Damage mapping in structural health monitoring using a multi-grid architecture

Energy Technology Data Exchange (ETDEWEB)

Mathews, V. John [Dept. of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT 84112 (United States)

2015-03-31

This paper presents a multi-grid architecture for tomography-based damage mapping of composite aerospace structures. The system employs an array of piezo-electric transducers bonded on the structure. Each transducer may be used as an actuator as well as a sensor. The structure is excited sequentially using the actuators and the guided waves arriving at the sensors in response to the excitations are recorded for further analysis. The sensor signals are compared to their baseline counterparts and a damage index is computed for each actuator-sensor pair. These damage indices are then used as inputs to the tomographic reconstruction system. Preliminary damage maps are reconstructed on multiple coordinate grids defined on the structure. These grids are shifted versions of each other where the shift is a fraction of the spatial sampling interval associated with each grid. These preliminary damage maps are then combined to provide a reconstruction that is more robust to measurement noise in the sensor signals and the ill-conditioned problem formulation for single-grid algorithms. Experimental results on a composite structure with complexity that is representative of aerospace structures included in the paper demonstrate that for sufficiently high sensor densities, the algorithm of this paper is capable of providing damage detection and characterization with accuracy comparable to traditional C-scan and A-scan-based ultrasound non-destructive inspection systems quickly and without human supervision.

Laser-Based Slam with Efficient Occupancy Likelihood Map Learning for Dynamic Indoor Scenes

Science.gov (United States)

Li, Li; Yao, Jian; Xie, Renping; Tu, Jinge; Feng, Chen

2016-06-01

Location-Based Services (LBS) have attracted growing attention in recent years, especially in indoor environments. The fundamental technique of LBS is the map building for unknown environments, this technique also named as simultaneous localization and mapping (SLAM) in robotic society. In this paper, we propose a novel approach for SLAMin dynamic indoor scenes based on a 2D laser scanner mounted on a mobile Unmanned Ground Vehicle (UGV) with the help of the grid-based occupancy likelihood map. Instead of applying scan matching in two adjacent scans, we propose to match current scan with the occupancy likelihood map learned from all previous scans in multiple scales to avoid the accumulation of matching errors. Due to that the acquisition of the points in a scan is sequential but not simultaneous, there unavoidably exists the scan distortion at different extents. To compensate the scan distortion caused by the motion of the UGV, we propose to integrate a velocity of a laser range finder (LRF) into the scan matching optimization framework. Besides, to reduce the effect of dynamic objects such as walking pedestrians often existed in indoor scenes as much as possible, we propose a new occupancy likelihood map learning strategy by increasing or decreasing the probability of each occupancy grid after each scan matching. Experimental results in several challenged indoor scenes demonstrate that our proposed approach is capable of providing high-precision SLAM results.

Collaborative DFA learning applied to Grid administration

NARCIS (Netherlands)

Mulder, W.; Jacobs, C.J.H.; van Someren, M.; van Erp, M.; Stehouwer, H.; van Zaanen, M.

2009-01-01

This paper proposes a distributed learning mechanism that learns patterns from distributed datasets. The complex and dynamic settings of grid environments requires supporting systems to be of a more sophisticated level. Contemporary tools lack the ability to relate and infer events. We developed an

Schwarz-Christoffel Conformal Mapping based Grid Generation for Global Oceanic Circulation Models

Science.gov (United States)

Xu, Shiming

2015-04-01

We propose new grid generation algorithms for global ocean general circulation models (OGCMs). Contrary to conventional, analytical forms based dipolar or tripolar grids, the new algorithm are based on Schwarz-Christoffel (SC) conformal mapping with prescribed boundary information. While dealing with the conventional grid design problem of pole relocation, it also addresses more advanced issues of computational efficiency and the new requirements on OGCM grids arisen from the recent trend of high-resolution and multi-scale modeling. The proposed grid generation algorithm could potentially achieve the alignment of grid lines to coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the generated grids are still orthogonal curvilinear, they can be readily 10 utilized in existing Bryan-Cox-Semtner type ocean models. The proposed methodology can also be applied to the grid generation task for regional ocean modeling when complex land-ocean distribution is present.

Simplified Occupancy Grid Indoor Mapping Optimized for Low-Cost Robots

Directory of Open Access Journals (Sweden)

Javier Garrido

2013-10-01

Full Text Available This paper presents a mapping system that is suitable for small mobile robots. An ad hoc algorithm for mapping based on the Occupancy Grid method has been developed. The algorithm includes some simplifications in order to be used with low-cost hardware resources. The proposed mapping system has been built in order to be completely autonomous and unassisted. The proposal has been tested with a mobile robot that uses infrared sensors to measure distances to obstacles and uses an ultrasonic beacon system for localization, besides wheel encoders. Finally, experimental results are presented.

On the use of Schwarz-Christoffel conformal mappings to the grid generation for global ocean models

Science.gov (United States)

Xu, S.; Wang, B.; Liu, J.

2015-10-01

In this article we propose two grid generation methods for global ocean general circulation models. Contrary to conventional dipolar or tripolar grids, the proposed methods are based on Schwarz-Christoffel conformal mappings that map areas with user-prescribed, irregular boundaries to those with regular boundaries (i.e., disks, slits, etc.). The first method aims at improving existing dipolar grids. Compared with existing grids, the sample grid achieves a better trade-off between the enlargement of the latitudinal-longitudinal portion and the overall smooth grid cell size transition. The second method addresses more modern and advanced grid design requirements arising from high-resolution and multi-scale ocean modeling. The generated grids could potentially achieve the alignment of grid lines to the large-scale coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the grids are orthogonal curvilinear, they can be easily utilized by the majority of ocean general circulation models that are based on finite difference and require grid orthogonality. The proposed grid generation algorithms can also be applied to the grid generation for regional ocean modeling where complex land-sea distribution is present.

Eastern Seaboard Electric Grid Fragility Maps Supporting Persistent Availability

Energy Technology Data Exchange (ETDEWEB)

Walker, Kimberly A [ORNL; Weigand, Gilbert G [ORNL; Fernandez, Steven J [ORNL

2012-11-01

Persistently available power transmission can be disrupted by weather causing power outages with economic and social consequences. This research investigated the effects on the national power grid from a specific weather event, Hurricane Irene, that caused approximately 5.7 million customer power outages along the Eastern Seaboard in August of 2011. The objective was to describe the geographic differences in the grid s vulnerability to these events. Individual factors, such as wind speed or precipitation, were correlated with the number of outages to determine the greatest mechanism of power failure in hopes of strengthening the future power grid. The resulting fragility maps not only depicted 18 counties that were less robust than the design-standard robustness model and three counties that were more robust, but also drew new damage contours with correlated wind speeds and county features.

Mapping PetaSHA Applications to TeraGrid Architectures

Science.gov (United States)

Cui, Y.; Moore, R.; Olsen, K.; Zhu, J.; Dalguer, L. A.; Day, S.; Cruz-Atienza, V.; Maechling, P.; Jordan, T.

2007-12-01

The Southern California Earthquake Center (SCEC) has a science program in developing an integrated cyberfacility - PetaSHA - for executing physics-based seismic hazard analysis (SHA) computations. The NSF has awarded PetaSHA 15 million allocation service units this year on the fastest supercomputers available within the NSF TeraGrid. However, one size does not fit all, a range of systems are needed to support this effort at different stages of the simulations. Enabling PetaSHA simulations on those TeraGrid architectures to solve both dynamic rupture and seismic wave propagation have been a challenge from both hardware and software levels. This is an adaptation procedure to meet specific requirements of each architecture. It is important to determine how fundamental system attributes affect application performance. We present an adaptive approach in our PetaSHA application that enables the simultaneous optimization of both computation and communication at run-time using flexible settings. These techniques optimize initialization, source/media partition and MPI-IO output in different ways to achieve optimal performance on the target machines. The resulting code is a factor of four faster than the orignial version. New MPI-I/O capabilities have been added for the accurate Staggered-Grid Split-Node (SGSN) method for dynamic rupture propagation in the velocity-stress staggered-grid finite difference scheme (Dalguer and Day, JGR, 2007), We use execution workflow across TeraGrid sites for managing the resulting data volumes. Our lessons learned indicate that minimizing time to solution is most critical, in particular when scheduling large scale simulations across supercomputer sites. The TeraShake platform has been ported to multiple architectures including TACC Dell lonestar and Abe, Cray XT3 Bigben and Blue Gene/L. Parallel efficiency of 96% with the PetaSHA application Olsen-AWM has been demonstrated on 40,960 Blue Gene/L processors at IBM TJ Watson Center. Notable

Mapping of grid faults and grid codes

DEFF Research Database (Denmark)

Iov, F.; Hansen, Anca Daniela; Sørensen, Poul Ejnar

loads of wind turbines. The goal is also to clarify and define possible new directions in the certification process of power plant wind turbines, namely wind turbines, which participate actively in the stabilisation of power systems. Practical experience shows that there is a need...... challenges for the design of both the electrical system and the mechanical structure of wind turbines. An overview over the frequency of grid faults and the grid connection requirements in different relevant countries is done in this report. The most relevant study cases for the quantification of the loads......The present report is a part of the research project ''Grid fault and designbasis for wind turbine'' supported by Energinet.dk through the grant PSO F&U 6319. The objective of this project is to investigate into the consequences of the new grid connection requirements for the fatigue and extreme...

TouchGrid: Touchpad pointing by recursively mapping taps to smaller display regions

DEFF Research Database (Denmark)

Hertzum, Morten; Hornbæk, Kasper

2005-01-01

Touchpad devices are widely used but lacking in pointing efficiency. The TouchGrid, an instance of what we term cell cursors, replaces moving the cursor through dragging the finger on a touchpad with tapping in different regions of the touchpad. The touchpad regions are recursively mapped...... to smaller display regions and thereby enable high-precision pointing without requiring high tapping precision. In an experiment, six subjects used the TouchGrid and a standard touchpad across different numbers of targets, distances to targets, and target widths. Whereas standard touchpad operation follows...... Fitts’ law, target selection time with the TouchGrid is a linear function of the required number of taps. The TouchGrid was significantly faster for small targets and for tasks requiring one tap, and marginally faster for two-tap tasks. Error rates tended to be higher with the TouchGrid than...

On Line Segment Length and Mapping 4-regular Grid Structures in Network Infrastructures

DEFF Research Database (Denmark)

Riaz, Muhammad Tahir; Nielsen, Rasmus Hjorth; Pedersen, Jens Myrup

2006-01-01

The paper focuses on mapping the road network into 4-regular grid structures. A mapping algorithm is proposed. To model the road network GIS data have been used. The Geographic Information System (GIS) data for the road network are composed with different size of line segment lengths...

Mapping of grid faults and grid codes

DEFF Research Database (Denmark)

Iov, Florin; Hansen, A.D.; Sørensen, P.

loads of wind turbines. The goal is also to clarify and define possible new directions in the certification process of power plant wind turbines, namely wind turbines, which participate actively in the stabilisation of power systems. Practical experience shows that there is a need...... challenges for the design of both the electrical system and the mechanical structure of wind turbines. An overview over the frequency of grid faults and the grid connection requirements in different relevant countries is done in this report. The most relevant study cases for the quantification of the loads......The present report is a part of the research project "Grid fault and design basis for wind turbine" supported by Energinet.dk through the grant PSO F&U 6319. The objective of this project is to investigate into the consequences of the new grid connection requirements for the fatigue and extreme...

Application of approximate pattern matching in two dimensional spaces to grid layout for biochemical network maps.

Science.gov (United States)

Inoue, Kentaro; Shimozono, Shinichi; Yoshida, Hideaki; Kurata, Hiroyuki

2012-01-01

For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor) algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.

Application of approximate pattern matching in two dimensional spaces to grid layout for biochemical network maps.

Directory of Open Access Journals (Sweden)

Kentaro Inoue

Full Text Available BACKGROUND: For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. RESULTS: We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. CONCLUSIONS: Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.

Gridded Uncertainty Maps of Fossil Fuel Carbon Dioxide Emissions: A New Data Product

Science.gov (United States)

Andres, R. J.; Boden, T.

2014-12-01

With the publication of a new assessment of the uncertainty associated with the mass of fossil fuel carbon dioxide (FFCO2) emissions (2014, Tellus B, 66, 23616, doi:10.3402/tellusb.v66.23616), it is now possible to extend that work with a gridded map of fossil fuel emission uncertainties. The new data product was created to be paired with the long-used, Carbon Dioxide Information Analysis Center (CDIAC), emission year 1751-present, one degree latitude by one degree longitude (1x1) mass of emissions data product (http://cdiac.ornl.gov/epubs/ndp/ndp058/ndp058_v2013.html). Now, for the first time, data users will have FFCO2 emission information that represents both mass and uncertainty, each of which varies in both time and space. The new data product was constructed by examining the individual uncertainties in each of the input data sets to the gridded mass maps and then combining these individual uncertainties into an overall uncertainty for the mass maps. The input data sets include a table of the mass of FFCO2 emissions by country and year, the one degree geographic map of emissions which includes changing borders on an annual time scale and ties the mass of emissions to location, and the one degree population proxy used to distribute the mass of emissions within each country. As the three input data sets are independent of each other, their combination for the overall uncertainty is accomplished by a simple square root of the sum of the squares procedure. The resulting uncertainty data product is gridded at 1x1 and exactly overlays the 1x1 mass emission maps. The default temporal resolution is annual, but a companion product is also available at monthly time scales. The monthly uncertainty product uses the same input data sets, but the mass uncertainty is scaled as described in the monthly mass product description paper (2011, Tellus B, 63:309-327, doi: 10.1111/j.1600-0889.2011.00530.x). The gridded uncertainty maps cover emission year 1950 to 2010. The start

A New Data Product: Gridded Uncertainty Maps of Fossil Fuel Carbon Dioxide Emissions

Science.gov (United States)

Andres, R. J.; Boden, T.

