemetry in unanesthetized mice revealed tachycardia in NET+/P mice without a change in blood pressure or baroreceptor sensitivity, consistent with studies of human NET A457P carriers. NET+/P mice also demonstrated behavioral changes consistent with CNS NET dysfunction. Our findings support that NET dysfunction is sufficient to produce a POTS phenotype and introduces the first genetic model suitable for more detailed mechanistic studies of the disorder and its comorbidities.

  20. Norepinephrine transporter variant A457P knock-in mice display key features of human postural orthostatic tachycardia syndrome.

    Science.gov (United States)

    Shirey-Rice, Jana K; Klar, Rebecca; Fentress, Hugh M; Redmon, Sarah N; Sabb, Tiffany R; Krueger, Jessica J; Wallace, Nathan M; Appalsamy, Martin; Finney, Charlene; Lonce, Suzanna; Diedrich, André; Hahn, Maureen K

    2013-07-01

    Postural orthostatic tachycardia syndrome (POTS) is a common autonomic disorder of largely unknown etiology that presents with sustained tachycardia on standing, syncope and elevated norepinephrine spillover. Some individuals with POTS experience anxiety, depression and cognitive dysfunction. Previously, we identified a mutation, A457P, in the norepinephrine (NE; also known as noradrenaline) transporter (NET; encoded by SLC6A2) in POTS patients. NET is expressed at presynaptic sites in NE neurons and plays a crucial role in regulating NE signaling and homeostasis through NE reuptake into noradrenergic nerve terminals. Our in vitro studies demonstrate that A457P reduces both NET surface trafficking and NE transport and exerts a dominant-negative impact on wild-type NET proteins. Here we report the generation and characterization of NET A457P mice, demonstrating the ability of A457P to drive the POTS phenotype and behaviors that are consistent with reported comorbidities. Mice carrying one A457P allele (NET(+/P)) exhibited reduced brain and sympathetic NE transport levels compared with wild-type (NET(+/+)) mice, whereas transport activity in mice carrying two A457P alleles (NET(P/P)) was nearly abolished. NET(+/P) and NET(P/P) mice exhibited elevations in plasma and urine NE levels, reduced 3,4-dihydroxyphenylglycol (DHPG), and reduced DHPG:NE ratios, consistent with a decrease in sympathetic nerve terminal NE reuptake. Radiotelemetry in unanesthetized mice revealed tachycardia in NET(+/P) mice without a change in blood pressure or baroreceptor sensitivity, consistent with studies of human NET A457P carriers. NET(+/P) mice also demonstrated behavioral changes consistent with CNS NET dysfunction. Our findings support that NET dysfunction is sufficient to produce a POTS phenotype and introduces the first genetic model suitable for more detailed mechanistic studies of the disorder and its comorbidities.

  1. FEATURES OF THE PROCESS MODEL FOR PENITENTIARY EDUCATION SYSTEM DIVERSIFICATION

    Directory of Open Access Journals (Sweden)

    Neile Kayumovna Schepkina

    2014-01-01

    Full Text Available The article covers features of the process model for penitentiary education system diversification. Issues of prison inmate education are of contemporary relevance over the past 30 years since criminal-executive system has undergone a number of changes due to changes and amendments to criminal laws and rules of proceedings, including those affected by international standards, European Prison Rules ensuring the rights of imprisoned persons to education. Russian criminal-executive, court supervision and correctional system adopted to have been implemented till 2020 provides qualitative changes in approaches related to practices of serving sentences and measures to prevent recidivism.Creating a set of incentives for social adaptation of a special group of inmates, while serving their sentences and after it, is the basic category in the range of initiatives that currently have been considered in terms of developing penitentiary system. One of the most significant ones among them is the incentive to take advantage of the educational opportunities available to them in prison.

  2. Key features for more successful place-based sustainability research on social-ecological systems: a Programme on Ecosystem Change and Society (PECS perspective

    Directory of Open Access Journals (Sweden)

    Patricia Balvanera

    2017-03-01

    Full Text Available The emerging discipline of sustainability science is focused explicitly on the dynamic interactions between nature and society and is committed to research that spans multiple scales and can support transitions toward greater sustainability. Because a growing body of place-based social-ecological sustainability research (PBSESR has emerged in recent decades, there is a growing need to understand better how to maximize the effectiveness of this work. The Programme on Ecosystem Change and Society (PECS provides a unique opportunity for synthesizing insights gained from this research community on key features that may contribute to the relative success of PBSESR. We surveyed the leaders of PECS-affiliated projects using a combination of open, closed, and semistructured questions to identify which features of a research project are perceived to contribute to successful research design and implementation. We assessed six types of research features: problem orientation, research team, and contextual, conceptual, methodological, and evaluative features. We examined the desirable and undesirable aspects of each feature, the enabling factors and obstacles associated with project implementation, and asked respondents to assess the performance of their own projects in relation to these features. Responses were obtained from 25 projects working in 42 social-ecological study cases within 25 countries. Factors that contribute to the overall success of PBSESR included: explicitly addressing integrated social-ecological systems; a focus on solution- and transformation-oriented research; adaptation of studies to their local context; trusted, long-term, and frequent engagement with stakeholders and partners; and an early definition of the purpose and scope of research. Factors that hindered the success of PBSESR included: the complexities inherent to social-ecological systems, the imposition of particular epistemologies and methods on the wider research group

  3. Design Intent for CAD Modeling Features Using Boolean Operations

    Science.gov (United States)

    Sonawane, Chandrakant R.; Sujit, Ghadge

    2017-05-01

    The objective of this paper is to add one more enhancement to design intent by adding a rule to find the intersection edges created between Boolean features. Design Intent is a core module in CAD software which is used for smart design of referencing elements to create required features. In general, the particular design intent will form a particular rule which can be utilized for specified purpose. In this paper, a design intent rule for Edge Blend feature is designed. The rule is also implemented and integrated with CAD software. The major contributions of this paper is to create a new intent design rule which picks the edges of the feature Present design intent rule is intended to pick the intersection edges of the feature, in doing so; the intent will avoid referencing to topology over referencing to hierarchy objects for greater reliability

  4. Characteristics of evolving models of care for arthritis: A key informant study

    Directory of Open Access Journals (Sweden)

    Veinot Paula

    2008-07-01

    Full Text Available Abstract Background The burden of arthritis is increasing in the face of diminishing health human resources to deliver care. In response, innovative models of care delivery are developing to facilitate access to quality care. Most models have developed in response to local needs with limited evaluation. The primary objective of this study is to a examine the range of models of care that deliver specialist services using a medical/surgical specialist and at least one other health care provider and b document the strengths and challenges of the identified models. A secondary objective is to identify key elements of best practice models of care for arthritis. Methods Semi-structured interviews were conducted with a sample of key informants with expertise in arthritis from jurisdictions with primarily publicly-funded health care systems. Qualitative data were analyzed using a constant comparative approach to identify common types of models of care, strengths and challenges of models, and key components of arthritis care. Results Seventy-four key informants were interviewed from six countries. Five main types of models of care emerged. 1 Specialized arthritis programs deliver comprehensive, multidisciplinary team care for arthritis. Two models were identified using health care providers (e.g. nurses or physiotherapists in expanded clinical roles: 2 triage of patients with musculoskeletal conditions to the appropriate services including specialists; and 3 ongoing management in collaboration with a specialist. Two models promoting rural access were 4 rural consultation support and 5 telemedicine. Key informants described important components of models of care including knowledgeable health professionals and patients. Conclusion A range of models of care for arthritis have been developed. This classification can be used as a framework for discussing care delivery. Areas for development include integration of care across the continuum, including primary

  5. Riparian erosion vulnerability model based on environmental features.

    Science.gov (United States)

    Botero-Acosta, Alejandra; Chu, Maria L; Guzman, Jorge A; Starks, Patrick J; Moriasi, Daniel N

    2017-12-01

    Riparian erosion is one of the major causes of sediment and contaminant load to streams, degradation of riparian wildlife habitats, and land loss hazards. Land and soil management practices are implemented as conservation and restoration measures to mitigate the environmental problems brought about by riparian erosion. This, however, requires the identification of vulnerable areas to soil erosion. Because of the complex interactions between the different mechanisms that govern soil erosion and the inherent uncertainties involved in quantifying these processes, assessing erosion vulnerability at the watershed scale is challenging. The main objective of this study was to develop a methodology to identify areas along the riparian zone that are susceptible to erosion. The methodology was developed by integrating the physically-based watershed model MIKE-SHE, to simulate water movement, and a habitat suitability model, MaxEnt, to quantify the probability of presences of elevation changes (i.e., erosion) across the watershed. The presences of elevation changes were estimated based on two LiDAR-based elevation datasets taken in 2009 and 2012. The changes in elevation were grouped into four categories: low (0.5 - 0.7 m), medium (0.7 - 1.0 m), high (1.0 - 1.7 m) and very high (1.7 - 5.9 m), considering each category as a studied "species". The categories' locations were then used as "species location" map in MaxEnt. The environmental features used as constraints to the presence of erosion were land cover, soil, stream power index, overland flow, lateral inflow, and discharge. The modeling framework was evaluated in the Fort Cobb Reservoir Experimental watershed in southcentral Oklahoma. Results showed that the most vulnerable areas for erosion were located at the upper riparian zones of the Cobb and Lake sub-watersheds. The main waterways of these sub-watersheds were also found to be prone to streambank erosion. Approximatively 80% of the riparian zone (streambank

  6. A Bayesian Mixture Model for PoS Induction Using Multiple Features

    OpenAIRE

    Christodoulopoulos, Christos; Goldwater, Sharon; Steedman, Mark

    2011-01-01

    In this paper we present a fully unsupervised syntactic class induction system formulated as a Bayesian multinomial mixture model, where each word type is constrained to belong to a single class. By using a mixture model rather than a sequence model (e.g., HMM), we are able to easily add multiple kinds of features, including those at both the type level (morphology features) and token level (context and alignment features, the latter from parallel corpora). Using only context features, our sy...

  7. Key features of wave energy.

    Science.gov (United States)

    Rainey, R C T

    2012-01-28

    For a weak point source or dipole, or a small body operating as either, we show that the power from a wave energy converter (WEC) is the product of the particle velocity in the waves, and the wave force (suitably defined). There is a thus a strong analogy with a wind or tidal turbine, where the power is the product of the fluid velocity through the turbine, and the force on it. As a first approximation, the cost of a structure is controlled by the force it has to carry, which governs its strength, and the distance it has to be carried, which governs its size. Thus, WECs are at a disadvantage compared with wind and tidal turbines because the fluid velocities are lower, and hence the forces are higher. On the other hand, the distances involved are lower. As with turbines, the implication is also that a WEC must make the most of its force-carrying ability-ideally, to carry its maximum force all the time, the '100% sweating WEC'. It must be able to limit the wave force on it in larger waves, ultimately becoming near-transparent to them in the survival condition-just like a turbine in extreme conditions, which can stop and feather its blades. A turbine of any force rating can achieve its maximum force in low wind speeds, if its diameter is sufficiently large. This is not possible with a simple monopole or dipole WEC, however, because of the 'nλ/2π' capture width limits. To achieve reasonable 'sweating' in typical wave climates, the force is limited to about 1 MN for a monopole device, or 2 MN for a dipole. The conclusion is that the future of wave energy is in devices that are not simple monopoles or dipoles, but multi-body devices or other shapes equivalent to arrays.

  8. Statistical key variable analysis and model-based control for improvement performance in a deep reactive ion etching process

    Institute of Scientific and Technical Information of China (English)

    Chen Shan; Pan Tianhong; Li Zhengming; Jang Shi-Shang

    2012-01-01

    This paper proposes to develop a data-driven via's depth estimator of the deep reactive ion etching process based on statistical identification of key variables.Several feature extraction algorithms are presented to reduce the high-dimensional data and effectively undertake the subsequent virtual metrology (VM) model building process.With the available on-line VM model,the model-based controller is hence readily applicable to improve the quality ofa via's depth.Real operational data taken from a industrial manufacturing process are used to verify the effectiveness of the proposed method.The results demonstrate that the proposed method can decrease the MSE from 2.2 × 10-2 to 9 × 10-4 and has great potential in improving the existing DRIE process.

  9. A Novel DBN Feature Fusion Model for Cross-Corpus Speech Emotion Recognition

    Directory of Open Access Journals (Sweden)

    Zou Cairong

    2016-01-01

    Full Text Available The feature fusion from separate source is the current technical difficulties of cross-corpus speech emotion recognition. The purpose of this paper is to, based on Deep Belief Nets (DBN in Deep Learning, use the emotional information hiding in speech spectrum diagram (spectrogram as image features and then implement feature fusion with the traditional emotion features. First, based on the spectrogram analysis by STB/Itti model, the new spectrogram features are extracted from the color, the brightness, and the orientation, respectively; then using two alternative DBN models they fuse the traditional and the spectrogram features, which increase the scale of the feature subset and the characterization ability of emotion. Through the experiment on ABC database and Chinese corpora, the new feature subset compared with traditional speech emotion features, the recognition result on cross-corpus, distinctly advances by 8.8%. The method proposed provides a new idea for feature fusion of emotion recognition.

  10. Passage Key Inlet, Florida; CMS Modeling and Borrow Site Impact Analysis

    Science.gov (United States)

    2016-06-01

    use of a nested Coastal Modeling System (CMS) model for Passage Key Inlet, which is one of the connections between the Gulf of Mexico and Tampa Bay...XIV-51 June 2016 2 Figure 1. Active USACE Jacksonville District (SAJ) projects in Pinellas, Manatee, and Sarasota Counties, FL. METHOD : The CMS...is a product of the Coastal Inlets Research Program (http://cirp.usace.army.mil) managed at ERDC. CMS is composed of two models, CMS-Flow (Buttolph

  11. Key-Aspects of Scientific Modeling Exemplified by School Science Models: Some Units for Teaching Contextualized Scientific Methodology

    Science.gov (United States)

    Develaki, Maria

    2016-01-01

    Models and modeling are core elements of scientific methods and consequently also are of key importance for the conception and teaching of scientific methodology. The epistemology of models and its transfer and adaption to nature of science education are not, however, simple themes. We present some conceptual units in which school science models…

  12. The Sender-Excited Secret Key Agreement Model: Capacity and Error Exponents

    CERN Document Server

    Chou, Tzu-Han; Draper, Stark C

    2011-01-01

    We consider fundamental limits of the secret key generation problem when the sources are randomly excited by the sender and there is a noiseless public discussion channel. In many practical communication settings, the sources or channels may be influenced by some parties involved. Similar to recent works on probing capacity and channels with action-dependent states, our system model captures such a scenario. We derive single-letter expressions for the secret key capacity. Our coding strategy involves wiretap channel coding and a key generation scheme. We show that the secret key capacity is composed of both source- and channel-type randomness. By assuming that the eavesdropper receives a degraded version of the legitimate receiver's observation, we also obtain a capacity result that does not involve any auxiliary random variables, and thus it is amenable to numerical evaluation. By evaluating the capacity for several degraded channels, we show that there is a fundamental interplay between the portion of the s...

  13. Key Frame Extraction Using Unsupervised Clustering Based on a Statistical Model

    Institute of Scientific and Technical Information of China (English)

    YANG Shuping; LIN Xinggang

    2005-01-01

    This paper proposes a novel algorithm for extracting key frames to represent video shots. Regarding whether, or how well, a key frame represents a shot, different interpretations have been suggested. We develop our algorithm on the assumption that more important content may demand more attention and may last relatively more frames. Unsupervised clustering is used to divide the frames into clusters within a shot, and then a key frame is selected from each candidate cluster. To make the algorithm independent of video sequences, we employ a statistical model to calculate the clustering threshold. The proposed algorithm can capture the important yet salient content as the key frame. Its robustness and adaptability are validated by experiments with various kinds of video sequences.

  14. Ears Identification Based on key points of the Structural Features%基于几何结构关键点的人耳检测

    Institute of Scientific and Technical Information of China (English)

    宋晓坤

    2009-01-01

    Ear Identification is a new biometrics technique,The most distinctive Features of ear are that about its Geometry and Anatomy, such as antihelix、earlobe、triangular fossa.Method mentioned in this article uses the conception of the complexity extent to carry on the fast orientation for the key points position in human ear images, instead of gray Comparison,to improve maneuverability.Than,we can combine with the unique geometric characteristics that ear have to choose key points.During our choosing, we use optimization algorithm to decide which are the best points we need , partially.Finally,make curve fitting with the points we have chosed.Thus we get the curve which can reappear Geometry and Anatomy Features of ear.%人耳识别是目前生物特征识别的一种重要技术,外耳图像上最具区分能力的特征就是外耳的形状特征和外耳的解剖学特征,比如对耳轮、耳垂、三角窝等部分.本文的方法首先将基于灰度识别转化为复杂度比较,从而增强可操作性,然后结合人耳特有的几何特征,进行结构特征基本点的选取,在选取时考虑在局部采用优化算法进行最优化选点,最后抓取选取的最优点进行曲线的拟合,得到人耳轮廓及特征结构.

  15. Password-only authenticated three-party key exchange with provable security in the standard model.

    Science.gov (United States)

    Nam, Junghyun; Choo, Kim-Kwang Raymond; Kim, Junghwan; Kang, Hyun-Kyu; Kim, Jinsoo; Paik, Juryon; Won, Dongho

    2014-01-01

    Protocols for password-only authenticated key exchange (PAKE) in the three-party setting allow two clients registered with the same authentication server to derive a common secret key from their individual password shared with the server. Existing three-party PAKE protocols were proven secure under the assumption of the existence of random oracles or in a model that does not consider insider attacks. Therefore, these protocols may turn out to be insecure when the random oracle is instantiated with a particular hash function or an insider attack is mounted against the partner client. The contribution of this paper is to present the first three-party PAKE protocol whose security is proven without any idealized assumptions in a model that captures insider attacks. The proof model we use is a variant of the indistinguishability-based model of Bellare, Pointcheval, and Rogaway (2000), which is one of the most widely accepted models for security analysis of password-based key exchange protocols. We demonstrated that our protocol achieves not only the typical indistinguishability-based security of session keys but also the password security against undetectable online dictionary attacks.

  16. Password-Only Authenticated Three-Party Key Exchange with Provable Security in the Standard Model

    Directory of Open Access Journals (Sweden)

    Junghyun Nam

    2014-01-01

    Full Text Available Protocols for password-only authenticated key exchange (PAKE in the three-party setting allow two clients registered with the same authentication server to derive a common secret key from their individual password shared with the server. Existing three-party PAKE protocols were proven secure under the assumption of the existence of random oracles or in a model that does not consider insider attacks. Therefore, these protocols may turn out to be insecure when the random oracle is instantiated with a particular hash function or an insider attack is mounted against the partner client. The contribution of this paper is to present the first three-party PAKE protocol whose security is proven without any idealized assumptions in a model that captures insider attacks. The proof model we use is a variant of the indistinguishability-based model of Bellare, Pointcheval, and Rogaway (2000, which is one of the most widely accepted models for security analysis of password-based key exchange protocols. We demonstrated that our protocol achieves not only the typical indistinguishability-based security of session keys but also the password security against undetectable online dictionary attacks.

  17. Valuing snorkeling visits to the Florida Keys with stated and revealed preference models.

    Science.gov (United States)

    Park, Timothy; Bowker, J M; Leeworthy, Vernon R

    2002-07-01

    Coastal coral reefs, especially in the Florida Keys, are declining at a disturbing rate. Marine ecologists and reef scientists have emphasized the importance of establishing nonmarket values of coral reefs to assess the cost effectiveness of coral reef management and remediation programs. The purpose of this paper is to develop a travel cost-contingent valuation model of demand for trips to the Florida Keys focusing on willingness to pay (WTP) to preserve the current water quality and health of the coral reefs. The stated and revealed preference models allow the marginal valuation of recreationists to adjust depending on current and planned trip commitments in valuing nonmarginal policy changes in recreational opportunities. The integrated model incorporates key factors for establishing baseline amenity values for tourist dive sites, including perceptions of reef quality and dive conditions, the role of substitute sites, and the quality and availability of tourist facilities and recreation opportunities. The travel cost and WTP model differ in identifying critical variables and provide insight into the adjustment of trip decisions across alternative destination sites and the valuation of trips. In contrast to the travel cost model, a measure of the availability of substitute sites and total recreation activities does not have a significant impact on WTP valuations reported by snorkelers. Snorkelers engage in a relatively focused set of activities, suggesting that these recreationists may not shift expenditures to other sites or other recreation activities in the Florida Keys when confronted with increased access costs for the snorkeling experience.

  18. Research on the Price Features of Oil Stochastic Model Based on the Continuous Jump Model

    Directory of Open Access Journals (Sweden)

    Hou Mengmeng

    2017-01-01

    Full Text Available Aiming at calculating the price changes under the price features of oil stochastic model, the continuous jump model is proposed in this paper for data processing. The procedure is flexible, may be used with market prices of any oil contingent claim with closed form pricing solution, and easily deals with missing data problems. The results show that the accuracy can thus be improved overall the proposed system substantially.

  19. Operational Details of the Five Domains Model and Its Key Applications to the Assessment and Management of Animal Welfare

    Science.gov (United States)

    Mellor, David J.

    2017-01-01

    Simple Summary The Five Domains Model is a focusing device to facilitate systematic, structured, comprehensive and coherent assessment of animal welfare; it is not a definition of animal welfare, nor is it intended to be an accurate representation of body structure and function. The purpose of each of the five domains is to draw attention to areas that are relevant to both animal welfare assessment and management. This paper begins by briefly describing the major features of the Model and the operational interactions between the five domains, and then it details seven interacting applications of the Model. These underlie its utility and increasing application to welfare assessment and management in diverse animal use sectors. Abstract In accord with contemporary animal welfare science understanding, the Five Domains Model has a significant focus on subjective experiences, known as affects, which collectively contribute to an animal’s overall welfare state. Operationally, the focus of the Model is on the presence or absence of various internal physical/functional states and external circumstances that give rise to welfare-relevant negative and/or positive mental experiences, i.e., affects. The internal states and external circumstances of animals are evaluated systematically by referring to each of the first four domains of the Model, designated “Nutrition”, “Environment”, “Health” and “Behaviour”. Then affects, considered carefully and cautiously to be generated by factors in these domains, are accumulated into the fifth domain, designated “Mental State”. The scientific foundations of this operational procedure, published in detail elsewhere, are described briefly here, and then seven key ways the Model may be applied to the assessment and management of animal welfare are considered. These applications have the following beneficial objectives—they (1) specify key general foci for animal welfare management; (2) highlight the foundations of

  20. Feature and Model Selection in Feedforward Neural Networks

    Science.gov (United States)

    1994-06-01

    smaller than those experienced with the derivative-based saliencies. However, a minimal number of nodes were used to analyze the FLUIR problem, these...A4m. 101 Table 15. FLUIR Problem: Saliency Metric Loadings after Varimax Rotation Features Saliency Metrics 1 2 3 4 5 6 7181 1.__ _ 1_1 1 2 1 1 1 1 1

  1. Modelling Feature Interaction Patterns in Nokia Mobile Phones using Coloured Petri Nets and Design/CPN

    DEFF Research Database (Denmark)

    Lorentsen, Louise; Tuovinen, Antti-Pekka; Xu, Jianli

    2002-01-01

    This paper describes the first results of a project on modelling of important feature interaction patterns of Nokia mobile phones using Coloured Petri Nets. A modern mobile phone supports many features: voice and data calls, text messaging, personal information management (phonebook and calendar....... In this paper, we look at the problem of feature interaction in the user interface of Nokia mobile phones. We present a categorization of feature interactions and describe our approach to the modelling of feature interactions using Coloured Petri Nets (CP-nets or CPN). The CPN model is extended...

  2. Extracting Key Frames Based on Color Features and Motion Information%基于颜色特征及运动信息提取关键帧

    Institute of Scientific and Technical Information of China (English)

    邓斌; 张基宏

    2012-01-01

    视频关键帧提取是视频信号处理中的一个重要内容。由于一个镜头中视觉内容的变化具有连续性,本文采用了距离累加的算法;同时,为了提高检测相邻帧间的相似度,本文将颜色特征与运动变化信息相结合,提出一种关键帧提取方法。实验证明,与过去的关键帧提取方法相比,本文算法提取的关键帧能较完整地表现序列图像的运动过程,更有利于对视频内容的理解。%Video key frame extraction is an important part of video signal processing. In this paper, we propose a new key frame extraction method. As the visual change in a shot is continuous, the method of cumulative distance is adopted; color features and motion information are integrated to improve the detection precision of adjoining frames' similarities and differences. Experiment resuhs show that the new method proposed in this paper is superior to traditional methods based on color histogram and particle equivalent in that the key frames extracted with the new method give a better picture of the movement of sequential images.

  3. A new notion of soundness in bare public-key model

    Institute of Scientific and Technical Information of China (English)

    ZHAO Yunlei; ZHU Hong

    2003-01-01

    A new notion of soundness in bare public-key (BPK) model is presented. This new notion just lies in between one-time soundness and sequential soundness and its reasonableness is justified in the context of resettable zero-knowledge when resettable zero-knowledge prover is implemented by smart card.

  4. Enhancer identification in mouse embryonic stem cells using integrative modeling of chromatin and genomic features

    Directory of Open Access Journals (Sweden)

    Chen Chih-yu

    2012-04-01

    Full Text Available Abstract Background Epigenetic modifications, transcription factor (TF availability and differences in chromatin folding influence how the genome is interpreted by the transcriptional machinery responsible for gene expression. Enhancers buried in non-coding regions are found to be associated with significant differences in histone marks between different cell types. In contrast, gene promoters show more uniform modifications across cell types. Here we used histone modification and chromatin-associated protein ChIP-Seq data sets in mouse embryonic stem (ES cells as well as genomic features to identify functional enhancer regions. Using co-bound sites of OCT4, SOX2 and NANOG (co-OSN, validated enhancers and co-bound sites of MYC and MYCN (limited enhancer activity as enhancer positive and negative training sets, we performed multinomial logistic regression with LASSO regularization to identify key features. Results Cross validations reveal that a combination of p300, H3K4me1, MED12 and NIPBL features to be top signatures of co-OSN regions. Using a model from 10 signatures, 83% of top 1277 putative 1 kb enhancer regions (probability greater than or equal to 0.8 overlapped with at least one TF peak from 7 mouse ES cell ChIP-Seq data sets. These putative enhancers are associated with increased gene expression of neighbouring genes and significantly enriched in multiple TF bound loci in agreement with combinatorial models of TF binding. Furthermore, we identified several motifs of known TFs significantly enriched in putative enhancer regions compared to random promoter regions and background. Comparison with an active H3K27ac mark in various cell types confirmed cell type-specificity of these enhancers. Conclusions The top enhancer signatures we identified (p300, H3K4me1, MED12 and NIPBL will allow for the identification of cell type-specific enhancer regions in diverse cell types.

  5. 基于STEP的特征模型及重构算法%STEP-Based Feature Model and Feature Reconstructed Arithmetic

    Institute of Scientific and Technical Information of China (English)

    刘乃若; 王金伦

    2003-01-01

    For CAX systems,the technology of Feature-based product data integration is one of hot points. STEP AP214 protocol provides a standard to resolve this problem. This paper discusses the relations of entities in STEP AP214. Especially,for the problem that the protocol doesn't obviously give those features,it puts forward methods on expression and operation of feature-oriented data model. It gives the feature model mapping between AP214 and feature-based CAD systems,which is a basal theory to design out a uniform feature model of CAD/CAPP/CAM.

  6. Sequential Clustering based Facial Feature Extraction Method for Automatic Creation of Facial Models from Orthogonal Views

    CERN Document Server

    Ghahari, Alireza

    2009-01-01

    Multiview 3D face modeling has attracted increasing attention recently and has become one of the potential avenues in future video systems. We aim to make more reliable and robust automatic feature extraction and natural 3D feature construction from 2D features detected on a pair of frontal and profile view face images. We propose several heuristic algorithms to minimize possible errors introduced by prevalent nonperfect orthogonal condition and noncoherent luminance. In our approach, we first extract the 2D features that are visible to both cameras in both views. Then, we estimate the coordinates of the features in the hidden profile view based on the visible features extracted in the two orthogonal views. Finally, based on the coordinates of the extracted features, we deform a 3D generic model to perform the desired 3D clone modeling. Present study proves the scope of resulted facial models for practical applications like face recognition and facial animation.

  7. Feature-Enhanced, Model-Based Sparse Aperture Imaging

    Science.gov (United States)

    2008-03-01

    obtain a sharp estimate of the spatial spectrum that exhibits super-resolution. We propose to use the singular value decomposition ( SVD ) of the data...application in a variety of problems, including image reconstruction and restoration [5], wavelet denoising [6], feature selection in machine learning...on the singular value decomposition ( SVD ) to combine multiple samples and the use of second-order cone programming for optimization of the resulting

  8. An Investigation of Feature Models for Music Genre Classification using the Support Vector Classifier

    DEFF Research Database (Denmark)

    Meng, Anders; Shawe-Taylor, John

    2005-01-01

    autoregressive model for modelling short time features. Furthermore, it was investigated how these models can be integrated over a segment of short time features into a kernel such that a support vector machine can be applied. Two kernels with this property were considered, the convolution kernel and product...

  9. Nine key principles to guide youth mental health: development of service models in New South Wales.

    Science.gov (United States)

    Howe, Deborah; Batchelor, Samantha; Coates, Dominiek; Cashman, Emma

    2014-05-01

    Historically, the Australian health system has failed to meet the needs of young people with mental health problems and mental illness. In 2006, New South Wales (NSW) Health allocated considerable funds to the reform agenda of mental health services in NSW to address this inadequacy. Children and Young People's Mental Health (CYPMH), a service that provides mental health care for young people aged 12-24 years, with moderate to severe mental health problems, was chosen to establish a prototype Youth Mental Health (YMH) Service Model for NSW. This paper describes nine key principles developed by CYPMH to guide the development of YMH Service Models in NSW. A literature review, numerous stakeholder consultations and consideration of clinical best practice were utilized to inform the development of the key principles. Subsequent to their development, the nine key principles were formally endorsed by the Mental Health Program Council to ensure consistency and monitor the progress of YMH services across NSW. As a result, between 2008 and 2012 YMH Services across NSW regularly reported on their activities against each of the nine key principles demonstrating how each principle was addressed within their service. The nine key principles provide mental health services a framework for how to reorient services to accommodate YMH and provide a high-quality model of care. [Corrections added on 29 November 2013, after first online publication: The last two sentences of the Results section have been replaced with "As a result, between 2008 and 2012 YMH Services across NSW regularly reported on their activities against each of the nine key principles demonstrating how each principle was addressed within their service."]. © 2013 Wiley Publishing Asia Pty Ltd.

  10. Salient Features of the Harnischfeger-Wiley Model

    Science.gov (United States)

    Hallinan, Maureen T.

