Dry deposition of gaseous oxidized mercury in Western Maryland.

Science.gov (United States)

Castro, Mark S; Moore, Chris; Sherwell, John; Brooks, Steve B

2012-02-15

The purpose of this study was to directly measure the dry deposition of gaseous oxidized mercury (GOM) in western Maryland. Annual estimates were made using passive ion-exchange surrogate surfaces and a resistance model. Surrogate surfaces were deployed for seventeen weekly sampling periods between September 2009 and October 2010. Dry deposition rates from surrogate surfaces ranged from 80 to 1512 pgm(-2)h(-1). GOM dry deposition rates were strongly correlated (r(2)=0.75) with the weekly average atmospheric GOM concentrations, which ranged from 2.3 to 34.1 pgm(-3). Dry deposition of GOM could be predicted from the ambient air concentrations of GOM using this equation: GOM dry deposition (pgm(-2)h(-1))=43.2 × GOM concentration-80.3. Dry deposition velocities computed using GOM concentrations and surrogate surface GOM dry deposition rates, ranged from 0.2 to 1.7 cms(-1). Modeled dry deposition rates were highly correlated (r(2)=0.80) with surrogate surface dry deposition rates. Using the overall weekly average surrogate surface dry deposition rate (369 ± 340 pg m(-2)h(-1)), we estimated an annual GOM dry deposition rate of 3.2 μg m(-2)year(-1). Using the resistance model, we estimated an annual GOM dry deposition rate of 3.5 μg m(-2)year(-1). Our annual GOM dry deposition rates were similar to the dry deposition (3.3 μg m(-2)h(-1)) of gaseous elemental mercury (GEM) at our site. In addition, annual GOM dry deposition was approximately 1/2 of the average annual wet deposition of total mercury (7.7 ± 1.9 μg m(-2)year(-1)) at our site. Total annual mercury deposition from dry deposition of GOM and GEM and wet deposition was approximately 14.4 μg m(-2)year(-1), which was similar to the average annual litterfall deposition (15 ± 2.1 μg m(-2)year(-1)) of mercury, which was also measured at our site. Copyright © 2012 Elsevier B.V. All rights reserved.

Creation of 'Ukrytie' objects computer model

International Nuclear Information System (INIS)

Mazur, A.B.; Kotlyarov, V.T.; Ermolenko, A.I.; Podbereznyj, S.S.; Postil, S.D.; Shaptala, D.V.

1999-01-01

A partial computer model of the 'Ukrytie' object was created with the use of geoinformation technologies. The computer model makes it possible to carry out information support of the works related to the 'Ukrytie' object stabilization and its conversion into ecologically safe system for analyzing, forecasting and controlling the processes occurring in the 'Ukrytie' object. Elements and structures of the 'Ukryttia' object were designed and input into the model

The Composite OLAP-Object Data Model

Energy Technology Data Exchange (ETDEWEB)

Pourabbas, Elaheh; Shoshani, Arie

2005-12-07

In this paper, we define an OLAP-Object model that combines the main characteristics of OLAP and Object data models in order to achieve their functionalities in a common framework. We classify three different object classes: primitive, regular and composite. Then, we define a query language which uses the path concept in order to facilitate data navigation and data manipulation. The main feature of the proposed language is an anchor. It allows us to fix dynamically an object class (primitive, regular or composite) along the paths over the OLAP-Object data model for expressing queries. The queries can be formulated on objects, composite objects and combination of both. The power of the proposed query language is investigated through multiple query examples. The semantic of different clauses and syntax of the proposed language are investigated.

Object-oriented biomedical system modelling--the language.

Science.gov (United States)

Hakman, M; Groth, T

1999-11-01

The paper describes a new object-oriented biomedical continuous system modelling language (OOBSML). It is fully object-oriented and supports model inheritance, encapsulation, and model component instantiation and behaviour polymorphism. Besides the traditional differential and algebraic equation expressions the language includes also formal expressions for documenting models and defining model quantity types and quantity units. It supports explicit definition of model input-, output- and state quantities, model components and component connections. The OOBSML model compiler produces self-contained, independent, executable model components that can be instantiated and used within other OOBSML models and/or stored within model and model component libraries. In this way complex models can be structured as multilevel, multi-component model hierarchies. Technically the model components produced by the OOBSML compiler are executable computer code objects based on distributed object and object request broker technology. This paper includes both the language tutorial and the formal language syntax and semantic description.

A Model for Concurrent Objects

DEFF Research Database (Denmark)

Sørensen, Morten U.

1996-01-01

We present a model for concurrent objects where obejcts interact by taking part in common events that are closely matched to form call-response pairs, resulting in resulting in rendez-vous like communications. Objects are built from primitive objects by parallel composition, encapsulation...

Gaseous Oxidized Mercury Dry Deposition Measurements in the Southwestern USA: A Comparison between Texas, Eastern Oklahoma, and the Four Corners Area

Directory of Open Access Journals (Sweden)

Mark E. Sather

2014-01-01

Full Text Available Gaseous oxidized mercury (GOM dry deposition measurements using aerodynamic surrogate surface passive samplers were collected in central and eastern Texas and eastern Oklahoma, from September 2011 to September 2012. The purpose of this study was to provide an initial characterization of the magnitude and spatial extent of ambient GOM dry deposition in central and eastern Texas for a 12-month period which contained statistically average annual results for precipitation totals, temperature, and wind speed. The research objective was to investigate GOM dry deposition in areas of Texas impacted by emissions from coal-fired utility boilers and compare it with GOM dry deposition measurements previously observed in eastern Oklahoma and the Four Corners area. Annual GOM dry deposition rate estimates were relatively low in Texas, ranging from 0.1 to 0.3 ng/m2h at the four Texas monitoring sites, similar to the 0.2 ng/m2h annual GOM dry deposition rate estimate recorded at the eastern Oklahoma monitoring site. The Texas and eastern Oklahoma annual GOM dry deposition rate estimates were at least four times lower than the highest annual GOM dry deposition rate estimate previously measured in the more arid bordering western states of New Mexico and Colorado in the Four Corners area.

From DNS to RANS: A Multi-model workflow to understand the Influence of Hurricanes on Generating Turbidity Currents in the Gulf of Mexico

Science.gov (United States)

Syvitski, J. P.; Arango, H.; Harris, C. K.; Meiburg, E. H.; Jenkins, C. J.; Auad, G.; Hutton, E.; Kniskern, T. A.; Radhakrishnan, S.

2016-12-01

A loosely coupled numerical workflow is developed to address land-sea pathways for sediment routing from terrestrial and coastal sources, across the continental shelf and ultimately down the continental slope canyon system of the northern Gulf of Mexico (GOM). Model simulations represent a range of environmental conditions that might lead to the generation of turbidity-currents. The workflow comprises: 1) A simulator for the water and sediment discharged from rivers into the GOM with WMBsedv2 with calibration using USGS and USACE gauged river data; 2) Domain grids and bathymetry (ETOPO2) for the ocean models and realistic seabed sediment texture grids (dbSEABED) for the sediment transport models; 3) A spectral wave action simulator (10 km resolution) (WaveWatch III) driven by GFDL - GFS winds; 4) A simulator for ocean dynamics (ROMS) forced with ECMWF ERA winds; 5) A simulator for seafloor resuspension and transport (CSTMS); 6) Simulators (HurriSlip) of seafloor failure and flow ignition locations for boundary input to a turbidity current model; and 7) A RANS turbidity current model (TURBINS) to route sediment flows down GOM canyons, providing estimates of bottom shear stresses. TURBINS was developed first as a DNS model and then converted to an LES model wherein a dynamic turbulence closure scheme was employed. Like most DNS to LES model comparisons (these being done by the UCSB team), turbulence scaling allowed for higher Re applications but were found still not capable of simulating field scale (GOM continental canyons) environments. The LES model was next converted to a non-hydrostatic RANS model capable of field scale applications but only with a daisy-chain approach to multiple model runs along the simulated canyon floor. These model adaptations allowed the workflow to be tested for the year 1-Oct-2007 to 30-Sep-2008 that included two domain Hurricanes (Ike and Gustav). The RANS-TURBINS employed further boundary simplifications on both sediment erosion and

Availability analysis of subsea blowout preventer using Markov model considering demand rate

Directory of Open Access Journals (Sweden)

Sunghee Kim

2014-12-01

Full Text Available Availabilities of subsea Blowout Preventers (BOP in the Gulf of Mexico Outer Continental Shelf (GoM OCS is investigated using a Markov method. An updated β factor model by SINTEF is used for common-cause failures in multiple redundant systems. Coefficient values of failure rates for the Markov model are derived using the β factor model of the PDS (reliability of computer-based safety systems, Norwegian acronym method. The blind shear ram preventer system of the subsea BOP components considers a demand rate to reflect reality more. Markov models considering the demand rate for one or two components are introduced. Two data sets are compared at the GoM OCS. The results show that three or four pipe ram preventers give similar availabilities, but redundant blind shear ram preventers or annular preventers enhance the availability of the subsea BOP. Also control systems (PODs and connectors are contributable components to improve the availability of the subsea BOPs based on sensitivity analysis.

Object tracking using active appearance models

DEFF Research Database (Denmark)

Stegmann, Mikkel Bille

2001-01-01

This paper demonstrates that (near) real-time object tracking can be accomplished by the deformable template model; the Active Appearance Model (AAM) using only low-cost consumer electronics such as a PC and a web-camera. Successful object tracking of perspective, rotational and translational...

Multidimensional profiles of health status: an application of the grade of membership model to the world health survey.

Directory of Open Access Journals (Sweden)

Alessandra Andreotti

Full Text Available BACKGROUND: The World Health Organization (WHO conducted the World Health Survey (WHS between 2002 and 2004 in 70 countries to provide cross-population comparable data on health, health-related outcomes and risk factors. The aim of this study was to apply Grade of Membership (GoM modelling as a means to condense extensive health information from the WHS into a set of easily understandable health profiles and to assign the degree to which an individual belongs to each profile. PRINCIPAL FINDINGS: This paper described the application of the GoM models to summarize population health status using World Health Survey data. Grade of Membership analysis is a flexible, non-parametric, multivariate method, used to calculate health profiles from WHS self-reported health state and health conditions. The WHS dataset was divided into four country economic categories based on the World Bank economic groupings (high, upper-middle, lower-middle and low income economies for separate GoM analysis. Three main health profiles were produced for each of the four areas: I. Robust; II. Intermediate; III. Frail; moreover population health, wealth and inequalities are defined for countries in each economic area as a means to put the health results into perspective. CONCLUSIONS: These analyses have provided a robust method to better understand health profiles and the components which can help to identify healthy and non-healthy individuals. The obtained profiles have described concrete levels of health and have clearly delineated characteristics of healthy and non-healthy respondents. The GoM results provided both a useable way of summarising complex individual health information and a selection of intermediate determinants which can be targeted for interventions to improve health. As populations' age, and with limited budgets for additional costs for health care and social services, applying the GoM methods may assist with identifying higher risk profiles for decision

Intuitive modeling of vaporish objects

International Nuclear Information System (INIS)

Sokolov, Dmitry; Gentil, Christian

2015-01-01

Attempts to model gases in computer graphics started in the late 1970s. Since that time, there have been many approaches developed. In this paper we present a non-physical method allowing to create vaporish objects like clouds or smoky characters. The idea is to create a few sketches describing the rough shape of the final vaporish object. These sketches will be used as condensation sets of Iterated Function Systems, providing intuitive control over the object. The advantages of the new method are: simplicity, good control of resulting shapes and ease of eventual object animation.

Object feature extraction and recognition model

International Nuclear Information System (INIS)

Wan Min; Xiang Rujian; Wan Yongxing

2001-01-01

The characteristics of objects, especially flying objects, are analyzed, which include characteristics of spectrum, image and motion. Feature extraction is also achieved. To improve the speed of object recognition, a feature database is used to simplify the data in the source database. The feature vs. object relationship maps are stored in the feature database. An object recognition model based on the feature database is presented, and the way to achieve object recognition is also explained

A unified computational model of the development of object unity, object permanence, and occluded object trajectory perception.

Science.gov (United States)

Franz, A; Triesch, J

2010-12-01

The perception of the unity of objects, their permanence when out of sight, and the ability to perceive continuous object trajectories even during occlusion belong to the first and most important capacities that infants have to acquire. Despite much research a unified model of the development of these abilities is still missing. Here we make an attempt to provide such a unified model. We present a recurrent artificial neural network that learns to predict the motion of stimuli occluding each other and that develops representations of occluded object parts. It represents completely occluded, moving objects for several time steps and successfully predicts their reappearance after occlusion. This framework allows us to account for a broad range of experimental data. Specifically, the model explains how the perception of object unity develops, the role of the width of the occluders, and it also accounts for differences between data for moving and stationary stimuli. We demonstrate that these abilities can be acquired by learning to predict the sensory input. The model makes specific predictions and provides a unifying framework that has the potential to be extended to other visual event categories. Copyright © 2010 Elsevier Inc. All rights reserved.

Use of criteria pollutants, active and passive mercury sampling, and receptor modeling to understand the chemical forms of gaseous oxidized mercury in Florida

Science.gov (United States)

Huang, J.; Miller, M. B.; Edgerton, E.; Gustin, M. S.

2015-04-01

The highest mercury (Hg) wet deposition in the United States (US) occurs along the Gulf of Mexico, and in the southern and central Mississippi River Valley. Gaseous oxidized Hg (GOM) is thought to be a major contributor due to its high water solubility and reactivity. Therefore, it is critical to understand the concentrations, potential for wet and dry deposition, and GOM compounds present in the air. Concentrations and dry deposition fluxes of GOM were measured at Outlying Landing Field (OLF), Florida, using a Tekran® 2537/1130/1135, and active and passive samplers using cation-exchange and nylon membranes. Relationships with Tekran® derived data must be interpreted with caution, since GOM concentrations can be biased low depending on the chemical compounds in air, and interferences with water vapor and ozone. Only gaseous elemental Hg and GOM are discussed here since the PBM measurement uncertainties are higher. Criteria air pollutants were concurrently measured and Tekran® data were assessed along with these using Principal Component Analysis to identify associations among air pollutants. Based on the diel pattern, high GOM concentrations at this site were associated with fossil fuel combustion and gas phase oxidation during the day, and gas phase oxidation and transport in the free troposphere. The ratio of GEM/CO at OLF (0.008 ng m-3 ppbv-1) was much higher than the numbers reported for the Western United States and central New York for domestic emissions or biomass burning (0.001 ng m-3 ppbv-1), which we suggest is indicative of a marine boundary layer source. Results from nylon membranes with thermal desorption analyses suggest five potential GOM compounds exist in this area, including HgBr2, HgO, Hg(NO3)2, HgSO4, and an unknown compound. This indicates that the site is influenced by different gaseous phase reactions and sources. A~high GOM event related to high CO but average SO2 suggests the air parcels moved from the free troposphere and across

Malaysia and the Knowledge Economy: Building a World-Class Higher Education System. Human Development Sector Reports

Science.gov (United States)

Regel, Omporn; Salmi, Jamil; Watkins, Alfred; Tan, Hong; Dawkins, John; Saroyan, Alenoush; Vestergaard, Jakob

2007-01-01

This report was prepared at the request of the Government of Malaysia (GOM) as a contribution to the long term development objectives for the university sector under the Ninth Malaysia Plan. The GOM is considering new policy directions to make the country a more competitive player in the world economy. Such a strategy will require bold innovations…

Ferromanganese Furnace Modelling Using Object-Oriented Principles

Energy Technology Data Exchange (ETDEWEB)

Wasboe, S.O.

1996-12-31

This doctoral thesis defines an object-oriented framework for aiding unit process modelling and applies it to model high-carbon ferromanganese furnaces. A framework is proposed for aiding modelling of the internal topology and the phenomena taking place inside unit processes. Complex unit processes may consist of a number of zones where different phenomena take place. A topology is therefore defined for the unit process itself, which shows the relations between the zones. Inside each zone there is a set of chemical species and phenomena, such as reactions, phase transitions, heat transfer etc. A formalized graphical methodology is developed as a tool for modelling these zones and their interaction. The symbols defined in the graphical framework are associated with objects and classes. The rules for linking the objects are described using OMT (Object Modeling Technique) diagrams and formal language formulations. The basic classes that are defined are implemented using the C++ programming language. The ferromanganese process is a complex unit process. A general description of the process equipment is given, and a detailed discussion of the process itself and a system theoretical overview of it. The object-oriented framework is then used to develop a dynamic model based on mass and energy balances. The model is validated by measurements from an industrial furnace. 101 refs., 119 figs., 20 tabs.

An object model for beamline descriptions

International Nuclear Information System (INIS)

Hill, B.W.; Martono, H.; Gillespie, J.S.

1997-01-01

Translation of beamline model descriptions between different accelerator codes presents a unique challenge due to the different representations used for various elements and subsystems. These differences range from simple units conversions to more complex translations involving multiple beamline components. A representation of basic accelerator components is being developed in order to define a meta-structure from which beamline models, in different codes, can be described and to facilitate the translation of models between these codes. Sublines of basic components will be used to represent more complex beamline descriptions and bridge the gap between codes which may represent a beamline element as a single entity, and those which use multiple elements to describe the same physical device. A C++ object model for supporting this beamline description and a grammar for describing beamlines in terms of these components is being developed. The object model will support a common graphic user interface and translation filters for representing native beamline descriptions for a variety of accelerator codes. An overview of our work on the object model for beamline descriptions is presented here. copyright 1997 American Institute of Physics

An object-oriented approach to energy-economic modeling

Energy Technology Data Exchange (ETDEWEB)

Wise, M.A.; Fox, J.A.; Sands, R.D.

1993-12-01

In this paper, the authors discuss the experiences in creating an object-oriented economic model of the U.S. energy and agriculture markets. After a discussion of some central concepts, they provide an overview of the model, focusing on the methodology of designing an object-oriented class hierarchy specification based on standard microeconomic production functions. The evolution of the model from the class definition stage to programming it in C++, a standard object-oriented programming language, will be detailed. The authors then discuss the main differences between writing the object-oriented program versus a procedure-oriented program of the same model. Finally, they conclude with a discussion of the advantages and limitations of the object-oriented approach based on the experience in building energy-economic models with procedure-oriented approaches and languages.

Learning models of activities involving interacting objects

DEFF Research Database (Denmark)

Manfredotti, Cristina; Pedersen, Kim Steenstrup; Hamilton, Howard J.

2013-01-01

We propose the LEMAIO multi-layer framework, which makes use of hierarchical abstraction to learn models for activities involving multiple interacting objects from time sequences of data concerning the individual objects. Experiments in the sea navigation domain yielded learned models that were t...

Object interaction competence model v. 2.0

DEFF Research Database (Denmark)

Bennedsen, Jens; Schulte, C.

2013-01-01

Teaching and learning object oriented programming has to take into account the specific object oriented characteristics of program execution, namely the interaction of objects during runtime. Prior to the research reported in this article, we have developed a competence model for object interaction...

Variational data assimilative modeling of the Gulf of Maine in spring and summer 2010

Science.gov (United States)

Li, Yizhen; He, Ruoying; Chen, Ke; McGillicuddy, Dennis J.

2015-05-01

A data assimilative ocean circulation model is used to hindcast the Gulf of Maine [GOM) circulation in spring and summer 2010. Using the recently developed incremental strong constraint 4D Variational data assimilation algorithm, the model assimilates satellite sea surface temperature and in situ temperature and salinity profiles measured by expendable bathythermograph, Argo floats, and shipboard CTD casts. Validation against independent observations shows that the model skill is significantly improved after data assimilation. The data-assimilative model hindcast reproduces the temporal and spatial evolution of the ocean state, showing that a sea level depression southwest of the Scotian Shelf played a critical role in shaping the gulf-wide circulation. Heat budget analysis further demonstrates that both advection and surface heat flux contribute to temperature variability. The estimated time scale for coastal water to travel from the Scotian Shelf to the Jordan Basin is around 60 days, which is consistent with previous estimates based on in situ observations. Our study highlights the importance of resolving upstream and offshore forcing conditions in predicting the coastal circulation in the GOM.

Concurrent Models for Object Execution

OpenAIRE

Diertens, Bob

2012-01-01

In previous work we developed a framework of computational models for the concurrent execution of functions on different levels of abstraction. It shows that the traditional sequential execution of function is just a possible implementation of an abstract computational model that allows for the concurrent execution of functions. We use this framework as base for the development of abstract computational models that allow for the concurrent execution of objects.

A Bayesian alternative for multi-objective ecohydrological model specification

Science.gov (United States)

Tang, Yating; Marshall, Lucy; Sharma, Ashish; Ajami, Hoori

2018-01-01

Recent studies have identified the importance of vegetation processes in terrestrial hydrologic systems. Process-based ecohydrological models combine hydrological, physical, biochemical and ecological processes of the catchments, and as such are generally more complex and parametric than conceptual hydrological models. Thus, appropriate calibration objectives and model uncertainty analysis are essential for ecohydrological modeling. In recent years, Bayesian inference has become one of the most popular tools for quantifying the uncertainties in hydrological modeling with the development of Markov chain Monte Carlo (MCMC) techniques. The Bayesian approach offers an appealing alternative to traditional multi-objective hydrologic model calibrations by defining proper prior distributions that can be considered analogous to the ad-hoc weighting often prescribed in multi-objective calibration. Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological modeling framework based on a traditional Pareto-based model calibration technique. In our study, a Pareto-based multi-objective optimization and a formal Bayesian framework are implemented in a conceptual ecohydrological model that combines a hydrological model (HYMOD) and a modified Bucket Grassland Model (BGM). Simulations focused on one objective (streamflow/LAI) and multiple objectives (streamflow and LAI) with different emphasis defined via the prior distribution of the model error parameters. Results show more reliable outputs for both predicted streamflow and LAI using Bayesian multi-objective calibration with specified prior distributions for error parameters based on results from the Pareto front in the ecohydrological modeling. The methodology implemented here provides insight into the usefulness of multiobjective Bayesian calibration for ecohydrologic systems and the importance of appropriate prior

On the effect of model parameters on forecast objects

Science.gov (United States)

Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott

2018-04-01

Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

An object-based visual attention model for robotic applications.

Science.gov (United States)

Yu, Yuanlong; Mann, George K I; Gosine, Raymond G

2010-10-01

By extending integrated competition hypothesis, this paper presents an object-based visual attention model, which selects one object of interest using low-dimensional features, resulting that visual perception starts from a fast attentional selection procedure. The proposed attention model involves seven modules: learning of object representations stored in a long-term memory (LTM), preattentive processing, top-down biasing, bottom-up competition, mediation between top-down and bottom-up ways, generation of saliency maps, and perceptual completion processing. It works in two phases: learning phase and attending phase. In the learning phase, the corresponding object representation is trained statistically when one object is attended. A dual-coding object representation consisting of local and global codings is proposed. Intensity, color, and orientation features are used to build the local coding, and a contour feature is employed to constitute the global coding. In the attending phase, the model preattentively segments the visual field into discrete proto-objects using Gestalt rules at first. If a task-specific object is given, the model recalls the corresponding representation from LTM and deduces the task-relevant feature(s) to evaluate top-down biases. The mediation between automatic bottom-up competition and conscious top-down biasing is then performed to yield a location-based saliency map. By combination of location-based saliency within each proto-object, the proto-object-based saliency is evaluated. The most salient proto-object is selected for attention, and it is finally put into the perceptual completion processing module to yield a complete object region. This model has been applied into distinct tasks of robots: detection of task-specific stationary and moving objects. Experimental results under different conditions are shown to validate this model.

Tsunami-Induced Nearshore Hydrodynamic Modeling using a 3D VOF Method: A Gulf of Mexico Case Study

Science.gov (United States)

Kian, R.; Horrillo, J. J.; Fang, N. Z.

2017-12-01

Long-term morphology changes can be interrupted by extreme events such as hurricanes and tsunamis. In particular, the impact of tsunamis on coastal erosion and accretion patterns is presently not well understood. In order to understand the sediment movement during coastal tsunami impact a numerical sediment transport model is added to a 3D VOF model. This model allows for spatially varying bottom sediment characteristics and entails functions for entrainment, bedload, and suspended load transport. As a case study, a Gulf of Mexico (GOM) coastal study site is selected to investigate the effect of a landslide-tsunami on the coastal morphology. The GOM is recognized as a vast and productive body of water with great ecologic and economic value. The morphodynamic response of the nearshore environment to the tsunami hydrodynamic forcing is influenced by many factors including bathymetry, topography, tsunami wave and current magnitude, and the characteristics of the local bottom substrate. The 3D model addition can account for all these factors. Finally, necessary strategies for reduction of the potential tsunami impact and management of the morphological changes are discussed.

Protein Nano-Object Integrator (ProNOI for generating atomic style objects for molecular modeling

Directory of Open Access Journals (Sweden)

Smith Nicholas

2012-12-01

Full Text Available Abstract Background With the progress of nanotechnology, one frequently has to model biological macromolecules simultaneously with nano-objects. However, the atomic structures of the nano objects are typically not available or they are solid state entities. Because of that, the researchers have to investigate such nano systems by generating models of the nano objects in a manner that the existing software be able to carry the simulations. In addition, it should allow generating composite objects with complex shape by combining basic geometrical figures and embedding biological macromolecules within the system. Results Here we report the Protein Nano-Object Integrator (ProNOI which allows for generating atomic-style geometrical objects with user desired shape and dimensions. Unlimited number of objects can be created and combined with biological macromolecules in Protein Data Bank (PDB format file. Once the objects are generated, the users can use sliders to manipulate their shape, dimension and absolute position. In addition, the software offers the option to charge the objects with either specified surface or volumetric charge density and to model them with user-desired dielectric constants. According to the user preference, the biological macromolecule atoms can be assigned charges and radii according to four different force fields: Amber, Charmm, OPLS and PARSE. The biological macromolecules and the atomic-style objects are exported as a position, charge and radius (PQR file, or if a default dielectric constant distribution is not selected, it is exported as a position, charge, radius and epsilon (PQRE file. As illustration of the capabilities of the ProNOI, we created a composite object in a shape of a robot, aptly named the Clemson Robot, whose parts are charged with various volumetric charge densities and holds the barnase-barstar protein complex in its hand. Conclusions The Protein Nano-Object Integrator (ProNOI is a convenient tool for

Real time natural object modeling framework

International Nuclear Information System (INIS)

Rana, H.A.; Shamsuddin, S.M.; Sunar, M.H.

2008-01-01

CG (Computer Graphics) is a key technology for producing visual contents. Currently computer generated imagery techniques are being developed and applied, particularly in the field of virtual reality applications, film production, training and flight simulators, to provide total composition of realistic computer graphic images. Natural objects like clouds are an integral feature of the sky without them synthetic outdoor scenes seem unrealistic. Modeling and animating such objects is a difficult task. Most systems are difficult to use, as they require adjustment of numerous, complex parameters and are non-interactive. This paper presents an intuitive, interactive system to artistically model, animate, and render visually convincing clouds using modern graphics hardware. A high-level interface models clouds through the visual use of cubes. Clouds are rendered by making use of hardware accelerated API -OpenGL. The resulting interactive design and rendering system produces perceptually convincing cloud models that can be used in any interactive system. (author)

Toward a quantitative and empirical dissolved organic carbon budget for the Gulf of Maine, a semienclosed shelf sea

Science.gov (United States)

Balch, William; Huntington, Thomas G.; Aiken, George R.; Drapeau, David; Bowler, Bruce; Lubelczyk, Laura; Butler, Kenna D.

2016-01-01

A time series of organic carbon export from Gulf of Maine (GoM) watersheds was compared to a time series of biological, chemical, bio-optical, and hydrographic properties, measured across the GoM between Yarmouth, NS, Canada, and Portland, ME, U.S. Optical proxies were used to quantify the dissolved organic carbon (DOC) and particulate organic carbon in the GoM. The Load Estimator regression model applied to river discharge data demonstrated that riverine DOC export (and its decadal variance) has increased over the last 80 years. Several extraordinarily wet years (2006–2010) resulted in a massive pulse of chromophoric dissolved organic matter (CDOM; proxy for DOC) into the western GoM along with unidentified optically scattering material (Time lags between DOC discharge and its appearance in the GoM increased with distance from the river mouths. Algae were also a significant source of DOC but not CDOM. Gulf-wide algal primary production has decreased. Increases in precipitation and DOC discharge to the GoM are predicted over the next century.

Toward a quantitative and empirical dissolved organic carbon budget for the Gulf of Maine, a semienclosed shelf sea

Science.gov (United States)

Balch, William; Huntington, Thomas; Aiken, George; Drapeau, David; Bowler, Bruce; Lubelczyk, Laura; Butler, Kenna

2016-02-01

A time series of organic carbon export from Gulf of Maine (GoM) watersheds was compared to a time series of biological, chemical, bio-optical, and hydrographic properties, measured across the GoM between Yarmouth, NS, Canada, and Portland, ME, U.S. Optical proxies were used to quantify the dissolved organic carbon (DOC) and particulate organic carbon in the GoM. The Load Estimator regression model applied to river discharge data demonstrated that riverine DOC export (and its decadal variance) has increased over the last 80 years. Several extraordinarily wet years (2006-2010) resulted in a massive pulse of chromophoric dissolved organic matter (CDOM; proxy for DOC) into the western GoM along with unidentified optically scattering material (DOC in the GoM and Scotian Shelf showed the strong influence of the Gulf of Saint Lawrence on the DOC that enters the GoM. A deep plume of CDOM-rich water was observed near the coast of Maine which decreased in concentration eastward. The Forel-Ule color scale was derived and compared to the same measurements made in 1912-1913 by Henry Bigelow. Results show that the GoM has yellowed in the last century, particularly in the region of the extension of the Eastern Maine Coastal Current. Time lags between DOC discharge and its appearance in the GoM increased with distance from the river mouths. Algae were also a significant source of DOC but not CDOM. Gulf-wide algal primary production has decreased. Increases in precipitation and DOC discharge to the GoM are predicted over the next century.

Variational Data Assimilative Modeling of the Gulf of Maine Circulation in Spring and Summer 2010

OpenAIRE

Li, Yizhen; He, Ruoying; Chen, Ke; McGillicuddy, Dennis J.

2015-01-01

A data assimilative ocean circulation model is used to hindcast the Gulf of Maine (GOM) circulation in spring and summer 2010. Using the recently developed incremental strong constraint 4D Variational data assimilation algorithm, the model assimilates satellite sea surface temperature and in situ temperature and salinity profiles measured by expendable bathythermograph, Argo floats, and shipboard CTD casts. Validation against independent observations shows that the model skill is significantl...

The IRMIS object model and services API

International Nuclear Information System (INIS)

Saunders, C.; Dohan, D.A.; Arnold, N.D.

2005-01-01

The relational model developed for the Integrated Relational Model of Installed Systems (IRMIS) toolkit has been successfully used to capture the Advanced Photon Source (APS) control system software (EPICS process variables and their definitions). The relational tables are populated by a crawler script that parses each Input/Output Controller (IOC) start-up file when an IOC reboot is detected. User interaction is provided by a Java Swing application that acts as a desktop for viewing the process variable information. Mapping between the display objects and the relational tables was carried out with the Hibernate Object Relational Modeling (ORM) framework. Work is well underway at the APS to extend the relational modeling to include control system hardware. For this work, due in part to the complex user interaction required, the primary application development environment has shifted from the relational database view to the object oriented (Java) perspective. With this approach, the business logic is executed in Java rather than in SQL stored procedures. This paper describes the object model used to represent control system software, hardware, and interconnects in IRMIS. We also describe the services API used to encapsulate the required behaviors for creating and maintaining the complex data. In addition to the core schema and object model, many important concepts in IRMIS are captured by the services API. IRMIS is an ambitious collaborative effort for defining and developing a relational database and associated applications to comprehensively document the large and complex EPICS-based control systems of today's accelerators. The documentation effort includes process variables, control system hardware, and interconnections. The approach could also be used to document all components of the accelerator, including mechanical, vacuum, power supplies, etc. One key aspect of IRMIS is that it is a documentation framework, not a design and development tool. We do not

A hierarchical probabilistic model for rapid object categorization in natural scenes.

Directory of Open Access Journals (Sweden)

Xiaofu He

Full Text Available Humans can categorize objects in complex natural scenes within 100-150 ms. This amazing ability of rapid categorization has motivated many computational models. Most of these models require extensive training to obtain a decision boundary in a very high dimensional (e.g., ∼6,000 in a leading model feature space and often categorize objects in natural scenes by categorizing the context that co-occurs with objects when objects do not occupy large portions of the scenes. It is thus unclear how humans achieve rapid scene categorization.To address this issue, we developed a hierarchical probabilistic model for rapid object categorization in natural scenes. In this model, a natural object category is represented by a coarse hierarchical probability distribution (PD, which includes PDs of object geometry and spatial configuration of object parts. Object parts are encoded by PDs of a set of natural object structures, each of which is a concatenation of local object features. Rapid categorization is performed as statistical inference. Since the model uses a very small number (∼100 of structures for even complex object categories such as animals and cars, it requires little training and is robust in the presence of large variations within object categories and in their occurrences in natural scenes. Remarkably, we found that the model categorized animals in natural scenes and cars in street scenes with a near human-level performance. We also found that the model located animals and cars in natural scenes, thus overcoming a flaw in many other models which is to categorize objects in natural context by categorizing contextual features. These results suggest that coarse PDs of object categories based on natural object structures and statistical operations on these PDs may underlie the human ability to rapidly categorize scenes.

Principles of object-oriented modeling and simulation with Modelica 2.1

CERN Document Server

Fritzson, Peter

2004-01-01

A timely introduction to the latest modeling and simulation techniques. Object-oriented modeling is a fast-growing area of modeling and simulation that provides a structured, computer-supported way of doing mathematical and equation-based modeling. Modelica is today's most promising modeling language in that it effectively unifies and generalizes previous object-oriented modeling languages and provides a sound basis for the basic concepts. Principles of Object-Oriented Modeling and Simulation with Modelica 2.1 introduces the latest methods of object-oriented component-based system modeling and

Conditioning 3D object-based models to dense well data

Science.gov (United States)

Wang, Yimin C.; Pyrcz, Michael J.; Catuneanu, Octavian; Boisvert, Jeff B.

2018-06-01

Object-based stochastic simulation models are used to generate categorical variable models with a realistic representation of complicated reservoir heterogeneity. A limitation of object-based modeling is the difficulty of conditioning to dense data. One method to achieve data conditioning is to apply optimization techniques. Optimization algorithms can utilize an objective function measuring the conditioning level of each object while also considering the geological realism of the object. Here, an objective function is optimized with implicit filtering which considers constraints on object parameters. Thousands of objects conditioned to data are generated and stored in a database. A set of objects are selected with linear integer programming to generate the final realization and honor all well data, proportions and other desirable geological features. Although any parameterizable object can be considered, objects from fluvial reservoirs are used to illustrate the ability to simultaneously condition multiple types of geologic features. Channels, levees, crevasse splays and oxbow lakes are parameterized based on location, path, orientation and profile shapes. Functions mimicking natural river sinuosity are used for the centerline model. Channel stacking pattern constraints are also included to enhance the geological realism of object interactions. Spatial layout correlations between different types of objects are modeled. Three case studies demonstrate the flexibility of the proposed optimization-simulation method. These examples include multiple channels with high sinuosity, as well as fragmented channels affected by limited preservation. In all cases the proposed method reproduces input parameters for the object geometries and matches the dense well constraints. The proposed methodology expands the applicability of object-based simulation to complex and heterogeneous geological environments with dense sampling.

Mercury Speciation at a Coastal Site in the Northern Gulf of Mexico: Results from the Grand Bay Intensive Studies in Summer 2010 and Spring 2011

Directory of Open Access Journals (Sweden)

Xinrong Ren

2014-04-01

Full Text Available During two intensive studies in summer 2010 and spring 2011, measurements of mercury species including gaseous elemental mercury (GEM, gaseous oxidized mercury (GOM, and particulate-bound mercury (PBM, trace chemical species including O3, SO2, CO, NO, NOY, and black carbon, and meteorological parameters were made at an Atmospheric Mercury Network (AMNet site at the Grand Bay National Estuarine Research Reserve (NERR in Moss Point, Mississippi. Surface measurements indicate that the mean mercury concentrations were 1.42 ± 0.12 ng∙m−3 for GEM, 5.4 ± 10.2 pg∙m−3 for GOM, and 3.1 ± 1.9 pg∙m−3 for PBM during the summer 2010 intensive and 1.53 ± 0.11 ng∙m−3 for GEM, 5.3 ± 10.2 pg∙m−3 for GOM, and 5.7 ± 6.2 pg∙m−3 for PBM during the spring 2011 intensive. Elevated daytime GOM levels (>20 pg∙m−3 were observed on a few days in each study and were usually associated with either elevated O3 (>50 ppbv, BrO, and solar radiation or elevated SO2 (>a few ppbv but lower O3 (~20–40 ppbv. This behavior suggests two potential sources of GOM: photochemical oxidation of GEM and direct emissions of GOM from nearby local sources. Lack of correlation between GOM and Beryllium-7 (7Be suggests little influence on surface GOM from downward mixing of GOM from the upper troposphere. These data were analyzed using the HYSPLIT back trajectory model and principal component analysis in order to develop source-receptor relationships for mercury species in this coastal environment. Trajectory frequency analysis shows that high GOM events were generally associated with high frequencies of the trajectories passing through the areas with high mercury emissions, while low GOM levels were largely associated the trajectories passing through relatively clean areas. Principal component analysis also reveals two main factors: direct emission and photochemical processes that were clustered with high GOM and PBM. This study indicates that the receptor site

Model-based recognition of 3-D objects by geometric hashing technique

International Nuclear Information System (INIS)

Severcan, M.; Uzunalioglu, H.

1992-09-01

A model-based object recognition system is developed for recognition of polyhedral objects. The system consists of feature extraction, modelling and matching stages. Linear features are used for object descriptions. Lines are obtained from edges using rotation transform. For modelling and recognition process, geometric hashing method is utilized. Each object is modelled using 2-D views taken from the viewpoints on the viewing sphere. A hidden line elimination algorithm is used to find these views from the wire frame model of the objects. The recognition experiments yielded satisfactory results. (author). 8 refs, 5 figs

Development of a cultural heritage object BIM model

Science.gov (United States)

Braila, Natalya; Vakhrusheva, Svetlana; Martynenko, Elena; Kisel, Tatyana

2017-10-01

The BIM technology during her creation has been aimed, first of all, at design and construction branch, but its application in the field of studying and operation of architectural heritage can essentially change and transfer this kind of activity to new qualitative level. The question of effective introduction of BIM technologies at the solution of administrative questions of operation and development of monuments of architecture is considered in article. Creation of the information model of the building object of cultural heritage including a full complex of information on an object is offered: historical and archival, legal, technical, administrative, etc. The 3D model of an object of cultural heritage with color marking of elements on degree of wear and a first priority of carrying out repair will become one of components of model. This model will allow to estimate visually technical condition of the building in general and to gain general idea about scales of necessary repair and construction actions that promotes improvement of quality of operation of an object, and also simplifies and accelerates processing of information and in need of a memorial building assessment as subject to investment.

Object-Oriented Approach to Modeling Units of Pneumatic Systems

Directory of Open Access Journals (Sweden)

Yu. V. Kyurdzhiev

2014-01-01

Full Text Available The article shows the relevance of the approaches to the object-oriented programming when modeling the pneumatic units (PU.Based on the analysis of the calculation schemes of aggregates pneumatic systems two basic objects, namely a cavity flow and a material point were highlighted.Basic interactions of objects are defined. Cavity-cavity interaction: ex-change of matter and energy with the flows of mass. Cavity-point interaction: force interaction, exchange of energy in the form of operation. Point-point in-teraction: force interaction, elastic interaction, inelastic interaction, and inter-vals of displacement.The authors have developed mathematical models of basic objects and interactions. Models and interaction of elements are implemented in the object-oriented programming.Mathematical models of elements of PU design scheme are implemented in derived from the base class. These classes implement the models of flow cavity, piston, diaphragm, short channel, diaphragm to be open by a given law, spring, bellows, elastic collision, inelastic collision, friction, PU stages with a limited movement, etc.A numerical integration of differential equations for the mathematical models of PU design scheme elements is based on the Runge-Kutta method of the fourth order. On request each class performs a tact of integration i.e. calcu-lation of the coefficient method.The paper presents an integration algorithm of the system of differential equations. All objects of the PU design scheme are placed in a unidirectional class list. Iterator loop cycle initiates the integration tact of all the objects in the list. One in four iteration makes a transition to the next step of integration. Calculation process stops when any object shows a shutdowns flag.The proposed approach was tested in the calculation of a number of PU designs. With regard to traditional approaches to modeling, the authors-proposed method features in easy enhancement, code reuse, high reliability

Modeling recall memory for emotional objects in Alzheimer's disease.

Science.gov (United States)

Sundstrøm, Martin

2011-07-01

To examine whether emotional memory (EM) of objects with self-reference in Alzheimer's disease (AD) can be modeled with binomial logistic regression in a free recall and an object recognition test to predict EM enhancement. Twenty patients with AD and twenty healthy controls were studied. Six objects (three presented as gifts) were shown to each participant. Ten minutes later, a free recall and a recognition test were applied. The recognition test had target-objects mixed with six similar distracter objects. Participants were asked to name any object in the recall test and identify each object in the recognition test as known or unknown. The total of gift objects recalled in AD patients (41.6%) was larger than neutral objects (13.3%) and a significant EM recall effect for gifts was found (Wilcoxon: p recall and recognition but showed no EM enhancement due to a ceiling effect. A logistic regression showed that likelihood of emotional recall memory can be modeled as a function of MMSE score (p Recall memory was enhanced in AD patients for emotional objects indicating that EM in mild to moderate AD although impaired can be provoked with strong emotional load. The logistic regression model suggests that EM declines with the progression of AD rather than disrupts and may be a useful tool for evaluating magnitude of emotional load.

The internal/external issue what is an outer object? Another person as object and as separate other in object relations models.

Science.gov (United States)

Zachrisson, Anders

2013-01-01

The question of what we mean by the term outer object has its roots in the epistemological foundation of psychoanalysis. From the very beginning, Freud's view was Kantian, and psychoanalysis has kept that stance, as it seems. The author reviews the internal/external issue in Freud's thinking and in the central object relations theories (Klein, Winnicott, and Bion). On this background he proposes a simple model to differentiate the concept of object along one central dimension: internal object, external object, and actual person. The main arguments are: (1) there is no direct, unmediated perception of the actual person--the experience of the other is always affected by the perceiver's subjectivity; (2) in intense transference reactions and projections, the perception of the person is dominated by the qualities of an inner object--and the other person "becomes" an external object for the perceiver; (3) when this distortion is less dominating, the other person to a higher degree remains a separate other--a person in his or her own right. Clinical material illustrates these phenomena, and a graphical picture of the model is presented. Finally with the model as background, the author comments on a selection of phenomena and concepts such as unobjectionable transference, "the third position," mourning and loneliness. The way that the internal colours and distorts the external is of course a central preoccupation of psychoanalysis generally. (Spillius et al., 2011, p. 326)

Turbulence and Self-Organization Modeling Astrophysical Objects

CERN Document Server

Marov, Mikhail Ya

2013-01-01

This book focuses on the development of continuum models of natural turbulent media. It provides a theoretical approach to the solutions of different problems related to the formation, structure and evolution of astrophysical and geophysical objects. A stochastic modeling approach is used in the mathematical treatment of these problems, which reflects self-organization processes in open dissipative systems. The authors also consider examples of ordering for various objects in space throughout their evolutionary processes. This volume is aimed at graduate students and researchers in the fields of mechanics, astrophysics, geophysics, planetary and space science.