2015-12-01

Gridded uncertainty maps of fossil fuel carbon dioxide (FFCO2) emissions are a new data product that is currently in the process of being completed and published. This work is based on the relatively new assessment of the uncertainty associated with the mass of FFCO2 emissions (2014, Tellus B, 66, 23616, doi:10.3402/tellusb.v66.23616). The new data product was created to be paired with the long-used, Carbon Dioxide Information Analysis Center (CDIAC), emission year 1751-present, one degree latitude by one degree longitude (1x1) mass of emissions data product (http://cdiac.ornl.gov/epubs/ndp/ndp058/ndp058_v2013.html). Now, data users will have FFCO2 emission information that represents both mass and uncertainty, each of which varies in both time and space. The new data product was constructed by examining the individual uncertainties in each of the input data sets to the gridded mass maps and then combining these individual uncertainties into an overall uncertainty for the mass maps. The input data sets include a table of the mass of FFCO2 emissions by country and year, the one degree geographic map of emissions which includes changing borders on an annual time scale and ties the mass of emissions to location, and the one degree population proxy used to distribute the mass of emissions within each country. As the three input data sets are independent of each other, their combination for the overall uncertainty is accomplished by a simple square root of the sum of the squares procedure. The resulting uncertainty data product is gridded at 1x1 and exactly overlays the 1x1 mass emission maps. The default temporal resolution is annual, but a companion product is also available at monthly time scales. The monthly uncertainty product uses the same input data sets, but the mass uncertainty is scaled as described in the monthly mass product description paper (2011, Tellus B, 63:309-327, doi: 10.1111/j.1600-0889.2011.00530.x). The gridded uncertainty maps cover emission year

Building a grid-semantic map for the navigation of service robots through human–robot interaction

Directory of Open Access Journals (Sweden)

Cheng Zhao

2015-11-01

Full Text Available This paper presents an interactive approach to the construction of a grid-semantic map for the navigation of service robots in an indoor environment. It is based on the Robot Operating System (ROS framework and contains four modules, namely Interactive Module, Control Module, Navigation Module and Mapping Module. Three challenging issues have been focused during its development: (i how human voice and robot visual information could be effectively deployed in the mapping and navigation process; (ii how semantic names could combine with coordinate data in an online Grid-Semantic map; and (iii how a localization–evaluate–relocalization method could be used in global localization based on modified maximum particle weight of the particle swarm. A number of experiments are carried out in both simulated and real environments such as corridors and offices to verify its feasibility and performance.

How Does the Modular Organization of Entorhinal Grid Cells Develop?

Directory of Open Access Journals (Sweden)

Stephen eGrossberg

2014-06-01

Full Text Available The entorhinal-hippocampal system plays a crucial role in spatial cognition and navigation. Since the discovery of grid cells in layer II of medial entorhinal cortex (MEC, several types of models have been proposed to explain their development and operation; namely, continuous attractor network models, oscillatory interference models, and self-organizing map (SOM models. Recent experiments revealing the in vivo intracellular signatures of grid cells (Domnisoru et al., 2013; Schmidt-Heiber & Hausser, 2013, the primarily inhibitory recurrent connectivity of grid cells (Couey et al., 2013; Pastoll et al., 2013, and the topographic organization of grid cells within anatomically overlapping modules of multiple spatial scales along the dorsoventral axis of MEC (Stensola et al., 2012 provide strong constraints and challenges to existing grid cell models. This article provides a computational explanation for how MEC cells can emerge through learning with grid cell properties in modular structures. Within this SOM model, grid cells with different rates of temporal integration learn modular properties with different spatial scales. Model grid cells learn in response to inputs from multiple scales of directionally-selective stripe cells (Krupic et al., 2012; Mhatre et al., 2012 that perform path integration of the linear velocities that are experienced during navigation. Slower rates of grid cell temporal integration support learned associations with stripe cells of larger scales. The explanatory and predictive capabilities of the three types of grid cell models are comparatively analyzed in light of recent data to illustrate how the SOM model overcomes problems that other types of models have not yet handled.

Deep learning for classification of islanding and grid disturbance based on multi-resolution singular spectrum entropy

Science.gov (United States)

Li, Tie; He, Xiaoyang; Tang, Junci; Zeng, Hui; Zhou, Chunying; Zhang, Nan; Liu, Hui; Lu, Zhuoxin; Kong, Xiangrui; Yan, Zheng

2018-02-01

Forasmuch as the distinguishment of islanding is easy to be interfered by grid disturbance, island detection device may make misjudgment thus causing the consequence of photovoltaic out of service. The detection device must provide with the ability to differ islanding from grid disturbance. In this paper, the concept of deep learning is introduced into classification of islanding and grid disturbance for the first time. A novel deep learning framework is proposed to detect and classify islanding or grid disturbance. The framework is a hybrid of wavelet transformation, multi-resolution singular spectrum entropy, and deep learning architecture. As a signal processing method after wavelet transformation, multi-resolution singular spectrum entropy combines multi-resolution analysis and spectrum analysis with entropy as output, from which we can extract the intrinsic different features between islanding and grid disturbance. With the features extracted, deep learning is utilized to classify islanding and grid disturbance. Simulation results indicate that the method can achieve its goal while being highly accurate, so the photovoltaic system mistakenly withdrawing from power grids can be avoided.

A novel gridding algorithm to create regional trace gas maps from satellite observations

Science.gov (United States)

Kuhlmann, G.; Hartl, A.; Cheung, H. M.; Lam, Y. F.; Wenig, M. O.

2014-02-01

The recent increase in spatial resolution for satellite instruments has made it feasible to study distributions of trace gas column densities on a regional scale. For this application a new gridding algorithm was developed to map measurements from the instrument's frame of reference (level 2) onto a longitude-latitude grid (level 3). The algorithm is designed for the Ozone Monitoring Instrument (OMI) and can easily be employed for similar instruments - for example, the upcoming TROPOspheric Monitoring Instrument (TROPOMI). Trace gas distributions are reconstructed by a continuous parabolic spline surface. The algorithm explicitly considers the spatially varying sensitivity of the sensor resulting from the instrument function. At the swath edge, the inverse problem of computing the spline coefficients is very sensitive to measurement errors and is regularised by a second-order difference matrix. Since this regularisation corresponds to the penalty term for smoothing splines, it similarly attenuates the effect of measurement noise over the entire swath width. Monte Carlo simulations are conducted to study the performance of the algorithm for different distributions of trace gas column densities. The optimal weight of the penalty term is found to be proportional to the measurement uncertainty and the width of the instrument function. A comparison with an established gridding algorithm shows improved performance for small to moderate measurement errors due to better parametrisation of the distribution. The resulting maps are smoother and extreme values are more accurately reconstructed. The performance improvement is further illustrated with high-resolution distributions obtained from a regional chemistry model. The new algorithm is applied to tropospheric NO2 column densities measured by OMI. Examples of regional NO2 maps are shown for densely populated areas in China, Europe and the United States of America. This work demonstrates that the newly developed gridding

A novel gridding algorithm to create regional trace gas maps from satellite observations

Directory of Open Access Journals (Sweden)

G. Kuhlmann

2014-02-01

Full Text Available The recent increase in spatial resolution for satellite instruments has made it feasible to study distributions of trace gas column densities on a regional scale. For this application a new gridding algorithm was developed to map measurements from the instrument's frame of reference (level 2 onto a longitude–latitude grid (level 3. The algorithm is designed for the Ozone Monitoring Instrument (OMI and can easily be employed for similar instruments – for example, the upcoming TROPOspheric Monitoring Instrument (TROPOMI. Trace gas distributions are reconstructed by a continuous parabolic spline surface. The algorithm explicitly considers the spatially varying sensitivity of the sensor resulting from the instrument function. At the swath edge, the inverse problem of computing the spline coefficients is very sensitive to measurement errors and is regularised by a second-order difference matrix. Since this regularisation corresponds to the penalty term for smoothing splines, it similarly attenuates the effect of measurement noise over the entire swath width. Monte Carlo simulations are conducted to study the performance of the algorithm for different distributions of trace gas column densities. The optimal weight of the penalty term is found to be proportional to the measurement uncertainty and the width of the instrument function. A comparison with an established gridding algorithm shows improved performance for small to moderate measurement errors due to better parametrisation of the distribution. The resulting maps are smoother and extreme values are more accurately reconstructed. The performance improvement is further illustrated with high-resolution distributions obtained from a regional chemistry model. The new algorithm is applied to tropospheric NO2 column densities measured by OMI. Examples of regional NO2 maps are shown for densely populated areas in China, Europe and the United States of America. This work demonstrates that the newly

road-map for smart grids and electricity systems integrating renewable energy sources

International Nuclear Information System (INIS)

Rebec, Gaelle; Moisan, Francois; Gioria, Michel

2009-12-01

The vision of smart grids and electricity systems elaborated in this road-map was drawn up on the basis of consultation and talks with a group of experts from industry (EDF, AREVA, GDF-Suez), public research bodies (SUPELEC, Ecole des Mines, INES, universities), grid operators (ERDF, RTE), local authorities' groups (FNCCR) and ADEME. In the course of these working sessions the experts expressed their opinions intuitu personae. The views outlined in this road-map are not to be assimilated with the official positions of the corporations or research organisations to which the members of the group belong. The visions of smart electricity grids and systems integrating renewable energies in 2020 and in 2050 are in sharp contrast. This contrast was deliberately sought out, for two reasons: - to offer the most exhaustive panorama possible of imaginable futures; - to avoid neglecting a critical technological, organisational or socioeconomic bottleneck that might be associated with a possible scenario left out of the discussion. Accordingly, in seeking contrasting visions the group arrived at extreme representations and even caricatures of the future, which nonetheless help define the outer limit of possibilities, and the scope within which the actual situation will most likely be situated in 2020 and in 2050

Grid-based modeling for land use planning and environmental resource mapping.

Energy Technology Data Exchange (ETDEWEB)

Kuiper, J. A.

1999-08-04

Geographic Information System (GIS) technology is used by land managers and natural resource planners for examining resource distribution and conducting project planning, often by visually interpreting spatial data representing environmental or regulatory variables. Frequently, many variables influence the decision-making process, and modeling can improve results with even a small investment of time and effort. Presented are several grid-based GIS modeling projects, including: (1) land use optimization under environmental and regulatory constraints; (2) identification of suitable wetland mitigation sites; and (3) predictive mapping of prehistoric cultural resource sites. As different as the applications are, each follows a similar process of problem conceptualization, implementation of a practical grid-based GIS model, and evaluation of results.

Mapping shape to visuomotor mapping: learning and generalisation of sensorimotor behaviour based on contextual information.

Directory of Open Access Journals (Sweden)

Loes C J van Dam

2015-03-01

Full Text Available Humans can learn and store multiple visuomotor mappings (dual-adaptation when feedback for each is provided alternately. Moreover, learned context cues associated with each mapping can be used to switch between the stored mappings. However, little is known about the associative learning between cue and required visuomotor mapping, and how learning generalises to novel but similar conditions. To investigate these questions, participants performed a rapid target-pointing task while we manipulated the offset between visual feedback and movement end-points. The visual feedback was presented with horizontal offsets of different amounts, dependent on the targets shape. Participants thus needed to use different visuomotor mappings between target location and required motor response depending on the target shape in order to "hit" it. The target shapes were taken from a continuous set of shapes, morphed between spiky and circular shapes. After training we tested participants performance, without feedback, on different target shapes that had not been learned previously. We compared two hypotheses. First, we hypothesised that participants could (explicitly extract the linear relationship between target shape and visuomotor mapping and generalise accordingly. Second, using previous findings of visuomotor learning, we developed a (implicit Bayesian learning model that predicts generalisation that is more consistent with categorisation (i.e. use one mapping or the other. The experimental results show that, although learning the associations requires explicit awareness of the cues' role, participants apply the mapping corresponding to the trained shape that is most similar to the current one, consistent with the Bayesian learning model. Furthermore, the Bayesian learning model predicts that learning should slow down with increased numbers of training pairs, which was confirmed by the present results. In short, we found a good correspondence between the

Sparse Jacobian construction for mapped grid visco-resistive magnetohydrodynamics

KAUST Repository

Reynolds, Daniel R.

2012-01-01

We apply the automatic differentiation tool OpenAD toward constructing a preconditioner for fully implicit simulations of mapped grid visco-resistive magnetohydrodynamics (MHD), used in modeling tokamak fusion devices. Our simulation framework employs a fully implicit formulation in time, and a mapped finite volume spatial discretization. We solve this model using inexact Newton-Krylov methods. Of critical importance in these iterative solvers is the development of an effective preconditioner, which typically requires knowledge of the Jacobian of the nonlinear residual function. However, due to significant nonlinearity within our PDE system, our mapped spatial discretization, and stencil adaptivity at physical boundaries, analytical derivation of these Jacobian entries is highly nontrivial. This paper therefore focuses on Jacobian construction using automatic differentiation. In particular, we discuss applying OpenAD to the case of a spatially-adaptive stencil patch that automatically handles differences between the domain interior and boundary, and configuring AD for reduced stencil approximations to the Jacobian. We investigate both scalar and vector tangent mode differentiation, along with simple finite difference approaches, to compare the resulting accuracy and efficiency of Jacobian construction in this application. © 2012 Springer-Verlag.

Machine learning for the New York City power grid.

Science.gov (United States)

Rudin, Cynthia; Waltz, David; Anderson, Roger N; Boulanger, Albert; Salleb-Aouissi, Ansaf; Chow, Maggie; Dutta, Haimonti; Gross, Philip N; Huang, Bert; Ierome, Steve; Isaac, Delfina F; Kressner, Arthur; Passonneau, Rebecca J; Radeva, Axinia; Wu, Leon

2012-02-01

Power companies can benefit from the use of knowledge discovery methods and statistical machine learning for preventive maintenance. We introduce a general process for transforming historical electrical grid data into models that aim to predict the risk of failures for components and systems. These models can be used directly by power companies to assist with prioritization of maintenance and repair work. Specialized versions of this process are used to produce 1) feeder failure rankings, 2) cable, joint, terminator, and transformer rankings, 3) feeder Mean Time Between Failure (MTBF) estimates, and 4) manhole events vulnerability rankings. The process in its most general form can handle diverse, noisy, sources that are historical (static), semi-real-time, or realtime, incorporates state-of-the-art machine learning algorithms for prioritization (supervised ranking or MTBF), and includes an evaluation of results via cross-validation and blind test. Above and beyond the ranked lists and MTBF estimates are business management interfaces that allow the prediction capability to be integrated directly into corporate planning and decision support; such interfaces rely on several important properties of our general modeling approach: that machine learning features are meaningful to domain experts, that the processing of data is transparent, and that prediction results are accurate enough to support sound decision making. We discuss the challenges in working with historical electrical grid data that were not designed for predictive purposes. The “rawness” of these data contrasts with the accuracy of the statistical models that can be obtained from the process; these models are sufficiently accurate to assist in maintaining New York City’s electrical grid.