    1976-01-01

    Explicates the Harnischfeger-Wiley model and points out its properties, underlying assumptions, and location in the literature on achievement. It also describes and critiques an empirical test by Harnischfeger and Wiley of their model. (Author/IRT)

  11. SYNERGIES BETWEEN SOCIAL MEDIA FEATURES AND USER ENGAGEMENT TO ENHANCE ONLINE BRAND VISIBILITY - A CONCEPTUAL MODEL

    Directory of Open Access Journals (Sweden)

    Anuradha Goswami

    2013-06-01

    Full Text Available Organizations today are fast realizing the impact of social media as a significant business driver for capitalizing the advantages on certain key strategic issues like user engagement and brand visibility. Integrating social media characteristics is one of the key differentiators for enhancing online brand visibility. Though a lot of research has been made on the social media usability and userengagement, the uniqueness of this research paper is the identification of synergies between the features of social media and user engagement to enhance online brand visibility. In this paper a conceptual model is explained by developing a social media-user engagement matrix to explain the synergies. The matrix integrates four parameters of User Engagement namely Involvement, Interaction, Intimacy and Influence with four Social Media characteristics namely Content, Relationship, Value and Structure to bring out the essence of interoperability. This paper has identified and listed certain metrics for measuring the online brand visibility. We believe that the outcome of this paper will make significant contribution tothe existing body of knowledge by uniquely identifying and explaining the ‘social media-user engagement synergy’ and also listing appropriate metrics for measuring online brand visibility.

  12. AIDS policy modeling for the 21st century: an overview of key issues.

    Science.gov (United States)

    Rauner, M S; Brandeau, M L

    2001-09-01

    Decisions about HIV prevention and treatment programs are based on factors such as program costs and health benefits, social and ethical issues, and political considerations. AIDS policy models--that is, models that evaluate the monetary and non-monetary consequences of decisions about HIV/AIDS interventions--can play a role in helping policy makers make better decisions. This paper provides an overview of the key issues related to developing useful AIDS policy models. We highlight issues of importance for researchers in the field of AIDS policy modeling as well as for policy makers. These include geographic area, setting, target groups, interventions, affordability and effectiveness of interventions, type and time horizon of policy model, and type of economic analysis. This paper is not intended to be an exhaustive review of the AIDS policy modeling literature, although many papers from the literature are discussed as examples; rather, we aim to convey the composition, achievements, and challenges of AIDS policy modeling.

  13. Adaptive object recognition model using incremental feature representation and hierarchical classification.

    Science.gov (United States)

    Jeong, Sungmoon; Lee, Minho

    2012-01-01

    This paper presents an adaptive object recognition model based on incremental feature representation and a hierarchical feature classifier that offers plasticity to accommodate additional input data and reduces the problem of forgetting previously learned information. The incremental feature representation method applies adaptive prototype generation with a cortex-like mechanism to conventional feature representation to enable an incremental reflection of various object characteristics, such as feature dimensions in the learning process. A feature classifier based on using a hierarchical generative model recognizes various objects with variant feature dimensions during the learning process. Experimental results show that the adaptive object recognition model successfully recognizes single and multiple-object classes with enhanced stability and flexibility.

  14. Features of Balance Model Development of Exclave Region

    Directory of Open Access Journals (Sweden)

    Timur Rustamovich Gareev

    2015-06-01

    Full Text Available In the article, the authors build a balance model for an exclave region. The aim of the work is to explore the unique properties of exclaves to evaluate the possibility of development of a more complex model for the economy of a region. Exclaves are strange phenomena in both theoretical and practical regional economy. There is lack of comparative models, so it is typically quite challenging to study exclaves. At the same time, exclaves produce better statistics, which gives more careful consideration of cross-regional economic flows. The authors discuss methodologies of model-based regional development forecasting. They analyze balance approach on a more general level of regional governance and individually, on the example of specific territories. Thus, they identify and explain the need to develop balance approach models fitted to the special needs of certain territories. By combining regional modeling for an exclave with traditional balance and simulation-based methods and event-based approach, they come up with a more detailed model for the economy of a region. Having taken one Russian exclave as an example, the authors have developed a simulation event-based long-term sustainability model. In the article, they provide the general characteristics of the model, describe its components, and simulation algorithm. The approach introduced in this article combines the traditional balance models and the peculiarities of an exclave region to develop a holistic regional economy model (with the Kaliningrad region serving as an example. It is important to underline that the resulting model helps to evaluate the degree of influence of preferential economic regimes (such as Free Customs Zone, for example on the economy of a region.

  15. Estimation of key parameters in adaptive neuron model according to firing patterns based on improved particle swarm optimization algorithm

    Science.gov (United States)

    Yuan, Chunhua; Wang, Jiang; Yi, Guosheng

    2017-03-01

    Estimation of ion channel parameters is crucial to spike initiation of neurons. The biophysical neuron models have numerous ion channel parameters, but only a few of them play key roles in the firing patterns of the models. So we choose three parameters featuring the adaptation in the Ermentrout neuron model to be estimated. However, the traditional particle swarm optimization (PSO) algorithm is still easy to fall into local optimum and has the premature convergence phenomenon in the study of some problems. In this paper, we propose an improved method that uses a concave function and dynamic logistic chaotic mapping mixed to adjust the inertia weights of the fitness value, effectively improve the global convergence ability of the algorithm. The perfect predicting firing trajectories of the rebuilt model using the estimated parameters prove that only estimating a few important ion channel parameters can establish the model well and the proposed algorithm is effective. Estimations using two classic PSO algorithms are also compared to the improved PSO to verify that the algorithm proposed in this paper can avoid local optimum and quickly converge to the optimal value. The results provide important theoretical foundations for building biologically realistic neuron models.

  16. Geometric Feature Extraction and Model Reconstruction Based on Scattered Data

    Institute of Scientific and Technical Information of China (English)

    胡鑫; 习俊通; 金烨

    2004-01-01

    A method of 3D model reconstruction based on scattered point data in reverse engineering is presented here. The topological relationship of scattered points was established firstly, then the data set was triangulated to reconstruct the mesh surface model. The curvatures of cloud data were calculated based on the mesh surface, and the point data were segmented by edge-based method; Every patch of data was fitted by quadric surface of freeform surface, and the type of quadric surface was decided by parameters automatically, at last the whole CAD model was created. An example of mouse model was employed to confirm the effect of the algorithm.

  17. A Web-Based Data Collection Platform for Multisite Randomized Behavioral Intervention Trials: Development, Key Software Features, and Results of a User Survey.

    Science.gov (United States)

    Modi, Riddhi A; Mugavero, Michael J; Amico, Rivet K; Keruly, Jeanne; Quinlivan, Evelyn Byrd; Crane, Heidi M; Guzman, Alfredo; Zinski, Anne; Montue, Solange; Roytburd, Katya; Church, Anna; Willig, James H

    2017-06-16

    Meticulous tracking of study data must begin early in the study recruitment phase and must account for regulatory compliance, minimize missing data, and provide high information integrity and/or reduction of errors. In behavioral intervention trials, participants typically complete several study procedures at different time points. Among HIV-infected patients, behavioral interventions can favorably affect health outcomes. In order to empower newly diagnosed HIV positive individuals to learn skills to enhance retention in HIV care, we developed the behavioral health intervention Integrating ENGagement and Adherence Goals upon Entry (iENGAGE) funded by the National Institute of Allergy and Infectious Diseases (NIAID), where we deployed an in-clinic behavioral health intervention in 4 urban HIV outpatient clinics in the United States. To scale our intervention strategy homogenously across sites, we developed software that would function as a behavioral sciences research platform. This manuscript aimed to: (1) describe the design and implementation of a Web-based software application to facilitate deployment of a multisite behavioral science intervention; and (2) report on results of a survey to capture end-user perspectives of the impact of this platform on the conduct of a behavioral intervention trial. In order to support the implementation of the NIAID-funded trial iENGAGE, we developed software to deploy a 4-site behavioral intervention for new clinic patients with HIV/AIDS. We integrated the study coordinator into the informatics team to participate in the software development process. Here, we report the key software features and the results of the 25-item survey to evaluate user perspectives on research and intervention activities specific to the iENGAGE trial (N=13). The key features addressed are study enrollment, participant randomization, real-time data collection, facilitation of longitudinal workflow, reporting, and reusability. We found 100% user

  18. Clinical Features of Bacterial Vaginosis in a Murine Model of Vaginal Infection with Gardnerella vaginalis

    Science.gov (United States)

    Gilbert, Nicole M.; Lewis, Warren G.; Lewis, Amanda L.

    2013-01-01

    Bacterial vaginosis (BV) is a dysbiosis of the vaginal flora characterized by a shift from a Lactobacillus-dominant environment to a polymicrobial mixture including Actinobacteria and Gram-negative bacilli. BV is a common vaginal condition in women and is associated with increased risk of sexually transmitted infection and adverse pregnancy outcomes such as preterm birth. Gardnerella vaginalis is one of the most frequently isolated bacterial species in BV. However, there has been much debate in the literature concerning the contribution of G. vaginalis to the etiology of BV, since it is also present in a significant proportion of healthy women. Here we present a new murine vaginal infection model with a clinical isolate of G. vaginalis. Our data demonstrate that this model displays key features used clinically to diagnose BV, including the presence of sialidase activity and exfoliated epithelial cells with adherent bacteria (reminiscent of clue cells). G. vaginalis was capable of ascending uterine infection, which correlated with the degree of vaginal infection and level of vaginal sialidase activity. The host response to G. vaginalis infection was characterized by robust vaginal epithelial cell exfoliation in the absence of histological inflammation. Our analyses of clinical specimens from women with BV revealed a measureable epithelial exfoliation response compared to women with normal flora, a phenotype that, to our knowledge, is measured here for the first time. The results of this study demonstrate that G. vaginalis is sufficient to cause BV phenotypes and suggest that this organism may contribute to BV etiology and associated complications. This is the first time vaginal infection by a BV associated bacterium in an animal has been shown to parallel the human disease with regard to clinical diagnostic features. Future studies with this model should facilitate investigation of important questions regarding BV etiology, pathogenesis and associated complications

  19. Clinical features of bacterial vaginosis in a murine model of vaginal infection with Gardnerella vaginalis.

    Directory of Open Access Journals (Sweden)

    Nicole M Gilbert

    Full Text Available Bacterial vaginosis (BV is a dysbiosis of the vaginal flora characterized by a shift from a Lactobacillus-dominant environment to a polymicrobial mixture including Actinobacteria and gram-negative bacilli. BV is a common vaginal condition in women and is associated with increased risk of sexually transmitted infection and adverse pregnancy outcomes such as preterm birth. Gardnerella vaginalis is one of the most frequently isolated bacterial species in BV. However, there has been much debate in the literature concerning the contribution of G. vaginalis to the etiology of BV, since it is also present in a significant proportion of healthy women. Here we present a new murine vaginal infection model with a clinical isolate of G. vaginalis. Our data demonstrate that this model displays key features used clinically to diagnose BV, including the presence of sialidase activity and exfoliated epithelial cells with adherent bacteria (reminiscent of clue cells. G. vaginalis was capable of ascending uterine infection, which correlated with the degree of vaginal infection and level of vaginal sialidase activity. The host response to G. vaginalis infection was characterized by robust vaginal epithelial cell exfoliation in the absence of histological inflammation. Our analyses of clinical specimens from women with BV revealed a measureable epithelial exfoliation response compared to women with normal flora, a phenotype that, to our knowledge, is measured here for the first time. The results of this study demonstrate that G. vaginalis is sufficient to cause BV phenotypes and suggest that this organism may contribute to BV etiology and associated complications. This is the first time vaginal infection by a BV associated bacterium in an animal has been shown to parallel the human disease with regard to clinical diagnostic features. Future studies with this model should facilitate investigation of important questions regarding BV etiology, pathogenesis and

  20. Formal Modeling and Verification of Interlocking Systems Featuring Sequential Release

    DEFF Research Database (Denmark)

    Vu, Linh Hong; Haxthausen, Anne Elisabeth; Peleska, Jan

    2015-01-01

    In this paper, we present a method and an associated tool suite for formal verification of the new ETCS level 2 based Danish railway interlocking systems. We have made a generic and reconfigurable model of the system behavior and generic high-level safety properties. This model accommodates seque...

  1. Formal modelling and verification of interlocking systems featuring sequential release

    DEFF Research Database (Denmark)

    Vu, Linh Hong; Haxthausen, Anne Elisabeth; Peleska, Jan

    2016-01-01

    checking (BMC) and inductive reasoning, it is verified that the generated model instance satisfies the generated safety properties. Using this method, we are able to verify the safety properties for model instances corresponding to railway networks of industrial size. Experiments show that BMC is also...

  2. Entropy Error Model of Planar Geometry Features in GIS

    Institute of Scientific and Technical Information of China (English)

    LI Dajun; GUAN Yunlan; GONG Jianya; DU Daosheng

    2003-01-01

    Positional error of line segments is usually described by using "g-band", however, its band width is in relation to the confidence level choice. In fact, given different confidence levels, a series of concentric bands can be obtained. To overcome the effect of confidence level on the error indicator, by introducing the union entropy theory, we propose an entropy error ellipse index of point, then extend it to line segment and polygon,and establish an entropy error band of line segment and an entropy error donut of polygon. The research shows that the entropy error index can be determined uniquely and is not influenced by confidence level, and that they are suitable for positional uncertainty of planar geometry features.

  3. Correlation between clinical and histological features in a pig model of choroidal neovascularization

    DEFF Research Database (Denmark)

    Lassota, Nathan; Kiilgaard, Jens Folke; Prause, Jan Ulrik;

    2006-01-01

    To analyse the histological changes in the retina and the choroid in a pig model of choroidal neovascularization (CNV) and to correlate these findings with fundus photographic and fluorescein angiographic features.......To analyse the histological changes in the retina and the choroid in a pig model of choroidal neovascularization (CNV) and to correlate these findings with fundus photographic and fluorescein angiographic features....

  4. Design models as emergent features: An empirical study in communication and shared mental models in instructional

    Directory of Open Access Journals (Sweden)

    Lucca Botturi

    2006-06-01

    Full Text Available This paper reports the results of an empirical study that investigated the instructional design process of three teams involved in the development of an e-learning unit. The teams declared they were using the same fast-prototyping design and development model, and were composed of the same roles (although with a different number of SMEs. Results indicate that the design and development model actually informs the activities of the group, but that it is interpreted and adapted by the team for the specific project. Thus, the actual practice model of each team can be regarded as an emergent feature. This analysis delivers insights concerning issues about team communication, shared understanding, individual perspectives and the implementation of prescriptive instructional design models.

  5. Thermodynamic modeling of Cu–Ni–Y system coupled with key experiments

    Energy Technology Data Exchange (ETDEWEB)

    Mezbahul-Islam, Mohammad [Department of Mechanical Engineering, Concordia University, 1455 de Maisonneuve Blvd West, Montreal, Quebec, Montreal H3G 1M8 (Canada); Medraj, Mamoun, E-mail: mmedraj@encs.concordia.ca [Department of Mechanical Engineering, Concordia University, 1455 de Maisonneuve Blvd West, Montreal, Quebec, Montreal H3G 1M8 (Canada); Department of Mechanical and Materials Engineering, Masdar Institute of Science and Technology, Masdar City, Abu Dhabi (United Arab Emirates)

    2015-03-01

    A complete thermodynamic description of the Cu–Ni–Y ternary system has been obtained using the CALPHAD (CALculation of PHAse Diagram) approach. Ternary solubility of the third element in the binary compounds in the Cu–Ni–Y system is described using sublattice model within the compound energy formalism (CEF) to take into account the recently reported experimental solubility ranges. The modified quasi-chemical model (MQM) has been used to describe the liquid phase in order to account for the presence of short range ordering properly. To study the melting behavior of the Cu–Ni–Y alloys and to verify the consistency of the thermodynamic model with experimental results, 10 key samples were prepared and the phase transformation temperatures were measured using differential scanning calorimeter (DSC). The microstructural characterization and crystallographic analysis of the alloys were carried out using scanning electron microscopy (SEM) coupled with WDS analysis and X-ray diffraction (XRD). Several vertical sections, liquidus projection and isothermal section at 973 K have been calculated and found to be in good agreement with the current experimental data as well as with the literature. - Highlights: • Thermodynamic modeling of the Cu–Ni–Y system has been performed. • Ternary solubilities of the binary compounds have been reproduced. • Modified quasi-chemical model is used to model the liquid phase. • DSC experiments are performed on selected key alloys. • The calculations are consistent with the experimental results.

  6. Structural and Molecular Modeling Features of P2X Receptors

    Directory of Open Access Journals (Sweden)

    Luiz Anastacio Alves

    2014-03-01

    Full Text Available Currently, adenosine 5'-triphosphate (ATP is recognized as the extracellular messenger that acts through P2 receptors. P2 receptors are divided into two subtypes: P2Y metabotropic receptors and P2X ionotropic receptors, both of which are found in virtually all mammalian cell types studied. Due to the difficulty in studying membrane protein structures by X-ray crystallography or NMR techniques, there is little information about these structures available in the literature. Two structures of the P2X4 receptor in truncated form have been solved by crystallography. Molecular modeling has proven to be an excellent tool for studying ionotropic receptors. Recently, modeling studies carried out on P2X receptors have advanced our knowledge of the P2X receptor structure-function relationships. This review presents a brief history of ion channel structural studies and shows how modeling approaches can be used to address relevant questions about P2X receptors.

  7. Modeling place field activity with hierarchical slow feature analysis

    Directory of Open Access Journals (Sweden)

    Fabian eSchoenfeld

    2015-05-01

    Full Text Available In this paper we present six experimental studies from the literature on hippocampal place cells and replicate their main results in a computational framework based on the principle of slowness. Each of the chosen studies first allows rodents to develop stable place field activity and then examines a distinct property of the established spatial encoding, namely adaptation to cue relocation and removal; directional firing activity in the linear track and open field; and results of morphing and stretching the overall environment. To replicate these studies we employ a hierarchical Slow Feature Analysis (SFA network. SFA is an unsupervised learning algorithm extracting slowly varying information from a given stream of data, and hierarchical application of SFA allows for high dimensional input such as visual images to be processed efficiently and in a biologically plausible fashion. Training data for the network is produced in ratlab, a free basic graphics engine designed to quickly set up a wide range of 3D environments mimicking real life experimental studies, simulate a foraging rodent while recording its visual input, and training & sampling a hierarchical SFA network.

  8. Collisional features in a model of a planetary ring

    NARCIS (Netherlands)

    Lawney, Brian; Jenkins, J.T; Burns, J.A.

    2012-01-01

    Images taken by the Cassini spacecraft display numerous “propellers”, telltale disturbances detected in Saturn’s outer A ring. In conventionally accepted models (Seiß, M., Spahn, F., Sremčević, M., Salo, H. [2005]. Geophys. Res. Lett. 32, L11205; Lewis, M., Stewart, G. [2009]. Icarus 199, 387–412),

  9. Molecular modeling of mechanosensory ion channel structural and functional features.

    Science.gov (United States)

    Gessmann, Renate; Kourtis, Nikos; Petratos, Kyriacos; Tavernarakis, Nektarios

    2010-09-16

    The DEG/ENaC (Degenerin/Epithelial Sodium Channel) protein family comprises related ion channel subunits from all metazoans, including humans. Members of this protein family play roles in several important biological processes such as transduction of mechanical stimuli, sodium re-absorption and blood pressure regulation. Several blocks of amino acid sequence are conserved in DEG/ENaC proteins, but structure/function relations in this channel class are poorly understood. Given the considerable experimental limitations associated with the crystallization of integral membrane proteins, knowledge-based modeling is often the only route towards obtaining reliable structural information. To gain insight into the structural characteristics of DEG/ENaC ion channels, we derived three-dimensional models of MEC-4 and UNC-8, based on the available crystal structures of ASIC1 (Acid Sensing Ion Channel 1). MEC-4 and UNC-8 are two DEG/ENaC family members involved in mechanosensation and proprioception respectively, in the nematode Caenorhabditis elegans. We used these models to examine the structural effects of specific mutations that alter channel function in vivo. The trimeric MEC-4 model provides insight into the mechanism by which gain-of-function mutations cause structural alterations that result in increased channel permeability, which trigger cell degeneration. Our analysis provides an introductory framework to further investigate the multimeric organization of the DEG/ENaC ion channel complex.

  10. Molecular modeling of mechanosensory ion channel structural and functional features.

    Directory of Open Access Journals (Sweden)

    Renate Gessmann

    Full Text Available The DEG/ENaC (Degenerin/Epithelial Sodium Channel protein family comprises related ion channel subunits from all metazoans, including humans. Members of this protein family play roles in several important biological processes such as transduction of mechanical stimuli, sodium re-absorption and blood pressure regulation. Several blocks of amino acid sequence are conserved in DEG/ENaC proteins, but structure/function relations in this channel class are poorly understood. Given the considerable experimental limitations associated with the crystallization of integral membrane proteins, knowledge-based modeling is often the only route towards obtaining reliable structural information. To gain insight into the structural characteristics of DEG/ENaC ion channels, we derived three-dimensional models of MEC-4 and UNC-8, based on the available crystal structures of ASIC1 (Acid Sensing Ion Channel 1. MEC-4 and UNC-8 are two DEG/ENaC family members involved in mechanosensation and proprioception respectively, in the nematode Caenorhabditis elegans. We used these models to examine the structural effects of specific mutations that alter channel function in vivo. The trimeric MEC-4 model provides insight into the mechanism by which gain-of-function mutations cause structural alterations that result in increased channel permeability, which trigger cell degeneration. Our analysis provides an introductory framework to further investigate the multimeric organization of the DEG/ENaC ion channel complex.

  11. TU-CD-BRB-01: Normal Lung CT Texture Features Improve Predictive Models for Radiation Pneumonitis

    Energy Technology Data Exchange (ETDEWEB)

    Krafft, S [The University of Texas MD Anderson Cancer Center, Houston, TX (United States); The University of Texas Graduate School of Biomedical Sciences, Houston, TX (United States); Briere, T; Court, L; Martel, M [The University of Texas MD Anderson Cancer Center, Houston, TX (United States)

    2015-06-15

    Purpose: Existing normal tissue complication probability (NTCP) models for radiation pneumonitis (RP) traditionally rely on dosimetric and clinical data but are limited in terms of performance and generalizability. Extraction of pre-treatment image features provides a potential new category of data that can improve NTCP models for RP. We consider quantitative measures of total lung CT intensity and texture in a framework for prediction of RP. Methods: Available clinical and dosimetric data was collected for 198 NSCLC patients treated with definitive radiotherapy. Intensity- and texture-based image features were extracted from the T50 phase of the 4D-CT acquired for treatment planning. A total of 3888 features (15 clinical, 175 dosimetric, and 3698 image features) were gathered and considered candidate predictors for modeling of RP grade≥3. A baseline logistic regression model with mean lung dose (MLD) was first considered. Additionally, a least absolute shrinkage and selection operator (LASSO) logistic regression was applied to the set of clinical and dosimetric features, and subsequently to the full set of clinical, dosimetric, and image features. Model performance was assessed by comparing area under the curve (AUC). Results: A simple logistic fit of MLD was an inadequate model of the data (AUC∼0.5). Including clinical and dosimetric parameters within the framework of the LASSO resulted in improved performance (AUC=0.648). Analysis of the full cohort of clinical, dosimetric, and image features provided further and significant improvement in model performance (AUC=0.727). Conclusions: To achieve significant gains in predictive modeling of RP, new categories of data should be considered in addition to clinical and dosimetric features. We have successfully incorporated CT image features into a framework for modeling RP and have demonstrated improved predictive performance. Validation and further investigation of CT image features in the context of RP NTCP

  12. Evaluation of various feature extraction methods for landmine detection using hidden Markov models

    Science.gov (United States)

    Hamdi, Anis; Frigui, Hichem

    2012-06-01

    Hidden Markov Models (HMM) have proved to be eective for detecting buried land mines using data collected by a moving-vehicle-mounted ground penetrating radar (GPR). The general framework for a HMM-based landmine detector consists of building a HMM model for mine signatures and a HMM model for clutter signatures. A test alarm is assigned a condence proportional to the probability of that alarm being generated by the mine model and inversely proportional to its probability in the clutter model. The HMM models are built based on features extracted from GPR training signatures. These features are expected to capture the salient properties of the 3-dimensional alarms in a compact representation. The baseline HMM framework for landmine detection is based on gradient features. It models the time varying behavior of GPR signals, encoded using edge direction information, to compute the likelihood that a sequence of measurements is consistent with a buried landmine. In particular, the HMM mine models learns the hyperbolic shape associated with the signature of a buried mine by three states that correspond to the succession of an increasing edge, a at edge, and a decreasing edge. Recently, for the same application, other features have been used with dierent classiers. In particular, the Edge Histogram Descriptor (EHD) has been used within a K-nearest neighbor classier. Another descriptor is based on Gabor features and has been used within a discrete HMM classier. A third feature, that is closely related to the EHD, is the Bar histogram feature. This feature has been used within a Neural Networks classier for handwritten word recognition. In this paper, we propose an evaluation of the HMM based landmine detection framework with several feature extraction techniques. We adapt and evaluate the EHD, Gabor, Bar, and baseline gradient feature extraction methods. We compare the performance of these features using a large and diverse GPR data collection.

  13. Superfield Approach to Nilpotent Symmetries of the Freedman-Townsend Model: Novel Features

    Science.gov (United States)

    Malik, R. P.

    2012-09-01

    We perform the Becchi-Rouet-Stora-Tyutin (BRST) analysis of the Freedman-Townsend (FT) model of topologically massive non-Abelian theory by exploiting its (1-form) Yang-Mills (YM) gauge transformations to show the existence of some novel features that are totally different from the results obtained in such a kind of consideration carried out for the dynamical non-Abelian 2-form theory. We tap here the potential and power of the augmented version of Bonora-Tonin's superfield approach to BRST formalism to derive the full set of off-shell nilpotent and absolutely anticommuting (anti-)BRST symmetry transformations where, in addition to the horizontality condition (HC), we are theoretically compelled to exploit the appropriate gauge-invariant restrictions (GIRs) on the (super)fields for the derivation of the appropriate symmetry transformations for all the relevant fields. We compare our key results with that of the other such attempt for the discussion of the present model within the framework of BRST formalism.

  14. The Key Variables for the Development of a Care Model for Stroke

    Directory of Open Access Journals (Sweden)

    Stavrianopoulos T.

    2011-10-01

    Full Text Available Introduction Stroke is a major cause of death, threatened and reduced health, and a patient’s dependence on support after the acute phase. The increase in knowledge of neurological recovery after a stroke has led to new treatment strategies, where the importance of the physical environment and rehabilitation is on par with the importance of the medical treatment. It is crucial that the whole stroke team is involved in assessing, planning, and evaluating the care provided. Aim The presentation of the variables that are needed for the development of a general model of care for stroke. Material and Methods Method was used is to search electronic databases (MEDLINE, CINAHL for a review of international literature to 2009 and became selection of books, articles and studies from libraries. The search was done the December of 2010. Results The key variables to develop a model of care are: the care planning, the team culture, the care culture, the professional knowledge, the quality of space, the observation and assessment, the patient participation and the inter-professional teamwork. Conclusions The model presents stroke care as a complex system, with many feedback relationships between key variables for care. The development of the model, with the contributions of existing literature, enables further tests in practice and improvements in stroke care and further refinement of variables which include the model of care.

  15. Pointing, looking at, and pressing keys: A diffusion model account of response modality.

    Science.gov (United States)

    Gomez, Pablo; Ratcliff, Roger; Childers, Russ

    2015-12-01

    Accumulation of evidence models of perceptual decision making have been able to account for data from a wide range of domains at an impressive level of precision. In particular, Ratcliff's (1978) diffusion model has been used across many different 2-choice tasks in which the response is executed via a key-press. In this article, we present 2 experiments in which we used a letter-discrimination task exploring 3 central aspects of a 2-choice task: the discriminability of the stimulus, the modality of the response execution (eye movement, key pressing, and pointing on a touchscreen), and the mapping of the response areas for the eye movement and the touchscreen conditions (consistent vs. inconsistent). We fitted the diffusion model to the data from these experiments and examined the behavior of the model's parameters. Fits of the model were consistent with the hypothesis that the same decision mechanism is used in the task with 3 different response methods. Drift rates are affected by the duration of the presentation of the stimulus while the response execution time changed as a function of the response modality.

  16. PrEP for key populations in combination HIV prevention in Nairobi: a mathematical modelling study.

    Science.gov (United States)

    Cremin, Ide; McKinnon, Lyle; Kimani, Joshua; Cherutich, Peter; Gakii, Gloria; Muriuki, Festus; Kripke, Katharine; Hecht, Robert; Kiragu, Michael; Smith, Jennifer; Hinsley, Wes; Gelmon, Lawrence; Hallett, Timothy B

    2017-05-01

    The HIV epidemic in the population of Nairobi as a whole is in decline, but a concentrated sub-epidemic persists in key populations. We aimed to identify an optimal portfolio of interventions to reduce HIV incidence for a given budget and to identify the circumstances in which pre-exposure prophylaxis (PrEP) could be used in Nairobi, Kenya. A mathematical model was developed to represent HIV transmission in specific key populations (female sex workers, male sex workers, and men who have sex with men [MSM]) and among the wider population of Nairobi. The scale-up of existing interventions (condom promotion, antiretroviral therapy, and male circumcision) for key populations and the wider population as have occurred in Nairobi is represented. The model includes a detailed representation of a PrEP intervention and is calibrated to prevalence and incidence estimates specific to key populations and the wider population. In the context of a declining epidemic overall but with a large sub-epidemic in MSM and male sex workers, an optimal prevention portfolio for Nairobi should focus on condom promotion for male sex workers and MSM in particular, followed by improved antiretroviral therapy retention, earlier antiretroviral therapy, and male circumcision as the budget allows. PrEP for male sex workers could enter an optimal portfolio at similar levels of spending to when earlier antiretroviral therapy is included; however, PrEP for MSM and female sex workers would be included only at much higher budgets. If PrEP for male sex workers cost as much as US$500, average annual spending on the interventions modelled would need to be less than $3·27 million for PrEP for male sex workers to be excluded from an optimal portfolio. Estimated costs per infection averted when providing PrEP to all female sex workers regardless of their risk of infection, and to high-risk female sex workers only, are $65 160 (95% credible interval [CrI] $43 520-$90 250) and $10 920 (95% CrI $4700

  17. Crystalline structure of accretion disks: features of a global model.

    Science.gov (United States)

    Montani, Giovanni; Benini, Riccardo

    2011-08-01

    In this paper, we develop the analysis of a two-dimensional magnetohydrodynamical configuration for an axially symmetric and rotating plasma (embedded in a dipolelike magnetic field), modeling the structure of a thin accretion disk around a compact astrophysical object. Our study investigates the global profile of the disk plasma, in order to fix the conditions for the existence of a crystalline morphology and ring sequence, as outlined by the local analysis pursued in Coppi [Phys. Plasmas 12, 7302 (2005)] and Coppi and Rousseau [Astrophys. J. 641, 458 (2006)]. In the linear regime, when the electromagnetic back-reaction of the plasma is small enough, we show the existence of an oscillating radial behavior for the flux surface function, which very closely resembles the one outlined in the local model, apart from a radial modulation of the amplitude. In the opposite limit, corresponding to a dominant back-reaction in the magnetic structure over the field of central object, we can recognize the existence of a ringlike decomposition of the disk, according to the same modulation of the magnetic flux surface, and a smoother radial decay of the disk density, with respect to the linear case. In this extreme nonlinear regime, the global model seems to predict a configuration very close to that of the local analysis, but here the thermostatic pressure, crucial for the equilibrium setting, is also radially modulated. Among the conditions requested for the validity of such a global model, the confinement of the radial coordinate within a given value sensitive to the disk temperature and to the mass of the central objet, stands; however, this condition corresponds to dealing with a thin disk configuration.