Constructing Multidatabase Collections Using Extended ODMG Object Model

Directory of Open Access Journals (Sweden)

Adrian Skehill Mark Roantree

1999-11-01

Full Text Available Collections are an important feature in database systems. They provide us with the ability to group objects of interest together, and then to manipulate them in the required fashion. The OASIS project is focused on the construction a multidatabase prototype which uses the ODMG model and a canonical model. As part of this work we have extended the base model to provide a more powerful collection mechanism, and to permit the construction of a federated collection, a collection of heterogenous objects taken from distributed data sources

Uncertain and multi-objective programming models for crop planting structure optimization

Directory of Open Access Journals (Sweden)

Mo LI,Ping GUO,Liudong ZHANG,Chenglong ZHANG

2016-03-01

Full Text Available Crop planting structure optimization is a significant way to increase agricultural economic benefits and improve agricultural water management. The complexities of fluctuating stream conditions, varying economic profits, and uncertainties and errors in estimated modeling parameters, as well as the complexities among economic, social, natural resources and environmental aspects, have led to the necessity of developing optimization models for crop planting structure which consider uncertainty and multi-objectives elements. In this study, three single-objective programming models under uncertainty for crop planting structure optimization were developed, including an interval linear programming model, an inexact fuzzy chance-constrained programming (IFCCP model and an inexact fuzzy linear programming (IFLP model. Each of the three models takes grayness into account. Moreover, the IFCCP model considers fuzzy uncertainty of parameters/variables and stochastic characteristics of constraints, while the IFLP model takes into account the fuzzy uncertainty of both constraints and objective functions. To satisfy the sustainable development of crop planting structure planning, a fuzzy-optimization-theory-based fuzzy linear multi-objective programming model was developed, which is capable of reflecting both uncertainties and multi-objective. In addition, a multi-objective fractional programming model for crop structure optimization was also developed to quantitatively express the multi-objective in one optimization model with the numerator representing maximum economic benefits and the denominator representing minimum crop planting area allocation. These models better reflect actual situations, considering the uncertainties and multi-objectives of crop planting structure optimization systems. The five models developed were then applied to a real case study in Minqin County, north-west China. The advantages, the applicable conditions and the solution methods

A Dynamic Object Behavior Model and Implementation Based on Computational Reflection

Institute of Scientific and Technical Information of China (English)

HE Cheng-wan; HE Fei; HE Ke-qing

2005-01-01

A dynamic object behavior model based on computational reflection is proposed. This model consists of function level and meta level, the meta objects in meta level manage the base objects and behaviors in function level, including dynamic binding and unbinding of base object and behavior.We implement this model with RoleJava Language, which is our self linguistic extension of the Java Language. Meta Objects are generated automatically at compile-time, this makes the reflecton mechanism transparent to programmers. Finally an example applying this model to a banking system is presented.

Oscillating shells: A model for a variable cosmic object

OpenAIRE

Nunez, Dario

1997-01-01

A model for a possible variable cosmic object is presented. The model consists of a massive shell surrounding a compact object. The gravitational and self-gravitational forces tend to collapse the shell, but the internal tangential stresses oppose the collapse. The combined action of the two types of forces is studied and several cases are presented. In particular, we investigate the spherically symmetric case in which the shell oscillates radially around a central compact object.

Probabilistic object and viewpoint models for active object recognition

CSIR Research Space (South Africa)

Govender, N

2013-09-01

Full Text Available ,θ′(f occ). V. EXPERIMENTS A. Dataset For our experiments, we use the active recognition dataset introduced by [12]. The training data consists of everyday objects such as cereal boxes, ornaments, spice bottle, etc. Images were captured every 20 degrees... are to be verified TABLE I CONFUSION MATRIX FOR BINARY A MODEL Obscured Obscured Obscured Obscured Obscured Obscured Obscured Obscured Obscured Obscured Cereal Battery Curry box Elephant Handbag MrMin Salad Bottle Spice Bottle Spray Can Spray Can 1 Cereal 0.9800 0...

Apricot - An Object-Oriented Modeling Language for Hybrid Systems

OpenAIRE

Fang, Huixing; Zhu, Huibiao; Shi, Jianqi

2013-01-01

We propose Apricot as an object-oriented language for modeling hybrid systems. The language combines the features in domain specific language and object-oriented language, that fills the gap between design and implementation, as a result, we put forward the modeling language with simple and distinct syntax, structure and semantics. In addition, we introduce the concept of design by convention into Apricot.As the characteristic of object-oriented and the component architecture in Apricot, we c...

Time-dependent inhomogeneous jet models for BL Lac objects

Science.gov (United States)

Marlowe, A. T.; Urry, C. M.; George, I. M.

1992-05-01

Relativistic beaming can explain many of the observed properties of BL Lac objects (e.g., rapid variability, high polarization, etc.). In particular, the broadband radio through X-ray spectra are well modeled by synchrotron-self Compton emission from an inhomogeneous relativistic jet. We have done a uniform analysis on several BL Lac objects using a simple but plausible inhomogeneous jet model. For all objects, we found that the assumed power-law distribution of the magnetic field and the electron density can be adjusted to match the observed BL Lac spectrum. While such models are typically unconstrained, consideration of spectral variability strongly restricts the allowed parameters, although to date the sampling has generally been too sparse to constrain the current models effectively. We investigate the time evolution of the inhomogeneous jet model for a simple perturbation propagating along the jet. The implications of this time evolution model and its relevance to observed data are discussed.

A PDP model of the simultaneous perception of multiple objects

Science.gov (United States)

Henderson, Cynthia M.; McClelland, James L.

2011-06-01

Illusory conjunctions in normal and simultanagnosic subjects are two instances where the visual features of multiple objects are incorrectly 'bound' together. A connectionist model explores how multiple objects could be perceived correctly in normal subjects given sufficient time, but could give rise to illusory conjunctions with damage or time pressure. In this model, perception of two objects benefits from lateral connections between hidden layers modelling aspects of the ventral and dorsal visual pathways. As with simultanagnosia, simulations of dorsal lesions impair multi-object recognition. In contrast, a large ventral lesion has minimal effect on dorsal functioning, akin to dissociations between simple object manipulation (retained in visual form agnosia and semantic dementia) and object discrimination (impaired in these disorders) [Hodges, J.R., Bozeat, S., Lambon Ralph, M.A., Patterson, K., and Spatt, J. (2000), 'The Role of Conceptual Knowledge: Evidence from Semantic Dementia', Brain, 123, 1913-1925; Milner, A.D., and Goodale, M.A. (2006), The Visual Brain in Action (2nd ed.), New York: Oxford]. It is hoped that the functioning of this model might suggest potential processes underlying dorsal and ventral contributions to the correct perception of multiple objects.

Model-based object classification using unification grammars and abstract representations

Science.gov (United States)

Liburdy, Kathleen A.; Schalkoff, Robert J.

1993-04-01

The design and implementation of a high level computer vision system which performs object classification is described. General object labelling and functional analysis require models of classes which display a wide range of geometric variations. A large representational gap exists between abstract criteria such as `graspable' and current geometric image descriptions. The vision system developed and described in this work addresses this problem and implements solutions based on a fusion of semantics, unification, and formal language theory. Object models are represented using unification grammars, which provide a framework for the integration of structure and semantics. A methodology for the derivation of symbolic image descriptions capable of interacting with the grammar-based models is described and implemented. A unification-based parser developed for this system achieves object classification by determining if the symbolic image description can be unified with the abstract criteria of an object model. Future research directions are indicated.

Heterogeneous Deformable Modeling of Bio-Tissues and Haptic Force Rendering for Bio-Object Modeling

Science.gov (United States)

Lin, Shiyong; Lee, Yuan-Shin; Narayan, Roger J.

This paper presents a novel technique for modeling soft biological tissues as well as the development of an innovative interface for bio-manufacturing and medical applications. Heterogeneous deformable models may be used to represent the actual internal structures of deformable biological objects, which possess multiple components and nonuniform material properties. Both heterogeneous deformable object modeling and accurate haptic rendering can greatly enhance the realism and fidelity of virtual reality environments. In this paper, a tri-ray node snapping algorithm is proposed to generate a volumetric heterogeneous deformable model from a set of object interface surfaces between different materials. A constrained local static integration method is presented for simulating deformation and accurate force feedback based on the material properties of a heterogeneous structure. Biological soft tissue modeling is used as an example to demonstrate the proposed techniques. By integrating the heterogeneous deformable model into a virtual environment, users can both observe different materials inside a deformable object as well as interact with it by touching the deformable object using a haptic device. The presented techniques can be used for surgical simulation, bio-product design, bio-manufacturing, and medical applications.

Multi-objective possibilistic model for portfolio selection with transaction cost

Science.gov (United States)

Jana, P.; Roy, T. K.; Mazumder, S. K.

2009-06-01

In this paper, we introduce the possibilistic mean value and variance of continuous distribution, rather than probability distributions. We propose a multi-objective Portfolio based model and added another entropy objective function to generate a well diversified asset portfolio within optimal asset allocation. For quantifying any potential return and risk, portfolio liquidity is taken into account and a multi-objective non-linear programming model for portfolio rebalancing with transaction cost is proposed. The models are illustrated with numerical examples.

Knowledge-Based Topic Model for Unsupervised Object Discovery and Localization.

Science.gov (United States)

Niu, Zhenxing; Hua, Gang; Wang, Le; Gao, Xinbo

Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object

Conceptual Modeling of Events as Information Objects and Change Agents

DEFF Research Database (Denmark)

Bækgaard, Lars

as a totality of an information object and a change agent. When an event is modeled as an information object it is comparable to an entity that exists only at a specific point in time. It has attributes and can be used for querying and specification of constraints. When an event is modeled as a change agent...... it is comparable to an executable transaction schema. Finally, we briefly compare our approach to object-oriented approaches based on encapsulated objects....

The areal extent of brown shrimp habitat suitability in Mobile Bay, Alabama, USA: Targeting vegetated habitat restoration

Science.gov (United States)

Smith, L.M.; Nestlerode, J.A.; Harwell, L.C.; Bourgeois, P.

2010-01-01

The availability of wetlands and shallow water habitats significantly influences Gulf of Mexico (GOM) penaeid shrimp fishery productivity. However, the GOM region has the highest rate of wetland loss in the USA. Protection and management of these vital GOM habitats are critical to sustainable shrimp fisheries. Brown shrimp (Farfantepenaeus aztecus) are a major component of GOM fisheries. We present an approach for estimating the areal extent of suitable habitat for post-larval and juvenile brown shrimp in Mobile Bay, Alabama, using an existing habitat suitability index model for the northern GOM calculated from probabilistic survey of water quality and sediment data, land cover data, and submerged aquatic vegetation coverages. This estuarine scale approach is intended to support targeted protection and restoration of these habitats. These analyses indicate that approximately 60% of the area of Mobile Bay is categorized as suitable to near optimal for post-larval and juvenile shrimp and 38% of the area is marginally to minimally suitable. We identify potential units within Mobile Bay for targeted restoration to improve habitat suitability. ?? 2010 Springer Science+Business Media B.V.

Modeling business objects with XML schema

CERN Document Server

Daum, Berthold

2003-01-01

XML Schema is the new language standard from the W3C and the new foundation for defining data in Web-based systems. There is a wealth of information available about Schemas but very little understanding of how to use this highly formal specification for creating documents. Grasping the power of Schemas means going back to the basics of documents themselves, and the semantic rules, or grammars, that define them. Written for schema designers, system architects, programmers, and document authors, Modeling Business Objects with XML Schema guides you through understanding Schemas from the basic concepts, type systems, type derivation, inheritance, namespace handling, through advanced concepts in schema design.*Reviews basic XML syntax and the Schema recommendation in detail.*Builds a knowledge base model step by step (about jazz music) that is used throughout the book.*Discusses Schema design in large environments, best practice design patterns, and Schema''s relation to object-oriented concepts.

Fuzzy object models for newborn brain MR image segmentation

Science.gov (United States)

Kobashi, Syoji; Udupa, Jayaram K.

2013-03-01

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

Fast Appearance Modeling for Automatic Primary Video Object Segmentation.

Science.gov (United States)

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

2016-02-01

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

3D object-oriented image analysis in 3D geophysical modelling

DEFF Research Database (Denmark)

Fadel, I.; van der Meijde, M.; Kerle, N.

2015-01-01

Non-uniqueness of satellite gravity interpretation has traditionally been reduced by using a priori information from seismic tomography models. This reduction in the non-uniqueness has been based on velocity-density conversion formulas or user interpretation of the 3D subsurface structures (objects......) based on the seismic tomography models and then forward modelling these objects. However, this form of object-based approach has been done without a standardized methodology on how to extract the subsurface structures from the 3D models. In this research, a 3D object-oriented image analysis (3D OOA......) approach was implemented to extract the 3D subsurface structures from geophysical data. The approach was applied on a 3D shear wave seismic tomography model of the central part of the East African Rift System. Subsequently, the extracted 3D objects from the tomography model were reconstructed in the 3D...

A Convergent Participation Model for Evaluation of Learning Objects

Directory of Open Access Journals (Sweden)

John Nesbit

2002-10-01

Full Text Available The properties that distinguish learning objects from other forms of educational software - global accessibility, metadata standards, finer granularity and reusability - have implications for evaluation. This article proposes a convergent participation model for learning object evaluation in which representatives from stakeholder groups (e.g., students, instructors, subject matter experts, instructional designers, and media developers converge toward more similar descriptions and ratings through a two-stage process supported by online collaboration tools. The article reviews evaluation models that have been applied to educational software and media, considers models for gathering and meta-evaluating individual user reviews that have recently emerged on the Web, and describes the peer review model adopted for the MERLOT repository. The convergent participation model is assessed in relation to other models and with respect to its support for eight goals of learning object evaluation: (1 aid for searching and selecting, (2 guidance for use, (3 formative evaluation, (4 influence on design practices, (5 professional development and student learning, (6 community building, (7 social recognition, and (8 economic exchange.

Integrated production planning and control: A multi-objective optimization model

Directory of Open Access Journals (Sweden)

Cheng Wang

2013-09-01

Full Text Available Purpose: Production planning and control has crucial impact on the production and business activities of enterprise. Enterprise Resource Planning (ERP is the most popular resources planning and management system, however there are some shortcomings and deficiencies in the production planning and control because its core component is still the Material Requirements Planning (MRP. For the defects of ERP system, many local improvement and optimization schemes have been proposed, and improve the feasibility and practicality of the plan in some extent, but study considering the whole planning system optimization in the multiple performance management objectives and achieving better application performance is less. The purpose of this paper is to propose a multi-objective production planning optimization model Based on the point of view of the integration of production planning and control, in order to achieve optimization and control of enterprise manufacturing management. Design/methodology/approach: On the analysis of ERP planning system’s defects and disadvantages, and related research and literature, a multi-objective production planning optimization model is proposed, in addition to net demand and capacity, multiple performance management objectives, such as on-time delivery, production balance, inventory, overtime production, are considered incorporating into the examination scope of the model, so that the manufacturing process could be management and controlled Optimally between multiple objectives. The validity and practicability of the model will be verified by the instance in the last part of the paper. Findings: The main finding is that production planning management of manufacturing enterprise considers not only the capacity and materials, but also a variety of performance management objectives in the production process, and building a multi-objective optimization model can effectively optimize the management and control of enterprise

POMP - Pervasive Object Model Project

DEFF Research Database (Denmark)

Schougaard, Kari Rye; Schultz, Ulrik Pagh

The focus on mobile devices is continuously increasing, and improved device connectivity enables the construction of pervasive computing systems composed of heterogeneous collections of devices. Users who employ different devices throughout their daily activities naturally expect their applications...... computing environment. This system, named POM (Pervasive Object Model), supports applications split into coarse-grained, strongly mobile units that communicate using method invocations through proxies. We are currently investigating efficient execution of mobile applications, scalability to suit...

Behavioral models as theoretical frames to analyze the business objective

Directory of Open Access Journals (Sweden)

Hernán Alonso Bafico

2015-12-01

Full Text Available This paper examines Pfeffer’s Models of Behavior and connects each of them with attributes of the definition of the firm’s objective, assumed as the maximization of the sustainable, long term valor of the residual claims.Each of the five models of behavior (rational, social, moral, retrospective and cognitive contributes to the decision making and goal setting processes with its particular and complementary elements. From those assuming complete rationality and frictionless markets, to the models emphasizing the role of ethical positions, and the presence of perceptive and cognitive mechanisms. The analysis highlights the main contributions of critical theories and models of behavior, underlining their focus on non-traditional variables, regarded as critical inputs for goal setting processes and designing alternative executive incentive schemes.  The explicit consideration of those variables does not indicate the need for a new definition of corporate objective. The maximization of the long term value of the shareholders’ claims still defines the relevant objective function of the firm, remaining as the main yardstick of corporate performance.Behavioral models are recognized as important tools to help managers direct their attention to long term strategies. In the last part, we comment on the relationship between the objective function and behavioral models, from the practitioners’ perspective.Key words: Firm Objectives, Behavioral Models, Value Maximization, Stakeholder Theory.

[Requirements imposed on model objects in microevolutionary investigations].

Science.gov (United States)

Mina, M V

2015-01-01

Extrapolation of results of investigations of a model object is justified only within the limits of a set of objects that have essential properties in common with the modal object. Which properties are essential depends on the aim of a study. Similarity of objects emerged in the process of their independent evolution does not prove similarity of ways and mechanisms of their evolution. If the objects differ in their essential properties then extrapolation of results of investigation of an object on another one is risky because it may lead to wrong decisions and, moreover, to the loss of interest to alternative hypotheses. Positions formulated above are considered with the reference to species flocks of fishes, large African Barbus in particular.

Object Oriented Modelling and Dynamical Simulation

DEFF Research Database (Denmark)

Wagner, Falko Jens; Poulsen, Mikael Zebbelin

1998-01-01

This report with appendix describes the work done in master project at DTU.The goal of the project was to develop a concept for simulation of dynamical systems based on object oriented methods.The result was a library of C++-classes, for use when both building componentbased models and when...

Moving objects management models, techniques and applications

CERN Document Server

Meng, Xiaofeng; Xu, Jiajie

2014-01-01

This book describes the topics of moving objects modeling and location tracking, indexing and querying, clustering, location uncertainty, traffic aware navigation and privacy issues as well as the application to intelligent transportation systems.

Effectiveness of meta-models for multi-objective optimization of centrifugal impeller

Energy Technology Data Exchange (ETDEWEB)

Bellary, Sayed Ahmed Imran; Samad, Abdus [Indian Institute of Technology Madras, Chennai (India); Husain, Afzal [Sultan Qaboos University, Al-Khoudh (Oman)

2014-12-15

The major issue of multiple fidelity based analysis and optimization of fluid machinery system depends upon the proper construction of low fidelity model or meta-model. A low fidelity model uses responses obtained from a high fidelity model, and the meta-model is then used to produce population of solutions required for evolutionary algorithm for multi-objective optimization. The Pareto-optimal front which shows functional relationships among the multiple objectives can produce erroneous results if the low fidelity models are not well-constructed. In the present research, response surface approximation and Kriging meta-models were evaluated for their effectiveness for the application in the turbomachinery design and optimization. A high fidelity model such as CFD technique along with the metamodels was used to obtain Pareto-optimal front via multi-objective genetic algorithm. A centrifugal impeller has been considered as case study to find relationship between two conflicting objectives, viz., hydraulic efficiency and head. Design variables from the impeller geometry have been chosen and the responses of the objective functions were evaluated through CFD analysis. The fidelity of each metamodel has been discussed in context of their predictions in entire design space in general and near optimal region in particular. Exploitation of the multiple meta-models enhances the quality of multi-objective optimization and provides the information pertaining to fidelity of optimization model. It was observed that the Kriging meta-model was better suited for this type of problem as it involved less approximation error in the Pareto-optimal front.

Effectiveness of meta-models for multi-objective optimization of centrifugal impeller

International Nuclear Information System (INIS)

Bellary, Sayed Ahmed Imran; Samad, Abdus; Husain, Afzal

2014-01-01

The major issue of multiple fidelity based analysis and optimization of fluid machinery system depends upon the proper construction of low fidelity model or meta-model. A low fidelity model uses responses obtained from a high fidelity model, and the meta-model is then used to produce population of solutions required for evolutionary algorithm for multi-objective optimization. The Pareto-optimal front which shows functional relationships among the multiple objectives can produce erroneous results if the low fidelity models are not well-constructed. In the present research, response surface approximation and Kriging meta-models were evaluated for their effectiveness for the application in the turbomachinery design and optimization. A high fidelity model such as CFD technique along with the metamodels was used to obtain Pareto-optimal front via multi-objective genetic algorithm. A centrifugal impeller has been considered as case study to find relationship between two conflicting objectives, viz., hydraulic efficiency and head. Design variables from the impeller geometry have been chosen and the responses of the objective functions were evaluated through CFD analysis. The fidelity of each metamodel has been discussed in context of their predictions in entire design space in general and near optimal region in particular. Exploitation of the multiple meta-models enhances the quality of multi-objective optimization and provides the information pertaining to fidelity of optimization model. It was observed that the Kriging meta-model was better suited for this type of problem as it involved less approximation error in the Pareto-optimal front.

GSMNet: A Hierarchical Graph Model for Moving Objects in Networks

Directory of Open Access Journals (Sweden)

Hengcai Zhang

2017-03-01

Full Text Available Existing data models for moving objects in networks are often limited by flexibly controlling the granularity of representing networks and the cost of location updates and do not encompass semantic information, such as traffic states, traffic restrictions and social relationships. In this paper, we aim to fill the gap of traditional network-constrained models and propose a hierarchical graph model called the Geo-Social-Moving model for moving objects in Networks (GSMNet that adopts four graph structures, RouteGraph, SegmentGraph, ObjectGraph and MoveGraph, to represent the underlying networks, trajectories and semantic information in an integrated manner. The bulk of user-defined data types and corresponding operators is proposed to handle moving objects and answer a new class of queries supporting three kinds of conditions: spatial, temporal and semantic information. Then, we develop a prototype system with the native graph database system Neo4Jto implement the proposed GSMNet model. In the experiment, we conduct the performance evaluation using simulated trajectories generated from the BerlinMOD (Berlin Moving Objects Database benchmark and compare with the mature MOD system Secondo. The results of 17 benchmark queries demonstrate that our proposed GSMNet model has strong potential to reduce time-consuming table join operations an d shows remarkable advantages with regard to representing semantic information and controlling the cost of location updates.

Source characterization and tsunami modeling of submarine landslides along the Yucatán Shelf/Campeche Escarpment, southern Gulf of Mexico

Science.gov (United States)

Chaytor, Jason D.; Geist, Eric L.; Paull, Charles K.; Caress, David W; Gwiazda, Roberto; Urrutia Fucugauchi, Jaime; Rebolledo Vieyra, Mario

2016-01-01

Submarine landslides occurring along the margins of the Gulf of Mexico (GOM) represent a low-likelihood, but potentially damaging source of tsunamis. New multibeam bathymetry coverage reveals that mass wasting is pervasive along the Yucatán Shelf edge with several large composite landslides possibly removing as much as 70 km3 of the Cenozoic sedimentary section in a single event. Using GIS-based analysis, the dimensions of six landslides from the central and northern sections of the Yucatán Shelf/Campeche Escarpment were determined and used as input for preliminary tsunami generation and propagation models. Tsunami modeling is performed to compare the propagation characteristics and distribution of maximum amplitudes throughout the GOM among the different landslide scenarios. Various factors such as landslide geometry, location along the Yucatán Shelf/Campeche Escarpment, and refraction during propagation result in significant variations in the affected part of the Mexican and US Gulf Coasts. In all cases, however, tsunami amplitudes are greatest along the northern Yucatán Peninsula.

Farm Planning by Fuzzy Multi Objective Programming Model

Directory of Open Access Journals (Sweden)

m Raei Jadidi

2010-05-01

Full Text Available In current study, Fuzzy Goal Programming (FGP model by considering a set of social and economic goals, was applied to optimal land allocation in Koshksaray district, Marand city, East Azarbaijan province, Iran. Farmer goals including total cultivable area, factor of production, production levels of various crops and total expected profit were considered fuzzily in establishment of the model. The goals were considered by 16 scenarios in the form of single objective, compound and priority structures. Results showed that, cost minimization in single objective and compound scenario is the best as compared with current conditions. In priority structure, scenario 10 with priorities of profit maximization, cost minimization, satisfying of production goals considering cost minimization and production goals, and scenario 13 with priorities of profit maximization, satisfying factor of production goals, cost minimization and fulfilling production goals, had minimum Euclidean Distance and satisfied the fuzzy objectives. Moreover, dry barley, irrigated and dry wheat and irrigated barely had maximum and minimum cultivated area, respectively. According to the findings, by reallocation of resources, farmers can achieve their better goals and objectives.

Parametric Adjustments to the Rankine Vortex Wind Model for Gulf of Mexico Hurricanes

Science.gov (United States)

2012-11-01

2012 4. TITLE AND SUBTITLE Parametric Adjustments to the Rankine Vortex Wind Model for Gulf of Mexico Hurricanes 5a. CONTRACT NUMBER 5b. GRANT ...may be used to construct spatially varying wind fields for the GOM region (e.g., Thompson and Cardone [12]), but this requires using a complicated...Storm Damage Reduc- tion, and Dredging Operations and Environmental Research (DOER). The USACE Headquarters granted permission to publish this paper

Sound Synthesis of Objects Swinging through Air Using Physical Models

Directory of Open Access Journals (Sweden)

Rod Selfridge

2017-11-01

Full Text Available A real-time physically-derived sound synthesis model is presented that replicates the sounds generated as an object swings through the air. Equations obtained from fluid dynamics are used to determine the sounds generated while exposing practical parameters for a user or game engine to vary. Listening tests reveal that for the majority of objects modelled, participants rated the sounds from our model as plausible as actual recordings. The sword sound effect performed worse than others, and it is speculated that one cause may be linked to the difference between expectations of a sound and the actual sound for a given object.

Moving object detection using dynamic motion modelling from UAV aerial images.

Science.gov (United States)

Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid

2014-01-01

Motion analysis based moving object detection from UAV aerial image is still an unsolved issue due to inconsideration of proper motion estimation. Existing moving object detection approaches from UAV aerial images did not deal with motion based pixel intensity measurement to detect moving object robustly. Besides current research on moving object detection from UAV aerial images mostly depends on either frame difference or segmentation approach separately. There are two main purposes for this research: firstly to develop a new motion model called DMM (dynamic motion model) and secondly to apply the proposed segmentation approach SUED (segmentation using edge based dilation) using frame difference embedded together with DMM model. The proposed DMM model provides effective search windows based on the highest pixel intensity to segment only specific area for moving object rather than searching the whole area of the frame using SUED. At each stage of the proposed scheme, experimental fusion of the DMM and SUED produces extracted moving objects faithfully. Experimental result reveals that the proposed DMM and SUED have successfully demonstrated the validity of the proposed methodology.

Balance between calibration objectives in a conceptual hydrological model

NARCIS (Netherlands)

Booij, Martijn J.; Krol, Martinus S.

2010-01-01

Three different measures to determine the optimum balance between calibration objectives are compared: the combined rank method, parameter identifiability and model validation. Four objectives (water balance, hydrograph shape, high flows, low flows) are included in each measure. The contributions of

Application of object modeling technique to medical image retrieval system

International Nuclear Information System (INIS)

Teshima, Fumiaki; Abe, Takeshi

1993-01-01

This report describes the results of discussions on the object-oriented analysis methodology, which is one of the object-oriented paradigms. In particular, we considered application of the object modeling technique (OMT) to the analysis of a medical image retrieval system. The object-oriented methodology places emphasis on the construction of an abstract model from real-world entities. The effectiveness of and future improvements to OMT are discussed from the standpoint of the system's expandability. These discussions have elucidated that the methodology is sufficiently well-organized and practical to be applied to commercial products, provided that it is applied to the appropriate problem domain. (author)

An object model for genome information at all levels of resolution

Energy Technology Data Exchange (ETDEWEB)

Honda, S.; Parrott, N.W.; Smith, R.; Lawrence, C.

1993-12-31

An object model for genome data at all levels of resolution is described. The model was derived by considering the requirements for representing genome related objects in three application domains: genome maps, large-scale DNA sequencing, and exploring functional information in gene and protein sequences. The methodology used for the object-oriented analysis is also described.

Single-objective vs. multi-objective autocalibration in modelling total suspended solids and phosphorus in a small agricultural watershed with SWAT.

Science.gov (United States)

Rasolomanana, Santatriniaina Denise; Lessard, Paul; Vanrolleghem, Peter A

2012-01-01

To obtain greater precision in modelling small agricultural watersheds, a shorter simulation time step is beneficial. A daily time step better represents the dynamics of pollutants in the river and provides more realistic simulation results. However, with a daily evaluation performance, good fits are rarely obtained. With the Shuffled Complex Evolution (SCE) method embedded in the Soil and Water Assessment Tool (SWAT), two calibration approaches are available, single-objective or multi-objective optimization. The goal of the present study is to evaluate which approach can improve the daily performance with SWAT, in modelling flow (Q), total suspended solids (TSS) and total phosphorus (TP). The influence of weights assigned to the different variables included in the objective function has also been tested. The results showed that: (i) the model performance depends not only on the choice of calibration approach, but essentially on the influential parameters; (ii) the multi-objective calibration estimating at once all parameters related to all measured variables is the best approach to model Q, TSS and TP; (iii) changing weights does not improve model performance; and (iv) with a single-objective optimization, an excellent water quality modelling performance may hide a loss of performance of predicting flows and unbalanced internal model components.

Feedforward Object-Vision Models Only Tolerate Small Image Variations Compared to Human

Directory of Open Access Journals (Sweden)

Masoud eGhodrati

2014-07-01

Full Text Available Invariant object recognition is a remarkable ability of primates' visual system that its underlying mechanism has constantly been under intense investigations. Computational modelling is a valuable tool toward understanding the processes involved in invariant object recognition. Although recent computational models have shown outstanding performances on challenging image databases, they fail to perform well when images with more complex variations of the same object are applied to them. Studies have shown that making sparse representation of objects by extracting more informative visual features through a feedforward sweep can lead to higher recognition performances. Here, however, we show that when the complexity of image variations is high, even this approach results in poor performance compared to humans. To assess the performance of models and humans in invariant object recognition tasks, we built a parametrically controlled image database consisting of several object categories varied in different dimensions and levels, rendered from 3D planes. Comparing the performance of several object recognition models with human observers shows that only in low-level image variations the models perform similar to humans in categorization tasks. Furthermore, the results of our behavioral experiments demonstrate that, even under difficult experimental conditions (i.e. briefly presented masked stimuli with complex image variations, human observers performed outstandingly well, suggesting that the models are still far from resembling humans in invariant object recognition. Taken together, we suggest that learning sparse informative visual features, although desirable, is not a complete solution for future progresses in object-vision modelling. We show that this approach is not of significant help in solving the computational crux of object recognition (that is invariant object recognition when the identity-preserving image variations become more complex.

Efficient view based 3-D object retrieval using Hidden Markov Model

Science.gov (United States)

Jain, Yogendra Kumar; Singh, Roshan Kumar

2013-12-01

Recent research effort has been dedicated to view based 3-D object retrieval, because of highly discriminative property of 3-D object and has multi view representation. The state-of-art method is highly depending on their own camera array setting for capturing views of 3-D object and use complex Zernike descriptor, HAC for representative view selection which limit their practical application and make it inefficient for retrieval. Therefore, an efficient and effective algorithm is required for 3-D Object Retrieval. In order to move toward a general framework for efficient 3-D object retrieval which is independent of camera array setting and avoidance of representative view selection, we propose an Efficient View Based 3-D Object Retrieval (EVBOR) method using Hidden Markov Model (HMM). In this framework, each object is represented by independent set of view, which means views are captured from any direction without any camera array restriction. In this, views are clustered (including query view) to generate the view cluster, which is then used to build the query model with HMM. In our proposed method, HMM is used in twofold: in the training (i.e. HMM estimate) and in the retrieval (i.e. HMM decode). The query model is trained by using these view clusters. The EVBOR query model is worked on the basis of query model combining with HMM. The proposed approach remove statically camera array setting for view capturing and can be apply for any 3-D object database to retrieve 3-D object efficiently and effectively. Experimental results demonstrate that the proposed scheme has shown better performance than existing methods. [Figure not available: see fulltext.

Critically Important Object Security System Element Model

Directory of Open Access Journals (Sweden)

I. V. Khomyackov

2012-03-01

Full Text Available A stochastic model of critically important object security system element has been developed. The model includes mathematical description of the security system element properties and external influences. The state evolution of the security system element is described by the semi-Markov process with finite states number, the semi-Markov matrix and the initial semi-Markov process states probabilities distribution. External influences are set with the intensity of the Poisson thread.

Combining multi-objective optimization and bayesian model averaging to calibrate forecast ensembles of soil hydraulic models

Energy Technology Data Exchange (ETDEWEB)

Vrugt, Jasper A [Los Alamos National Laboratory; Wohling, Thomas [NON LANL

2008-01-01

Most studies in vadose zone hydrology use a single conceptual model for predictive inference and analysis. Focusing on the outcome of a single model is prone to statistical bias and underestimation of uncertainty. In this study, we combine multi-objective optimization and Bayesian Model Averaging (BMA) to generate forecast ensembles of soil hydraulic models. To illustrate our method, we use observed tensiometric pressure head data at three different depths in a layered vadose zone of volcanic origin in New Zealand. A set of seven different soil hydraulic models is calibrated using a multi-objective formulation with three different objective functions that each measure the mismatch between observed and predicted soil water pressure head at one specific depth. The Pareto solution space corresponding to these three objectives is estimated with AMALGAM, and used to generate four different model ensembles. These ensembles are post-processed with BMA and used for predictive analysis and uncertainty estimation. Our most important conclusions for the vadose zone under consideration are: (1) the mean BMA forecast exhibits similar predictive capabilities as the best individual performing soil hydraulic model, (2) the size of the BMA uncertainty ranges increase with increasing depth and dryness in the soil profile, (3) the best performing ensemble corresponds to the compromise (or balanced) solution of the three-objective Pareto surface, and (4) the combined multi-objective optimization and BMA framework proposed in this paper is very useful to generate forecast ensembles of soil hydraulic models.

Information model of the 'Ukryttya' object

International Nuclear Information System (INIS)

Batij, E.V.; Ermolenko, A.A.; Kotlyarov, V.T.

2008-01-01

There were described the building principles and content of the 'Ukryttya' object information model that has been developed at the Institute for Safety Problems of NPP. Using the client/server architecture in this system (the simultaneous access of the many users), Autodesk Map Guide and ASP.NET technologies allowed avoiding the typical defects of the 'stand-alone desktop' information systems (that aimed for a single user)

Metodology of identification parameters of models control objects of automatic trailing system

Directory of Open Access Journals (Sweden)

I.V. Zimchuk

2017-04-01

Full Text Available The determining factor for the successful solution of the problem of synthesis of optimal control systems of different processes are adequacy of mathematical model of control object. In practice, the options can differ from the objects taken priori, causing a need to clarification of them. In this context, the article presents the results of the development and application of methods parameters identification of mathematical models of control object of automatic trailing system. The stated problem in the article is solved provided that control object is fully controlled and observed, and a differential equation of control object is known a priori. The coefficients of this equation to be determined. Identifying quality criterion is to minimize the integral value of squared error of identification. The method is based on a description of the dynamics of the object in space state. Equation of identification synthesized using the vector-matrix representation of model. This equation describes the interconnection of coefficients of matrix state and control with inputs and outputs of object. The initial data for calculation are the results of experimental investigation of the reaction of phase coordinates of control object at a typical input signal. The process of calculating the model parameters is reduced to solving the system of equations of the first order each. Application the above approach is illustrated in the example identification of coefficients transfer function of control object first order. Results of digital simulation are presented, they are confirming the justice of set out mathematical calculations. The approach enables to do the identification of models of one-dimensional and multidimensional objects and does not require a large amount of calculation for its implementation. The order of identified model is limited capabilities of measurement phase coordinates of corresponding control object. The practical significance of the work is

Engineering the object-relation database model in O-Raid

Science.gov (United States)

Dewan, Prasun; Vikram, Ashish; Bhargava, Bharat

1989-01-01

Raid is a distributed database system based on the relational model. O-raid is an extension of the Raid system and will support complex data objects. The design of O-Raid is evolutionary and retains all features of relational data base systems and those of a general purpose object-oriented programming language. O-Raid has several novel properties. Objects, classes, and inheritance are supported together with a predicate-base relational query language. O-Raid objects are compatible with C++ objects and may be read and manipulated by a C++ program without any 'impedance mismatch'. Relations and columns within relations may themselves be treated as objects with associated variables and methods. Relations may contain heterogeneous objects, that is, objects of more than one class in a certain column, which can individually evolve by being reclassified. Special facilities are provided to reduce the data search in a relation containing complex objects.

Object recognition in images via a factor graph model

Science.gov (United States)

He, Yong; Wang, Long; Wu, Zhaolin; Zhang, Haisu

2018-04-01

Object recognition in images suffered from huge search space and uncertain object profile. Recently, the Bag-of- Words methods are utilized to solve these problems, especially the 2-dimension CRF(Conditional Random Field) model. In this paper we suggest the method based on a general and flexible fact graph model, which can catch the long-range correlation in Bag-of-Words by constructing a network learning framework contrasted from lattice in CRF. Furthermore, we explore a parameter learning algorithm based on the gradient descent and Loopy Sum-Product algorithms for the factor graph model. Experimental results on Graz 02 dataset show that, the recognition performance of our method in precision and recall is better than a state-of-art method and the original CRF model, demonstrating the effectiveness of the proposed method.

Design of a Model Execution Framework: Repetitive Object-Oriented Simulation Environment (ROSE)

Science.gov (United States)

Gray, Justin S.; Briggs, Jeffery L.

2008-01-01

The ROSE framework was designed to facilitate complex system analyses. It completely divorces the model execution process from the model itself. By doing so ROSE frees the modeler to develop a library of standard modeling processes such as Design of Experiments, optimizers, parameter studies, and sensitivity studies which can then be applied to any of their available models. The ROSE framework accomplishes this by means of a well defined API and object structure. Both the API and object structure are presented here with enough detail to implement ROSE in any object-oriented language or modeling tool.

Model-Based Software Testing for Object-Oriented Software

Science.gov (United States)

Biju, Soly Mathew

2008-01-01

Model-based testing is one of the best solutions for testing object-oriented software. It has a better test coverage than other testing styles. Model-based testing takes into consideration behavioural aspects of a class, which are usually unchecked in other testing methods. An increase in the complexity of software has forced the software industry…

Whole object surface area and volume of partial-view 3D models

International Nuclear Information System (INIS)

Mulukutla, Gopal K; Proussevitch, Alexander A; Genareau, Kimberly D; Durant, Adam J

2017-01-01

Micro-scale 3D models, important components of many studies in science and engineering, are often used to determine morphological characteristics such as shape, surface area and volume. The application of techniques such as stereoscopic scanning electron microscopy on whole objects often results in ‘partial-view’ models with a portion of object not within the field of view thus not captured in the 3D model. The nature and extent of the surface not captured is dependent on the complex interaction of imaging system attributes (e.g. working distance, viewing angle) with object size, shape and morphology. As a result, any simplistic assumptions in estimating whole object surface area or volume can lead to significant errors. In this study, we report on a novel technique to estimate the physical fraction of an object captured in a partial-view 3D model of an otherwise whole object. This allows a more accurate estimate of surface area and volume. Using 3D models, we demonstrate the robustness of this method and the accuracy of surface area and volume estimates relative to true values. (paper)

Сontrol systems using mathematical models of technological objects ...

African Journals Online (AJOL)

Сontrol systems using mathematical models of technological objects in the control loop. ... Journal of Fundamental and Applied Sciences ... Such mathematical models make it possible to specify the optimal operating modes of the considered ...

Modeling real conditions of 'Ukrytie' object in 3D measurement

International Nuclear Information System (INIS)

Podbereznyj, S.S.

2001-01-01

The article covers a technology of creation on soft products basis for designing: AutoCad, and computer graphics and animation 3D Studio, 3DS MAX, of 3D model of geometrical parameters of current conditions of building structures, technological equipment, fuel-containing materials, concrete, water of ruined Unit 4, 'Ukryttia' object, of Chernobyl NPP. The model built using the above technology will be applied in the future as a basis when automating the design and computer modeling of processes at the 'Ukryttia' object

Speciated atmospheric mercury on haze and non-haze days in an inland city in China

Directory of Open Access Journals (Sweden)

Q. Hong

2016-11-01

photochemical oxidation. This is supported by simple box-model calculations, which showed that oxidation of GEM to GOM does occur and that the transport of free tropospheric GOM alone is not large enough to account for the observed increase in daytime GOM. Our results further postulate that NO2 aggregation with the HgOH intermediate may be a potential mechanism for the enhanced production of GOM during daytime.

Final Report: Legion Core Object Model, March 1, 1996 - September 30, 1999

Energy Technology Data Exchange (ETDEWEB)

Grimshaw, Andrew S.

1999-09-30

The model specifies the composition and functionality of Legion's core objects - those objects that cooperate to create, locate, manage, and remove objects from the legion project. In particular, the object model facilitates a flexible extensible implementation, provides a single persistent name space, grants site autonomy to participating organizations, and scales to millions of sites and trillions of objects. Further, it offers a framework that is well suited to providing mechanisms for high performance, security, fault tolerance and commerce.

Multi-objective compared to single-objective optimization with application to model validation and uncertainty quantification

Energy Technology Data Exchange (ETDEWEB)

Schulze-Riegert, R.; Krosche, M.; Stekolschikov, K. [Scandpower Petroleum Technology GmbH, Hamburg (Germany); Fahimuddin, A. [Technische Univ. Braunschweig (Germany)

2007-09-13

History Matching in Reservoir Simulation, well location and production optimization etc. is generally a multi-objective optimization problem. The problem statement of history matching for a realistic field case includes many field and well measurements in time and type, e.g. pressure measurements, fluid rates, events such as water and gas break-throughs, etc. Uncertainty parameters modified as part of the history matching process have varying impact on the improvement of the match criteria. Competing match criteria often reduce the likelihood of finding an acceptable history match. It is an engineering challenge in manual history matching processes to identify competing objectives and to implement the changes required in the simulation model. In production optimization or scenario optimization the focus on one key optimization criterion such as NPV limits the identification of alternatives and potential opportunities, since multiple objectives are summarized in a predefined global objective formulation. Previous works primarily focus on a specific optimization method. Few works actually concentrate on the objective formulation and multi-objective optimization schemes have not yet been applied to reservoir simulations. This paper presents a multi-objective optimization approach applicable to reservoir simulation. It addresses the problem of multi-objective criteria in a history matching study and presents analysis techniques identifying competing match criteria. A Pareto-Optimizer is discussed and the implementation of that multi-objective optimization scheme is applied to a case study. Results are compared to a single-objective optimization method. (orig.)

Child's objection to non-beneficial research: capacity and distress based models.

Science.gov (United States)

Waligora, Marcin; Różyńska, Joanna; Piasecki, Jan

2016-03-01

A child's objection, refusal and dissent regarding participation in non-beneficial biomedical research must be respected, even when the parents or legal representatives have given their permission. There is, however, no consensus on the definition and criteria of a meaningful and valid child's objection. The aim of this article is to clarify this issue. In the first part we describe the problems of a child's assent in research. In the second part we distinguish and analyze two models of a child's objection to research: the capacity-based model and the distress-based model. In the last part we present arguments for a broader and unified understanding of a child's objection within regulations and practices. This will strengthen children's rights and facilitate the entire process of assessment of research protocols.

Field Model: An Object-Oriented Data Model for Fields

Science.gov (United States)

Moran, Patrick J.

2001-01-01

We present an extensible, object-oriented data model designed for field data entitled Field Model (FM). FM objects can represent a wide variety of fields, including fields of arbitrary dimension and node type. FM can also handle time-series data. FM achieves generality through carefully selected topological primitives and through an implementation that leverages the potential of templated C++. FM supports fields where the nodes values are paired with any cell type. Thus FM can represent data where the field nodes are paired with the vertices ("vertex-centered" data), fields where the nodes are paired with the D-dimensional cells in R(sup D) (often called "cell-centered" data), as well as fields where nodes are paired with edges or other cell types. FM is designed to effectively handle very large data sets; in particular FM employs a demand-driven evaluation strategy that works especially well with large field data. Finally, the interfaces developed for FM have the potential to effectively abstract field data based on adaptive meshes. We present initial results with a triangular adaptive grid in R(sup 2) and discuss how the same design abstractions would work equally well with other adaptive-grid variations, including meshes in R(sup 3).

MODELING OF TECHNICAL CHANNELS OF INFORMATION LEAKAGE AT DISTRIBUTED CONTROL OBJECTS

Directory of Open Access Journals (Sweden)

Aleksander Vladimirovich Karpov

2018-05-01

Full Text Available The significant increase in requirements for distributed control objects’ functioning can’t be realized only at the expense of the widening and strengthening of security control measures. The first step in ensuring the information security at such objects is the analysis of the conditions of their functioning and modeling of technical channels of information leakage. The development of models of such channels is essentially the only method of complete study of their opportunities and it is pointed toward receiving quantitative assessments of the safe operation of compound objects. The evaluation data are necessary to make a decision on the degree of the information security from a leak according to the current criterion. The existing models are developed for the standard concentrated objects and allow to evaluate the level of information security from a leak on each of channels separately, what involves the significant increase in the required protective resource and time of assessment of information security on an object in general. The article deals with a logical-and-probabilistic method of a security assessment of structurally-compound objects. The model of a security leak on the distributed control objects is cited as an example. It is recommended to use a software package of an automated structurally-logistical modeling of compound systems, which allows to evaluate risk of information leakage in the loudspeaker. A possibility of information leakage by technical channels is evaluated and such differential characteristics of the safe operation of the distributed control objects as positive and negative contributions of the initiating events and conditions, which cause a leak are calculated. Purpose. The aim is a quantitative assessment of data risk, which is necessary for justifying the rational composition of organizational and technical protection measures, as well as a variant of the structure of the information security system from a

C++, objected-oriented programming, and astronomical data models

Science.gov (United States)

Farris, A.