Multigrid on unstructured grids using an auxiliary set of structured grids

Energy Technology Data Exchange (ETDEWEB)

Douglas, C.C.; Malhotra, S.; Schultz, M.H. [Yale Univ., New Haven, CT (United States)

1996-12-31

Unstructured grids do not have a convenient and natural multigrid framework for actually computing and maintaining a high floating point rate on standard computers. In fact, just the coarsening process is expensive for many applications. Since unstructured grids play a vital role in many scientific computing applications, many modifications have been proposed to solve this problem. One suggested solution is to map the original unstructured grid onto a structured grid. This can be used as a fine grid in a standard multigrid algorithm to precondition the original problem on the unstructured grid. We show that unless extreme care is taken, this mapping can lead to a system with a high condition number which eliminates the usefulness of the multigrid method. Theorems with lower and upper bounds are provided. Simple examples show that the upper bounds are sharp.

GridWise Standards Mapping Overview

Energy Technology Data Exchange (ETDEWEB)

Bosquet, Mia L.

2004-04-01

''GridWise'' is a concept of how advanced communications, information and controls technology can transform the nation's energy system--across the spectrum of large scale, central generation to common consumer appliances and equipment--into a collaborative network, rich in the exchange of decision making information and an abundance of market-based opportunities (Widergren and Bosquet 2003) accompanying the electric transmission and distribution system fully into the information and telecommunication age. This report summarizes a broad review of standards efforts which are related to GridWise--those which could ultimately contribute significantly to advancements toward the GridWise vision, or those which represent today's current technological basis upon which this vision must build.

Concept Mapping Using Cmap Tools to Enhance Meaningful Learning

Science.gov (United States)

Cañas, Alberto J.; Novak, Joseph D.

Concept maps are graphical tools that have been used in all facets of education and training for organizing and representing knowledge. When learners build concept maps, meaningful learning is facilitated. Computer-based concept mapping software such as CmapTools have further extended the use of concept mapping and greatly enhanced the potential of the tool, facilitating the implementation of a concept map-centered learning environment. In this chapter, we briefly present concept mapping and its theoretical foundation, and illustrate how it can lead to an improved learning environment when it is combined with CmapTools and the Internet. We present the nationwide “Proyecto Conéctate al Conocimiento” in Panama as an example of how concept mapping, together with technology, can be adopted by hundreds of schools as a means to enhance meaningful learning.

Smart grid

International Nuclear Information System (INIS)

Choi, Dong Bae

2001-11-01

This book describes press smart grid from basics to recent trend. It is divided into ten chapters, which deals with smart grid as green revolution in energy with introduction, history, the fields, application and needed technique for smart grid, Trend of smart grid in foreign such as a model business of smart grid in foreign, policy for smart grid in U.S.A, Trend of smart grid in domestic with international standard of smart grid and strategy and rood map, smart power grid as infrastructure of smart business with EMS development, SAS, SCADA, DAS and PQMS, smart grid for smart consumer, smart renewable like Desertec project, convergence IT with network and PLC, application of an electric car, smart electro service for realtime of electrical pricing system, arrangement of smart grid.

Combined effect of pulse density and grid cell size on predicting and mapping aboveground carbon in fast-growing Eucalyptus forest plantation using airborne LiDAR data.

Science.gov (United States)

Silva, Carlos Alberto; Hudak, Andrew Thomas; Klauberg, Carine; Vierling, Lee Alexandre; Gonzalez-Benecke, Carlos; de Padua Chaves Carvalho, Samuel; Rodriguez, Luiz Carlos Estraviz; Cardil, Adrián

2017-12-01

LiDAR remote sensing is a rapidly evolving technology for quantifying a variety of forest attributes, including aboveground carbon (AGC). Pulse density influences the acquisition cost of LiDAR, and grid cell size influences AGC prediction using plot-based methods; however, little work has evaluated the effects of LiDAR pulse density and cell size for predicting and mapping AGC in fast-growing Eucalyptus forest plantations. The aim of this study was to evaluate the effect of LiDAR pulse density and grid cell size on AGC prediction accuracy at plot and stand-levels using airborne LiDAR and field data. We used the Random Forest (RF) machine learning algorithm to model AGC using LiDAR-derived metrics from LiDAR collections of 5 and 10 pulses m -2 (RF5 and RF10) and grid cell sizes of 5, 10, 15 and 20 m. The results show that LiDAR pulse density of 5 pulses m -2 provides metrics with similar prediction accuracy for AGC as when using a dataset with 10 pulses m -2 in these fast-growing plantations. Relative root mean square errors (RMSEs) for the RF5 and RF10 were 6.14 and 6.01%, respectively. Equivalence tests showed that the predicted AGC from the training and validation models were equivalent to the observed AGC measurements. The grid cell sizes for mapping ranging from 5 to 20 also did not significantly affect the prediction accuracy of AGC at stand level in this system. LiDAR measurements can be used to predict and map AGC across variable-age Eucalyptus plantations with adequate levels of precision and accuracy using 5 pulses m -2 and a grid cell size of 5 m. The promising results for AGC modeling in this study will allow for greater confidence in comparing AGC estimates with varying LiDAR sampling densities for Eucalyptus plantations and assist in decision making towards more cost effective and efficient forest inventory.

Superior cognitive mapping through single landmark-related learning than through boundary-related learning.

Science.gov (United States)

Zhou, Ruojing; Mou, Weimin

2016-08-01

Cognitive mapping is assumed to be through hippocampus-dependent place learning rather than striatum-dependent response learning. However, we proposed that either type of spatial learning, as long as it involves encoding metric relations between locations and reference points, could lead to a cognitive map. Furthermore, the fewer reference points to specify individual locations, the more accurate a cognitive map of these locations will be. We demonstrated that participants have more accurate representations of vectors between 2 locations and of configurations among 3 locations when locations are individually encoded in terms of a single landmark than when locations are encoded in terms of a boundary. Previous findings have shown that learning locations relative to a boundary involve stronger place learning and higher hippocampal activation whereas learning relative to a single landmark involves stronger response learning and higher striatal activation. Recognizing this, we have provided evidence challenging the cognitive map theory but favoring our proposal. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Energy solutions in rural Africa: mapping electrification costs of distributed solar and diesel generation versus grid extension

Energy Technology Data Exchange (ETDEWEB)

Szabo, S; Bodis, K; Huld, T [European Commission Joint Research Centre, Institute for Energy, Renewable Energy Unit, 2749 via Enrico Fermi, TP450, 21027 Ispra (Vatican City State, Holy See) (Italy); Moner-Girona, M, E-mail: Sandor.Szabo@ec.europa.eu [UNEP Energy Branch Division of Technology, Industry and Economics, 15 rue de Milan, F-75441, Paris CEDEX09 (France)

2011-07-15

Three rural electrification options are analysed showing the cost optimal conditions for a sustainable energy development applying renewable energy sources in Africa. A spatial electricity cost model has been designed to point out whether diesel generators, photovoltaic systems or extension of the grid are the least-cost option in off-grid areas. The resulting mapping application offers support to decide in which regions the communities could be electrified either within the grid or in an isolated mini-grid. Donor programs and National Rural Electrification Agencies (or equivalent governmental departments) could use this type of delineation for their program boundaries and then could use the local optimization tools adapted to the prevailing parameters.

Energy solutions in rural Africa: mapping electrification costs of distributed solar and diesel generation versus grid extension

International Nuclear Information System (INIS)

Szabo, S; Bodis, K; Huld, T; Moner-Girona, M

2011-01-01

Three rural electrification options are analysed showing the cost optimal conditions for a sustainable energy development applying renewable energy sources in Africa. A spatial electricity cost model has been designed to point out whether diesel generators, photovoltaic systems or extension of the grid are the least-cost option in off-grid areas. The resulting mapping application offers support to decide in which regions the communities could be electrified either within the grid or in an isolated mini-grid. Donor programs and National Rural Electrification Agencies (or equivalent governmental departments) could use this type of delineation for their program boundaries and then could use the local optimization tools adapted to the prevailing parameters.

e-Portfolios for Learning and Development: without constant internet or electrical grid access

NARCIS (Netherlands)

Casey, John; Calverley, Gayle; Greller, Wolfgang; Uhomoibhi, James

2011-01-01

Casey, J., Calverley, G., Greller, W., & Uhomoibhi, J. (2010, 26-28 May). e-Portfolios for Learning and Development: without constant internet or electrical grid access. Presentation at the 5th International Conference on ICT for Development, Education, and Training - eLearning Africa, Lusaka,

Concept Maps for Evaluating Learning of Sustainable Development

Science.gov (United States)

Shallcross, David C.

2016-01-01

Concept maps are used to assess student and cohort learning of sustainable development. The concept maps of 732 first-year engineering students were individually analyzed to detect patterns of learning and areas that were not well understood. Students were given 20 minutes each to prepare a concept map of at least 20 concepts using paper and pen.…

Concept mapping as learning tool in problem-oriented learning

NARCIS (Netherlands)

Fürstenau, B.; Kneppers, L.; Sánchez, J.; Cañas, A.J.; Novak, J.D.

2010-01-01

In two studies we investigated whether concept mapping or summary writing is more effective in supporting students’ learning from authentic problems in the field of business. We interpret concept mapping and summary writing as elaboration tools aiming at helping students to understand new

Mapping Sub-Saharan African Agriculture in High-Resolution Satellite Imagery with Computer Vision & Machine Learning

Science.gov (United States)

Debats, Stephanie Renee

Smallholder farms dominate in many parts of the world, including Sub-Saharan Africa. These systems are characterized by small, heterogeneous, and often indistinct field patterns, requiring a specialized methodology to map agricultural landcover. In this thesis, we developed a benchmark labeled data set of high-resolution satellite imagery of agricultural fields in South Africa. We presented a new approach to mapping agricultural fields, based on efficient extraction of a vast set of simple, highly correlated, and interdependent features, followed by a random forest classifier. The algorithm achieved similar high performance across agricultural types, including spectrally indistinct smallholder fields, and demonstrated the ability to generalize across large geographic areas. In sensitivity analyses, we determined multi-temporal images provided greater performance gains than the addition of multi-spectral bands. We also demonstrated how active learning can be incorporated in the algorithm to create smaller, more efficient training data sets, which reduced computational resources, minimized the need for humans to hand-label data, and boosted performance. We designed a patch-based uncertainty metric to drive the active learning framework, based on the regular grid of a crowdsourcing platform, and demonstrated how subject matter experts can be replaced with fleets of crowdsourcing workers. Our active learning algorithm achieved similar performance as an algorithm trained with randomly selected data, but with 62% less data samples. This thesis furthers the goal of providing accurate agricultural landcover maps, at a scale that is relevant for the dominant smallholder class. Accurate maps are crucial for monitoring and promoting agricultural production. Furthermore, improved agricultural landcover maps will aid a host of other applications, including landcover change assessments, cadastral surveys to strengthen smallholder land rights, and constraints for crop modeling

Machine learning-based dual-energy CT parametric mapping.

Science.gov (United States)

Su, Kuan-Hao; Kuo, Jung-Wen; Jordan, David W; Van Hedent, Steven; Klahr, Paul; Wei, Zhouping; Al Helo, Rose; Liang, Fan; Qian, Pengjiang; Pereira, Gisele C; Rassouli, Negin; Gilkeson, Robert C; Traughber, Bryan J; Cheng, Chee-Wai; Muzic, Raymond F

2018-05-22

The aim is to develop and evaluate machine learning methods for generating quantitative parametric maps of effective atomic number (Z_eff), relative electron density (ρ_e), mean excitation energy (I_x), and relative stopping power (RSP) from clinical dual-energy CT data. The maps could be used for material identification and radiation dose calculation. Machine learning methods of historical centroid (HC), random forest (RF), and artificial neural networks (ANN) were used to learn the relationship between dual-energy CT input data and ideal output parametric maps calculated for phantoms from the known compositions of 13 tissue substitutes. After training and model selection steps, the machine learning predictors were used to generate parametric maps from independent phantom and patient input data. Precision and accuracy were evaluated using the ideal maps. This process was repeated for a range of exposure doses, and performance was compared to that of the clinically-used dual-energy, physics-based method which served as the reference. The machine learning methods generated more accurate and precise parametric maps than those obtained using the reference method. Their performance advantage was particularly evident when using data from the lowest exposure, one-fifth of a typical clinical abdomen CT acquisition. The RF method achieved the greatest accuracy. In comparison, the ANN method was only 1% less accurate but had much better computational efficiency than RF, being able to produce parametric maps in 15 seconds. Machine learning methods outperformed the reference method in terms of accuracy and noise tolerance when generating parametric maps, encouraging further exploration of the techniques. Among the methods we evaluated, ANN is the most suitable for clinical use due to its combination of accuracy, excellent low-noise performance, and computational efficiency. . © 2018 Institute of Physics and Engineering in

Y2K lessons learned for electric grid stability

International Nuclear Information System (INIS)

Gueorguiev, B.; Ianev, I. L.; Purvis, E. E.

2000-01-01

Y2K was an example of a worldwide infrastructure threat. Actions to understand infrastructure risks and mitigate infrastructure threats are a continuing and increasing part of the worlds corporate, government, and international organizations systems, and the severe implications of infrastructure failures to the health, safety, and financial well being of people and organizations are the deriving force. The IAEA conducted a number of Y2K related activities in nuclear power and fuel cycle activities. A set of these activities address the interface between electric power generation facilities and electric power grids in the region of Eastern Europe and the countries of the former Soviet Union. This addressed a continuing infrastructure risks and actions to mitigate these risk. The results were shown by events to have made positive contributions. The potential loss of nuclear power plant generation is a significant risk to electric power grids, an important critical infrastructure. Not only does the threat constitute a problem with the potential loss of the grid, loss of the electric power grid increases the probability of accidents in nuclear power plants. Recognizing that these activities addressed only one area of infrastructure risk in one region, there are some key lessons that were learned that could have general applicability

Group Concept Mapping on Learning Analytics

NARCIS (Netherlands)

Stoyanov, Slavi; Drachsler, Hendrik

2013-01-01

Stoyanov, S., & Drachsler, H. (2013, 5 July). Group Concept Mapping on Learning Analytics. Presentation given at Learning Analytics Summer School Institute (LASI) to kickoff the national GCM study on LA, Amsterdam, The Netherlands.