  18. Using Feature Modelling and Automations to Select among Cloud Solutions

    OpenAIRE

    Quinton, Clément; Duchien, Laurence; Heymans, patrick; Mouton, Stéphane; Charlier, Etienne

    2012-01-01

    International audience; Cloud computing is a major trend in distributed computing environments. Resources are accessed on demand by customers and are delivered as services by cloud providers in a pay-per-use model. Companies provide their applications as services and rely on cloud providers to provision, host and manage such applications on top of their infrastructure. However, the wide range of cloud solutions and the lack of knowledge in this domain is a real problem for companies when faci...

  19. UNIVERSITY INNOVATION INFRASTRUCTURE MODEL AS A KEY PART OF A TERRITORAL CLUST

    Directory of Open Access Journals (Sweden)

    Nataliya P. Ivashchenko

    2015-01-01

    Full Text Available Over the recent decades there have been increasing efforts by developing countries to reduce the economic gap between developed and developing countries. Asian and Northern European countries demonstrate good progress in these areas.Sweden,Denmark,Chinashow stable high economic indicators that have been achieved by targeted government programs. These programs were aimed at creating a new type of economy based on knowledge and new technologies. Given the success of these countries, a number of developing countries, whose economies are dependent on resources, today, are looking to repeat their way; those countries areRussia,Indonesia,BrazilandChile. The modernization of the economy and the formation of innovative economy are key objectives of the state policies of these countries. The research by leading economists and scientists led to the conclusion that the regional level of national economy plays a key role in formation of knowledgebase economy, which indicates the need to differentiate the innovation policy of the state depending on the economy parameters of each region. This paper presents a model of the first stage of the formation of the entrepreneurialuniversityUniversityinnovation infrastructure model, which is a key part of a territoral cluster. The article consists of five parts. The first part covers the analysis of the two main models of regional development: clustering theory and Triple Helix. This section describes a positive result, which is achieved by using these models simultaneously. The second part of the article shows the importance and the role of the entrepreneurial university in the formation of innovative clusters. It will be explained how and under what conditions this formation is achieved. The third part of this paper will present University innovation infrastructure model. The fourth part will examine the practical first steps to create a cluster "Vorob’evi Gori" on the basis of theMoscowStateUniversity. The fifth

  20. Feature learning for a hidden Markov model approach to landmine detection

    Science.gov (United States)

    Zhang, Xuping; Gader, Paul; Frigui, Hichem

    2007-04-01

    Hidden Markov Models (HMMs) are useful tools for landmine detection and discrimination using Ground Penetrating Radar (GPR). The performance of HMMs, as well as other feature-based methods, depends not only on the design of the classifier but on the features. Traditionally, algorithms for learning the parameters of classifiers have been intensely investigated while algorithms for learning parameters of the feature extraction process have been much less intensely investigated. In this paper, we describe experiments for learning feature extraction and classification parameters simultaneously in the context of using hidden Markov models for landmine detection.

  1. Key role of local regulation in chemosensing revealed by a new molecular interaction-based modeling method.

    Directory of Open Access Journals (Sweden)

    Martin Meier-Schellersheim

    2006-07-01

    Full Text Available The signaling network underlying eukaryotic chemosensing is a complex combination of receptor-mediated transmembrane signals, lipid modifications, protein translocations, and differential activation/deactivation of membrane-bound and cytosolic components. As such, it provides particularly interesting challenges for a combined computational and experimental analysis. We developed a novel detailed molecular signaling model that, when used to simulate the response to the attractant cyclic adenosine monophosphate (cAMP, made nontrivial predictions about Dictyostelium chemosensing. These predictions, including the unexpected existence of spatially asymmetrical, multiphasic, cyclic adenosine monophosphate-induced PTEN translocation and phosphatidylinositol-(3,4,5P3 generation, were experimentally verified by quantitative single-cell microscopy leading us to propose significant modifications to the current standard model for chemoattractant-induced biochemical polarization in this organism. Key to this successful modeling effort was the use of "Simmune," a new software package that supports the facile development and testing of detailed computational representations of cellular behavior. An intuitive interface allows user definition of complex signaling networks based on the definition of specific molecular binding site interactions and the subcellular localization of molecules. It automatically translates such inputs into spatially resolved simulations and dynamic graphical representations of the resulting signaling network that can be explored in a manner that closely parallels wet lab experimental procedures. These features of Simmune were critical to the model development and analysis presented here and are likely to be useful in the computational investigation of many aspects of cell biology.

  2. Key elements for implementing comprehensive health care models for persons with HIV: a stakeholder analysis.

    Science.gov (United States)

    Melchior, L A; Panter, A T; Larson, T A; Meredith, K L; Richardson-Nassif, K; Huba, G J

    2000-09-01

    A semistructured interview was conducted with 69 stakeholders in three university-based health care projects that were funded to provide an integrated continuum of care for persons living with HIV/AIDS. Data from the key informant interviews yielded composite indicators of familiarity with the service model, the importance of the elements in the service model, and the perceived quality of services provided by these innovative HIV service demonstration projects. Ratings of service quality were related to ratings of the respondent's knowledge of the service demonstration project, the importance of the various elements in the service continuum, and several indicators of stakeholder characteristics using the data modeling method of Exhaustive CHAID (Chi-squared Automatic Interaction Detector). The groups of stakeholders most likely to give the highest quality or success ratings for these projects are identified. The implications of these findings for developing collaborative and comprehensive service models for persons with HIV/AIDS are discussed.

  3. Modeling the pairwise key distribution scheme in the presence of unreliable links

    CERN Document Server

    Yagan, Osman

    2011-01-01

    We investigate the secure connectivity of wireless sensor networks under the pairwise key distribution scheme of Chan et al.. Unlike recent work which was carried out under the assumption of full visibility, here we assume a (simplified) communication model where unreliable wireless links are represented as on/off channels. We present conditions on how to scale the model parameters so that the network i) has no secure node which is isolated and ii) is securely connected, both with high probability when the number of sensor nodes becomes large. The results are given in the form of zero-one laws, and exhibit significant differences with corresponding results in the full visibility case. Through simulations these zero-one laws are shown to be valid also under a more realistic communication model, i.e., the disk model.

  4. Hoyle state and rotational features in Carbon-12 within a no-core shell-model framework

    Energy Technology Data Exchange (ETDEWEB)

    Dreyfuss, Alison C., E-mail: adreyf1@lsu.edu [Keene State College, Keene, NH 03435 (United States); Launey, Kristina D.; Dytrych, Tomáš; Draayer, Jerry P. [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, LA 70803 (United States); Bahri, Chairul [Department of Physics, University of Notre Dame, Notre Dame, IN 46556-5670 (United States)

    2013-12-18

    By using only a fraction of the model space extended beyond current no-core shell-model limits and a many-nucleon interaction with a single parameter, we gain additional insight within a symmetry-guided shell-model framework, into the many-body dynamics that gives rise to the ground state rotational band together with phenomena tied to alpha-clustering substructures in the low-lying states in {sup 12}C, and in particular, the challenging Hoyle state and its first 2{sup +} and 4{sup +} excitations. For these states, we offer a novel perspective emerging out of no-core shell-model considerations, including a discussion of associated nuclear deformation and matter radii. This, in turn, provides guidance for ab initio shell models by informing key features of nuclear structure and the interaction.

  5. Modeling of the ground-to-SSFMB link networking features using SPW

    Science.gov (United States)

    Watson, John C.

    1993-01-01

    This report describes the modeling and simulation of the networking features of the ground-to-Space Station Freedom manned base (SSFMB) link using COMDISCO signal processing work-system (SPW). The networking features modeled include the implementation of Consultative Committee for Space Data Systems (CCSDS) protocols in the multiplexing of digitized audio and core data into virtual channel data units (VCDU's) in the control center complex and the demultiplexing of VCDU's in the onboard baseband signal processor. The emphasis of this work has been placed on techniques for modeling the CCSDS networking features using SPW. The objectives for developing the SPW models are to test the suitability of SPW for modeling networking features and to develop SPW simulation models of the control center complex and space station baseband signal processor for use in end-to-end testing of the ground-to-SSFMB S-band single access forward (SSAF) link.

  6. Crystalline Structure of Accretion Disks: Features of the Global Model

    CERN Document Server

    Montani, Giovanni

    2012-01-01

    In this paper, we develop the analysis of a two-dimensional magnetohydrodynamical configuration for an axially symmetric and rotating plasma (embedded in a dipole like magnetic field), modeling the structure of a thin accretion disk around a compact astrophysical object. Our study investigates the global profile of the disk plasma, in order to fix the conditions for the existence of a crystalline morphology and ring sequence, as outlined by the local analysis pursued in [1, 2]. In the linear regime, when the electromagnetic back-reaction of the plasma is small enough, we show the existence of an oscillating radial behavior for the flux surface function which very closely resembles the one outlined in the local model, apart from a radial modulation of the amplitude. In the opposite limit, corresponding to a dominant back-reaction in the magnetic structure over the field of central object, we can recognize the existence of a ring-like decomposition of the disk, according to the same modulation of the magnetic f...

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

    Science.gov (United States)

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

    2017-10-01

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

  8. Modeling halotropism: a key role for root tip architecture and reflux loop remodeling in redistributing auxin.

    Science.gov (United States)

    van den Berg, Thea; Korver, Ruud A; Testerink, Christa; Ten Tusscher, Kirsten H W J

    2016-09-15

    A key characteristic of plant development is its plasticity in response to various and dynamically changing environmental conditions. Tropisms contribute to this flexibility by allowing plant organs to grow from or towards environmental cues. Halotropism is a recently described tropism in which plant roots bend away from salt. During halotropism, as in most other tropisms, directional growth is generated through an asymmetric auxin distribution that generates differences in growth rate and hence induces bending. Here, we develop a detailed model of auxin transport in the Arabidopsis root tip and combine this with experiments to investigate the processes generating auxin asymmetry during halotropism. Our model points to the key role of root tip architecture in allowing the decrease in PIN2 at the salt-exposed side of the root to result in a re-routing of auxin to the opposite side. In addition, our model demonstrates how feedback of auxin on the auxin transporter AUX1 amplifies this auxin asymmetry, while a salt-induced transient increase in PIN1 levels increases the speed at which this occurs. Using AUX1-GFP imaging and pin1 mutants, we experimentally confirmed these model predictions, thus expanding our knowledge of the cellular basis of halotropism.

  9. [A model for evaluation of key measures for control of chikungunya fever outbreak in China].

    Science.gov (United States)

    Zhao, Jin; Liu, Ruchun; Chen, Shuilian; Chen, Tianmu

    2015-11-01

    To analyze the transmission pattern of Chikungunya (CHIK) fever in community and evaluate the effectiveness of mosquito control, case isolation and other key control measures by using ordinary differential equation (ODE) model. According to natural history of CHIK, an ODE model for the epidemiological analysis of CHIK outbreak was established. The key parameters of the model were obtained by fitting the model with reported outbreak data of the first CHIK outbreak in China. Then the outbreak characteristics without intervention, the effectiveness of mosquito control and case isolation were simulated. Without intervention, an imported case would cause an outbreak in a community with population of 11 000, and cumulative case number would exceed 941 when the total attack rate was 8.55%. The results of our simulation revealed that the effectiveness of case isolation was not perfect enough when it was implemented alone. Although the number of cases could be decreased by case isolation, the duration of outbreak would not be shortened. Differently, the effectiveness of mosquito control was remarkable. In addition, the earlier the measure was implemented, the better the effectiveness would be. The effectiveness of mosquito control plus case isolation was same with mosquito control. To control a CHIK outbreak, mosquito control is the most recommended measures. However, case isolation is also necessary as the supplementation of mosquito control.

  10. Effective, clinically feasible and sustainable: Key design features of psycho-educational and supportive care interventions to promote individualised self-management in cancer care.

    Science.gov (United States)

    Schofield, Penelope; Chambers, Suzanne

    2015-05-01

    As the global burden of cancer increases healthcare services will face increasing challenges in meet the complex needs of these patients, their families and the communities in which they live. This raises the question of how to meet patient need where direct clinical contact may be constrained or not readily available. Patients and families require resources and skills to manage their illness outside of the hospital setting within their own communities. To propose a framework for the development and delivery of psycho-educational and supportive care interventions drawing on theoretical principles of behaviour change and evidence-based interventions, and based on extensive experience in developing and testing complex interventions in oncology. At the core of this intervention framework are considerations of efficiency: interventions are designed to cater for individuals' unique needs; to place minimal demands on the health system infrastructure and to be rapidly disseminated into usual care if successful. There are seven key features: 1) Targeting cancer type and stage; 2) Tailoring to unique individual needs; 3) Promotion of patient self-management of their disease and treatment side effects; 4) Efficient delivery of the intervention; 5) Training and adherence to protocol; 6) Ensuring the intervention is evidence-based; 7) Confirming stakeholder acceptability of the intervention. A case study of a randomised controlled trial which tested psycho-educational oncology interventions using this framework is presented. These interventions were designed to cater for individuals' unique needs and promote self-management while placing minimal demands on the acute health care setting. Innovative ways to realise the potentially major impact that psycho-educational and supportive care interventions can have on psychological morbidity, coping, symptoms and quality of life in serious and chronic illness are needed. This framework, which is driven by theory, evidence, and

  11. Structural characterization of native autoinducing peptides and abiotic analogues reveals key features essential for activation and inhibition of an AgrC quorum sensing receptor in Staphylococcus aureus.

    Science.gov (United States)

    Tal-Gan, Yftah; Ivancic, Monika; Cornilescu, Gabriel; Cornilescu, Claudia C; Blackwell, Helen E

    2013-12-11

    Staphylococcus aureus is a major human pathogen that uses quorum sensing (QS) to control virulence. Its QS system is regulated by macrocyclic peptide signals (or autoinducing peptides (AIPs)) and their cognate transmembrane receptors (AgrCs). Four different specificity groups of S. aureus have been identified to date (groups I-IV), each of which uses a different AIP:AgrC pair. Non-native ligands capable of intercepting AIP:AgrC binding, and thereby QS, in S. aureus have attracted considerable interest as chemical tools to study QS pathways and as possible antivirulence strategies for the treatment of infection. We recently reported a set of analogues of the group-III AIP that are capable of strongly modulating the activity of all four AgrC receptors. Critical to the further development of such ligands is a detailed understanding of the structural features of both native AIPs and non-native analogues that are essential for activity. Herein, we report the first three-dimensional structural analysis of the known native AIP signals (AIPs-I-IV) and several AIP-III analogues with varied biological activities using NMR spectroscopy. Integration of these NMR studies with the known agonism and antagonism profiles of these peptides in AgrC-III revealed two key structural elements that control AIP-III (and non-native peptide) activity: (1) a tri-residue hydrophobic "knob" essential for both activation and inhibition and (2) a fourth anchor point on the exocyclic tail needed for receptor activation. These results provide strong structural support for a mechanism of AIP-mediated AgrC activation and inhibition in S. aureus , and should facilitate the design of new AgrC ligands with enhanced activities (as agonists or antagonists) and simplified chemical structures.

  12. Coupling process-based models and plant architectural models: A key issue for simulating crop production

    NARCIS (Netherlands)

    Reffye, de P.; Heuvelink, E.; Guo, Y.; Hu, B.G.; Zhang, B.G.

    2009-01-01

    Process-Based Models (PBMs) can successfully predict the impact of environmental factors (temperature, light, CO2, water and nutrients) on crop growth and yield. These models are used widely for yield prediction and optimization of water and nutrient supplies. Nevertheless, PBMs do not consider plan

  13. Toward a model for lexical access based on acoustic landmarks and distinctive features

    Science.gov (United States)

    Stevens, Kenneth N.

    2002-04-01

    This article describes a model in which the acoustic speech signal is processed to yield a discrete representation of the speech stream in terms of a sequence of segments, each of which is described by a set (or bundle) of binary distinctive features. These distinctive features specify the phonemic contrasts that are used in the language, such that a change in the value of a feature can potentially generate a new word. This model is a part of a more general model that derives a word sequence from this feature representation, the words being represented in a lexicon by sequences of feature bundles. The processing of the signal proceeds in three steps: (1) Detection of peaks, valleys, and discontinuities in particular frequency ranges of the signal leads to identification of acoustic landmarks. The type of landmark provides evidence for a subset of distinctive features called articulator-free features (e.g., [vowel], [consonant], [continuant]). (2) Acoustic parameters are derived from the signal near the landmarks to provide evidence for the actions of particular articulators, and acoustic cues are extracted by sampling selected attributes of these parameters in these regions. The selection of cues that are extracted depends on the type of landmark and on the environment in which it occurs. (3) The cues obtained in step (2) are combined, taking context into account, to provide estimates of ``articulator-bound'' features associated with each landmark (e.g., [lips], [high], [nasal]). These articulator-bound features, combined with the articulator-free features in (1), constitute the sequence of feature bundles that forms the output of the model. Examples of cues that are used, and justification for this selection, are given, as well as examples of the process of inferring the underlying features for a segment when there is variability in the signal due to enhancement gestures (recruited by a speaker to make a contrast more salient) or due to overlap of gestures from

  14. Fin Buffeting Features of an Early F-22 Model

    Science.gov (United States)

    Moses, Robert W.; Huttsell, Lawrence

    2000-01-01

    Fin buffeting is an aeroelastic phenomenon encountered by high performance aircraft, especially those with twin vertical tails that must operate at high angles of attack. This buffeting is a concern from fatigue and inspection points of view. To date, the buffet (unsteady pressures) and buffeting (structural response) characteristics of the F-15 and F/A-18 fins have been studied extensively using flow visualization, flow velocity measurements, pressure transducers, and response gages. By means of windtunnel and flight tests of the F-15 and F/A-18, this phenomenon is well studied to the point that buffet loads can be estimated and fatigue life can he increased by structural enhancements to these airframes. However, prior to the present research, data was not available outside the F-22 program regarding fin buffeting on the F-22 configuration. During a test in the Langley Transonic Dynamics Tunnel, flow visualization and unsteady fin surface pressures were recorded for a 13.3%-scale F-22 model at high angles of attack for the purpose of comparing with results available for similar aircraft configurations. Details of this test and fin buffeting are presented herein.

  15. Gravitational wave background from Standard Model physics: qualitative features

    Energy Technology Data Exchange (ETDEWEB)

    Ghiglieri, J.; Laine, M. [Institute for Theoretical Physics, Albert Einstein Center, University of Bern,Sidlerstrasse 5, CH-3012 Bern (Switzerland)

    2015-07-16

    Because of physical processes ranging from microscopic particle collisions to macroscopic hydrodynamic fluctuations, any plasma in thermal equilibrium emits gravitational waves. For the largest wavelengths the emission rate is proportional to the shear viscosity of the plasma. In the Standard Model at T>160 GeV, the shear viscosity is dominated by the most weakly interacting particles, right-handed leptons, and is relatively large. We estimate the order of magnitude of the corresponding spectrum of gravitational waves. Even though at small frequencies (corresponding to the sub-Hz range relevant for planned observatories such as eLISA) this background is tiny compared with that from non-equilibrium sources, the total energy carried by the high-frequency part of the spectrum is non-negligible if the production continues for a long time. We suggest that this may constrain (weakly) the highest temperature of the radiation epoch. Observing the high-frequency part directly sets a very ambitious goal for future generations of GHz-range detectors.

  16. Gravitational wave background from Standard Model physics: Qualitative features

    CERN Document Server

    Ghiglieri, J

    2015-01-01

    Because of physical processes ranging from microscopic particle collisions to macroscopic hydrodynamic fluctuations, any plasma in thermal equilibrium emits gravitational waves. For the largest wavelengths the emission rate is proportional to the shear viscosity of the plasma. In the Standard Model at T > 160 GeV, the shear viscosity is dominated by the most weakly interacting particles, right-handed leptons, and is relatively large. We estimate the order of magnitude of the corresponding spectrum of gravitational waves. Even though at small frequencies (corresponding to the sub-Hz range relevant for planned observatories such as eLISA) this background is tiny compared with that from non-equilibrium sources, the total energy carried by the high-frequency part of the spectrum is non-negligible if the production continues for a long time. We suggest that this may constrain (weakly) the highest temperature of the radiation epoch. Observing the high-frequency part directly sets a very ambitious goal for future ge...

  17. Modeling succession of key resource-harvesting traits of mixotrophic plankton

    DEFF Research Database (Denmark)

    Berge, Terje; Chakraborty, Subhendu; Hansen, Per Juel

    2017-01-01

    -based model for mixotrophy with three key resource-harvesting traits: photosynthesis, phagotrophy and inorganic nutrient uptake, which predicts the trophic strategy of species throughout the seasonal cycle. Assuming that simple carbohydrates from photosynthesis fuel respiration, and feeding primarily provides...... in the spring and increased phagotrophy during the summer, reflecting general seasonal succession patterns of temperate waters. Our trait-based model presents a simple and general approach for the inclusion of mixotrophy, succession and evolution in ecosystem models.The ISME Journal advance online publication......Unicellular eukaryotes make up the base of the ocean food web and exist as a continuum in trophic strategy from pure heterotrophy (phagotrophic zooplankton) to pure photoautotrophy (‘phytoplankton’), with a dominance of mixotrophic organisms combining both strategies. Here we formulate a trait...

  18. Impact of SLA assimilation in the Sicily Channel Regional Model: model skills and mesoscale features

    Directory of Open Access Journals (Sweden)

    A. Olita

    2012-07-01

    Full Text Available The impact of the assimilation of MyOcean sea level anomalies along-track data on the analyses of the Sicily Channel Regional Model was studied. The numerical model has a resolution of 1/32° degrees and is capable to reproduce mesoscale and sub-mesoscale features. The impact of the SLA assimilation is studied by comparing a simulation (SIM, which does not assimilate data with an analysis (AN assimilating SLA along-track multi-mission data produced in the framework of MyOcean project. The quality of the analysis was evaluated by computing RMSE of the misfits between analysis background and observations (sea level before assimilation. A qualitative evaluation of the ability of the analyses to reproduce mesoscale structures is accomplished by comparing model results with ocean colour and SST satellite data, able to detect such features on the ocean surface. CTD profiles allowed to evaluate the impact of the SLA assimilation along the water column. We found a significant improvement for AN solution in terms of SLA RMSE with respect to SIM (the averaged RMSE of AN SLA misfits over 2 years is about 0.5 cm smaller than SIM. Comparison with CTD data shows a questionable improvement produced by the assimilation process in terms of vertical features: AN is better in temperature while for salinity it gets worse than SIM at the surface. This suggests that a better a-priori description of the vertical error covariances would be desirable. The qualitative comparison of simulation and analyses with synoptic satellite independent data proves that SLA assimilation allows to correctly reproduce some dynamical features (above all the circulation in the Ionian portion of the domain and mesoscale structures otherwise misplaced or neglected by SIM. Such mesoscale changes also infer that the eddy momentum fluxes (i.e. Reynolds stresses show major changes in the Ionian area. Changes in Reynolds stresses reflect a different pumping of eastward momentum from the eddy to

  19. Key Technology Research on Open Architecture for The Sharing of Heterogeneous Geographic Analysis Models

    Science.gov (United States)

    Yue, S. S.; Wen, Y. N.; Lv, G. N.; Hu, D.

    2013-10-01

    In recent years, the increasing development of cloud computing technologies laid critical foundation for efficiently solving complicated geographic issues. However, it is still difficult to realize the cooperative operation of massive heterogeneous geographical models. Traditional cloud architecture is apt to provide centralized solution to end users, while all the required resources are often offered by large enterprises or special agencies. Thus, it's a closed framework from the perspective of resource utilization. Solving comprehensive geographic issues requires integrating multifarious heterogeneous geographical models and data. In this case, an open computing platform is in need, with which the model owners can package and deploy their models into cloud conveniently, while model users can search, access and utilize those models with cloud facility. Based on this concept, the open cloud service strategies for the sharing of heterogeneous geographic analysis models is studied in this article. The key technology: unified cloud interface strategy, sharing platform based on cloud service, and computing platform based on cloud service are discussed in detail, and related experiments are conducted for further verification.

  20. Key Issues in Modeling of Complex 3D Structures from Video Sequences

    Directory of Open Access Journals (Sweden)

    Shengyong Chen

    2012-01-01

    Full Text Available Construction of three-dimensional structures from video sequences has wide applications for intelligent video analysis. This paper summarizes the key issues of the theory and surveys the recent advances in the state of the art. Reconstruction of a scene object from video sequences often takes the basic principle of structure from motion with an uncalibrated camera. This paper lists the typical strategies and summarizes the typical solutions or algorithms for modeling of complex three-dimensional structures. Open difficult problems are also suggested for further study.

  1. Muninn: A versioning flash key-value store using an object-based storage model

    OpenAIRE

    Kang, Y.; Pitchumani, R; Marlette, T; Miller, El

    2014-01-01

    While non-volatile memory (NVRAM) devices have the po-tential to alleviate the trade-off between performance, scal-ability, and energy in storage and memory subsystems, a block interface and storage subsystems designed for slow I/O devices make it difficult to efficiently exploit NVRAMs in a portable and extensible way. We propose an object-based storage model as a way of addressing the shortfalls of the current interfaces. Through the design of Muninn, an object-based versioning key-value st...

  2. Key factors regulating the mass delivery of macromolecules to model cell membranes

    DEFF Research Database (Denmark)

    Campbell, Richard A.; Watkins, Erik B.; Jagalski, Vivien

    2014-01-01

    We show that both gravity and electrostatics are key factors regulating interactions between model cell membranes and self-assembled liquid crystalline aggregates of dendrimers and phospholipids. The system is a proxy for the trafficking of reservoirs of therapeutic drugs to cell membranes for slow...... diffusion and continuous delivery. Neutron reflectometry measurements were carried out on supported lipid bilayers of varying charge and on hydrophilic silica surfaces. Translocation of the macromolecule across the membrane and adsorption of the lamellar aggregates occur only when the membrane (1...... of the aggregates to activate endocytosis pathways on specific cell types is discussed in the context of targeted drug delivery applications....

  3. Implementing the Five-A Model of Technical Refinement: Key Roles of the Sport Psychologist.

    Science.gov (United States)

    Carson, Howie J; Collins, Dave

    2016-10-01

    There is increasing evidence for the significant contribution provided by sport psychologists within applied coaching environments. However, this rarely considers their skills/knowledge being applied when refining athletes' already learned and well-established motor skills. Therefore, this article focuses on how a sport psychologist might assist a coach and athlete to implement long-term permanent and pressure proof refinements. It highlights key contributions at each stage of the Five-A model-designed to deliver these important outcomes-providing both psychomotor and psychosocial input to the support delivery. By employing these recommendations, sport psychologists can make multiple positive contributions to completion of this challenging task.

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

    Science.gov (United States)

    Zhu, Haihong; Li, You; Zhang, Hang

    2017-01-01

    Electronic maps (E-maps) provide people with convenience in real-world space. Although web map services can display maps on screens, a more important function is their ability to access geographical features. An E-map that is based on raster tiles is inferior to vector tiles in terms of interactive ability because vector maps provide a convenient and effective method to access and manipulate web map features. However, the critical issue regarding rendering tiled vector maps is that geographical features that are rendered in the form of map symbols via vector tiles may cause visual discontinuities, such as graphic conflicts and losses of data around the borders of tiles, which likely represent the main obstacles to exploring vector map tiles on the web. This paper proposes a tiled vector data model for geographical features in symbolized maps that considers the relationships among geographical features, symbol representations and map renderings. This model presents a method to tailor geographical features in terms of map symbols and ‘addition’ (join) operations on the following two levels: geographical features and map features. Thus, these maps can resolve the visual discontinuity problem based on the proposed model without weakening the interactivity of vector maps. The proposed model is validated by two map data sets, and the results demonstrate that the rendered (symbolized) web maps present smooth visual continuity. PMID:28475578

  5. 2D-HIDDEN MARKOV MODEL FEATURE EXTRACTION STRATEGY OF ROTATING MACHINERY FAULT DIAGNOSIS

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A new feature extraction method based on 2D-hidden Markov model(HMM) is proposed.Meanwhile the time index and frequency index are introduced to represent the new features. The new feature extraction strategy is tested by the experimental data that collected from Bently rotor experiment system. The results show that this methodology is very effective to extract the feature of vibration signals in the rotor speed-up course and can be extended to other non-stationary signal analysis fields in the future.

  6. The embedded feature model for the interpretation of chromospheric contrast profiles

    Science.gov (United States)

    Steinitz, R.; Gebbie, K. B.; Bar, V.

    1977-01-01

    Contrast profiles obtained from chromospheric filtergrams and spectra of bright and dark mottles have to date been interpreted almost exclusively in terms of Becker's cloud model. Here we demonstrate the failure of this model to account in a physically consistent way for the observed contrasts. As an alternative, we introduce an embedded-feature model, restricting our discussion in this paper to stationary features. Our model is then characterized by three independent parameters: the density of absorbing atoms, the geometrical depth, and the profile of the absorption coefficient. An analytic approximation to the contrast resulting from such a model reproduces well the observed behavior of all types of contrast profiles.

  7. Genetically engineered rat gliomas: PDGF-driven tumor initiation and progression in tv-a transgenic rats recreate key features of human brain cancer.

    Science.gov (United States)

    Connolly, Nina P; Stokum, Jesse A; Schneider, Craig S; Ozawa, Tatsuya; Xu, Su; Galisteo, Rebeca; Castellani, Rudolph J; Kim, Anthony J; Simard, J Marc; Winkles, Jeffrey A; Holland, Eric C; Woodworth, Graeme F

    2017-01-01

    Previously rodent preclinical research in gliomas frequently involved implantation of cell lines such as C6 and 9L into the rat brain. More recently, mouse models have taken over, the genetic manipulability of the mouse allowing the creation of genetically accurate models outweighed the disadvantage of its smaller brain size that limited time allowed for tumor progression. Here we illustrate a method that allows glioma formation in the rat using the replication competent avian-like sarcoma (RCAS) virus / tumor virus receptor-A (tv-a) transgenic system of post-natal cell type-specific gene transfer. The RCAS/tv-a model has emerged as a particularly versatile and accurate modeling technology by enabling spatial, temporal, and cell type-specific control of individual gene transformations and providing de novo formed glial tumors with distinct molecular subtypes mirroring human GBM. Nestin promoter-driven tv-a (Ntv-a) transgenic Sprague-Dawley rat founder lines were created and RCAS PDGFA and p53 shRNA constructs were used to initiate intracranial brain tumor formation. Tumor formation and progression were confirmed and visualized by magnetic resonance imaging (MRI) and spectroscopy. The tumors were analyzed using histopathological and immunofluorescent techniques. All experimental animals developed large, heterogeneous brain tumors that closely resembled human GBM. Median survival was 92 days from tumor initiation and 62 days from the first point of tumor visualization on MRI. Each tumor-bearing animal showed time dependent evidence of malignant progression to high-grade glioma by MRI and neurological examination. Post-mortem tumor analysis demonstrated the presence of several key characteristics of human GBM, including high levels of tumor cell proliferation, pseudopalisading necrosis, microvascular proliferation, invasion of tumor cells into surrounding tissues, peri-tumoral reactive astrogliosis, lymphocyte infiltration, presence of numerous tumor

  8. A model of biological neuron with terminal chaos and quantum-like features

    Energy Technology Data Exchange (ETDEWEB)

    Conte, Elio [Department of Neuroscience, Psychiatric Clinic L. Bini, Bari University, 70100 Bari (Italy); Department of Pharmacology and Human Physiology, TIRES-Center for Innovative Technology for Signal Detection and Processing, Bari University, 70100 Bari (Italy); Pierri, GianPaolo [Department of Neuroscience, Psychiatric Clinic L. Bini, Bari University, 70100 Bari (Italy); Federici, Antonio [Department of Pharmacology and Human Physiology, TIRES-Center for Innovative Technology for Signal Detection and Processing, Bari University, 70100 Bari (Italy); Mendolicchio, Leonardo [Department of Neuroscience, Psychiatric Clinic L. Bini, Bari University, 70100 Bari (Italy); Zbilut, Joseph P. [Department of Molecular Biophysics and Physiology, Rush University, Chicago, IL 60612 (United States)

    2006-11-15

    A model of biological neuron is proposed combining terminal dynamics with quantum-like mechanical features, assuming the spin to be an important entity in neurodynamics, and, in particular, in synaptic transmission.