1992-01-01

Contemporary astronomy is characterized by increasingly complex instruments and observational techniques, higher data collection rates, and large data archives, placing severe stress on software analysis systems. The object-oriented paradigm represents a significant new approach to software design and implementation that holds great promise for dealing with this increased complexity. The basic concepts of this approach will be characterized in contrast to more traditional procedure-oriented approaches. The fundamental features of objected-oriented programming will be discussed from a C++ programming language perspective, using examples familiar to astronomers. This discussion will focus on objects, classes and their relevance to the data type system; the principle of information hiding; and the use of inheritance to implement generalization/specialization relationships. Drawing on the object-oriented approach, features of a new database model to support astronomical data analysis will be presented.

RANCANGAN DATABASE SUBSISTEM PRODUKSI DENGAN PENDEKATAN SEMANTIC OBJECT MODEL

Directory of Open Access Journals (Sweden)

Oviliani Yenty Yuliana

2002-01-01

Full Text Available To compete in the global market, business performer who active in industry fields should have and get information quickly and accurately, so they could make the precise decision. Traditional cost accounting system cannot give sufficient information, so many industries shift to Activity-Based Costing system (ABC. ABC system is more complex and need more data that should be save and process, so it should be applied information technology and database than traditional cost accounting system. The development of the software technology recently makes the construction of application program is not problem again. The primary problem is how to design database that presented information quickly and accurately. For that reason it necessary to make the model first. This paper discusses database modelling with semantic object model approach. This model is easier to use and is generate more normal database design than entity relationship model approach. Abstract in Bahasa Indonesia : Dalam persaingan di pasar bebas, para pelaku bisnis di bidang industri dalam membuat suatu keputusan yang tepat memerlukan informasi secara cepat dan akurat. Sistem akuntansi biaya tradisional tidak dapat menyediakan informasi yang memadai, sehingga banyak perusahaan industri yang beralih ke sistem Activity-Based Costing (ABC. Tetapi, sistem ABC merupakan sistem yang kompleks dan memerlukan banyak data yang harus disimpan dan diolah, sehingga harus menggunakan teknologi informasi dan database. Kemajuan di bidang perangkat lunak mengakibatkan pembuatan aplikasi program bukan masalah lagi. Permasalahan utama adalah bagaimana merancang database, agar dapat menyajikan informasi secara cepat dan akurat. Untuk itu, dalam makalah ini dibahas pemodelan database dengan pendekatan semantic object model. Model data ini lebih mudah digunakan dan menghasilkan transformasi yang lebih normal, jika dibandingkan dengan entity relationship model yang umum digunakan. Kata kunci: Sub Sistem

An ODP computational model of a cooperative binding object

Science.gov (United States)

Logé, Christophe; Najm, Elie; Chen, Ken

1997-12-01

A next generation of systems that should appear will have to manage simultaneously several geographically distributed users. These systems belong to the class of computer-supported cooperative work systems (CSCW). The development of such complex systems requires rigorous development methods and flexible open architectures. Open distributed processing (ODP) is a standardization effort that aims at providing such architectures. ODP features appropriate abstraction levels and a clear articulation between requirements, programming and infrastructure support. ODP advocates the use of formal methods for the specification of systems and components. The computational model, an object-based model, one of the abstraction levels identified within ODP, plays a central role in the global architecture. In this model, basic objects can be composed with communication and distribution abstractions (called binding objects) to form a computational specification of distributed systems, or applications. Computational specifications can then be mapped (in a mechanism akin to compilation) onto an engineering solution. We use an ODP-inspired method to computationally specify a cooperative system. We start from a general purpose component that we progressively refine into a collection of basic and binding objects. We focus on two issues of a co-authoring application, namely, dynamic reconfiguration and multiview synchronization. We discuss solutions for these issues and formalize them using the MT-LOTOS specification language that is currently studied in the ISO standardization formal description techniques group.

Adjoint sensitivity studies of loop current and eddy shedding in the Gulf of Mexico

KAUST Repository

Gopalakrishnan, Ganesh; Cornuelle, Bruce D.; Hoteit, Ibrahim

2013-01-01

Adjoint model sensitivity analyses were applied for the loop current (LC) and its eddy shedding in the Gulf of Mexico (GoM) using the MIT general circulation model (MITgcm). The circulation in the GoM is mainly driven by the energetic LC and subsequent LC eddy separation. In order to understand which ocean regions and features control the evolution of the LC, including anticyclonic warm-core eddy shedding in the GoM, forward and adjoint sensitivities with respect to previous model state and atmospheric forcing were computed using the MITgcm and its adjoint. Since the validity of the adjoint model sensitivities depends on the capability of the forward model to simulate the real LC system and the eddy shedding processes, a 5 year (2004–2008) forward model simulation was performed for the GoM using realistic atmospheric forcing, initial, and boundary conditions. This forward model simulation was compared to satellite measurements of sea-surface height (SSH) and sea-surface temperature (SST), and observed transport variability. Despite realistic mean state, standard deviations, and LC eddy shedding period, the simulated LC extension shows less variability and more regularity than the observations. However, the model is suitable for studying the LC system and can be utilized for examining the ocean influences leading to a simple, and hopefully generic LC eddy separation in the GoM. The adjoint sensitivities of the LC show influences from the Yucatan Channel (YC) flow and Loop Current Frontal Eddy (LCFE) on both LC extension and eddy separation, as suggested by earlier work. Some of the processes that control LC extension after eddy separation differ from those controlling eddy shedding, but include YC through-flow. The sensitivity remains stable for more than 30 days and moves generally upstream, entering the Caribbean Sea. The sensitivities of the LC for SST generally remain closer to the surface and move at speeds consistent with advection by the high-speed core of

Adjoint sensitivity studies of loop current and eddy shedding in the Gulf of Mexico

KAUST Repository

Gopalakrishnan, Ganesh

2013-07-01

Adjoint model sensitivity analyses were applied for the loop current (LC) and its eddy shedding in the Gulf of Mexico (GoM) using the MIT general circulation model (MITgcm). The circulation in the GoM is mainly driven by the energetic LC and subsequent LC eddy separation. In order to understand which ocean regions and features control the evolution of the LC, including anticyclonic warm-core eddy shedding in the GoM, forward and adjoint sensitivities with respect to previous model state and atmospheric forcing were computed using the MITgcm and its adjoint. Since the validity of the adjoint model sensitivities depends on the capability of the forward model to simulate the real LC system and the eddy shedding processes, a 5 year (2004–2008) forward model simulation was performed for the GoM using realistic atmospheric forcing, initial, and boundary conditions. This forward model simulation was compared to satellite measurements of sea-surface height (SSH) and sea-surface temperature (SST), and observed transport variability. Despite realistic mean state, standard deviations, and LC eddy shedding period, the simulated LC extension shows less variability and more regularity than the observations. However, the model is suitable for studying the LC system and can be utilized for examining the ocean influences leading to a simple, and hopefully generic LC eddy separation in the GoM. The adjoint sensitivities of the LC show influences from the Yucatan Channel (YC) flow and Loop Current Frontal Eddy (LCFE) on both LC extension and eddy separation, as suggested by earlier work. Some of the processes that control LC extension after eddy separation differ from those controlling eddy shedding, but include YC through-flow. The sensitivity remains stable for more than 30 days and moves generally upstream, entering the Caribbean Sea. The sensitivities of the LC for SST generally remain closer to the surface and move at speeds consistent with advection by the high-speed core of

Controlling Business Object States in Business Process Models to Support Compliance

OpenAIRE

Peņicina, L

2016-01-01

The doctoral thesis addresses the existing gap between business process models and states of business objects. Existing modelling methods such as BPMN and ArchiMate lack an explicitly declarative approach for capturing states of business objects and laws of state transitions. This gap hinders the compliance of business process models with regulations imposed internally or externally, and can result in potential legal problems for organizations. Also this g...

D Modelling and Interactive Web-Based Visualization of Cultural Heritage Objects

Science.gov (United States)

Koeva, M. N.

2016-06-01

Nowadays, there are rapid developments in the fields of photogrammetry, laser scanning, computer vision and robotics, together aiming to provide highly accurate 3D data that is useful for various applications. In recent years, various LiDAR and image-based techniques have been investigated for 3D modelling because of their opportunities for fast and accurate model generation. For cultural heritage preservation and the representation of objects that are important for tourism and their interactive visualization, 3D models are highly effective and intuitive for present-day users who have stringent requirements and high expectations. Depending on the complexity of the objects for the specific case, various technological methods can be applied. The selected objects in this particular research are located in Bulgaria - a country with thousands of years of history and cultural heritage dating back to ancient civilizations. This motivates the preservation, visualisation and recreation of undoubtedly valuable historical and architectural objects and places, which has always been a serious challenge for specialists in the field of cultural heritage. In the present research, comparative analyses regarding principles and technological processes needed for 3D modelling and visualization are presented. The recent problems, efforts and developments in interactive representation of precious objects and places in Bulgaria are presented. Three technologies based on real projects are described: (1) image-based modelling using a non-metric hand-held camera; (2) 3D visualization based on spherical panoramic images; (3) and 3D geometric and photorealistic modelling based on architectural CAD drawings. Their suitability for web-based visualization are demonstrated and compared. Moreover the possibilities for integration with additional information such as interactive maps, satellite imagery, sound, video and specific information for the objects are described. This comparative study

Hydrologic Model Development and Calibration: Contrasting a Single- and Multi-Objective Approach for Comparing Model Performance

Science.gov (United States)

Asadzadeh, M.; Maclean, A.; Tolson, B. A.; Burn, D. H.

2009-05-01

Hydrologic model calibration aims to find a set of parameters that adequately simulates observations of watershed behavior, such as streamflow, or a state variable, such as snow water equivalent (SWE). There are different metrics for evaluating calibration effectiveness that involve quantifying prediction errors, such as the Nash-Sutcliffe (NS) coefficient and bias evaluated for the entire calibration period, on a seasonal basis, for low flows, or for high flows. Many of these metrics are conflicting such that the set of parameters that maximizes the high flow NS differs from the set of parameters that maximizes the low flow NS. Conflicting objectives are very likely when different calibration objectives are based on different fluxes and/or state variables (e.g., NS based on streamflow versus SWE). One of the most popular ways to balance different metrics is to aggregate them based on their importance and find the set of parameters that optimizes a weighted sum of the efficiency metrics. Comparing alternative hydrologic models (e.g., assessing model improvement when a process or more detail is added to the model) based on the aggregated objective might be misleading since it represents one point on the tradeoff of desired error metrics. To derive a more comprehensive model comparison, we solved a bi-objective calibration problem to estimate the tradeoff between two error metrics for each model. Although this approach is computationally more expensive than the aggregation approach, it results in a better understanding of the effectiveness of selected models at each level of every error metric and therefore provides a better rationale for judging relative model quality. The two alternative models used in this study are two MESH hydrologic models (version 1.2) of the Wolf Creek Research basin that differ in their watershed spatial discretization (a single Grouped Response Unit, GRU, versus multiple GRUs). The MESH model, currently under development by Environment

Dew Point modelling using GEP based multi objective optimization

OpenAIRE

Shroff, Siddharth; Dabhi, Vipul

2013-01-01

Different techniques are used to model the relationship between temperatures, dew point and relative humidity. Gene expression programming is capable of modelling complex realities with great accuracy, allowing at the same time, the extraction of knowledge from the evolved models compared to other learning algorithms. We aim to use Gene Expression Programming for modelling of dew point. Generally, accuracy of the model is the only objective used by selection mechanism of GEP. This will evolve...

An object-oriented, coprocessor-accelerated model for ice sheet simulations

Science.gov (United States)

Seddik, H.; Greve, R.

2013-12-01

Recently, numerous models capable of modeling the thermo-dynamics of ice sheets have been developed within the ice sheet modeling community. Their capabilities have been characterized by a wide range of features with different numerical methods (finite difference or finite element), different implementations of the ice flow mechanics (shallow-ice, higher-order, full Stokes) and different treatments for the basal and coastal areas (basal hydrology, basal sliding, ice shelves). Shallow-ice models (SICOPOLIS, IcIES, PISM, etc) have been widely used for modeling whole ice sheets (Greenland and Antarctica) due to the relatively low computational cost of the shallow-ice approximation but higher order (ISSM, AIF) and full Stokes (Elmer/Ice) models have been recently used to model the Greenland ice sheet. The advance in processor speed and the decrease in cost for accessing large amount of memory and storage have undoubtedly been the driving force in the commoditization of models with higher capabilities, and the popularity of Elmer/Ice (http://elmerice.elmerfem.com) with an active user base is a notable representation of this trend. Elmer/Ice is a full Stokes model built on top of the multi-physics package Elmer (http://www.csc.fi/english/pages/elmer) which provides the full machinery for the complex finite element procedure and is fully parallel (mesh partitioning with OpenMPI communication). Elmer is mainly written in Fortran 90 and targets essentially traditional processors as the code base was not initially written to run on modern coprocessors (yet adding support for the recently introduced x86 based coprocessors is possible). Furthermore, a truly modular and object-oriented implementation is required for quick adaptation to fast evolving capabilities in hardware (Fortran 2003 provides an object-oriented programming model while not being clean and requiring a tricky refactoring of Elmer code). In this work, the object-oriented, coprocessor-accelerated finite element

The Game Object Model and expansive learning: Creation ...

African Journals Online (AJOL)

The Game Object Model and expansive learning: Creation, instantiation, ... The aim of the paper is to develop insights into the design, integration, evaluation and use of video games in learning and teaching. ... AJOL African Journals Online.

Development and investigation of aggregate models for nuclear objects with time shifts

International Nuclear Information System (INIS)

Gharakhanlou, J.; Kazachkov, I.V.

2012-01-01

The development and investigation of aggregate models for nuclear objects with shift arguments are discussed.The nonlinear differential equations of the model are described and the Cauchy problem is stated. The specific feature of the mathematical model for potentially hazardous nuclear objects are analyzed and computer simulation is presented

A General Polygon-based Deformable Model for Object Recognition

DEFF Research Database (Denmark)

Jensen, Rune Fisker; Carstensen, Jens Michael

1999-01-01

We propose a general scheme for object localization and recognition based on a deformable model. The model combines shape and image properties by warping a arbitrary prototype intensity template according to the deformation in shape. The shape deformations are constrained by a probabilistic distr...

Multi-objective optimization of GENIE Earth system models.

Science.gov (United States)

Price, Andrew R; Myerscough, Richard J; Voutchkov, Ivan I; Marsh, Robert; Cox, Simon J

2009-07-13

The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem of parameter estimation in climate models. This optimization process involves the iterative evaluation of response surface models (RSMs), followed by the execution of multiple Earth system simulations. These computations require an infrastructure that provides high-performance computing for building and searching the RSMs and high-throughput computing for the concurrent evaluation of a large number of models. Grid computing technology is therefore essential to make this algorithm practical for members of the GENIE project.

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

Science.gov (United States)

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

2006-10-01

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

Nitrogen delivery from the Mississippi-Atchafalaya River Basin to the Gulf of Mexico: magnitude, attribution, and uncertainty

Science.gov (United States)

Tian, H.; Xu, R.; Yang, J.; Zhang, B.; Yao, Y.; Pan, S.; Cai, W. J.; Lohrenz, S. E.

2017-12-01

The northern Gulf of Mexico (GOM), as one of the largest hypoxic zone in the world, is near the outlet of the Mississippi-Atchafalaya River Basin (MARB) that contributed to the increased fluxes of agriculturally derived nitrogen (N) since the 1950s. This increase of N exports could be primarily attributed to anthropogenic N inputs into the MARB (e.g., N fertilizer application), climate (e.g., precipitation), and land use change. A long-term data of monthly/annual dissolved inorganic nitrogen (DIN) exports from the MARB to the GOM had been released by the United States Geological Survey (USGS) since the 1970s. However, on one hand, dissolved organic nitrogen (DON) also plays an active role in supplying N for phytoplankton and bacteria in aquatic ecosystems; on the other hand, monitoring data provided by the USGS could not attribute the contributions of various factors to this N increase in the northern GOM. Here, we used a coupled hydrological-biogeochemical model, the Dynamic Land Ecosystem Model, to examine changes in DIN (ammonium and nitrate) and DON exports from the MARB to the GOM during 1901 2014. Meanwhile, we investigated how climate variability, land use change, land management, and atmospheric chemistry affected the annual and seasonal patterns of N export in the study area.

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

Directory of Open Access Journals (Sweden)

Jui-Yuan Su

2015-04-01

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

Working memory contributes to the encoding of object location associations: Support for a 3-part model of object location memory.

Science.gov (United States)

Gillis, M Meredith; Garcia, Sarah; Hampstead, Benjamin M

2016-09-15

A recent model by Postma and colleagues posits that the encoding of object location associations (OLAs) requires the coordination of several cognitive processes mediated by ventral (object perception) and dorsal (spatial perception) visual pathways as well as the hippocampus (feature binding) [1]. Within this model, frontoparietal network recruitment is believed to contribute to both the spatial processing and working memory task demands. The current study used functional magnetic resonance imaging (fMRI) to test each step of this model in 15 participants who encoded OLAs and performed standard n-back tasks. As expected, object processing resulted in activation of the ventral visual stream. Object in location processing resulted in activation of both the ventral and dorsal visual streams as well as a lateral frontoparietal network. This condition was also the only one to result in medial temporal lobe activation, supporting its role in associative learning. A conjunction analysis revealed areas of shared activation between the working memory and object in location phase within the lateral frontoparietal network, anterior insula, and basal ganglia; consistent with prior working memory literature. Overall, findings support Postma and colleague's model and provide clear evidence for the role of working memory during OLA encoding. Published by Elsevier B.V.

Toward Self-Referential Autonomous Learning of Object and Situation Models.

Science.gov (United States)

Damerow, Florian; Knoblauch, Andreas; Körner, Ursula; Eggert, Julian; Körner, Edgar

2016-01-01

Most current approaches to scene understanding lack the capability to adapt object and situation models to behavioral needs not anticipated by the human system designer. Here, we give a detailed description of a system architecture for self-referential autonomous learning which enables the refinement of object and situation models during operation in order to optimize behavior. This includes structural learning of hierarchical models for situations and behaviors that is triggered by a mismatch between expected and actual action outcome. Besides proposing architectural concepts, we also describe a first implementation of our system within a simulated traffic scenario to demonstrate the feasibility of our approach.

Modeling and Simulation of Grasping of Deformable Objects

DEFF Research Database (Denmark)

Fugl, Andreas Rune

Automated robot solutions have for decades been increasing productivity around the world. They are attractive for being fast, accurate and able to work in dangerous and repetitive environments. In traditional applications the grasped object is kinematically attached to the Tool Center Point....... The purpose of this thesis is to address the modeling and simulation of deformable objects, as applied to robotic grasping and manipulation. The main contributions of this work are: An evaluation of 3D linear elasticity used for robot grasping as implemented by a Finite Difference Method supporting regular...

Soft object deformation monitoring and learning for model-based robotic hand manipulation.

Science.gov (United States)

Cretu, Ana-Maria; Payeur, Pierre; Petriu, Emil M

2012-06-01

This paper discusses the design and implementation of a framework that automatically extracts and monitors the shape deformations of soft objects from a video sequence and maps them with force measurements with the goal of providing the necessary information to the controller of a robotic hand to ensure safe model-based deformable object manipulation. Measurements corresponding to the interaction force at the level of the fingertips and to the position of the fingertips of a three-finger robotic hand are associated with the contours of a deformed object tracked in a series of images using neural-network approaches. The resulting model captures the behavior of the object and is able to predict its behavior for previously unseen interactions without any assumption on the object's material. The availability of such models can contribute to the improvement of a robotic hand controller, therefore allowing more accurate and stable grasp while providing more elaborate manipulation capabilities for deformable objects. Experiments performed for different objects, made of various materials, reveal that the method accurately captures and predicts the object's shape deformation while the object is submitted to external forces applied by the robot fingers. The proposed method is also fast and insensitive to severe contour deformations, as well as to smooth changes in lighting, contrast, and background.

OBJECT ORIENTED MODELLING, A MODELLING METHOD OF AN ECONOMIC ORGANIZATION ACTIVITY

Directory of Open Access Journals (Sweden)

TĂNĂSESCU ANA

2014-05-01

Full Text Available Now, most economic organizations use different information systems types in order to facilitate their activity. There are different methodologies, methods and techniques that can be used to design information systems. In this paper, I propose to present the advantages of using the object oriented modelling at the information system design of an economic organization. Thus, I have modelled the activity of a photo studio, using Visual Paradigm for UML as a modelling tool. For this purpose, I have identified the use cases for the analyzed system and I have presented the use case diagram. I have, also, realized the system static and dynamic modelling, through the most known UML diagrams.

MODELING OF CONVECTIVE STREAMS IN PNEUMOBASIC OBJECTS (Part 2

Directory of Open Access Journals (Sweden)

B. M. Khroustalev

2015-01-01

Full Text Available The article presents modeling for investigation of aerodynamic processes on area sections (including a group of complex constructional works for different regimes of drop and wind streams  and  temperature  conditions  and  in  complex  constructional  works  (for  different regimes of heating and ventilation. There were developed different programs for innovation problems solution in the field of heat and mass exchange in three-dimensional space of pres- sures-speeds-temperatures of оbjects.The field of uses of pneumobasic objects: construction and roof of tennis courts, hockey pitches, swimming pools , and also exhibitions’ buildings, circus buildings, cafes, aqua parks, studios, mobile objects of medical purposes, hangars, garages, construction sites, service sta- tions and etc. Advantages of such objects are the possibility and simplicity of multiple instal- lation and demolition works. Their large-scale implementation is determined by temperature- moisture conditions under the shells.Analytical and calculating researches, real researches of thermodynamic parameters of heat and mass exchange, multifactorial processes of air in pneumobasic objects, their shells in a wide range of climatic parameters of air (January – December in the Republic of Belarus, in many geographical latitudes of many countries have shown that the limit of the possibility of optimizing wind loads, heat flow, acoustic effects is infinite (sports, residential, industrial, warehouse, the military-technical units (tanks, airplanes, etc.. In modeling of convective flows in pneumobasic objects (part 1 there are processes with higher dynamic parameters of the air flow for the characteristic pneumobasic object, carried out the calculation of the velocity field, temperature, pressure at the speed of access of air through the inflow holes up to 5 m/sec at the moments of times (20, 100, 200, 400 sec. The calculation was performed using the developed mathematical

THE INVESTMENT MODEL OF THE CONSTRUCTION OF PUBLIC OBJECTS

Directory of Open Access Journals (Sweden)

Reperger Šandor

2009-11-01

Full Text Available One of the possible models of the construction and use of sports objects, especi- ally indoor facilities (sports centres, halls, swimming pools, shooting alleys and others is the cooperation of the public and private sector, by the investment model of PPP (Pu- blic-Private Partnership. PPP (Public-Private Partnership construction is the new form of securing civil works, already known in the developed countries, in which the job of planning, construc- tion, functioning and financing is done by the private sector – in the scope of a precisely elaborated cooperation with the state. The state engages the private sector for the administering of the civil works. By public adverstisements and contests they will find the investors who accept the administe- ring of certain public works by themselves or with the help of project partners with their own resources (with 60-85% of bank loans, secure the conditions for conducting certain services (by using the objects, halls, etc until the expiration of the agreed deadline. The essence of PPP construction is the fact that an investor from the private sec- tor, chosen through a contest, realizes the project using its own means. The object beco- mes the property of the investor and it secures the regular functioning of the object with exclusive rights. The income from the functioning belongs to the investor, in return the costs of the functioning of the object, the upkeep, as well as the costs of the personnel and public utilities are the responsibility of the investor. The public use of the object is realised by the means that the authorised ministry and the partner from the contest in an agreement of the realization and functioning of the object accurately define the time of maintenance and the duration of the services on the behalf of social interest. From the time specified in the agreement the investor doesn’t charge precisely defined users for general and specific services. As Sebia, with all its

Modeling Dynamic Objects in Monte Carlo Particle Transport Calculations

International Nuclear Information System (INIS)

Yegin, G.

2008-01-01

In this study, the Multi-Geometry geometry modeling technique was improved in order to handle moving objects in a Monte Carlo particle transport calculation. In the Multi-Geometry technique, the geometry is a superposition of objects not surfaces. By using this feature, we developed a new algorithm which allows a user to make enable or disable geometry elements during particle transport. A disabled object can be ignored at a certain stage of a calculation and switching among identical copies of the same object located adjacent poins during a particle simulation corresponds to the movement of that object in space. We called this powerfull feature as Dynamic Multi-Geometry technique (DMG) which is used for the first time in Brachy Dose Monte Carlo code to simulate HDR brachytherapy treatment systems. Our results showed that having disabled objects in a geometry does not effect calculated dose values. This technique is also suitable to be used in other areas such as IMRT treatment planning systems

Are Face and Object Recognition Independent? A Neurocomputational Modeling Exploration.

Science.gov (United States)

Wang, Panqu; Gauthier, Isabel; Cottrell, Garrison

2016-04-01

Are face and object recognition abilities independent? Although it is commonly believed that they are, Gauthier et al. [Gauthier, I., McGugin, R. W., Richler, J. J., Herzmann, G., Speegle, M., & VanGulick, A. E. Experience moderates overlap between object and face recognition, suggesting a common ability. Journal of Vision, 14, 7, 2014] recently showed that these abilities become more correlated as experience with nonface categories increases. They argued that there is a single underlying visual ability, v, that is expressed in performance with both face and nonface categories as experience grows. Using the Cambridge Face Memory Test and the Vanderbilt Expertise Test, they showed that the shared variance between Cambridge Face Memory Test and Vanderbilt Expertise Test performance increases monotonically as experience increases. Here, we address why a shared resource across different visual domains does not lead to competition and to an inverse correlation in abilities? We explain this conundrum using our neurocomputational model of face and object processing ["The Model", TM, Cottrell, G. W., & Hsiao, J. H. Neurocomputational models of face processing. In A. J. Calder, G. Rhodes, M. Johnson, & J. Haxby (Eds.), The Oxford handbook of face perception. Oxford, UK: Oxford University Press, 2011]. We model the domain general ability v as the available computational resources (number of hidden units) in the mapping from input to label and experience as the frequency of individual exemplars in an object category appearing during network training. Our results show that, as in the behavioral data, the correlation between subordinate level face and object recognition accuracy increases as experience grows. We suggest that different domains do not compete for resources because the relevant features are shared between faces and objects. The essential power of experience is to generate a "spreading transform" for faces (separating them in representational space) that

The Aalborg Model and management by objectives and resources

DEFF Research Database (Denmark)

Qvist, Palle; Spliid, Claus Monrad

2010-01-01

Model is successful has never been subject to a scientific study. An educational program in an HEI (Higher Education Institution) can be seen and understood as a system managed by objectives (MBO)5 within a given resource frame and based on an “agreement” between the student and the study board....... The student must achieve the objectives decided by the study board and that achievement is then documented with an exam. The study board supports the student with resources which helps them to fulfill the objectives. When the resources are divided into human, material and methodological resources...

A fast mass spring model solver for high-resolution elastic objects

Science.gov (United States)

Zheng, Mianlun; Yuan, Zhiyong; Zhu, Weixu; Zhang, Guian

2017-03-01

Real-time simulation of elastic objects is of great importance for computer graphics and virtual reality applications. The fast mass spring model solver can achieve visually realistic simulation in an efficient way. Unfortunately, this method suffers from resolution limitations and lack of mechanical realism for a surface geometry model, which greatly restricts its application. To tackle these problems, in this paper we propose a fast mass spring model solver for high-resolution elastic objects. First, we project the complex surface geometry model into a set of uniform grid cells as cages through *cages mean value coordinate method to reflect its internal structure and mechanics properties. Then, we replace the original Cholesky decomposition method in the fast mass spring model solver with a conjugate gradient method, which can make the fast mass spring model solver more efficient for detailed surface geometry models. Finally, we propose a graphics processing unit accelerated parallel algorithm for the conjugate gradient method. Experimental results show that our method can realize efficient deformation simulation of 3D elastic objects with visual reality and physical fidelity, which has a great potential for applications in computer animation.

A Deep-Structured Conditional Random Field Model for Object Silhouette Tracking.

Directory of Open Access Journals (Sweden)

Mohammad Javad Shafiee

Full Text Available In this work, we introduce a deep-structured conditional random field (DS-CRF model for the purpose of state-based object silhouette tracking. The proposed DS-CRF model consists of a series of state layers, where each state layer spatially characterizes the object silhouette at a particular point in time. The interactions between adjacent state layers are established by inter-layer connectivity dynamically determined based on inter-frame optical flow. By incorporate both spatial and temporal context in a dynamic fashion within such a deep-structured probabilistic graphical model, the proposed DS-CRF model allows us to develop a framework that can accurately and efficiently track object silhouettes that can change greatly over time, as well as under different situations such as occlusion and multiple targets within the scene. Experiment results using video surveillance datasets containing different scenarios such as occlusion and multiple targets showed that the proposed DS-CRF approach provides strong object silhouette tracking performance when compared to baseline methods such as mean-shift tracking, as well as state-of-the-art methods such as context tracking and boosted particle filtering.

Dynamic information processing states revealed through neurocognitive models of object semantics

Science.gov (United States)

Clarke, Alex

2015-01-01

Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations – a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time. PMID:25745632

Application of multiple objective models to water resources planning and management

International Nuclear Information System (INIS)

North, R.M.

1993-01-01

Over the past 30 years, we have seen the birth and growth of multiple objective analysis from an idea without tools to one with useful applications. Models have been developed and applications have been researched to address the multiple purposes and objectives inherent in the development and management of water resources. A practical approach to multiple objective modelling incorporates macroeconomic-based policies and expectations in order to optimize the results from both engineering (structural) and management (non-structural) alternatives, while taking into account the economic and environmental trade-offs. (author). 27 refs, 4 figs, 3 tabs

Wind field and trajectory models for tornado-propelled objects

International Nuclear Information System (INIS)

Anon

1978-01-01

This report contains the results of the second phase of a research program which has as its objective the development of a mathematical model to predict the trajectory of tornado-borne objects postulated to be in the vicinity of nuclear power plants. An improved tornado wind field model satisfies the no-slip ground boundary condition of fluid mechanics and includes the functional dependence of eddy viscosity with altitude. Sub-scale wind tunnel data are obtained for all of the missiles currently specified for nuclear plant design. Confirmatory full-scale data are obtained for a 12-inch pipe and automobile. The original six-degree-of-freedom trajectory model is modified to include the improved wind field and increased capability as to body shapes and inertial characteristics that can be handled. The improved trajectory model is used to calculate maximum credible speeds, which for all of the heavy missiles are considerably less than those currently specified for design. Equivalent coefficients for use in three-degree-of-freedom models are developed and the sensitivity of range and speed to various trajectory parameters for the 12-inch diameter pipe is examined

Modeling the Object-Oriented Software Process: OPEN and the Unified Process

NARCIS (Netherlands)

van den Berg, Klaas; Aksit, Mehmet; van den Broek, P.M.

A short introduction to software process modeling is presented, particularly object-oriented modeling. Two major industrial process models are discussed: the OPEN model and the Unified Process model. In more detail, the quality assurance in the Unified Process tool (formally called Objectory) is

Solving a bi-objective mathematical programming model for bloodmobiles location routing problem

Directory of Open Access Journals (Sweden)

Masoud Rabbani

2017-01-01

Full Text Available Perishability of platelets, uncertainty of donors’ arrival and conflicting views in platelet supply chain have made platelet supply chain planning a problematic issue. In this paper, mobile blood collection system for platelet production is investigated. Two mathematical models are presented to cover the bloodmobile collection planning problem. The first model is a multi-objective fuzzy mathematical programming in which the bloodmobiles locations are considered with the aim of maximizing potential amount of blood collection and minimizing the operational cost. The second model is a vehicle routing problem with time windows which studies the shuttles routing problem. To tackle the first model, it is reformulated as a crisp multi objective linear programming model and then solved through a fuzzy multi objective programming approach. Several sensitivity analysis are conducted on important parameters to demonstrate the applicability of the proposed model. The proposed model is then solved by using a tailored Simulated Annealing (SA algorithm. The numerical results demonstrate promising efficiency of the proposed solution method.

Modeling the Object-Oriented Software Process: OPEN and the Unified Process

OpenAIRE

van den Berg, Klaas; Aksit, Mehmet; van den Broek, P.M.

1999-01-01

A short introduction to software process modeling is presented, particularly object-oriented modeling. Two major industrial process models are discussed: the OPEN model and the Unified Process model. In more detail, the quality assurance in the Unified Process tool (formally called Objectory) is reviewed.

A Multi-Objective Trade-Off Model in Sustainable Construction Projects

Directory of Open Access Journals (Sweden)

Guangdong Wu

2017-10-01

Full Text Available Based on the consideration of the relative importance of sustainability-related objectives and the inherent nature of sustainable construction projects, this study proposes that the contractor can balance the levels of efforts and resources used to improve the overall project sustainability. A multi-objective trade-off model using game theory was established and verified through simulation and numerical example under a moral hazard situation. Results indicate that effort levels of the contractor on sustainability-related objectives are positively related to the outcome coefficient while negatively to the coefficients of effort cost of the relevant objectives. High levels of the relative importance of sustainability-related objectives contribute to high levels of effort of the contractor. With the variation in effort levels and the coefficient of benefit allocation, the project net benefit increases before declining. The function of project benefit has a marked peak value, with an inverted “U” shape. An equilibrium always exists as for the given relative importance and coefficients of the effort costs of sustainability-related objectives. Under this condition, the owner may offer the contractor a less intense incentive and motivate the contractor reasonably arranging input resources. The coefficient of benefit allocation is affected by the contractor characteristic factors and the project characteristic factors. The owner should balance these two types of factors and select the most appropriate incentive mechanism to improve the project benefit. Meanwhile, the contractor can balance the relative importance of the objectives and arrange the appropriate levels of effort and resources to achieve a sustainability-related objective. Very few studies have emphasized the effects of the relative importance of sustainability-related objectives on the benefits of sustainable construction projects. This study therefore builds a multi-objective trade

Towards a semantic learning model fostering learning object reusability

OpenAIRE

Fernandes , Emmanuel; Madhour , Hend; Wentland Forte , Maia; Miniaoui , Sami

2005-01-01

We try in this paper to propose a domain model for both author's and learner's needs concerning learning objects reuse. First of all, we present four key criteria for an efficient authoring tool: adaptive level of granularity, flexibility, integration and interoperability. Secondly, we introduce and describe our six-level Semantic Learning Model (SLM) designed to facilitate multi-level reuse of learning materials and search by defining a multi-layer model for metadata. Finally, after mapping ...

2D Modeling and Classification of Extended Objects in a Network of HRR Radars

NARCIS (Netherlands)

Fasoula, A.

2011-01-01

In this thesis, the modeling of extended objects with low-dimensional representations of their 2D geometry is addressed. The ultimate objective is the classification of the objects using libraries of such compact 2D object models that are much smaller than in the state-of-the-art classification

A multi-objective programming model for assessment the GHG emissions in MSW management

Energy Technology Data Exchange (ETDEWEB)

Mavrotas, George, E-mail: mavrotas@chemeng.ntua.gr [National Technical University of Athens, Iroon Polytechniou 9, Zografou, Athens, 15780 (Greece); Skoulaxinou, Sotiria [EPEM SA, 141 B Acharnon Str., Athens, 10446 (Greece); Gakis, Nikos [FACETS SA, Agiou Isidorou Str., Athens, 11471 (Greece); Katsouros, Vassilis [Athena Research and Innovation Center, Artemidos 6 and Epidavrou Str., Maroussi, 15125 (Greece); Georgopoulou, Elena [National Observatory of Athens, Thisio, Athens, 11810 (Greece)

2013-09-15

Highlights: • The multi-objective multi-period optimization model. • The solution approach for the generation of the Pareto front with mathematical programming. • The very detailed description of the model (decision variables, parameters, equations). • The use of IPCC 2006 guidelines for landfill emissions (first order decay model) in the mathematical programming formulation. - Abstract: In this study a multi-objective mathematical programming model is developed for taking into account GHG emissions for Municipal Solid Waste (MSW) management. Mathematical programming models are often used for structure, design and operational optimization of various systems (energy, supply chain, processes, etc.). The last twenty years they are used all the more often in Municipal Solid Waste (MSW) management in order to provide optimal solutions with the cost objective being the usual driver of the optimization. In our work we consider the GHG emissions as an additional criterion, aiming at a multi-objective approach. The Pareto front (Cost vs. GHG emissions) of the system is generated using an appropriate multi-objective method. This information is essential to the decision maker because he can explore the trade-offs in the Pareto curve and select his most preferred among the Pareto optimal solutions. In the present work a detailed multi-objective, multi-period mathematical programming model is developed in order to describe the waste management problem. Apart from the bi-objective approach, the major innovations of the model are (1) the detailed modeling considering 34 materials and 42 technologies, (2) the detailed calculation of the energy content of the various streams based on the detailed material balances, and (3) the incorporation of the IPCC guidelines for the CH{sub 4} generated in the landfills (first order decay model). The equations of the model are described in full detail. Finally, the whole approach is illustrated with a case study referring to the

A multi-objective programming model for assessment the GHG emissions in MSW management

International Nuclear Information System (INIS)

Mavrotas, George; Skoulaxinou, Sotiria; Gakis, Nikos; Katsouros, Vassilis; Georgopoulou, Elena

2013-01-01

Highlights: • The multi-objective multi-period optimization model. • The solution approach for the generation of the Pareto front with mathematical programming. • The very detailed description of the model (decision variables, parameters, equations). • The use of IPCC 2006 guidelines for landfill emissions (first order decay model) in the mathematical programming formulation. - Abstract: In this study a multi-objective mathematical programming model is developed for taking into account GHG emissions for Municipal Solid Waste (MSW) management. Mathematical programming models are often used for structure, design and operational optimization of various systems (energy, supply chain, processes, etc.). The last twenty years they are used all the more often in Municipal Solid Waste (MSW) management in order to provide optimal solutions with the cost objective being the usual driver of the optimization. In our work we consider the GHG emissions as an additional criterion, aiming at a multi-objective approach. The Pareto front (Cost vs. GHG emissions) of the system is generated using an appropriate multi-objective method. This information is essential to the decision maker because he can explore the trade-offs in the Pareto curve and select his most preferred among the Pareto optimal solutions. In the present work a detailed multi-objective, multi-period mathematical programming model is developed in order to describe the waste management problem. Apart from the bi-objective approach, the major innovations of the model are (1) the detailed modeling considering 34 materials and 42 technologies, (2) the detailed calculation of the energy content of the various streams based on the detailed material balances, and (3) the incorporation of the IPCC guidelines for the CH 4 generated in the landfills (first order decay model). The equations of the model are described in full detail. Finally, the whole approach is illustrated with a case study referring to the application

Topical video object discovery from key frames by modeling word co-occurrence prior.

Science.gov (United States)

Zhao, Gangqiang; Yuan, Junsong; Hua, Gang; Yang, Jiong

2015-12-01

A topical video object refers to an object, that is, frequently highlighted in a video. It could be, e.g., the product logo and the leading actor/actress in a TV commercial. We propose a topic model that incorporates a word co-occurrence prior for efficient discovery of topical video objects from a set of key frames. Previous work using topic models, such as latent Dirichelet allocation (LDA), for video object discovery often takes a bag-of-visual-words representation, which ignored important co-occurrence information among the local features. We show that such data driven co-occurrence information from bottom-up can conveniently be incorporated in LDA with a Gaussian Markov prior, which combines top-down probabilistic topic modeling with bottom-up priors in a unified model. Our experiments on challenging videos demonstrate that the proposed approach can discover different types of topical objects despite variations in scale, view-point, color and lighting changes, or even partial occlusions. The efficacy of the co-occurrence prior is clearly demonstrated when compared with topic models without such priors.

Definition of an Object-Oriented Modeling Language for Enterprise Architecture

OpenAIRE

Lê, Lam Son; Wegmann, Alain

2005-01-01

In enterprise architecture, the goal is to integrate business resources and IT resources in order to improve an enterprises competitiveness. In an enterprise architecture project, the development team usually constructs a model that represents the enterprise: the enterprise model. In this paper, we present a modeling language for building such enterprise models. Our enterprise models are hierarchical object-oriented representations of the enterprises. This paper presents the foundations of o...

3D MODELLING AND INTERACTIVE WEB-BASED VISUALIZATION OF CULTURAL HERITAGE OBJECTS

Directory of Open Access Journals (Sweden)

M. N. Koeva

2016-06-01

Full Text Available Nowadays, there are rapid developments in the fields of photogrammetry, laser scanning, computer vision and robotics, together aiming to provide highly accurate 3D data that is useful for various applications. In recent years, various LiDAR and image-based techniques have been investigated for 3D modelling because of their opportunities for fast and accurate model generation. For cultural heritage preservation and the representation of objects that are important for tourism and their interactive visualization, 3D models are highly effective and intuitive for present-day users who have stringent requirements and high expectations. Depending on the complexity of the objects for the specific case, various technological methods can be applied. The selected objects in this particular research are located in Bulgaria – a country with thousands of years of history and cultural heritage dating back to ancient civilizations. \\this motivates the preservation, visualisation and recreation of undoubtedly valuable historical and architectural objects and places, which has always been a serious challenge for specialists in the field of cultural heritage. In the present research, comparative analyses regarding principles and technological processes needed for 3D modelling and visualization are presented. The recent problems, efforts and developments in interactive representation of precious objects and places in Bulgaria are presented. Three technologies based on real projects are described: (1 image-based modelling using a non-metric hand-held camera; (2 3D visualization based on spherical panoramic images; (3 and 3D geometric and photorealistic modelling based on architectural CAD drawings. Their suitability for web-based visualization are demonstrated and compared. Moreover the possibilities for integration with additional information such as interactive maps, satellite imagery, sound, video and specific information for the objects are described. This

AVIATION SECURITY AS AN OBJECT OF MATHEMATICAL MODELING

Directory of Open Access Journals (Sweden)

N. Elisov Lev

2017-01-01

Full Text Available The paper presents a mathematical formulation of the problem formalization of the subject area related to aviation security in civil aviation. The formalization task is determined by the modern issue of providing aviation security. Aviationsecurity in modern systems is based upon organizational standard of security control. This standard doesn’t require calcu- lating the security level. It allows solving the aviation security task without estimating the solution and evaluating the per- formance of security facilities. The issue of acceptable aviation security level stays unsolved, because its control lies in inspections that determine whether the object security facilities meet the requirements or not. The pending problem is also in whether the requirements are calculable and the evaluation is subjective.Lately, there has been determined quite a certain tendency to consider aviation security issues from the perspective of its level optimal control with the following identification, calculation and evaluation problems solving and decision mak- ing. The obtained results analysis in this direction shows that it’s strongly recommended to move to object formalization problem, which provides a mathematical modeling for aviation security control optimization.In this case, the authors assume to find the answer in the process of object formalization. Therefore aviation secu- rity is presented as some security environment condition, which defines the parameters associated with the object protec-tion system quality that depends on the use of protective equipment in conditions of counteraction to factors of external andinternal threats. It is shown that the proposed model belongs to a class of boundary value problems described by differential equations in partial derivatives. The classification of boundary value problems is presented.

Archive Design Based on Planets Inspired Logical Object Model

DEFF Research Database (Denmark)

Zierau, Eld; Johansen, Anders

2008-01-01

We describe a proposal for a logical data model based on preliminary work the Planets project In OAIS terms the main areas discussed are related to the introduction of a logical data model for representing the past, present and future versions of the digital object associated with the Archival St...... Storage Package for the publications deposited by our client repositories....

Tool Support for Collaborative Teaching and Learning of Object-Oriented Modelling

DEFF Research Database (Denmark)

Hansen, Klaus Marius; Ratzer, Anne Vinter

2002-01-01

Modeling is central to doing and learning object-oriented development. We present a new tool, Ideogramic UML, for gesture-based collaborative modeling with the Unified Modeling Language (UML), which can be used to collaboratively teach and learn modeling. Furthermore, we discuss how we have...