Modelling noise propagation using Grid Resources. Progress within GDI-Grid

Science.gov (United States)

Kiehle, Christian; Mayer, Christian; Padberg, Alexander; Stapelfeld, Hartmut

2010-05-01

Modelling noise propagation using Grid Resources. Progress within GDI-Grid. GDI-Grid (english: SDI-Grid) is a research project funded by the German Ministry for Science and Education (BMBF). It aims at bridging the gaps between OGC Web Services (OWS) and Grid infrastructures and identifying the potential of utilizing the superior storage capacities and computational power of grid infrastructures for geospatial applications while keeping the well-known service interfaces specified by the OGC. The project considers all major OGC webservice interfaces for Web Mapping (WMS), Feature access (Web Feature Service), Coverage access (Web Coverage Service) and processing (Web Processing Service). The major challenge within GDI-Grid is the harmonization of diverging standards as defined by standardization bodies for Grid computing and spatial information exchange. The project started in 2007 and will continue until June 2010. The concept for the gridification of OWS developed by lat/lon GmbH and the Department of Geography of the University of Bonn is applied to three real-world scenarios in order to check its practicability: a flood simulation, a scenario for emergency routing and a noise propagation simulation. The latter scenario is addressed by the Stapelfeldt Ingenieurgesellschaft mbH located in Dortmund adapting their LimA software to utilize grid resources. Noise mapping of e.g. traffic noise in urban agglomerates and along major trunk roads is a reoccurring demand of the EU Noise Directive. Input data requires road net and traffic, terrain, buildings and noise protection screens as well as population distribution. Noise impact levels are generally calculated in 10 m grid and along relevant building facades. For each receiver position sources within a typical range of 2000 m are split down into small segments, depending on local geometry. For each of the segments propagation analysis includes diffraction effects caused by all obstacles on the path of sound propagation

Mapping Students’ Informal Learning Using Personal Learning Environment

Directory of Open Access Journals (Sweden)

Jelena Anđelković Labrović

2014-07-01

Full Text Available Personal learning environments are a widely spared ways of learning, especially for the informal learning process. The aim of this research is to identify the elements of studens’ personal learning environment and to identify the extent to which students use modern technology for learning as part of their non-formal learning. A mapping system was used for gathering data and an analysis of percentages and frequency counts was used for data analysis in the SPSS. The results show that students’ personal learning environment includes the following elements: Wikipedia, Google, YouTube and Facebook in 75% of all cases, and an interesting fact is that all of them belong to a group of Web 2.0 tools and applications.

Improved visibility computation on massive grid terrains

NARCIS (Netherlands)

Fishman, J.; Haverkort, H.J.; Toma, L.; Wolfson, O.; Agrawal, D.; Lu, C.-T.

2009-01-01

This paper describes the design and engineering of algorithms for computing visibility maps on massive grid terrains. Given a terrain T, specified by the elevations of points in a regular grid, and given a viewpoint v, the visibility map or viewshed of v is the set of grid points of T that are

SoilGrids1km--global soil information based on automated mapping.

Directory of Open Access Journals (Sweden)

Tomislav Hengl

Full Text Available BACKGROUND: Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. METHODOLOGY/PRINCIPAL FINDINGS: We present SoilGrids1km--a global 3D soil information system at 1 km resolution--containing spatial predictions for a selection of soil properties (at six standard depths: soil organic carbon (g kg-1, soil pH, sand, silt and clay fractions (%, bulk density (kg m-3, cation-exchange capacity (cmol+/kg, coarse fragments (%, soil organic carbon stock (t ha-1, depth to bedrock (cm, World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles, and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images, lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database. Prediction accuracies assessed using 5-fold cross-validation were between 23-51%. CONCLUSIONS/SIGNIFICANCE: SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1 weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2 difficulty to obtain covariates that capture soil forming factors, (3 low sampling density and spatial clustering of soil profile locations. However, as the SoilGrids system is

Machine Learning Methods for Attack Detection in the Smart Grid.

Science.gov (United States)

Ozay, Mete; Esnaola, Inaki; Yarman Vural, Fatos Tunay; Kulkarni, Sanjeev R; Poor, H Vincent

2016-08-01

Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used to classify measurements as being either secure or attacked. An attack detection framework is provided to exploit any available prior knowledge about the system and surmount constraints arising from the sparse structure of the problem in the proposed approach. Well-known batch and online learning algorithms (supervised and semisupervised) are employed with decision- and feature-level fusion to model the attack detection problem. The relationships between statistical and geometric properties of attack vectors employed in the attack scenarios and learning algorithms are analyzed to detect unobservable attacks using statistical learning methods. The proposed algorithms are examined on various IEEE test systems. Experimental analyses show that machine learning algorithms can detect attacks with performances higher than attack detection algorithms that employ state vector estimation methods in the proposed attack detection framework.

Land Cover Change Detection using Neural Network and Grid Cells Techniques

Science.gov (United States)

Bagan, H.; Li, Z.; Tangud, T.; Yamagata, Y.

2017-12-01

In recent years, many advanced neural network methods have been applied in land cover classification, each of which has both strengths and limitations. In which, the self-organizing map (SOM) neural network method have been used to solve remote sensing data classification problems and have shown potential for efficient classification of remote sensing data. In SOM, both the distribution and the topology of features of the input layer are identified by using an unsupervised, competitive, neighborhood learning method. The high-dimensional data are then projected onto a low-dimensional map (competitive layer), usually as a two-dimensional map. The neurons (nodes) in the competitive layer are arranged by topological order in the input space. Spatio-temporal analyses of land cover change based on grid cells have demonstrated that gridded data are useful for obtaining spatial and temporal information about areas that are smaller than municipal scale and are uniform in size. Analysis based on grid cells has many advantages: grid cells all have the same size allowing for easy comparison; grids integrate easily with other scientific data; grids are stable over time and thus facilitate the modelling and analysis of very large multivariate spatial data sets. This study chose time-series MODIS and Landsat images as data sources, applied SOM neural network method to identify the land utilization in Inner Mongolia Autonomous Region of China. Then the results were integrated into grid cell to get the dynamic change maps. Land cover change using MODIS data in Inner Mongolia showed that urban area increased more than fivefold in recent 15 years, along with the growth of mining area. In terms of geographical distribution, the most obvious place of urban expansion is Ordos in southwest Inner Mongolia. The results using Landsat images from 1986 to 2014 in northeastern part of the Inner Mongolia show degradation in grassland from 1986 to 2014. Grid-cell-based spatial correlation

Learning Bing maps API

CERN Document Server

Sinani, Artan

2013-01-01

This is a practical, hands-on guide with illustrative examples, which will help you explore the vast universe of Bing maps.If you are a developer who wants to learn how to exploit the numerous features of Bing Maps then this book is ideal for you. It can also be useful for more experienced developers who wish to explore other areas of the APIs. It is assumed that you have some knowledge of JavaScript, HTML, and CSS. For some chapters a working knowledge of .Net and Visual Studio is also needed.

EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets

OpenAIRE

Brodzik, Mary J.; Billingsley, Brendan; Haran, Terry; Raup, Bruce; Savoie, Matthew H.

2012-01-01

Defined in the early 1990s for use with gridded satellite passive microwave data, the Equal-Area Scalable Earth Grid (EASE-Grid) was quickly adopted and used for distribution of a variety of satellite and in situ data sets. Conceptually easy to understand, EASE-Grid suffers from limitations that make it impossible to format in the widely popular GeoTIFF convention without reprojection. Importing EASE-Grid data into standard mapping software packages is nontrivial and error-prone. This article...

Mapping as a learning strategy in health professions education: a critical analysis.

Science.gov (United States)

Pudelko, Beatrice; Young, Meredith; Vincent-Lamarre, Philippe; Charlin, Bernard

2012-12-01

Mapping is a means of representing knowledge in a visual network and is becoming more commonly used as a learning strategy in medical education. The assumption driving the development and use of concept mapping is that it supports and furthers meaningful learning. The goal of this paper was to examine the effectiveness of concept mapping as a learning strategy in health professions education. The authors conducted a critical analysis of recent literature on the use of concept mapping as a learning strategy in the area of health professions education. Among the 65 studies identified, 63% were classified as empirical work, the majority (76%) of which used pre-experimental designs. Only 24% of empirical studies assessed the impact of mapping on meaningful learning. Results of the analysis do not support the hypothesis that mapping per se furthers and supports meaningful learning, memorisation or factual recall. When documented improvements in learning were found, they often occurred when mapping was used in concert with other strategies, such as collaborative learning or instructor modelling, scaffolding and feedback. Current empirical research on mapping as a learning strategy presents methodological shortcomings that limit its internal and external validity. The results of our analysis indicate that mapping strategies that make use of feedback and scaffolding have beneficial effects on learning. Accordingly, we see a need to expand the process of reflection on the characteristics of representational guidance as it is provided by mapping techniques and tools based on field of knowledge, instructional objectives, and the characteristics of learners in health professions education. © Blackwell Publishing Ltd 2012.

Enhanced STEM Learning with the GeoMapApp Data Exploration Tool

Science.gov (United States)

Goodwillie, A. M.

2014-12-01

GeoMapApp (http://www.geomapapp.org), is a free, map-based data discovery and visualisation tool developed with NSF funding at Lamont-Doherty Earth Observatory. GeoMapApp provides casual and specialist users alike with access to hundreds of built-in geoscience data sets covering geology, geophysics, geochemistry, oceanography, climatology, cryospherics, and the environment. Users can also import their own data tables, spreadsheets, shapefiles, grids and images. Simple manipulation and analysis tools combined with layering capabilities and engaging visualisations provide a powerful platform with which to explore and interrogate geoscience data in its proper geospatial context thus helping users to more easily gain insight into the meaning of the data. A global elevation base map covering the oceans as well as continents forms the backbone of GeoMapApp. The multi-resolution base map is updated regularly and includes data sources ranging from Space Shuttle elevation data for land areas to ultra-high-resolution surveys of coral reefs and seafloor hydrothermal vent fields. Examples of built-in data sets that can be layered over the elevation model include interactive earthquake and volcano data, plate tectonic velocities, hurricane tracks, land and ocean temperature, water column properties, age of the ocean floor, and deep submersible bottom photos. A versatile profiling tool provides instant access to data cross-sections. Contouring and 3-D views are also offered - the attached image shows a 3-D view of East Africa's Ngorongoro Crater as an example. Tabular data - both imported and built-in - can be displayed in a variety of ways and a lasso tool enables users to quickly select data points directly from the map. A range of STEM-based education material based upon GeoMapApp is already available, including a number of self-contained modules for school- and college-level students (http://www.geomapapp.org/education/contributed_material.html). More learning modules are

Concept mapping learning strategy to enhance students' mathematical connection ability

Science.gov (United States)

Hafiz, M.; Kadir, Fatra, Maifalinda

2017-05-01

The concept mapping learning strategy in teaching and learning mathematics has been investigated by numerous researchers. However, there are still less researchers who have scrutinized about the roles of map concept which is connected to the mathematical connection ability. Being well understood on map concept, it may help students to have ability to correlate one concept to other concept in order that the student can solve mathematical problems faced. The objective of this research was to describe the student's mathematical connection ability and to analyze the effect of using concept mapping learning strategy to the students' mathematical connection ability. This research was conducted at senior high school in Jakarta. The method used a quasi-experimental with randomized control group design with the total number was 72 students as the sample. Data obtained through using test in the post-test after giving the treatment. The results of the research are: 1) Students' mathematical connection ability has reached the good enough level category; 2) Students' mathematical connection ability who had taught with concept mapping learning strategy is higher than who had taught with conventional learning strategy. Based on the results above, it can be concluded that concept mapping learning strategycould enhance the students' mathematical connection ability, especially in trigonometry.

GeoMapApp Learning Activities: Enabling the democratisation of geoscience learning

Science.gov (United States)

Goodwillie, A. M.; Kluge, S.

2011-12-01

GeoMapApp Learning Activities (http://serc.carleton.edu/geomapapp) are step-by-step guided inquiry geoscience education activities that enable students to dictate the pace of learning. They can be used in the classroom or out of class, and their guided nature means that the requirement for teacher intervention is minimised which allows students to spend increased time analysing and understanding a broad range of geoscience data, content and concepts. Based upon GeoMapApp (http://www.geomapapp.org), a free, easy-to-use map-based data exploration and visualisation tool, each activity furnishes the educator with an efficient package of downloadable documents. This includes step-by-step student instructions and answer sheet; a teacher's edition annotated worksheet containing teaching tips, additional content and suggestions for further work; quizzes for use before and after the activity to assess learning; and a multimedia tutorial. The activities can be used by anyone at any time in any place with an internet connection. In essence, GeoMapApp Learning Activities provide students with cutting-edge technology, research-quality geoscience data sets, and inquiry-based learning in a virtual lab-like environment. Examples of activities so far created are student calculation and analysis of the rate of seafloor spreading, and present-day evidence on the seafloor for huge ancient landslides around the Hawaiian islands. The activities are designed primarily for students at the community college, high school and introductory undergraduate levels, exposing students to content and concepts typically found in those settings.

World Gravity Map: a set of global complete spherical Bouguer and isostatic anomaly maps and grids

Science.gov (United States)

Bonvalot, S.; Balmino, G.; Briais, A.; Kuhn, M.; Peyrefitte, A.; Vales, N.; Biancale, R.; Gabalda, G.; Reinquin, F.