  9. Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

    Science.gov (United States)

    Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

    2011-12-01

    Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling

  10. Key challenges and priorities for modelling European grasslands under climate change.

    Science.gov (United States)

    Kipling, Richard P; Virkajärvi, Perttu; Breitsameter, Laura; Curnel, Yannick; De Swaef, Tom; Gustavsson, Anne-Maj; Hennart, Sylvain; Höglind, Mats; Järvenranta, Kirsi; Minet, Julien; Nendel, Claas; Persson, Tomas; Picon-Cochard, Catherine; Rolinski, Susanne; Sandars, Daniel L; Scollan, Nigel D; Sebek, Leon; Seddaiu, Giovanna; Topp, Cairistiona F E; Twardy, Stanislaw; Van Middelkoop, Jantine; Wu, Lianhai; Bellocchi, Gianni

    2016-10-01

    Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research

  11. The Assessment of Patient Clinical Outcome: Advantages, Models, Features of an Ideal Model

    Directory of Open Access Journals (Sweden)

    Mou’ath Hourani

    2016-06-01

    Full Text Available Background: The assessment of patient clinical outcome focuses on measuring various aspects of the health status of a patient who is under healthcare intervention. Patient clinical outcome assessment is a very significant process in the clinical field as it allows health care professionals to better understand the effectiveness of their health care programs and thus for enhancing the health care quality in general. It is thus vital that a high quality, informative review of current issues regarding the assessment of patient clinical outcome should be conducted. Aims & Objectives: 1 Summarizes the advantages of the assessment of patient clinical outcome; 2 reviews some of the existing patient clinical outcome assessment models namely: Simulation, Markov, Bayesian belief networks, Bayesian statistics and Conventional statistics, and Kaplan-Meier analysis models; and 3 demonstrates the desired features that should be fulfilled by a well-established ideal patient clinical outcome assessment model. Material & Methods: An integrative review of the literature has been performed using the Google Scholar to explore the field of patient clinical outcome assessment. Conclusion: This paper will directly support researchers, clinicians and health care professionals in their understanding of developments in the domain of the assessment of patient clinical outcome, thus enabling them to propose ideal assessment models.

  12. An Extended Normalization Model of Attention Accounts for Feature-Based Attentional Enhancement of Both Response and Coherence Gain.

    Science.gov (United States)

    Schwedhelm, Philipp; Krishna, B Suresh; Treue, Stefan

    2016-12-01

    Paying attention to a sensory feature improves its perception and impairs that of others. Recent work has shown that a Normalization Model of Attention (NMoA) can account for a wide range of physiological findings and the influence of different attentional manipulations on visual performance. A key prediction of the NMoA is that attention to a visual feature like an orientation or a motion direction will increase the response of neurons preferring the attended feature (response gain) rather than increase the sensory input strength of the attended stimulus (input gain). This effect of feature-based attention on neuronal responses should translate to similar patterns of improvement in behavioral performance, with psychometric functions showing response gain rather than input gain when attention is directed to the task-relevant feature. In contrast, we report here that when human subjects are cued to attend to one of two motion directions in a transparent motion display, attentional effects manifest as a combination of input and response gain. Further, the impact on input gain is greater when attention is directed towards a narrow range of motion directions than when it is directed towards a broad range. These results are captured by an extended NMoA, which either includes a stimulus-independent attentional contribution to normalization or utilizes direction-tuned normalization. The proposed extensions are consistent with the feature-similarity gain model of attention and the attentional modulation in extrastriate area MT, where neuronal responses are enhanced and suppressed by attention to preferred and non-preferred motion directions respectively.

  13. An Extended Normalization Model of Attention Accounts for Feature-Based Attentional Enhancement of Both Response and Coherence Gain.

    Directory of Open Access Journals (Sweden)

    Philipp Schwedhelm

    2016-12-01

    Full Text Available Paying attention to a sensory feature improves its perception and impairs that of others. Recent work has shown that a Normalization Model of Attention (NMoA can account for a wide range of physiological findings and the influence of different attentional manipulations on visual performance. A key prediction of the NMoA is that attention to a visual feature like an orientation or a motion direction will increase the response of neurons preferring the attended feature (response gain rather than increase the sensory input strength of the attended stimulus (input gain. This effect of feature-based attention on neuronal responses should translate to similar patterns of improvement in behavioral performance, with psychometric functions showing response gain rather than input gain when attention is directed to the task-relevant feature. In contrast, we report here that when human subjects are cued to attend to one of two motion directions in a transparent motion display, attentional effects manifest as a combination of input and response gain. Further, the impact on input gain is greater when attention is directed towards a narrow range of motion directions than when it is directed towards a broad range. These results are captured by an extended NMoA, which either includes a stimulus-independent attentional contribution to normalization or utilizes direction-tuned normalization. The proposed extensions are consistent with the feature-similarity gain model of attention and the attentional modulation in extrastriate area MT, where neuronal responses are enhanced and suppressed by attention to preferred and non-preferred motion directions respectively.

  14. Key transmission parameters of an institutional outbreak during the 1918 influenza pandemic estimated by mathematical modelling

    Directory of Open Access Journals (Sweden)

    Nelson Peter

    2006-11-01

    Full Text Available Abstract Aim To estimate the key transmission parameters associated with an outbreak of pandemic influenza in an institutional setting (New Zealand 1918. Methods Historical morbidity and mortality data were obtained from the report of the medical officer for a large military camp. A susceptible-exposed-infectious-recovered epidemiological model was solved numerically to find a range of best-fit estimates for key epidemic parameters and an incidence curve. Mortality data were subsequently modelled by performing a convolution of incidence distribution with a best-fit incidence-mortality lag distribution. Results Basic reproduction number (R0 values for three possible scenarios ranged between 1.3, and 3.1, and corresponding average latent period and infectious period estimates ranged between 0.7 and 1.3 days, and 0.2 and 0.3 days respectively. The mean and median best-estimate incidence-mortality lag periods were 6.9 and 6.6 days respectively. This delay is consistent with secondary bacterial pneumonia being a relatively important cause of death in this predominantly young male population. Conclusion These R0 estimates are broadly consistent with others made for the 1918 influenza pandemic and are not particularly large relative to some other infectious diseases. This finding suggests that if a novel influenza strain of similar virulence emerged then it could potentially be controlled through the prompt use of major public health measures.

  15. Initial Content Validation Results of a New Simulation Model for Flexible Ureteroscopy: The Key-Box.

    Science.gov (United States)

    Villa, Luca; Şener, Tarik Emre; Somani, Bhaskar K; Cloutier, Jonathan; Butticè, Salvatore; Marson, Francesco; Doizi, Steeve; Proietti, Silvia; Traxer, Olivier

    2017-01-01

    We sought to test the content validity of a new training model for flexible ureteroscopy: the Key-Box. Sixteen medical students were randomized to undergo a 10-day training consisting of performing 10 different exercises aimed at learning specific movements with the flexible ureteroscope, and how to catch and release stones with a nitinol basket using the Key-Box (n = 8 students in the training group, n = 8 students in the nontraining control group). Subsequently, an expert endourologist (O.T.) blindly assessed skills acquired by the whole cohort of students through two exercises on ureteroscope manipulation and one exercise on stone capture selected among those used for the training. A performance scale (1-5) assessing different steps of the procedure was used to evaluate each student. Time to complete the exercises was measured. Mann-Whitney Rank Sum test was used for comparisons between the two groups. Mean scores obtained by trained students were significantly higher compared with those obtained by nontrained students (all p six (75%) nontrained students were not able to finish one out of the two exercises on ureteroscope manipulation and the exercise on stone capture, respectively. The mean time to complete the three exercises was 76.3, 69.9, and 107 and 172.5, 137.9, and 168 seconds in the trained and nontrained groups, respectively (all p Box(®) seems to be a valid easy-to-use training model for initiating novel endoscopists to flexible ureteroscopy.

  16. Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update.

    Science.gov (United States)

    Gao, Changxin; Shi, Huizhang; Yu, Jin-Gang; Sang, Nong

    2016-04-15

    Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA) model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN) features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the "good" models (detectors), which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM) to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm.

  17. Enhancement of ELDA Tracker Based on CNN Features and Adaptive Model Update

    Directory of Open Access Journals (Sweden)

    Changxin Gao

    2016-04-01

    Full Text Available Appearance representation and the observation model are the most important components in designing a robust visual tracking algorithm for video-based sensors. Additionally, the exemplar-based linear discriminant analysis (ELDA model has shown good performance in object tracking. Based on that, we improve the ELDA tracking algorithm by deep convolutional neural network (CNN features and adaptive model update. Deep CNN features have been successfully used in various computer vision tasks. Extracting CNN features on all of the candidate windows is time consuming. To address this problem, a two-step CNN feature extraction method is proposed by separately computing convolutional layers and fully-connected layers. Due to the strong discriminative ability of CNN features and the exemplar-based model, we update both object and background models to improve their adaptivity and to deal with the tradeoff between discriminative ability and adaptivity. An object updating method is proposed to select the “good” models (detectors, which are quite discriminative and uncorrelated to other selected models. Meanwhile, we build the background model as a Gaussian mixture model (GMM to adapt to complex scenes, which is initialized offline and updated online. The proposed tracker is evaluated on a benchmark dataset of 50 video sequences with various challenges. It achieves the best overall performance among the compared state-of-the-art trackers, which demonstrates the effectiveness and robustness of our tracking algorithm.

  18. Determining Key Model Parameters of Rapidly Intensifying Hurricane Guillermo(1997) using the Ensemble Kalman Filter

    CERN Document Server

    Godinez, Humberto C; Fierro, Alexandre O; Guimond, Stephen R; Kao, Jim

    2011-01-01

    In this work we present the assimilation of dual-Doppler radar observations for rapidly intensifying hurricane Guillermo (1997) using the Ensemble Kalman Filter (EnKF) to determine key model parameters. A unique aspect of Guillermo was that during the period of radar observations strong convective bursts, attributable to wind shear, formed primarily within the eastern semicircle of the eyewall. To reproduce this observed structure within a hurricane model, background wind shear of some magnitude must be specified; as well as turbulence and surface parameters appropriately specified so that the impact of the shear on the simulated hurricane vortex can be realized. To first illustrate the complex nonlinear interactions induced by changes in these parameters, an ensemble of 120 simulations have been conducted in which individual members were formulated by sampling the parameters within a certain range via a Latin hypercube approach. Next, data from the 120 simulations and two distinct derived fields of observati...

  19. Development of generic key performance indicators for PMBOK® using a 3D project integration model

    Directory of Open Access Journals (Sweden)

    Craig Langston

    2013-12-01

    Full Text Available Since Martin Barnes’ so-called ‘iron triangle’ circa 1969, much debate has occurred over how best to describe the fundamental constraints that underpin project success. This paper develops a 3D project integration model for PMBOK® comprising core constraints of scope, cost, time and risk as a basis to propose six generic key performance indicators (KPIs that articulate successful project delivery. These KPIs are defined as value, efficiency, speed, innovation, complexity and impact and can each be measured objectively as ratios of the core constraints. An overall KPI (denoted as s3/ctr is also derived. The aim in this paper is to set out the case for such a model and to demonstrate how it can be employed to assess the performance of project teams in delivering successful outcomes at various stages in the project life cycle. As part of the model’s development, a new PMBOK® knowledge area concerning environmental management is advanced.

  20. SU-E-T-214: Predicting Plan Quality from Patient Geometry: Feature Selection and Inference Modeling.

    Science.gov (United States)

    Ruan, D; Shao, W; DeMarco, J; Kupelian, P; Low, D

    2012-06-01

    To investigate and develop methods to infer treatment plan quality from the geometric features of PTV/OAR structures; to discover and identify features of high prognostic values. This study explores the prognostic utility of geometric features of two categories: (1) absolute geometry, characterizing the volumes of single structures (PTV, OARs); and (2) relative geometry, based on the minimal 3D distance and/or overlapping volume between pairs of structures. Using prostate as a pilot site, we developed inference models to 'predict' SBRT plan quality of DVH end points. We developed and assessed (1) a full linear regression model based on both absolute and relative geometric features, (2) a sparsity-penalized linear regression model, (3) a linear regression model based on absolute geometry features only; (4) a learning-based nonparametric model. Cross-validation was used for both selecting the parameter values as well as quantifying the inference performance. The best inference method for each of the DVH end points was identified to reveal the structural and prognostic differences among them. For linear regression, using sparsity-regularization discovered geometric features that were mostly absolute, demonstrating their dominant linear prognostic utility. However, introducing relative geometric features improved the plan quality prediction by 15% for all DVH end points. In contrast, nonparametric models had a heavier dependence on relative geometry features. While linear regression based on both features sets predicted OAR DVH points slightly better, the nonparametric method excelled in predicting PTV coverage and conformality. The inference result from this study provides an 'expectation' for the plan quality before the planning is to be performed, providing reference goals for the planner and a baseline for detecting abnormality. The use of relative geometry complements the absolute geometry with information on spatial configuration of the PTV/OAR structures of

  1. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

    DEFF Research Database (Denmark)

    Huang, Sijia; Chong, Nicole; Lewis, Nathan

    2016-01-01

    . Methods: We propose that higher-order functional representation of metabolomics data, such as pathway-based metabolomic features, can be used as robust biomarkers for breast cancer. Towards this, we have developed a new computational method that uses personalized pathway dysregulation scores for disease...... the Curve, a receiver operating characteristic curve) of 0.968 and 0.934, sensitivities of 0.946 and 0.954, and specificities of 0.934 and 0.918. These two metabolomics-based pathway models are further validated by RNA-Seq-based TCGA (The Cancer Genome Atlas) breast cancer data, with AUCs of 0.995 and 0.......993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions: We have successfully developed a new type of pathway-based model to study...

  2. The Laser Scan Data as a Key Element in the Hydraulic Flood Modelling in Urban Areas

    Science.gov (United States)

    Sole, A.; Giosa, L.; Albano, R.; Cantisani, A.

    2013-05-01

    This paper is intended to highlight the need to use data at high spatial resolution, such as those obtained through the use of Airborne Laser Scanning (ALS) techniques, to support hydraulic models for the assessment of flood hazards in urban territory. In fact, the significant structural features (houses, walls, roads, etc.) in the city are important in relation to both the volume of the floodplain that can be occupied by the flow and the direction that the flow takes across the floodplain. ALS data can range up to several terabytes in size and is a function of the geographic scale of the mission. Also, this data is typically irregular with uneven point density. Therefore, a quick method is described to ride out the difficulties to handle the large datasets with uneven point densities and to improve the extracting of feature information for further use in Geographic Information System (GIS) analysis. Finally, a comparison is made between the maximum inundated area obtained from ALS data and that one calculated using a traditional topographic map. The results show that the high-resolution data obtained from airborne remote sensing can increase the opportunities for representation of small-scale structural elements in complex systems using two-dimensional models of flood inundation.

  3. A Feature Model Based Framework for Refactoring Software Product Line Architecture

    Institute of Scientific and Technical Information of China (English)

    Mohammad Tanhaei; Jafar Habibi∗

    2016-01-01

    Software product line (SPL) is an approach used to develop a range of software products with a high degree of similarity. In this approach, a feature model is usually used to keep track of similarities and differences. Over time, as modifications are made to the SPL, inconsistencies with the feature model could arise. The first approach to dealing with these inconsistencies is refactoring. Refactoring consists of small steps which, when accumulated, may lead to large-scale changes in the SPL, resulting in features being added to or eliminated from the SPL. In this paper, we propose a framework for refactoring SPLs, which helps keep SPLs consistent with the feature model. After some introductory remarks, we describe a formal model for representing the feature model. We express various refactoring patterns applicable to the feature model and the SPL formally, and then introduce an algorithm for finding them in the SPL. In the end, we use a real-world case study of an SPL to illustrate the applicability of the framework introduced in the paper.

  4. The giant Jiaodong gold province: The key to a unified model for orogenic gold deposits?

    Directory of Open Access Journals (Sweden)

    David I. Groves

    2016-05-01

    Full Text Available Although the term orogenic gold deposit has been widely accepted for all gold-only lode-gold deposits, with the exception of Carlin-type deposits and rare intrusion-related gold systems, there has been continuing debate on their genesis. Early syngenetic models and hydrothermal models dominated by meteoric fluids are now clearly unacceptable. Magmatic-hydrothermal models fail to explain the genesis of orogenic gold deposits because of the lack of consistent spatially – associated granitic intrusions and inconsistent temporal relationships. The most plausible, and widely accepted, models involve metamorphic fluids, but the source of these fluids is hotly debated. Sources within deeper segments of the supracrustal successions hosting the deposits, the underlying continental crust, and subducted oceanic lithosphere and its overlying sediment wedge all have their proponents. The orogenic gold deposits of the giant Jiaodong gold province of China, in the delaminated North China Craton, contain ca. 120 Ma gold deposits in Precambrian crust that was metamorphosed over 2000 million years prior to gold mineralization. The only realistic source of fluid and gold is a subducted oceanic slab with its overlying sulfide-rich sedimentary package, or the associated mantle wedge. This could be viewed as an exception to a general metamorphic model where orogenic gold has been derived during greenschist- to amphibolite-facies metamorphism of supracrustal rocks: basaltic rocks in the Precambrian and sedimentary rocks in the Phanerozoic. Alternatively, if a holistic view is taken, Jiaodong can be considered the key orogenic gold province for a unified model in which gold is derived from late-orogenic metamorphic devolatilization of stalled subduction slabs and oceanic sediments throughout Earth history. The latter model satisfies all geological, geochronological, isotopic and geochemical constraints but the precise mechanisms of auriferous fluid release, like many

  5. The giant Jiaodong gold province:The key to a unified model for orogenic gold deposits?

    Institute of Scientific and Technical Information of China (English)

    David I. Groves; M. Santosh

    2016-01-01

    Although the term orogenic gold deposit has been widely accepted for all gold-only lode-gold deposits, with the exception of Carlin-type deposits and rare intrusion-related gold systems, there has been continuing debate on their genesis. Early syngenetic models and hydrothermal models dominated by meteoric fluids are now clearly unacceptable. Magmatic-hydrothermal models fail to explain the genesis of orogenic gold deposits because of the lack of consistent spatially e associated granitic intrusions and inconsistent temporal relationships. The most plausible, and widely accepted, models involve meta-morphic fluids, but the source of these fluids is hotly debated. Sources within deeper segments of the supracrustal successions hosting the deposits, the underlying continental crust, and subducted oceanic lithosphere and its overlying sediment wedge all have their proponents. The orogenic gold deposits of the giant Jiaodong gold province of China, in the delaminated North China Craton, contain ca. 120 Ma gold deposits in Precambrian crust that was metamorphosed over 2000 million years prior to gold mineralization. The only realistic source of fluid and gold is a subducted oceanic slab with its overlying sulfide-rich sedimentary package, or the associated mantle wedge. This could be viewed as an exception to a general metamorphic model where orogenic gold has been derived during greenschist- to amphibolite-facies metamorphism of supracrustal rocks: basaltic rocks in the Precambrian and sedi-mentary rocks in the Phanerozoic. Alternatively, if a holistic view is taken, Jiaodong can be considered the key orogenic gold province for a unified model in which gold is derived from late-orogenic metamorphic devolatilization of stalled subduction slabs and oceanic sediments throughout Earth history. The latter model satisfies all geological, geochronological, isotopic and geochemical constraints but the precise mechanisms of auriferous fluid release, like many other subduction

  6. Choosing preclinical study models of diabetic retinopathy: key problems for consideration

    Directory of Open Access Journals (Sweden)

    Mi XS

    2014-11-01

    Full Text Available Xue-Song Mi,1,2 Ti-Fei Yuan,3,4 Yong Ding,1 Jing-Xiang Zhong,1 Kwok-Fai So4,5 1Department of Ophthalmology, First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People’s Republic of China; 2Department of Anatomy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, People’s Republic of China; 3School of Psychology, Nanjing Normal University, Nanjing, People’s Republic of China; 4Department of Ophthalmology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong; 5Guangdong-Hongkong-Macau Institute of Central Nervous System, Jinan University, Guangzhou, People’s Republic of China Abstract: Diabetic retinopathy (DR is the most common complication of diabetes mellitus in the eye. Although the clinical treatment for DR has already developed to a relative high level, there are still many urgent problems that need to be investigated in clinical and basic science. Currently, many in vivo animal models and in vitro culture systems have been applied to solve these problems. Many approaches have also been used to establish different DR models. However, till now, there has not been a single study model that can clearly and exactly mimic the developmental process of the human DR. Choosing the suitable model is important, not only for achieving our research goals smoothly, but also, to better match with different experimental proposals in the study. In this review, key problems for consideration in choosing study models of DR are discussed. These problems relate to clinical relevance, different approaches for establishing models, and choice of different species of animals as well as of the specific in vitro culture systems. Attending to these considerations will deepen the understanding on current study models and optimize the experimental design for the final goal of preventing DR. Keywords: animal model, in vitro culture, ex vivo culture, neurovascular dysfunction

  7. Feature Extraction

    CERN Document Server

    CERN. Geneva

    2015-01-01

    Feature selection and reduction are key to robust multivariate analyses. In this talk I will focus on pros and cons of various variable selection methods and focus on those that are most relevant in the context of HEP.

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

    Directory of Open Access Journals (Sweden)

    Sirinoot Boonsuk

    2014-01-01

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

  9. Re-orienting a remote acute care model towards a primary health care approach: key enablers.

    Science.gov (United States)

    Carroll, Vicki; Reeve, Carole A; Humphreys, John S; Wakerman, John; Carter, Maureen

    2015-01-01

    The objective of this study was to identify the key enablers of change in re-orienting a remote acute care model to comprehensive primary healthcare delivery. The setting of the study was a 12-bed hospital in Fitzroy Crossing, Western Australia. Individual key informant, in-depth interviews were completed with five of six identified senior leaders involved in the development of the Fitzroy Valley Health Partnership. Interviews were recorded and transcripts were thematically analysed by two investigators for shared views about the enabling factors strengthening primary healthcare delivery in a remote region of Australia. Participants described theestablishment of a culturally relevant primary healthcare service, using a community-driven, 'bottom up' approach characterised by extensive community participation. The formal partnership across the government and community controlled health services was essential, both to enable change to occur and to provide sustainability in the longer term. A hierarchy of major themes emerged. These included community participation, community readiness and desire for self-determination; linkages in the form of a government community controlled health service partnership; leadership; adequate infrastructure; enhanced workforce supply; supportive policy; and primary healthcare funding. The strong united leadership shown by the community and the health service enabled barriers to be overcome and it maximised the opportunities provided by government policy changes. The concurrent alignment around a common vision enabled implementation of change. The key principle learnt from this study is the importance of community and health service relationships and local leadership around a shared vision for the re-orientation of community health services.

  10. A Multistage Feature Selection Model for Document Classification Using Information Gain and Rough Set

    Directory of Open Access Journals (Sweden)

    Mrs. Leena. H. Patil

    2014-11-01

    Full Text Available Huge number of documents are increasing rapidly, therefore, to organize it in digitized form text categorization becomes an challenging issue. A major issue for text categorization is its large number of features. Most of the features are noisy, irrelevant and redundant, which may mislead the classifier. Hence, it is most important to reduce dimensionality of data to get smaller subset and provide the most gain in information. Feature selection techniques reduce the dimensionality of feature space. It also improves the overall accuracy and performance. Hence, to overcome the issues of text categorization feature selection is considered as an efficient technique . Therefore, we, proposed a multistage feature selection model to improve the overall accuracy and performance of classification. In the first stage document preprocessing part is performed. Secondly, each term within the documents are ranked according to their importance for classification using the information gain. Thirdly rough set technique is applied to the terms which are ranked importantly and feature reduction is carried out. Finally a document classification is performed on the core features using Naive Bayes and KNN classifier. Experiments are carried out on three UCI datasets, Reuters 21578, Classic 04 and Newsgroup 20. Results show the better accuracy and performance of the proposed model.

  11. Landmine detection with ground penetrating radar using discrete hidden Markov models with symbol dependent features

    Science.gov (United States)

    Frigui, Hichem; Missaoui, Oualid; Gader, Paul

    2008-04-01

    In this paper, we propose an efficient Discrete Hidden Markov Models (DHMM) for landmine detection that rely on training data to learn the relevant features that characterize different signatures (mines and non-mines), and can adapt to different environments and different radar characteristics. Our work is motivated by the fact that mines and clutter objects have different characteristics depending on the mine type, soil and weather conditions, and burial depth. Thus, ideally different sets of specialized features may be needed to achieve high detection and low false alarm rates. The proposed approach includes three main components: feature extraction, clustering, and DHMM. First, since we do not assume that the relevant features for the different signatures are known a priori, we proceed by extracting several sets of features for each signature. Then, we apply a clustering and feature discrimination algorithm to the training data to quantize it into a set of symbols and learn feature relevance weights for each symbol. These symbols and their weights are then used in a DHMM framework to learn the parameters of the mine and the background models. Preliminary results on large and diverse ground penetrating radar data show that the proposed method outperforms the basic DHMM where all the features are treated equally important.

  12. Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion

    Science.gov (United States)

    Luisier, Raphaëlle; Unterberger, Elif B.; Goodman, Jay I.; Schwarz, Michael; Moggs, Jonathan; Terranova, Rémi; van Nimwegen, Erik

    2014-01-01

    Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesis. PMID:24464994

  13. Efficient and robust model-to-image alignment using 3D scale-invariant features.

    Science.gov (United States)

    Toews, Matthew; Wells, William M

    2013-04-01

    This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down.

  14. The undecided have the key: Interaction-driven opinion dynamics in a three state model

    CERN Document Server

    Balenzuela, Pablo; Semeshenko, Viktoriya

    2015-01-01

    The effects of interpersonal interactions on individual's agreements result in a social aggregation process which is reflected in the formation of collective states, as for instance, groups of individuals with a similar opinion about a given issue. This field, which has been a longstanding concern of sociologists and psychologists, has been extended into an area of experimental social psychology, and even has attracted the attention of physicists and mathematicians. In this article, we present a novel model of opinion formation in which agents may either have a strict preference for a choice, or be undecided. The opinion shift emerges during interpersonal communications, as a consequence of a cumulative process of conviction for one of the two extremes opinions through repeated interactions. There are two main ingredients which play key roles in determining the steady state: the initial fraction of undecided agents and the conviction's sensitivity in each interaction. As a function of these two parameters, th...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-09-24

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

  16. Cadmium-induced immune abnormality is a key pathogenic event in human and rat models of preeclampsia.

    Science.gov (United States)

    Zhang, Qiong; Huang, Yinping; Zhang, Keke; Huang, Yanjun; Yan, Yan; Wang, Fan; Wu, Jie; Wang, Xiao; Xu, Zhangye; Chen, Yongtao; Cheng, Xue; Li, Yong; Jiao, Jinyu; Ye, Duyun

    2016-11-01

    With increased industrial development, cadmium is an increasingly important environmental pollutant. Studies have identified various adverse effects of cadmium on human beings. However, the relationships between cadmium pollution and the pathogenesis of preeclampsia remain elusive. The objective of this study is to explore the effects of cadmium on immune system among preeclamptic patients and rats. The results showed that the cadmium levels in the peripheral blood of preeclamptic patients were significantly higher than those observed in normal pregnancy. Based on it, a novel rat model of preeclampsia was established by the intraperitoneal administration of cadmium chloride (CdCl2) (0.125 mg of Cd/kg body weight) on gestational days 9-14. Key features of preeclampsia, including hypertension, proteinuria, placental abnormalities and small foetal size, appeared in pregnant rats after the administration of low-dose of CdCl2. Cadmium increased immunoglobulin production, mainly angiotensin II type 1-receptor-agonistic autoantibodies (AT1-AA), by increasing the expression of activation-induced cytosine deaminase (AID) in B cells. AID is critical for the maturation of antibody and autoantibody responses. In addition, angiotensin II type 1-receptor-agonistic autoantibody, which emerged recently as a potential pathogenic contributor to PE, was responsible for the deposition of complement component 5 (C5) in kidneys of pregnant rats via angiotensin II type 1 receptor (AT1R) activation. C5a is a fragment of C5 that is released during C5 activation. Selectively interfering with C5a signalling by a complement C5a receptor-specific antagonist significantly attenuated hypertension and proteinuria in Cd-injected pregnant rats. Our results suggest that cadmium induces immune abnormalities that may be a key pathogenic contributor to preeclampsia and provide new insights into treatment strategies of preeclampsia. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. How can selection of biologically inspired features improve the performance of a robust object recognition model?

    Directory of Open Access Journals (Sweden)

    Masoud Ghodrati

    Full Text Available Humans can effectively and swiftly recognize objects in complex natural scenes. This outstanding ability has motivated many computational object recognition models. Most of these models try to emulate the behavior of this remarkable system. The human visual system hierarchically recognizes objects in several processing stages. Along these stages a set of features with increasing complexity is extracted by different parts of visual system. Elementary features like bars and edges are processed in earlier levels of visual pathway and as far as one goes upper in this pathway more complex features will be spotted. It is an important interrogation in the field of visual processing to see which features of an object are selected and represented by the visual cortex. To address this issue, we extended a hierarchical model, which is motivated by biology, for different object recognition tasks. In this model, a set of object parts, named patches, extracted in the intermediate stages. These object parts are used for training procedure in the model and have an important role in object recognition. These patches are selected indiscriminately from different positions of an image and this can lead to the extraction of non-discriminating patches which eventually may reduce the performance. In the proposed model we used an evolutionary algorithm approach to select a set of informative patches. Our reported results indicate that these patches are more informative than usual random patches. We demonstrate the strength of the proposed model on a range of object recognition tasks. The proposed model outperforms the original model in diverse object recognition tasks. It can be seen from the experiments that selected features are generally particular parts of target images. Our results suggest that selected features which are parts of target objects provide an efficient set for robust object recognition.