An object-oriented computational model to study cardiopulmonary hemodynamic interactions in humans.

Science.gov (United States)

Ngo, Chuong; Dahlmanns, Stephan; Vollmer, Thomas; Misgeld, Berno; Leonhardt, Steffen

2018-06-01

This work introduces an object-oriented computational model to study cardiopulmonary interactions in humans. Modeling was performed in object-oriented programing language Matlab Simscape, where model components are connected with each other through physical connections. Constitutive and phenomenological equations of model elements are implemented based on their non-linear pressure-volume or pressure-flow relationship. The model includes more than 30 physiological compartments, which belong either to the cardiovascular or respiratory system. The model considers non-linear behaviors of veins, pulmonary capillaries, collapsible airways, alveoli, and the chest wall. Model parameters were derisved based on literature values. Model validation was performed by comparing simulation results with clinical and animal data reported in literature. The model is able to provide quantitative values of alveolar, pleural, interstitial, aortic and ventricular pressures, as well as heart and lung volumes during spontaneous breathing and mechanical ventilation. Results of baseline simulation demonstrate the consistency of the assigned parameters. Simulation results during mechanical ventilation with PEEP trials can be directly compared with animal and clinical data given in literature. Object-oriented programming languages can be used to model interconnected systems including model non-linearities. The model provides a useful tool to investigate cardiopulmonary activity during spontaneous breathing and mechanical ventilation. Copyright © 2018 Elsevier B.V. All rights reserved.

Modeling guidance and recognition in categorical search: bridging human and computer object detection.

Science.gov (United States)

Zelinsky, Gregory J; Peng, Yifan; Berg, Alexander C; Samaras, Dimitris

2013-10-08

Search is commonly described as a repeating cycle of guidance to target-like objects, followed by the recognition of these objects as targets or distractors. Are these indeed separate processes using different visual features? We addressed this question by comparing observer behavior to that of support vector machine (SVM) models trained on guidance and recognition tasks. Observers searched for a categorically defined teddy bear target in four-object arrays. Target-absent trials consisted of random category distractors rated in their visual similarity to teddy bears. Guidance, quantified as first-fixated objects during search, was strongest for targets, followed by target-similar, medium-similarity, and target-dissimilar distractors. False positive errors to first-fixated distractors also decreased with increasing dissimilarity to the target category. To model guidance, nine teddy bear detectors, using features ranging in biological plausibility, were trained on unblurred bears then tested on blurred versions of the same objects appearing in each search display. Guidance estimates were based on target probabilities obtained from these detectors. To model recognition, nine bear/nonbear classifiers, trained and tested on unblurred objects, were used to classify the object that would be fixated first (based on the detector estimates) as a teddy bear or a distractor. Patterns of categorical guidance and recognition accuracy were modeled almost perfectly by an HMAX model in combination with a color histogram feature. We conclude that guidance and recognition in the context of search are not separate processes mediated by different features, and that what the literature knows as guidance is really recognition performed on blurred objects viewed in the visual periphery.

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

Science.gov (United States)

Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

2017-01-01

Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

An object-oriented framework for magnetic-fusion modeling and analysis codes

International Nuclear Information System (INIS)

Cohen, R H; Yang, T Y Brian.

1999-01-01

The magnetic-fusion energy (MFE) program, like many other scientific and engineering activities, has a need to efficiently develop complex modeling codes which combine detailed models of components to make an integrated model of a device, as well as a rich supply of legacy code that could provide the component models. There is also growing recognition in many technical fields of the desirability of steerable software: computer programs whose functionality can be changed by the user as it is run. This project had as its goals the development of two key pieces of infrastructure that are needed to combine existing code modules, written mainly in Fortran, into flexible, steerable, object-oriented integrated modeling codes for magnetic- fusion applications. These two pieces are (1) a set of tools to facilitate the interfacing of Fortran code with a steerable object-oriented framework (which we have chosen to be based on PythonlW3, an object-oriented interpreted language), and (2) a skeleton for the integrated modeling code which defines the relationships between the modules. The first of these activities obviously has immediate applicability to a spectrum of projects; the second is more focussed on the MFE application, but may be of value as an example for other applications

A Model of Socially Connected Web Objects for IoT Applications

Directory of Open Access Journals (Sweden)

Sajjad Ali

2018-01-01

Full Text Available The Internet of Things (IoT is evolving with the connected objects at an unprecedented rate, bringing about enormous opportunities for the future IoT applications as well as challenges. One of the major challenges is to handle the complexity generated by the interconnection of billions of objects. However, Social Internet of Things (SIoT, emerging from the conglomeration of IoT and social networks, has realized an efficient way to facilitate the development of complex future IoT applications. Nevertheless, to fully utilize the benefits of SIoT, a platform that can provide efficient services using social relations among heterogeneous objects is highly required. The web objects enabled IoT environment promotes SIoT features by enabling virtualization using virtual objects and supporting the modularity with microservices. To realize SIoT services, this article proposes an architecture that provides a foundation for the development of lightweight microservices based on socially connected web objects. To efficiently discover web objects and reduce the complexity of service provisioning processes, a social relationship model is presented. To realize the interoperable service operations, a semantic ontology model has been developed. Finally, to evaluate the proposed design, a prototype has been implemented based on a use case scenario.

An object-oriented language-database integration model: The composition filters approach

NARCIS (Netherlands)

Aksit, Mehmet; Bergmans, Lodewijk; Vural, Sinan; Vural, S.

1991-01-01

This paper introduces a new model, based on so-called object-composition filters, that uniformly integrates database-like features into an object-oriented language. The focus is on providing persistent dynamic data structures, data sharing, transactions, multiple views and associative access,

An Object-Oriented Language-Database Integration Model: The Composition-Filters Approach

NARCIS (Netherlands)

Aksit, Mehmet; Bergmans, Lodewijk; Vural, S.; Vural, Sinan; Lehrmann Madsen, O.

1992-01-01

This paper introduces a new model, based on so-called object-composition filters, that uniformly integrates database-like features into an object-oriented language. The focus is on providing persistent dynamic data structures, data sharing, transactions, multiple views and associative access,

Improved object optimal synthetic description, modeling, learning, and discrimination by GEOGINE computational kernel

Science.gov (United States)

Fiorini, Rodolfo A.; Dacquino, Gianfranco

2005-03-01

GEOGINE (GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for n-Dimensional shape/texture optimal synthetic representation, description and learning, was presented in previous conferences elsewhere recently. Improved computational algorithms based on the computational invariant theory of finite groups in Euclidean space and a demo application is presented. Progressive model automatic generation is discussed. GEOGINE can be used as an efficient computational kernel for fast reliable application development and delivery in advanced biomedical engineering, biometric, intelligent computing, target recognition, content image retrieval, data mining technological areas mainly. Ontology can be regarded as a logical theory accounting for the intended meaning of a formal dictionary, i.e., its ontological commitment to a particular conceptualization of the world object. According to this approach, "n-D Tensor Calculus" can be considered a "Formal Language" to reliably compute optimized "n-Dimensional Tensor Invariants" as specific object "invariant parameter and attribute words" for automated n-Dimensional shape/texture optimal synthetic object description by incremental model generation. The class of those "invariant parameter and attribute words" can be thought as a specific "Formal Vocabulary" learned from a "Generalized Formal Dictionary" of the "Computational Tensor Invariants" language. Even object chromatic attributes can be effectively and reliably computed from object geometric parameters into robust colour shape invariant characteristics. As a matter of fact, any highly sophisticated application needing effective, robust object geometric/colour invariant attribute capture and parameterization features, for reliable automated object learning and discrimination can deeply benefit from GEOGINE progressive automated model generation computational kernel performance. Main operational advantages over previous

Investigation of the 2006 Alexandrium fundyense Bloom in the Gulf of Maine: In situ Observations and Numerical Modeling.

Science.gov (United States)

Li, Yizhen; He, Ruoying; McGillicuddy, Dennis J; Anderson, Donald M; Keafer, Bruce A

2009-09-30

In situ observations and a coupled bio-physical model were used to study the germination, initiation, and development of the Gulf of Maine (GOM) Alexandrium fundyense bloom in 2006. Hydrographic measurements and comparisons with GOM climatology indicate that 2006 was a year with normal coastal water temperature, salinity, current and river runoff conditions. A. fundyense cyst abundance in bottom sediments preceding the 2006 bloom was at a moderate level compared to other recent annual cyst survey data. We used the coupled bio-physical model to hindcast coastal circulation and A. fundyense cell concentrations. Field data including water temperature, salinity, velocity time series and surface A. fundyense cell concentration maps were applied to gauge the model's fidelity. The coupled model is capable of reproducing the hydrodynamics and the temporal and spatial distributions of A. fundyense cell concentration reasonably well. Model hindcast solutions were further used to diagnose physical and biological factors controlling the bloom dynamics. Surface wind fields modulated the bloom's horizontal and vertical distribution. The initial cyst distribution was found to be the dominant factor affecting the severity and the interannual variability of the A. fundyense bloom. Initial cyst abundance for the 2006 bloom was about 50% of that prior to the 2005 bloom. As the result, the time-averaged gulf-wide cell concentration in 2006 was also only about 60% of that in 2005. In addition, weaker alongshore currents and episodic upwelling-favorable winds in 2006 reduced the spatial extent of the bloom as compared with 2005.

Developing a Novel Multi-objective Programming Model for Personnel Assignment Problem

Directory of Open Access Journals (Sweden)

Mehdi Seifbarghy

2014-05-01

Full Text Available The assignment of personnel to the right positions in order to increase organization's performance is one of the most crucial tasks in human resource management. In this paper, personnel assignment problem is formulated as a multi-objective binary integer programming model in which skills, level of satisfaction and training cost of personnel are considered simultaneously in productive company. The purpose of this model is to obtain the best matching between candidates and positions. In this model, a set of methods such as a group analytic hierarchy process (GAHP, Shannon entropy, coefficient of variation (CV and fuzzy logic are used to calculate the weights of evaluation criteria, weights of position and coefficient of objective functions. This proposed model can rationalize the subjective judgments of decision makers with mathematic models.

Geospatial Database for Strata Objects Based on Land Administration Domain Model (ladm)

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Nasorudin, N. N.; Hassan, M. I.; Zulkifli, N. A.; Rahman, A. Abdul

2016-09-01

Recently in our country, the construction of buildings become more complex and it seems that strata objects database becomes more important in registering the real world as people now own and use multilevel of spaces. Furthermore, strata title was increasingly important and need to be well-managed. LADM is a standard model for land administration and it allows integrated 2D and 3D representation of spatial units. LADM also known as ISO 19152. The aim of this paper is to develop a strata objects database using LADM. This paper discusses the current 2D geospatial database and needs for 3D geospatial database in future. This paper also attempts to develop a strata objects database using a standard data model (LADM) and to analyze the developed strata objects database using LADM data model. The current cadastre system in Malaysia includes the strata title is discussed in this paper. The problems in the 2D geospatial database were listed and the needs for 3D geospatial database in future also is discussed. The processes to design a strata objects database are conceptual, logical and physical database design. The strata objects database will allow us to find the information on both non-spatial and spatial strata title information thus shows the location of the strata unit. This development of strata objects database may help to handle the strata title and information.

Objectives for next generation of practical short-range atmospheric dispersion models

International Nuclear Information System (INIS)

Olesen, H.R.; Mikkelsen, T.

1992-01-01

The proceedings contains papers from the workshop ''Objectives for Next Generation of Practical Short-Range Atmospheric Dispersion Models''. They deal with two types of models, namely models for regulatory purposes and models for real-time applications. The workshop was the result of an action started in 1991 for increased cooperation and harmonization within atmospheric dispersion modelling. The focus of the workshop was on the management of model development and the definition of model objectives, rather than on detailed model contents. It was the intention to identify actions that can be taken in order to improve the development and use of atmospheric dispersion models. The papers in the proceedings deal with various topics within the broad spectrum of matters related to up-to-date practical models, such as their scientific basis, requirements for model input and output, meteorological preprocessing, standardisation within modelling, electronic information exchange as a potentially useful tool, model evaluation and data bases for model evaluation. In addition to the papers, the proceedings contain summaries of the discussions at the workshop. These summaries point to a number of recommended actions which can be taken in order to improve ''modelling culture''. (AB)

Requirements-level semantics and model checking of object-oriented statecharts

NARCIS (Netherlands)

Eshuis, H.; Jansen, D.N.; Wieringa, Roelf J.

2002-01-01

In this paper we define a requirements-level execution semantics for object-oriented statecharts and show how properties of a system specified by these statecharts can be model checked using tool support for model checkers. Our execution semantics is requirements-level because it uses the perfect

Learning-based stochastic object models for characterizing anatomical variations

Science.gov (United States)

Dolly, Steven R.; Lou, Yang; Anastasio, Mark A.; Li, Hua

2018-03-01

It is widely known that the optimization of imaging systems based on objective, task-based measures of image quality via computer-simulation requires the use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in human anatomy within a specified ensemble of patients remains a challenging task. Previously reported numerical anatomic models lack the ability to accurately model inter-patient and inter-organ variations in human anatomy among a broad patient population, mainly because they are established on image data corresponding to a few of patients and individual anatomic organs. This may introduce phantom-specific bias into computer-simulation studies, where the study result is heavily dependent on which phantom is used. In certain applications, however, databases of high-quality volumetric images and organ contours are available that can facilitate this SOM development. In this work, a novel and tractable methodology for learning a SOM and generating numerical phantoms from a set of volumetric training images is developed. The proposed methodology learns geometric attribute distributions (GAD) of human anatomic organs from a broad patient population, which characterize both centroid relationships between neighboring organs and anatomic shape similarity of individual organs among patients. By randomly sampling the learned centroid and shape GADs with the constraints of the respective principal attribute variations learned from the training data, an ensemble of stochastic objects can be created. The randomness in organ shape and position reflects the learned variability of human anatomy. To demonstrate the methodology, a SOM of an adult male pelvis is computed and examples of corresponding numerical phantoms are created.

Multi-objective calibration of a reservoir model: aggregation and non-dominated sorting approaches

Science.gov (United States)

Huang, Y.

2012-12-01

Numerical reservoir models can be helpful tools for water resource management. These models are generally calibrated against historical measurement data made in reservoirs. In this study, two methods are proposed for the multi-objective calibration of such models: aggregation and non-dominated sorting methods. Both methods use a hybrid genetic algorithm as an optimization engine and are different in fitness assignment. In the aggregation method, a weighted sum of scaled simulation errors is designed as an overall objective function to measure the fitness of solutions (i.e. parameter values). The contribution of this study to the aggregation method is the correlation analysis and its implication to the choice of weight factors. In the non-dominated sorting method, a novel method based on non-dominated sorting and the method of minimal distance is used to calculate the dummy fitness of solutions. The proposed methods are illustrated using a water quality model that was set up to simulate the water quality of Pepacton Reservoir, which is located to the north of New York City and is used for water supply of city. The study also compares the aggregation and the non-dominated sorting methods. The purpose of this comparison is not to evaluate the pros and cons between the two methods but to determine whether the parameter values, objective function values (simulation errors) and simulated results obtained are significantly different with each other. The final results (objective function values) from the two methods are good compromise between all objective functions, and none of these results are the worst for any objective function. The calibrated model provides an overall good performance and the simulated results with the calibrated parameter values match the observed data better than the un-calibrated parameters, which supports and justifies the use of multi-objective calibration. The results achieved in this study can be very useful for the calibration of water

Multi-Model Estimation Based Moving Object Detection for Aerial Video

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Yanning Zhang

2015-04-01

Full Text Available With the wide development of UAV (Unmanned Aerial Vehicle technology, moving target detection for aerial video has become a popular research topic in the computer field. Most of the existing methods are under the registration-detection framework and can only deal with simple background scenes. They tend to go wrong in the complex multi background scenarios, such as viaducts, buildings and trees. In this paper, we break through the single background constraint and perceive the complex scene accurately by automatic estimation of multiple background models. First, we segment the scene into several color blocks and estimate the dense optical flow. Then, we calculate an affine transformation model for each block with large area and merge the consistent models. Finally, we calculate subordinate degree to multi-background models pixel to pixel for all small area blocks. Moving objects are segmented by means of energy optimization method solved via Graph Cuts. The extensive experimental results on public aerial videos show that, due to multi background models estimation, analyzing each pixel’s subordinate relationship to multi models by energy minimization, our method can effectively remove buildings, trees and other false alarms and detect moving objects correctly.

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

International Nuclear Information System (INIS)

Zhou, Z; Folkert, M; Wang, J

2016-01-01

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidential reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

Energy Technology Data Exchange (ETDEWEB)

Zhou, Z; Folkert, M; Wang, J [UT Southwestern Medical Center, Dallas, TX (United States)

2016-06-15

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidential reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

Directory of Open Access Journals (Sweden)

Marko Budinich

Full Text Available Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA and multi-objective flux variability analysis (MO-FVA. Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity that take place at the ecosystem scale.

Connected Component Model for Multi-Object Tracking.

Science.gov (United States)

He, Zhenyu; Li, Xin; You, Xinge; Tao, Dacheng; Tang, Yuan Yan

2016-08-01

In multi-object tracking, it is critical to explore the data associations by exploiting the temporal information from a sequence of frames rather than the information from the adjacent two frames. Since straightforwardly obtaining data associations from multi-frames is an NP-hard multi-dimensional assignment (MDA) problem, most existing methods solve this MDA problem by either developing complicated approximate algorithms, or simplifying MDA as a 2D assignment problem based upon the information extracted only from adjacent frames. In this paper, we show that the relation between associations of two observations is the equivalence relation in the data association problem, based on the spatial-temporal constraint that the trajectories of different objects must be disjoint. Therefore, the MDA problem can be equivalently divided into independent subproblems by equivalence partitioning. In contrast to existing works for solving the MDA problem, we develop a connected component model (CCM) by exploiting the constraints of the data association and the equivalence relation on the constraints. Based upon CCM, we can efficiently obtain the global solution of the MDA problem for multi-object tracking by optimizing a sequence of independent data association subproblems. Experiments on challenging public data sets demonstrate that our algorithm outperforms the state-of-the-art approaches.

Identification of a Multicriteria Decision-Making Model Using the Characteristic Objects Method

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Andrzej Piegat

2014-01-01

Full Text Available This paper presents a new, nonlinear, multicriteria, decision-making method: the characteristic objects (COMET. This approach, which can be characterized as a fuzzy reference model, determines a measurement standard for decision-making problems. This model is distinguished by a constant set of specially chosen characteristic objects that are independent of the alternatives. After identifying a multicriteria model, this method can be used to compare any number of decisional objects (alternatives and select the best one. In the COMET, in contrast to other methods, the rank-reversal phenomenon is not observed. Rank-reversal is a paradoxical feature in the decision-making methods, which is caused by determining the absolute evaluations of considered alternatives on the basis of the alternatives themselves. In the Analytic Hierarchy Process (AHP method and similar methods, when a new alternative is added to the original alternative set, the evaluation base and the resulting evaluations of all objects change. A great advantage of the COMET is its ability to identify not only linear but also nonlinear multicriteria models of decision makers. This identification is based not on a ranking of component criteria of the multicriterion but on a ranking of a larger set of characteristic objects (characteristic alternatives that are independent of the small set of alternatives analyzed in a given problem. As a result, the COMET is free of the faults of other methods.

Using the object modeling system for hydrological model development and application

Directory of Open Access Journals (Sweden)

S. Kralisch

2005-01-01

Full Text Available State of the art challenges in sustainable management of water resources have created demand for integrated, flexible and easy to use hydrological models which are able to simulate the quantitative and qualitative aspects of the hydrological cycle with a sufficient degree of certainty. Existing models which have been de-veloped to fit these needs are often constrained to specific scales or purposes and thus can not be easily adapted to meet different challenges. As a solution for flexible and modularised model development and application, the Object Modeling System (OMS has been developed in a joint approach by the USDA-ARS, GPSRU (Fort Collins, CO, USA, USGS (Denver, CO, USA, and the FSU (Jena, Germany. The OMS provides a modern modelling framework which allows the implementation of single process components to be compiled and applied as custom tailored model assemblies. This paper describes basic principles of the OMS and its main components and explains in more detail how the problems during coupling of models or model components are solved inside the system. It highlights the integration of different spatial and temporal scales by their representation as spatial modelling entities embedded into time compound components. As an exam-ple the implementation of the hydrological model J2000 is discussed.

USE OF IMAGE BASED MODELLING FOR DOCUMENTATION OF INTRICATELY SHAPED OBJECTS

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M. Marčiš

2016-06-01

Full Text Available In the documentation of cultural heritage, we can encounter three dimensional shapes and structures which are complicated to measure. Such objects are for example spiral staircases, timber roof trusses, historical furniture or folk costume where it is nearly impossible to effectively use the traditional surveying or the terrestrial laser scanning due to the shape of the object, its dimensions and the crowded environment. The actual methods of digital photogrammetry can be very helpful in such cases with the emphasis on the automated processing of the extensive image data. The created high resolution 3D models and 2D orthophotos are very important for the documentation of architectural elements and they can serve as an ideal base for the vectorization and 2D drawing documentation. This contribution wants to describe the various usage of image based modelling in specific interior spaces and specific objects. The advantages and disadvantages of the photogrammetric measurement of such objects in comparison to other surveying methods are reviewed.

Use of Image Based Modelling for Documentation of Intricately Shaped Objects

Science.gov (United States)

Marčiš, M.; Barták, P.; Valaška, D.; Fraštia, M.; Trhan, O.

2016-06-01

In the documentation of cultural heritage, we can encounter three dimensional shapes and structures which are complicated to measure. Such objects are for example spiral staircases, timber roof trusses, historical furniture or folk costume where it is nearly impossible to effectively use the traditional surveying or the terrestrial laser scanning due to the shape of the object, its dimensions and the crowded environment. The actual methods of digital photogrammetry can be very helpful in such cases with the emphasis on the automated processing of the extensive image data. The created high resolution 3D models and 2D orthophotos are very important for the documentation of architectural elements and they can serve as an ideal base for the vectorization and 2D drawing documentation. This contribution wants to describe the various usage of image based modelling in specific interior spaces and specific objects. The advantages and disadvantages of the photogrammetric measurement of such objects in comparison to other surveying methods are reviewed.

Comparison of gaseous oxidized Hg measured by KCl-coated denuders, and nylon and cation exchange membranes.

Science.gov (United States)

Huang, Jiaoyan; Miller, Matthieu B; Weiss-Penzias, Peter; Gustin, Mae Sexauer

2013-07-02

The chemical compounds that make up gaseous oxidized mercury (GOM) in the atmosphere, and the reactions responsible for their formation, are not well understood. The limitations and uncertainties associated with the current method applied to measure these compounds, the KCl-coated denuder, are not known due to lack of calibration and testing. This study systematically compared the uptake of specific GOM compounds by KCl-coated denuders with that collected using nylon and cation exchange membranes in the laboratory and field. In addition, a new method for identifying different GOM compounds using thermal desorption is presented. Different GOM compounds (HgCl2, HgBr2, and HgO) were found to have different affinities for the denuder surface and the denuder underestimated each of these compounds. Membranes measured 1.3 to 3.7 times higher GOM than denuders in laboratory and field experiments. Cation exchange membranes had the highest collection efficiency. Thermodesorption profiles for the release of GOM compounds from the nylon membrane were different for HgO versus HgBr2 and HgCl2. Application of the new field method for collection and identification of GOM compounds demonstrated these vary as a function of location and time of year. Understanding the chemistry of GOM across space and time has important implications for those developing policy regarding this environmental contaminant.

A multiple objective mixed integer linear programming model for power generation expansion planning

Energy Technology Data Exchange (ETDEWEB)

Antunes, C. Henggeler; Martins, A. Gomes [INESC-Coimbra, Coimbra (Portugal); Universidade de Coimbra, Dept. de Engenharia Electrotecnica, Coimbra (Portugal); Brito, Isabel Sofia [Instituto Politecnico de Beja, Escola Superior de Tecnologia e Gestao, Beja (Portugal)

2004-03-01

Power generation expansion planning inherently involves multiple, conflicting and incommensurate objectives. Therefore, mathematical models become more realistic if distinct evaluation aspects, such as cost and environmental concerns, are explicitly considered as objective functions rather than being encompassed by a single economic indicator. With the aid of multiple objective models, decision makers may grasp the conflicting nature and the trade-offs among the different objectives in order to select satisfactory compromise solutions. This paper presents a multiple objective mixed integer linear programming model for power generation expansion planning that allows the consideration of modular expansion capacity values of supply-side options. This characteristic of the model avoids the well-known problem associated with continuous capacity values that usually have to be discretized in a post-processing phase without feedback on the nature and importance of the changes in the attributes of the obtained solutions. Demand-side management (DSM) is also considered an option in the planning process, assuming there is a sufficiently large portion of the market under franchise conditions. As DSM full costs are accounted in the model, including lost revenues, it is possible to perform an evaluation of the rate impact in order to further inform the decision process (Author)

Creation of integrated information model of 'Ukryttia' object premises condition to support the works

International Nuclear Information System (INIS)

Postil, S.D.; Ermolenko, A.I.; Ivanov, V.V.; Kotlyarov, V.T.

2002-01-01

A technology for creation of integrated information model of 'Ukryttia' Object premises conditions was developed on the basis of geoinformation system AutoCad. DB Access and instrumental utility 3D MAX. Information models and database for conditions of 'Ukryttia' object's premises located between 0.000 and 67.000 marks in axes 41-52, row G-T, were created. Using integrated information model of 'Ukryttia' object premises conditions, 3D surface distribution of radiation field in the object premises on level 0.000 has been received. It is revealed that maximum values of radiation field are concentrated over the clusters of fuel-containing materials

Perceptual video quality assessment in H.264 video coding standard using objective modeling.

Science.gov (United States)

Karthikeyan, Ramasamy; Sainarayanan, Gopalakrishnan; Deepa, Subramaniam Nachimuthu

2014-01-01

Since usage of digital video is wide spread nowadays, quality considerations have become essential, and industry demand for video quality measurement is rising. This proposal provides a method of perceptual quality assessment in H.264 standard encoder using objective modeling. For this purpose, quality impairments are calculated and a model is developed to compute the perceptual video quality metric based on no reference method. Because of the shuttle difference between the original video and the encoded video the quality of the encoded picture gets degraded, this quality difference is introduced by the encoding process like Intra and Inter prediction. The proposed model takes into account of the artifacts introduced by these spatial and temporal activities in the hybrid block based coding methods and an objective modeling of these artifacts into subjective quality estimation is proposed. The proposed model calculates the objective quality metric using subjective impairments; blockiness, blur and jerkiness compared to the existing bitrate only calculation defined in the ITU G 1070 model. The accuracy of the proposed perceptual video quality metrics is compared against popular full reference objective methods as defined by VQEG.

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

Science.gov (United States)

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

2016-08-01

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

Uncertainties of Gaseous Oxidized Mercury Measurements Using KCl-Coated Denuders, Cation-Exchange Membranes, and Nylon Membranes: Humidity Influences.

Science.gov (United States)

Huang, Jiaoyan; Gustin, Mae Sexauer

2015-05-19

Quantifying the concentration of gaseous oxidized mercury (GOM) and identifying the chemical compounds in the atmosphere are important for developing accurate local, regional, and global biogeochemical cycles. The major hypothesis driving this work was that relative humidity affects collection of GOM on KCl-coated denuders and nylon membranes, both currently being applied to measure GOM. Using a laboratory manifold system and ambient air, GOM capture efficiency on 3 different collection surfaces, including KCl-coated denuders, nylon membranes, and cation-exchange membranes, was investigated at relative humidity ranging from 25 to 75%. Recovery of permeated HgBr2 on KCl-coated denuders declined by 4-60% during spikes of relative humidity (25 to 75%). When spikes were turned off GOM recoveries returned to 60 ± 19% of permeated levels. In some cases, KCl-coated denuders were gradually passivated over time after additional humidity was applied. In this study, GOM recovery on nylon membranes decreased with high humidity and ozone concentrations. However, additional humidity enhanced GOM recovery on cation-exchange membranes. In addition, reduction and oxidation of elemental mercury during experiments was observed. The findings in this study can help to explain field observations in previous studies.

Single and multiple object tracking using log-euclidean Riemannian subspace and block-division appearance model.

Science.gov (United States)

Hu, Weiming; Li, Xi; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen; Zhang, Zhongfei

2012-12-01

Object appearance modeling is crucial for tracking objects, especially in videos captured by nonstationary cameras and for reasoning about occlusions between multiple moving objects. Based on the log-euclidean Riemannian metric on symmetric positive definite matrices, we propose an incremental log-euclidean Riemannian subspace learning algorithm in which covariance matrices of image features are mapped into a vector space with the log-euclidean Riemannian metric. Based on the subspace learning algorithm, we develop a log-euclidean block-division appearance model which captures both the global and local spatial layout information about object appearances. Single object tracking and multi-object tracking with occlusion reasoning are then achieved by particle filtering-based Bayesian state inference. During tracking, incremental updating of the log-euclidean block-division appearance model captures changes in object appearance. For multi-object tracking, the appearance models of the objects can be updated even in the presence of occlusions. Experimental results demonstrate that the proposed tracking algorithm obtains more accurate results than six state-of-the-art tracking algorithms.

Aggregate meta-models for evolutionary multiobjective and many-objective optimization

Czech Academy of Sciences Publication Activity Database

Pilát, Martin; Neruda, Roman

Roč. 116, 20 September (2013), s. 392-402 ISSN 0925-2312 R&D Projects: GA ČR GAP202/11/1368 Institutional support: RVO:67985807 Keywords : evolutionary algorithms * multiobjective optimization * many-objective optimization * surrogate models * meta-models * memetic algorithm Subject RIV: IN - Informatics, Computer Science Impact factor: 2.005, year: 2013

Object as a model of intelligent robot in the virtual workspace

Science.gov (United States)

Foit, K.; Gwiazda, A.; Banas, W.; Sekala, A.; Hryniewicz, P.

2015-11-01

The contemporary industry requires that every element of a production line will fit into the global schema, which is connected with the global structure of business. There is the need to find the practical and effective ways of the design and management of the production process. The term “effective” should be understood in a manner that there exists a method, which allows building a system of nodes and relations in order to describe the role of the particular machine in the production process. Among all the machines involved in the manufacturing process, industrial robots are the most complex ones. This complexity is reflected in the realization of elaborated tasks, involving handling, transporting or orienting the objects in a work space, and even performing simple machining processes, such as deburring, grinding, painting, applying adhesives and sealants etc. The robot also performs some activities connected with automatic tool changing and operating the equipment mounted on the wrist of the robot. Because of having the programmable control system, the robot also performs additional activities connected with sensors, vision systems, operating the storages of manipulated objects, tools or grippers, measuring stands, etc. For this reason the description of the robot as a part of production system should take into account the specific nature of this machine: the robot is a substitute of a worker, who performs his tasks in a particular environment. In this case, the model should be able to characterize the essence of "employment" in the sufficient way. One of the possible approaches to this problem is to treat the robot as an object, in the sense often used in computer science. This allows both: to describe certain operations performed on the object, as well as describing the operations performed by the object. This paper focuses mainly on the definition of the object as the model of the robot. This model is confronted with the other possible descriptions. The

Object as a model of intelligent robot in the virtual workspace

International Nuclear Information System (INIS)

Foit, K; Gwiazda, A; Banas, W; Sekala, A; Hryniewicz, P

2015-01-01

The contemporary industry requires that every element of a production line will fit into the global schema, which is connected with the global structure of business. There is the need to find the practical and effective ways of the design and management of the production process. The term “effective” should be understood in a manner that there exists a method, which allows building a system of nodes and relations in order to describe the role of the particular machine in the production process. Among all the machines involved in the manufacturing process, industrial robots are the most complex ones. This complexity is reflected in the realization of elaborated tasks, involving handling, transporting or orienting the objects in a work space, and even performing simple machining processes, such as deburring, grinding, painting, applying adhesives and sealants etc. The robot also performs some activities connected with automatic tool changing and operating the equipment mounted on the wrist of the robot. Because of having the programmable control system, the robot also performs additional activities connected with sensors, vision systems, operating the storages of manipulated objects, tools or grippers, measuring stands, etc. For this reason the description of the robot as a part of production system should take into account the specific nature of this machine: the robot is a substitute of a worker, who performs his tasks in a particular environment. In this case, the model should be able to characterize the essence of 'employment' in the sufficient way. One of the possible approaches to this problem is to treat the robot as an object, in the sense often used in computer science. This allows both: to describe certain operations performed on the object, as well as describing the operations performed by the object. This paper focuses mainly on the definition of the object as the model of the robot. This model is confronted with the other possible

A Proposed Model for Assessing Organisational Culture Towards Achieving Business Objectives

Directory of Open Access Journals (Sweden)

Hafez Salleh

2011-09-01

Full Text Available Most of the traditional business performances measures are based on productivity and process criteria, which mainly focus on method of investment appraisal such as payback method, return on investment (ROI, cost-benefits analysis (CBA, net present value (NPV, internal rate of return (IRR. However, the measurement scales of business performance are not limited to those measures. One element that has strong correlation to the business performances is ‘organisational culture’. Many studies proved that one of the significant criteria for achieving desired business objectives is the right organisational culture within workplace. Basically, the measurement of organisational culture is reflecting on two distinct elements: organisational culture and business objectives. In broader perspective, an organisation is considered effective if it meets its business objectives. This paper aims to present and discuss the preliminary culture model to indicate the culture performance within organisational. The model has been developed through literature review, expert opinion and experience which is anticipated of being able to potentially measure the culture capability of organisations across industries to “successfully achieve business objectives”. The model is composed of six progressive stages of maturity that an organisation can achieve its culture performance. For each maturity stage, the model describes a set of characteristics that must be in place for the company to achieve each stage. The validity of the proposed model will be tested by a few case studies. The idea is to provide managers with a qualitative measurement tools to enable them to identify where culture improvements are required within their organisations and to indicate their readiness for achieving business objectives.

An Object-Relational Ifc Storage Model Based on Oracle Database

Science.gov (United States)

Li, Hang; Liu, Hua; Liu, Yong; Wang, Yuan

2016-06-01

With the building models are getting increasingly complicated, the levels of collaboration across professionals attract more attention in the architecture, engineering and construction (AEC) industry. In order to adapt the change, buildingSMART developed Industry Foundation Classes (IFC) to facilitate the interoperability between software platforms. However, IFC data are currently shared in the form of text file, which is defective. In this paper, considering the object-based inheritance hierarchy of IFC and the storage features of different database management systems (DBMS), we propose a novel object-relational storage model that uses Oracle database to store IFC data. Firstly, establish the mapping rules between data types in IFC specification and Oracle database. Secondly, design the IFC database according to the relationships among IFC entities. Thirdly, parse the IFC file and extract IFC data. And lastly, store IFC data into corresponding tables in IFC database. In experiment, three different building models are selected to demonstrate the effectiveness of our storage model. The comparison of experimental statistics proves that IFC data are lossless during data exchange.

A knowledge discovery object model API for Java

Directory of Open Access Journals (Sweden)

Jones Steven JM

2003-10-01

Full Text Available Abstract Background Biological data resources have become heterogeneous and derive from multiple sources. This introduces challenges in the management and utilization of this data in software development. Although efforts are underway to create a standard format for the transmission and storage of biological data, this objective has yet to be fully realized. Results This work describes an application programming interface (API that provides a framework for developing an effective biological knowledge ontology for Java-based software projects. The API provides a robust framework for the data acquisition and management needs of an ontology implementation. In addition, the API contains classes to assist in creating GUIs to represent this data visually. Conclusions The Knowledge Discovery Object Model (KDOM API is particularly useful for medium to large applications, or for a number of smaller software projects with common characteristics or objectives. KDOM can be coupled effectively with other biologically relevant APIs and classes. Source code, libraries, documentation and examples are available at http://www.bcgsc.ca/bioinfo/software.

An Overview of the Object Protocol Model (OPM) and the OPM Data Management Tools.

Science.gov (United States)

Chen, I-Min A.; Markowitz, Victor M.

1995-01-01

Discussion of database management tools for scientific information focuses on the Object Protocol Model (OPM) and data management tools based on OPM. Topics include the need for new constructs for modeling scientific experiments, modeling object structures and experiments in OPM, queries and updates, and developing scientific database applications…

The OCoN approach to workflow modeling in object-oriented systems

NARCIS (Netherlands)

Wirtz, G.; Weske, M.H.; Giese, H.

2001-01-01

Workflow management aims at modeling and executing application processes in complex technical and organizational environments. Modern information systems are often based on object-oriented design techniques, for instance, the Unified Modeling Language (UML). These systems consist of application

An object-oriented approach to evaluating multiple spectral models

International Nuclear Information System (INIS)

Majoras, R.E.; Richardson, W.M.; Seymour, R.S.

1995-01-01

A versatile, spectroscopy analysis engine has been developed by using object-oriented design and analysis techniques coupled with an object-oriented language, C++. This engine provides the spectroscopist with the choice of several different peak shape models that are tailored to the type of spectroscopy being performed. It also allows ease of development in adapting the engine to other analytical methods requiring more complex peak fitting in the future. This results in a program that can currently be used across a wide range of spectroscopy applications and anticipates inclusion of future advances in the field. (author) 6 refs.; 1 fig

Positioning graphical objects on computer screens: a three-phase model.

Science.gov (United States)

Pastel, Robert

2011-02-01

This experiment identifies and models phases during the positioning of graphical objects (called cursors in this article) on computer displays. The human computer-interaction community has traditionally used Fitts' law to model selection in graphical user interfaces, whereas human factors experiments have found the single-component Fitts' law inadequate to model positioning of real objects. Participants (N=145) repeatedly positioned variably sized square cursors within variably sized rectangular targets using computer mice. The times for the cursor to just touch the target, for the cursor to enter the target, and for participants to indicate positioning completion were observed. The positioning tolerances were varied from very precise and difficult to imprecise and easy. The time for the cursor to touch the target was proportional to the initial cursor-target distance. The time for the cursor to completely enter the target after touching was proportional to the logarithms of cursor size divided by target tolerances. The time for participants to indicate positioning after entering was inversely proportional to the tolerance. A three-phase model defined by regions--distant, proximate, and inside the target--was proposed and could model the positioning tasks. The three-phase model provides a framework for ergonomists to evaluate new positioning techniques and can explain their deficiencies. The model provides a means to analyze tasks and enhance interaction during positioning.

SU-F-R-46: Predicting Distant Failure in Lung SBRT Using Multi-Objective Radiomics Model

Energy Technology Data Exchange (ETDEWEB)

Zhou, Z; Folkert, M; Iyengar, P; Zhang, Y; Wang, J [UT Southwestern Medical Center, Dallas, TX (United States)

2016-06-15

Purpose: To predict distant failure in lung stereotactic body radiation therapy (SBRT) in early stage non-small cell lung cancer (NSCLC) by using a new multi-objective radiomics model. Methods: Currently, most available radiomics models use the overall accuracy as the objective function. However, due to data imbalance, a single object may not reflect the performance of a predictive model. Therefore, we developed a multi-objective radiomics model which considers both sensitivity and specificity as the objective functions simultaneously. The new model is used to predict distant failure in lung SBRT using 52 patients treated at our institute. Quantitative imaging features of PET and CT as well as clinical parameters are utilized to build the predictive model. Image features include intensity features (9), textural features (12) and geometric features (8). Clinical parameters for each patient include demographic parameters (4), tumor characteristics (8), treatment faction schemes (4) and pretreatment medicines (6). The modelling procedure consists of two steps: extracting features from segmented tumors in PET and CT; and selecting features and training model parameters based on multi-objective. Support Vector Machine (SVM) is used as the predictive model, while a nondominated sorting-based multi-objective evolutionary computation algorithm II (NSGA-II) is used for solving the multi-objective optimization. Results: The accuracy for PET, clinical, CT, PET+clinical, PET+CT, CT+clinical, PET+CT+clinical are 71.15%, 84.62%, 84.62%, 85.54%, 82.69%, 84.62%, 86.54%, respectively. The sensitivities for the above seven combinations are 41.76%, 58.33%, 50.00%, 50.00%, 41.67%, 41.67%, 58.33%, while the specificities are 80.00%, 92.50%, 90.00%, 97.50%, 92.50%, 97.50%, 97.50%. Conclusion: A new multi-objective radiomics model for predicting distant failure in NSCLC treated with SBRT was developed. The experimental results show that the best performance can be obtained by combining

User's Manual for the Object User Interface (OUI): An Environmental Resource Modeling Framework

Science.gov (United States)

Markstrom, Steven L.; Koczot, Kathryn M.

2008-01-01

The Object User Interface is a computer application that provides a framework for coupling environmental-resource models and for managing associated temporal and spatial data. The Object User Interface is designed to be easily extensible to incorporate models and data interfaces defined by the user. Additionally, the Object User Interface is highly configurable through the use of a user-modifiable, text-based control file that is written in the eXtensible Markup Language. The Object User Interface user's manual provides (1) installation instructions, (2) an overview of the graphical user interface, (3) a description of the software tools, (4) a project example, and (5) specifications for user configuration and extension.

Improving a Deep Learning based RGB-D Object Recognition Model by Ensemble Learning

DEFF Research Database (Denmark)

Aakerberg, Andreas; Nasrollahi, Kamal; Heder, Thomas

2018-01-01

Augmenting RGB images with depth information is a well-known method to significantly improve the recognition accuracy of object recognition models. Another method to im- prove the performance of visual recognition models is ensemble learning. However, this method has not been widely explored...... in combination with deep convolutional neural network based RGB-D object recognition models. Hence, in this paper, we form different ensembles of complementary deep convolutional neural network models, and show that this can be used to increase the recognition performance beyond existing limits. Experiments...

A multi-objective approach to improve SWAT model calibration in alpine catchments

Science.gov (United States)

Tuo, Ye; Marcolini, Giorgia; Disse, Markus; Chiogna, Gabriele

2018-04-01

Multi-objective hydrological model calibration can represent a valuable solution to reduce model equifinality and parameter uncertainty. The Soil and Water Assessment Tool (SWAT) model is widely applied to investigate water quality and water management issues in alpine catchments. However, the model calibration is generally based on discharge records only, and most of the previous studies have defined a unique set of snow parameters for an entire basin. Only a few studies have considered snow observations to validate model results or have taken into account the possible variability of snow parameters for different subbasins. This work presents and compares three possible calibration approaches. The first two procedures are single-objective calibration procedures, for which all parameters of the SWAT model were calibrated according to river discharge alone. Procedures I and II differ from each other by the assumption used to define snow parameters: The first approach assigned a unique set of snow parameters to the entire basin, whereas the second approach assigned different subbasin-specific sets of snow parameters to each subbasin. The third procedure is a multi-objective calibration, in which we considered snow water equivalent (SWE) information at two different spatial scales (i.e. subbasin and elevation band), in addition to discharge measurements. We tested these approaches in the Upper Adige river basin where a dense network of snow depth measurement stations is available. Only the set of parameters obtained with this multi-objective procedure provided an acceptable prediction of both river discharge and SWE. These findings offer the large community of SWAT users a strategy to improve SWAT modeling in alpine catchments.

Electricity supply industry modelling for multiple objectives under demand growth uncertainty

International Nuclear Information System (INIS)

Heinrich, G.; Basson, L.; Howells, M.; Petrie, J.

2007-01-01

Appropriate energy-environment-economic (E3) modelling provides key information for policy makers in the electricity supply industry (ESI) faced with navigating a sustainable development path. Key challenges include engaging with stakeholder values and preferences, and exploring trade-offs between competing objectives in the face of underlying uncertainty. As a case study we represent the South African ESI using a partial equilibrium E3 modelling approach, and extend the approach to include multiple objectives under selected future uncertainties. This extension is achieved by assigning cost penalties to non-cost attributes to force the model's least-cost objective function to better satisfy non-cost criteria. This paper incorporates aspects of flexibility to demand growth uncertainty into each future expansion alternative by introducing stochastic programming with recourse into the model. Technology lead times are taken into account by the inclusion of a decision node along the time horizon where aspects of real options theory are considered within the planning process. Hedging in the recourse programming is automatically translated from being purely financial, to include the other attributes that the cost penalties represent. From a retrospective analysis of the cost penalties, the correct market signals, can be derived to meet policy goal, with due regard to demand uncertainty. (author)

The significance of the choice of radiobiological (NTCP) models in treatment plan objective functions

International Nuclear Information System (INIS)

Miller, J.; Fuller, M.; Vinod, S.; Holloway, L.