2012-04-01

We present here a set of digital maps of the Earth's gravity anomalies (surface free air, Bouguer and isostatic), computed at Bureau Gravimetric International (BGI) as a contribution to the Global Geodetic Observing Systems (GGOS) and to the global geophysical maps published by the Commission for the Geological Map of the World (CGMW) with support of UNESCO and other institutions. The Bouguer anomaly concept is extensively used in geophysical interpretation to investigate the density distributions in the Earth's interior. Complete Bouguer anomalies (including terrain effects) are usually computed at regional scales by integrating the gravity attraction of topography elements over and beyond a given area (under planar or spherical approximations). Here, we developed and applied a worldwide spherical approach aimed to provide a set of homogeneous and high resolution gravity anomaly maps and grids computed at the Earth's surface, taking into account a realistic Earth model and reconciling geophysical and geodetic definitions of gravity anomalies. This first version (1.0) has been computed by spherical harmonics analysis / synthesis of the Earth's topography-bathymetry up to degree 10800. The detailed theory of the spherical harmonics approach is given in Balmino et al., (Journal of Geodesy, 2011). The Bouguer and terrain corrections have thus been computed in spherical geometry at 1'x1' resolution using the ETOPO1 topography/bathymetry, ice surface and bedrock models from the NOAA (National Oceanic and Atmospheric Administration) and taking into account precise characteristics (boundaries and densities) of major lakes, inner seas, polar caps and of land areas below sea level. Isostatic corrections have been computed according to the Airy-Heiskanen model in spherical geometry for a constant depth of compensation of 30km. The gravity information given here is provided by the Earth Geopotential Model (EGM2008), developed at degree 2160 by the National Geospatial

A teaching-learning sequence about weather map reading

Science.gov (United States)

Mandrikas, Achilleas; Stavrou, Dimitrios; Skordoulis, Constantine

2017-07-01

In this paper a teaching-learning sequence (TLS) introducing pre-service elementary teachers (PET) to weather map reading, with emphasis on wind assignment, is presented. The TLS includes activities about recognition of wind symbols, assignment of wind direction and wind speed on a weather map and identification of wind characteristics in a weather forecast. Sixty PET capabilities and difficulties in understanding weather maps were investigated, using inquiry-based learning activities. The results show that most PET became more capable of reading weather maps and assigning wind direction and speed on them. Our results also show that PET could be guided to understand meteorology concepts useful in everyday life and in teaching their future students.

Discourse-Centric Learning Analytics: Mapping the Terrain

Science.gov (United States)

Knight, Simon; Littleton, Karen

2015-01-01

There is an increasing interest in developing learning analytic techniques for the analysis, and support of, high-quality learning discourse. This paper maps the terrain of discourse-centric learning analytics (DCLA), outlining the distinctive contribution of DCLA and outlining a definition for the field moving forwards. It is our claim that DCLA…

The Grid

CERN Document Server

Klotz, Wolf-Dieter

2005-01-01

Grid technology is widely emerging. Grid computing, most simply stated, is distributed computing taken to the next evolutionary level. The goal is to create the illusion of a simple, robust yet large and powerful self managing virtual computer out of a large collection of connected heterogeneous systems sharing various combinations of resources. This talk will give a short history how, out of lessons learned from the Internet, the vision of Grids was born. Then the extensible anatomy of a Grid architecture will be discussed. The talk will end by presenting a selection of major Grid projects in Europe and US and if time permits a short on-line demonstration.

Ontology-based concept map learning path reasoning system using SWRL rules

Energy Technology Data Exchange (ETDEWEB)

Chu, K.-K.; Lee, C.-I. [National Univ. of Tainan, Taiwan (China). Dept. of Computer Science and Information Learning Technology

2010-08-13

Concept maps are graphical representations of knowledge. Concept mapping may reduce students' cognitive load and extend simple memory function. The purpose of this study was on the diagnosis of students' concept map learning abilities and the provision of personally constructive advice dependant on their learning path and progress. Ontology is a useful method with which to represent and store concept map information. Semantic web rule language (SWRL) rules are easy to understand and to use as specific reasoning services. This paper discussed the selection of grade 7 lakes and rivers curriculum for which to devise a concept map learning path reasoning service. The paper defined a concept map e-learning ontology and two SWRL semantic rules, and collected users' concept map learning path data to infer implicit knowledge and to recommend the next learning path for users. It was concluded that the designs devised in this study were feasible and advanced and the ontology kept the domain knowledge preserved. SWRL rules identified an abstraction model for inferred properties. Since they were separate systems, they did not interfere with each other, while ontology or SWRL rules were maintained, ensuring persistent system extensibility and robustness. 15 refs., 1 tab., 8 figs.

A Multianalyzer Machine Learning Model for Marine Heterogeneous Data Schema Mapping

Science.gov (United States)

Yan, Wang; Jiajin, Le; Yun, Zhang

2014-01-01

The main challenges that marine heterogeneous data integration faces are the problem of accurate schema mapping between heterogeneous data sources. In order to improve the schema mapping efficiency and get more accurate learning results, this paper proposes a heterogeneous data schema mapping method basing on multianalyzer machine learning model. The multianalyzer analysis the learning results comprehensively, and a fuzzy comprehensive evaluation system is introduced for output results' evaluation and multi factor quantitative judging. Finally, the data mapping comparison experiment on the East China Sea observing data confirms the effectiveness of the model and shows multianalyzer's obvious improvement of mapping error rate. PMID:25250372

Coding Model and Mapping Method of Spherical Diamond Discrete Grids Based on Icosahedron

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LIN Bingxian

2016-12-01

Full Text Available Discrete Global Grid(DGG provides a fundamental environment for global-scale spatial data's organization and management. DGG's encoding scheme, which blocks coordinate transformation between different coordination reference frames and reduces the complexity of spatial analysis, contributes a lot to the multi-scale expression and unified modeling of spatial data. Compared with other kinds of DGGs, Diamond Discrete Global Grid(DDGG based on icosahedron is beneficial to the spherical spatial data's integration and expression for much better geometric properties. However, its structure seems more complicated than DDGG on octahedron due to its initial diamond's edges cannot fit meridian and parallel. New challenges are posed when it comes to the construction of hierarchical encoding system and mapping relationship with geographic coordinates. On this issue, this paper presents a DDGG's coding system based on the Hilbert curve and designs conversion methods between codes and geographical coordinates. The study results indicate that this encoding system based on the Hilbert curve can express space scale and location information implicitly with the similarity between DDG and planar grid put into practice, and balances efficiency and accuracy of conversion between codes and geographical coordinates in order to support global massive spatial data's modeling, integrated management and all kinds of spatial analysis.

JColorGrid: software for the visualization of biological measurements.

Science.gov (United States)

Joachimiak, Marcin P; Weisman, Jennifer L; May, Barnaby Ch

2006-04-27

Two-dimensional data colourings are an effective medium by which to represent three-dimensional data in two dimensions. Such "color-grid" representations have found increasing use in the biological sciences (e.g. microarray 'heat maps' and bioactivity data) as they are particularly suited to complex data sets and offer an alternative to the graphical representations included in traditional statistical software packages. The effectiveness of color-grids lies in their graphical design, which introduces a standard for customizable data representation. Currently, software applications capable of generating limited color-grid representations can be found only in advanced statistical packages or custom programs (e.g. micro-array analysis tools), often associated with steep learning curves and requiring expert knowledge. Here we describe JColorGrid, a Java library and platform independent application that renders color-grid graphics from data. The software can be used as a Java library, as a command-line application, and as a color-grid parameter interface and graphical viewer application. Data, titles, and data labels are input as tab-delimited text files or Microsoft Excel spreadsheets and the color-grid settings are specified through the graphical interface or a text configuration file. JColorGrid allows both user graphical data exploration as well as a means of automatically rendering color-grids from data as part of research pipelines. The program has been tested on Windows, Mac, and Linux operating systems, and the binary executables and source files are available for download at http://jcolorgrid.ucsf.edu.

A Multianalyzer Machine Learning Model for Marine Heterogeneous Data Schema Mapping

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Wang Yan

2014-01-01

Full Text Available The main challenges that marine heterogeneous data integration faces are the problem of accurate schema mapping between heterogeneous data sources. In order to improve the schema mapping efficiency and get more accurate learning results, this paper proposes a heterogeneous data schema mapping method basing on multianalyzer machine learning model. The multianalyzer analysis the learning results comprehensively, and a fuzzy comprehensive evaluation system is introduced for output results’ evaluation and multi factor quantitative judging. Finally, the data mapping comparison experiment on the East China Sea observing data confirms the effectiveness of the model and shows multianalyzer’s obvious improvement of mapping error rate.

Concept mapping enhances learning of biochemistry.

Science.gov (United States)

Surapaneni, Krishna M; Tekian, Ara

2013-03-05

Teaching basic science courses is challenging in undergraduate medical education because of the ubiquitous use of didactic lectures and reward for recall of factual information during examinations. The purpose of this study is to introduce concept maps with clinical cases (the innovative program) to improve learning of biochemistry course content. Participants were first year medical students (n=150) from Saveetha Medical College and Hospital (India); they were randomly divided into two groups of 75, one group attending the traditional program, the other the innovative program. Student performance was measured using three written knowledge tests (each with a maximum score of 20). The students also evaluated the relevance of the learning process using a 12-item questionnaire. Students in the innovative program using concept mapping outperformed those in the traditional didactic program (means of 7.13-8.28 vs. 12.33-13.93, pbiochemistry to clinical practice, and to enhance their reasoning and learning skills, as well as their deeper understanding for biochemistry.

Concept mapping enhances learning of biochemistry.

Science.gov (United States)

Surapaneni, KrishnaM; Tekian, Ara

2013-01-01

Teaching basic science courses is challenging in undergraduate medical education because of the ubiquitous use of didactic lectures and reward for recall of factual information during examinations. The purpose of this study is to introduce concept maps with clinical cases (the innovative program) to improve learning of biochemistry course content. Participants were first year medical students (n=150) from Saveetha Medical College and Hospital (India); they were randomly divided into two groups of 75, one group attending the traditional program, the other the innovative program. Student performance was measured using three written knowledge tests (each with a maximum score of 20). The students also evaluated the relevance of the learning process using a 12-item questionnaire. Students in the innovative program using concept mapping outperformed those in the traditional didactic program (means of 7.13-8.28 vs. 12.33-13.93, pbiochemistry to clinical practice, and to enhance their reasoning and learning skills, as well as their deeper understanding for biochemistry.

EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets

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Matthew H. Savoie

2012-03-01

Full Text Available Defined in the early 1990s for use with gridded satellite passive microwave data, the Equal-Area Scalable Earth Grid (EASE-Grid was quickly adopted and used for distribution of a variety of satellite and in situ data sets. Conceptually easy to understand, EASE-Grid suffers from limitations that make it impossible to format in the widely popular GeoTIFF convention without reprojection. Importing EASE-Grid data into standard mapping software packages is nontrivial and error-prone. This article defines a standard for an improved EASE-Grid 2.0 definition, addressing how the changes rectify issues with the original grid definition. Data distributed using the EASE-Grid 2.0 standard will be easier for users to import into standard software packages and will minimize common reprojection errors that users had encountered with the original EASE-Grid definition.

Techniques for grid manipulation and adaptation. [computational fluid dynamics

Science.gov (United States)

Choo, Yung K.; Eisemann, Peter R.; Lee, Ki D.

1992-01-01

Two approaches have been taken to provide systematic grid manipulation for improved grid quality. One is the control point form (CPF) of algebraic grid generation. It provides explicit control of the physical grid shape and grid spacing through the movement of the control points. It works well in the interactive computer graphics environment and hence can be a good candidate for integration with other emerging technologies. The other approach is grid adaptation using a numerical mapping between the physical space and a parametric space. Grid adaptation is achieved by modifying the mapping functions through the effects of grid control sources. The adaptation process can be repeated in a cyclic manner if satisfactory results are not achieved after a single application.

Concept mapping and text writing as learning tools in problem-oriented learning

NARCIS (Netherlands)

Fürstenau, B.; Kneppers, L.; Dekker, R.; Cañas, A.J.; Novak, J.D.; Vanhaer, J.

2012-01-01

In two studies we investigated whether concept mapping or summary writing better support students while learning from authentic problems in the field of business. We interpret concept mapping and summary writing as elaboration tools aiming at helping students to understand new information, and to

JColorGrid: software for the visualization of biological measurements

Directory of Open Access Journals (Sweden)

May Barnaby CH

2006-04-01

Full Text Available Abstract Background Two-dimensional data colourings are an effective medium by which to represent three-dimensional data in two dimensions. Such "color-grid" representations have found increasing use in the biological sciences (e.g. microarray 'heat maps' and bioactivity data as they are particularly suited to complex data sets and offer an alternative to the graphical representations included in traditional statistical software packages. The effectiveness of color-grids lies in their graphical design, which introduces a standard for customizable data representation. Currently, software applications capable of generating limited color-grid representations can be found only in advanced statistical packages or custom programs (e.g. micro-array analysis tools, often associated with steep learning curves and requiring expert knowledge. Results Here we describe JColorGrid, a Java library and platform independent application that renders color-grid graphics from data. The software can be used as a Java library, as a command-line application, and as a color-grid parameter interface and graphical viewer application. Data, titles, and data labels are input as tab-delimited text files or Microsoft Excel spreadsheets and the color-grid settings are specified through the graphical interface or a text configuration file. JColorGrid allows both user graphical data exploration as well as a means of automatically rendering color-grids from data as part of research pipelines. Conclusion The program has been tested on Windows, Mac, and Linux operating systems, and the binary executables and source files are available for download at http://jcolorgrid.ucsf.edu.