  18. How can selection of biologically inspired features improve the performance of a robust object recognition model?

    Science.gov (United States)

    Ghodrati, Masoud; Khaligh-Razavi, Seyed-Mahdi; Ebrahimpour, Reza; Rajaei, Karim; Pooyan, Mohammad

    2012-01-01

    Humans can effectively and swiftly recognize objects in complex natural scenes. This outstanding ability has motivated many computational object recognition models. Most of these models try to emulate the behavior of this remarkable system. The human visual system hierarchically recognizes objects in several processing stages. Along these stages a set of features with increasing complexity is extracted by different parts of visual system. Elementary features like bars and edges are processed in earlier levels of visual pathway and as far as one goes upper in this pathway more complex features will be spotted. It is an important interrogation in the field of visual processing to see which features of an object are selected and represented by the visual cortex. To address this issue, we extended a hierarchical model, which is motivated by biology, for different object recognition tasks. In this model, a set of object parts, named patches, extracted in the intermediate stages. These object parts are used for training procedure in the model and have an important role in object recognition. These patches are selected indiscriminately from different positions of an image and this can lead to the extraction of non-discriminating patches which eventually may reduce the performance. In the proposed model we used an evolutionary algorithm approach to select a set of informative patches. Our reported results indicate that these patches are more informative than usual random patches. We demonstrate the strength of the proposed model on a range of object recognition tasks. The proposed model outperforms the original model in diverse object recognition tasks. It can be seen from the experiments that selected features are generally particular parts of target images. Our results suggest that selected features which are parts of target objects provide an efficient set for robust object recognition.

  19. Antimicrobial Nanoplexes meet Model Bacterial Membranes: the key role of Cardiolipin

    Science.gov (United States)

    Marín-Menéndez, Alejandro; Montis, Costanza; Díaz-Calvo, Teresa; Carta, Davide; Hatzixanthis, Kostas; Morris, Christopher J.; McArthur, Michael; Berti, Debora

    2017-01-01

    Antimicrobial resistance to traditional antibiotics is a crucial challenge of medical research. Oligonucleotide therapeutics, such as antisense or Transcription Factor Decoys (TFDs), have the potential to circumvent current resistance mechanisms by acting on novel targets. However, their full translation into clinical application requires efficient delivery strategies and fundamental comprehension of their interaction with target bacterial cells. To address these points, we employed a novel cationic bolaamphiphile that binds TFDs with high affinity to form self-assembled complexes (nanoplexes). Confocal microscopy revealed that nanoplexes efficiently transfect bacterial cells, consistently with biological efficacy on animal models. To understand the factors affecting the delivery process, liposomes with varying compositions, taken as model synthetic bilayers, were challenged with nanoplexes and investigated with Scattering and Fluorescence techniques. Thanks to the combination of results on bacteria and synthetic membrane models we demonstrate for the first time that the prokaryotic-enriched anionic lipid Cardiolipin (CL) plays a key-role in the TFDs delivery to bacteria. Moreover, we can hypothesize an overall TFD delivery mechanism, where bacterial membrane reorganization with permeability increase and release of the TFD from the nanoplexes are the main factors. These results will be of great benefit to boost the development of oligonucleotides-based antimicrobials of superior efficacy.

  20. Characterization of a Field Spectroradiometer for Unattended Vegetation Monitoring. Key Sensor Models and Impacts on Reflectance

    Directory of Open Access Journals (Sweden)

    Javier Pacheco-Labrador

    2015-02-01

    Full Text Available Field spectroradiometers integrated in automated systems at Eddy Covariance (EC sites are a powerful tool for monitoring and upscaling vegetation physiology and carbon and water fluxes. However, exposure to varying environmental conditions can affect the functioning of these sensors, especially if these cannot be completely insulated and stabilized. This can cause inaccuracy in the spectral measurements and hinder the comparison between data acquired at different sites. This paper describes the characterization of key sensor models in a double beam spectroradiometer necessary to calculate the Hemispherical-Conical Reflectance Factor (HCRF. Dark current, temperature dependence, non-linearity, spectral calibration and cosine receptor directional responses are modeled in the laboratory as a function of temperature, instrument settings, radiation measured or illumination angle. These models are used to correct the spectral measurements acquired continuously by the same instrument integrated outdoors in an automated system (AMSPEC-MED. Results suggest that part of the instrumental issues cancel out mutually or can be controlled by the instrument configuration, so that changes induced in HCFR reached about 0.05 at maximum. However, these corrections are necessary to ensure the inter-comparison of data with other ground or remote sensors and to discriminate instrumentally induced changes in HCRF from those related with vegetation physiology and directional effects.

  1. Features Extraction of Flotation Froth Images and BP Neural Network Soft-Sensor Model of Concentrate Grade Optimized by Shuffled Cuckoo Searching Algorithm

    Directory of Open Access Journals (Sweden)

    Jie-sheng Wang

    2014-01-01

    Full Text Available For meeting the forecasting target of key technology indicators in the flotation process, a BP neural network soft-sensor model based on features extraction of flotation froth images and optimized by shuffled cuckoo search algorithm is proposed. Based on the digital image processing technique, the color features in HSI color space, the visual features based on the gray level cooccurrence matrix, and the shape characteristics based on the geometric theory of flotation froth images are extracted, respectively, as the input variables of the proposed soft-sensor model. Then the isometric mapping method is used to reduce the input dimension, the network size, and learning time of BP neural network. Finally, a shuffled cuckoo search algorithm is adopted to optimize the BP neural network soft-sensor model. Simulation results show that the model has better generalization results and prediction accuracy.

  2. Features extraction of flotation froth images and BP neural network soft-sensor model of concentrate grade optimized by shuffled cuckoo searching algorithm.

    Science.gov (United States)

    Wang, Jie-sheng; Han, Shuang; Shen, Na-na; Li, Shu-xia

    2014-01-01

    For meeting the forecasting target of key technology indicators in the flotation process, a BP neural network soft-sensor model based on features extraction of flotation froth images and optimized by shuffled cuckoo search algorithm is proposed. Based on the digital image processing technique, the color features in HSI color space, the visual features based on the gray level cooccurrence matrix, and the shape characteristics based on the geometric theory of flotation froth images are extracted, respectively, as the input variables of the proposed soft-sensor model. Then the isometric mapping method is used to reduce the input dimension, the network size, and learning time of BP neural network. Finally, a shuffled cuckoo search algorithm is adopted to optimize the BP neural network soft-sensor model. Simulation results show that the model has better generalization results and prediction accuracy.

  3. On the crucial features of a single-file transport model for ion channels

    CERN Document Server

    Liang, Kuo Kan

    2013-01-01

    It has long been accepted that the multiple-ion single-file transport model is appropriate for many kinds of ion channels. However, most of the purely theoretical works in this field did not capture all of the important features of the realistic systems. Nowadays, large-scale atomic-level simulations are more feasible. Discrepancy between theories, simulations and experiments are getting obvious, enabling people to carefully examine the missing parts of the theoretical models and methods. In this work, it is attempted to find out the essential features that such kind of models should possess, in order that the physical properties of an ion channel be adequately reflected.

  4. Active Shape Model of Combining Pca and Ica: Application to Facial Feature Extraction

    Institute of Scientific and Technical Information of China (English)

    DENG Lin; RAO Ni-ni; WANG Gang

    2006-01-01

    Active Shape Model (ASM) is a powerful statistical tool to extract the facial features of a face image under frontal view. It mainly relies on Principle Component Analysis (PCA) to statistically model the variability in the training set of example shapes. Independent Component Analysis (ICA) has been proven to be more efficient to extract face features than PCA . In this paper, we combine the PCA and ICA by the consecutive strategy to form a novel ASM. Firstly, an initial model, which shows the global shape variability in the training set, is generated by the PCA-based ASM. And then, the final shape model, which contains more local characters, is established by the ICA-based ASM. Experimental results verify that the accuracy of facial feature extraction is statistically significantly improved by applying the ICA modes after the PCA modes.

  5. Construction Method of the Topographical Features Model for Underwater Terrain Navigation

    Directory of Open Access Journals (Sweden)

    Wang Lihui

    2015-09-01

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

  6. Model Compensation Approach Based on Nonuniform Spectral Compression Features for Noisy Speech Recognition

    Directory of Open Access Journals (Sweden)

    Ning Geng-Xin

    2007-01-01

    Full Text Available This paper presents a novel model compensation (MC method for the features of mel-frequency cepstral coefficients (MFCCs with signal-to-noise-ratio- (SNR- dependent nonuniform spectral compression (SNSC. Though these new MFCCs derived from a SNSC scheme have been shown to be robust features under matched case, they suffer from serious mismatch when the reference models are trained at different SNRs and in different environments. To solve this drawback, a compressed mismatch function is defined for the static observations with nonuniform spectral compression. The means and variances of the static features with spectral compression are derived according to this mismatch function. Experimental results show that the proposed method is able to provide recognition accuracy better than conventional MC methods when using uncompressed features especially at very low SNR under different noises. Moreover, the new compensation method has a computational complexity slightly above that of conventional MC methods.

  7. Testing Models: A Key Aspect to Promote Teaching Activities Related to Models and Modelling in Biology Lessons?

    Science.gov (United States)

    Krell, Moritz; Krüger, Dirk

    2016-01-01

    This study investigated biology teachers' (N = 148) understanding of models and modelling (MoMo), their model-related teaching activities and relations between the two. A framework which distinguishes five aspects of MoMo in science ("nature of models," "multiple models," "purpose of models," "testing…

  8. Testing Models: A Key Aspect to Promote Teaching Activities Related to Models and Modelling in Biology Lessons?

    Science.gov (United States)

    Krell, Moritz; Krüger, Dirk

    2016-01-01

    This study investigated biology teachers' (N = 148) understanding of models and modelling (MoMo), their model-related teaching activities and relations between the two. A framework which distinguishes five aspects of MoMo in science ("nature of models," "multiple models," "purpose of models," "testing…

  9. Featuring Multiple Local Optima to Assist the User in the Interpretation of Induced Bayesian Network Models

    DEFF Research Database (Denmark)

    Dalgaard, Jens; Pena, Jose; Kocka, Tomas

    2004-01-01

    We propose a method to assist the user in the interpretation of the best Bayesian network model indu- ced from data. The method consists in extracting relevant features from the model (e.g. edges, directed paths and Markov blankets) and, then, assessing the con¯dence in them by studying multiple...

  10. Representation of fluctuation features in pathological knee joint vibroarthrographic signals using kernel density modeling method.

    Science.gov (United States)

    Yang, Shanshan; Cai, Suxian; Zheng, Fang; Wu, Yunfeng; Liu, Kaizhi; Wu, Meihong; Zou, Quan; Chen, Jian

    2014-10-01

    This article applies advanced signal processing and computational methods to study the subtle fluctuations in knee joint vibroarthrographic (VAG) signals. Two new features are extracted to characterize the fluctuations of VAG signals. The fractal scaling index parameter is computed using the detrended fluctuation analysis algorithm to describe the fluctuations associated with intrinsic correlations in the VAG signal. The averaged envelope amplitude feature measures the difference between the upper and lower envelopes averaged over an entire VAG signal. Statistical analysis with the Kolmogorov-Smirnov test indicates that both of the fractal scaling index (p=0.0001) and averaged envelope amplitude (p=0.0001) features are significantly different between the normal and pathological signal groups. The bivariate Gaussian kernels are utilized for modeling the densities of normal and pathological signals in the two-dimensional feature space. Based on the feature densities estimated, the Bayesian decision rule makes better signal classifications than the least-squares support vector machine, with the overall classification accuracy of 88% and the area of 0.957 under the receiver operating characteristic (ROC) curve. Such VAG signal classification results are better than those reported in the state-of-the-art literature. The fluctuation features of VAG signals developed in the present study can provide useful information on the pathological conditions of degenerative knee joints. Classification results demonstrate the effectiveness of the kernel feature density modeling method for computer-aided VAG signal analysis.

  11. Independent component feature-based human activity recognition via Linear Discriminant Analysis and Hidden Markov Model.

    Science.gov (United States)

    Uddin, Md; Lee, J J; Kim, T S

    2008-01-01

    In proactive computing, human activity recognition from image sequences is an active research area. This paper presents a novel approach of human activity recognition based on Linear Discriminant Analysis (LDA) of Independent Component (IC) features from shape information. With extracted features, Hidden Markov Model (HMM) is applied for training and recognition. The recognition performance using LDA of IC features has been compared to other approaches including Principle Component Analysis (PCA), LDA of PC, and ICA. The preliminary results show much improved performance in the recognition rate with our proposed method.

  12. Towards semantically sensitive text clustering: a feature space modeling technology based on dimension extension.

    Science.gov (United States)

    Liu, Yuanchao; Liu, Ming; Wang, Xin

    2015-01-01

    The objective of text clustering is to divide document collections into clusters based on the similarity between documents. In this paper, an extension-based feature modeling approach towards semantically sensitive text clustering is proposed along with the corresponding feature space construction and similarity computation method. By combining the similarity in traditional feature space and that in extension space, the adverse effects of the complexity and diversity of natural language can be addressed and clustering semantic sensitivity can be improved correspondingly. The generated clusters can be organized using different granularities. The experimental evaluations on well-known clustering algorithms and datasets have verified the effectiveness of our approach.

  13. Modeling Training of Future Teachers Aimed on Innovation Activities Based on the System of Design Features

    Directory of Open Access Journals (Sweden)

    Yury S. Tyunnikov

    2015-05-01

    Full Text Available Modeling of training system of future teachers aimed on innovation activities performed in a certain project logic and procedures, which is possible only through a specific set of design features, based on capability and peculiar properties of the university. The article is formulated and solved the problem of design features, revealing in its set the characteristic properties, organization and functioning of training system aimed on innovation in specific terms of professional education.

  14. Representing Microbial Dormancy in Soil Decomposition Models Improves Model Performance and Reveals Key Ecosystem Controls on Microbial Activity

    Science.gov (United States)

    He, Y.; Yang, J.; Zhuang, Q.; Wang, G.; Liu, Y.

    2014-12-01

    Climate feedbacks from soils can result from environmental change and subsequent responses of plant and microbial communities and nutrient cycling. Explicit consideration of microbial life history traits and strategy may be necessary to predict climate feedbacks due to microbial physiology and community changes and their associated effect on carbon cycling. In this study, we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of dormancy at six temperate forest sites with observed soil efflux ranged from 4 to 10 years across different forest types. We then extrapolated the model to all temperate forests in the Northern Hemisphere (25-50°N) to investigate spatial controls on microbial and soil C dynamics. Both models captured the observed soil heterotrophic respiration (RH), yet no-dormancy model consistently exhibited large seasonal amplitude and overestimation in microbial biomass. Spatially, the total RH from temperate forests based on dormancy model amounts to 6.88PgC/yr, and 7.99PgC/yr based on no-dormancy model. However, no-dormancy model notably overestimated the ratio of microbial biomass to SOC. Spatial correlation analysis revealed key controls of soil C:N ratio on the active proportion of microbial biomass, whereas local dormancy is primarily controlled by soil moisture and temperature, indicating scale-dependent environmental and biotic controls on microbial and SOC dynamics. These developments should provide essential support to modeling future soil carbon dynamics and enhance the avenue for collaboration between empirical soil experiment and modeling in the sense that more microbial physiological measurements are needed to better constrain and evaluate the models.

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

    Directory of Open Access Journals (Sweden)

    Eilon Sharon

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

  16. Pattern Classification Using an Olfactory Model with PCA Feature Selection in Electronic Noses: Study and Application

    Directory of Open Access Journals (Sweden)

    Junbao Zheng

    2012-03-01

    Full Text Available Biologically-inspired models and algorithms are considered as promising sensor array signal processing methods for electronic noses. Feature selection is one of the most important issues for developing robust pattern recognition models in machine learning. This paper describes an investigation into the classification performance of a bionic olfactory model with the increase of the dimensions of input feature vector (outer factor as well as its parallel channels (inner factor. The principal component analysis technique was applied for feature selection and dimension reduction. Two data sets of three classes of wine derived from different cultivars and five classes of green tea derived from five different provinces of China were used for experiments. In the former case the results showed that the average correct classification rate increased as more principal components were put in to feature vector. In the latter case the results showed that sufficient parallel channels should be reserved in the model to avoid pattern space crowding. We concluded that 6~8 channels of the model with principal component feature vector values of at least 90% cumulative variance is adequate for a classification task of 3~5 pattern classes considering the trade-off between time consumption and classification rate.

  17. Robustness of digitally modulated signal features against variation in HF noise model

    Directory of Open Access Journals (Sweden)

    Shoaib Mobien

    2011-01-01

    Full Text Available Abstract High frequency (HF band has both military and civilian uses. It can be used either as a primary or backup communication link. Automatic modulation classification (AMC is of an utmost importance in this band for the purpose of communications monitoring; e.g., signal intelligence and spectrum management. A widely used method for AMC is based on pattern recognition (PR. Such a method has two main steps: feature extraction and classification. The first step is generally performed in the presence of channel noise. Recent studies show that HF noise could be modeled by Gaussian or bi-kappa distributions, depending on day-time. Therefore, it is anticipated that change in noise model will have impact on features extraction stage. In this article, we investigate the robustness of well known digitally modulated signal features against variation in HF noise. Specifically, we consider temporal time domain (TTD features, higher order cumulants (HOC, and wavelet based features. In addition, we propose new features extracted from the constellation diagram and evaluate their robustness against the change in noise model. This study is targeting 2PSK, 4PSK, 8PSK, 16QAM, 32QAM, and 64QAM modulations, as they are commonly used in HF communications.

  18. A Labeling Model Based on the Region of Movability for Point-Feature Label Placement

    Directory of Open Access Journals (Sweden)

    Lin Li

    2016-09-01

    Full Text Available Automatic point-feature label placement (PFLP is a fundamental task for map visualization. As the dominant solutions to the PFLP problem, fixed-position and slider models have been widely studied in previous research. However, the candidate labels generated with these models are set to certain fixed positions or a specified track line for sliding. Thus, the whole surrounding space of a point feature is not sufficiently used for labeling. Hence, this paper proposes a novel label model based on the region of movability, which comes from plane collision detection theory. The model defines a complete conflict-free search space for label placement. On the premise of no conflict with the point, line, and area features, the proposed model utilizes the surrounding zone of the point feature to generate candidate label positions. By combining with heuristic search method, the model achieves high-quality label placement. In addition, the flexibility of the proposed model enables placing arbitrarily shaped labels.

  19. GNAR-GARCH model and its application in feature extraction for rolling bearing fault diagnosis

    Science.gov (United States)

    Ma, Jiaxin; Xu, Feiyun; Huang, Kai; Huang, Ren

    2017-09-01

    Given its simplicity of modeling and sensitivity to condition variations, time series model is widely used in feature extraction to realize fault classification and diagnosis. However, nonlinear and nonstationary characteristics common in fault signals of rolling bearing bring challenges to the diagnosis. In this paper, a hybrid model, the combination of a general expression for linear and nonlinear autoregressive (GNAR) model and a generalized autoregressive conditional heteroscedasticity (GARCH) model, (i.e., GNAR-GARCH), is proposed and applied to rolling bearing fault diagnosis. An exact expression of GNAR-GARCH model is given. Maximum likelihood method is used for parameter estimation and modified Akaike Information Criterion is adopted for structure identification of GNAR-GARCH model. The main advantage of this novel model over other models is that the combination makes the model suitable for nonlinear and nonstationary signals. It is verified with statistical tests that contain comparisons among the different time series models. Finally, GNAR-GARCH model is applied to fault diagnosis by modeling mechanical vibration signals including simulation and real data. With the parameters estimated and taken as feature vectors, k-nearest neighbor algorithm is utilized to realize the classification of fault status. The results show that GNAR-GARCH model exhibits higher accuracy and better performance than do other models.

  20. Developmental programming: the concept, large animal models, and the key role of uteroplacental vascular development.

    Science.gov (United States)

    Reynolds, L P; Borowicz, P P; Caton, J S; Vonnahme, K A; Luther, J S; Hammer, C J; Maddock Carlin, K R; Grazul-Bilska, A T; Redmer, D A

    2010-04-01

    Developmental programming refers to the programming of various bodily systems and processes by a stressor of the maternal system during pregnancy or during the neonatal period. Such stressors include nutritional stress, multiple pregnancy (i.e., increased numbers of fetuses in the gravid uterus), environmental stress (e.g., high environmental temperature, high altitude, prenatal steroid exposure), gynecological immaturity, and maternal or fetal genotype. Programming refers to impaired function of numerous bodily systems or processes, leading to poor growth, altered body composition, metabolic dysfunction, and poor productivity (e.g., poor growth, reproductive dysfunction) of the offspring throughout their lifespan and even across generations. A key component of developmental programming seems to be placental dysfunction, leading to altered fetal growth and development. We discuss various large animal models of developmental programming and how they have and will continue to contribute to our understanding of the mechanisms underlying altered placental function and developmental programming, and, further, how large animal models also will be critical to the identification and application of therapeutic strategies that will alleviate the negative consequences of developmental programming to improve offspring performance in livestock production and human medicine.

  1. Key strategies for predictive exploration in mature environment: model innovation, exploration technology optimization and information integration

    Institute of Scientific and Technical Information of China (English)

    LIU Liang-ming; PENG Sheng-lin

    2005-01-01

    Prediction has become more and more difficult in mineral exploration, especially in the mature exploration environment such as Tongling copper district. For enhancing predictive discovery of hidden ore deposits in such mature environment, the key strategies which should be adopted include the innovation of the exploration models, application of the advanced exploration techniques and integration of multiple sets of information. The innovation of the exploration models should incorporate the new metallogenic concepts that are based on the geodynamic anatomization. The advanced techniques applied in the mature exploration environment should aim at the speciality and complexity of the geological setting and working environments. The information synthesis is to integrate multiple sets of data for giving a more credible and visual prospectivity map by using the geographic imformation system(GIS) and several mathematical methods, such as weight of evidence and fuzzy logic, which can extract useful information from every set of data as much as possible. Guided by these strategies, a predictive exploration in Fenghuangshan ore field of Tongling copper district was implemented, and a hidden ore deposit was discovered.

  2. Auditory-model-based Feature Extraction Method for Mechanical Faults Diagnosis

    Institute of Scientific and Technical Information of China (English)

    LI Yungong; ZHANG Jinping; DAI Li; ZHANG Zhanyi; LIU Jie

    2010-01-01

    It is well known that the human auditory system possesses remarkable capabilities to analyze and identify signals. Therefore, it would be significant to build an auditory model based on the mechanism of human auditory systems, which may improve the effects of mechanical signal analysis and enrich the methods of mechanical faults features extraction. However the existing methods are all based on explicit senses of mathematics or physics, and have some shortages on distinguishing different faults, stability, and suppressing the disturbance noise, etc. For the purpose of improving the performances of the work of feature extraction, an auditory model, early auditory(EA) model, is introduced for the first time. This auditory model transforms time domain signal into auditory spectrum via bandpass filtering, nonlinear compressing, and lateral inhibiting by simulating the principle of the human auditory system. The EA model is developed with the Gammatone filterbank as the basilar membrane. According to the characteristics of vibration signals, a method is proposed for determining the parameter of inner hair cells model of EA model. The performance of EA model is evaluated through experiments on four rotor faults, including misalignment, rotor-to-stator rubbing, oil film whirl, and pedestal looseness. The results show that the auditory spectrum, output of EA model, can effectively distinguish different faults with satisfactory stability and has the ability to suppress the disturbance noise. Then, it is feasible to apply auditory model, as a new method, to the feature extraction for mechanical faults diagnosis with effect.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-01-01

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

  4. Multi-resolution representation of digital terrain models with terrain features preservation

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    multi-resolution TIN model is an important issue in the contexts of visu-alization,virtual reality (VR),and geographic information systems (GIS). This paper proposes a new method for constructing multi-resolution TIN models with multi-scale topographic features preservation. The proposed method is driven by a half-edge collapse operation in a greedy framework and employs a new quadric error metric to efficiently measure geometric errors. We define topographic features in a multi-scale manner using a center-surround operator on Gaussian-weighted mean curvatures. Experimental results demonstrate that the proposed method performs better than previous methods in terms of topographic features preservation,and is able to achieve multi-resolution TIN models with a higher accuracy.

  5. Novel gamma-ray spectral features in the inert doublet model

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Cely, Camilo; Ibarra, Alejandro, E-mail: camilo.garcia@tum.de, E-mail: alejandro.ibarra@ph.tum.de [Physik-Department T30d, Technische Universität München, James-Franck-Straße, 85748 Garching (Germany)

    2013-09-01

    The inert doublet model contains a neutral stable particle which is an excellent dark matter candidate. We discuss in this paper the indirect signatures of this model in gamma-rays when the dark matter mass is larger than the W boson mass. We show that, in addition to the featureless gamma-ray spectrum produced in the annihilations into two weak gauge bosons, the model generically predicts a distinctive spectral feature from the internal bremsstrahlung process H{sup 0}H{sup 0}→W{sup +}W{sup −}γ. We discuss under which conditions the spectral feature is generated and we construct a number of benchmark points, compatible with the observed relic density and all other direct and indirect detection experiments, which lead to a sharp gamma-ray feature from internal bremsstrahlung.

  6. A Classifier Model based on the Features Quantitative Analysis for Facial Expression Recognition

    Directory of Open Access Journals (Sweden)

    Amir Jamshidnezhad

    2011-01-01

    Full Text Available In recent decades computer technology has considerable developed in use of intelligent systems for classification. The development of HCI systems is highly depended on accurate understanding of emotions. However, facial expressions are difficult to classify by a mathematical models because of natural quality. In this paper, quantitative analysis is used in order to find the most effective features movements between the selected facial feature points. Therefore, the features are extracted not only based on the psychological studies, but also based on the quantitative methods to arise the accuracy of recognitions. Also in this model, fuzzy logic and genetic algorithm are used to classify facial expressions. Genetic algorithm is an exclusive attribute of proposed model which is used for tuning membership functions and increasing the accuracy.

  7. Business models of sharing economy companies : exploring features responsible for sharing economy companies’ internationalization

    OpenAIRE

    Kosintceva, Aleksandra

    2016-01-01

    This paper is dedicated to the sharing economy business models and their features responsible for internationalization. The study proposes derived definitions for the concepts of “sharing economy” and “business model” and first generic sharing economy business models typology. The typology was created through the qualitative analysis of secondary data on twenty sharing economy companies from nine different industries. The outlined categories of sharing economy business models a...

  8. Orientation Modeling for Amateur Cameras by Matching Image Line Features and Building Vector Data

    Science.gov (United States)

    Hung, C. H.; Chang, W. C.; Chen, L. C.

    2016-06-01

    With the popularity of geospatial applications, database updating is getting important due to the environmental changes over time. Imagery provides a lower cost and efficient way to update the database. Three dimensional objects can be measured by space intersection using conjugate image points and orientation parameters of cameras. However, precise orientation parameters of light amateur cameras are not always available due to their costliness and heaviness of precision GPS and IMU. To automatize data updating, the correspondence of object vector data and image may be built to improve the accuracy of direct georeferencing. This study contains four major parts, (1) back-projection of object vector data, (2) extraction of image feature lines, (3) object-image feature line matching, and (4) line-based orientation modeling. In order to construct the correspondence of features between an image and a building model, the building vector features were back-projected onto the image using the initial camera orientation from GPS and IMU. Image line features were extracted from the imagery. Afterwards, the matching procedure was done by assessing the similarity between the extracted image features and the back-projected ones. Then, the fourth part utilized line features in orientation modeling. The line-based orientation modeling was performed by the integration of line parametric equations into collinearity condition equations. The experiment data included images with 0.06 m resolution acquired by Canon EOS Mark 5D II camera on a Microdrones MD4-1000 UAV. Experimental results indicate that 2.1 pixel accuracy may be reached, which is equivalent to 0.12 m in the object space.

  9. The SSB-positive/SSA-negative antibody profile is not associated with key phenotypic features of Sjögren's syndrome

    DEFF Research Database (Denmark)

    Baer, Alan N; McAdams DeMarco, Mara; Shiboski, Stephen C

    2015-01-01

    phenotypic features. Among SICCA participants classified with SS on the basis of the American-European Consensus Group or American College of Rheumatology criteria, only 2% required the anti-SSB-alone test result to meet these criteria. CONCLUSIONS: The presence of anti-SSB, without anti-SSA antibodies, had...

  10. Evaluation of Feature Selection Methods for Predictive Modeling Using Neural Networks in Credits Scoring

    Directory of Open Access Journals (Sweden)

    Raghavendra B. K

    2010-11-01

    Full Text Available A credit-risk evaluation decision involves processing huge volumes of raw data, and hence requires powerful data mining tools. Several techniques that were developed in machine learning have been used for financial credit-risk evaluation decisions. Data mining is the process of finding patterns and relations in large databases. Neural Networks are one of the popular tools for building predictive models in data mining. The major drawback of neural network is the curse of dimensionality which requires optimal feature subset. Feature selection is an important topic of research in data mining. Feature selection is the problem of choosing a small subset of features that optimally is necessary and sufficient to describe the target concept. In this research an attempt has been made to investigate the preprocessing framework for feature selection in credit scoring using neural network. Feature selection techniques like best first search, info gain etc. methods have been evaluated for the effectiveness of the classification of the risk groups on publicly available data sets. In particular, German, Australian, and Japanese credit rating data sets have been used for evaluation. The results have been conclusive about the effectiveness of feature selection for neural networks and validate the hypothesis of the research.

  11. Nonlinear model calibration of a shear wall building using time and frequency data features

    Science.gov (United States)

    Asgarieh, Eliyar; Moaveni, Babak; Barbosa, Andre R.; Chatzi, Eleni

    2017-02-01

    This paper investigates the effects of different factors on the performance of nonlinear model updating for a seven-story shear wall building model. The accuracy of calibrated models using different data features and modeling assumptions is studied by comparing the time and frequency responses of the models with the exact simulated ones. Simplified nonlinear finite element models of the shear wall building are calibrated so that the misfit between the considered response data features of the models and the structure is minimized. A refined FE model of the test structure, which was calibrated manually to match the shake table test data, is used instead of the real structure for this performance evaluation study. The simplified parsimonious FE models are composed of simple nonlinear beam-column fiber elements with nonlinearity infused in them by assigning generated hysteretic nonlinear material behaviors to uniaxial stress-strain relationship of the fibers. Four different types of data features and their combinations are used for model calibration: (1) time-varying instantaneous modal parameters, (2) displacement time histories, (3) acceleration time histories, and (4) dissipated hysteretic energy. It has been observed that the calibrated simplified FE models can accurately predict the nonlinear structural response in the absence of significant modeling errors. In the last part of this study, the physics-based models are further simplified for casting into state-space formulation and a real-time identification is performed using an Unscented Kalman filter. It has been shown that the performance of calibrated state-space models can be satisfactory when reasonable modeling assumptions are used.

  12. Elysium region, Mars - Tests of lithospheric loading models for the formation of tectonic features

    Science.gov (United States)

    Hall, J. Lynn; Solomon, Sean C.; Head, James W.

    1986-01-01

    The hypothesis that the tectonic features in the Elysium region are the product of stress produced by loading of the Martian lithosphere is tested. The lithospheric loading models for the formation of tectonic features in the Elysium region are evaluated under local loading, regional loading of the lithosphere from above and below, and quasi-global loading by Tharsis. The physiographic features in the Elysium region are described. The stress fields predicted by volcanic loading and uplift of the Martian lithosphere are compared with the tectonic features in the Elysium region. It is noted that the comparison suggests the succession of stress fields operating at different times in the region and supports the hypothesis.