2009-01-01

Full text: A Clinician's discrimination between radiation therapy treatment plans is traditionally a subjective process, based on experience and existing protocols. A more objective and quantitative approach to distinguish between treatment plans is to use radiobiological or dosimetric objective functions, based on radiobiological or dosimetric models. The efficacy of models is not well understood, nor is the correlation of the rank of plans resulting from the use of models compared to the traditional subjective approach. One such radiobiological model is the Normal Tissue Complication Probability (NTCP). Dosimetric models or indicators are more accepted in clinical practice. In this study, three radiobiological models, Lyman NTCP, critical volume NTCP and relative seriality NTCP, and three dosimetric models, Mean Lung Dose (MLD) and the Lung volumes irradiated at lOGy (V|0) and 20 G y (V20), were used to rank a series of treatment plans using, harm to normal (Lung) tissue as the objective criterion. None of the models considered in this study showed consistent correlation with the Radiation Oncologists plan ranking. If radiobiological or dosimetric models are to be used in objective functions for lung treatments, based on this study it is recommended that the Lyman NTCP model be used because it will provide most consistency with traditional clinician ranking.

Modreg: A Modular Framework for RGB-D Image Acquisition and 3D Object Model Registration

Directory of Open Access Journals (Sweden)

Kornuta Tomasz

2017-09-01

Full Text Available RGB-D sensors became a standard in robotic applications requiring object recognition, such as object grasping and manipulation. A typical object recognition system relies on matching of features extracted from RGB-D images retrieved from the robot sensors with the features of the object models. In this paper we present ModReg: a system for registration of 3D models of objects. The system consists of a modular software associated with a multi-camera setup supplemented with an additional pattern projector, used for the registration of high-resolution RGB-D images. The objects are placed on a fiducial board with two dot patterns enabling extraction of masks of the placed objects and estimation of their initial poses. The acquired dense point clouds constituting subsequent object views undergo pairwise registration and at the end are optimized with a graph-based technique derived from SLAM. The combination of all those elements resulted in a system able to generate consistent 3D models of objects.

Development of Large Concrete Object Geometrical Model Based on Terrestrial Laser Scanning

Directory of Open Access Journals (Sweden)

Zaczek-Peplinska Janina

2015-02-01

Full Text Available The paper presents control periodic measurements of movements and survey of concrete dam on Dunajec River in Rożnów, Poland. Topographical survey was conducted using laser scanning technique. The goal of survey was data collection and creation of a geometrical model. Acquired cross- and horizontal sections were utilised to create a numerical model of object behaviour at various load depending of changing level of water in reservoir. Modelling was accomplished using finite elements technique. During the project an assessment was conducted to terrestrial laser scanning techniques for such type of research of large hydrotechnical objects such as gravitational water dams. Developed model can be used to define deformations and displacement prognosis.

Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

Directory of Open Access Journals (Sweden)

Lei Qin

2014-05-01

Full Text Available We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences.

Modelling and Order of Acoustic Transfer Functions Due to Reflections from Augmented Objects

Directory of Open Access Journals (Sweden)

Diemer de Vries

2007-01-01

Full Text Available It is commonly accepted that the sound reflections from real physical objects are much more complicated than what usually is and can be modelled by room acoustics modelling software. The main reason for this limitation is the level of detail inherent in the physical object in terms of its geometrical and acoustic properties. In the present paper, the complexity of the sound reflections from a corridor wall is investigated by modelling the corresponding acoustic transfer functions at several receiver positions in front of the wall. The complexity for different wall configurations has been examined and the changes have been achieved by altering its acoustic image. The results show that for a homogenous flat wall, the complexity is significant and for a wall including various smaller objects, the complexity is highly dependent on the position of the receiver with respect to the objects.

Country Selection Model for Sustainable Construction Businesses Using Hybrid of Objective and Subjective Information

Directory of Open Access Journals (Sweden)

Kang-Wook Lee

2017-05-01

Full Text Available An important issue for international businesses and academia is selecting countries in which to expand in order to achieve entrepreneurial sustainability. This study develops a country selection model for sustainable construction businesses using both objective and subjective information. The objective information consists of 14 variables related to country risk and project performance in 32 countries over 25 years. This hybrid model applies subjective weighting from industrial experts to objective information using a fuzzy LinPreRa-based Analytic Hierarchy Process. The hybrid model yields a more accurate country selection compared to a purely objective information-based model in experienced countries. Interestingly, the hybrid model provides some different predictions with only subjective opinions in unexperienced countries, which implies that expert opinion is not always reliable. In addition, feedback from five experts in top international companies is used to validate the model’s completeness, effectiveness, generality, and applicability. The model is expected to aid decision makers in selecting better candidate countries that lead to sustainable business success.

Real-time Pipeline for Object Modeling and Grasping Pose Selection via Superquadric Functions

Directory of Open Access Journals (Sweden)

Giulia Vezzani

2017-11-01

Full Text Available This work provides a novel real-time pipeline for modeling and grasping of unknown objects with a humanoid robot. Such a problem is of great interest for the robotic community, since conventional approaches fail when the shape, dimension, or pose of the objects are missing. Our approach reconstructs in real-time a model for the object under consideration and represents the robot hand both with proper and mathematically usable models, i.e., superquadric functions. The volume graspable by the hand is represented by an ellipsoid and is defined a priori, because the shape of the hand is known in advance. The superquadric representing the object is obtained in real-time from partial vision information instead, e.g., one stereo view of the object under consideration, and provides an approximated 3D full model. The optimization problem we formulate for the grasping pose computation is solved online by using the Ipopt software package and, thus, does not require off-line computation or learning. Even though our approach is for a generic humanoid robot, we developed a complete software architecture for executing this approach on the iCub humanoid robot. Together with that, we also provide a tutorial on how to use this framework. We believe that our work, together with the available code, is of a strong utility for the iCub community for three main reasons: object modeling and grasping are relevant problems for the robotic community, our code can be easily applied on every iCub, and the modular structure of our framework easily allows extensions and communications with external code.

Object location and object recognition memory impairments, motivation deficits and depression in a model of Gulf War illness.

Science.gov (United States)

Hattiangady, Bharathi; Mishra, Vikas; Kodali, Maheedhar; Shuai, Bing; Rao, Xiolan; Shetty, Ashok K

2014-01-01

Memory and mood deficits are the enduring brain-related symptoms in Gulf War illness (GWI). Both animal model and epidemiological investigations have indicated that these impairments in a majority of GW veterans are linked to exposures to chemicals such as pyridostigmine bromide (PB, an antinerve gas drug), permethrin (PM, an insecticide) and DEET (a mosquito repellant) encountered during the Persian Gulf War-1. Our previous study in a rat model has shown that combined exposures to low doses of GWI-related (GWIR) chemicals PB, PM, and DEET with or without 5-min of restraint stress (a mild stress paradigm) causes hippocampus-dependent spatial memory dysfunction in a water maze test (WMT) and increased depressive-like behavior in a forced swim test (FST). In this study, using a larger cohort of rats exposed to GWIR-chemicals and stress, we investigated whether the memory deficiency identified earlier in a WMT is reproducible with an alternative and stress free hippocampus-dependent memory test such as the object location test (OLT). We also ascertained the possible co-existence of hippocampus-independent memory dysfunction using a novel object recognition test (NORT), and alterations in mood function with additional tests for motivation and depression. Our results provide new evidence that exposure to low doses of GWIR-chemicals and mild stress for 4 weeks causes deficits in hippocampus-dependent object location memory and perirhinal cortex-dependent novel object recognition memory. An open field test performed prior to other behavioral analyses revealed that memory impairments were not associated with increased anxiety or deficits in general motor ability. However, behavioral tests for mood function such as a voluntary physical exercise paradigm and a novelty suppressed feeding test (NSFT) demonstrated decreased motivation levels and depression. Thus, exposure to GWIR-chemicals and stress causes both hippocampus-dependent and hippocampus-independent memory

State estimates and forecasts of the loop current in the Gulf of Mexico using the MITgcm and its adjoint

KAUST Repository

Gopalakrishnan, Ganesh

2013-07-01

An ocean state estimate has been developed for the Gulf of Mexico (GoM) using the MIT general circulation model and its adjoint. The estimate has been tested by forecasting loop current (LC) evolution and eddy shedding in the GoM. The adjoint (or four-dimensional variational) method was used to match the model evolution to observations by adjusting model temperature and salinity initial conditions, open boundary conditions, and atmospheric forcing fields. The model was fit to satellite-derived along-track sea surface height, separated into temporal mean and anomalies, and gridded sea surface temperature for 2 month periods. The optimized state at the end of the assimilation period was used to initialize the forecast for 2 months. Forecasts explore practical LC predictability and provide a cross-validation test of the state estimate by comparing it to independent future observations. The model forecast was tested for several LC eddy separation events, including Eddy Franklin in May 2010 during the deepwater horizon oil spill disaster in the GoM. The forecast used monthly climatological open boundary conditions, atmospheric forcing, and run-off fluxes. The model performance was evaluated by computing model-observation root-mean-square difference (rmsd) during both the hindcast and forecast periods. The rmsd metrics for the forecast generally outperformed persistence (keeping the initial state fixed) and reference (forecast initialized using assimilated Hybrid Coordinate Ocean Model 1/12° global analysis) model simulations during LC eddy separation events for a period of 1̃2 months.

State estimates and forecasts of the loop current in the Gulf of Mexico using the MITgcm and its adjoint

KAUST Repository

Gopalakrishnan, Ganesh; Cornuelle, Bruce D.; Hoteit, Ibrahim; Rudnick, Daniel L.; Owens, W. Brechner

2013-01-01

An ocean state estimate has been developed for the Gulf of Mexico (GoM) using the MIT general circulation model and its adjoint. The estimate has been tested by forecasting loop current (LC) evolution and eddy shedding in the GoM. The adjoint (or four-dimensional variational) method was used to match the model evolution to observations by adjusting model temperature and salinity initial conditions, open boundary conditions, and atmospheric forcing fields. The model was fit to satellite-derived along-track sea surface height, separated into temporal mean and anomalies, and gridded sea surface temperature for 2 month periods. The optimized state at the end of the assimilation period was used to initialize the forecast for 2 months. Forecasts explore practical LC predictability and provide a cross-validation test of the state estimate by comparing it to independent future observations. The model forecast was tested for several LC eddy separation events, including Eddy Franklin in May 2010 during the deepwater horizon oil spill disaster in the GoM. The forecast used monthly climatological open boundary conditions, atmospheric forcing, and run-off fluxes. The model performance was evaluated by computing model-observation root-mean-square difference (rmsd) during both the hindcast and forecast periods. The rmsd metrics for the forecast generally outperformed persistence (keeping the initial state fixed) and reference (forecast initialized using assimilated Hybrid Coordinate Ocean Model 1/12° global analysis) model simulations during LC eddy separation events for a period of 1̃2 months.

Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.

Science.gov (United States)

Spoerer, Courtney J; McClure, Patrick; Kriegeskorte, Nikolaus

2017-01-01

Feedforward neural networks provide the dominant model of how the brain performs visual object recognition. However, these networks lack the lateral and feedback connections, and the resulting recurrent neuronal dynamics, of the ventral visual pathway in the human and non-human primate brain. Here we investigate recurrent convolutional neural networks with bottom-up (B), lateral (L), and top-down (T) connections. Combining these types of connections yields four architectures (B, BT, BL, and BLT), which we systematically test and compare. We hypothesized that recurrent dynamics might improve recognition performance in the challenging scenario of partial occlusion. We introduce two novel occluded object recognition tasks to test the efficacy of the models, digit clutter (where multiple target digits occlude one another) and digit debris (where target digits are occluded by digit fragments). We find that recurrent neural networks outperform feedforward control models (approximately matched in parametric complexity) at recognizing objects, both in the absence of occlusion and in all occlusion conditions. Recurrent networks were also found to be more robust to the inclusion of additive Gaussian noise. Recurrent neural networks are better in two respects: (1) they are more neurobiologically realistic than their feedforward counterparts; (2) they are better in terms of their ability to recognize objects, especially under challenging conditions. This work shows that computer vision can benefit from using recurrent convolutional architectures and suggests that the ubiquitous recurrent connections in biological brains are essential for task performance.

Remote object authentication: confidence model, cryptosystem and protocol

Science.gov (United States)

Lancrenon, Jean; Gillard, Roland; Fournel, Thierry

2009-04-01

This paper follows a paper by Bringer et al.3 to adapt a security model and protocol used for remote biometric authentication to the case of remote morphometric object authentication. We use a different type of encryption technique that requires smaller key sizes and has a built-in mechanism to help control the integrity of the messages received by the server. We also describe the optical technology used to extract the morphometric templates.

A recurrent neural model for proto-object based contour integration and figure-ground segregation.

Science.gov (United States)

Hu, Brian; Niebur, Ernst

2017-12-01

Visual processing of objects makes use of both feedforward and feedback streams of information. However, the nature of feedback signals is largely unknown, as is the identity of the neuronal populations in lower visual areas that receive them. Here, we develop a recurrent neural model to address these questions in the context of contour integration and figure-ground segregation. A key feature of our model is the use of grouping neurons whose activity represents tentative objects ("proto-objects") based on the integration of local feature information. Grouping neurons receive input from an organized set of local feature neurons, and project modulatory feedback to those same neurons. Additionally, inhibition at both the local feature level and the object representation level biases the interpretation of the visual scene in agreement with principles from Gestalt psychology. Our model explains several sets of neurophysiological results (Zhou et al. Journal of Neuroscience, 20(17), 6594-6611 2000; Qiu et al. Nature Neuroscience, 10(11), 1492-1499 2007; Chen et al. Neuron, 82(3), 682-694 2014), and makes testable predictions about the influence of neuronal feedback and attentional selection on neural responses across different visual areas. Our model also provides a framework for understanding how object-based attention is able to select both objects and the features associated with them.

Interactive object modelling based on piecewise planar surface patches.

Science.gov (United States)

Prankl, Johann; Zillich, Michael; Vincze, Markus

2013-06-01

Detecting elements such as planes in 3D is essential to describe objects for applications such as robotics and augmented reality. While plane estimation is well studied, table-top scenes exhibit a large number of planes and methods often lock onto a dominant plane or do not estimate 3D object structure but only homographies of individual planes. In this paper we introduce MDL to the problem of incrementally detecting multiple planar patches in a scene using tracked interest points in image sequences. Planar patches are reconstructed and stored in a keyframe-based graph structure. In case different motions occur, separate object hypotheses are modelled from currently visible patches and patches seen in previous frames. We evaluate our approach on a standard data set published by the Visual Geometry Group at the University of Oxford [24] and on our own data set containing table-top scenes. Results indicate that our approach significantly improves over the state-of-the-art algorithms.

Interactive object modelling based on piecewise planar surface patches☆

Science.gov (United States)

Prankl, Johann; Zillich, Michael; Vincze, Markus

2013-01-01

Detecting elements such as planes in 3D is essential to describe objects for applications such as robotics and augmented reality. While plane estimation is well studied, table-top scenes exhibit a large number of planes and methods often lock onto a dominant plane or do not estimate 3D object structure but only homographies of individual planes. In this paper we introduce MDL to the problem of incrementally detecting multiple planar patches in a scene using tracked interest points in image sequences. Planar patches are reconstructed and stored in a keyframe-based graph structure. In case different motions occur, separate object hypotheses are modelled from currently visible patches and patches seen in previous frames. We evaluate our approach on a standard data set published by the Visual Geometry Group at the University of Oxford [24] and on our own data set containing table-top scenes. Results indicate that our approach significantly improves over the state-of-the-art algorithms. PMID:24511219

On hierarchical models for visual recognition and learning of objects, scenes, and activities

CERN Document Server

Spehr, Jens

2015-01-01

In many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information. Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model...

An Object-oriented Knowledge Link Model for General Knowledge Management

OpenAIRE

Xiao-hong, CHEN; Bang-chuan, LAI

2005-01-01

The knowledge link is the basic on knowledge share and the indispensable part in knowledge standardization management. In this paper, a object-oriented knowledge link model is proposed for general knowledge management by using objectoriented representation based on knowledge levels system. In the model, knowledge link is divided into general knowledge link and integrated knowledge with corresponding link properties and methods. What’s more, its BNF syntax is described and designed.

Advertising Model of Residential Real Estate Object in Lithuania

Directory of Open Access Journals (Sweden)

Jelena Mazaj

2012-07-01

Full Text Available Since the year 2000, during the period of economic growth, the real estate market has been rapidly expanding. During this period advertising of real estate objects was implemented using one set of similar channels (press advertising, Internet advertising, leaflets with contact information of real estate agents and others, however the start of the economic recession has intensified the competition in the market and forced companies to search for new advertising means or to diversify the advertising package. The article presents real estate property, as a product, one of the marketing components – including advertising, conclusions and suggestions based on conducted surveys and a model for advertising the residential real estate objects.Article in Lithuanian

Personalised learning object based on multi-agent model and learners’ learning styles

Directory of Open Access Journals (Sweden)

Noppamas Pukkhem

2011-09-01

Full Text Available A multi-agent model is proposed in which learning styles and a word analysis technique to create a learning object recommendation system are used. On the basis of a learning style-based design, a concept map combination model is proposed to filter out unsuitable learning concepts from a given course. Our learner model classifies learners into eight styles and implements compatible computational methods consisting of three recommendations: i non-personalised, ii preferred feature-based, and iii neighbour-based collaborative filtering. The analysis of preference error (PE was performed by comparing the actual preferred learning object with the predicted one. In our experiments, the feature-based recommendation algorithm has the fewest PE.

Objects Classification by Learning-Based Visual Saliency Model and Convolutional Neural Network.

Science.gov (United States)

Li, Na; Zhao, Xinbo; Yang, Yongjia; Zou, Xiaochun

2016-01-01

Humans can easily classify different kinds of objects whereas it is quite difficult for computers. As a hot and difficult problem, objects classification has been receiving extensive interests with broad prospects. Inspired by neuroscience, deep learning concept is proposed. Convolutional neural network (CNN) as one of the methods of deep learning can be used to solve classification problem. But most of deep learning methods, including CNN, all ignore the human visual information processing mechanism when a person is classifying objects. Therefore, in this paper, inspiring the completed processing that humans classify different kinds of objects, we bring forth a new classification method which combines visual attention model and CNN. Firstly, we use the visual attention model to simulate the processing of human visual selection mechanism. Secondly, we use CNN to simulate the processing of how humans select features and extract the local features of those selected areas. Finally, not only does our classification method depend on those local features, but also it adds the human semantic features to classify objects. Our classification method has apparently advantages in biology. Experimental results demonstrated that our method made the efficiency of classification improve significantly.

Object and subject relations in adulthood--towards an integrative model of interpersonal relationships.

Science.gov (United States)

Zvelc, Gregor

2010-12-01

In the article the author presents a model of interpersonal relationships based on integration of object relations theory and theory of attachment. He proposes three main bipolar dimensions of interpersonal relationships: Independence - Dependence, Connectedness - Alienation and Reciprocity - Self-absorption. The author also proposes that it is important to distinguish between two main types of adult interpersonal relationships: object and subject relations. Object relations describe relationships in which the other person is perceived as an object that serves the satisfaction of the first person's needs. Object relations are a manifestation of the right pole of the three main dimensions of interpersonal relationships (Dependence, Alienation and Self-absorption). Subject relations are a counter-pole to the concept of object relations. They describe relationships with other people who are experienced as subjects with their own wishes, interests and needs. Subject relations are a manifestation of the left pole of the main dimensions (Independence, Connectedness and Reciprocity). In this article the author specifically focuses on definitions of object relations in adulthood through a description of six sub-dimensions of object relations: Symbiotic Merging, Separation Anxiety, Social Isolation, Fear of Engulfment, Egocentrism and Narcissism. Every sub-dimension is described in connection to adaptive and pathological functioning. Further research is needed to test the clinical and scientific validity of the model.

A neural network model of semantic memory linking feature-based object representation and words.

Science.gov (United States)

Cuppini, C; Magosso, E; Ursino, M

2009-06-01

Recent theories in cognitive neuroscience suggest that semantic memory is a distributed process, which involves many cortical areas and is based on a multimodal representation of objects. The aim of this work is to extend a previous model of object representation to realize a semantic memory, in which sensory-motor representations of objects are linked with words. The model assumes that each object is described as a collection of features, coded in different cortical areas via a topological organization. Features in different objects are segmented via gamma-band synchronization of neural oscillators. The feature areas are further connected with a lexical area, devoted to the representation of words. Synapses among the feature areas, and among the lexical area and the feature areas are trained via a time-dependent Hebbian rule, during a period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from acoustic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits).

Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet.

Science.gov (United States)

Rolls, Edmund T

2012-01-01

Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus.

A probabilistic multi objective CLSC model with Genetic algorithm-ε_Constraint approach

Directory of Open Access Journals (Sweden)

Alireza TaheriMoghadam

2014-05-01

Full Text Available In this paper an uncertain multi objective closed-loop supply chain is developed. The first objective function is maximizing the total profit. The second objective function is minimizing the use of row materials. In the other word, the second objective function is maximizing the amount of remanufacturing and recycling. Genetic algorithm is used for optimization and for finding the pareto optimal line, Epsilon-constraint method is used. Finally a numerical example is solved with proposed approach and performance of the model is evaluated in different sizes. The results show that this approach is effective and useful for managerial decisions.

Models for predicting objective function weights in prostate cancer IMRT

International Nuclear Information System (INIS)

Boutilier, Justin J.; Lee, Taewoo; Craig, Tim; Sharpe, Michael B.; Chan, Timothy C. Y.

2015-01-01

Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR

Models for predicting objective function weights in prostate cancer IMRT

Energy Technology Data Exchange (ETDEWEB)

Boutilier, Justin J., E-mail: j.boutilier@mail.utoronto.ca; Lee, Taewoo [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8 (Canada); Craig, Tim [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9, Canada and Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Sharpe, Michael B. [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9 (Canada); Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada); Chan, Timothy C. Y. [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8, Canada and Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada)

2015-04-15

Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR

Model of Recommendation System for for Indexing and Retrieving the Learning Object based on Multiagent System

Directory of Open Access Journals (Sweden)

Ronaldo Lima Rocha Campos

2012-07-01

Full Text Available This paper proposes a multiagent system application model for indexing, retrieving and recommendation learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata standards. The searching mechanism covers several different learning object repositories and the same object can be described in these repositories by the use of different types of fields. Aiming to improve accuracy and coverage in terms of recovering a learning object and improve the signification of the results we propose an information retrieval model based on the multiagent system approach and an ontological model to describe the knowledge domain covered.

Comparison of different multi-objective calibration criteria using a conceptual rainfall-runoff model of flood events

Directory of Open Access Journals (Sweden)

R. Moussa

2009-04-01

Full Text Available A conceptual lumped rainfall-runoff flood event model was developed and applied on the Gardon catchment located in Southern France and various single-objective and multi-objective functions were used for its calibration. The model was calibrated on 15 events and validated on 14 others. The results of both the calibration and validation phases are compared on the basis of their performance with regards to six criteria, three global criteria and three relative criteria representing volume, peakflow, and the root mean square error. The first type of criteria gives more weight to large events whereas the second considers all events to be of equal weight. The results show that the calibrated parameter values are dependent on the type of criteria used. Significant trade-offs are observed between the different objectives: no unique set of parameters is able to satisfy all objectives simultaneously. Instead, the solution to the calibration problem is given by a set of Pareto optimal solutions. From this set of optimal solutions, a balanced aggregated objective function is proposed, as a compromise between up to three objective functions. The single-objective and multi-objective calibration strategies are compared both in terms of parameter variation bounds and simulation quality. The results of this study indicate that two well chosen and non-redundant objective functions are sufficient to calibrate the model and that the use of three objective functions does not necessarily yield different results. The problems of non-uniqueness in model calibration, and the choice of the adequate objective functions for flood event models, emphasise the importance of the modeller's intervention. The recent advances in automatic optimisation techniques do not minimise the user's responsibility, who has to choose multiple criteria based on the aims of the study, his appreciation on the errors induced by data and model structure and his knowledge of the

Development of a Conceptual Model and Survey Instrument to Measure Conscientious Objection to Abortion Provision.

Directory of Open Access Journals (Sweden)

Laura Florence Harris

Full Text Available Conscientious objection to abortion, clinicians' refusal to perform legal abortions because of their religious or moral beliefs, has been the subject of increasing debate among bioethicists, policymakers, and public health advocates in recent years. Conscientious objection policies are intended to balance reproductive rights and clinicians' beliefs. However, in practice, clinician objection can act as a barrier to abortion access-impinging on reproductive rights, and increasing unsafe abortion and related morbidity and mortality. There is little information about conscientious objection from a medical or public health perspective. A quantitative instrument is needed to assess prevalence of conscientious objection and to provide insight on its practice. This paper describes the development of a survey instrument to measure conscientious objection to abortion provision.A literature review, and in-depth formative interviews with stakeholders in Colombia were used to develop a conceptual model of conscientious objection. This model led to the development of a survey, which was piloted, and then administered, in Ghana.The model posits three domains of conscientious objection that form the basis for the survey instrument: 1 beliefs about abortion and conscientious objection; 2 actions related to conscientious objection and abortion; and 3 self-identification as a conscientious objector.The instrument is intended to be used to assess prevalence among clinicians trained to provide abortions, and to gain insight on how conscientious objection is practiced in a variety of settings. Its results can inform more effective and appropriate strategies to regulate conscientious objection.

An Object-Oriented Information Model for Policy-based Management of Distributed Applications

NARCIS (Netherlands)

Diaz, G.; Gay, V.C.J.; Horlait, E.; Hamza, M.H.

2002-01-01

This paper presents an object-oriented information model to support a policy-based management for distributed multimedia applications. The information base contains application-level information about the users, the applications, and their profile. Our Information model is described in details and

Deconvolution of Complex 1D NMR Spectra Using Objective Model Selection.

Directory of Open Access Journals (Sweden)

Travis S Hughes

Full Text Available Fluorine (19F NMR has emerged as a useful tool for characterization of slow dynamics in 19F-labeled proteins. One-dimensional (1D 19F NMR spectra of proteins can be broad, irregular and complex, due to exchange of probe nuclei between distinct electrostatic environments; and therefore cannot be deconvoluted and analyzed in an objective way using currently available software. We have developed a Python-based deconvolution program, decon1d, which uses Bayesian information criteria (BIC to objectively determine which model (number of peaks would most likely produce the experimentally obtained data. The method also allows for fitting of intermediate exchange spectra, which is not supported by current software in the absence of a specific kinetic model. In current methods, determination of the deconvolution model best supported by the data is done manually through comparison of residual error values, which can be time consuming and requires model selection by the user. In contrast, the BIC method used by decond1d provides a quantitative method for model comparison that penalizes for model complexity helping to prevent over-fitting of the data and allows identification of the most parsimonious model. The decon1d program is freely available as a downloadable Python script at the project website (https://github.com/hughests/decon1d/.

Efficient Use of Video for 3d Modelling of Cultural Heritage Objects

Science.gov (United States)

Alsadik, B.; Gerke, M.; Vosselman, G.

2015-03-01

Currently, there is a rapid development in the techniques of the automated image based modelling (IBM), especially in advanced structure-from-motion (SFM) and dense image matching methods, and camera technology. One possibility is to use video imaging to create 3D reality based models of cultural heritage architectures and monuments. Practically, video imaging is much easier to apply when compared to still image shooting in IBM techniques because the latter needs a thorough planning and proficiency. However, one is faced with mainly three problems when video image sequences are used for highly detailed modelling and dimensional survey of cultural heritage objects. These problems are: the low resolution of video images, the need to process a large number of short baseline video images and blur effects due to camera shake on a significant number of images. In this research, the feasibility of using video images for efficient 3D modelling is investigated. A method is developed to find the minimal significant number of video images in terms of object coverage and blur effect. This reduction in video images is convenient to decrease the processing time and to create a reliable textured 3D model compared with models produced by still imaging. Two experiments for modelling a building and a monument are tested using a video image resolution of 1920×1080 pixels. Internal and external validations of the produced models are applied to find out the final predicted accuracy and the model level of details. Related to the object complexity and video imaging resolution, the tests show an achievable average accuracy between 1 - 5 cm when using video imaging, which is suitable for visualization, virtual museums and low detailed documentation.

EFFICIENT USE OF VIDEO FOR 3D MODELLING OF CULTURAL HERITAGE OBJECTS

Directory of Open Access Journals (Sweden)

B. Alsadik

2015-03-01

Full Text Available Currently, there is a rapid development in the techniques of the automated image based modelling (IBM, especially in advanced structure-from-motion (SFM and dense image matching methods, and camera technology. One possibility is to use video imaging to create 3D reality based models of cultural heritage architectures and monuments. Practically, video imaging is much easier to apply when compared to still image shooting in IBM techniques because the latter needs a thorough planning and proficiency. However, one is faced with mainly three problems when video image sequences are used for highly detailed modelling and dimensional survey of cultural heritage objects. These problems are: the low resolution of video images, the need to process a large number of short baseline video images and blur effects due to camera shake on a significant number of images. In this research, the feasibility of using video images for efficient 3D modelling is investigated. A method is developed to find the minimal significant number of video images in terms of object coverage and blur effect. This reduction in video images is convenient to decrease the processing time and to create a reliable textured 3D model compared with models produced by still imaging. Two experiments for modelling a building and a monument are tested using a video image resolution of 1920×1080 pixels. Internal and external validations of the produced models are applied to find out the final predicted accuracy and the model level of details. Related to the object complexity and video imaging resolution, the tests show an achievable average accuracy between 1 – 5 cm when using video imaging, which is suitable for visualization, virtual museums and low detailed documentation.

An object-oriented forest landscape model and its representation of tree species

Science.gov (United States)

Hong S. He; David J. Mladenoff; Joel Boeder

1999-01-01

LANDIS is a forest landscape model that simulates the interaction of large landscape processes and forest successional dynamics at tree species level. We discuss how object-oriented design (OOD) approaches such as modularity, abstraction and encapsulation are integrated into the design of LANDIS. We show that using OOD approaches, model decisions (olden as model...

Closed-loop model identification of cooperative manipulators holding deformable objects

Science.gov (United States)

Alkathiri, A. A.; Akmeliawati, R.; Azlan, N. Z.

2017-11-01

This paper presents system identification to obtain the closed-loop models of a couple of cooperative manipulators in a system, which function to hold deformable objects. The system works using the master-slave principle. In other words, one of the manipulators is position-controlled through encoder feedback, while a force sensor gives feedback to the other force-controlled manipulator. Using the closed-loop input and output data, the closed-loop models, which are useful for model-based control design, are estimated. The criteria for model validation are a 95% fit between the measured and simulated output of the estimated models and residual analysis. The results show that for both position and force control respectively, the fits are 95.73% and 95.88%.

Considering Decision Variable Diversity in Multi-Objective Optimization: Application in Hydrologic Model Calibration

Science.gov (United States)

Sahraei, S.; Asadzadeh, M.

2017-12-01

Any modern multi-objective global optimization algorithm should be able to archive a well-distributed set of solutions. While the solution diversity in the objective space has been explored extensively in the literature, little attention has been given to the solution diversity in the decision space. Selection metrics such as the hypervolume contribution and crowding distance calculated in the objective space would guide the search toward solutions that are well-distributed across the objective space. In this study, the diversity of solutions in the decision-space is used as the main selection criteria beside the dominance check in multi-objective optimization. To this end, currently archived solutions are clustered in the decision space and the ones in less crowded clusters are given more chance to be selected for generating new solution. The proposed approach is first tested on benchmark mathematical test problems. Second, it is applied to a hydrologic model calibration problem with more than three objective functions. Results show that the chance of finding more sparse set of high-quality solutions increases, and therefore the analyst would receive a well-diverse set of options with maximum amount of information. Pareto Archived-Dynamically Dimensioned Search, which is an efficient and parsimonious multi-objective optimization algorithm for model calibration, is utilized in this study.

Multi-objective decision-making model based on CBM for an aircraft fleet

Science.gov (United States)

Luo, Bin; Lin, Lin

2018-04-01

Modern production management patterns, in which multi-unit (e.g., a fleet of aircrafts) are managed in a holistic manner, have brought new challenges for multi-unit maintenance decision making. To schedule a good maintenance plan, not only does the individual machine maintenance have to be considered, but also the maintenance of the other individuals have to be taken into account. Since most condition-based maintenance researches for aircraft focused on solely reducing maintenance cost or maximizing the availability of single aircraft, as well as considering that seldom researches concentrated on both the two objectives: minimizing cost and maximizing the availability of a fleet (total number of available aircraft in fleet), a multi-objective decision-making model based on condition-based maintenance concentrated both on the above two objectives is established. Furthermore, in consideration of the decision maker may prefer providing the final optimal result in the form of discrete intervals instead of a set of points (non-dominated solutions) in real decision-making problem, a novel multi-objective optimization method based on support vector regression is proposed to solve the above multi-objective decision-making model. Finally, a case study regarding a fleet is conducted, with the results proving that the approach efficiently generates outcomes that meet the schedule requirements.

Use of an object model in three dimensional image reconstruction. Application in medical imaging

International Nuclear Information System (INIS)

Delageniere-Guillot, S.

1993-02-01

Threedimensional image reconstruction from projections corresponds to a set of techniques which give information on the inner structure of the studied object. These techniques are mainly used in medical imaging or in non destructive evaluation. Image reconstruction is an ill-posed problem. So the inversion has to be regularized. This thesis deals with the introduction of a priori information within the reconstruction algorithm. The knowledge is introduced through an object model. The proposed scheme is applied to the medical domain for cone beam geometry. We address two specific problems. First, we study the reconstruction of high contrast objects. This can be applied to bony morphology (bone/soft tissue) or to angiography (vascular structures opacified by injection of contrast agent). With noisy projections, the filtering steps of standard methods tend to smooth the natural transitions of the investigated object. In order to regularize the reconstruction but to keep contrast, we introduce a model of classes which involves the Markov random fields theory. We develop a reconstruction scheme: analytic reconstruction-reprojection. Then, we address the case of an object changing during the acquisition. This can be applied to angiography when the contrast agent is moving through the vascular tree. The problem is then stated as a dynamic reconstruction. We define an evolution AR model and we use an algebraic reconstruction method. We represent the object at a particular moment as an intermediary state between the state of the object at the beginning and at the end of the acquisition. We test both methods on simulated and real data, and we prove how the use of an a priori model can improve the results. (author)

Operation room tool handling and miscommunication scenarios: an object-process methodology conceptual model.

Science.gov (United States)

Wachs, Juan P; Frenkel, Boaz; Dori, Dov

2014-11-01

Errors in the delivery of medical care are the principal cause of inpatient mortality and morbidity, accounting for around 98,000 deaths in the United States of America (USA) annually. Ineffective team communication, especially in the operation room (OR), is a major root of these errors. This miscommunication can be reduced by analyzing and constructing a conceptual model of communication and miscommunication in the OR. We introduce the principles underlying Object-Process Methodology (OPM)-based modeling of the intricate interactions between the surgeon and the surgical technician while handling surgical instruments in the OR. This model is a software- and hardware-independent description of the agents engaged in communication events, their physical activities, and their interactions. The model enables assessing whether the task-related objectives of the surgical procedure were achieved and completed successfully and what errors can occur during the communication. The facts used to construct the model were gathered from observations of various types of operations miscommunications in the operating room and its outcomes. The model takes advantage of the compact ontology of OPM, which is comprised of stateful objects - things that exist physically or informatically, and processes - things that transform objects by creating them, consuming them or changing their state. The modeled communication modalities are verbal and non-verbal, and errors are modeled as processes that deviate from the "sunny day" scenario. Using OPM refinement mechanism of in-zooming, key processes are drilled into and elaborated, along with the objects that are required as agents or instruments, or objects that these processes transform. The model was developed through an iterative process of observation, modeling, group discussions, and simplification. The model faithfully represents the processes related to tool handling that take place in an OR during an operation. The specification is at

Object Oriented Toolbox for Modelling and Simulation of Dynamical Systems

DEFF Research Database (Denmark)

Poulsen, Mikael Zebbelin; Wagner, Falko Jens; Thomsen, Per Grove

1998-01-01

This paper presents the results of an ongoing project, dealing with design and implementation of a simulation toolbox based on object oriented modelling techniques. The paper describes an experimental implementation of parts of such a toolbox in C++, and discusses the experiences drawn from that ...... that process. Essential to the work is the focus on simulation of complex dynamical systems, from modelling the single components/subsystems to building complete systemssuch a toolbox in C++, and discusses the experiences drawn from that process....

A fuzzy multi-objective optimization model for sustainable reverse logistics network design

DEFF Research Database (Denmark)

Govindan, Kannan; Paam, Parichehr; Abtahi, Amir Reza

2016-01-01

Decreasing the environmental impact, increasing the degree of social responsibility, and considering the economic motivations of organizations are three significant features in designing a reverse logistics network under sustainability respects. Developing a model, which can simultaneously consider...... a multi-echelon multi-period multi-objective model for a sustainable reverse logistics network. To reflect all aspects of sustainability, we try to minimize the present value of costs, as well as environmental impacts, and optimize the social responsibility as objective functions of the model. In order...... these environmental, social, and economic aspects and their indicators, is an important problem for both researchers and practitioners. In this paper, we try to address this comprehensive approach by using indicators for measurement of aforementioned aspects and by applying fuzzy mathematical programming to design...

Mathematical programming model for heat exchanger design through optimization of partial objectives

International Nuclear Information System (INIS)

Onishi, Viviani C.; Ravagnani, Mauro A.S.S.; Caballero, José A.

2013-01-01

Highlights: • Rigorous design of shell-and-tube heat exchangers according to TEMA standards. • Division of the problem into sets of equations that are easier to solve. • Selected heuristic objective functions based on the physical behavior of the problem. • Sequential optimization approach to avoid solutions stuck in local minimum. • The results obtained with this model improved the values reported in the literature. - Abstract: Mathematical programming can be used for the optimal design of shell-and-tube heat exchangers (STHEs). This paper proposes a mixed integer non-linear programming (MINLP) model for the design of STHEs, following rigorously the standards of the Tubular Exchanger Manufacturers Association (TEMA). Bell–Delaware Method is used for the shell-side calculations. This approach produces a large and non-convex model that cannot be solved to global optimality with the current state of the art solvers. Notwithstanding, it is proposed to perform a sequential optimization approach of partial objective targets through the division of the problem into sets of related equations that are easier to solve. For each one of these problems a heuristic objective function is selected based on the physical behavior of the problem. The global optimal solution of the original problem cannot be ensured even in the case in which each of the sub-problems is solved to global optimality, but at least a very good solution is always guaranteed. Three cases extracted from the literature were studied. The results showed that in all cases the values obtained using the proposed MINLP model containing multiple objective functions improved the values presented in the literature

Identification of a putative man-made object from an underwater crash site using CAD model superimposition.

Science.gov (United States)

Vincelli, Jay; Calakli, Fatih; Stone, Michael; Forrester, Graham; Mellon, Timothy; Jarrell, John

2018-04-01

In order to identify an object in video, a comparison with an exemplar object is typically needed. In this paper, we discuss the methodology used to identify an object detected in underwater video that was recorded during an investigation into Amelia Earhart's purported crash site. A computer aided design (CAD) model of the suspected aircraft component was created based on measurements made from orthogonally rectified images of a reference aircraft, and validated against historical photographs of the subject aircraft prior to the crash. The CAD model was then superimposed on the underwater video, and specific features on the object were geometrically compared between the CAD model and the video. This geometrical comparison was used to assess the goodness of fit between the purported object and the object identified in the underwater video. Copyright © 2018 Elsevier B.V. All rights reserved.

Invariant visual object and face recognition: neural and computational bases, and a model, VisNet

Directory of Open Access Journals (Sweden)

Edmund T eRolls

2012-06-01

Full Text Available Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy modelin which invariant representations can be built by self-organizing learning based on the temporal and spatialstatistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associativesynaptic learning rule with a short term memory trace, and/or it can use spatialcontinuity in Continuous Spatial Transformation learning which does not require a temporal trace. The model of visual processing in theventral cortical stream can build representations of objects that are invariant withrespect to translation, view, size, and also lighting. The modelhas been extended to provide an account of invariant representations in the dorsal visualsystem of the global motion produced by objects such as looming, rotation, and objectbased movement. The model has been extended to incorporate top-down feedback connectionsto model the control of attention by biased competition in for example spatial and objectsearch tasks. The model has also been extended to account for how the visual system canselect single objects in complex visual scenes, and how multiple objects can berepresented in a scene. The model has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus.

Space Object Radiometric Modeling for Hardbody Optical Signature Database Generation

Science.gov (United States)

2009-09-01

Introduction This presentation summarizes recent activity in monitoring spacecraft health status using passive remote optical nonimaging ...Approved for public release; distribution is unlimited. Space Object Radiometric Modeling for Hardbody Optical Signature Database Generation...It is beneficial to the observer/analyst to understand the fundamental optical signature variability associated with these detection and

Modeling guidance and recognition in categorical search: Bridging human and computer object detection

OpenAIRE

Zelinsky, Gregory J.; Peng, Yifan; Berg, Alexander C.; Samaras, Dimitris

2013-01-01

Search is commonly described as a repeating cycle of guidance to target-like objects, followed by the recognition of these objects as targets or distractors. Are these indeed separate processes using different visual features? We addressed this question by comparing observer behavior to that of support vector machine (SVM) models trained on guidance and recognition tasks. Observers searched for a categorically defined teddy bear target in four-object arrays. Target-absent trials consisted of ...

A User-Centric Knowledge Creation Model in a Web of Object-Enabled Internet of Things Environment

Science.gov (United States)

Kibria, Muhammad Golam; Fattah, Sheik Mohammad Mostakim; Jeong, Kwanghyeon; Chong, Ilyoung; Jeong, Youn-Kwae

2015-01-01

User-centric service features in a Web of Object-enabled Internet of Things environment can be provided by using a semantic ontology that classifies and integrates objects on the World Wide Web as well as shares and merges context-aware information and accumulated knowledge. The semantic ontology is applied on a Web of Object platform to virtualize the real world physical devices and information to form virtual objects that represent the features and capabilities of devices in the virtual world. Detailed information and functionalities of multiple virtual objects are combined with service rules to form composite virtual objects that offer context-aware knowledge-based services, where context awareness plays an important role in enabling automatic modification of the system to reconfigure the services based on the context. Converting the raw data into meaningful information and connecting the information to form the knowledge and storing and reusing the objects in the knowledge base can both be expressed by semantic ontology. In this paper, a knowledge creation model that synchronizes a service logistic model and a virtual world knowledge model on a Web of Object platform has been proposed. To realize the context-aware knowledge-based service creation and execution, a conceptual semantic ontology model has been developed and a prototype has been implemented for a use case scenario of emergency service. PMID:26393609

A User-Centric Knowledge Creation Model in a Web of Object-Enabled Internet of Things Environment

Directory of Open Access Journals (Sweden)

Muhammad Golam Kibria

2015-09-01

Full Text Available User-centric service features in a Web of Object-enabled Internet of Things environment can be provided by using a semantic ontology that classifies and integrates objects on the World Wide Web as well as shares and merges context-aware information and accumulated knowledge. The semantic ontology is applied on a Web of Object platform to virtualize the real world physical devices and information to form virtual objects that represent the features and capabilities of devices in the virtual world. Detailed information and functionalities of multiple virtual objects are combined with service rules to form composite virtual objects that offer context-aware knowledge-based services, where context awareness plays an important role in enabling automatic modification of the system to reconfigure the services based on the context. Converting the raw data into meaningful information and connecting the information to form the knowledge and storing and reusing the objects in the knowledge base can both be expressed by semantic ontology. In this paper, a knowledge creation model that synchronizes a service logistic model and a virtual world knowledge model on a Web of Object platform has been proposed. To realize the context-aware knowledge-based service creation and execution, a conceptual semantic ontology model has been developed and a prototype has been implemented for a use case scenario of emergency service.

A User-Centric Knowledge Creation Model in a Web of Object-Enabled Internet of Things Environment.

Science.gov (United States)

Kibria, Muhammad Golam; Fattah, Sheik Mohammad Mostakim; Jeong, Kwanghyeon; Chong, Ilyoung; Jeong, Youn-Kwae

2015-09-18

User-centric service features in a Web of Object-enabled Internet of Things environment can be provided by using a semantic ontology that classifies and integrates objects on the World Wide Web as well as shares and merges context-aware information and accumulated knowledge. The semantic ontology is applied on a Web of Object platform to virtualize the real world physical devices and information to form virtual objects that represent the features and capabilities of devices in the virtual world. Detailed information and functionalities of multiple virtual objects are combined with service rules to form composite virtual objects that offer context-aware knowledge-based services, where context awareness plays an important role in enabling automatic modification of the system to reconfigure the services based on the context. Converting the raw data into meaningful information and connecting the information to form the knowledge and storing and reusing the objects in the knowledge base can both be expressed by semantic ontology. In this paper, a knowledge creation model that synchronizes a service logistic model and a virtual world knowledge model on a Web of Object platform has been proposed. To realize the context-aware knowledge-based service creation and execution, a conceptual semantic ontology model has been developed and a prototype has been implemented for a use case scenario of emergency service.