SoilGrids1km — Global Soil Information Based on Automated Mapping

Science.gov (United States)

Hengl, Tomislav; de Jesus, Jorge Mendes; MacMillan, Robert A.; Batjes, Niels H.; Heuvelink, Gerard B. M.; Ribeiro, Eloi; Samuel-Rosa, Alessandro; Kempen, Bas; Leenaars, Johan G. B.; Walsh, Markus G.; Gonzalez, Maria Ruiperez

2014-01-01

Background Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. Methodology/Principal Findings We present SoilGrids1km — a global 3D soil information system at 1 km resolution — containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kg−1), soil pH, sand, silt and clay fractions (%), bulk density (kg m−3), cation-exchange capacity (cmol+/kg), coarse fragments (%), soil organic carbon stock (t ha−1), depth to bedrock (cm), World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles), and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images), lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database). Prediction accuracies assessed using 5–fold cross-validation were between 23–51%. Conclusions/Significance SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1) weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2) difficulty to obtain covariates that capture soil forming factors, (3) low sampling density and spatial clustering of soil profile locations. However, as the SoilGrids

Learning Quantum Chemical Model with Learning Media Concept Map and Power Point Viewed from Memory and Creativity Skills Students

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Agus Wahidi

2017-03-01

Full Text Available This research is experimental, using first class learning a quantum model of learning with concept maps media and the second media using real environments by power point presentation. The population is all class XI Science, number 2 grade. The sampling technique is done by purposive random sampling. Data collection techniques to test for cognitive performance and memory capabilities, with a questionnaire for creativity. Hypothesis testing using three-way ANOVA different cells with the help of software Minitab 15.Based on the results of data processing, concluded: (1 there is no influence of the quantum model of learning with media learning concept maps and real environments for learning achievement chemistry, (2 there is a high impact memory ability and low on student achievement, (3 there is no the effect of high and low creativity in student performance, (4 there is no interaction learning model quantum media learning concept maps and real environments with memory ability on student achievement, (5 there is no interaction learning model quantum media learning concept maps and real environments with creativity of student achievement, (6 there is no interaction memory skills and creativity of student achievement, (7 there is no interaction learning model quantum media learning concept maps and real environments, memory skills, and creativity on student achievement.

SCIENCE TEACHERS’ UNDERSTANDING OF MIND MAP LEARNING STRATEGY (PEMAHAMAN GURU IPA DALAM STRATEGI PEMBELAJARAN PETA PIKIRAN (MIND MAP

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Natalia Rosa Keliat

2017-02-01

Full Text Available Abstract. This researchs were conducted in Salatiga primary high school, Central Java and the subject of were taken from 23 science teachers which used interview and observation tech-niques. The aim of this study was firstly, to assess learning strategies of science in Salatiga prima-ry high school, and secondly to assess the obstacles and constraints that faced the science teach-ers in the implementation of learning strategies in the classroom. Further more the percentage of the understanding and application of mind map model, and also to assess the obstacles and con-straints in the implementation of mind map in the classroom. Data were analyzed by using de-scriptive qualitative method. The results showed that the percentage of science teachers using discussion methods are 78.26%, 21.74% by concept maps, 30.43% by demonstrations, 39.13% by lectures, 34.78% using mind map respectively by other strategies such as card games, quiz, pro-ject based learning, discovery, problem based learning, contextual teaching learning, and inquiry is 43,8%. Teachers faced difficulty to allocate the time in the classroom because students who had lower levels of cognitive abilities require a longer time to understand the strategies in the class-room. The percentage of teachers using mind map in teaching only reach at 34.78%, while 65.22% teachers still not applying yet. Results of interview which were conducted approximately 47.83% to the teachers who understand the learning mechanisms model of mind map, and 52.17% did not understand the principles of learning using mind map. However, in its application in the classroom teachers face some problems, for example, it is take time to implemented, and the other subjects difficult to finished on time. More over, other constraints that faced are the students still have difficulty in making mind map because lack of exercise, as well as students who are already familiar with the habit pattern of teacher using teaching

Mapping glaucoma patients' 30-2 and 10-2 visual fields reveals clusters of test points damaged in the 10-2 grid that are not sampled in the sparse 30-2 grid.

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Ryo Asaoka

Full Text Available PURPOSE: To cluster test points in glaucoma patients' 30-2 and 10-2 visual field (VF (Humphrey Field Analyzer: HFA, Carl Zeiss Meditec, Dublin, CA in order to map the different regions damaged by the disease. METHOD: This retrospective study included 128 eyes from 128 patients. 142 total deviation (TD values (74 from the 30-2 VF and 68 from the 10-2 VF were clustered using the 'Hierarchical Ordered Partitioning And Collapsing Hybrid-Partitioning Around Medoids' algorithm. The stability of the identified clusters was evaluated using bootstrapping. RESULTS: 65 sectors were identified in total: 38 sectors were located outside the 10-2 VF whereas 29 sectors were located inside the 10-2 VF (two sectors overlap in both grids. The mapping of many sectors appeared to follow the distribution of retinal nerve fiber bundles. The results of bootstrapping suggested clusters were stable whether they were outside or inside the 10-2 VF. CONCLUSION: A considerable number of sectors were identified in the 10-2 VF area, despite the fact that clustering was carried out on all points in both the 30-2 VF and 10-2 VF simultaneously. These findings suggest that glaucomatous central VF deterioration cannot be picked up by the 30-2 test grid alone, because of poor spatial sampling; denser estimation of the central ten degrees, than offered by the 30-2 test grid alone, is needed. It may be beneficial to develop a new VF test grid that combines test points from 30-2 and 10-2 VFs--the results of this study could help to devise this test grid.

Online testable concept maps: benefits for learning about the pathogenesis of disease.

Science.gov (United States)

Ho, Veronica; Kumar, Rakesh K; Velan, Gary

2014-07-01

Concept maps have been used to promote meaningful learning and critical thinking. Although these are crucially important in all disciplines, evidence for the benefits of concept mapping for learning in medicine is limited. We performed a randomised crossover study to assess the benefits of online testable concept maps for learning in pathology by volunteer junior medical students. Participants (n = 65) were randomly allocated to either of two groups with equivalent mean prior academic performance, in which they were given access to either online maps or existing online resources for a 2-week block on renal disease. Groups then crossed over for a 2-week block on hepatic disease. Outcomes were assessed using timed online quizzes, which included questions unrelated to topics in the pathogenesis maps as an internal control. Questionnaires were administered to evaluate students' acceptance of the maps. In both blocks, the group with access to pathogenesis maps achieved significantly higher average scores than the control group on quiz questions related to topics covered by the maps (Block 1: p online testable pathogenesis maps are well accepted and can improve learning of concepts in pathology by medical students. © 2014 John Wiley & Sons Ltd.

Enhancing Simulation Learning with Team Mental Model Mapping

Science.gov (United States)

Goltz, Sonia M.

2017-01-01

Simulations have been developed for many business courses because of enhanced student engagement and learning. A challenge for instructors using simulations is how to take this learning to the next level since student reflection and learning can vary. This article describes how to use a conceptual mapping game at the beginning and end of a…

Mind map learning for advanced engineering study: case study in system dynamics

Science.gov (United States)

Woradechjumroen, Denchai

2018-01-01

System Dynamics (SD) is one of the subjects that were use in learning Automatic Control Systems in dynamic and control field. Mathematical modelling and solving skills of students for engineering systems are expecting outcomes of the course which can be further used to efficiently study control systems and mechanical vibration; however, the fundamental of the SD includes strong backgrounds in Dynamics and Differential Equations, which are appropriate to the students in governmental universities that have strong skills in Mathematics and Scientifics. For private universities, students are weak in the above subjects since they obtained high vocational certificate from Technical College or Polytechnic School, which emphasize the learning contents in practice. To enhance their learning for improving their backgrounds, this paper applies mind maps based problem based learning to relate the essential relations of mathematical and physical equations. With the advantages of mind maps, each student is assigned to design individual mind maps for self-leaning development after they attend the class and learn overall picture of each chapter from the class instructor. Four problems based mind maps learning are assigned to each student. Each assignment is evaluated via mid-term and final examinations, which are issued in terms of learning concepts and applications. In the method testing, thirty students are tested and evaluated via student learning backgrounds in the past. The result shows that well-design mind maps can improve learning performance based on outcome evaluation. Especially, mind maps can reduce time-consuming and reviewing for Mathematics and Physics in SD significantly.

U.S. Isostatic Residual Gravity Grid

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — isores.bin - standard grid containing isostatic residual gravity map for U.S. Grid interval = 4 km. Projection is Albers (central meridian = 96 degrees West; base...

Revisiting Renewable Energy Map in Indonesia: Seasonal Hydro and Solar Energy Potential for Rural Off-Grid Electrification (Provincial Level

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Agung Wahyuono Ruri

2018-01-01

Full Text Available Regarding the acceleration of renewable energy diffusion in Indonesia as well as achieving the national energy mix target, renewable energy map is essential to provide useful information to build renewable energy system. This work aims at updating the renewable energy potential map, i.e. hydro and solar energy potential, with a revised model based on the global climate data. The renewable energy map is intended to assist the design off-grid system by hydropower plant or photovoltaic system, particularly for rural electrification. Specifically, the hydro energy map enables the stakeholders to determine the suitable on-site hydro energy technology (from pico-hydro, micro-hydro, mini-hydro to large hydropower plant. Meanwhile, the solar energy map depicts not only seasonal solar energy potential but also estimated energy output from photovoltaic system.

Grid generation methods

CERN Document Server

Liseikin, Vladimir D

2017-01-01

This new edition provides a description of current developments relating to grid methods, grid codes, and their applications to actual problems. Grid generation methods are indispensable for the numerical solution of differential equations. Adaptive grid-mapping techniques, in particular, are the main focus and represent a promising tool to deal with systems with singularities. This 3rd edition includes three new chapters on numerical implementations (10), control of grid properties (11), and applications to mechanical, fluid, and plasma related problems (13). Also the other chapters have been updated including new topics, such as curvatures of discrete surfaces (3). Concise descriptions of hybrid mesh generation, drag and sweeping methods, parallel algorithms for mesh generation have been included too. This new edition addresses a broad range of readers: students, researchers, and practitioners in applied mathematics, mechanics, engineering, physics and other areas of applications.

Toward accelerating landslide mapping with interactive machine learning techniques

Science.gov (United States)

Stumpf, André; Lachiche, Nicolas; Malet, Jean-Philippe; Kerle, Norman; Puissant, Anne

2013-04-01

Despite important advances in the development of more automated methods for landslide mapping from optical remote sensing images, the elaboration of inventory maps after major triggering events still remains a tedious task. Image classification with expert defined rules typically still requires significant manual labour for the elaboration and adaption of rule sets for each particular case. Machine learning algorithm, on the contrary, have the ability to learn and identify complex image patterns from labelled examples but may require relatively large amounts of training data. In order to reduce the amount of required training data active learning has evolved as key concept to guide the sampling for applications such as document classification, genetics and remote sensing. The general underlying idea of most active learning approaches is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and/or the data structure to iteratively select the most valuable samples that should be labelled by the user and added in the training set. With relatively few queries and labelled samples, an active learning strategy should ideally yield at least the same accuracy than an equivalent classifier trained with many randomly selected samples. Our study was dedicated to the development of an active learning approach for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. The developed approach is a region-based query heuristic that enables to guide the user attention towards few compact spatial batches rather than distributed points resulting in time savings of 50% and more compared to standard active learning techniques. The approach was tested with multi-temporal and multi-sensor satellite images capturing recent large scale triggering events in Brazil and China and demonstrated balanced user's and producer's accuracies between 74% and 80%. The assessment also

Integrating collaborative concept mapping in case based learning

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Alfredo Tifi

2013-03-01

Full Text Available Different significance of collaborative concept mapping and collaborative argumentation in Case Based Learning are discussed and compared in the different perspectives of answering focus questions, of fostering reflective thinking skills and in managing uncertainty in problem solving in a scaffolded environment. Marked differences are pointed out between the way concepts are used in constructing concept maps and the way meanings are adopted in case based learning through guided argumentation activities. Shared concept maps should be given different scopes, as for example a as an advance organizer in preparing a background system of concepts that will undergo transformation while accompanying the inquiry activities on case studies or problems; b together with narratives, to enhance awareness of the situated epistemologies that are being entailed in choosing certain concepts during more complex case studies, and c after-learning construction of a holistic vision of the whole domain by means of the most inclusive concepts, while scaffoldedcollaborative writing of narratives and arguments in describing-treating cases could better serve as a source of situated-inspired tools to create-refine meanings for particular concepts.

Learning Inverse Rig Mappings by Nonlinear Regression.

Science.gov (United States)

Holden, Daniel; Saito, Jun; Komura, Taku

2017-03-01

We present a framework to design inverse rig-functions-functions that map low level representations of a character's pose such as joint positions or surface geometry to the representation used by animators called the animation rig. Animators design scenes using an animation rig, a framework widely adopted in animation production which allows animators to design character poses and geometry via intuitive parameters and interfaces. Yet most state-of-the-art computer animation techniques control characters through raw, low level representations such as joint angles, joint positions, or vertex coordinates. This difference often stops the adoption of state-of-the-art techniques in animation production. Our framework solves this issue by learning a mapping between the low level representations of the pose and the animation rig. We use nonlinear regression techniques, learning from example animation sequences designed by the animators. When new motions are provided in the skeleton space, the learned mapping is used to estimate the rig controls that reproduce such a motion. We introduce two nonlinear functions for producing such a mapping: Gaussian process regression and feedforward neural networks. The appropriate solution depends on the nature of the rig and the amount of data available for training. We show our framework applied to various examples including articulated biped characters, quadruped characters, facial animation rigs, and deformable characters. With our system, animators have the freedom to apply any motion synthesis algorithm to arbitrary rigging and animation pipelines for immediate editing. This greatly improves the productivity of 3D animation, while retaining the flexibility and creativity of artistic input.