  13. Multiscale vascular surface model generation from medical imaging data using hierarchical features.

    Science.gov (United States)

    Bekkers, Eric J; Taylor, Charles A

    2008-03-01

    Computational fluid dynamics (CFD) modeling of blood flow from image-based patient specific models can provide useful physiologic information for guiding clinical decision making. A novel method for the generation of image-based, 3-D, multiscale vascular surface models for CFD is presented. The method generates multiscale surfaces based on either a linear triangulated or a globally smooth nonuniform rational B-spline (NURB) representation. A robust local curvature analysis is combined with a novel global feature analysis to set mesh element size. The method is particularly useful for CFD modeling of complex vascular geometries that have a wide range of vasculature size scales, in conditions where 1) initial surface mesh density is an important consideration for balancing surface accuracy with manageable size volumetric meshes, 2) adaptive mesh refinement based on flow features makes an underlying explicit smooth surface representation desirable, and 3) semi-automated detection and trimming of a large number of inlet and outlet vessels expedites model construction.

  14. Specific features pertinent to modeling of hydraulic systems containing control members

    Science.gov (United States)

    Tverskoy, Yu. S.; Marshalov, E. D.

    2014-09-01

    The theoretical principles applied for modeling of hydraulic systems fitted with control members that allow a hydraulic line's specific features (topology) to be taken into account are considered. Such modeling opens the possibility to predict the actual flow (throttling) characteristics at early design stages and timely introduce the appropriate corrections in pipeline topology. The modeling problem is solved with the use of generalized thermodynamic analysis methods. The mathematical models of hydraulic systems containing control members are brought to the level of real-time simulation models, which can be used for setting up computation experiments for achieving better performance of automatic closed-loop control systems.

  15. Computer-aided design–computer-aided engineering associative feature-based heterogeneous object modeling

    Directory of Open Access Journals (Sweden)

    Jikai Liu

    2015-12-01

    Full Text Available Conventionally, heterogeneous object modeling methods paid limited attention to the concurrent modeling of geometry design and material composition distribution. Procedural method was normally employed to generate the geometry first and then determine the heterogeneous material distribution, which ignores the mutual influence. Additionally, limited capability has been established about irregular material composition distribution modeling with strong local discontinuities. This article overcomes these limitations by developing the computer-aided design–computer-aided engineering associative feature-based heterogeneous object modeling method. Level set functions are applied to model the geometry within computer-aided design module, which enables complex geometry modeling. Finite element mesh is applied to store the local material compositions within computer-aided engineering module, which allows any local discontinuities. Then, the associative feature concept builds the correspondence relationship between these modules. Additionally, the level set geometry and material optimization method are developed to concurrently generate the geometry and material information which fills the contents of the computer-aided design–computer-aided engineering associative feature model. Micro-geometry is investigated as well, instead of only the local material composition. A few cases are studied to prove the effectiveness of this new heterogeneous object modeling method.

  16. Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification

    Science.gov (United States)

    Liu, Da; Li, Jianxun

    2016-01-01

    Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches. PMID:27999259

  17. Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.

    Science.gov (United States)

    Liu, Da; Li, Jianxun

    2016-12-16

    Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches.

  18. On a Variational Model for Selective Image Segmentation of Features with Infinite Perimeter

    Institute of Scientific and Technical Information of China (English)

    Lavdie RADA; Ke CHEN

    2013-01-01

    Variational models provide reliable formulation for segmentation of features and their boundaries in an image,following the seminal work of Mumford-Shah (1989,Commun.Pure Appl.Math.) on dividing a general surface into piecewise smooth sub-surfaces.A central idea of models based on this work is to minimize the length of feature's boundaries (i.e.,(H)1 Hausdorff measure).However there exist problems with irregular and oscillatory object boundaries,where minimizing such a length is not appropriate,as noted by Barchiesi et al.(2010,SIAM J.Multiscale Model.Simu.) who proposed to miminize (L)2 Lebesgue measure of the γ-neighborhood of the boundaries.This paper presents a dual level set selective segmentation model based on Barchiesi et al.(2010) to automatically select a local feature instead of all global features.Our model uses two level set functions:a global level set which segments all boundaries,and the local level set which evolves and finds the boundary of the object closest to the geometric constraints.Using real life images with oscillatory boundaries,we show qualitative results demonstrating the effectiveness of the proposed method.

  19. Comprehensible Predictive Modeling Using Regularized Logistic Regression and Comorbidity Based Features.

    Directory of Open Access Journals (Sweden)

    Gregor Stiglic

    Full Text Available Different studies have demonstrated the importance of comorbidities to better understand the origin and evolution of medical complications. This study focuses on improvement of the predictive model interpretability based on simple logical features representing comorbidities. We use group lasso based feature interaction discovery followed by a post-processing step, where simple logic terms are added. In the final step, we reduce the feature set by applying lasso logistic regression to obtain a compact set of non-zero coefficients that represent a more comprehensible predictive model. The effectiveness of the proposed approach was demonstrated on a pediatric hospital discharge dataset that was used to build a readmission risk estimation model. The evaluation of the proposed method demonstrates a reduction of the initial set of features in a regression model by 72%, with a slight improvement in the Area Under the ROC Curve metric from 0.763 (95% CI: 0.755-0.771 to 0.769 (95% CI: 0.761-0.777. Additionally, our results show improvement in comprehensibility of the final predictive model using simple comorbidity based terms for logistic regression.

  20. iPSC-Based Models to Unravel Key Pathogenetic Processes Underlying Motor Neuron Disease Development

    Directory of Open Access Journals (Sweden)

    Irene Faravelli

    2014-10-01

    Full Text Available Motor neuron diseases (MNDs are neuromuscular disorders affecting rather exclusively upper motor neurons (UMNs and/or lower motor neurons (LMNs. The clinical phenotype is characterized by muscular weakness and atrophy leading to paralysis and almost invariably death due to respiratory failure. Adult MNDs include sporadic and familial amyotrophic lateral sclerosis (sALS-fALS, while the most common infantile MND is represented by spinal muscular atrophy (SMA. No effective treatment is ccurrently available for MNDs, as for the vast majority of neurodegenerative disorders, and cures are limited to supportive care and symptom relief. The lack of a deep understanding of MND pathogenesis accounts for the difficulties in finding a cure, together with the scarcity of reliable in vitro models. Recent progresses in stem cell field, in particular in the generation of induced Pluripotent Stem Cells (iPSCs has made possible for the first time obtaining substantial amounts of human cells to recapitulate in vitro some of the key pathogenetic processes underlying MNDs. In the present review, recently published studies involving the use of iPSCs to unravel aspects of ALS and SMA pathogenesis are discussed with an overview of their implications in the process of finding a cure for these still orphan disorders.

  1. Modelling management process of key drivers for economic sustainability in the modern conditions of economic development

    Directory of Open Access Journals (Sweden)

    Pishchulina E.S.

    2017-01-01

    Full Text Available The text is about issues concerning the management of driver for manufacturing enterprise economic sustainability and manufacturing enterprise sustainability assessment as the key aspect of the management of enterprise economic sustainability. The given issues become topical as new requirements for the methods of manufacturing enterprise management in the modern conditions of market economy occur. An economic sustainability model that is considered in the article is an integration of enterprise economic growth, economic balance of external and internal environment and economic sustainability. The method of assessment of economic sustainability of a manufacturing enterprise proposed in the study allows to reveal some weaknesses in the enterprise performance, and untapped reserves, which can be further used to improve the economic sustainability and efficiency of the enterprise. The management of manufacturing enterprise economic sustainability is one of the most important factors of business functioning and development in modern market economy. The relevance of this trend is increasing in accordance with the objective requirements of the growing volumes of production and sale, the increasing complexity of economic relations, changing external environment of an enterprise.

  2. Precision tests of the Standard Model using key observables of $CP$ violation and rare decays

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00346274; Albrecht, Johannes

    In this thesis advanced statistical methods are used for precision studies in the flavour sector of the Standard Model of particle physics. The necessary tools are developed and applied to two key measurements of the LHCb experiment: the determination of the CKM angle $\\gamma$ and the search for rare $B^{0} _{s} \\to \\mu^+ \\mu^-$ and $B^0 \\to \\mu^+ \\mu^-$ decays. The CKM angle $\\gamma$ is, for the first time, measured from $B^0 _s \\to D^\\mp _s K^\\pm$ decays using a dataset corresponding to $1\\,\\mathrm{fb}^{-1}$ of $pp$ interactions at a centre-of-mass energy of $\\sqrt{s} = 7\\mathrm{TeV}$. The result of $\\gamma = (115^{+27}_{-43})^{\\circ}$ is then combined with a set of $\\gamma$ measurements in ${B} \\to Dh$ decays resulting in a precision on $\\gamma$ of $<8^{\\circ}$. This result improves the legacy results from the $B$-factories by more than a factor of two. The rare decays $B^{0} _{s} \\to \\mu^+ \\mu^-$ and $B^0 \\to \\mu^+ \\mu^-$ are analysed on a dataset corresponding to $3\\,\\mathrm{fb}^{-1}$ of $pp$ interac...

  3. Imbalanced Insulin Actions in Obesity and Type 2 Diabetes: Key Mouse Models of Insulin Signaling Pathway.

    Science.gov (United States)

    Kubota, Tetsuya; Kubota, Naoto; Kadowaki, Takashi

    2017-04-04

    Since the discovery of the tyrosine kinase activity of the insulin receptor (IR), researchers have been engaged in intensive efforts to resolve physiological functions of IR and its major downstream targets, insulin receptor substrate 1 (Irs1) and Irs2. Studies conducted using systemic and tissue-specific gene-knockout mice of IR, Irs1, and Irs2 have revealed the physiological roles of these molecules in each tissue and interactions among multiple tissues. In obesity and type 2 diabetes, selective downregulation of Irs2 and its downstream actions to cause reduced insulin actions was associated with increased insulin actions through Irs1 in variety tissues. Thus, we propose the novel concept of "organ- and pathway-specific imbalanced insulin action" in obesity and type 2 diabetes, which includes and extends "selective insulin resistance." This Review focuses on recent progress in understanding insulin signaling and insulin resistance using key mouse models for elucidating pathophysiology of human obesity and type 2 diabetes. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Modeling and analysis of PM2.5 generation for key factors identification in China

    Science.gov (United States)

    Xia, Dehong; Jiang, Binfan; Xie, Yulei

    2016-06-01

    Recently, the PM2.5 pollution in China has occurred frequently and caused widely concern. In order to identify the key factors for PM2.5 generation, the formation characteristics of PM2.5 would be revealed. A property of electric neutrality of PM2.5 was proposed under the least-energy principle and verified through electricity-charge calculation in this paper. It indicated that PM2.5 is formed by the effect of electromagnetic force, including the effect of ionic bond, hydrogen bond and polarization. According to the analysis of interactive forces among different chemical components, a simulation model is developed for describing the random process of PM2.5 generation. In addition, an orthogonal test with two levels and four factors has been designed and carried out through the proposed model. From the text analysis, PM2.5 would be looser and suspend longer in atmosphere due to Organic Compound (OC) existing (OC can reduce about 67% of PM2.5 density). Considering that NH4+ is the only cation in the main chemical components of PM2.5, it would be vital for anions (such as SO42- and NO3-) to aggregate together for facilitating PM2.5 growing. Therefore, in order to relieve PM2.5 pollution, control strategies for OC and NH4+ would be enhanced by government through improving the quality of oils and solvent products, decreasing the amount of nitrogenous fertilizer utilization, or changing the fertilizing environment from dry condition to wet condition.

  5. Dynamic Arm Gesture Recognition Using Spherical Angle Features and Hidden Markov Models

    Directory of Open Access Journals (Sweden)

    Hyesuk Kim

    2015-01-01

    Full Text Available We introduce a vision-based arm gesture recognition (AGR system using Kinect. The AGR system learns the discrete Hidden Markov Model (HMM, an effective probabilistic graph model for gesture recognition, from the dynamic pose of the arm joints provided by the Kinect API. Because Kinect’s viewpoint and the subject’s arm length can substantially affect the estimated 3D pose of each joint, it is difficult to recognize gestures reliably with these features. The proposed system performs the feature transformation that changes the 3D Cartesian coordinates of each joint into the 2D spherical angles of the corresponding arm part to obtain view-invariant and more discriminative features. We confirmed high recognition performance of the proposed AGR system through experiments with two different datasets.

  6. Model of the Students' Key Competences Development through Interactive Whiteboard in the Subject of Technology

    Science.gov (United States)

    Brecka, Peter; Valentová, Monika

    2017-01-01

    The basis of the submitted study are the continuously rising demands to alter the curricula with the aim to develop students' key competences in order to increase their professional versatility. The lack of scientific research and discussions show that little investigation has been done on the issue of development of key competences. Therefore,…

  7. Short-Term Solar Irradiance Forecasting Model Based on Artificial Neural Network Using Statistical Feature Parameters

    Directory of Open Access Journals (Sweden)

    Hongshan Zhao

    2012-05-01

    Full Text Available Short-term solar irradiance forecasting (STSIF is of great significance for the optimal operation and power predication of grid-connected photovoltaic (PV plants. However, STSIF is very complex to handle due to the random and nonlinear characteristics of solar irradiance under changeable weather conditions. Artificial Neural Network (ANN is suitable for STSIF modeling and many research works on this topic are presented, but the conciseness and robustness of the existing models still need to be improved. After discussing the relation between weather variations and irradiance, the characteristics of the statistical feature parameters of irradiance under different weather conditions are figured out. A novel ANN model using statistical feature parameters (ANN-SFP for STSIF is proposed in this paper. The input vector is reconstructed with several statistical feature parameters of irradiance and ambient temperature. Thus sufficient information can be effectively extracted from relatively few inputs and the model complexity is reduced. The model structure is determined by cross-validation (CV, and the Levenberg-Marquardt algorithm (LMA is used for the network training. Simulations are carried out to validate and compare the proposed model with the conventional ANN model using historical data series (ANN-HDS, and the results indicated that the forecast accuracy is obviously improved under variable weather conditions.

  8. A Study of the Key Elements in the Jerome Model, the Horace Model and the Schleiermacher Model

    Institute of Scientific and Technical Information of China (English)

    都潇潇

    2016-01-01

    There are Two very popular and important translation models, namely the Jerome Model, the Horace Model , which can be thought to be the forerunner of the translation theory nowadays. They share one common concept—faithfulness. the Two models are discussed one by one to aim at pointing out the main differences and similarities, from which we can learn more and do better translation in our studies and works. Finally, the paper draws a conclusion that no single translation model is really better than another because the criteria of translation are dynamic rather than static.

  9. The consensus in the two-feature two-state one-dimensional Axelrod model revisited

    CERN Document Server

    Biral, Elias J P; Fontanari, José F

    2015-01-01

    The Axelrod model for the dissemination of culture exhibits a rich spatial distribution of cultural domains, which depends on the values of the two model parameters: $F$, the number of cultural features and $q$, the number of states each feature can assume. In the one-dimensional model with $F=q=2$, which is equivalent to the constrained voter model, Monte Carlo simulations indicate the existence of multicultural absorbing configurations in which at least one macroscopic domain coexist with a multitude of microscopic ones in the thermodynamic limit. However, rigorous analytical results for an infinite system indicate the existence of only monocultural or consensus configurations at equilibrium. Here we show that this disagreement is due simply to the different orders that the time-asymptotic limit and the thermodynamic limit are taken in those two approaches. In addition, we show how the consensus-only result can be derived using Monte Carlo simulations of finite chains.

  10. Combining Model-Based and Feature-Driven Diagnosis Approaches - A Case Study on Electromechanical Actuators

    Science.gov (United States)

    Narasimhan, Sriram; Roychoudhury, Indranil; Balaban, Edward; Saxena, Abhinav

    2010-01-01

    Model-based diagnosis typically uses analytical redundancy to compare predictions from a model against observations from the system being diagnosed. However this approach does not work very well when it is not feasible to create analytic relations describing all the observed data, e.g., for vibration data which is usually sampled at very high rates and requires very detailed finite element models to describe its behavior. In such cases, features (in time and frequency domains) that contain diagnostic information are extracted from the data. Since this is a computationally intensive process, it is not efficient to extract all the features all the time. In this paper we present an approach that combines the analytic model-based and feature-driven diagnosis approaches. The analytic approach is used to reduce the set of possible faults and then features are chosen to best distinguish among the remaining faults. We describe an implementation of this approach on the Flyable Electro-mechanical Actuator (FLEA) test bed.

  11. An Exemplar-Model Account of Feature Inference from Uncertain Categorizations

    Science.gov (United States)

    Nosofsky, Robert M.

    2015-01-01

    In a highly systematic literature, researchers have investigated the manner in which people make feature inferences in paradigms involving uncertain categorizations (e.g., Griffiths, Hayes, & Newell, 2012; Murphy & Ross, 1994, 2007, 2010a). Although researchers have discussed the implications of the results for models of categorization and…

  12. Metallogenic Features and Metalogenic Model of Laterite Gold Deposits in Southern China

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The modern laterite gold deposits in southern China, which belong to reworked laterite deposits, can be further divided into three subclasses and seven types. Their geological features, ore-forming conditions and regularities are discussed. A geologic-geochemical metallogenic model for laterite gold deposits has been established.

  13. Finite element modeling of small-scale tapered wood-laminated composite poles with biomimicry features

    Science.gov (United States)

    Cheng Piao; Todd F. Shupe; R.C. Tang; Chung Y. Hse

    2008-01-01

    Tapered composite poles with biomimicry features as in bamboo are a new generation of wood laminated composite poles that may some day be considered as an alternative to solid wood poles that are widely used in the transmission and telecommunication fields. Five finite element models were developed with ANSYS to predict and assess the performance of five types of...

  14. Understanding of a Key Aspect of Situation Awareness: A Research and Development Agenda to Refine the Model of Spatial Orientation

    Science.gov (United States)

    2017-07-10

    USAARL Report No. 2017-14 Understanding of a Key Aspect of Situation Awareness: A Research and Development Agenda to Refine the Model of Spatial...Understanding of a Key Aspect of Situation Awareness: a Research and Development Agenda to Refine the Model of Spatial Orientation N/A N/A N/A N/A N/A N/A Lawson...supporting the initial model development for military applications by authors Newman, Lawson, and Rupert.  Small Business Innovative Research program

  15. A short-term mouse model that reproduces the immunopathological features of rhinovirus-induced exacerbation of COPD.

    Science.gov (United States)

    Singanayagam, Aran; Glanville, Nicholas; Walton, Ross P; Aniscenko, Julia; Pearson, Rebecca M; Pinkerton, James W; Horvat, Jay C; Hansbro, Philip M; Bartlett, Nathan W; Johnston, Sebastian L

    2015-08-01

    Viral exacerbations of chronic obstructive pulmonary disease (COPD), commonly caused by rhinovirus (RV) infections, are poorly controlled by current therapies. This is due to a lack of understanding of the underlying immunopathological mechanisms. Human studies have identified a number of key immune responses that are associated with RV-induced exacerbations including neutrophilic inflammation, expression of inflammatory cytokines and deficiencies in innate anti-viral interferon. Animal models of COPD exacerbation are required to determine the contribution of these responses to disease pathogenesis. We aimed to develop a short-term mouse model that reproduced the hallmark features of RV-induced exacerbation of COPD. Evaluation of complex protocols involving multiple dose elastase and lipopolysaccharide (LPS) administration combined with RV1B infection showed suppression rather than enhancement of inflammatory parameters compared with control mice infected with RV1B alone. Therefore, these approaches did not accurately model the enhanced inflammation associated with RV infection in patients with COPD compared with healthy subjects. In contrast, a single elastase treatment followed by RV infection led to heightened airway neutrophilic and lymphocytic inflammation, increased expression of tumour necrosis factor (TNF)-α, C-X-C motif chemokine 10 (CXCL10)/IP-10 (interferon γ-induced protein 10) and CCL5 [chemokine (C-C motif) ligand 5]/RANTES (regulated on activation, normal T-cell expressed and secreted), mucus hypersecretion and preliminary evidence for increased airway hyper-responsiveness compared with mice treated with elastase or RV infection alone. In summary, we have developed a new mouse model of RV-induced COPD exacerbation that mimics many of the inflammatory features of human disease. This model, in conjunction with human models of disease, will provide an essential tool for studying disease mechanisms and allow testing of novel therapies with potential to

  16. 基于关键帧多特征融合的视频拷贝检测%Video Copy Detection Based on Key Frame Multi-feature Fusion

    Institute of Scientific and Technical Information of China (English)

    张兴忠; 李皓; 张三义

    2015-01-01

    Retrieval speed is an important issue in video copy detection .This paper proposed a fast video copy detection method ,w hich uses a local sensitive hashing index to achive fast retriev‐al by mapping videos with similar clips into the same buckets ,and combines multi‐features of key frames to achieve high accuracy .To improve retrieval accuracy ,the method extracts key frames by using shot segmentation techniques ,and then obtains the Hilbert feature based on key points , ordinal measure feature and ORB (Oriented FAST and Rotated BRIEF ) feature from key frames . This allows the method make full use of both local features and global features .The hash index is built by hash the combined features .Experimental results show that this proposed method not only achieves high precision and recall rate ,but also has high spead .%针对视频拷贝检测中检索速度问题,提出一种基于关键帧多特征融合的类局部敏感哈希索引方法,将存在拷贝片段的视频映射到同一个哈希桶中,减少检索的范围,达到提高检索速度的目的。该算法首先对视频进行镜头分割提取关键帧,为了提高检测精度,分别提取了灰度序全局特征、基于关键点的希尔伯特特征、ORB(Oriented FAST and Rotated BRIEF )局部特征,综合利用全局特征和局部特征两者各自的优势;然后根据视频关键帧序列建立了类局部敏感哈希索引,利用建立好的索引获得拷贝检测结果。实验结果表明,该方法在保证检测精度的同时,速度上也有很大提升,具有重要的应用价值。

  17. From conceptual model to remediation: bioavailability, a key to clean up heavy metal contaminated soils.

    Science.gov (United States)

    Petruzzelli, Gianniantonio; Pedron, Francesca; Pezzarossa, Beatrice

    2013-04-01

    that aim to increase the bioavailability of pollutants are used in technologies which remove or destroy the solubilized contaminants. These procedures can increase mass transfer from the absorbed phase by means of sieving in order to decrease the diffusion processes (soil washing), by increasing the temperature (low temperature thermal desorption), or through the addition of chemical additives, such as chelating agents (Phytoextraction Elektrokinetic remediation). Concluding remarks Bioavailability should be a key component of the exposure evaluation in order to develop the conceptual model and to select the technology, in particular when: • only some chemical forms of contaminants are a source of risk for the site; • default assumptions regarding bioavailability are not suitable because of the site's specific characteristics; • the final destination of the site will not be modified at least in the near future.

  18. Integration of Error Compensation of Coordinate Measuring Machines into Feature Measurement: Part I—Model Development

    Directory of Open Access Journals (Sweden)

    Roque Calvo

    2016-09-01

    Full Text Available The development of an error compensation model for coordinate measuring machines (CMMs and its integration into feature measurement is presented. CMMs are widespread and dependable instruments in industry and laboratories for dimensional measurement. From the tip probe sensor to the machine display, there is a complex transformation of probed point coordinates through the geometrical feature model that makes the assessment of accuracy and uncertainty measurement results difficult. Therefore, error compensation is not standardized, conversely to other simpler instruments. Detailed coordinate error compensation models are generally based on CMM as a rigid-body and it requires a detailed mapping of the CMM’s behavior. In this paper a new model type of error compensation is proposed. It evaluates the error from the vectorial composition of length error by axis and its integration into the geometrical measurement model. The non-explained variability by the model is incorporated into the uncertainty budget. Model parameters are analyzed and linked to the geometrical errors and uncertainty of CMM response. Next, the outstanding measurement models of flatness, angle, and roundness are developed. The proposed models are useful for measurement improvement with easy integration into CMM signal processing, in particular in industrial environments where built-in solutions are sought. A battery of implementation tests are presented in Part II, where the experimental endorsement of the model is included.

  19. Efficient feature selection and multiclass classification with integrated instance and model based learning.

    Science.gov (United States)

    Liu, Zhenqiu; Bensmail, Halima; Tan, Ming

    2012-01-01

    Multiclass classification and feature (variable) selections are commonly encountered in many biological and medical applications. However, extending binary classification approaches to multiclass problems is not trivial. Instance-based methods such as the K nearest neighbor (KNN) can naturally extend to multiclass problems and usually perform well with unbalanced data, but suffer from the curse of dimensionality. Their performance is degraded when applied to high dimensional data. On the other hand, model-based methods such as logistic regression require the decomposition of the multiclass problem into several binary problems with one-vs.-one or one-vs.-rest schemes. Even though they can be applied to high dimensional data with L(1) or L(p) penalized methods, such approaches can only select independent features and the features selected with different binary problems are usually different. They also produce unbalanced classification problems with one vs. the rest scheme even if the original multiclass problem is balanced.By combining instance-based and model-based learning, we propose an efficient learning method with integrated KNN and constrained logistic regression (KNNLog) for simultaneous multiclass classification and feature selection. Our proposed method simultaneously minimizes the intra-class distance and maximizes the interclass distance with fewer estimated parameters. It is very efficient for problems with small sample size and unbalanced classes, a case common in many real applications. In addition, our model-based feature selection methods can identify highly correlated features simultaneously avoiding the multiplicity problem due to multiple tests. The proposed method is evaluated with simulation and real data including one unbalanced microRNA dataset for leukemia and one multiclass metagenomic dataset from the Human Microbiome Project (HMP). It performs well with limited computational experiments.

  20. Solid images for geostructural mapping and key block modeling of rock discontinuities

    Science.gov (United States)

    Assali, Pierre; Grussenmeyer, Pierre; Villemin, Thierry; Pollet, Nicolas; Viguier, Flavien

    2016-04-01

    Rock mass characterization is obviously a key element in rock fall hazard analysis. Managing risk and determining the most adapted reinforcement method require a proper understanding of the considered rock mass. Description of discontinuity sets is therefore a crucial first step in the reinforcement work design process. The on-field survey is then followed by a structural modeling in order to extrapolate the data collected at the rock surface to the inner part of the massif. Traditional compass survey and manual observations can be undoubtedly surpassed by dense 3D data such as LiDAR or photogrammetric point clouds. However, although the acquisition phase is quite fast and highly automated, managing, handling and exploiting such great amount of collected data is an arduous task and especially for non specialist users. In this study, we propose a combined approached using both 3D point clouds (from LiDAR or image matching) and 2D digital images, gathered into the concept of ''solid image''. This product is the connection between the advantages of classical true colors 2D digital images, accessibility and interpretability, and the particular strengths of dense 3D point clouds, i.e. geometrical completeness and accuracy. The solid image can be considered as the information support for carrying-out a digital survey at the surface of the outcrop without being affected by traditional deficiencies (lack of data and sampling difficulties due to inaccessible areas, safety risk in steep sectors, etc.). Computational tools presented in this paper have been implemented into one standalone software through a graphical user interface helping operators with the completion of a digital geostructural survey and analysis. 3D coordinates extraction, 3D distances and area measurement, planar best-fit for discontinuity orientation, directional roughness profiles, block size estimation, and other tools have been experimented on a calcareous quarry in the French Alps.

  1. Model-based defect detection on structured surfaces having optically unresolved features.

    Science.gov (United States)

    O'Connor, Daniel; Henning, Andrew J; Sherlock, Ben; Leach, Richard K; Coupland, Jeremy; Giusca, Claudiu L

    2015-10-20

    In this paper, we demonstrate, both numerically and experimentally, a method for the detection of defects on structured surfaces having optically unresolved features. The method makes use of synthetic reference data generated by an observational model that is able to simulate the response of the selected optical inspection system to the ideal structure, thereby providing an ideal measure of deviation from nominal geometry. The method addresses the high dynamic range challenge faced in highly parallel manufacturing by enabling the use of low resolution, wide field of view optical systems for defect detection on surfaces containing small features over large regions.

  2. Highly accurate SVM model with automatic feature selection for word sense disambiguation

    Institute of Scientific and Technical Information of China (English)

    王浩; 陈贵林; 吴连献

    2004-01-01

    A novel algorithm for word sense disambiguation(WSD) that is based on SVM model improved with automatic feature selection is introduced. This learning method employs rich contextual features to predict the proper senses for specific words. Experimental results show that this algorithm can achieve an execellent performance on the set of data released during the SENSEEVAL-2 competition. We present the results obtained and discuss the transplantation of this algorithm to other languages such as Chinese. Experimental results on Chinese corpus show that our algorithm achieves an accuracy of 70.0 % even with small training data.

  3. Model predictions of features in microsaccade-related neural responses in a feedforward network with short-term synaptic depression.

    Science.gov (United States)

    Zhou, Jian-Fang; Yuan, Wu-Jie; Zhou, Zhao; Zhou, Changsong

    2016-02-08

    Recently, the significant microsaccade-induced neural responses have been extensively observed in experiments. To explore the underlying mechanisms of the observed neural responses, a feedforward network model with short-term synaptic depression has been proposed [Yuan, W.-J., Dimigen, O., Sommer, W. and Zhou, C. Front. Comput. Neurosci. 7, 47 (2013)]. The depression model not only gave an explanation for microsaccades in counteracting visual fading, but also successfully reproduced several microsaccade-related features in experimental findings. These results strongly suggest that, the depression model is very useful to investigate microsaccade-related neural responses. In this paper, by using the model, we extensively study and predict the dependance of microsaccade-related neural responses on several key parameters, which could be tuned in experiments. Particularly, we provide a significant prediction that microsaccade-related neural response also complies with the property "sharper is better" observed in many contexts in neuroscience. Importantly, the property exhibits a power-law relationship between the width of input signal and the responsive effectiveness, which is robust against many parameters in the model. By using mean field theory, we analytically investigate the robust power-law property. Our predictions would give theoretical guidance for further experimental investigations of the functional role of microsaccades in visual information processing.

  4. A general gridding, discretization, and coarsening methodology for modeling flow in porous formations with discrete geological features

    Science.gov (United States)

    Karimi-Fard, M.; Durlofsky, L. J.

    2016-10-01

    A comprehensive framework for modeling flow in porous media containing thin, discrete features, which could be high-permeability fractures or low-permeability deformation bands, is presented. The key steps of the methodology are mesh generation, fine-grid discretization, upscaling, and coarse-grid discretization. Our specialized gridding technique combines a set of intersecting triangulated surfaces by constructing approximate intersections using existing edges. This procedure creates a conforming mesh of all surfaces, which defines the internal boundaries for the volumetric mesh. The flow equations are discretized on this conforming fine mesh using an optimized two-point flux finite-volume approximation. The resulting discrete model is represented by a list of control-volumes with associated positions and pore-volumes, and a list of cell-to-cell connections with associated transmissibilities. Coarse models are then constructed by the aggregation of fine-grid cells, and the transmissibilities between adjacent coarse cells are obtained using flow-based upscaling procedures. Through appropriate computation of fracture-matrix transmissibilities, a dual-continuum representation is obtained on the coarse scale in regions with connected fracture networks. The fine and coarse discrete models generated within the framework are compatible with any connectivity-based simulator. The applicability of the methodology is illustrated for several two- and three-dimensional examples. In particular, we consider gas production from naturally fractured low-permeability formations, and transport through complex fracture networks. In all cases, highly accurate solutions are obtained with significant model reduction.