Appropriate Objective Functions for Quantifying Iris Mechanical Properties Using Inverse Finite Element Modeling.

Science.gov (United States)

Pant, Anup D; Dorairaj, Syril K; Amini, Rouzbeh

2018-07-01

Quantifying the mechanical properties of the iris is important, as it provides insight into the pathophysiology of glaucoma. Recent ex vivo studies have shown that the mechanical properties of the iris are different in glaucomatous eyes as compared to normal ones. Notwithstanding the importance of the ex vivo studies, such measurements are severely limited for diagnosis and preclude development of treatment strategies. With the advent of detailed imaging modalities, it is possible to determine the in vivo mechanical properties using inverse finite element (FE) modeling. An inverse modeling approach requires an appropriate objective function for reliable estimation of parameters. In the case of the iris, numerous measurements such as iris chord length (CL) and iris concavity (CV) are made routinely in clinical practice. In this study, we have evaluated five different objective functions chosen based on the iris biometrics (in the presence and absence of clinical measurement errors) to determine the appropriate criterion for inverse modeling. Our results showed that in the absence of experimental measurement error, a combination of iris CL and CV can be used as the objective function. However, with the addition of measurement errors, the objective functions that employ a large number of local displacement values provide more reliable outcomes.

Ownership transfer for non-federate object and time management in developing an hla compliant logistics model.

Energy Technology Data Exchange (ETDEWEB)

Li, Z.

1998-01-12

A seaport simulation model, PORTSIM, has been developed for the Department of Defense (DOD) at Argonne National Laboratory. PORTSIM simulates the detailed processes of cargo loading and unloading in a seaport and provides throughput capability, resource utilization, and other important information on the bottlenecks in a seaport operation, which are crucial data in determining troop and equipment deployment capability. There are two key problems to solve in developing the HLA-compliant PORTSIM model. The first is the cargo object ownership transfer problem. In PORTSIM, cargo items, e.g. vehicles, containers, and pallets, are objects having asset attributes. Cargo comes to a seaport for loading or unloading. The ownership of a cargo object transfers from its carrier to the port and then from the port to a new carrier. Each owner of the cargo object is responsible for publishing and updating the attributes of the cargo object when it has the ownership. This creates a unique situation in developing the PORTSIM federate object model, that is, the ownership of the object instead of the attributes needs to be changed in handling the cargo object in the PORTSIM federate. The ownership management service provided by the current RTI does not directly address this issue. The second is the time management issue. PORTSIM is an event-driven simulation that models seaport operations over time. To make PORTSIM HLA compliant, time management must be addressed to allow for synchronization with other simulation models. This paper attempts to address these two issues and methodologies developed for solving these two problems.

Neuronal encoding of object and distance information: A model simulation study on naturalistic optic flow processing

Directory of Open Access Journals (Sweden)

Patrick eHennig

2012-03-01

Full Text Available We developed a model of the input circuitry of the FD1 cell, an identified motion-sensitive interneuron in the blowfly’s visual system. The model circuit successfully reproduces the FD1 cell’s most conspicuous property: Its larger responses to objects than to spatially extended patterns. The model circuit also mimics the time-dependent responses of FD1 to dynamically complex naturalistic stimuli, shaped by the blowfly’s saccadic flight and gaze strategy: The FD1 responses are enhanced when, as a consequence of self-motion, a nearby object crosses the receptive field during intersaccadic intervals. Moreover, the model predicts that these object-induced responses are superimposed by pronounced pattern-dependent fluctuations during movements on virtual test flights in a three-dimensional environment with systematic modifications of the environmental patterns. Hence, the FD1 cell is predicted to detect not unambiguously objects defined by the spatial layout of the environment, but to be also sensitive to objects distinguished by textural features. These ambiguous detection abilities suggest an encoding of information about objects - irrespective of the features by which the objects are defined - by a population of cells, with the FD1 cell presumably playing a prominent role in such an ensemble.

Mathematical model of innovative sustainability “green” construction object

Directory of Open Access Journals (Sweden)

Slesarev Michail

2016-01-01

Full Text Available The paper addresses the issue of finding sustainability of “green” innovative processes in interaction between construction activities and the environment. The problem of today’s construction science is stated as comprehensive integration and automation of natural and artificial intellects within systems that ensure environmental safety of construction based on innovative sustainability of “green” technologies in the life environment, and “green” innovative products. The suggested solution to the problem should formalize sustainability models and methods for interpretation of optimization mathematical modeling problems respective to problems of environmental-based innovative process management, adapted to construction of “green” objects, “green” construction technologies, “green” innovative materials and structures.

Piles of objects

KAUST Repository

Hsu, Shu-Wei

2010-01-01

We present a method for directly modeling piles of objects in multi-body simulations. Piles of objects represent some of the more interesting, but also most time-consuming portion of simulation. We propose a method for reducing computation in many of these situations by explicitly modeling the piles that the objects may form into. By modeling pile behavior rather than the behavior of all individual objects, we can achieve realistic results in less time, and without directly modeling the frictional component that leads to desired pile shapes. Our method is simple to implement and can be easily integrated with existing rigid body simulations. We observe notable speedups in several rigid body examples, and generate a wider variety of piled structures than possible with strict impulse-based simulation. © 2010 ACM.

Wonderful Things? A Consideration of 3D Modelling of Objects in Material Culture Research

Directory of Open Access Journals (Sweden)

Molloy Barry

2018-04-01

Full Text Available The role of 3D modelling in archaeology is increasing exponentially, from fieldwork to architecture to material culture studies. For the study of archaeological objects the roles of digital and print models for public engagement has been much considered in recent literature. For model makers, focus has typically been placed on exceptional and visually striking objects with inherent appeal. In contrast, this paper explores some of the potential roles for 3D digital models for routine artefact research and publication. Particular emphasis is placed on the challenges this technology raises for archaeological theory and practice. Following a consideration of how 3D models relate to established illustration and photographic traditions, the paper evaluates some of the unique features of 3D models, focussing on both positive and negative aspects of these. This is followed by a discussion of the role of potential research connections between digital and craft models in experimental research. Our overall objective is to emphasise a need to engage with the ways in which this gradual development has begun to change aspects of longestablished workflows. In turn, the increasing use of this technology is argued to have wider ramifications for the development of archaeology, and material culture studies in particular, as a discipline that requires reflection.

Multi-Objective Optimization of the Hedging Model for reservoir Operation Using Evolutionary Algorithms

Directory of Open Access Journals (Sweden)

sadegh sadeghitabas

2015-12-01

Full Text Available Multi-objective problems rarely ever provide a single optimal solution, rather they yield an optimal set of outputs (Pareto fronts. Solving these problems was previously accomplished by using some simplifier methods such as the weighting coefficient method used for converting a multi-objective problem to a single objective function. However, such robust tools as multi-objective meta-heuristic algorithms have been recently developed for solving these problems. The hedging model is one of the classic problems for reservoir operation that is generally employed for mitigating drought impacts in water resources management. According to this method, although it is possible to supply the total planned demands, only portions of the demands are met to save water by allowing small deficits in the current conditions in order to avoid or reduce severe deficits in future. The approach heavily depends on economic and social considerations. In the present study, the meta-heuristic algorithms of NSGA-II, MOPSO, SPEA-II, and AMALGAM are used toward the multi-objective optimization of the hedging model. For this purpose, the rationing factors involved in Taleghan dam operation are optimized over a 35-year statistical period of inflow. There are two objective functions: a minimizing the modified shortage index, and b maximizing the reliability index (i.e., two opposite objectives. The results show that the above algorithms are applicable to a wide range of optimal solutions. Among the algorithms, AMALGAM is found to produce a better Pareto front for the values of the objective function, indicating its more satisfactory performance.

SED Modeling of 20 Massive Young Stellar Objects

Science.gov (United States)

Tanti, Kamal Kumar

In this paper, we present the spectral energy distributions (SEDs) modeling of twenty massive young stellar objects (MYSOs) and subsequently estimated different physical and structural/geometrical parameters for each of the twenty central YSO outflow candidates, along with their associated circumstellar disks and infalling envelopes. The SEDs for each of the MYSOs been reconstructed by using 2MASS, MSX, IRAS, IRAC & MIPS, SCUBA, WISE, SPIRE and IRAM data, with the help of a SED Fitting Tool, that uses a grid of 2D radiative transfer models. Using the detailed analysis of SEDs and subsequent estimation of physical and geometrical parameters for the central YSO sources along with its circumstellar disks and envelopes, the cumulative distribution of the stellar, disk and envelope parameters can be analyzed. This leads to a better understanding of massive star formation processes in their respective star forming regions in different molecular clouds.

Quantum superposition of massive objects and collapse models

International Nuclear Information System (INIS)

Romero-Isart, Oriol

2011-01-01

We analyze the requirements to test some of the most paradigmatic collapse models with a protocol that prepares quantum superpositions of massive objects. This consists of coherently expanding the wave function of a ground-state-cooled mechanical resonator, performing a squared position measurement that acts as a double slit, and observing interference after further evolution. The analysis is performed in a general framework and takes into account only unavoidable sources of decoherence: blackbody radiation and scattering of environmental particles. We also discuss the limitations imposed by the experimental implementation of this protocol using cavity quantum optomechanics with levitating dielectric nanospheres.

Quantum superposition of massive objects and collapse models

Energy Technology Data Exchange (ETDEWEB)

Romero-Isart, Oriol [Max-Planck-Institut fuer Quantenoptik, Hans-Kopfermann-Str. 1, D-85748 Garching (Germany)

2011-11-15

We analyze the requirements to test some of the most paradigmatic collapse models with a protocol that prepares quantum superpositions of massive objects. This consists of coherently expanding the wave function of a ground-state-cooled mechanical resonator, performing a squared position measurement that acts as a double slit, and observing interference after further evolution. The analysis is performed in a general framework and takes into account only unavoidable sources of decoherence: blackbody radiation and scattering of environmental particles. We also discuss the limitations imposed by the experimental implementation of this protocol using cavity quantum optomechanics with levitating dielectric nanospheres.

Towards a Unified Theory of Health-Disease: I. Health as a complex model-object

Directory of Open Access Journals (Sweden)

Naomar Almeida-Filho

2013-06-01

Full Text Available Theory building is one of the most crucial challenges faced by basic, clinical and population research, which form the scientific foundations of health practices in contemporary societies. The objective of the study is to propose a Unified Theory of Health-Disease as a conceptual tool for modeling health-disease-care in the light of complexity approaches. With this aim, the epistemological basis of theoretical work in the health field and concepts related to complexity theory as concerned to health problems are discussed. Secondly, the concepts of model-object, multi-planes of occurrence, modes of health and disease-illness-sickness complex are introduced and integrated into a unified theoretical framework. Finally, in the light of recent epistemological developments, the concept of Health-Disease-Care Integrals is updated as a complex reference object fit for modeling health-related processes and phenomena.

A foreground object features-based stereoscopic image visual comfort assessment model

Science.gov (United States)

Jin, Xin; Jiang, G.; Ying, H.; Yu, M.; Ding, S.; Peng, Z.; Shao, F.

2014-11-01

Since stereoscopic images provide observers with both realistic and discomfort viewing experience, it is necessary to investigate the determinants of visual discomfort. By considering that foreground object draws most attention when human observing stereoscopic images. This paper proposes a new foreground object based visual comfort assessment (VCA) metric. In the first place, a suitable segmentation method is applied to disparity map and then the foreground object is ascertained as the one having the biggest average disparity. In the second place, three visual features being average disparity, average width and spatial complexity of foreground object are computed from the perspective of visual attention. Nevertheless, object's width and complexity do not consistently influence the perception of visual comfort in comparison with disparity. In accordance with this psychological phenomenon, we divide the whole images into four categories on the basis of different disparity and width, and exert four different models to more precisely predict its visual comfort in the third place. Experimental results show that the proposed VCA metric outperformance other existing metrics and can achieve a high consistency between objective and subjective visual comfort scores. The Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) are over 0.84 and 0.82, respectively.

An Object-Oriented Python Implementation of an Intermediate-Level Atmospheric Model

Science.gov (United States)

Lin, J. W.

2008-12-01

The Neelin-Zeng Quasi-equilibrium Tropical Circulation Model (QTCM1) is a Fortran-based intermediate-level atmospheric model that includes simplified treatments of several physical processes, including a GCM-like convective scheme and a land-surface scheme with representations of different surface types, evaporation, and soil moisture. This model has been used in studies of the Madden-Julian oscillation, ENSO, and vegetation-atmosphere interaction effects on climate. Through the assumption of convective quasi-equilibrium in the troposphere, the QTCM1 is able to include full nonlinearity, resolve baroclinic disturbances, and generate a reasonable climatology, all at low computational cost. One year of simulation on a PC at 5.625 × 3.75 degree longitude-latitude resolution takes under three minutes of wall-clock time. The Python package qtcm implements the QTCM1 in a mixed-language environment that retains the speed of compiled Fortran while providing the benefits of Python's object-oriented framework and robust suite of utilities and datatypes. We describe key programming constructs used to create this modeling environment: the decomposition of model runs into Python objects, providing methods so visualization tools are attached to model runs, and the use of Python's mutable datatypes (lists and dictionaries) to implement the "run list" entity, which enables total runtime control of subroutine execution order and content. The result is an interactive modeling environment where the traditional sequence of "hypothesis → modeling → visualization and analysis" is opened up and made nonlinear and flexible. In this environment, science tasks such as parameter-space exploration and testing alternative parameterizations can be easily automated, without the need for multiple versions of the model code interacting with a bevy of makefiles and shell scripts. The environment also simplifies interfacing of the atmospheric model to other models (e.g., hydrologic models

Computation of spatial significance of mountain objects extracted from multiscale digital elevation models

International Nuclear Information System (INIS)

Sathyamoorthy, Dinesh

2014-01-01

The derivation of spatial significance is an important aspect of geospatial analysis and hence, various methods have been proposed to compute the spatial significance of entities based on spatial distances with other entities within the cluster. This paper is aimed at studying the spatial significance of mountain objects extracted from multiscale digital elevation models (DEMs). At each scale, the value of spatial significance index SSI of a mountain object is the minimum number of morphological dilation iterations required to occupy all the other mountain objects in the terrain. The mountain object with the lowest value of SSI is the spatially most significant mountain object, indicating that it has the shortest distance to the other mountain objects. It is observed that as the area of the mountain objects reduce with increasing scale, the distances between the mountain objects increase, resulting in increasing values of SSI. The results obtained indicate that the strategic location of a mountain object at the centre of the terrain is more important than its size in determining its reach to other mountain objects and thus, its spatial significance

Neo: an object model for handling electrophysiology data in multiple formats

Directory of Open Access Journals (Sweden)

Samuel eGarcia

2014-02-01

Full Text Available Neuroscientists use many different software tools to acquire, analyse and visualise electrophysiological signals. However, incompatible data models and file formats make it difficult to exchange data between these tools. This reduces scientific productivity, renders potentially useful analysis methods inaccessible and impedes collaboration between labs.A common representation of the core data would improve interoperability and facilitate data-sharing.To that end, we propose here a language-independent object model, named Neo, suitable for representing data acquired from electroencephalographic, intracellular, or extracellular recordings, or generated from simulations. As a concrete instantiation of this object model we have developed an open source implementation in the Python programming language.In addition to representing electrophysiology data in memory for the purposes of analysis and visualisation, the Python implementation provides a set of input/output (IO modules for reading/writing the data from/to a variety of commonly used file formats.Support is included for formats produced by most of the major manufacturers of electrophysiology recording equipment and also for more generic formats such as MATLAB.Data representation and data analysis are conceptually separate: it is easier to write robust analysis code if it is focused on analysis and relies on an underlying package to handle data representation.For that reason, and also to be as lightweight as possible, the Neo object model and the associated Python package are deliberately limited to representation of data, with no functions for data analysis or visualisation.Software for neurophysiology data analysis and visualisation built on top of Neo automatically gains the benefits of interoperability, easier data sharing and automatic format conversion; there is already a burgeoning ecosystem of such tools. We intend that Neo should become the standard basis for Python tools in

Downscaling, 2-way Nesting, and Data Assimilative Modeling in Coastal and Shelf Waters of the U.S. Mid-Atlantic Bight and Gulf of Maine

Science.gov (United States)

Wilkin, J.; Levin, J.; Lopez, A.; Arango, H.

2016-02-01

Coastal ocean models that downscale output from basin and global scale models are widely used to study regional circulation at enhanced resolution and locally important ecosystem, biogeochemical, and geomorphologic processes. When operated as now-cast or forecast systems, these models offer predictions that assist decision-making for numerous maritime applications. We describe such a system for shelf waters of the Mid-Atlantic Bight (MAB) and Gulf of Maine (GoM) where the MARACOOS and NERACOOS associations of U.S. IOOS operate coastal ocean observing systems that deliver a dense observation set using CODAR HF-radar, autonomous underwater glider vehicles (AUGV), telemetering moorings, and drifting buoys. Other U.S. national and global observing systems deliver further sustained observations from moorings, ships, profiling floats, and a constellation of satellites. Our MAB and GoM re-analysis and forecast system uses the Regional Ocean Modeling System (ROMS; myroms.org) with 4-dimensional Variational (4D-Var) data assimilation to adjust initial conditions, boundary conditions, and surface forcing in each analysis cycle. Data routinely assimilated include CODAR velocities, altimeter satellite sea surface height (with coastal corrections), satellite temperature, in situ CTD data from AUGV and ships (NMFS Ecosystem Monitoring voyages), and all in situ data reported via the WMO GTS network. A climatological data assimilative analysis of hydrographic and long-term mean velocity observations specifies the regional Mean Dynamic Topography that augments altimeter sea level anomaly data and is also used to adjust boundary condition biases that would otherwise be introduced in the process of downscaling from global models. System performance is described with respect to the impact of satellite, CODAR and in situ observations on analysis skill. Results from a 2-way nested modeling system that adds enhanced resolution over the NSF OOI Pioneer Array in the central MAB are also

Objective Characterization of Snow Microstructure for Microwave Emission Modeling

Science.gov (United States)

Durand, Michael; Kim, Edward J.; Molotch, Noah P.; Margulis, Steven A.; Courville, Zoe; Malzler, Christian

2012-01-01

Passive microwave (PM) measurements are sensitive to the presence and quantity of snow, a fact that has long been used to monitor snowcover from space. In order to estimate total snow water equivalent (SWE) within PM footprints (on the order of approx 100 sq km), it is prerequisite to understand snow microwave emission at the point scale and how microwave radiation integrates spatially; the former is the topic of this paper. Snow microstructure is one of the fundamental controls on the propagation of microwave radiation through snow. Our goal in this study is to evaluate the prospects for driving the Microwave Emission Model of Layered Snowpacks with objective measurements of snow specific surface area to reproduce measured brightness temperatures when forced with objective measurements of snow specific surface area (S). This eliminates the need to treat the grain size as a free-fit parameter.

A MITgcm/DART ensemble analysis and prediction system with application to the Gulf of Mexico

KAUST Repository

Hoteit, Ibrahim

2013-09-01

This paper describes the development of an advanced ensemble Kalman filter (EnKF)-based ocean data assimilation system for prediction of the evolution of the loop current in the Gulf of Mexico (GoM). The system integrates the Data Assimilation Research Testbed (DART) assimilation package with the Massachusetts Institute of Technology ocean general circulation model (MITgcm). The MITgcm/DART system supports the assimilation of a wide range of ocean observations and uses an ensemble approach to solve the nonlinear assimilation problems. The GoM prediction system was implemented with an eddy-resolving 1/10th degree configuration of the MITgcm. Assimilation experiments were performed over a 6-month period between May and October during a strong loop current event in 1999. The model was sequentially constrained with weekly satellite sea surface temperature and altimetry data. Experiments results suggest that the ensemble-based assimilation system shows a high predictive skill in the GoM, with estimated ensemble spread mainly concentrated around the front of the loop current. Further analysis of the system estimates demonstrates that the ensemble assimilation accurately reproduces the observed features without imposing any negative impact on the dynamical balance of the system. Results from sensitivity experiments with respect to the ensemble filter parameters are also presented and discussed. © 2013 Elsevier B.V.

Minimal Camera Networks for 3D Image Based Modeling of Cultural Heritage Objects

Science.gov (United States)

Alsadik, Bashar; Gerke, Markus; Vosselman, George; Daham, Afrah; Jasim, Luma

2014-01-01

3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue “Lamassu”. Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883–859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm. PMID:24670718

Minimal camera networks for 3D image based modeling of cultural heritage objects.

Science.gov (United States)

Alsadik, Bashar; Gerke, Markus; Vosselman, George; Daham, Afrah; Jasim, Luma

2014-03-25

3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue "Lamassu". Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883-859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm.

Offshore Pipeline Locations in the Gulf of Mexico, Geographic NAD27, MMS (2007) [pipelines_vectors_mms_2007

Data.gov (United States)

Louisiana Geographic Information Center — Offshore Minerals Management Pipeline Locations for the Gulf of Mexico (GOM). Contains the lines of the pipeline in the GOM. All pipelines existing in the databases...

Offshore Pipeline Locations in the Gulf of Mexico, Geographic NAD27, MMS (2007) [pipelines_points_mms_2007

Data.gov (United States)

Louisiana Geographic Information Center — Offshore Minerals Management Pipeline Locations for the Gulf of Mexico (GOM). Contains the points of the pipeline in the GOM. All pipelines existing in the databases...

Nonlinear bioheat transfer models and multi-objective numerical optimization of the cryosurgery operations

Energy Technology Data Exchange (ETDEWEB)

Kudryashov, Nikolay A.; Shilnikov, Kirill E. [National Research Nuclear University MEPhI, Department of Applied Mathematics, Moscow (Russian Federation)

2016-06-08

Numerical computation of the three dimensional problem of the freezing interface propagation during the cryosurgery coupled with the multi-objective optimization methods is used in order to improve the efficiency and safety of the cryosurgery operations performing. Prostate cancer treatment and cutaneous cryosurgery are considered. The heat transfer in soft tissue during the thermal exposure to low temperature is described by the Pennes bioheat model and is coupled with an enthalpy method for blurred phase change computations. The finite volume method combined with the control volume approximation of the heat fluxes is applied for the cryosurgery numerical modeling on the tumor tissue of a quite arbitrary shape. The flux relaxation approach is used for the stability improvement of the explicit finite difference schemes. The method of the additional heating elements mounting is studied as an approach to control the cellular necrosis front propagation. Whereas the undestucted tumor tissue and destucted healthy tissue volumes are considered as objective functions, the locations of additional heating elements in cutaneous cryosurgery and cryotips in prostate cancer cryotreatment are considered as objective variables in multi-objective problem. The quasi-gradient method is proposed for the searching of the Pareto front segments as the multi-objective optimization problem solutions.

Catchment variability and parameter estimation in multi-objective regionalisation of a rainfall-runoff model

NARCIS (Netherlands)

Deckers, Dave L.E.H.; Booij, Martijn J.; Rientjes, T.H.M.; Krol, Martinus S.

2010-01-01

This study attempts to examine if catchment variability favours regionalisation by principles of catchment similarity. Our work combines calibration of a simple conceptual model for multiple objectives and multi-regression analyses to establish a regional model between model sensitive parameters and

Complexity analysis of dual-channel game model with different managers' business objectives

Science.gov (United States)

Li, Ting; Ma, Junhai

2015-01-01

This paper considers dual-channel game model with bounded rationality, using the theory of bifurcations of dynamical system. The business objectives of retailers are assumed to be different, which is closer to reality than previous studies. We study the local stable region of Nash equilibrium point and find that business objectives can expand the stable region and play an important role in price strategy. One interesting finding is that a fiercer competition tends to stabilize the Nash equilibrium. Simulation shows the complex behavior of two dimensional dynamic system, we find period doubling bifurcation and chaos phenomenon. We measure performances of the model in different period by using the index of average profit. The results show that unstable behavior in economic system is often an unfavorable outcome. So this paper discusses the application of adaptive adjustment mechanism when the model exhibits chaotic behavior and then allows the retailers to eliminate the negative effects.

The application of the unified modeling language in object-oriented analysis of healthcare information systems.

Science.gov (United States)

Aggarwal, Vinod

2002-10-01

This paper concerns itself with the beneficial effects of the Unified Modeling Language (UML), a nonproprietary object modeling standard, in specifying, visualizing, constructing, documenting, and communicating the model of a healthcare information system from the user's perspective. The author outlines the process of object-oriented analysis (OOA) using the UML and illustrates this with healthcare examples to demonstrate the practicality of application of the UML by healthcare personnel to real-world information system problems. The UML will accelerate advanced uses of object-orientation such as reuse technology, resulting in significantly higher software productivity. The UML is also applicable in the context of a component paradigm that promises to enhance the capabilities of healthcare information systems and simplify their management and maintenance.

Modelling with Relational Calculus of Object and Component Systems - rCOS

DEFF Research Database (Denmark)

Chen, Zhenbang; Hannousse, Abdel Hakim; Hung, Dang Van

2008-01-01

This chapter presents a formalization of functional and behavioural requirements, and a refinement of requirements to a design for CoCoME using the Relational Calculus of Object and Component Systems (rCOS). We give a model of requirements based on an abstraction of the use cases described...... in Chapter 3.2. Then the refinement calculus of rCOS is used to derive design models corresponding to the top level designs of Chapter 3.4. We demonstrate how rCOS supports modelling different views and their relationships of the system and the separation of concerns in the development....

GOSAILT: A hybrid of GOMS and SAILT with topography consideration

Science.gov (United States)

Wu, S.; Wen, J.

2017-12-01

Heterogeneous terrain significantly complicated the energy, mass and momentum exchange between the atmosphere and terrestrial ecosystem. Understanding of topographic effect on the forest reflectance is critical for biophysical parameters retrieval over rugged area. In this paper, a new hybrid bidirectional reflectance distribution function (BRDF) model of geometric optical mutual shadowing and scattering-from-arbitrarily-inclined-leaves model coupled topography (GOSAILT) for sloping forest was proposed. The effects of slope, aspect, gravity field of tree crown, multiple scattering scheme, and diffuse skylight are considered. The area proportions of scene components estimated by the GOSAILT model were compared with the geometric optical model for sloping terrains (GOST) model. The 3-D discrete anisotropic radiative transfer (DART) simulations were used to evaluate the performance of GOSAILT. The results indicate that the canopy reflectance is distorted by the slopes with a maximum variation of 78.3% in the red band and 17.3% in the NIR band on a steep 60 º slope. Compared with the DART simulations, the proposed GOSAILT model can capture anisotropic reflectance well with a determine coefficient (R2) of 0.9720 and 0.6701, root-mean-square error (RMSE) of 0.0024 and 0.0393, mean absolute percentage error of 2.4% and 4.61% for the red and near-infrared (NIR) band. The comparison results indicate the GOSAIL model can accurately reproducing the angular feature of discrete canopy over rugged terrain conditions. The GOSAILT model is promising for the land surface biophysical parameters retrieval (e.g. albedo, leaf area index) over the heterogeneous terrain.

Deep Convolutional Neural Networks Outperform Feature-Based But Not Categorical Models in Explaining Object Similarity Judgments

Science.gov (United States)

Jozwik, Kamila M.; Kriegeskorte, Nikolaus; Storrs, Katherine R.; Mur, Marieke

2017-01-01

Recent advances in Deep convolutional Neural Networks (DNNs) have enabled unprecedentedly accurate computational models of brain representations, and present an exciting opportunity to model diverse cognitive functions. State-of-the-art DNNs achieve human-level performance on object categorisation, but it is unclear how well they capture human behavior on complex cognitive tasks. Recent reports suggest that DNNs can explain significant variance in one such task, judging object similarity. Here, we extend these findings by replicating them for a rich set of object images, comparing performance across layers within two DNNs of different depths, and examining how the DNNs’ performance compares to that of non-computational “conceptual” models. Human observers performed similarity judgments for a set of 92 images of real-world objects. Representations of the same images were obtained in each of the layers of two DNNs of different depths (8-layer AlexNet and 16-layer VGG-16). To create conceptual models, other human observers generated visual-feature labels (e.g., “eye”) and category labels (e.g., “animal”) for the same image set. Feature labels were divided into parts, colors, textures and contours, while category labels were divided into subordinate, basic, and superordinate categories. We fitted models derived from the features, categories, and from each layer of each DNN to the similarity judgments, using representational similarity analysis to evaluate model performance. In both DNNs, similarity within the last layer explains most of the explainable variance in human similarity judgments. The last layer outperforms almost all feature-based models. Late and mid-level layers outperform some but not all feature-based models. Importantly, categorical models predict similarity judgments significantly better than any DNN layer. Our results provide further evidence for commonalities between DNNs and brain representations. Models derived from visual features

A new multi objective optimization model for designing a green supply chain network under uncertainty

Directory of Open Access Journals (Sweden)

Mohammad Mahdi Saffar

2015-01-01

Full Text Available Recently, researchers have focused on how to minimize the negative effects of industrial activities on environment. Consequently, they work on mathematical models, which minimize the environmental issues as well as optimizing the costs. In the field of supply chain network design, most managers consider economic and environmental issues, simultaneously. This paper introduces a bi-objective supply chain network design, which uses fuzzy programming to obtain the capability of resisting uncertain conditions. The design considers production, recovery, and distribution centers. The advantage of using this model includes the optimal facilities, locating them and assigning the optimal facilities to them. It also chooses the type and the number of technologies, which must be bought. The fuzzy programming converts the multi objective model to an auxiliary crisp model by Jimenez approach and solves it with ε-constraint. For solving large size problems, the Multi Objective Differential Evolutionary algorithm (MODE is applied.

Preparation of graphene oxide-manganese dioxide for highly efficient adsorption and separation of Th(IV)/U(VI).

Science.gov (United States)

Pan, Ning; Li, Long; Ding, Jie; Li, Shengke; Wang, Ruibing; Jin, Yongdong; Wang, Xiangke; Xia, Chuanqin

2016-05-15

Manganese dioxide decorated graphene oxide (GOM) was prepared via fixation of crystallographic MnO2 (α, γ) on the surface of graphene oxide (GO) and was explored as an adsorbent material for simultaneous removal of thorium/uranium ions from aqueous solutions. In single component systems (Th(IV) or U(VI)), the α-GOM2 (the weight ratio of GO/α-MnO2 of 2) exhibited higher maximum adsorption capacities toward both Th(IV) (497.5mg/g) and U(VI) (185.2 mg/g) than those of GO. In the binary component system (Th(IV)/U(VI)), the saturated adsorption capacity of Th(IV) (408.8 mg/g)/U(VI) (66.8 mg/g) on α-GOM2 was also higher than those on GO. Based on the analysis of various data, it was proposed that the adsorption process may involve four types of molecular interactions including coordination, electrostatic interaction, cation-pi interaction, and Lewis acid-base interaction between Th(IV)/U(VI) and α-GOM2. Finally, the Th(IV)/U(VI) ions on α-GOM2 can be separated by a two-stage desorption process with Na2CO3/EDTA. Those results displayed that the α-GOM2 may be utilized as an potential adsorbent for removing and separating Th(IV)/U(VI) ions from aqueous solutions. Copyright © 2016 Elsevier B.V. All rights reserved.

GOOSE Version 1.4: A powerful object-oriented simulation environment for developing reactor models

International Nuclear Information System (INIS)

Nypaver, D.J.; March-Leuba, C.; Abdalla, M.A.; Guimaraes, L.

1992-01-01

A prototype software package for a fully interactive Generalized Object-Oriented Simulation Environment (GOOSE) is being developed at Oak Ridge National Laboratory. Dynamic models are easily constructed and tested; fully interactive capabilities allow the user to alter model parameters and complexity without recompilation. This environment provides assess to powerful tools such as numerical integration packages, graphical displays, and online help. In GOOSE, portability has been achieved by creating the environment in Objective-C 1 , which is supported by a variety of platforms including UNIX and DOS. GOOSE Version 1.4 introduces new enhancements like the capability of creating ''initial,'' ''dynamic,'' and ''digital'' methods. The object-oriented approach to simulation used in GOOSE combines the concept of modularity with the additional features of allowing precompilation, optimization, testing, and validation of individual modules. Once a library of classes has been defined and compiled, models can be built and modified without recompilation. GOOSE Version 1.4 is primarily command-line driven

Objective Tuning of Model Parameters in CAM5 Across Different Spatial Resolutions

Science.gov (United States)

Bulaevskaya, V.; Lucas, D. D.

2014-12-01

Parameterizations of physical processes in climate models are highly dependent on the spatial and temporal resolution and must be tuned for each resolution under consideration. At high spatial resolutions, objective methods for parameter tuning are computationally prohibitive. Our work has focused on calibrating parameters in the Community Atmosphere Model 5 (CAM5) for three spatial resolutions: 1, 2, and 4 degrees. Using perturbed-parameter ensembles and uncertainty quantification methodology, we have identified input parameters that minimize discrepancies of energy fluxes simulated by CAM5 across the three resolutions and with respect to satellite observations. We are also beginning to exploit the parameter-resolution relationships to objectively tune parameters in a high-resolution version of CAM5 by leveraging cheaper, low-resolution simulations and statistical models. We will present our approach to multi-resolution climate model parameter tuning, as well as the key findings. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344 and was supported from the DOE Office of Science through the Scientific Discovery Through Advanced Computing (SciDAC) project on Multiscale Methods for Accurate, Efficient, and Scale-Aware Models of the Earth System.

A Mixed Land Cover Spatio-temporal Data Model Based on Object-oriented and Snapshot

Directory of Open Access Journals (Sweden)

LI Yinchao

2016-07-01

Full Text Available Spatio-temporal data model (STDM is one of the hot topics in the domains of spatio-temporal database and data analysis. There is a common view that a universal STDM is always of high complexity due to the various situation of spatio-temporal data. In this article, a mixed STDM is proposed based on object-oriented and snapshot models for modelling and analyzing landcover change (LCC. This model uses the object-oriented STDM to describe the spatio-temporal processes of land cover patches and organize their spatial and attributive properties. In the meantime, it uses the snapshot STDM to present the spatio-temporal distribution of LCC on the whole via snapshot images. The two types of models are spatially and temporally combined into a mixed version. In addition to presenting the spatio-temporal events themselves, this model could express the transformation events between different classes of spatio-temporal objects. It can be used to create database for historical data of LCC, do spatio-temporal statistics, simulation and data mining with the data. In this article, the LCC data in Heilongjiang province is used for case study to validate spatio-temporal data management and analysis abilities of mixed STDM, including creating database, spatio-temporal query, global evolution analysis and patches spatio-temporal process expression.

Reprint of - Deep-sea coral and hardbottom habitats on the west Florida slope, eastern Gulf of Mexico

Science.gov (United States)

Ross, Steve W.; Rhode, Mike; Brooke, Sandra

2017-09-01

Until recently, benthic habitats dominated by deep-sea corals (DSC) appeared to be less extensive on the slope of the Gulf of Mexico (GOM) than in the northeast Atlantic Ocean or off the southeastern US. There are relatively few bioherms (i.e., coral-built mounds) in the northern GOM, and most DSCs are attached to existing hard substrata (e.g., authigenically formed carbonate). The primary structure-forming, DSC in the GOM is Lophelia pertusa, but structure is also provided by other living and dead scleractinians, antipatharians (black corals), octocorals (gorgonians, soft corals), hydrocorals and sponges, as well as abundant rocky substrata. The best development of DSCs in the GOM was previously documented within Viosca Knoll oil and gas lease blocks 826 and 862/906 (north-central GOM) and on the Campeche Bank (southern GOM in Mexican waters). This paper documents extensive deep reef ecosystems composed of DSC and rocky hard-bottom recently surveyed on the West Florida Slope (WFS, eastern GOM) during six research cruises (2008-2012). Using multibeam sonar, CTD casts, and video from underwater vehicles, we describe the physical and oceanographic characteristics of these deep reefs and provide size or area estimates of deep coral and hardground habitats. The multibeam sonar analyses revealed hundreds of mounds and ridges, some of which were subsequently surveyed using underwater vehicles. Mounds and ridges in <525 m depths were usually capped with living coral colonies, dominated by L. pertusa. An extensive rocky scarp, running roughly north-south for at least 229 km, supported lower abundances of scleractinian corals than the mounds and ridges, despite an abundance of settlement substrata. Areal comparisons suggested that the WFS may exceed other parts of the GOM slope in extent of living deep coral coverage and other deep-reef habitat (dead coral and rock). The complex WFS region warrants additional studies to better understand the influences of oceanography and

An insect-inspired model for visual binding I: learning objects and their characteristics.

Science.gov (United States)

Northcutt, Brandon D; Dyhr, Jonathan P; Higgins, Charles M

2017-04-01

Visual binding is the process of associating the responses of visual interneurons in different visual submodalities all of which are responding to the same object in the visual field. Recently identified neuropils in the insect brain termed optic glomeruli reside just downstream of the optic lobes and have an internal organization that could support visual binding. Working from anatomical similarities between optic and olfactory glomeruli, we have developed a model of visual binding based on common temporal fluctuations among signals of independent visual submodalities. Here we describe and demonstrate a neural network model capable both of refining selectivity of visual information in a given visual submodality, and of associating visual signals produced by different objects in the visual field by developing inhibitory neural synaptic weights representing the visual scene. We also show that this model is consistent with initial physiological data from optic glomeruli. Further, we discuss how this neural network model may be implemented in optic glomeruli at a neuronal level.

A flexible object-based software framework for modeling complex systems with interacting natural and societal processes.

Energy Technology Data Exchange (ETDEWEB)

Christiansen, J. H.

2000-06-15

The Dynamic Information Architecture System (DIAS) is a flexible, extensible, object-based framework for developing and maintaining complex multidisciplinary simulations. The DIAS infrastructure makes it feasible to build and manipulate complex simulation scenarios in which many thousands of objects can interact via dozens to hundreds of concurrent dynamic processes. The flexibility and extensibility of the DIAS software infrastructure stem mainly from (1) the abstraction of object behaviors, (2) the encapsulation and formalization of model functionality, and (3) the mutability of domain object contents. DIAS simulation objects are inherently capable of highly flexible and heterogeneous spatial realizations. Geospatial graphical representation of DIAS simulation objects is addressed via the GeoViewer, an object-based GIS toolkit application developed at ANL. DIAS simulation capabilities have been extended by inclusion of societal process models generated by the Framework for Addressing Cooperative Extended Transactions (FACET), another object-based framework developed at Argonne National Laboratory. By using FACET models to implement societal behaviors of individuals and organizations within larger DIAS-based natural systems simulations, it has become possible to conveniently address a broad range of issues involving interaction and feedback among natural and societal processes. Example DIAS application areas discussed in this paper include a dynamic virtual oceanic environment, detailed simulation of clinical, physiological, and logistical aspects of health care delivery, and studies of agricultural sustainability of urban centers under environmental stress in ancient Mesopotamia.

Polarimetry of Solar System Objects: Observations vs. Models

Science.gov (United States)

Yanamandra-Fisher, P. A.

2014-04-01

The overarching goals for the remote sensing and robotic exploration of planetary systems are: (1) understanding the formation of planetary systems and their diversity; and (2) search for habitability. Since all objects have unique polarimetric signatures inclusion of spectrophotopolarimetry as a complementary approach to standard techniques of imaging and spectroscopy, provides insight into the scattering properties of the planetary media. Specifically, linear and circular polarimetric signatures of the object arise from different physical processes and their study proves essential to the characterization of the object. Linear polarization of reflected light by various solar system objects provides insight into the scattering characteristics of atmospheric aerosols and hazes? and surficial properties of atmosphereless bodies. Many optically active materials are anisotropic and so their scattering properties differ with the object's principal axes (such as dichroic or birefringent materials) and are crystalline in structure instead of amorphous, (eg., the presence of olivines and silicates in cometary dust and circumstellar disks? Titan, etc.). Ices (water and other species) are abundant in the system indicated in their near - infrared spectra. Gas giants form outside the frost line (where ices condense), and their satellites and ring systems exhibit signature of water ice? clathrates, nonices (Si, C, Fe) in their NIR spectra and spectral dependence of linear polarization. Additionally, spectral dependence of polarization is important to separate the macroscopic (bulk) properties of the scattering medium from the microscopic (particulate) properties of the scattering medium. Circular polarization, on the other hand, is indicative of magnetic fields and biologically active molecules, necessary for habitability. These applications suffer from lack of detailed observations, instrumentation, dedicated missions and numericalretrieval methods. With recent discoveries and

An interactive system for creating object models from range data based on simulated annealing

International Nuclear Information System (INIS)

Hoff, W.A.; Hood, F.W.; King, R.H.

1997-01-01

In hazardous applications such as remediation of buried waste and dismantlement of radioactive facilities, robots are an attractive solution. Sensing to recognize and locate objects is a critical need for robotic operations in unstructured environments. An accurate 3-D model of objects in the scene is necessary for efficient high level control of robots. Drawing upon concepts from supervisory control, the authors have developed an interactive system for creating object models from range data, based on simulated annealing. Site modeling is a task that is typically performed using purely manual or autonomous techniques, each of which has inherent strengths and weaknesses. However, an interactive modeling system combines the advantages of both manual and autonomous methods, to create a system that has high operator productivity as well as high flexibility and robustness. The system is unique in that it can work with very sparse range data, tolerate occlusions, and tolerate cluttered scenes. The authors have performed an informal evaluation with four operators on 16 different scenes, and have shown that the interactive system is superior to either manual or automatic methods in terms of task time and accuracy

Seismic Interferometry of Gulf of Mexico Basin Opening (GUMBO) Data: Extraction of Body and Surface Waves with a Mixed-Mode Array

Science.gov (United States)

Thangraj, J. S.; Quiros, D.; Pulliam, J.

2017-12-01

The Gulf of Mexico (GoM) is a relative small oceanic basin that formed by rifting between the continental blocks of North America and Yucatan in the Middle to Late Jurassic. Following the breakup, seafloor spreading continued until the Early Cretaceous. Since then, subsidence and sedimentation have shaped the GoM margin that we see today. To better understand the opening of the GoM, a long-offset (307 km) seismic refraction line was acquired in 2010. The transect was located on the northwest GoM margin, and consisted of several types of instruments. This mixed-mode array combined 31 ocean bottom seismographs (OBS), 412 high-frequency instruments (4.5 Hz geophones with RefTek 125A "Texan" digitizers) and 12 broadband stations. The R/V Iron Cat provided the airgun source used in the refraction experiment. The airgun generated 2028 shots in a period of 2.5 days which were recorded by the entire array. The airgun-generated seismic energy was clearly visible on the OBS recordings, however its amplitude was too low to be discerned on most of the onshore stations. In fact, this energy was only visible on Texan stations 1-50 (station 1 is located at the coast), extending 18 km inland, limiting the extend of the velocity model that can be obtained. Here, we apply seismic interferometry techniques to the 2.5 days of continuous data recorded by the Texan array with the goal of extending the spatial range for which the airgun-generated seismic energy can be observed. Preliminary results show that by treating the 2.5 days of continuously recorded airgun data as ambient noise, and applying time-domain cross-correlation, we can observe energy propagating 50 to 70 km inland with apparent velocities of 1800 - 2200 ms-1. These velocities agree with the compressional seismic velocity for the top 5 km of sediments under the GoM obtained from the OBS records, suggesting that we are observing compressional energy in the virtual source gathers (VSG). We also observe arrivals in the VSG

Principles of object-oriented modeling and simulation with Modelica 3.3 a cyber-physical approach

CERN Document Server

Fritzson, Peter

2014-01-01

Fritzson covers the Modelica language in impressive depth from the basic concepts such as cyber-physical, equation-base, object-oriented, system, model, and simulation, while also incorporating over a hundred exercises and their solutions for a tutorial, easy-to-read experience. The only book with complete Modelica 3.3 coverage Over one hundred exercises and solutions Examines basic concepts such as cyber-physical, equation-based, object-oriented, system, model, and simulation

MULTIPLE OBJECTS

Directory of Open Access Journals (Sweden)

A. A. Bosov

2015-04-01

Full Text Available Purpose. The development of complicated techniques of production and management processes, information systems, computer science, applied objects of systems theory and others requires improvement of mathematical methods, new approaches for researches of application systems. And the variety and diversity of subject systems makes necessary the development of a model that generalizes the classical sets and their development – sets of sets. Multiple objects unlike sets are constructed by multiple structures and represented by the structure and content. The aim of the work is the analysis of multiple structures, generating multiple objects, the further development of operations on these objects in application systems. Methodology. To achieve the objectives of the researches, the structure of multiple objects represents as constructive trio, consisting of media, signatures and axiomatic. Multiple object is determined by the structure and content, as well as represented by hybrid superposition, composed of sets, multi-sets, ordered sets (lists and heterogeneous sets (sequences, corteges. Findings. In this paper we study the properties and characteristics of the components of hybrid multiple objects of complex systems, proposed assessments of their complexity, shown the rules of internal and external operations on objects of implementation. We introduce the relation of arbitrary order over multiple objects, we define the description of functions and display on objects of multiple structures. Originality.In this paper we consider the development of multiple structures, generating multiple objects.Practical value. The transition from the abstract to the subject of multiple structures requires the transformation of the system and multiple objects. Transformation involves three successive stages: specification (binding to the domain, interpretation (multiple sites and particularization (goals. The proposed describe systems approach based on hybrid sets

VNM: An R Package for Finding Multiple-Objective Optimal Designs for the 4-Parameter Logistic Model

OpenAIRE

Hyun, Seung Won; Wong, Weng Kee; Yang, Yarong

2018-01-01

A multiple-objective optimal design is useful for dose-response studies because it can incorporate several objectives at the design stage. Objectives can be of varying interests and a properly constructed multiple-objective optimal design can provide user-specified efficiencies, delivering higher efficiencies for the more important objectives. In this work, we introduce the VNM package written in R for finding 3-objective locally optimal designs for the 4-parameter logistic (4PL) model widely...