The effect of Using Mind Mapping and Learning Styles to Geography Learning outcomes of Junior High School Students

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Sigit Purwoko

2015-02-01

Full Text Available Pengaruh Penggunaan Peta Pikiran dan Gaya Belajar terhadap Hasil Belajar Geografi Siswa SMP Abstract: This study aimed to determine the effect of the use of mind maps, learning styles and inter-action using a mind map learning style on geography learning outcomes. This study was a quasi-experimental study, with a 2 x 3 factorial design study subject consisted of two classes of class VII G as experimental class and class VII F as a control class. Variables consisted of: (1 the dependent variable is the student learning outcomes; (2 the independent variable is the use of mind maps; and (3 is the moderator variable learning styles. Geography learning outcomes were measured using an objective test, whereas learning styles with questionnaires. Measurement data are then analyzed using ANOVA two paths with SPSS v.7. Results of data analysis using ANOVA two path showed that: (1 the use of mind maps significantly effect on learning outcomes geography; (2 learning style does not significantly affect the results of learning geography; and (3 there is no interaction between the use of mind maps and learning style on learning outcomes. Key Words: mind maps, learning styles, learning outcomes   Abstrak: Penelitian ini bertujuan untuk mengetahui pengaruh penggunaan peta pikiran, gaya belajar dan interaksi penggunaan peta pikiran dengan gaya belajar terhadap hasil belajar geografi. Penelitian ini merupakan penelitian eksperimen semu, dengan desain faktorial 2 x 3. Subjek penelitian terdiri dari dua kelas yaitu kelas VII G sebagai kelas eksperimen dan kelas VII F sebagai kelas kontrol. Variabel penelitian terdiri dari: (1 variabel terikat adalah hasil belajar siswa; (2 variabel bebas adalah pengguna-an peta pikiran; dan (3 variabel moderator adalah gaya belajar. Hasil belajar geografi diukur menggunakan tes objektif, sedangkan gaya belajar dengan angket. Data hasil pengukuran dianalisis menggunakan anova dua jalur dengan bantuan SPSS v.7. Hasil analisis data

OGC and Grid Interoperability in enviroGRIDS Project

Science.gov (United States)

Gorgan, Dorian; Rodila, Denisa; Bacu, Victor; Giuliani, Gregory; Ray, Nicolas

2010-05-01

the OGC Web service protocols, the advantages offered by the Grid technology - such as providing a secure interoperability between the distributed geospatial resource -and the issues introduced by the integration of distributed geospatial data in a secure environment: data and service discovery, management, access and computation. enviroGRIDS project proposes a new architecture which allows a flexible and scalable approach for integrating the geospatial domain represented by the OGC Web services with the Grid domain represented by the gLite middleware. The parallelism offered by the Grid technology is discussed and explored at the data level, management level and computation level. The analysis is carried out for OGC Web service interoperability in general but specific details are emphasized for Web Map Service (WMS), Web Feature Service (WFS), Web Coverage Service (WCS), Web Processing Service (WPS) and Catalog Service for Web (CSW). Issues regarding the mapping and the interoperability between the OGC and the Grid standards and protocols are analyzed as they are the base in solving the communication problems between the two environments: grid and geospatial. The presetation mainly highlights how the Grid environment and Grid applications capabilities can be extended and utilized in geospatial interoperability. Interoperability between geospatial and Grid infrastructures provides features such as the specific geospatial complex functionality and the high power computation and security of the Grid, high spatial model resolution and geographical area covering, flexible combination and interoperability of the geographical models. According with the Service Oriented Architecture concepts and requirements of interoperability between geospatial and Grid infrastructures each of the main functionality is visible from enviroGRIDS Portal and consequently, by the end user applications such as Decision Maker/Citizen oriented Applications. The enviroGRIDS portal is the single way

A sparse grid based method for generative dimensionality reduction of high-dimensional data

Science.gov (United States)

Bohn, Bastian; Garcke, Jochen; Griebel, Michael

2016-03-01

Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative dimensionality reduction algorithms exploit the representer theorem for reproducing kernel Hilbert spaces, their computational costs grow at least quadratically in the number n of data. Instead, we introduce a grid-based discretization approach which automatically scales just linearly in n. To circumvent the curse of dimensionality of full tensor product grids, we use the concept of sparse grids. Furthermore, in real-world applications, some embedding directions are usually more important than others and it is reasonable to refine the underlying discretization space only in these directions. To this end, we employ a dimension-adaptive algorithm which is based on the ANOVA (analysis of variance) decomposition of a function. In particular, the reconstruction error is used to measure the quality of an embedding. As an application, the study of large simulation data from an engineering application in the automotive industry (car crash simulation) is performed.

Bifurcation of learning and structure formation in neuronal maps

DEFF Research Database (Denmark)

Marschler, Christian; Faust-Ellsässer, Carmen; Starke, Jens

2014-01-01

to map formation in the laminar nucleus of the barn owl's auditory system. Using equation-free methods, we perform a bifurcation analysis of spatio-temporal structure formation in the associated synaptic-weight matrix. This enables us to analyze learning as a bifurcation process and follow the unstable...... states as well. A simple time translation of the learning window function shifts the bifurcation point of structure formation and goes along with traveling waves in the map, without changing the animal's sound localization performance....

The Effect of Guided Inquiry Learning with Mind Map to Science Process Skills and Learning Outcomes of Natural Sciences

Directory of Open Access Journals (Sweden)

Hilman .

2015-04-01

Full Text Available Pengaruh Pembelajaran Inkuiri Terbimbing dengan Mind Map terhadap Keterampilan Proses Sains dan Hasil Belajar IPA   Abstract: Science learning in junior high school aims to enable students conducts scientific inquiry, improves knowledge, concepts, and science skills. Organization materials for students supports learning process so that needs to be explored techniques that allows students to enable it. This study aimed to determine the effect of guided inquiry learning with mind map on science process skills and cognitive learning outcomes. This experimental quasi studey used pretest-posttest control group design and consisted eighth grade students of SMP Negeri 1 Papalang Mamuju of West Sulawesi. The results showed there where significant positive effect of guided inquiry learning with mind map on process science skills and cognitive learning outcomes. Key Words: guided inquiry, mind map, science process skills, cognitive learning outcomes   Abstrak: Pembelajaran Ilmu Pengetahuan Alam (IPA di SMP bertujuan agar siswa dapat melakukan inkuiri ilmiah, meningkatkan pengetahuan, konsep, dan keterampilan IPA. Dalam pembelajaran, organisasi materi berperan penting dalam memudahkan anak belajar sehingga perlu ditelaah teknik yang memudahkan siswa membuat organisasi materi. Penelitian ini bertujuan mengetahui pengaruh pembelajaran inkuiri terbimbing dengan mind map terhadap keterampilan proses sains dan hasil belajar kognitif. Penelitian kuasi eksperimen ini menggunakan rancangan pre test-post test control group design dengan subjek penelitian siswa kelas VIII SMP Negeri 1 Papalang. Hasil penelitian menunjukkan ada pengaruh positif yang signifikan pembelajaran inkuiri terbimbing dengan mind map terhadap kemampuan keterampilan proses sains dan hasil belajar kognitif siswa. Kata kunci:  inkuiri terbimbing, mind map, keterampilan proses sains,  hasil belajar kognitif

Enhancing Collaborative and Meaningful Language Learning Through Concept Mapping

Science.gov (United States)

Marriott, Rita De Cássia Veiga; Torres, Patrícia Lupion

This chapter aims to investigate new ways of foreign-language teaching/learning via a study of how concept mapping can help develop a student's reading, writing and oral skills as part of a blended methodology for language teaching known as LAPLI (Laboratorio de Aprendizagem de LInguas: The Language Learning Lab). LAPLI is a student-centred and collaborative methodology which encourages students to challenge their limitations and expand their current knowledge whilst developing their linguistic and interpersonal skills. We explore the theories that underpin LAPLI and detail the 12 activities comprising its programme with specify reference to the use of "concept mapping". An innovative table enabling a formative and summative assessment of the concept maps is formulated. Also presented are some of the qualitative and quantitative results achieved when this methodology was first implemented with a group of pre-service students studying for a degree in English and Portuguese languages at the Catholic University of Parana (PUCPR) in Brazil. The contribution of concept mapping and LAPLI to an under standing of language learning along with a consideration of the difficulties encountered in its implementation with student groups is discussed and suggestions made for future research.

Decreasing Data Analytics Time: Hybrid Architecture MapReduce-Massive Parallel Processing for a Smart Grid

Directory of Open Access Journals (Sweden)

Abdeslam Mehenni

2017-03-01

Full Text Available As our populations grow in a world of limited resources enterprise seek ways to lighten our load on the planet. The idea of modifying consumer behavior appears as a foundation for smart grids. Enterprise demonstrates the value available from deep analysis of electricity consummation histories, consumers’ messages, and outage alerts, etc. Enterprise mines massive structured and unstructured data. In a nutshell, smart grids result in a flood of data that needs to be analyzed, for better adjust to demand and give customers more ability to delve into their power consumption. Simply put, smart grids will increasingly have a flexible data warehouse attached to them. The key driver for the adoption of data management strategies is clearly the need to handle and analyze the large amounts of information utilities are now faced with. New approaches to data integration are nauseating moment; Hadoop is in fact now being used by the utility to help manage the huge growth in data whilst maintaining coherence of the Data Warehouse. In this paper we define a new Meter Data Management System Architecture repository that differ with three leaders MDMS, where we use MapReduce programming model for ETL and Parallel DBMS in Query statements(Massive Parallel Processing MPP.

Topological schemas of cognitive maps and spatial learning

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Andrey eBabichev

2016-03-01

Full Text Available Spatial navigation in mammals is based on building a mental representation of their environment---a cognitive map. However, both the nature of this cognitive map and its underpinning in neural structures and activity remains vague. A key difficulty is that these maps are collective, emergent phenomena that cannot be reduced to a simple combination of inputs provided by individual neurons. In this paper we suggest computational frameworks for integrating the spiking signals of individual cells into a spatial map, which we call schemas. We provide examples of four schemas defined by different types of topological relations that may be neurophysiologically encoded in the brain and demonstrate that each schema provides its own large-scale characteristics of the environment---the schema integrals. Moreover, we find that, in all cases, these integrals are learned at a rate which is faster than the rate of complete training of neural networks. Thus, the proposed schema framework differentiates between the cognitive aspect of spatial learning and the physiological aspect at the neural network level.

Topological Schemas of Cognitive Maps and Spatial Learning.

Science.gov (United States)

Babichev, Andrey; Cheng, Sen; Dabaghian, Yuri A

2016-01-01

Spatial navigation in mammals is based on building a mental representation of their environment-a cognitive map. However, both the nature of this cognitive map and its underpinning in neural structures and activity remains vague. A key difficulty is that these maps are collective, emergent phenomena that cannot be reduced to a simple combination of inputs provided by individual neurons. In this paper we suggest computational frameworks for integrating the spiking signals of individual cells into a spatial map, which we call schemas. We provide examples of four schemas defined by different types of topological relations that may be neurophysiologically encoded in the brain and demonstrate that each schema provides its own large-scale characteristics of the environment-the schema integrals. Moreover, we find that, in all cases, these integrals are learned at a rate which is faster than the rate of complete training of neural networks. Thus, the proposed schema framework differentiates between the cognitive aspect of spatial learning and the physiological aspect at the neural network level.

Learning the Attachment Theory with the CM-ED Concept Map Editor

Science.gov (United States)

Rueda, U.; Arruarte, A.; Elorriaga, J. A.; Herran, E.

2009-01-01

This paper presents a study carried out at the University of the Basque Country UPV/EHU with the aim of evaluating the CM-ED (concept map editor) with social education students. Concept mapping is a widely accepted technique that promotes meaningful learning. Graphically representing concepts of the learning domain and relationships between them…

Benchmarking of Grid Fault Modes in Single-Phase Grid-Connected Photovoltaic Systems

DEFF Research Database (Denmark)

Yang, Yongheng; Blaabjerg, Frede; Zou, Zhixiang

2013-01-01

Pushed by the booming installations of singlephase photovoltaic (PV) systems, the grid demands regarding the integration of PV systems are expected to be modified. Hence, the future PV systems should become more active with functionalities of Low Voltage Ride-Through (LVRT) and grid support...... phase systems under grid faults. The intent of this paper is to present a benchmarking of grid fault modes that might come in future single-phase PV systems. In order to map future challenges, the relevant synchronization and control strategies are discussed. Some faulty modes are studied experimentally...... and provided at the end of this paper. It is concluded that there are extensive control possibilities in single-phase PV systems under grid faults. The Second Order General Integral based PLL technique might be the most promising candidate for future single-phase PV systems because of its fast adaptive...

An Educational Data Mining Approach to Concept Map Construction for Web based Learning

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Anal ACHARYA

2017-01-01

Full Text Available This aim of this article is to study the use of Educational Data Mining (EDM techniques in constructing concept maps for organizing knowledge in web based learning systems whereby studying their synergistic effects in enhancing learning. This article first provides a tutorial based introduction to EDM. The applicability of web based learning systems in enhancing the efficiency of EDM techniques in real time environment is investigated. Web based learning systems often use a tool for organizing knowledge. This article explores the use of one such tool called concept map for this purpose. The pioneering works by various researchers who proposed web based learning systems in personalized and collaborative environment in this arena are next presented. A set of parameters are proposed based on which personalized and collaborative learning applications may be generalized and their performances compared. It is found that personalized learning environment uses EDM techniques more exhaustively compared to collaborative learning for concept map construction in web based environment. This article can be used as a starting point for freshers who would like to use EDM techniques for concept map construction for web based learning purposes.

Collaborative and Multilingual Approach to Learn Database Topics Using Concept Maps

Science.gov (United States)

Calvo, Iñaki

2014-01-01

Authors report on a study using the concept mapping technique in computer engineering education for learning theoretical introductory database topics. In addition, the learning of multilingual technical terminology by means of the collaborative drawing of a concept map is also pursued in this experiment. The main characteristics of a study carried out in the database subject at the University of the Basque Country during the 2011/2012 course are described. This study contributes to the field of concept mapping as these kinds of cognitive tools have proved to be valid to support learning in computer engineering education. It contributes to the field of computer engineering education, providing a technique that can be incorporated with several educational purposes within the discipline. Results reveal the potential that a collaborative concept map editor offers to fulfil the above mentioned objectives. PMID:25538957

Using enriched skeleton concept mapping to support meaningful learning

NARCIS (Netherlands)

Maree, A.J.; Bruggen, van J.M.; Jochems, W.M.G.; Cañas, A.J.; Novak, J.D.; Vanhear, J.

2012-01-01

Abstract. There has been significant interest among researchers in the instructional use of concept maps and collaboration scripts. Some studies focus on students' collaboration on concept mapping tasks; others focus on scripts to structure learning tasks and guide interactions. Little is known

Learning big data with Amazon Elastic MapReduce

CERN Document Server

Singh, Amarkant

2014-01-01

This book is aimed at developers and system administrators who want to learn about Big Data analysis using Amazon Elastic MapReduce. Basic Java programming knowledge is required. You should be comfortable with using command-line tools. Prior knowledge of AWS, API, and CLI tools is not assumed. Also, no exposure to Hadoop and MapReduce is expected.