  5. Gliovascular disruption and cognitive deficits in a mouse model with features of small vessel disease.

    Science.gov (United States)

    Holland, Philip R; Searcy, James L; Salvadores, Natalia; Scullion, Gillian; Chen, Guiquan; Lawson, Greig; Scott, Fiona; Bastin, Mark E; Ihara, Masafumi; Kalaria, Rajesh; Wood, Emma R; Smith, Colin; Wardlaw, Joanna M; Horsburgh, Karen

    2015-06-01

    Cerebral small vessel disease (SVD) is a major cause of age-related cognitive impairment and dementia. The pathophysiology of SVD is not well understood and is hampered by a limited range of relevant animal models. Here, we describe gliovascular alterations and cognitive deficits in a mouse model of sustained cerebral hypoperfusion with features of SVD (microinfarcts, hemorrhage, white matter disruption) induced by bilateral common carotid stenosis. Multiple features of SVD were determined on T2-weighted and diffusion-tensor magnetic resonance imaging scans and confirmed by pathologic assessment. These features, which were absent in sham controls, included multiple T2-hyperintense infarcts and T2-hypointense hemosiderin-like regions in subcortical nuclei plus increased cerebral atrophy compared with controls. Fractional anisotropy was also significantly reduced in several white matter structures including the corpus callosum. Investigation of gliovascular changes revealed a marked increase in microvessel diameter, vascular wall disruption, fibrinoid necrosis, hemorrhage, and blood-brain barrier alterations. Widespread reactive gliosis, including displacement of the astrocytic water channel, aquaporin 4, was observed. Hypoperfused mice also demonstrated deficits in spatial working and reference memory tasks. Overall, gliovascular disruption is a prominent feature of this mouse, which could provide a useful model for early-phase testing of potential SVD treatment strategies.

  6. Different developmental trajectories across feature types support a dynamic field model of visual working memory development.

    Science.gov (United States)

    Simmering, Vanessa R; Miller, Hilary E; Bohache, Kevin

    2015-05-01

    Research on visual working memory has focused on characterizing the nature of capacity limits as "slots" or "resources" based almost exclusively on adults' performance with little consideration for developmental change. Here we argue that understanding how visual working memory develops can shed new light onto the nature of representations. We present an alternative model, the Dynamic Field Theory (DFT), which can capture effects that have been previously attributed either to "slot" or "resource" explanations. The DFT includes a specific developmental mechanism to account for improvements in both resolution and capacity of visual working memory throughout childhood. Here we show how development in the DFT can account for different capacity estimates across feature types (i.e., color and shape). The current paper tests this account by comparing children's (3, 5, and 7 years of age) performance across different feature types. Results showed that capacity for colors increased faster over development than capacity for shapes. A second experiment confirmed this difference across feature types within subjects, but also showed that the difference can be attenuated by testing memory for less familiar colors. Model simulations demonstrate how developmental changes in connectivity within the model-purportedly arising through experience-can capture differences across feature types.

  7. Enhanced retinal modeling for face recognition and facial feature point detection under complex illumination conditions

    Science.gov (United States)

    Cheng, Yong; Li, Zuoyong; Jiao, Liangbao; Lu, Hong; Cao, Xuehong

    2016-07-01

    We improved classic retinal modeling to alleviate the adverse effect of complex illumination on face recognition and extracted robust image features. Our improvements on classic retinal modeling included three aspects. First, a combined filtering scheme was applied to simulate functions of horizontal and amacrine cells for accurate local illumination estimation. Second, we developed an optimal threshold method for illumination classification. Finally, we proposed an adaptive factor acquisition model based on the arctangent function. Experimental results on the combined Yale B; the Carnegie Mellon University poses, illumination, and expression; and the Labeled Face Parts in the Wild databases show that the proposed method can effectively alleviate illumination difference of images under complex illumination conditions, which is helpful for improving the accuracy of face recognition and that of facial feature point detection.

  8. Learning to Automatically Detect Features for Mobile Robots Using Second-Order Hidden Markov Models

    Directory of Open Access Journals (Sweden)

    Olivier Aycard

    2004-12-01

    Full Text Available In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features. Hidden Markov Models have been used for a long time in pattern recognition, especially in speech recognition. Their main advantages over other methods (such as neural networks are their ability to model noisy temporal signals of variable length. We show in this paper that this approach is well suited for interpretation of temporal sequences of mobile-robot sensor data. We present two distinct experiments and results: the first one in an indoor environment where a mobile robot learns to detect features like open doors or T-intersections, the second one in an outdoor environment where a different mobile robot has to identify situations like climbing a hill or crossing a rock.

  9. Learning to Automatically Detect Features for Mobile Robots Using Second-Order Hidden Markov Models

    Directory of Open Access Journals (Sweden)

    Richard Washington

    2008-11-01

    Full Text Available In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features. Hidden Markov Models have been used for a long time in pattern recognition, especially in speech recognition. Their main advantages over other methods (such as neural networks are their ability to model noisy temporal signals of variable length. We show in this paper that this approach is well suited for interpretation of temporal sequences of mobile-robot sensor data. We present two distinct experiments and results: the first one in an indoor environment where a mobile robot learns to detect features like open doors or T- intersections, the second one in an outdoor environment where a different mobile robot has to identify situations like climbing a hill or crossing a rock.

  10. A Modeling Approach for Burn Scar Assessment Using Natural Features and Elastic Property

    Energy Technology Data Exchange (ETDEWEB)

    Tsap, L V; Zhang, Y; Goldgof, D B; Sarkar, S

    2004-04-02

    A modeling approach is presented for quantitative burn scar assessment. Emphases are given to: (1) constructing a finite element model from natural image features with an adaptive mesh, and (2) quantifying the Young's modulus of scars using the finite element model and the regularization method. A set of natural point features is extracted from the images of burn patients. A Delaunay triangle mesh is then generated that adapts to the point features. A 3D finite element model is built on top of the mesh with the aid of range images providing the depth information. The Young's modulus of scars is quantified with a simplified regularization functional, assuming that the knowledge of scar's geometry is available. The consistency between the Relative Elasticity Index and the physician's rating based on the Vancouver Scale (a relative scale used to rate burn scars) indicates that the proposed modeling approach has high potentials for image-based quantitative burn scar assessment.

  11. Support vector machine model for diagnosing pneumoconiosis based on wavelet texture features of digital chest radiographs.

    Science.gov (United States)

    Zhu, Biyun; Chen, Hui; Chen, Budong; Xu, Yan; Zhang, Kuan

    2014-02-01

    This study aims to explore the classification ability of decision trees (DTs) and support vector machines (SVMs) to discriminate between the digital chest radiographs (DRs) of pneumoconiosis patients and control subjects. Twenty-eight wavelet-based energy texture features were calculated at the lung fields on DRs of 85 healthy controls and 40 patients with stage I and stage II pneumoconiosis. DTs with algorithm C5.0 and SVMs with four different kernels were trained by samples with two combinations of the texture features to classify a DR as of a healthy subject or of a patient with pneumoconiosis. All of the models were developed with fivefold cross-validation, and the final performances of each model were compared by the area under receiver operating characteristic (ROC) curve. For both SVM (with a radial basis function kernel) and DT (with algorithm C5.0), areas under ROC curves (AUCs) were 0.94 ± 0.02 and 0.86 ± 0.04 (P = 0.02) when using the full feature set and 0.95 ± 0.02 and 0.88 ± 0.04 (P = 0.05) when using the selected feature set, respectively. When built on the selected texture features, the SVM with a polynomial kernel showed a higher diagnostic performance with an AUC value of 0.97 ± 0.02 than SVMs with a linear kernel, a radial basis function kernel and a sigmoid kernel with AUC values of 0.96 ± 0.02 (P = 0.37), 0.95 ± 0.02 (P = 0.24), and 0.90 ± 0.03 (P = 0.01), respectively. The SVM model with a polynomial kernel built on the selected feature set showed the highest diagnostic performance among all tested models when using either all the wavelet texture features or the selected ones. The model has a good potential in diagnosing pneumoconiosis based on digital chest radiographs.

  12. A retrospective cohort study of cancer mortality in employees of a Russian chrysotile asbestos mine and mills: study rationale and key features.

    Science.gov (United States)

    Schüz, J; Schonfeld, S J; Kromhout, H; Straif, K; Kashanskiy, S V; Kovalevskiy, E V; Bukhtiyarov, I V; McCormack, V

    2013-08-01

    Chrysotile, a serpentine asbestos fibre, is the only type of asbestos produced and consumed in the world today. It is an established human carcinogen. We have begun fieldwork on a retrospective cohort study of employees of one of the world's largest chrysotile mine and mills, situated in Asbest, Russia. The primary aim of the study is to better characterize and quantify the risk of cancer mortality in terms of (i) the dose-response relationship of exposure with risk; (ii) the range of cancer sites affected, including female-specific cancers; and (iii) effects of duration of exposure and latency periods. This information will expand our understanding of the scale of the impending cancer burden due to chrysotile, including if chrysotile use ceased worldwide forthwith. Herein we describe the scientific rationale for conducting this study and the main features of its study design.

  13. Habitat features and predictive habitat modeling for the Colorado chipmunk in southern New Mexico

    Science.gov (United States)

    Rivieccio, M.; Thompson, B.C.; Gould, W.R.; Boykin, K.G.

    2003-01-01

    Two subspecies of Colorado chipmunk (state threatened and federal species of concern) occur in southern New Mexico: Tamias quadrivittatus australis in the Organ Mountains and T. q. oscuraensis in the Oscura Mountains. We developed a GIS model of potentially suitable habitat based on vegetation and elevation features, evaluated site classifications of the GIS model, and determined vegetation and terrain features associated with chipmunk occurrence. We compared GIS model classifications with actual vegetation and elevation features measured at 37 sites. At 60 sites we measured 18 habitat variables regarding slope, aspect, tree species, shrub species, and ground cover. We used logistic regression to analyze habitat variables associated with chipmunk presence/absence. All (100%) 37 sample sites (28 predicted suitable, 9 predicted unsuitable) were classified correctly by the GIS model regarding elevation and vegetation. For 28 sites predicted suitable by the GIS model, 18 sites (64%) appeared visually suitable based on habitat variables selected from logistic regression analyses, of which 10 sites (36%) were specifically predicted as suitable habitat via logistic regression. We detected chipmunks at 70% of sites deemed suitable via the logistic regression models. Shrub cover, tree density, plant proximity, presence of logs, and presence of rock outcrop were retained in the logistic model for the Oscura Mountains; litter, shrub cover, and grass cover were retained in the logistic model for the Organ Mountains. Evaluation of predictive models illustrates the need for multi-stage analyses to best judge performance. Microhabitat analyses indicate prospective needs for different management strategies between the subspecies. Sensitivities of each population of the Colorado chipmunk to natural and prescribed fire suggest that partial burnings of areas inhabited by Colorado chipmunks in southern New Mexico may be beneficial. These partial burnings may later help avoid a fire

  14. Prediction of hot spots in protein interfaces using a random forest model with hybrid features.

    Science.gov (United States)

    Wang, Lin; Liu, Zhi-Ping; Zhang, Xiang-Sun; Chen, Luonan

    2012-03-01

    Prediction of hot spots in protein interfaces provides crucial information for the research on protein-protein interaction and drug design. Existing machine learning methods generally judge whether a given residue is likely to be a hot spot by extracting features only from the target residue. However, hot spots usually form a small cluster of residues which are tightly packed together at the center of protein interface. With this in mind, we present a novel method to extract hybrid features which incorporate a wide range of information of the target residue and its spatially neighboring residues, i.e. the nearest contact residue in the other face (mirror-contact residue) and the nearest contact residue in the same face (intra-contact residue). We provide a novel random forest (RF) model to effectively integrate these hybrid features for predicting hot spots in protein interfaces. Our method can achieve accuracy (ACC) of 82.4% and Matthew's correlation coefficient (MCC) of 0.482 in Alanine Scanning Energetics Database, and ACC of 77.6% and MCC of 0.429 in Binding Interface Database. In a comparison study, performance of our RF model exceeds other existing methods, such as Robetta, FOLDEF, KFC, KFC2, MINERVA and HotPoint. Of our hybrid features, three physicochemical features of target residues (mass, polarizability and isoelectric point), the relative side-chain accessible surface area and the average depth index of mirror-contact residues are found to be the main discriminative features in hot spots prediction. We also confirm that hot spots tend to form large contact surface areas between two interacting proteins. Source data and code are available at: http://www.aporc.org/doc/wiki/HotSpot.

  15. Research on P2P Overlay Network Model with Small-world Features

    OpenAIRE

    Liu, Hao; Chen, Zhigang

    2013-01-01

    Topology structure of P2P network decides its system performance. However, the existing P2P network models don’t take clustering and symmetry of nodes into account. Based on the algebra and graph theory method of Cayley graph, this paper proposes a novel P2P overlay network model with small-world features. Its simplicity and symmetry can ensure the self-organization and scalability of P2P network. The results of analysis and experiment shows that this model provides better robustness, h...

  16. Nonlocal sparse model with adaptive structural clustering for feature extraction of aero-engine bearings

    Science.gov (United States)

    Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Li, Xiang; Yan, Ruqiang

    2016-04-01

    Fault information of aero-engine bearings presents two particular phenomena, i.e., waveform distortion and impulsive feature frequency band dispersion, which leads to a challenging problem for current techniques of bearing fault diagnosis. Moreover, although many progresses of sparse representation theory have been made in feature extraction of fault information, the theory also confronts inevitable performance degradation due to the fact that relatively weak fault information has not sufficiently prominent and sparse representations. Therefore, a novel nonlocal sparse model (coined NLSM) and its algorithm framework has been proposed in this paper, which goes beyond simple sparsity by introducing more intrinsic structures of feature information. This work adequately exploits the underlying prior information that feature information exhibits nonlocal self-similarity through clustering similar signal fragments and stacking them together into groups. Within this framework, the prior information is transformed into a regularization term and a sparse optimization problem, which could be solved through block coordinate descent method (BCD), is formulated. Additionally, the adaptive structural clustering sparse dictionary learning technique, which utilizes k-Nearest-Neighbor (kNN) clustering and principal component analysis (PCA) learning, is adopted to further enable sufficient sparsity of feature information. Moreover, the selection rule of regularization parameter and computational complexity are described in detail. The performance of the proposed framework is evaluated through numerical experiment and its superiority with respect to the state-of-the-art method in the field is demonstrated through the vibration signals of experimental rig of aircraft engine bearings.

  17. Encoding Scratch and Scrape Features for Wear Modeling of Total Joint Replacements

    Directory of Open Access Journals (Sweden)

    Karen M. Kruger

    2013-01-01

    Full Text Available Damage to hard bearing surfaces of total joint replacement components typically includes both thin discrete scratches and broader areas of more diffuse scraping. Traditional surface metrology parameters such as average roughness or peak asperity height are not well suited to quantifying those counterface damage features in a manner allowing their incorporation into models predictive of polyethylene wear. A diffused lighting technique, which had been previously developed to visualize these microscopic damage features on a global implant level, also allows damaged regions to be automatically segmented. These global-level segmentations in turn provide a basis for performing high-resolution optical profilometry (OP areal scans, to quantify the microscopic-level damage features. Algorithms are here reported by means of which those imaged damage features can be encoded for input into finite element (FE wear simulations. A series of retrieved clinically failed implant femoral heads analyzed in this manner exhibited a wide range of numbers and severity of damage features. Illustrative results from corresponding polyethylene wear computations are also presented.

  18. 基于关键帧颜色和纹理特征的视频拷贝检测%Video Copy Detection Method Based on Color and Texture Features of Key Frames

    Institute of Scientific and Technical Information of China (English)

    陈秀新; 贾克斌; 魏世昂

    2012-01-01

    提出了一种基于关键帧颜色和纹理特征的视频拷贝检测方法.首先通过子片段方法提取视频的关键帧,然后将关键帧分成3个子块,提取每个子块的三维量化颜色直方图,通过直方图相交法来进行颜色特征的匹配.对检索得到的结果视频关键帧进行纹理特征提取,通过其灰度共生矩阵的角二阶矩和熵来表征其纹理特征,纹理特征的匹配可进一步过滤不相关的视频.实验结果表明,该方法效果好、稳健性强且可应用于多种类型的视频.%A video copy detection method based on color and texture features of key frames is proposed Firstly, key frames are extracted based on clip-method. Then, key frames are divided into 3 blocks and three-dimensional quantized color histograms are extracted from the blocks. Color matching is based on histogram intersection. Texture features are further extracted from the key frames of the resulting videos and are represented with angular second moment and entropy of the co-occurrence matrix. With the matching of texture features, more irrelative videos are filtered. Experiments show that this method is effective, high robust and can be used for various types of videos.

  19. 9.7 um Silicate Features in AGNs: New Insights into Unification Models

    CERN Document Server

    Shi, Y; Hines, D C; Gorjian, V; Werner, M W; Cleary, K; Low, F J; Smith, P S; Bouwman, J

    2006-01-01

    We describe observations of 9.7 um silicate features in 97 AGNs, exhibiting a wide range of AGN types and of X-ray extinction toward the central nuclei. We find that the strength of the silicate feature correlates with the HI column density estimated from fitting the X-ray data, such that low HI columns correspond to silicate emission while high columns correspond to silicate absorption. The behavior is generally consistent with unification models where the large diversity in AGN properties is caused by viewing-angle-dependent obscuration of the nucleus. Radio-loud AGNs and radio-quiet quasars follow roughly the correlation between HI columns and the strength of the silicate feature defined by Seyfert galaxies. The agreement among AGN types suggests a high-level unification with similar characteristics for the structure of the obscuring material. We demonstrate the implications for unification models qualitatively with a conceptual disk model. The model includes an inner accretion disk (< 0.1 pc in radius)...

  20. Modeling the Formation Process of Grouping Stimuli Sets through Cortical Columns and Microcircuits to Feature Neurons

    Directory of Open Access Journals (Sweden)

    Frank Klefenz

    2013-01-01

    Full Text Available A computational model of a self-structuring neuronal net is presented in which repetitively applied pattern sets induce the formation of cortical columns and microcircuits which decode distinct patterns after a learning phase. In a case study, it is demonstrated how specific neurons in a feature classifier layer become orientation selective if they receive bar patterns of different slopes from an input layer. The input layer is mapped and intertwined by self-evolving neuronal microcircuits to the feature classifier layer. In this topical overview, several models are discussed which indicate that the net formation converges in its functionality to a mathematical transform which maps the input pattern space to a feature representing output space. The self-learning of the mathematical transform is discussed and its implications are interpreted. Model assumptions are deduced which serve as a guide to apply model derived repetitive stimuli pattern sets to in vitro cultures of neuron ensembles to condition them to learn and execute a mathematical transform.

  1. Predictive features of persistent activity emergence in regular spiking and intrinsic bursting model neurons.

    Science.gov (United States)

    Sidiropoulou, Kyriaki; Poirazi, Panayiota

    2012-01-01

    Proper functioning of working memory involves the expression of stimulus-selective persistent activity in pyramidal neurons of the prefrontal cortex (PFC), which refers to neural activity that persists for seconds beyond the end of the stimulus. The mechanisms which PFC pyramidal neurons use to discriminate between preferred vs. neutral inputs at the cellular level are largely unknown. Moreover, the presence of pyramidal cell subtypes with different firing patterns, such as regular spiking and intrinsic bursting, raises the question as to what their distinct role might be in persistent firing in the PFC. Here, we use a compartmental modeling approach to search for discriminatory features in the properties of incoming stimuli to a PFC pyramidal neuron and/or its response that signal which of these stimuli will result in persistent activity emergence. Furthermore, we use our modeling approach to study cell-type specific differences in persistent activity properties, via implementing a regular spiking (RS) and an intrinsic bursting (IB) model neuron. We identify synaptic location within the basal dendrites as a feature of stimulus selectivity. Specifically, persistent activity-inducing stimuli consist of activated synapses that are located more distally from the soma compared to non-inducing stimuli, in both model cells. In addition, the action potential (AP) latency and the first few inter-spike-intervals of the neuronal response can be used to reliably detect inducing vs. non-inducing inputs, suggesting a potential mechanism by which downstream neurons can rapidly decode the upcoming emergence of persistent activity. While the two model neurons did not differ in the coding features of persistent activity emergence, the properties of persistent activity, such as the firing pattern and the duration of temporally-restricted persistent activity were distinct. Collectively, our results pinpoint to specific features of the neuronal response to a given stimulus that code

  2. Research on texture feature of RS image based on cloud model

    Science.gov (United States)

    Wang, Zuocheng; Xue, Lixia

    2008-10-01

    This paper presents a new method applied to texture feature representation in RS image based on cloud model. Aiming at the fuzziness and randomness of RS image, we introduce the cloud theory into RS image processing in a creative way. The digital characteristics of clouds well integrate the fuzziness and randomness of linguistic terms in a unified way and map the quantitative and qualitative concepts. We adopt texture multi-dimensions cloud to accomplish vagueness and randomness handling of texture feature in RS image. The method has two steps: 1) Correlativity analyzing of texture statistical parameters in Grey Level Co-occurrence Matrix (GLCM) and parameters fuzzification. GLCM can be used to representing the texture feature in many aspects perfectly. According to the expressive force of texture statistical parameters and by Correlativity analyzing of texture statistical parameters, we can abstract a few texture statistical parameters that can best represent the texture feature. By the fuzziness algorithm, the texture statistical parameters can be mapped to fuzzy cloud space. 2) Texture multi-dimensions cloud model constructing. Based on the abstracted texture statistical parameters and fuzziness cloud space, texture multi-dimensions cloud model can be constructed in micro-windows of image. According to the membership of texture statistical parameters, we can achieve the samples of cloud-drop. By backward cloud generator, the digital characteristics of texture multi-dimensions cloud model can be achieved and the Mathematical Expected Hyper Surface(MEHS) of multi-dimensions cloud of micro-windows can be constructed. At last, the weighted sum of the 3 digital characteristics of micro-window cloud model was proposed and used in texture representing in RS image. The method we develop is demonstrated by applying it to texture representing in many RS images, various performance studies testify that the method is both efficient and effective. It enriches the cloud

  3. Predictive features of persistent activity emergence in regular spiking and intrinsic bursting model neurons.

    Directory of Open Access Journals (Sweden)

    Kyriaki Sidiropoulou

    Full Text Available Proper functioning of working memory involves the expression of stimulus-selective persistent activity in pyramidal neurons of the prefrontal cortex (PFC, which refers to neural activity that persists for seconds beyond the end of the stimulus. The mechanisms which PFC pyramidal neurons use to discriminate between preferred vs. neutral inputs at the cellular level are largely unknown. Moreover, the presence of pyramidal cell subtypes with different firing patterns, such as regular spiking and intrinsic bursting, raises the question as to what their distinct role might be in persistent firing in the PFC. Here, we use a compartmental modeling approach to search for discriminatory features in the properties of incoming stimuli to a PFC pyramidal neuron and/or its response that signal which of these stimuli will result in persistent activity emergence. Furthermore, we use our modeling approach to study cell-type specific differences in persistent activity properties, via implementing a regular spiking (RS and an intrinsic bursting (IB model neuron. We identify synaptic location within the basal dendrites as a feature of stimulus selectivity. Specifically, persistent activity-inducing stimuli consist of activated synapses that are located more distally from the soma compared to non-inducing stimuli, in both model cells. In addition, the action potential (AP latency and the first few inter-spike-intervals of the neuronal response can be used to reliably detect inducing vs. non-inducing inputs, suggesting a potential mechanism by which downstream neurons can rapidly decode the upcoming emergence of persistent activity. While the two model neurons did not differ in the coding features of persistent activity emergence, the properties of persistent activity, such as the firing pattern and the duration of temporally-restricted persistent activity were distinct. Collectively, our results pinpoint to specific features of the neuronal response to a given

  4. A Robust Fuzzy Neural Network Model for Soil Lead Estimation from Spectral Features

    Directory of Open Access Journals (Sweden)

    Rohollah Goodarzi

    2015-06-01

    Full Text Available Soil lead content is an important parameter in environmental and industrial applications. Chemical analysis, the most commonly method for studying soil samples, are costly, however application of soil spectroscopy presents a more viable alternative. The first step in the method is usually to extract some appropriate spectral features and then regression models are applied to these extracted features. The aim of this paper was to design an accurate and robust regression technique to estimate soil lead contents from laboratory observed spectra. Three appropriate spectral features were selected according to information from other research as well as the spectrum interpretation of field collected soil samples containing lead. These features were then applied to common Multiple Linear Regression (MLR, Partial Least Square Regression (PLSR and Neural Network (NN regression models. Results showed that although NN had adequate accuracy, it produced unstable results (i.e., variation of response in different runs. This problem was addressed with application of a Fuzzy Neural Network (FNN with a least square training strategy. In addition to the stabilized and unique response, the capability of the proposed FNN was proved in terms of regression accuracy where a Ratio of Performance to Deviation (RPD of 8.76 was achieved for test samples.

  5. [Analysis of tobacco style features using near-infrared spectroscopy and projection model].

    Science.gov (United States)

    Shu, Ru-Xin; Cai, Jia-Yue; Yang, Zheng-Yu; Yang, Kai; Zhao, Long-Lian; Zhang, Lu-Da; Zhang Ye-Hui; Li, Ye-Hui

    2014-10-01

    In the present paper, a total of 4,733 flue-cured tobacco samples collected from 2003 to 2012 in 17 provincial origins and 5 ecological areas were tested by near infrared spectroscopy, including the NONG(Luzhou) flavor 1,580 cartons, QING (Fen) flavor 2004 cartons and Intermediate flavor 1 149 cartons. Using projection model based on principal component and Fisher criterion (PPF), Projection analysis models of tobacco ecological regions and style characteristics were established. Reasonableness of style flavor division is illustrated by the model results of tobacco ecological areas. With the Euclidean distance between the predicted sample projection values and the mean projection values of each class in style characteristics model, a description is given for the prediction samples to quantify the extent of the style features, and their first and second close categories. Using the dispersion of projected values in model and the given threshold value, prediction results can be refined into typical NONG, NONG to Intermediate, Intermediate to NONG, typical Intermediate, Intermediate to QING, QING to Intermediate, typical QING, QING to NONG, NONG to QING, or super-model range. The model was validated by 35 tobacco samples obtained from the re-dryingprocess in 2012 with different origins and parts. This kind of analysis methods not only can achieve discriminant analysis, but also can get richer feature attribute information and provide guidance to raw tobacco processing and formulations.

  6. Morphological leaf variability in natural populations of Pistacia atlantica Desf. subsp. atlantica along climatic gradient: new features to update Pistacia atlantica subsp. atlantica key

    Science.gov (United States)

    El Zerey-Belaskri, Asma; Benhassaini, Hachemi

    2016-04-01

    The effect of bioclimate range on the variation in Pistacia atlantica Desf. subsp. atlantica leaf morphology was studied on 16 sites in Northwest Algeria. The study examined biometrically mature leaves totaling 3520 compound leaves. Fifteen characters (10 quantitative and 5 qualitative) were assessed on each leaf. For each quantitative character, the nested analysis of variance (ANOVA) was used to examine relative magnitude of variation at each level of the nested hierarchy. The correlation between the climatic parameters and the leaf morphology was examined. The statistical analysis applied on the quantitative leaf characters showed highly significant variation at the within-site level and between-site variation. The correlation coefficient ( r) showed also an important correlation between climatic parameters and leaf morphology. The results of this study exhibited several values reported for the first time on the species, such as the length and the width of the leaf (reaching up to 24.5 cm/21.9 cm), the number of leaflets (up to 18 leaflets/leaf), and the petiole length of the terminal leaflet (reaching up to 3.4 cm). The original findings of this study are used to update the P. atlantica subsp. atlantica identification key.

  7. Assessing impact of changes in human resources features on enterprise activities: simulation model

    Directory of Open Access Journals (Sweden)

    Kalmykova Svetlana

    2017-01-01

    Full Text Available The need for creating programs of human resources development is shown; the impact of these programs on organizational effectiveness is taken into account. The stages of development tools and HRD programs on the basis of cognitive modelling are disclosed; these stages will help assess the impact of HR-practices on the key indicators of organization activity at the design stage. The method of HR-practices’ pre-selection in professional development of the employees is represented.

  8. Mast cells play a key role in Th2 cytokine-dependent asthma model through production of adhesion molecules by liberation of TNF-α.

    Science.gov (United States)

    Chai, Ok Hee; Han, Eui-Hyeog; Lee, Hern-Ku; Song, Chang Ho

    2011-01-31

    Mast cells are well recognized as key cells in allergic reactions, such as asthma and allergic airway diseases. However, the effects of mast cells and TNF-α on T-helper type 2 (Th2) cytokine-dependent asthma are not clearly understood. Therefore, an aim of this study was to investigate the role of mast cells on Th2 cytokine-dependent airway hyperresponsiveness and inflammation. We used genetically mast cell-deficient WBB6F1/J-Kitw/Kitw-v (W/Wv), congenic normal WBB6F1/J-Kit+/Kit+ (+/+), and mast cell-reconstituted W/Wv mouse models of allergic asthma to investigate the role of mast cells in Th2 cytokine-dependent asthma induced by ovalbumin (OVA). And we investigated whether the intratracheal injection of TNF-α directly induce the expression of ICAM-1 and VCAM-1 in W/Wv mice. This study, with OVA-sensitized and OVA-challenged mice, revealed the following typical histopathologic features of allergic diseases: increased inflammatory cells of the airway, airway hyperresponsiveness, and increased levels of TNF-α, intercellular adhesion molecule (ICAM)-1, and vascular cellular adhesion molecule (VCAM)-1. However, the histopathologic features and levels of ICAM-1 and VCAM-1 proteins in W/Wv mice after OVA challenges were significantly inhibited. Moreover, mast cell-reconstituted W/Wv mice showed restoration of histopathologic features and recovery of ICAM-1 and VCAM-1 protein levels that were similar to those found in +/+ mice. Intratracheal administration of TNF-α resulted in increased ICAM-1 and VCAM-1 protein levels in W/Wv mice. These results suggest that mast cells play a key role in a Th2 cytokine-dependent asthma model through production of adhesion molecules, including ICAM-1 and VCAM-1, by liberation of TNF-α.