An object-oriented model for complex bills of materials in process industries

Directory of Open Access Journals (Sweden)

Vegetti M.

2002-01-01

Full Text Available In recent years, many process industries have been forced to drastically increase their product variety and adopt mass customization production strategies. Many of them have found that traditional bill of material (BOM processing systems do not sufficiently support the maintenance of the very large amounts of data (concerned with product structure demanded by these new production policies. Due to the use of BOM technology within the framework of integrated information systems, there is a demand for both (i a new representation of BOMs, able to deal efficiently with product variants and to handle decomposition-based production strategies, and (ii its corresponding BOM information processing system. This paper describes a conceptual representation that integrates elements of semantic relationships with object-oriented concepts to develop a data model for a hybrid bill of materials. The proposed semantic relationships include composed-of, decomposed-into, variant-of, restriction-of, and their corresponding reverse relationships. The conceptual model has been implemented using object-oriented data-based management system (OODBMS technology that allows creation of persistent Java objects. Preliminary tests show a remarkable reduction in the number of relationships when compared with former approaches.

Multi-objective Analysis for a Sequencing Planning of Mixed-model Assembly Line

Science.gov (United States)

Shimizu, Yoshiaki; Waki, Toshiya; Yoo, Jae Kyu

Diversified customer demands are raising importance of just-in-time and agile manufacturing much more than before. Accordingly, introduction of mixed-model assembly lines becomes popular to realize the small-lot-multi-kinds production. Since it produces various kinds on the same assembly line, a rational management is of special importance. With this point of view, this study focuses on a sequencing problem of mixed-model assembly line including a paint line as its preceding process. By taking into account the paint line together, reducing work-in-process (WIP) inventory between these heterogeneous lines becomes a major concern of the sequencing problem besides improving production efficiency. Finally, we have formulated the sequencing problem as a bi-objective optimization problem to prevent various line stoppages, and to reduce the volume of WIP inventory simultaneously. Then we have proposed a practical method for the multi-objective analysis. For this purpose, we applied the weighting method to derive the Pareto front. Actually, the resulting problem is solved by a meta-heuristic method like SA (Simulated Annealing). Through numerical experiments, we verified the validity of the proposed approach, and discussed the significance of trade-off analysis between the conflicting objectives.

A hybrid input–output multi-objective model to assess economic–energy–environment trade-offs in Brazil

International Nuclear Information System (INIS)

Carvalho, Ariovaldo Lopes de; Antunes, Carlos Henggeler; Freire, Fausto; Henriques, Carla Oliveira

2015-01-01

A multi-objective linear programming (MOLP) model based on a hybrid Input–Output (IO) framework is presented. This model aims at assessing the trade-offs between economic, energy, environmental (E3) and social objectives in the Brazilian economic system. This combination of multi-objective models with Input–Output Analysis (IOA) plays a supplementary role in understanding the interactions between the economic and energy systems, and the corresponding impacts on the environment, offering a consistent framework for assessing the effects of distinct policies on these systems. Firstly, the System of National Accounts (SNA) is reorganized to include the National Energy Balance, creating a hybrid IO framework that is extended to assess Greenhouse Gas (GHG) emissions and the employment level. The objective functions considered are the maximization of GDP (gross domestic product) and employment levels, as well as the minimization of energy consumption and GHG emissions. An interactive method enabling a progressive and selective search of non-dominated solutions with distinct characteristics and underlying trade-offs is utilized. Illustrative results indicate that the maximization of GDP and the employment levels lead to an increase of both energy consumption and GHG emissions, while the minimization of either GHG emissions or energy consumption cause negative impacts on GDP and employment. - Highlights: • A hybrid Input–Output multi-objective model is applied to the Brazilian economy. • Objective functions are GDP, employment level, energy consumption and GHG emissions. • Interactive search process identifies trade-offs between the competing objectives. • Positive correlations between GDP growth and employment. • Positive correlations between energy consumption and GHG emissions

Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems.

Directory of Open Access Journals (Sweden)

Zili Zhang

Full Text Available Bi-objective Traveling Salesman Problem (bTSP is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM. PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs.

An Object Model for Integrating Diverse Remote Sensing Satellite Sensors: A Case Study of Union Operation

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Chuli Hu

2014-01-01

Full Text Available In the Earth Observation sensor web environment, the rapid, accurate, and unified discovery of diverse remote sensing satellite sensors, and their association to yield an integrated solution for a comprehensive response to specific emergency tasks pose considerable challenges. In this study, we propose a remote sensing satellite sensor object model, based on the object-oriented paradigm and the Open Geospatial Consortium Sensor Model Language. The proposed model comprises a set of sensor resource objects. Each object consists of identification, state of resource attribute, and resource method. We implement the proposed attribute state description by applying it to different remote sensors. A real application, involving the observation of floods at the Yangtze River in China, is undertaken. Results indicate that the sensor inquirer can accurately discover qualified satellite sensors in an accurate and unified manner. By implementing the proposed union operation among the retrieved sensors, the inquirer can further determine how the selected sensors can collaboratively complete a specific observation requirement. Therefore, the proposed model provides a reliable foundation for sharing and integrating multiple remote sensing satellite sensors and their observations.

Effect Analysis of Early Warning for Abandoned Object on Highway Based on Internet-of-Vehicles CA Model

Directory of Open Access Journals (Sweden)

Juan Bao

2018-01-01

Full Text Available An early warning on the highway will effectively reduce traffic accidents. Considering the influence of an abandoned object on driving behavior, a Visual-based Asymmetric Two-lane Cellular Automata model with Abandoned Object (V-ATCA-AO and an Internet-of-Vehicles-based Asymmetric Two-lane Cellular Automata model with Abandoned Object (IoV-ATCA-AO are proposed. Based on the two models, two types of traffic accidents caused by an abandoned object are analyzed: rear-end collision caused by the abandoned object ahead and collision of the vehicle with the abandoned object. Simulation results show the following: (1 the accidents occur when the road density is smaller, while the accidents will not occur when the density is larger. The results are different from the rear-end collision rate curve without abandoned object in a single lane. (2 Compared with the visual-based avoidance pattern in V-ATCA-AO, the Internet-of-Vehicles-based avoidance pattern in IoV-ATCA-AO can create an early warning for the abandoned object and tell the vehicle to make an earlier lane change and decelerate in advance, thereby significantly reducing the accident rate. (3 Spatiotemporal characteristics in front of the abandoned object directly affect the accident rate: the less the “stability” of a traffic jam in front of the abandoned object, the higher the accident rate.

Integration of a Three-Dimensional Process-Based Hydrological Model into the Object Modeling System

Directory of Open Access Journals (Sweden)

Giuseppe Formetta

2016-01-01

Full Text Available The integration of a spatial process model into an environmental modeling framework can enhance the model’s capabilities. This paper describes a general methodology for integrating environmental models into the Object Modeling System (OMS regardless of the model’s complexity, the programming language, and the operating system used. We present the integration of the GEOtop model into the OMS version 3.0 and illustrate its application in a small watershed. OMS is an environmental modeling framework that facilitates model development, calibration, evaluation, and maintenance. It provides innovative techniques in software design such as multithreading, implicit parallelism, calibration and sensitivity analysis algorithms, and cloud-services. GEOtop is a physically based, spatially distributed rainfall-runoff model that performs three-dimensional finite volume calculations of water and energy budgets. Executing GEOtop as an OMS model component allows it to: (1 interact directly with the open-source geographical information system (GIS uDig-JGrass to access geo-processing, visualization, and other modeling components; and (2 use OMS components for automatic calibration, sensitivity analysis, or meteorological data interpolation. A case study of the model in a semi-arid agricultural catchment is presented for illustration and proof-of-concept. Simulated soil water content and soil temperature results are compared with measured data, and model performance is evaluated using goodness-of-fit indices. This study serves as a template for future integration of process models into OMS.

Towards Real-Time GOMS

Science.gov (United States)

1990-12-28

as possible, thinking aloud as he played. Gray videotaped KP performing this task to provide observed behavior against which to measure the...Lehman, J. F., Newell, A., Rosenblom, P. S., Simon , T., & Tessler, S. G. "Soar as a Unified Theory of Cognition: Spring 1990. in the Proceedings of the...Center Brown University Dr. Michael Blackburns User Interface Institute Department of Psychology Code 943 P.O. Box 704 Proience. RI 02912 Naval Ocean

GoM Diet Matrix

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set was taken from CRD 08-18 at the NEFSC. Specifically, the Gulf of Maine diet matrix was developed for the EMAX exercise described in that center...

Modeling and query the uncertainty of network constrained moving objects based on RFID data

Science.gov (United States)

Han, Liang; Xie, Kunqing; Ma, Xiujun; Song, Guojie

2007-06-01

The management of network constrained moving objects is more and more practical, especially in intelligent transportation system. In the past, the location information of moving objects on network is collected by GPS, which cost high and has the problem of frequent update and privacy. The RFID (Radio Frequency IDentification) devices are used more and more widely to collect the location information. They are cheaper and have less update. And they interfere in the privacy less. They detect the id of the object and the time when moving object passed by the node of the network. They don't detect the objects' exact movement in side the edge, which lead to a problem of uncertainty. How to modeling and query the uncertainty of the network constrained moving objects based on RFID data becomes a research issue. In this paper, a model is proposed to describe the uncertainty of network constrained moving objects. A two level index is presented to provide efficient access to the network and the data of movement. The processing of imprecise time-slice query and spatio-temporal range query are studied in this paper. The processing includes four steps: spatial filter, spatial refinement, temporal filter and probability calculation. Finally, some experiments are done based on the simulated data. In the experiments the performance of the index is studied. The precision and recall of the result set are defined. And how the query arguments affect the precision and recall of the result set is also discussed.

Renewable Electricity Grid Integration Roadmap for Mexico. Supplement to the IEA Expert Group Report on Recommended Practices for Wind Integration Studies

Energy Technology Data Exchange (ETDEWEB)

Parsons, Brian [Evergreen Renewable Consulting, Evergreen, CO (United States); Cochran, Jaquelin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Watson, Andrea [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Katz, Jessica [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bracho, Ricardo [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2015-08-19

As a recognized leader in efforts to mitigate global climate change, the Government of Mexico (GOM) works proactively to reduce emissions, demonstrating strong political will and capacity to comprehensively address climate change. Since 2010, the U.S. government (USG) has supported these efforts by partnering with Mexico under the Enhancing Capacity for Low Emission Development Strategies (EC-LEDS) program. Through the program, the USG has partnered with Mexico’s Ministry of Energy (SENER), as well as other government agencies, to support GOM in reaching its clean energy and climate change goals. Specifically, the EC-LEDS program is supporting GOM’s clean energy goal of generating 35% of its electricity from renewable energy (RE) by 2024. EC-LEDS, through the U.S. Agency for International Development (USAID) and the U.S Department of Energy’s (DOE’s) National Renewable Energy Laboratory (NREL), has been collaborating with SENER and GOM interagency working group—the Consejo Consultivo para las Energías Renovables (Consultative Council on Renewable Energy)—to create a grid integration roadmap for variable RE. 1 A key objective in creating a grid integration roadmap is assessing likely impacts of wind and solar energy on the power system and modifying planning and operations accordingly. This paper applies best practices in conducting a grid integration study to the Mexican context.

A sustainable manufacturing system design: A fuzzy multi-objective optimization model.

Science.gov (United States)

Nujoom, Reda; Mohammed, Ahmed; Wang, Qian

2017-08-10

In the past decade, there has been a growing concern about the environmental protection in public society as governments almost all over the world have initiated certain rules and regulations to promote energy saving and minimize the production of carbon dioxide (CO 2 ) emissions in many manufacturing industries. The development of sustainable manufacturing systems is considered as one of the effective solutions to minimize the environmental impact. Lean approach is also considered as a proper method for achieving sustainability as it can reduce manufacturing wastes and increase the system efficiency and productivity. However, the lean approach does not include environmental waste of such as energy consumption and CO 2 emissions when designing a lean manufacturing system. This paper addresses these issues by evaluating a sustainable manufacturing system design considering a measurement of energy consumption and CO 2 emissions using different sources of energy (oil as direct energy source to generate thermal energy and oil or solar as indirect energy source to generate electricity). To this aim, a multi-objective mathematical model is developed incorporating the economic and ecological constraints aimed for minimization of the total cost, energy consumption, and CO 2 emissions for a manufacturing system design. For the real world scenario, the uncertainty in a number of input parameters was handled through the development of a fuzzy multi-objective model. The study also addresses decision-making in the number of machines, the number of air-conditioning units, and the number of bulbs involved in each process of a manufacturing system in conjunction with a quantity of material flow for processed products. A real case study was used for examining the validation and applicability of the developed sustainable manufacturing system model using the fuzzy multi-objective approach.

Improved signal model for confocal sensors accounting for object depending artifacts.

Science.gov (United States)

Mauch, Florian; Lyda, Wolfram; Gronle, Marc; Osten, Wolfgang

2012-08-27

The conventional signal model of confocal sensors is well established and has proven to be exceptionally robust especially when measuring rough surfaces. Its physical derivation however is explicitly based on plane surfaces or point like objects, respectively. Here we show experimental results of a confocal point sensor measurement of a surface standard. The results illustrate the rise of severe artifacts when measuring curved surfaces. On this basis, we present a systematic extension of the conventional signal model that is proven to be capable of qualitatively explaining these artifacts.

Windfield and trajectory models for tornado-propelled objects. Final report

International Nuclear Information System (INIS)

Redmann, G.H.; Radbill, J.R.; Marte, J.E.; Dergarabedian, P.; Fendell, F.E.

1983-03-01

This is the final report of a three-phased research project to develop a six-degree-of-freedom mathematical model to predict the trajectories of tornado-propelled objects. The model is based on the meteorological, aerodynamic, and dynamic processes that govern the trajectories of missiles in a tornadic windfield. The aerodynamic coefficients for the postulated missiles were obtained from full-scale wind tunnel tests on a 12-inch pipe and car and from drop tests. Rocket sled tests were run whereby the 12-inch pipe and car were injected into a worst-case tornado windfield in order to verify the trajectory model. To simplify and facilitate the use of the trajectory model for design applications without having to run the computer program, this report gives the trajectory data for NRC-postulated missiles in tables based on given variables of initial conditions of injection and tornado windfield. Complete descriptions of the tornado windfield and trajectory models are presented. The trajectory model computer program is also included for those desiring to perform trajectory or sensitivity analyses beyond those included in the report or for those wishing to examine other missiles and use other variables

Object instance recognition using motion cues and instance specific appearance models

Science.gov (United States)

Schumann, Arne

2014-03-01

In this paper we present an object instance retrieval approach. The baseline approach consists of a pool of image features which are computed on the bounding boxes of a query object track and compared to a database of tracks in order to find additional appearances of the same object instance. We improve over this simple baseline approach in multiple ways: 1) we include motion cues to achieve improved robustness to viewpoint and rotation changes, 2) we include operator feedback to iteratively re-rank the resulting retrieval lists and 3) we use operator feedback and location constraints to train classifiers and learn an instance specific appearance model. We use these classifiers to further improve the retrieval results. The approach is evaluated on two popular public datasets for two different applications. We evaluate person re-identification on the CAVIAR shopping mall surveillance dataset and vehicle instance recognition on the VIVID aerial dataset and achieve significant improvements over our baseline results.

Demographic clusters identified within the northern Gulf of Mexico common bottlenose dolphin (Tursiops truncates unusual mortality event: January 2010-June 2013.

Directory of Open Access Journals (Sweden)

Stephanie Venn-Watson

Full Text Available A multi-year unusual mortality event (UME involving primarily common bottlenose dolphins (Tursiops truncates was declared in the northern Gulf of Mexico (GoM with an initial start date of February 2010 and remains ongoing as of August 2014. To examine potential changing characteristics of the UME over time, we compared the number and demographics of dolphin strandings from January 2010 through June 2013 across the entire GoM as well as against baseline (1990-2009 GoM stranding patterns. Years 2010 and 2011 had the highest annual number of stranded dolphins since Louisiana's record began, and 2011 was one of the years with the highest strandings for both Mississippi and Alabama. Statewide, annual numbers of stranded dolphins were not elevated for GoM coasts of Florida or Texas during the UME period. Demographic, spatial, and temporal clusters identified within this UME included increased strandings in northern coastal Louisiana and Mississippi (March-May 2010; Barataria Bay, Louisiana (August 2010-December 2011; Mississippi and Alabama (2011, including a high prevalence and number of stranded perinates; and multiple GoM states during early 2013. While the causes of the GoM UME have not been determined, the location and magnitude of dolphin strandings during and the year following the 2010 Deepwater Horizon oil spill, including the Barataria Bay cluster from August 2010 to December 2011, overlap in time and space with locations that received heavy and prolonged oiling. There are, however, multiple known causes of previous GoM dolphin UMEs, including brevetoxicosis and dolphin morbillivirus. Additionally, increased dolphin strandings occurred in northern Louisiana and Mississippi before the Deepwater Horizon oil spill. Identification of spatial, temporal, and demographic clusters within the UME suggest that this mortality event may involve different contributing factors varying by location, time, and bottlenose dolphin populations that will be

Probabilistic safety assessment model in consideration of human factors based on object-oriented bayesian networks

International Nuclear Information System (INIS)

Zhou Zhongbao; Zhou Jinglun; Sun Quan

2007-01-01

Effect of Human factors on system safety is increasingly serious, which is often ignored in traditional probabilistic safety assessment methods however. A new probabilistic safety assessment model based on object-oriented Bayesian networks is proposed in this paper. Human factors are integrated into the existed event sequence diagrams. Then the classes of the object-oriented Bayesian networks are constructed which are converted to latent Bayesian networks for inference. Finally, the inference results are integrated into event sequence diagrams for probabilistic safety assessment. The new method is applied to the accident of loss of coolant in a nuclear power plant. the results show that the model is not only applicable to real-time situation assessment, but also applicable to situation assessment based certain amount of information. The modeling complexity is kept down and the new method is appropriate to large complex systems due to the thoughts of object-oriented. (authors)

Towards a model for egocentric interaction with physical and virtual objects

DEFF Research Database (Denmark)

Pederson, Thomas; Janlert, Lars-Erik; Surie, Dipak

2010-01-01

Designers of mobile context-aware systems are struggling with the problem of conceptually incorporating the real world into the system design. We present a body-centric modeling framework (as opposed to device-centric) that incorporates physical and virtual objects of interest on the basis...... of proximity and human perception, framed in the context of an emerging "egocentric" interaction paradigm....

Processing Technology Selection for Municipal Sewage Treatment Based on a Multi-Objective Decision Model under Uncertainty.

Science.gov (United States)

Chen, Xudong; Xu, Zhongwen; Yao, Liming; Ma, Ning

2018-03-05

This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.

Gulf of Mexico development

International Nuclear Information System (INIS)

Krenz, D.

1998-01-01

In recent years, the Gulf of Mexico (GOM) has seen significant deepwater growth. An overview of the GOM deepwater leaseholds by Shell and developments by competing companies is presented. Deepwater GOM developments, total production from the shelf and from deepwater wells, new offshore pipeline capacity and ownership, and processing plant capacity are also discussed. Significant deepwater growth in the Gulf is anticipated. Despite significant economic and technological challenges, the area is judged to be the prime exploration and production opportunity in the lower 48 states of the USA. tabs., figs

[Location selection for Shenyang urban parks based on GIS and multi-objective location allocation model].

Science.gov (United States)

Zhou, Yuan; Shi, Tie-Mao; Hu, Yuan-Man; Gao, Chang; Liu, Miao; Song, Lin-Qi

2011-12-01

Based on geographic information system (GIS) technology and multi-objective location-allocation (LA) model, and in considering of four relatively independent objective factors (population density level, air pollution level, urban heat island effect level, and urban land use pattern), an optimized location selection for the urban parks within the Third Ring of Shenyang was conducted, and the selection results were compared with the spatial distribution of existing parks, aimed to evaluate the rationality of the spatial distribution of urban green spaces. In the location selection of urban green spaces in the study area, the factor air pollution was most important, and, compared with single objective factor, the weighted analysis results of multi-objective factors could provide optimized spatial location selection of new urban green spaces. The combination of GIS technology with LA model would be a new approach for the spatial optimizing of urban green spaces.

Usability engineering of "In Vehicle Information Systems" with multi-tasking GOMS

OpenAIRE

Urbas, L.; Leuchter, S.

2008-01-01

The developments in vehicle electronics and new services are supposed to promise more convenience in driving. The offers and ideas range from vehicle-related installations, such as accident alert, petrol station assistance, dynamic navigation and travel guide, to communication and entertainment services. There is one central design problem that is essential for achieving the main objective "safe motor vehicle driving", i.e. the use of the new service must not unduly distract the driver. In th...

Reasoning about Function Objects

Science.gov (United States)

Nordio, Martin; Calcagno, Cristiano; Meyer, Bertrand; Müller, Peter; Tschannen, Julian

Modern object-oriented languages support higher-order implementations through function objects such as delegates in C#, agents in Eiffel, or closures in Scala. Function objects bring a new level of abstraction to the object-oriented programming model, and require a comparable extension to specification and verification techniques. We introduce a verification methodology that extends function objects with auxiliary side-effect free (pure) methods to model logical artifacts: preconditions, postconditions and modifies clauses. These pure methods can be used to specify client code abstractly, that is, independently from specific instantiations of the function objects. To demonstrate the feasibility of our approach, we have implemented an automatic prover, which verifies several non-trivial examples.

Implementation of the Multidimensional Modeling Concepts into Object-Relational Databases

Directory of Open Access Journals (Sweden)

2007-01-01

Full Text Available A key to survival in the business world is being able to analyze, plan and react to changing business conditions as fast as possible. With multidimensional models the managers can explore information at different levels of granularity and the decision makers at all levels can quickly respond to changes in the business climate-the ultimate goal of business intelligence. This paper focuses on the implementation of the multidimensional concepts into object-relational databases.

Characterization of phytoplankton pigments and functional community structure in the Gulf of Mannar and the Palk Bay using HPLC–CHEMTAX analysis.

Digital Repository Service at National Institute of Oceanography (India)

Madhu, N.V.; Ullas, N.; Ashwini, R.; Meenu, P.; Rehitha, T.V.; Lallu, K.R.

Phytoplankton marker pigments and their functional groups were identified for the first time in the Gulf of Mannar (GoM) and the Palk Bay (PB), located in the southeast coast of India using HPLC–CHEMTAX analytical techniques. The GoM generally...

Modeling a terminology-based electronic nursing record system: an object-oriented approach.

Science.gov (United States)

Park, Hyeoun-Ae; Cho, InSook; Byeun, NamSoo

2007-10-01

The aim of this study was to present our perspectives on healthcare information analysis at a conceptual level and the lessons learned from our experience with the development of a terminology-based enterprise electronic nursing record system - which was one of components in an EMR system at a tertiary teaching hospital in Korea - using an object-oriented system analysis and design concept. To ensure a systematic approach and effective collaboration, the department of nursing constituted a system modeling team comprising a project manager, systems analysts, user representatives, an object-oriented methodology expert, and healthcare informaticists (including the authors). A rational unified process (RUP) and the Unified Modeling Language were used as a development process and for modeling notation, respectively. From the scenario and RUP approach, user requirements were formulated into use case sets and the sequence of activities in the scenario was depicted in an activity diagram. The structure of the system was presented in a class diagram. This approach allowed us to identify clearly the structural and behavioral states and important factors of a terminology-based ENR system (e.g., business concerns and system design concerns) according to the viewpoints of both domain and technical experts.

Modeling of information on the impact of mining exploitation on bridge objects in BIM

Science.gov (United States)

Bętkowski, Piotr

2018-04-01

The article discusses the advantages of BIM (Building Information Modeling) technology in the management of bridge infrastructure on mining areas. The article shows the problems with information flow in the case of bridge objects located on mining areas and the advantages of proper information management, e.g. the possibility of automatic monitoring of structures, improvement of safety, optimization of maintenance activities, cost reduction of damage removal and preventive actions, improvement of atmosphere for mining exploitation, improvement of the relationship between the manager of the bridge and the mine. Traditional model of managing bridge objects on mining areas has many disadvantages, which are discussed in this article. These disadvantages include among others: duplication of information about the object, lack of correlation in investments due to lack of information flow between bridge manager and mine, limited assessment possibilities of damage propagation on technical condition and construction resistance to mining influences.

Novel object exploration in the C58/J mouse model of autistic-like behavior.

Science.gov (United States)

Blick, Mikkal G; Puchalski, Breann H; Bolanos, Veronica J; Wolfe, Kaitlin M; Green, Matthew C; Ryan, Bryce C

2015-04-01

Mouse models of autistic like behaviors are a valuable tool to use when studying the causes, symptoms, and potential treatments for autism. The inbred C58/J strain is a strain of interest for this model and has previously been shown to possess face validity for some of the core traits of autism, including low social behavior and elevated motor stereotypies. Higher order repetitive behaviors have not been extensively studied in this strain, or in mice in general. In this study, we looked for evidence of higher-order repetitive behaviors in the C58/J strain using a novel object assay. This assay utilized a mouse's natural exploratory behavior among unfamiliar objects to identify potential sequencing patterns in motor activity. The motor stereotypies displayed by the C58/J strain during testing were consistent with past studies. The C58/J strain also displayed a high preference for a single object in the round arena assays and the females demonstrating elevated sequencing patterns in the round arena. Although the C58/J strain did not show pervasive evidence of higher-order repetitive behaviors across all measures, there was evidence of higher order repetitive behaviors in certain situations. This study further demonstrates the potential of the C58/J mouse strains as a model for lower-order and potentially, higher-order repetitive behaviors. This study also demonstrates that the shape of the novel object arena can change the behavior displayed by the test animals. Further studies utilizing the C58/J strain and further validation of the novel object assay are warranted. Copyright © 2014 Elsevier B.V. All rights reserved.

Teach it Yourself - Fast Modeling of Industrial Objects for 6D Pose Estimation

DEFF Research Database (Denmark)

Sølund, Thomas; Rajeeth Savarimuthu, Thiusius; Glent Buch, Anders

2015-01-01

In this paper, we present a vision system that allows a human to create new 3D models of novel industrial parts by placing the part in two different positions in the scene. The two shot modeling framework generates models with a precision that allows the model to be used for 6D pose estimation wi....... In addition, the models are applied in a pose estimation application, evaluated with 37 different scenes with 61 unique object poses. The pose estimation results show a mean translation error on 4.97 mm and a mean rotation error on 3.38 degrees....

Processing Technology Selection for Municipal Sewage Treatment Based on a Multi-Objective Decision Model under Uncertainty

Directory of Open Access Journals (Sweden)

Xudong Chen

2018-03-01

Full Text Available This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.

Multi-objective calibration of a reservoir water quality model in aggregation and non-dominated sorting approaches

Science.gov (United States)

Huang, Yongtai

2014-03-01

Numerical water quality models are developed to predict contaminant fate and transport in receiving waters such as reservoirs and lakes. They can be helpful tools for water resource management. The objective of this study is to calibrate a water quality model which was set up to simulate the water quality conditions of Pepacton Reservoir, Downsville, New York, USA, using an aggregation hybrid genetic algorithm (AHGA) and a non-dominated sorting hybrid genetic algorithm (NSHGA). Both AHGA and NSHGA use a hybrid genetic algorithm (HGA) as optimization engines but are different in fitness assignment. In the AHGA, a weighted sum of scaled simulation errors is designed as an overall objective function to measure the fitness of solutions (i.e., parameter values). In the NSHGA, a method based on non-dominated sorting and Euclidean distances is proposed to calculate the dummy fitness of solutions. In addition, this study also compares the AHGA and the NSHGA. The purpose of this comparison is to determine whether the objective function values (i.e., simulation errors) and simulated results obtained by the AHGA and the NSHGA are significantly different from each other. The results show that the objective function values from the two HGAs are good compromises between all objective functions, and the calibrated model results match the observed data reasonably well and are comparable to other studies, supporting and justifying the use of multi-objective calibration.

Deepwater Horizon oil in Gulf of Mexico waters after 2 years: transformation into the dissolved organic matter pool.

Science.gov (United States)

Bianchi, Thomas S; Osburn, Christopher; Shields, Michael R; Yvon-Lewis, Shari; Young, Jordan; Guo, Laodong; Zhou, Zhengzhen

2014-08-19

Recent work has shown the presence of anomalous dissolved organic matter (DOM), with high optical yields, in deep waters 15 months after the Deepwater Horizon (DWH) oil spill in the Gulf of Mexico (GOM). Here, we continue to use the fluorescence excitation-emission matrix (EEM) technique coupled with parallel factor analysis (PARAFAC) modeling, measurements of bulk organic carbon, dissolved inorganic carbon (DIC), oil indices, and other optical properties to examine the chemical evolution and transformation of oil components derived from the DWH in the water column of the GOM. Seawater samples were collected from the GOM during July 2012, 2 years after the oil spill. This study shows that, while dissolved organic carbon (DOC) values have decreased since just after the DWH spill, they remain higher at some stations than typical deep-water values for the GOM. Moreover, we continue to observe fluorescent DOM components in deep waters, similar to those of degraded oil observed in lab and field experiments, which suggest that oil-related fluorescence signatures, as part of the DOM pool, have persisted for 2 years in the deep waters. This supports the notion that some oil-derived chromophoric dissolved organic matter (CDOM) components could still be identified in deep waters after 2 years of degradation, which is further supported by the lower DIC and partial pressure of carbon dioxide (pCO2) associated with greater amounts of these oil-derived components in deep waters, assuming microbial activity on DOM in the current water masses is only the controlling factor of DIC and pCO2 concentrations.

Nearshore waves and longshore sediment transport along Rameshwaram Island off the east coast of India

Directory of Open Access Journals (Sweden)

Rajamanickam Gowthaman

2015-11-01

Full Text Available Wave-induced Longshore Sediment Transport (LST play an important role in the dynamics of the Dhanushkodi sandspit located southeast of Rameshwaram. The LST along the Dhanushkodi coast is studied based on data collected simultaneously in Gulf of Mannar (GoM and Palk Bay (PB using directional waverider buoys. The numerical model REF/DIF1 was used to calculate the nearshore waves and the LST rate was estimated using three different formulae. The model validation was done based on the measured nearshore waves using InterOcean S4DW. Numerical model LITPACK was also used for simulating non-cohesive sediment transport and the LITLINE module was used to study the shoreline evolution over 5 years. Low net annual LST along PB (~0.01 × 106 m3 compared to the GoM region (0.3 × 106 m3 were due to the weak waves. Accretion in the region led to growth of the Dhanushkodi sandspit by 65 m during the period 2010-2015.

Time-domain incomplete Gauss-Newton full-waveform inversion of Gulf of Mexico data

KAUST Repository

AlTheyab, Abdullah; Wang, Xin; Schuster, Gerard T.

2013-01-01

We apply the incomplete Gauss-Newton full-waveform inversion (TDIGN-FWI) to Gulf of Mexico (GOM) data in the space-time domain. In our application, iterative least-squares reverse-time migration (LSRTM) is used to estimate the model update at each

Application of an object-oriented programming paradigm in three-dimensional computer modeling of mechanically active gastrointestinal tissues.

Science.gov (United States)

Rashev, P Z; Mintchev, M P; Bowes, K L

2000-09-01

The aim of this study was to develop a novel three-dimensional (3-D) object-oriented modeling approach incorporating knowledge of the anatomy, electrophysiology, and mechanics of externally stimulated excitable gastrointestinal (GI) tissues and emphasizing the "stimulus-response" principle of extracting the modeling parameters. The modeling method used clusters of class hierarchies representing GI tissues from three perspectives: 1) anatomical; 2) electrophysiological; and 3) mechanical. We elaborated on the first four phases of the object-oriented system development life-cycle: 1) analysis; 2) design; 3) implementation; and 4) testing. Generalized cylinders were used for the implementation of 3-D tissue objects modeling the cecum, the descending colon, and the colonic circular smooth muscle tissue. The model was tested using external neural electrical tissue excitation of the descending colon with virtual implanted electrodes and the stimulating current density distributions over the modeled surfaces were calculated. Finally, the tissue deformations invoked by electrical stimulation were estimated and represented by a mesh-surface visualization technique.

Airborne Vertical Profiling of Mercury Speciation near Tullahoma, TN, USA

Directory of Open Access Journals (Sweden)

Steve Brooks

2014-08-01

Full Text Available Atmospheric transport and in situ oxidation are important factors influencing mercury concentrations at the surface and wet and dry deposition rates. Contributions of both natural and anthropogenic processes can significantly impact burdens of mercury on local, regional and global scales. To address these key issues in atmospheric mercury research, airborne measurements of mercury speciation and ancillary parameters were conducted over a region near Tullahoma, Tennessee, USA, from August 2012 to June 2013. Here, for the first time, we present vertical profiles of Hg speciation from aircraft for an annual cycle over the same location. These airborne measurements included gaseous elemental mercury (GEM, gaseous oxidized mercury (GOM and particulate bound mercury (PBM, as well as ozone (O3, sulfur dioxide (SO2, condensation nuclei (CN and meteorological parameters. The flights, each lasting ~3 h, were conducted typically one week out of each month to characterize seasonality in mercury concentrations. Data obtained from 0 to 6 km altitudes show that GEM exhibited a relatively constant vertical profile for all seasons with an average concentration of 1.38 ± 0.17 ng∙m−3. A pronounced seasonality of GOM was observed, with the highest GOM concentrations up to 120 pg∙m−3 in the summer flights and lowest (0–20 pg∙m−3 in the winter flights. Vertical profiles of GOM show the maximum levels at altitudes between 2 and 4 km. Limited PBM measurements exhibit similar levels to GOM at all altitudes. HYSPLIT back trajectories showed that the trajectories for elevated GOM (>70 pg∙m−3 or PBM concentrations (>30 pg∙m−3 were largely associated with air masses coming from west/northwest, while events with low GOM (<20 pg∙m−3 or PBM concentrations (<5 pg∙m−3 were generally associated with winds from a wider range of wind directions. This is the first set of speciated mercury vertical profiles collected in a single location over the course

A Robust Programming Approach to Bi-objective Optimization Model in the Disaster Relief Logistics Response Phase

Directory of Open Access Journals (Sweden)

Mohsen Saffarian

2015-05-01

Full Text Available Accidents and natural disasters and crises coming out of them indicate the importance of an integrated planning to reduce their effected. Therefore, disaster relief logistics is one of the main activities in disaster management. In this paper, we study the response phase of the disaster management cycle and a bi-objective model has been developed for relief chain logistic in uncertainty condition including uncertainty in traveling time an also amount of demand in damaged areas. The proposed mathematical model has two objective functions. The first one is to minimize the sum of arrival times to damaged area multiplying by amount of demand and the second objective function is to maximize the minimum ratio of satisfied demands in total period in order to fairness in the distribution of goods. In the proposed model, the problem has been considered periodically and in order to solve the mathematical model, Global Criterion method has been used and a case study has been done at South Khorasan.

Decision making model for Foreign Object Debris/Damage (FOD) elimination in aeronautics using quantitative modeling approach

Science.gov (United States)

Lafon, Jose J.

(FOD) Foreign Object Debris/Damage has been a costly issue for the commercial and military aircraft manufacturers at their production lines every day. FOD can put pilots, passengers and other crews' lives into high-risk. FOD refers to any type of foreign object, particle, debris or agent in the manufacturing environment, which could contaminate/damage the product or otherwise undermine quality standards. Nowadays, FOD is currently addressed with prevention programs, elimination techniques, and designation of FOD areas, controlled access to FOD areas, restrictions of personal items entering designated areas, tool accountability, etc. All of the efforts mentioned before, have not shown a significant reduction in FOD occurrence in the manufacturing processes. This research presents a Decision Making Model approach based on a logistic regression predictive model that was previously made by other researchers. With a general idea of the FOD expected, elimination plans can be put in place and start eradicating the problem minimizing the cost and time spend on the prediction, detection and/or removal of FOD.

Object-Oriented Plan Representation for the OMWG C2 Object Schema

National Research Council Canada - National Science Library

Reeves, Robert

1997-01-01

.... Chapter II discusses the theory and practice of modern Object Oriented modeling. The structure and conventions of object programming are covered as well as a method for information system abstraction...

Objective models of compressed breast shapes undergoing mammography

Science.gov (United States)

Feng, Steve Si Jia; Patel, Bhavika; Sechopoulos, Ioannis

2013-01-01

Purpose: To develop models of compressed breasts undergoing mammography based on objective analysis, that are capable of accurately representing breast shapes in acquired clinical images and generating new, clinically realistic shapes. Methods: An automated edge detection algorithm was used to catalogue the breast shapes of clinically acquired cranio-caudal (CC) and medio-lateral oblique (MLO) view mammograms from a large database of digital mammography images. Principal component analysis (PCA) was performed on these shapes to reduce the information contained within the shapes to a small number of linearly independent variables. The breast shape models, one of each view, were developed from the identified principal components, and their ability to reproduce the shape of breasts from an independent set of mammograms not used in the PCA, was assessed both visually and quantitatively by calculating the average distance error (ADE). Results: The PCA breast shape models of the CC and MLO mammographic views based on six principal components, in which 99.2% and 98.0%, respectively, of the total variance of the dataset is contained, were found to be able to reproduce breast shapes with strong fidelity (CC view mean ADE = 0.90 mm, MLO view mean ADE = 1.43 mm) and to generate new clinically realistic shapes. The PCA models based on fewer principal components were also successful, but to a lesser degree, as the two-component model exhibited a mean ADE = 2.99 mm for the CC view, and a mean ADE = 4.63 mm for the MLO view. The four-component models exhibited a mean ADE = 1.47 mm for the CC view and a mean ADE = 2.14 mm for the MLO view. Paired t-tests of the ADE values of each image between models showed that these differences were statistically significant (max p-value = 0.0247). Visual examination of modeled breast shapes confirmed these results. Histograms of the PCA parameters associated with the six principal components were fitted with Gaussian distributions. The six

Objective models of compressed breast shapes undergoing mammography

Energy Technology Data Exchange (ETDEWEB)

Feng, Steve Si Jia [Department of Biomedical Engineering, Georgia Institute of Technology and Emory University and Department of Radiology and Imaging Sciences, Emory University, 1701 Uppergate Drive Northeast, Suite 5018, Atlanta, Georgia 30322 (United States); Patel, Bhavika [Department of Radiology and Imaging Sciences, Emory University, 1701 Uppergate Drive Northeast, Suite 5018, Atlanta, Georgia 30322 (United States); Sechopoulos, Ioannis [Departments of Radiology and Imaging Sciences, Hematology and Medical Oncology and Winship Cancer Institute, Emory University, 1701 Uppergate Drive Northeast, Suite 5018, Atlanta, Georgia 30322 (United States)

2013-03-15

Purpose: To develop models of compressed breasts undergoing mammography based on objective analysis, that are capable of accurately representing breast shapes in acquired clinical images and generating new, clinically realistic shapes. Methods: An automated edge detection algorithm was used to catalogue the breast shapes of clinically acquired cranio-caudal (CC) and medio-lateral oblique (MLO) view mammograms from a large database of digital mammography images. Principal component analysis (PCA) was performed on these shapes to reduce the information contained within the shapes to a small number of linearly independent variables. The breast shape models, one of each view, were developed from the identified principal components, and their ability to reproduce the shape of breasts from an independent set of mammograms not used in the PCA, was assessed both visually and quantitatively by calculating the average distance error (ADE). Results: The PCA breast shape models of the CC and MLO mammographic views based on six principal components, in which 99.2% and 98.0%, respectively, of the total variance of the dataset is contained, were found to be able to reproduce breast shapes with strong fidelity (CC view mean ADE = 0.90 mm, MLO view mean ADE = 1.43 mm) and to generate new clinically realistic shapes. The PCA models based on fewer principal components were also successful, but to a lesser degree, as the two-component model exhibited a mean ADE = 2.99 mm for the CC view, and a mean ADE = 4.63 mm for the MLO view. The four-component models exhibited a mean ADE = 1.47 mm for the CC view and a mean ADE = 2.14 mm for the MLO view. Paired t-tests of the ADE values of each image between models showed that these differences were statistically significant (max p-value = 0.0247). Visual examination of modeled breast shapes confirmed these results. Histograms of the PCA parameters associated with the six principal components were fitted with Gaussian distributions. The six

Objective models of compressed breast shapes undergoing mammography

International Nuclear Information System (INIS)

Feng, Steve Si Jia; Patel, Bhavika; Sechopoulos, Ioannis

2013-01-01

Purpose: To develop models of compressed breasts undergoing mammography based on objective analysis, that are capable of accurately representing breast shapes in acquired clinical images and generating new, clinically realistic shapes. Methods: An automated edge detection algorithm was used to catalogue the breast shapes of clinically acquired cranio-caudal (CC) and medio-lateral oblique (MLO) view mammograms from a large database of digital mammography images. Principal component analysis (PCA) was performed on these shapes to reduce the information contained within the shapes to a small number of linearly independent variables. The breast shape models, one of each view, were developed from the identified principal components, and their ability to reproduce the shape of breasts from an independent set of mammograms not used in the PCA, was assessed both visually and quantitatively by calculating the average distance error (ADE). Results: The PCA breast shape models of the CC and MLO mammographic views based on six principal components, in which 99.2% and 98.0%, respectively, of the total variance of the dataset is contained, were found to be able to reproduce breast shapes with strong fidelity (CC view mean ADE = 0.90 mm, MLO view mean ADE = 1.43 mm) and to generate new clinically realistic shapes. The PCA models based on fewer principal components were also successful, but to a lesser degree, as the two-component model exhibited a mean ADE = 2.99 mm for the CC view, and a mean ADE = 4.63 mm for the MLO view. The four-component models exhibited a mean ADE = 1.47 mm for the CC view and a mean ADE = 2.14 mm for the MLO view. Paired t-tests of the ADE values of each image between models showed that these differences were statistically significant (max p-value = 0.0247). Visual examination of modeled breast shapes confirmed these results. Histograms of the PCA parameters associated with the six principal components were fitted with Gaussian distributions. The six

A Framework for Realistic Modeling and Display of Object Surface Appearance

Science.gov (United States)

Darling, Benjamin A.

With advances in screen and video hardware technology, the type of content presented on computers has progressed from text and simple shapes to high-resolution photographs, photorealistic renderings, and high-definition video. At the same time, there have been significant advances in the area of content capture, with the development of devices and methods for creating rich digital representations of real-world objects. Unlike photo or video capture, which provide a fixed record of the light in a scene, these new technologies provide information on the underlying properties of the objects, allowing their appearance to be simulated for novel lighting and viewing conditions. These capabilities provide an opportunity to continue the computer display progression, from high-fidelity image presentations to digital surrogates that recreate the experience of directly viewing objects in the real world. In this dissertation, a framework was developed for representing objects with complex color, gloss, and texture properties and displaying them onscreen to appear as if they are part of the real-world environment. At its core, there is a conceptual shift from a traditional image-based display workflow to an object-based one. Instead of presenting the stored patterns of light from a scene, the objective is to reproduce the appearance attributes of a stored object by simulating its dynamic patterns of light for the real viewing and lighting geometry. This is accomplished using a computational approach where the physical light sources are modeled and the observer and display screen are actively tracked. Surface colors are calculated for the real spectral composition of the illumination with a custom multispectral rendering pipeline. In a set of experiments, the accuracy of color and gloss reproduction was evaluated by measuring the screen directly with a spectroradiometer. Gloss reproduction was assessed by comparing gonio measurements of the screen output to measurements of the

Anthropogenic and climatic influences on carbon fluxes from eastern North America to the Atlantic Ocean: A process-based modeling study

Science.gov (United States)

Tian, Hanqin; Yang, Qichun; Najjar, Raymond G.; Ren, Wei; Friedrichs, Marjorie A. M.; Hopkinson, Charles S.; Pan, Shufen

2015-04-01

The magnitude, spatiotemporal patterns, and controls of carbon flux from land to the ocean remain uncertain. Here we applied a process-based land model with explicit representation of carbon processes in streams and rivers to examine how changes in climate, land conversion, management practices, atmospheric CO2, and nitrogen deposition affected carbon fluxes from eastern North America to the Atlantic Ocean, specifically the Gulf of Maine (GOM), Middle Atlantic Bight (MAB), and South Atlantic Bight (SAB). Our simulation results indicate that the mean annual fluxes (±1 standard deviation) of dissolved organic carbon (DOC), particulate organic carbon (POC), and dissolved inorganic carbon (DIC) in the past three decades (1980-2008) were 2.37 ± 0.60, 1.06 ± 0.20, and 3.57 ± 0.72 Tg C yr-1, respectively. Carbon export demonstrated substantial spatial and temporal variability. For the region as a whole, the model simulates a significant decrease in riverine DIC fluxes from 1901 to 2008, whereas there were no significant trends in DOC or POC fluxes. In the SAB, however, there were significant declines in the fluxes of all three forms of carbon, and in the MAB subregion, DIC and POC fluxes declined significantly. The only significant trend in the GOM subregion was an increase in DIC flux. Climate variability was the primary cause of interannual variability in carbon export. Land conversion from cropland to forest was the primary factor contributing to decreases in all forms of C export, while nitrogen deposition and fertilizer use, as well as atmospheric CO2 increases, tended to increase DOC, POC, and DIC fluxes.

A Simple Physics-Based Model Predicts Oil Production from Thousands of Horizontal Wells in Shales

KAUST Repository

Patzek, Tadeusz

2017-10-18

Over the last six years, crude oil production from shales and ultra-deep GOM in the United States has accounted for most of the net increase of global oil production. Therefore, it is important to have a good predictive model of oil production and ultimate recovery in shale wells. Here we introduce a simple model of producing oil and solution gas from the horizontal hydrofractured wells. This model is consistent with the basic physics and geometry of the extraction process. We then apply our model thousands of wells in the Eagle Ford shale. Given well geometry, we obtain a one-dimensional nonlinear pressure diffusion equation that governs flow of mostly oil and solution gas. In principle, solutions of this equation depend on many parameters, but in practice and within a given oil shale, all but three can be fixed at typical values, leading to a nonlinear diffusion problem we linearize and solve exactly with a scaling

Visuo-motor coordination and internal models for object interception.

Science.gov (United States)

Zago, Myrka; McIntyre, Joseph; Senot, Patrice; Lacquaniti, Francesco

2009-02-01

Intercepting and avoiding collisions with moving objects are fundamental skills in daily life. Anticipatory behavior is required because of significant delays in transforming sensory information about target and body motion into a timed motor response. The ability to predict the kinematics and kinetics of interception or avoidance hundreds of milliseconds before the event may depend on several different sources of information and on different strategies of sensory-motor coordination. What are exactly the sources of spatio-temporal information and what are the control strategies remain controversial issues. Indeed, these topics have been the battlefield of contrasting views on how the brain interprets visual information to guide movement. Here we attempt a synthetic overview of the vast literature on interception. We discuss in detail the behavioral and neurophysiological aspects of interception of targets falling under gravity, as this topic has received special attention in recent years. We show that visual cues alone are insufficient to predict the time and place of interception or avoidance, and they need to be supplemented by prior knowledge (or internal models) about several features of the dynamic interaction with the moving object.

Two fuzzy possibilistic bi-objective zero-one programming models for outsourcing the equipment maintenance problem

Science.gov (United States)

Vahdani, Behnam; Jolai, Fariborz; Tavakkoli-Moghaddam, Reza; Meysam Mousavi, S.

2012-07-01

Maintenance outsourcing can be regarded as a strategic weapon to increase productivity and customer satisfaction in many companies, and this critical activity can be performed in a more efficient and effective way. This article presents two novel fuzzy possibilistic bi-objective zero-one programming (FPBOZOP) models for outsourcing of the equipment maintenance. In these models, cost parameters, including outsourcing cost, risk cost, time operations for performing the equipment maintenance and reliability level, as well as other influential parameters are considered through the outsourcing process. Moreover, the presented models can measure the capability of the company in doing different activities, unlike previous studies, in order to see the possibility of maintenance in-house, and can lead to make a best decision on the basis of the models' results. Both models are developed under uncertainty, which bring top managers the possibility of assigning more than one equipment or project to the supplier so that the profit is maximized, and the cost is minimized by considering bi-objectives concurrently. Then, a new fuzzy mathematical programming based possibilistic approach is introduced as a solution methodology from the recent literature to solve the proposed bi-objective zero-one programming (BOZOP) models and to reach a preferred compromise solution. Furthermore, a real-case study is utilized to demonstrate and to validate the effectiveness of the presented models. The computational results revealed that the models can be implemented in variety of problems in the domain of the equipment maintenance outsourcing and project outsourcing either from theory or application perspectives.

Specification of Concurrent Objects

DEFF Research Database (Denmark)

Sørensen, Morten U.

relation over two objects and an event. In the model, objects can be composed by parallel composition, encapsulation, and hiding of operations. Refinement between objects is defined as fair trace inclusion.A specification language is presented where objects can be specified operationally by abstract...

Multi-Objective Nonlinear Model Predictive Control: Lexicographic Method

OpenAIRE

Zheng, Tao; Wu, Gang; Liu, Guang-Hong; Ling, Qing

2010-01-01

In this chapter, to avoid the disadvantages of weight coefficients in multi-objective dynamic optimization, lexicographic (completely stratified) and partially stratified frameworks of multi-objective controller are proposed. The lexicographic framework is absolutely prioritydriven and the partially stratified framework is a modification of it, they both can solve the multi-objective control problem with the concept of priority for objective’s relative importance, while the latter one is mo...

Coastal aquifer management based on surrogate models and multi-objective optimization

Science.gov (United States)

Mantoglou, A.; Kourakos, G.

2011-12-01

The demand for fresh water in coastal areas and islands can be very high, especially in summer months, due to increased local needs and tourism. In order to satisfy demand, a combined management plan is proposed which involves: i) desalinization (if needed) of pumped water to a potable level using reverse osmosis and ii) injection of biologically treated waste water into the aquifer. The management plan is formulated into a multiobjective optimization framework, where simultaneous minimization of economic and environmental costs is desired; subject to a constraint to satisfy demand. The method requires modeling tools, which are able to predict the salinity levels of the aquifer in response to different alternative management scenarios. Variable density models can simulate the interaction between fresh and saltwater; however, they are computationally intractable when integrated in optimization algorithms. In order to alleviate this problem, a multi objective optimization algorithm is developed combining surrogate models based on Modular Neural Networks [MOSA(MNN)]. The surrogate models are trained adaptively during optimization based on a Genetic Algorithm. In the crossover step of the genetic algorithm, each pair of parents generates a pool of offspring. All offspring are evaluated based on the fast surrogate model. Then only the most promising offspring are evaluated based on the exact numerical model. This eliminates errors in Pareto solution due to imprecise predictions of the surrogate model. Three new criteria for selecting the most promising offspring were proposed, which improve the Pareto set and maintain the diversity of the optimum solutions. The method has important advancements compared to previous methods, e.g. alleviation of propagation of errors due to surrogate model approximations. The method is applied to a real coastal aquifer in the island of Santorini which is a very touristy island with high water demands. The results show that the algorithm

An integrated approach to engineering curricula improvement with multi-objective decision modeling and linear programming

Science.gov (United States)

Shea, John E.

The structure of engineering curricula currently in place at most colleges and universities has existed since the early 1950's, and reflects an historical emphasis on a solid foundation in math, science, and engineering science. However, there is often not a close match between elements of the traditional engineering education, and the skill sets that graduates need to possess for success in the industrial environment. Considerable progress has been made to restructure engineering courses and curricula. What is lacking, however, are tools and methodologies that incorporate the many dimensions of college courses, and how they are structured to form a curriculum. If curriculum changes are to be made, the first objective must be to determine what knowledge and skills engineering graduates need to possess. To accomplish this, a set of engineering competencies was developed from existing literature, and used in the development of a comprehensive mail survey of alumni, employers, students and faculty. Respondents proposed some changes to the topics in the curriculum and recommended that work to improve the curriculum be focused on communication, problem solving and people skills. The process of designing a curriculum is similar to engineering design, with requirements that must be met, and objectives that must be optimized. From this similarity came the idea for developing a linear, additive, multi-objective model that identifies the objectives that must be considered when designing a curriculum, and contains the mathematical relationships necessary to quantify the value of a specific alternative. The model incorporates the three primary objectives of engineering topics, skills, and curriculum design principles and uses data from the survey. It was used to design new courses, to evaluate various curricula alternatives, and to conduct sensitivity analysis to better understand their differences. Using the multi-objective model to identify the highest scoring curriculum

How do en route events around the Gulf of Mexico influence landbird populations

Science.gov (United States)

Cohen, Emily B.; Barrow, Wylie C.; Buler, Jeffrey J.; Deppe, Jill L.; Farnsworth, Andrew; Marra, Peter P.; McWilliams, Scott R.; Mehlman, David W; Wilson, R. Randy; Woodrey, Mark S; Moore, Frank R.

2017-01-01

Habitats around the Gulf of Mexico (GOM) provide critical resources for Nearctic–Neotropical migratory landbirds, the majority of which travel across or around the GOM every spring and fall as they migrate between temperate breeding grounds in North America and tropical wintering grounds in the Caribbean and Central and South America. At the same time, ecosystems in the GOM are changing rapidly, with unknown consequences for migratory landbird populations, many of which are experiencing population declines. In general, the extent to which events encountered en route limit migratory bird populations is not well understood. At the same time, information from weather surveillance radar, stable isotopes, tracking, eBird, and genetic datasets is increasingly available to address many of the unanswered questions about bird populations that migrate through stopover and airspace habitats in the GOM. We review the state of the science and identify key research needs to understand the impacts of en route events around the GOM region on populations of intercontinental landbird migrants that breed in North America, including: (1) distribution, timing, and habitat associations; (2) habitat characteristics and quality; (3) migratory connectivity; and (4) threats to and current conservation status of airspace and stopover habitats. Finally, we also call for the development of unified and comprehensive long-term monitoring guidelines and international partnerships to advance our understanding of the role of habitats around the GOM in supporting migratory landbird populations moving between temperate breeding grounds and wintering grounds in Mexico, Central and South America, and the Caribbean.

Static Object Detection Based on a Dual Background Model and a Finite-State Machine

Directory of Open Access Journals (Sweden)

Heras Evangelio Rubén

2011-01-01

Full Text Available Detecting static objects in video sequences has a high relevance in many surveillance applications, such as the detection of abandoned objects in public areas. In this paper, we present a system for the detection of static objects in crowded scenes. Based on the detection of two background models learning at different rates, pixels are classified with the help of a finite-state machine. The background is modelled by two mixtures of Gaussians with identical parameters except for the learning rate. The state machine provides the meaning for the interpretation of the results obtained from background subtraction; it can be implemented as a look-up table with negligible computational cost and it can be easily extended. Due to the definition of the states in the state machine, the system can be used either full automatically or interactively, making it extremely suitable for real-life surveillance applications. The system was successfully validated with several public datasets.

Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

Directory of Open Access Journals (Sweden)

Kaveh Khalili-Damghani

2017-07-01

Full Text Available In this paper a multi-period multi-product multi-objective aggregate production planning (APP model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method.

Multi-objective optimization for generating a weighted multi-model ensemble

Science.gov (United States)

Lee, H.

2017-12-01

Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic

An Efficient Role and Object Based Access Control Model Implemented in a PDM System

Institute of Scientific and Technical Information of China (English)

HUANG Xiaowen; TAN Jian; HUANG Xiangguo

2006-01-01

An effective and reliable access control is crucial to a PDM system. This article has discussed the commonly used access control models, analyzed their advantages and disadvantages, and proposed a new Role and Object based access control model that suits the particular needs of a PDM system. The new model has been implemented in a commercial PDM system, which has demonstrated enhanced flexibility and convenience.

Alternative futures of dissolved inorganic nitrogen export from the Mississippi River Basin: influence of crop management, atmospheric deposition, and population growth

Science.gov (United States)

Nitrogen (N) export from the Mississippi River Basin contributes to seasonal hypoxia in the Gulf of Mexico (GOM). We explored monthly dissolved inorganic N (DIN) export to the GOM for a historical year (2002) and two future scenarios (year 2022) by linking macroeonomic energy, ag...

Structuring research methods and data with the research object model: genomics workflows as a case study.

Science.gov (United States)

Hettne, Kristina M; Dharuri, Harish; Zhao, Jun; Wolstencroft, Katherine; Belhajjame, Khalid; Soiland-Reyes, Stian; Mina, Eleni; Thompson, Mark; Cruickshank, Don; Verdes-Montenegro, Lourdes; Garrido, Julian; de Roure, David; Corcho, Oscar; Klyne, Graham; van Schouwen, Reinout; 't Hoen, Peter A C; Bechhofer, Sean; Goble, Carole; Roos, Marco

2014-01-01

One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e.g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows. We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as "which particular data was input to a particular workflow to test a particular hypothesis?", and "which particular conclusions were drawn from a particular workflow?". Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well. The Research Object is available at http://www.myexperiment.org/packs/428 The Wf4Ever Research Object Model is available at http://wf4ever.github.io/ro.

Graphene oxide membrane as an efficient extraction and ionization substrate for spray-mass spectrometric analysis of malachite green and its metabolite in fish samples.

Science.gov (United States)

Wei, Shih-Chun; Fan, Shen; Lien, Chia-Wen; Unnikrishnan, Binesh; Wang, Yi-Sheng; Chu, Han-Wei; Huang, Chih-Ching; Hsu, Pang-Hung; Chang, Huan-Tsung

2018-03-20

A graphene oxide (GO) nanosheet-modified N + -nylon membrane (GOM) has been prepared and used as an extraction and spray-ionization substrate for robust mass spectrometric detection of malachite green (MG), a highly toxic disinfectant in liquid samples and fish meat. The GOM is prepared by self-deposition of GO thin film onto an N + -nylon membrane, which has been used for efficient extraction of MG in aquaculture water samples or homogenized fish meat samples. Having a dissociation constant of 2.17 × 10 -9  M -1 , the GOM allows extraction of approximately 98% of 100 nM MG. Coupling of the GOM-spray with an ion-trap mass spectrometer allows quantitation of MG in aquaculture freshwater and seawater samples down to nanomolar levels. Furthermore, the system possesses high selectivity and sensitivity for the quantitation of MG and its metabolite (leucomalachite green) in fish meat samples. With easy extraction and efficient spray ionization properties of GOM, this membrane spray-mass spectrometry technique is relatively simple and fast in comparison to the traditional LC-MS/MS methods for the quantitation of MG and its metabolite in aquaculture products. Copyright © 2017 Elsevier B.V. All rights reserved.

Protein Nano-Object Integrator: Generating atomic-style objects for use in molecular biophysics

Science.gov (United States)

Smith, Nicholas David Fenimore

As researchers obtain access to greater and greater amounts of computational power, focus has shifted towards modeling macroscopic objects while still maintaining atomic-level details. The Protein Nano-Object Integrator (ProNOI) presented here has been designed to provide a streamlined solution for creating and designing macro-scale objects with atomic-level details to be used in molecular simulations and tools. To accomplish this, two different interfaces were developed: a Protein Data Bank (PDB), PDB-focused interface for generating regularly-shaped three-dimensional atomic objects and a 2D image-based interface for tracing images with irregularly shaped objects and then extracting three-dimensional models from these images. Each interface is dependent upon the C++ backend utility for generating the objects and ensures that the output is consistent across each program. The objects are exported in a standard PDB format which allows for the visualization and manipulation of the objects via standard tools available in Molecular Computational Biophysics.

OntoVIP: an ontology for the annotation of object models used for medical image simulation.

Science.gov (United States)

Gibaud, Bernard; Forestier, Germain; Benoit-Cattin, Hugues; Cervenansky, Frédéric; Clarysse, Patrick; Friboulet, Denis; Gaignard, Alban; Hugonnard, Patrick; Lartizien, Carole; Liebgott, Hervé; Montagnat, Johan; Tabary, Joachim; Glatard, Tristan

2014-12-01

This paper describes the creation of a comprehensive conceptualization of object models used in medical image simulation, suitable for major imaging modalities and simulators. The goal is to create an application ontology that can be used to annotate the models in a repository integrated in the Virtual Imaging Platform (VIP), to facilitate their sharing and reuse. Annotations make the anatomical, physiological and pathophysiological content of the object models explicit. In such an interdisciplinary context we chose to rely on a common integration framework provided by a foundational ontology, that facilitates the consistent integration of the various modules extracted from several existing ontologies, i.e. FMA, PATO, MPATH, RadLex and ChEBI. Emphasis is put on methodology for achieving this extraction and integration. The most salient aspects of the ontology are presented, especially the organization in model layers, as well as its use to browse and query the model repository. Copyright © 2014 Elsevier Inc. All rights reserved.

Accessing OSI Managed Objects from ANSAware

OpenAIRE

Genilloud, Guy; Gay, David

1995-01-01

This paper presents a mechanism allowing an ODP compliant distributed system, ANSA, to access OSI network management objects as if they were ANSA objects. It defines a mapping from the OSI object model to the ANSA object model, and it specifies how an adapter implements this mapping.

A genetic algorithm for a bi-objective mathematical model for dynamic virtual cell formation problem

Science.gov (United States)

Moradgholi, Mostafa; Paydar, Mohammad Mahdi; Mahdavi, Iraj; Jouzdani, Javid

2016-09-01

Nowadays, with the increasing pressure of the competitive business environment and demand for diverse products, manufacturers are force to seek for solutions that reduce production costs and rise product quality. Cellular manufacturing system (CMS), as a means to this end, has been a point of attraction to both researchers and practitioners. Limitations of cell formation problem (CFP), as one of important topics in CMS, have led to the introduction of virtual CMS (VCMS). This research addresses a bi-objective dynamic virtual cell formation problem (DVCFP) with the objective of finding the optimal formation of cells, considering the material handling costs, fixed machine installation costs and variable production costs of machines and workforce. Furthermore, we consider different skills on different machines in workforce assignment in a multi-period planning horizon. The bi-objective model is transformed to a single-objective fuzzy goal programming model and to show its performance; numerical examples are solved using the LINGO software. In addition, genetic algorithm (GA) is customized to tackle large-scale instances of the problems to show the performance of the solution method.

Improved Specification of Transboundary Air Pollution over the Gulf of Mexico Using Satellite Observations

Science.gov (United States)

Pour Biazar, A.; Khan, M. N.; Park, Y. H.; McNider, R. T.; Cameron, B.

2010-12-01

The assessment of potential environmental impact of oil and gas operations in the Gulf of Mexico (GoM) and in particular the onshore air quality impact of such operations is important to State and Federal regulatory agencies. In adapting sound policies for control strategies, it is crucial to assess the impact of local pollution versus transboundary air pollution, and in a region such as GoM with scarce monitoring capability over open waters such distinctions represents a challenge. Furthermore, GoM region can be impacted by the recirculation of pollution in the southeastern United States. The current study examines the efficacy of utilizing the newly available satellite observations of aerosols and trace gases in air quality impacts assessment for addressing these issues. In particular, ozone profiles from the Tropospheric Emission Spectrometer (TES) and Ozone Monitoring Instrument (OMI) onboard Aura and aerosol products from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua satellites were utilized in a modeling study during August 2006. The satellite observations were used in the specification of the background and lateral boundary and also once daily for the re-adjustment of the concentration fields. The results were then evaluated against ozonesonde and surface observations. The utilization of OMI ozone profiles significantly improved model performance in the free troposphere and the use of MODIS aerosol products substantially enhanced model prediction of aerosols in the boundary layer. Neither OMI nor TES provide adequate information in the boundary layer with respect to O3 and as a result they can only marginally impact ozone predictions in the boundary layer. The utilization of the satellite data for lateral boundary condition (BC) was helpful in the realization of transboundary transport of pollution. The hypothesis that the recirculation of pollution from Northeast Corridor can play a role over the Gulf of Mexico was tested and

Piles of objects

KAUST Repository

Hsu, Shu-Wei; Keyser, John

2010-01-01

We present a method for directly modeling piles of objects in multi-body simulations. Piles of objects represent some of the more interesting, but also most time-consuming portion of simulation. We propose a method for reducing computation in many

Land Use Allocation Based on a Multi-Objective Artificial Immune Optimization Model: An Application in Anlu County, China

Directory of Open Access Journals (Sweden)

Xiaoya Ma

2015-11-01

Full Text Available As the main feature of land use planning, land use allocation (LUA optimization is an important means of creating a balance between the land-use supply and demand in a region and promoting the sustainable utilization of land resources. In essence, LUA optimization is a multi-objective optimization problem under the land use supply and demand constraints in a region. In order to obtain a better sustainable multi-objective LUA optimization solution, the present study proposes a LUA model based on the multi-objective artificial immune optimization algorithm (MOAIM-LUA model. The main achievements of the present study are as follows: (a the land-use supply and demand factors are analyzed and the constraint conditions of LUA optimization problems are constructed based on the analysis framework of the balance between the land use supply and demand; (b the optimization objectives of LUA optimization problems are defined and modeled using ecosystem service value theory and land rent and price theory; and (c a multi-objective optimization algorithm is designed for solving multi-objective LUA optimization problems based on the novel immune clonal algorithm (NICA. On the basis of the aforementioned achievements, MOAIM-LUA was applied to a real case study of land-use planning in Anlu County, China. Compared to the current land use situation in Anlu County, optimized LUA solutions offer improvements in the social and ecological objective areas. Compared to the existing models, such as the non-dominated sorting genetic algorithm-II, experimental results demonstrate that the model designed in the present study can obtain better non-dominated solution sets and is superior in terms of algorithm stability.

Objects of consciousness

Directory of Open Access Journals (Sweden)

Donald David Hoffman

2014-06-01

Full Text Available Current models of visual perception typically assume that human vision estimates true properties of physical objects, properties that exist even if unperceived. However, recent studies of perceptual evolution, using evolutionary games and genetic algorithms, reveal that natural selection often drives true perceptions to extinction when they compete with perceptions tuned to fitness rather than truth: Perception guides adaptive behavior; it does not estimate a preexisting physical truth. Moreover, shifting from evolutionary biology to quantum physics, there is reason to disbelieve in preexist-ing physical truths: Certain interpretations of quantum theory deny that dynamical properties of physical objects have defi-nite values when unobserved. In some of these interpretations the observer is fundamental, and wave functions are com-pendia of subjective probabilities, not preexisting elements of physical reality. These two considerations, from evolutionary biology and quantum physics, suggest that current models of object perception require fundamental reformulation. Here we begin such a reformulation, starting with a formal model of consciousness that we call a conscious agent. We develop the dynamics of interacting conscious agents, and study how the perception of objects and space-time can emerge from such dynamics. We show that one particular object, the quantum free particle, has a wave function that is identical in form to the harmonic functions that characterize the asymptotic dynamics of conscious agents; particles are vibrations not of strings but of interacting conscious agents. This allows us to reinterpret physical properties such as position, momentum, and energy as properties of interacting conscious agents, rather than as preexisting physical truths. We sketch how this approach might extend to the perception of relativistic quantum objects, and to classical objects of macroscopic scale.

A NEW WASTE CLASSIFYING MODEL: HOW WASTE CLASSIFICATION CAN BECOME MORE OBJECTIVE?

Directory of Open Access Journals (Sweden)

Burcea Stefan Gabriel

2015-07-01

documents available in the virtual space, on the websites of certain international organizations involved in the wide and complex issue of waste management. The second part of the paper contains a proposal classification model with four main criteria in order to make waste classification a more objective process. The new classification model has the main role of transforming the traditional patterns of waste classification into an objective waste classification system and a second role of eliminating the strong contextuality of the actual waste classification models.

Multi-objective game-theory models for conflict analysis in reservoir watershed management.

Science.gov (United States)

Lee, Chih-Sheng

2012-05-01

This study focuses on the development of a multi-objective game-theory model (MOGM) for balancing economic and environmental concerns in reservoir watershed management and for assistance in decision. Game theory is used as an alternative tool for analyzing strategic interaction between economic development (land use and development) and environmental protection (water-quality protection and eutrophication control). Geographic information system is used to concisely illustrate and calculate the areas of various land use types. The MOGM methodology is illustrated in a case study of multi-objective watershed management in the Tseng-Wen reservoir, Taiwan. The innovation and advantages of MOGM can be seen in the results, which balance economic and environmental concerns in watershed management and which can be interpreted easily by decision makers. For comparison, the decision-making process using conventional multi-objective method to produce many alternatives was found to be more difficult. Copyright © 2012 Elsevier Ltd. All rights reserved.

Subsurface gas hydrates in the northern Gulf of Mexico

Science.gov (United States)

Boswell, Ray; Collett, Timothy S.; Frye, Matthew; Shedd, William; McConnell, Daniel R.; Shelander, Dianna

2012-01-01

The northernGulf of Mexico (GoM) has long been a focus area for the study of gashydrates. Throughout the 1980s and 1990s, work focused on massive gashydrates deposits that were found to form at and near the seafloor in association with hydrocarbon seeps. However, as global scientific and industrial interest in assessment of the drilling hazards and resource implications of gashydrate accelerated, focus shifted to understanding the nature and abundance of "buried" gashydrates. Through 2005, despite the drilling of more than 1200 oil and gas industry wells through the gashydrate stability zone, published evidence of significant sub-seafloor gashydrate in the GoM was lacking. A 2005 drilling program by the GoM GasHydrate Joint Industry Project (the JIP) provided an initial confirmation of the occurrence of gashydrates below the GoM seafloor. In 2006, release of data from a 2003 industry well in Alaminos Canyon 818 provided initial documentation of gashydrate occurrence at high concentrations in sand reservoirs in the GoM. From 2006 to 2008, the JIP facilitated the integration of geophysical and geological data to identify sites prospective for gashydrate-bearing sands, culminating in the recommendation of numerous drilling targets within four sites spanning a range of typical deepwater settings. Concurrent with, but independent of, the JIP prospecting effort, the Bureau of Ocean Energy Management (BOEM) conducted a preliminary assessment of the GoM gashydratepetroleum system, resulting in an estimate of 607 trillion cubic meters (21,444 trillion cubic feet) gas-in-place of which roughly one-third occurs at expected high concentrations in sand reservoirs. In 2009, the JIP drilled seven wells at three sites, discovering gashydrate at high saturation in sand reservoirs in four wells and suspected gashydrate at low to moderate saturations in two other wells. These results provide an initial confirmation of the complex nature and occurrence of gashydrate-bearing sands in

The Role of Transforms in Gulf of Mexico Opening

Science.gov (United States)

Lundin, E.; Doré, A. G.

2017-12-01

The curious pie-shaped Gulf of Mexico (GoM) may be considered a high-angle back-arc basin to the Pacific Ocean. Opening was strongly facilitated by transforms, including a terminal transform on its Pacific side. GoM also formed synchronously with the nearby Central Atlantic when Gondwanaland pulled away from Laurasia in the Jurassic. Notably, GoM's oceanic crust never connected with that of the Atlantic, and the isolated nature of this small ocean led to periodically confined conditions that influenced the petroleum system. Of particular importance are the deposition of Callovian age salt and Tithonian age source rocks. The central part of GoM is generally accepted as underlain by oceanic crust, but the position of the continent-ocean boundaries (COB) is debated, as well as the nature of intervening crust. We favor an interpretation of the COBs marked by the regional scale, large-amplitude Houston, Florida, and Campeche magnetic anomalies, in turn probably reflecting seaward dipping reflectors of magma-rich margins. GoM's unusual shape may indirectly represent utilization of pre-existing transforms during the break-up of Pangea. Transforms represent long, linear weaknesses where the crust and lithosphere is already broken. Transforms seem to have governed the break-up of several oceanic segments in the North Atlantic and Arctic. The Suwanne suture of the Rheic Ocean is a pronounced magnetic anomaly that crosses Georgia-Florida and becomes aligned with the Houston magnetic anomaly, which here is interpreted as the northern COB to GoM. The Suwanne suture is oriented at high angle to the rest of the Rheic suture along the Appalachians and probably experienced lateral motion during the transpressional closure of the Rheic Ocean. This transform arguably represents a weak element in the Ouachita-Marathon orogen that allowed the Yucatan microcontinent to easily be plucked from the North American margin during the dispersal of Pangea, forming the GoM in the process. This

Recovery and Lithologic Analysis of Sediment from Hole UT-GOM2-1-H002, Green Canyon 955, Northern Gulf of Mexico

Science.gov (United States)

Kinash, N.; Cook, A.; Sawyer, D.; Heber, R.

2017-12-01

In May 2017 the University of Texas led a drilling and pressure coring expedition in the northern Gulf of Mexico, UT-GOM2-01. The holes were located in Green Canyon Block 955, where the Gulf of Mexico Joint Industry Project Leg II identified an approximately 100m thick hydrate-filled course-grained levee unit in 2009. Two separate wells were drilled into this unit: Holes H002 and H005. In Hole H002, a cutting shoe drill bit was used to collect the pressure cores, and only 1 of the 8 cores collected was pressurized during recovery. The core recovery in Hole H002 was generally poor, about 34%, while the only pressurized core had 45% recovery. In Hole H005, a face bit was used during pressure coring where 13 cores were collected and 9 cores remained pressurized. Core recovery in Hole H005 was much higher, at about 75%. The type of bit was not the only difference between the holes, however. Drilling mud was used throughout the drilling and pressure coring of Hole H002, while only seawater was used during the first 80m of pressure cores collected in Hole H005. Herein we focus on lithologic analysis of Hole H002 with the goal of documenting and understanding core recovery in Hole H002 to compare with Hole H005. X-ray Computed Tomography (XCT) images were collected by Geotek on pressurized cores, mostly from Hole H005, and at Ohio State on unpressurized cores, mostly from Hole H002. The XCT images of unpressurized cores show minimal sedimentary structures and layering, unlike the XCT images acquired on the pressurized, hydrate-bearing cores. Only small sections of the unpressurized cores remained intact. The unpressurized cores appear to have two prominent facies: 1) silt that did not retain original sedimentary fabric and often was loose within the core barrel, and 2) dense mud sections with some sedimentary structures and layering present. On the XCT images, drilling mud appears to be concentrated on the sides of cores, but also appears in layers and fractures within

A multi-objective reliable programming model for disruption in supply chain

Directory of Open Access Journals (Sweden)

Emran Mohammadi

2013-05-01

Full Text Available One of the primary concerns on supply chain management is to handle risk components, properly. There are various reasons for having risk in supply chain such as natural disasters, unexpected incidents, etc. When a series of facilities are built and deployed, one or a number of them could probably fail at any time due to bad weather conditions, labor strikes, economic crises, sabotage or terrorist attacks and changes in ownership of the system. The objective of risk management is to reduce the effects of different domains to an acceptable level. To overcome the risk, we propose a reliable capacitated supply chain network design (RSCND model by considering random disruptions risk in both distribution centers and suppliers. The proposed study of this paper considers three objective functions and the implementation is verified using some instance.

A 3D City Model with Dynamic Behaviour Based on Geospatial Managed Objects

DEFF Research Database (Denmark)

Kjems, Erik; Kolář, Jan

2014-01-01

of a geographic data representation of the world. The combination of 3D city models and real time information based systems though can provide a whole new setup for data fusion within an urban environment and provide time critical information preserving our limited resources in the most sustainable way. Using 3D......One of the major development efforts within the GI Science domain are pointing at real time information coming from geographic referenced features in general. At the same time 3D City models are mostly justified as being objects for visualization purposes rather than constituting the foundation...... occasions we have been advocating for a new and advanced formulation of real world features using the concept of Geospatial Managed Objects (GMO). This chapter presents the outcome of the InfraWorld project, a 4 million Euro project financed primarily by the Norwegian Research Council where the concept...

Why do satellite imageries show exceptionally high chlorophyll in the Gulf of mannar and the Palk bay during the norteast monsoon?.

Digital Repository Service at National Institute of Oceanography (India)

Jyothibabu, R.; Madhu, N.V.; Jagadeesan, L.; Anjusha, A.; Mohan, A.P.; Ullas, N.; Sudheesh, K.; Karnan, C.

in the Indian sector of the GoM and the PB in January 2011 showed significant overestimations in the satellite data. This error was much higher in the PB (60–80 %) as compared to the GoM (18–28 %). The multivariate analyses evidenced that the exceptionally high...

Virtual memory support for distributed computing environments using a shared data object model

Science.gov (United States)

Huang, F.; Bacon, J.; Mapp, G.

1995-12-01

Conventional storage management systems provide one interface for accessing memory segments and another for accessing secondary storage objects. This hinders application programming and affects overall system performance due to mandatory data copying and user/kernel boundary crossings, which in the microkernel case may involve context switches. Memory-mapping techniques may be used to provide programmers with a unified view of the storage system. This paper extends such techniques to support a shared data object model for distributed computing environments in which good support for coherence and synchronization is essential. The approach is based on a microkernel, typed memory objects, and integrated coherence control. A microkernel architecture is used to support multiple coherence protocols and the addition of new protocols. Memory objects are typed and applications can choose the most suitable protocols for different types of object to avoid protocol mismatch. Low-level coherence control is integrated with high-level concurrency control so that the number of messages required to maintain memory coherence is reduced and system-wide synchronization is realized without severely impacting the system performance. These features together contribute a novel approach to the support for flexible coherence under application control.

From Functions to Object-Orientation by Abstraction

OpenAIRE

Diertens, Bob

2012-01-01

In previous work we developed a framework of computational models for function and object execution. The models on an higher level of abstraction in this framework allow for concurrent execution of functions and objects. We show that the computational model for object execution complies with the fundamentals of object-orientation.

Oil-Spill Analysis: Gulf of Mexico Outer Continental Shelf (OCS) Lease Sales, Eastern Planning Area, 2003-2007 and Gulfwide OCS Program, 2003-2042

Science.gov (United States)

2002-09-01

The Federal Government plans to offer U.S. Outer Continental Shelf (OCS) lands in the Eastern Planning Area of the Gulf of Mexico (GOM) for oil and gas leasing. This report summarizes results of that analysis, the objective of which was to estimate the risk of oil-spill contact to sensitive offshore and onshore environmental resources and socioeconomic features from oil spills accidentally occurring from the OCS activities.

SODA: Smart Objects, Dumb Archives

Science.gov (United States)

Nelson, Michael L.; Maly, Kurt; Zubair, Mohammad; Shen, Stewart N. T.

2004-01-01

We present the Smart Object, Dumb Archive (SODA) model for digital libraries (DLs). The SODA model transfers functionality traditionally associated with archives to the archived objects themselves. We are exploiting this shift of responsibility to facilitate other DL goals, such as interoperability, object intelligence and mobility, and heterogeneity. Objects in a SODA DL negotiate presentation of content and handle their own terms and conditions. In this paper we present implementations of our smart objects, buckets, and our dumb archive (DA). We discuss the status of buckets and DA and how they are used in a variety of DL projects.

ADPROCLUS: a graphical user interface for fitting additive profile clustering models to object by variable data matrices.

Science.gov (United States)

Wilderjans, Tom F; Ceulemans, Eva; Van Mechelen, Iven; Depril, Dirk

2011-03-01

In many areas of psychology, one is interested in disclosing the underlying structural mechanisms that generated an object by variable data set. Often, based on theoretical or empirical arguments, it may be expected that these underlying mechanisms imply that the objects are grouped into clusters that are allowed to overlap (i.e., an object may belong to more than one cluster). In such cases, analyzing the data with Mirkin's additive profile clustering model may be appropriate. In this model: (1) each object may belong to no, one or several clusters, (2) there is a specific variable profile associated with each cluster, and (3) the scores of the objects on the variables can be reconstructed by adding the cluster-specific variable profiles of the clusters the object in question belongs to. Until now, however, no software program has been publicly available to perform an additive profile clustering analysis. For this purpose, in this article, the ADPROCLUS program, steered by a graphical user interface, is presented. We further illustrate its use by means of the analysis of a patient by symptom data matrix.

Identification of mutated driver pathways in cancer using a multi-objective optimization model.

Science.gov (United States)

Zheng, Chun-Hou; Yang, Wu; Chong, Yan-Wen; Xia, Jun-Feng

2016-05-01

New-generation high-throughput technologies, including next-generation sequencing technology, have been extensively applied to solve biological problems. As a result, large cancer genomics projects such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium are producing large amount of rich and diverse data in multiple cancer types. The identification of mutated driver genes and driver pathways from these data is a significant challenge. Genome aberrations in cancer cells can be divided into two types: random 'passenger mutation' and functional 'driver mutation'. In this paper, we introduced a Multi-objective Optimization model based on a Genetic Algorithm (MOGA) to solve the maximum weight submatrix problem, which can be employed to identify driver genes and driver pathways promoting cancer proliferation. The maximum weight submatrix problem defined to find mutated driver pathways is based on two specific properties, i.e., high coverage and high exclusivity. The multi-objective optimization model can adjust the trade-off between high coverage and high exclusivity. We proposed an integrative model by combining gene expression data and mutation data to improve the performance of the MOGA algorithm in a biological context. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computational Modelling of the Neural Representation of Object Shape in the Primate Ventral Visual System

Directory of Open Access Journals (Sweden)

Akihiro eEguchi

2015-08-01

Full Text Available Neurons in successive stages of the primate ventral visual pathway encode the spatial structure of visual objects. In this paper, we investigate through computer simulation how these cell firing properties may develop through unsupervised visually-guided learning. Individual neurons in the model are shown to exploit statistical regularity and temporal continuity of the visual inputs during training to learn firing properties that are similar to neurons in V4 and TEO. Neurons in V4 encode the conformation of boundary contour elements at a particular position within an object regardless of the location of the object on the retina, while neurons in TEO integrate information from multiple boundary contour elements. This representation goes beyond mere object recognition, in which neurons simply respond to the presence of a whole object, but provides an essential foundation from which the brain is subsequently able to recognise the whole object.

Structural modeling of the production quality as a multidimensional object of measurement and control

OpenAIRE

Зубрецкая, Наталья Анатольевна

2015-01-01

The structural-analytical models of product quality as a multidimensional process of evaluation, measurement and control are developed. The product quality is represented as a multi-factor, multi-criteria and multi-parameter estimation object. This structural formalization of quality demonstrates the multidimensional qualities: comprehensiveness due to a set of environmental factors; multicriteriality due collectively evaluated quality criteria; multiparameter information models that describe...

The Object Oriented Model of the AD Cycle and its Implementation

CERN Document Server

Mulder, H

1999-01-01

Central to the control and operation of the CERN Antiproton Decelerator (AD) is the deceleration cycle which involves accelerator sub-systems such as magnet current, timing, RF systems etc. It is fundamental to AD operation that these sub-system cycles are coherent and an integrated AD Cycle Editor has been proposed to guarantee this coherence. In the object oriented model of the AD, the highest level of abstraction is the class "AD Cycle" which is described in physical terms with an associated set of operations. The accelerator sub-systems inherit from this class thus guaranteeing coherence. The model is implemented in the AD Cycle Editor, which acts on the AD Cycle class and implicitly therefore also on the sub-systems. In this paper the model of the AD Cycle and sub-systems are discussed. The AD Cycle Editor is also presented with comments on the results of the commissioned system.

Two Types of Visual Objects

Directory of Open Access Journals (Sweden)

Skrzypulec Błażej

2015-06-01

Full Text Available While it is widely accepted that human vision represents objects, it is less clear which of the various philosophical notions of ‘object’ adequately characterizes visual objects. In this paper, I show that within contemporary cognitive psychology visual objects are characterized in two distinct, incompatible ways. On the one hand, models of visual organization describe visual objects in terms of combinations of features, in accordance with the philosophical bundle theories of objects. However, models of visual persistence apply a notion of visual objects that is more similar to that endorsed in philosophical substratum theories. Here I discuss arguments that might show either that only one of the above notions of visual objects is adequate in the context of human vision, or that the category of visual objects is not uniform and contains entities properly characterized by different philosophical conceptions.

An object-oriented description method of EPMM process

Science.gov (United States)

Jiang, Zuo; Yang, Fan

2017-06-01

In order to use the object-oriented mature tools and language in software process model, make the software process model more accord with the industrial standard, it’s necessary to study the object-oriented modelling of software process. Based on the formal process definition in EPMM, considering the characteristics that Petri net is mainly formal modelling tool and combining the Petri net modelling with the object-oriented modelling idea, this paper provides this implementation method to convert EPMM based on Petri net into object models based on object-oriented description.

Modeling of Geological Objects and Geophysical Fields Using Haar Wavelets

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A. S. Dolgal

2014-12-01

Full Text Available This article is a presentation of application of the fast wavelet transform with basic Haar functions for modeling the structural surfaces and geophysical fields, characterized by fractal features. The multiscale representation of experimental data allows reducing significantly a cost of the processing of large volume data and improving the interpretation quality. This paper presents the algorithms for sectionally prismatic approximation of geological objects, for preliminary estimation of the number of equivalent sources for the analytical approximation of fields, and for determination of the rock magnetization in the upper part of the geological section.

Taming waveform inversion non-linearity through phase unwrapping of the model and objective functions

KAUST Repository

Alkhalifah, Tariq Ali

2012-09-25

Traveltime inversion focuses on the geometrical features of the waveform (traveltimes), which is generally smooth, and thus, tends to provide averaged (smoothed) information of the model. On other hand, general waveform inversion uses additional elements of the wavefield including amplitudes to extract higher resolution information, but this comes at the cost of introducing non-linearity to the inversion operator, complicating the convergence process. We use unwrapped phase-based objective functions in waveform inversion as a link between the two general types of inversions in a domain in which such contributions to the inversion process can be easily identified and controlled. The instantaneous traveltime is a measure of the average traveltime of the energy in a trace as a function of frequency. It unwraps the phase of wavefields yielding far less non-linearity in the objective function than that experienced with conventional wavefields, yet it still holds most of the critical wavefield information in its frequency dependency. However, it suffers from non-linearity introduced by the model (or reflectivity), as reflections from independent events in our model interact with each other. Unwrapping the phase of such a model can mitigate this non-linearity as well. Specifically, a simple modification to the inverted domain (or model), can reduce the effect of the model-induced non-linearity and, thus, make the inversion more convergent. Simple numerical examples demonstrate these assertions.

Taming waveform inversion non-linearity through phase unwrapping of the model and objective functions

KAUST Repository

Alkhalifah, Tariq Ali; Choi, Yun Seok

2012-01-01

Traveltime inversion focuses on the geometrical features of the waveform (traveltimes), which is generally smooth, and thus, tends to provide averaged (smoothed) information of the model. On other hand, general waveform inversion uses additional elements of the wavefield including amplitudes to extract higher resolution information, but this comes at the cost of introducing non-linearity to the inversion operator, complicating the convergence process. We use unwrapped phase-based objective functions in waveform inversion as a link between the two general types of inversions in a domain in which such contributions to the inversion process can be easily identified and controlled. The instantaneous traveltime is a measure of the average traveltime of the energy in a trace as a function of frequency. It unwraps the phase of wavefields yielding far less non-linearity in the objective function than that experienced with conventional wavefields, yet it still holds most of the critical wavefield information in its frequency dependency. However, it suffers from non-linearity introduced by the model (or reflectivity), as reflections from independent events in our model interact with each other. Unwrapping the phase of such a model can mitigate this non-linearity as well. Specifically, a simple modification to the inverted domain (or model), can reduce the effect of the model-induced non-linearity and, thus, make the inversion more convergent. Simple numerical examples demonstrate these assertions.

Multi-objective mean-variance-skewness model for generation portfolio allocation in electricity markets