  9. Chinese New Word Identification: A Latent Discriminative Model with Global Features

    Institute of Scientific and Technical Information of China (English)

    Xiao Sun; De-Gen Huang; Hai-Yu Song; Fu-Ji Ren

    2011-01-01

    Chinese new words are particularly problematic in Chinese natural language processing. With the fast deve-lopment of Internet and information explosion, it is impossible to get a complete system lexicon for applications in Chinese natural language processing, as new words out of dictionaries are always being created. The procedure of new words identification and POS tagging are usually separated and the features of lexical information cannot be fully used. A latent discriminative model, which combines the strengths of Latent Dynamic Conditional Random Field (LDCRF) and semi-CRF, is proposed to detect new words together with their POS synchronously regardless of the types of new words from Chinese text without being pre-segmented. Unlike semi-CRF, in proposed latent discriminative model, LDCRF is applied to generate candidate entities, which accelerates the training speed and decreases the computational cost. The complexity of proposed hidden semi-CRF could be further adjusted by tuning the number of hidden variables and the number of candidate entities from the Nbest outputs of LDCRF model. A new-word-generating framework is proposed for model training and testing, under which the definitions and distributions of new words conform to the ones in real text. The global feature called "Global Fragment Features" for new word identification is adopted. We tested our model on the corpus from SIGHAN-6. Experimental results show that the proposed method is capable of detecting even low frequency new words together with their POS tags with satisfactory results. The proposed model performs competitively with the state-of-the-art models.

  10. Modeling and Detecting Feature Interactions among Integrated Services of Home Network Systems

    Science.gov (United States)

    Igaki, Hiroshi; Nakamura, Masahide

    This paper presents a framework for formalizing and detecting feature interactions (FIs) in the emerging smart home domain. We first establish a model of home network system (HNS), where every networked appliance (or the HNS environment) is characterized as an object consisting of properties and methods. Then, every HNS service is defined as a sequence of method invocations of the appliances. Within the model, we next formalize two kinds of FIs: (a) appliance interactions and (b) environment interactions. An appliance interaction occurs when two method invocations conflict on the same appliance, whereas an environment interaction arises when two method invocations conflict indirectly via the environment. Finally, we propose offline and online methods that detect FIs before service deployment and during execution, respectively. Through a case study with seven practical services, it is shown that the proposed framework is generic enough to capture feature interactions in HNS integrated services. We also discuss several FI resolution schemes within the proposed framework.

  11. Saltation-threshold model can explain aeolian features on low-air-density planetary bodies

    CERN Document Server

    Pähtz, Thomas

    2016-01-01

    Knowledge of the minimal fluid speeds at which sediment transport can be sustained is crucial for understanding whether underwater landscapes exposed to water streams and wind-blown loose planetary surfaces can be altered. It also tells us whether surface features, such as ripples and dunes, can evolve. Here, guided by state-of-the-art numerical simulations, we propose an analytical model predicting the minimal fluid speeds required to sustain sediment transport in a Newtonian fluid. The model results are consistent with measurements and estimates of the transport threshold in water and Earth's and Mars' atmospheres. Furthermore, it predicts reasonable wind speeds to sustain aeolian sediment transport ("saltation") on the low-air-density planetary bodies Triton, Pluto, and 67P/Churyumov-Gerasimenko (comet). This offers an explanation for possible aeolian surface features photographed on these bodies during space missions.

  12. DIMENSION VARIATION OF FEATURE-BASED MODEL BY OPERATING DIRECTLY ON B-REP

    Institute of Scientific and Technical Information of China (English)

    1998-01-01

    A new algorithm for dimension variation of feature-based models is developed.The algorithm is based on B-Rep/CSG hybrid scheme and operates directly on B-Rep.Product information (including the features locating dimensions and other data for manufacture) will not lose after model variation and modification.Furthermore, the definition and solution of features constraints are also supported.The scheme of directly operating on B-Rep overcomes many drawbacks of other proposed methods, most of which need to redo all of the previous work to implement dimension variation, so the computational cost is expensive and product information will lose.What is presented in this paper makes a new way in the area of parametric design.

  13. Self-Organized Public-Key Management for Mobile Ad Hoc Networks Based on a Bidirectional Trust Model

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    In traditional networks ,the authentication is performed by certificate authoritys(CA),which can't be built in distributed mobile Ad Hoc Networks however. In this paper, we propose a fully self-organized public key management based on bidirectional trust model without any centralized authority that allows users to generate their public-private key pairs, to issue certificates, and the trust relation spreads rationally according to the truly human relations. In contrast with the traditional self-organized public-key management, the average certificates paths get more short,the authentication passing rate gets more high and the most important is that the bidirectional trust based model satisfys the trust requirement of hosts better.

  14. Structure of transmembrane domain of lysosome-associated membrane protein type 2a (LAMP-2A) reveals key features for substrate specificity in chaperone-mediated autophagy.

    Science.gov (United States)

    Rout, Ashok K; Strub, Marie-Paule; Piszczek, Grzegorz; Tjandra, Nico

    2014-12-19

    Chaperone-mediated autophagy (CMA) is a highly regulated cellular process that mediates the degradation of a selective subset of cytosolic proteins in lysosomes. Increasing CMA activity is one way for a cell to respond to stress, and it leads to enhanced turnover of non-critical cytosolic proteins into sources of energy or clearance of unwanted or damaged proteins from the cytosol. The lysosome-associated membrane protein type 2a (LAMP-2A) together with a complex of chaperones and co-chaperones are key regulators of CMA. LAMP-2A is a transmembrane protein component for protein translocation to the lysosome. Here we present a study of the structure and dynamics of the transmembrane domain of human LAMP-2A in n-dodecylphosphocholine micelles by nuclear magnetic resonance (NMR). We showed that LAMP-2A exists as a homotrimer in which the membrane-spanning helices wrap around each other to form a parallel coiled coil conformation, whereas its cytosolic tail is flexible and exposed to the cytosol. This cytosolic tail of LAMP-2A interacts with chaperone Hsc70 and a CMA substrate RNase A with comparable affinity but not with Hsp40 and RNase S peptide. Because the substrates and the chaperone complex can bind at the same time, thus creating a bimodal interaction, we propose that substrate recognition by chaperones and targeting to the lysosomal membrane by LAMP-2A are coupled. This can increase substrate affinity and specificity as well as prevent substrate aggregation, assist in the unfolding of the substrate, and promote the formation of the higher order complex of LAMP-2A required for translocation.

  15. 基于中心距离特征的人体运动序列关键帧提取%Key Frame Extraction Using Central Distance Feature for Human Motion Data

    Institute of Scientific and Technical Information of China (English)

    彭淑娟

    2012-01-01

    运动捕获数据的关键帧是原始运动序列的简洁表示,对于运动压缩、运动检索和运动分割起着重要的作用。提出了一种基于中心距离特征的人体运动捕获数据关键帧提取方法,通过提取四肢到中心点ROOT的距离,得到一组中心距离特征,将特征分为上肢和下肢来分别表示,并提取上下肢的距离模,得到二维的特征向量模;然后采用主成分分析得到一维特征,并提取其局部极值点作为初始关键帧;最后通过对初始关键帧的重新筛选与插入得到最终关键帧序列。实验结果表明,该方法提取的关键帧序列在视觉上能够很好的概括原始运动序列的内容,且具有高压缩率。%The key frames of the motion capture data are the concise description for the original motion sequence,which play an important role for the motion compression,motion retrieval and motion segmentation.A key frame extraction method based on the central distance features for the human motion capture data was proposed.The approach was divided into three main stages.In the first stage,a set of central distance features from the center joint ROOT to limbs was selected,and those features were divided into the upper and lower limbs norms.In the second stage,PCA method was used to get the one dimension principal component,which was used to extract the local optimum as the initial key frames.In the last stage,the initial key frames were filtered and inserted to get the final key frames.Experimental results show that the proposed method can get the needed key frames,which can have good visual generalization of the original motion sequence,and also be of high compression ratio as well.

  16. Combining features in a graphical model to predict protein binding sites.

    Science.gov (United States)

    Wierschin, Torsten; Wang, Keyu; Welter, Marlon; Waack, Stephan; Stanke, Mario

    2015-05-01

    Large efforts have been made in classifying residues as binding sites in proteins using machine learning methods. The prediction task can be translated into the computational challenge of assigning each residue the label binding site or non-binding site. Observational data comes from various possibly highly correlated sources. It includes the structure of the protein but not the structure of the complex. The model class of conditional random fields (CRFs) has previously successfully been used for protein binding site prediction. Here, a new CRF-approach is presented that models the dependencies of residues using a general graphical structure defined as a neighborhood graph and thus our model makes fewer independence assumptions on the labels than sequential labeling approaches. A novel node feature "change in free energy" is introduced into the model, which is then denoted by ΔF-CRF. Parameters are trained with an online large-margin algorithm. Using the standard feature class relative accessible surface area alone, the general graph-structure CRF already achieves higher prediction accuracy than the linear chain CRF of Li et al. ΔF-CRF performs significantly better on a large range of false positive rates than the support-vector-machine-based program PresCont of Zellner et al. on a homodimer set containing 128 chains. ΔF-CRF has a broader scope than PresCont since it is not constrained to protein subgroups and requires no multiple sequence alignment. The improvement is attributed to the advantageous combination of the novel node feature with the standard feature and to the adopted parameter training method.

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

    OpenAIRE

    Sirinoot Boonsuk; Atiwong Suchato; Proadpran Punyabukkana; Chai Wutiwiwatchai; Nattanun Thatphithakkul

    2014-01-01

    Spoken language recognition (SLR) has been of increasing interest in multilingual speech recognition for identifying the languages of speech utterances. Most existing SLR approaches apply statistical modeling techniques with acoustic and phonotactic features. Among the popular approaches, the acoustic approach has become of greater interest than others because it does not require any prior language-specific knowledge. Previous research on the acoustic approach has shown less interest in apply...

  18. Modeling halotropism : a key role for root tip architecture and reflux loop remodeling in redistributing auxin

    NARCIS (Netherlands)

    van den Berg, Thea; Korver, Ruud A; Testerink, Christa; ten Tusscher, Kirsten

    2016-01-01

    A key characteristic of plant development is its plasticity in response to various and dynamically changing environmental conditions. Tropisms contribute to this flexibility by allowing plant organs to grow from or towards environmental cues. Halotropism is a recently described tropism in which plan

  19. Modeling Key Drivers of E-Learning Satisfaction among Student Teachers

    Science.gov (United States)

    Teo, Timothy; Wong, Su Luan

    2013-01-01

    This study explored the key drivers of student teachers' e-learning satisfaction. Three hundred and eighty-seven participants completed a survey questionnaire measuring their self-reported responses to six constructs (tutor quality, perceived usefulness, perceived ease of use, course delivery, facilitating conditions, and course satisfaction).…

  20. Feature Specific Criminal Mapping using Data Mining Techniques and Generalized Gaussian Mixture Model

    Directory of Open Access Journals (Sweden)

    Uttam Mande

    2012-06-01

    Full Text Available Lot of research is projected to map the criminal with that of crime and it is observed that there is still a huge increase in the crime rate due to the gap between the optimal usage of technologies and investigation. This has given scope for the development of new methodologies in the area of crime investigation using the techniques based on data mining, image processing, forensic, and social mining. In this paper, presents a model using new methodology for mapping the criminal with the crime. This model clusters the criminal data basing on the type crime. When a crime occurs, based on the eye witness specified features, the criminal is mapped. Here we propose a novel methodology that uses Generalized Gaussian Mixture Model to map the features specified by the eyewitness with that of the features of the criminal who have committed the same type of the crime, if the criminal is not mapped, the suspect table is checked and the reports are generated

  1. Radiative emission of solar features in the Ca II K line: comparison of measurements and models

    CERN Document Server

    Ermolli, I; Uitenbroek, H; Giorgi, F; Rast, M P; Solanki, S K

    2010-01-01

    We study the radiative emission of various types of solar features, such as quiet Sun, enhanced network, plage, and bright plage regions, identified on filtergrams taken in the Ca II K line. We analysed fulldisk images obtained with the PSPT, by using three interference filters that sample the Ca II K line with different bandpasses. We studied the dependence of the radiative emission of disk features on the filter bandpass. We also performed a NLTE spectral synthesis of the Ca II K line integrated over the bandpass of PSPT filters. The synthesis was carried out by utilizing both the PRD and CRD with the most recent set of semi­empirical atmosphere models in the literature and some earlier atmosphere models. We measured the CLV of intensity values for various solar features identified on PSPT images and compared the results obtained with those derived from the synthesis. We find that CRD calculations derived using the most recent quiet Sun model, on average, reproduce the measured values of the quiet Sun regi...

  2. Features in geometric receiver shapes modelling bat-like directivity patterns.

    Science.gov (United States)

    Guarato, Francesco; Andrews, Heather; Windmill, James F C; Jackson, Joseph; Pierce, Gareth; Gachagan, Anthony

    2015-09-03

    The directional properties of bat ears as receivers is a current area of interest in ultrasound research. This paper presents a new approach to analyse the relationship between morphological features and acoustical properties of the external ear of bat species. The beam pattern of Rousettus leschenaultii's right ear is measured and compared to that of receiver structures whose design is inspired by the bat ear itself and made of appropriate geometric shapes. The regular shape of these receivers makes it possible to control the key reception parameters and thus to understand the effect on the associated beam pattern of the parameters themselves. Measurements show one receiver structure has a beam pattern very similar to that of R. leschenaultii's ear, thus explaining the function of individual parts constituting its ear. As it is applicable to all bat species, this approach can provide a useful tool to investigate acoustics in bats, and possibly other mammals.

  3. Quantum key management

    Energy Technology Data Exchange (ETDEWEB)

    Hughes, Richard John; Thrasher, James Thomas; Nordholt, Jane Elizabeth

    2016-11-29

    Innovations for quantum key management harness quantum communications to form a cryptography system within a public key infrastructure framework. In example implementations, the quantum key management innovations combine quantum key distribution and a quantum identification protocol with a Merkle signature scheme (using Winternitz one-time digital signatures or other one-time digital signatures, and Merkle hash trees) to constitute a cryptography system. More generally, the quantum key management innovations combine quantum key distribution and a quantum identification protocol with a hash-based signature scheme. This provides a secure way to identify, authenticate, verify, and exchange secret cryptographic keys. Features of the quantum key management innovations further include secure enrollment of users with a registration authority, as well as credential checking and revocation with a certificate authority, where the registration authority and/or certificate authority can be part of the same system as a trusted authority for quantum key distribution.

  4. Quantum key management

    Science.gov (United States)

    Hughes, Richard John; Thrasher, James Thomas; Nordholt, Jane Elizabeth

    2016-11-29

    Innovations for quantum key management harness quantum communications to form a cryptography system within a public key infrastructure framework. In example implementations, the quantum key management innovations combine quantum key distribution and a quantum identification protocol with a Merkle signature scheme (using Winternitz one-time digital signatures or other one-time digital signatures, and Merkle hash trees) to constitute a cryptography system. More generally, the quantum key management innovations combine quantum key distribution and a quantum identification protocol with a hash-based signature scheme. This provides a secure way to identify, authenticate, verify, and exchange secret cryptographic keys. Features of the quantum key management innovations further include secure enrollment of users with a registration authority, as well as credential checking and revocation with a certificate authority, where the registration authority and/or certificate authority can be part of the same system as a trusted authority for quantum key distribution.

  5. Generic feature of future crossing of phantom divide in viable $f(R)$ gravity models

    CERN Document Server

    Bamba, Kazuharu; Lee, Chung-Chi

    2010-01-01

    We study the equation of state for dark energy and explicitly demonstrate that the future crossings of the phantom divide line $w_{\\mathrm{DE}}=-1$ are the generic feature in the existing viable $f(R)$ gravity models. We also explore the future evolution of the cosmological horizon entropy and illustrate that the cosmological horizon entropy oscillates with time due to the oscillatory behavior of the Hubble parameter. The important cosmological consequence is that in the future, the sign of the time derivative of the Hubble parameter changes from negative to positive in these viable $f(R)$ gravity models.

  6. Generic feature of future crossing of phantom divide in viable f(R) gravity models

    Energy Technology Data Exchange (ETDEWEB)

    Bamba, Kazuharu; Geng, Chao-Qiang; Lee, Chung-Chi, E-mail: bamba@phys.nthu.edu.tw, E-mail: geng@phys.nthu.edu.tw, E-mail: g9522545@oz.nthu.edu.tw [Department of Physics, National Tsing Hua University, No. 101, Section 2, Kuang Fu Road, Hsinchu, Taiwan (China)

    2010-11-01

    We study the equation of state for dark energy and explicitly demonstrate that the future crossings of the phantom divide line w{sub DE} = −1 are the generic feature in the existing viable f(R) gravity models. We also explore the future evolution of the cosmological horizon entropy and illustrate that the cosmological horizon entropy oscillates with time due to the oscillatory behavior of the Hubble parameter. The important cosmological consequence is that in the future, the sign of the time derivative of the Hubble parameter changes from negative to positive in these viable f(R) gravity models.

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

    Science.gov (United States)

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

    2016-01-01

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

  8. Visual cortex inspired CNN model for feature construction in text analysis

    Directory of Open Access Journals (Sweden)

    Hongping Fu

    2016-07-01

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

  9. A deep bag-of-features model for the classification of melanomas in dermoscopy images.

    Science.gov (United States)

    Sabbaghi, S; Aldeen, M; Garnavi, R

    2016-08-01

    Deep learning and unsupervised feature learning have received great attention in past years for their ability to transform input data into high level representations using machine learning techniques. Such interest has been growing steadily in the field of medical image diagnosis, particularly in melanoma classification. In this paper, a novel application of deep learning (stacked sparse auto-encoders) is presented for skin lesion classification task. The stacked sparse auto-encoder discovers latent information features in input images (pixel intensities). These high-level features are subsequently fed into a classifier for classifying dermoscopy images. In addition, we proposed a new deep neural network architecture based on bag-of-features (BoF) model, which learns high-level image representation and maps images into BoF space. Then, we examine how using this deep representation of BoF, compared with pixel intensities of images, can improve the classification accuracy. The proposed method is evaluated on a test set of 244 skin images. To test the performance of the proposed method, the area under the receiver operating characteristics curve (AUC) is utilized. The proposed method is found to achieve 95% accuracy.

  10. Model dielectric function analysis of the critical point features of silicon nanocrystal films in a broad parameter range

    Energy Technology Data Exchange (ETDEWEB)

    Agocs, Emil, E-mail: agocsemil@gmail.com [Doctoral School of Molecular and Nanotechnologies, Faculty of Information Technology, University of Pannonia, Egyetem u.10, Veszprém, H-8200 (Hungary); Research Institute for Technical Physics and Material Science (MFA), Research Centre for Natural Sciences, H-1525 Budapest, POB 49 (Hungary); Nassiopoulou, Androula G. [IMEL/NCSR Demokritos, Aghia Paraskevi, 153 10 Athens (Greece); Milita, Silvia [CNR-IMM Sezione Bologna, Via Gobetti, 40129 Bologna (Italy); Petrik, Peter [Doctoral School of Molecular and Nanotechnologies, Faculty of Information Technology, University of Pannonia, Egyetem u.10, Veszprém, H-8200 (Hungary); Research Institute for Technical Physics and Material Science (MFA), Research Centre for Natural Sciences, H-1525 Budapest, POB 49 (Hungary)

    2013-08-31

    Due to quantum-confinement the band structure of silicon nanocrystals (NCs) is different from that of bulk silicon and strongly depends on the NC size. The samples we investigated have been prepared using chemical vapor deposition and annealing allowing a good control of the parameters in terms of both thickness and NC size, being suitable as model systems. The problem of the analysis is that the critical point features of the dielectric function can only be described with acceptable accuracy when using numerous parameters. The majority of the fit parameters are describing the oscillators of different line-shapes. In this work we show how the number of fit parameters can be reduced by a systematic analysis to find non-sensitive and correlating parameters to fix and couple as much parameters as possible. - Highlights: ► Silicon nanocrystal films were measured by spectroscopic ellipsometry. ► The dielectric functions were modeled with Adachi's model dielectric function. ► We developed a parameter analysis and fitting algorithm. ► The non-sensitive parameters were coupled and neglected. ► The behaviors of key material parameters were determined.

  11. Integration of Urban Features into a Coupled Groundwater-Surface Water Model

    Science.gov (United States)

    Bhaskar, A. S.; Welty, C.; Maxwell, R. M.

    2012-12-01

    To better understand the feedbacks between urban development and water availability, we are coupling an integrated hydrologic model with an urban growth model, both of the Baltimore, Maryland, USA region. The urban growth model SLEUTH has been calibrated, validated and run by collaborators at Shippensburg University. We are using ParFlow.CLM as the integrated hydrologic model. This model is applied to the 13,000 sq. km. Baltimore metropolitan area, which spans the Gunpowder and Patapsco watersheds. The model domain includes both Piedmont and Coastal Plain physiographic provinces. We have incorporated characteristics of both the natural hydrogeologic system and the superimposed urban environment. Standard hydrogeologic information such as hydraulic conductivity of fractured bedrock, Coastal Plain sediments, and surficial soils, as well as saprolite thickness, porosity, and specific storage properties have been included. We have also quantified a number of aspects representing urban development, such as residential and municipal well pumping, municipal reservoir use, lawn watering, and water supply pipe leakage estimates. We have represented impervious surface coverage using low surface hydraulic conductivity values. The land surface fluxes in CLM (Common Land Model) use surface land cover and therefore represent reduced evapotranspiration in urban areas. A study of urban and natural watershed inflows and inflows in this region indicated some urban features significantly modify catchment water balances. We are particularly interested in the effects of these urban hydrologic features on groundwater recharge in the Baltimore area. Prior to inclusion of subsurface heterogeneity, we initialized the model by running it hourly from 2000 to 2007. The initialization was generated by a dynamic spin-up process, using the UMBC High Performance Computing Facility. Observed meteorological forcing, such as hourly precipitation and air temperature, are used by the land surface

  12. Scale Effect Features During Simulation Tests of 3D Printer-Made Vane Pump Models

    Directory of Open Access Journals (Sweden)

    A. I. Petrov

    2015-01-01

    Full Text Available The article "Scale effect features during simulation tests of 3D printer-made vane pump models" discusses the influence of scale effect on translation of pump parameters from models, made with 3D-prototyping methods, to full-scale pumps. Widely spread now 3D-printer production of pump model parts or entire layouts can be considered to be the main direction of vane pumps modeling. This is due to the widespread development of pumps in different CAD-systems and the significant cost reduction in manufacturing such layouts, as compared to casting and other traditional methods.The phenomenon of scale effect in vane hydraulic machines, i.e. violation of similarity conditions when translating pump parameters from model to full-scale pumps is studied in detail in the theory of similarity. However, as the experience in the 3d-printer manufacturing of models and their testing gains it becomes clear that accounting large-scale effect for such models has a number of differences from the conventional techniques. The reason for this is the features of micro and macro geometry of parts made in different kinds of 3D-printers (extrusive, and powder sintering methods, ultraviolet light, etc..The article considers the converting features of external and internal mechanical losses, leakages, and hydraulic losses, as well as the specifics of the balance tests for such models. It also presents the basic conversion formulas describing the factors affecting the value of these losses. It shows photographs of part surfaces of models, manufactured by 3D-printer and subjected to subsequent machining. The paper shows results of translation from several pump models (layouts to the full-scale ones, using the techniques described, and it also shows that the error in translation efficiency does not exceed 1.15%. The conclusion emphasizes the importance of the balance tests of models to accumulate statistical data on the scale effect for pump layouts made by different 3D

  13. Mapping mantle flow during retreating subduction: Laboratory models analyzed by feature tracking

    Science.gov (United States)

    Funiciello, F.; Moroni, M.; Piromallo, C.; Faccenna, C.; Cenedese, A.; Bui, H. A.

    2006-03-01

    Three-dimensional dynamically consistent laboratory models are carried out to model the large-scale mantle circulation induced by subduction of a laterally migrating slab. A laboratory analogue of a slab-upper mantle system is set up with two linearly viscous layers of silicone putty and glucose syrup in a tank. The circulation pattern is continuously monitored and quantitatively estimated using a feature tracking image analysis technique. The effects of plate width and mantle viscosity/density on mantle circulation are systematically considered. The experiments show that rollback subduction generates a complex three-dimensional time-dependent mantle circulation pattern characterized by the presence of two distinct components: the poloidal and the toroidal circulation. The poloidal component is the answer to the viscous coupling between the slab motion and the mantle, while the toroidal one is produced by lateral slab migration. Spatial and temporal features of mantle circulation are carefully analyzed. These models show that (1) poloidal and toroidal mantle circulation are both active since the beginning of the subduction process, (2) mantle circulation is intermittent, (3) plate width affects the velocity and the dimension of subduction induced mantle circulation area, and (4) mantle flow in subduction zones cannot be correctly described by models assuming a two-dimensional steady state process. We show that the intermittent toroidal component of mantle circulation, missed in those models, plays a crucial role in modifying the geometry and the efficiency of the poloidal component.

  14. Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models

    Science.gov (United States)

    Bai, Yun; Chen, Zhiqiang; Xie, Jingjing; Li, Chuan

    2016-01-01

    Inflow forecasting applies data supports for the operations and managements of reservoirs. A multiscale deep feature learning (MDFL) method with hybrid models is proposed in this paper to deal with the daily reservoir inflow forecasting. Ensemble empirical mode decomposition and Fourier spectrum are first employed to extract multiscale (trend, period and random) features, which are then represented by three deep belief networks (DBNs), respectively. The weights of each DBN are subsequently applied to initialize a neural network (D-NN). The outputs of the three-scale D-NNs are finally reconstructed using a sum-up strategy toward the forecasting results. A historical daily inflow series (from 1/1/2000 to 31/12/2012) of the Three Gorges reservoir, China, is investigated by the proposed MDFL with hybrid models. For comparison, four peer models are adopted for the same task. The results show that, the present model overwhelms all the peer models in terms of mean absolute percentage error (MAPE = 11.2896%), normalized root-mean-square error (NRMSE = 0.2292), determination coefficient criteria (R2 = 0.8905), and peak percent threshold statistics (PPTS(5) = 10.0229%). The addressed method integrates the deep framework with multiscale and hybrid observations, and therefore being good at exploring sophisticated natures in the reservoir inflow forecasting.

  15. Computational Intelligence Modeling of the Macromolecules Release from PLGA Microspheres-Focus on Feature Selection.

    Directory of Open Access Journals (Sweden)

    Hossam M Zawbaa

    Full Text Available Poly-lactide-co-glycolide (PLGA is a copolymer of lactic and glycolic acid. Drug release from PLGA microspheres depends not only on polymer properties but also on drug type, particle size, morphology of microspheres, release conditions, etc. Selecting a subset of relevant properties for PLGA is a challenging machine learning task as there are over three hundred features to consider. In this work, we formulate the selection of critical attributes for PLGA as a multiobjective optimization problem with the aim of minimizing the error of predicting the dissolution profile while reducing the number of attributes selected. Four bio-inspired optimization algorithms: antlion optimization, binary version of antlion optimization, grey wolf optimization, and social spider optimization are used to select the optimal feature set for predicting the dissolution profile of PLGA. Besides these, LASSO algorithm is also used for comparisons. Selection of crucial variables is performed under the assumption that both predictability and model simplicity are of equal importance to the final result. During the feature selection process, a set of input variables is employed to find minimum generalization error across different predictive models and their settings/architectures. The methodology is evaluated using predictive modeling for which various tools are chosen, such as Cubist, random forests, artificial neural networks (monotonic MLP, deep learning MLP, multivariate adaptive regression splines, classification and regression tree, and hybrid systems of fuzzy logic and evolutionary computations (fugeR. The experimental results are compared with the results reported by Szlȩk. We obtain a normalized root mean square error (NRMSE of 15.97% versus 15.4%, and the number of selected input features is smaller, nine versus eleven.

  16. Structure and functional features of olive pollen pectin methylesterase using homology modeling and molecular docking methods.

    Science.gov (United States)

    Jimenez-Lopez, Jose C; Kotchoni, Simeon O; Rodríguez-García, María I; Alché, Juan D

    2012-12-01

    Pectin methylesterases (PMEs), a multigene family of proteins with multiple differentially regulated isoforms, are key enzymes implicated in the carbohydrates (pectin) metabolism of cell walls. Olive pollen PME has been identified as a new allergen (Ole e 11) of potential relevance in allergy amelioration, since it exhibits high prevalence among atopic patients. In this work, the structural and functional characterization of two olive pollen PME isoforms and their comparison with other PME plants was performed by using different approaches: (1) the physicochemical properties and functional-regulatory motifs characterization, (2) primary sequence analysis, 2D and 3D comparative structural features study, (3) conservation and evolutionary analysis, (4) catalytic activity and regulation based on molecular docking analysis of a homologue PME inhibitor, and (5) B-cell epitopes prediction by sequence and structural based methods and protein-protein interaction tools, while T-cell epitopes by inhibitory concentration and binding score methods. Our results indicate that the structural differences and low conservation of residues, together with differences in physicochemical and posttranslational motifs might be a mechanism for PME isovariants generation, regulation, and differential surface epitopes generation. Olive PMEs perform a processive catalytic mechanism, and a differential molecular interaction with specific PME inhibitor, opening new possibilities for PME activity regulation. Despite the common function of PMEs, differential features found in this study will lead to a better understanding of the structural and functional characterization of plant PMEs and help to improve the component-resolving diagnosis and immunotherapy of olive pollen allergy by epitopes identification.

  17. A neurophysiologically plausible population code model for feature integration explains visual crowding.

    Directory of Open Access Journals (Sweden)

    Ronald van den Berg

    2010-01-01

    Full Text Available An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called "crowding". Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, "compulsory averaging", and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality.

  18. A neurophysiologically plausible population code model for feature integration explains visual crowding.

    Science.gov (United States)

    van den Berg, Ronald; Roerdink, Jos B T M; Cornelissen, Frans W

    2010-01-22

    An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called "crowding". Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, "compulsory averaging", and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality.

  19. Research on P2P Overlay Network Model with Small-world Features

    Directory of Open Access Journals (Sweden)

    Hao LIU

    2013-09-01

    Full Text Available Topology structure of P2P network decides its system performance. However, the existing P2P network models don’t take clustering and symmetry of nodes into account. Based on the algebra and graph theory method of Cayley graph, this paper proposes a novel P2P overlay network model with small-world features. Its simplicity and symmetry can ensure the self-organization and scalability of P2P network. The results of analysis and experiment shows that this model provides better robustness, higher enquiry efficiency and better load balance than the existing P2P Overlay Network models such as Chord and CAN. Furthermore, it possesses the property of high clustering.

  20. Random forest-based protein model quality assessment (RFMQA) using structural features and potential energy terms.

    Science.gov (United States)

    Manavalan, Balachandran; Lee, Juyong; Lee, Jooyoung

    2014-01-01

    Recently, predicting proteins three-dimensional (3D) structure from its sequence information has made a significant progress due to the advances in computational techniques and the growth of experimental structures. However, selecting good models from a structural model pool is an important and challenging task in protein structure prediction. In this study, we present the first application of random forest based model quality assessment (RFMQA) to rank protein models using its structural features and knowledge-based potential energy terms. The method predicts a relative score of a model by using its secondary structure, solvent accessibility and knowledge-based potential energy terms. We trained and tested the RFMQA method on CASP8 and CASP9 targets using 5-fold cross-validation. The correlation coefficient between the TM-score of the model selected by RFMQA (TMRF) and the best server model (TMbest) is 0.945. We benchmarked our method on recent CASP10 targets by using CASP8 and 9 server models as a training set. The correlation coefficient and average difference between TMRF and TMbest over 95 CASP10 targets are 0.984 and 0.0385, respectively. The test results show that our method works better in selecting top models when compared with other top performing methods. RFMQA is available for download from http://lee.kias.re.kr/RFMQA/RFMQA_eval.tar.gz.