Concept maps and the meaningful learning of science

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José Antonio C. S. Valadares

2013-03-01

Full Text Available The foundations of the Meaningful Learning Theory (MLT were laid by David Ausubel. The MLT was highly valued by the contributions of Joseph Novak and D. B. Gowin. Unlike other learning theories, the MLT has an operational component, since there are some instruments based on it and with the meaningful learning facilitation as aim. These tools were designated graphic organizers by John Trowbridge and James Wandersee (2000, pp. 100-129. One of them is the concept map created by Novak to extract meanings from an amalgam of information, having currently many applications. The other one is the Vee diagram or knowledge Vee, also called epistemological Vee or heuristic Vee. It was created by Gowin, and is an excellent organizer, for example to unpack and make transparent the unclear information from an information source. Both instruments help us in processing and becoming conceptually transparent the information, to facilitate the cognitive process of new meanings construction. In this work, after a brief introduction, it will be developed the epistemological and psychological grounds of MLT, followed by a reference to constructivist learning environments facilitators of the meaningful learning, the characterization of concept maps and exemplification of its use in various applications that have proved to be very effective from the standpoint of meaningful learning.

Construction of concept maps as tool for Biochemistry learning

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Silvia Lopes de Menezes

2006-07-01

Full Text Available The use of concept maps on the teaching of sciences has been object of worldwide research with different purposes: to detect the previous knowledge of the students on certain topics or to evaluate learning, among others. Based on Ausubel´s cognitive psychology, concept maps assume that the learning is accomplished by assimilation of new concepts and propositions to the students´ cognitive structure, contributing to establish links between the previous and new knowledge. It is especially interesting on the approach of interdisciplinary issues, as many studied in Biochemistry.The relevance of the use of concept maps on biochemistry learning was evaluated on a thirty-hour undergraduation optional course, with interdisciplinary topics, which are not usually included on introductory Biochemistry courses. The course Biochemistry of Animal Venoms was structured in seven module where the biochemical action mechanisms of the venoms of Crotalus sp (south american rattlesnake, Bothrops sp (jararaca, Loxosceles sp (brown spider, Tityus sp (yellow scorpion, Phoneutria sp (armed spider, Apis mellifera (honey bee and Latrodectus sp (black widowwere discussed. The students worked in small groups and, at each module, there were (1 an oriented study, guided by questions, texts and schemes, supervised by the teachers, (2 the construction of individual concept maps, where the local and systemic effects of the venoms should be predicted by their biochemical composition and (3 the construction of a new map by the group, incorporating the information of the individual maps. The difficulty level of these tasks was gradually increased throughout the course, with lesser time to carry out the tasks, lesser assistance during the oriented study and even lesser information on the venom effects.The course assessment was given by the number, quality and correction of the concepts relationship present in the concept maps, through a questionnaire and by the

Peningkatan hasil belajar mahasiswa melalui metode quantum learning dengan teknik Mind mapping

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Andi Mariani Ramlan

2017-08-01

Full Text Available The purpose of this study is to improve the student learning outcomes in the course of Complex Analysis by applying Quantum Learning method with Mind Mapping technique. This research is conducted to give innovation method and technique of lecturer to reach the purpose and result of learning as expected. The research runs from September to December 2013 at the University of Sembilanbelas November Kolaka, Outheast Sulawesi.  The subject of the reserach is the B grade students of class VII 2011 with a total of 34 students. This research is included in Classroom Action Research (CAR. The researchers designed the study in several cycles each cycle with stages: 1 Planning, 2 Implementation; 3 Observation and Evaluation, and 4 Reflection. The students responded is positively to learning by using Quantum Learning method with Mind Mapping technique.  The students' learning achievement is 3,29 from the ideal value of 4,00; and 88,3% Student get A Or B. Then, it is concluded that Quantum Learning method with mind mapping technique can improve student learning outcomes in Complex Analysis program.

A design of irregular grid map for large-scale Wi-Fi LAN fingerprint positioning systems.

Science.gov (United States)

Kim, Jae-Hoon; Min, Kyoung Sik; Yeo, Woon-Young

2014-01-01

The rapid growth of mobile communication and the proliferation of smartphones have drawn significant attention to location-based services (LBSs). One of the most important factors in the vitalization of LBSs is the accurate position estimation of a mobile device. The Wi-Fi positioning system (WPS) is a new positioning method that measures received signal strength indication (RSSI) data from all Wi-Fi access points (APs) and stores them in a large database as a form of radio fingerprint map. Because of the millions of APs in urban areas, radio fingerprints are seriously contaminated and confused. Moreover, the algorithmic advances for positioning face computational limitation. Therefore, we present a novel irregular grid structure and data analytics for efficient fingerprint map management. The usefulness of the proposed methodology is presented using the actual radio fingerprint measurements taken throughout Seoul, Korea.

A Design of Irregular Grid Map for Large-Scale Wi-Fi LAN Fingerprint Positioning Systems

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Jae-Hoon Kim

2014-01-01

Full Text Available The rapid growth of mobile communication and the proliferation of smartphones have drawn significant attention to location-based services (LBSs. One of the most important factors in the vitalization of LBSs is the accurate position estimation of a mobile device. The Wi-Fi positioning system (WPS is a new positioning method that measures received signal strength indication (RSSI data from all Wi-Fi access points (APs and stores them in a large database as a form of radio fingerprint map. Because of the millions of APs in urban areas, radio fingerprints are seriously contaminated and confused. Moreover, the algorithmic advances for positioning face computational limitation. Therefore, we present a novel irregular grid structure and data analytics for efficient fingerprint map management. The usefulness of the proposed methodology is presented using the actual radio fingerprint measurements taken throughout Seoul, Korea.

Cartographic Production for the FLaSH Map Study: Generation of Rugosity Grids, 2008

Science.gov (United States)

Robbins, Lisa L.; Knorr, Paul O.; Hansen, Mark

2010-01-01

Project Summary This series of raster data is a U.S. Geological Survey (USGS) Data Series release from the Florida Shelf Habitat Project (FLaSH). This disc contains two raster images in Environmental Systems Research Institute, Inc. (ESRI) raster grid format, jpeg image format, and Geo-referenced Tagged Image File Format (GeoTIFF). Data is also provided in non-image ASCII format. Rugosity grids at two resolutions (250 m and 1000 m) were generated for West Florida shelf waters to 250 m using a custom algorithm that follows the methods of Valentine and others (2004). The Methods portion of this document describes the specific steps used to generate the raster images. Rugosity, also referred to as roughness, ruggedness, or the surface-area ratio (Riley and others, 1999; Wilson and others, 2007), is a visual and quantitative measurement of terrain complexity, a common variable in ecological habitat studies. The rugosity of an area can affect biota by influencing habitat, providing shelter from elements, determining the quantity and type of living space, influencing the type and quantity of flora, affecting predator-prey relationships by providing cover and concealment, and, as an expression of vertical relief, can influence local environmental conditions such as temperature and moisture. In the marine environment rugosity can furthermore influence current flow rate and direction, increase the residence time of water in an area through eddying and current deflection, influence local water conditions such as chemistry, turbidity, and temperature, and influence the rate and nature of sedimentary deposition. State-of-the-art computer-mapping techniques and data-processing tools were used to develop shelf-wide raster and vector data layers. Florida Shelf Habitat (FLaSH) Mapping Project (http://coastal.er.usgs.gov/flash) endeavors to locate available data, identify data gaps, synthesize existing information, and expand our understanding of geologic processes in our dynamic

Variation across individuals and items determine learning outcomes from fast mapping.

Science.gov (United States)

Coutanche, Marc N; Koch, Griffin E

2017-11-01

An approach to learning words known as "fast mapping" has been linked to unique neurobiological and behavioral markers in adult humans, including rapid lexical integration. However, the mechanisms supporting fast mapping are still not known. In this study, we sought to help change this by examining factors that modulate learning outcomes. In 90 subjects, we systematically manipulated the typicality of the items used to support fast mapping (foils), and quantified learners' inclination to employ semantic, episodic, and spatial memory through the Survey of Autobiographical Memory (SAM). We asked how these factors affect lexical competition and recognition performance, and then asked how foil typicality and lexical competition are related in an independent dataset. We find that both the typicality of fast mapping foils, and individual differences in how different memory systems are employed, influence lexical competition effects after fast mapping, but not after other learning approaches. Specifically, learning a word through fast mapping with an atypical foil led to lexical competition, while a typical foil led to lexical facilitation. This effect was particularly evident in individuals with a strong tendency to employ semantic memory. We further replicated the relationship between continuous foil atypicality and lexical competition in an independent dataset. These findings suggest that semantic properties of the foils that support fast mapping can influence the degree and nature of subsequent lexical integration. Further, the effects of foils differ based on an individual's tendency to draw-on the semantic memory system. Copyright © 2017 Elsevier Ltd. All rights reserved.

USGS Map Indices Overlay Map Service from The National Map

Data.gov (United States)

U.S. Geological Survey, Department of the Interior — The USGS Map Indices service from The National Map (TNM) consists of 1x1 Degree, 30x60 Minute (100K), 15 Minute (63K), 7.5 Minute (24K), and 3.75 Minute grid...

Using a Metro Map Metaphor for organizing Web-based learning resources

DEFF Research Database (Denmark)

Grønbæk, Kaj; Bang, Tove; Hansen, Per Steen

2002-01-01

This paper briefly describes the WebNize system and how it applies a Metro Map metaphor for organizing guided tours in Web based resources. Then, experiences in using the Metro Map based tours in a Knowledge Sharing project at the library at Aarhus School of Business (ASB) in Denmark, are discussed...... is to create models for Intelligent Knowledge Solutions that can contribute to form the learning environments of the School in the 21st century. The WebNize system is used for sharing of knowledge through metro maps for specific subject areas made available in the Learning Resource Centre at ASB. The metro....... The Library has been involved in establishing a Learning Resource Center (LRC). The LRC serves as an exploratorium for the development and the testing of new forms of communication and learning, at the same time as it integrates the information resources of the electronic research library. The objective...

Mapping the ‘End Austerity Now’ protest day in Central London using a 3D Twitter density grid

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Seungho Yoo

2016-01-01

Full Text Available The mapping and spatial analysis of social media data can show the dynamics of activities in urban space, such as protest events. This work focuses on the spatial relationship between the density of geo-tagged tweets and a large anti-government protest in London on 20 June 2015. The tweets are aggregated to hexagonal grid cells to visualize activity density in different Central London areas. The results of the mapping illustrate very high densities at the beginning and endpoints of the protest (the Bank of England and Parliament Square. Additionally, there are high tweet densities in the West End and Bank than in other neighbouring areas.

The use of concept maps as an indicator of significant learning in Calculus

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Naíma Soltau Ferrão

2014-03-01

Full Text Available This paper contains reflections and results of a research that aimed to apply and analyze the use of concept maps in Higher Education as an indicator of significant learning concerning derivative as mathematical object with students that finished Differential and Integral Calculus. This is a qualitative approach, situated in the area of mathematics education, based on Ausubel's Theory of Meaningful Learning and on technique of Novak's Concept Mapping. As data acquisition instruments, use of classroom observations, questionnaire, brainstorming and digital conceptual mapping, made by an undergraduate physics course. To analyze we defined four aspects to be observed in the maps constructed by students: (i validity of propositions formed with concepts, (ii hierarchization, (iii cross-links between the propositions, and (vi the presence of applications. The identification of these elements, taken as reference to analyze the maps, allowed the collection of information about how each student has structured and correlated the set of concepts learned on the derivative of a function along their course. Based on the results, we have identified in the digital conceptual maps effective tools to evaluate the students in terms of meaningful learning about specific contents of Differential and Integral Calculus by the hierarchy of concepts, progressive differentiation and integrative reconciliation as defined in the Theory of Meaningful Learning.

An associative model of adaptive inference for learning word-referent mappings.

Science.gov (United States)

Kachergis, George; Yu, Chen; Shiffrin, Richard M

2012-04-01

People can learn word-referent pairs over a short series of individually ambiguous situations containing multiple words and referents (Yu & Smith, 2007, Cognition 106: 1558-1568). Cross-situational statistical learning relies on the repeated co-occurrence of words with their intended referents, but simple co-occurrence counts cannot explain the findings. Mutual exclusivity (ME: an assumption of one-to-one mappings) can reduce ambiguity by leveraging prior experience to restrict the number of word-referent pairings considered but can also block learning of non-one-to-one mappings. The present study first trained learners on one-to-one mappings with varying numbers of repetitions. In late training, a new set of word-referent pairs were introduced alongside pretrained pairs; each pretrained pair consistently appeared with a new pair. Results indicate that (1) learners quickly infer new pairs in late training on the basis of their knowledge of pretrained pairs, exhibiting ME; and (2) learners also adaptively relax the ME bias and learn two-to-two mappings involving both pretrained and new words and objects. We present an associative model that accounts for both results using competing familiarity and uncertainty biases.

Socioeconomic assessment of smart grids. Summary

International Nuclear Information System (INIS)

2015-07-01

In September of 2013, the President of France identified smart grids as an important part of the country's industrial strategy, given the opportunities and advantages they can offer French industry, and asked the Chairman of the RTE Management Board to prepare a road-map outlining ways to support and accelerate smart grid development. This road-map, prepared in cooperation with stakeholders from the power and smart grids industries, identifies ten actions that can be taken in priority to consolidate the smart grids sector and help French firms play a leading role in the segment. These priorities were presented to the President of France on 7 May 2014. Action items 5 and 6 of the road-map on smart grid development relate, respectively, to the quantification of the value of smart grid functions from an economic, environmental and social (impact on employment) standpoint and to the large-scale deployment of some of the functions. Two tasks were set out in the 'Smart Grids' plan for action item 5: - Create a methodological framework that, for all advanced functions, allows the quantification of benefits and costs from an economic, environmental and social (effect on jobs) standpoint; - Quantify, based on this methodological framework, the potential benefits of a set of smart grid functions considered sufficiently mature to be deployed on a large scale in the near future. Having a methodology that can be applied in the same manner to all solutions, taking into account their impacts on the environment and employment in France, will considerably add to and complement the information drawn from demonstration projects. It will notably enable comparisons of benefits provided by smart grid functions and thus help give rise to a French smart grids industry that is competitive. At first, the smart grids industry was organised around demonstration projects testing different advanced functions within specific geographic areas. These projects covered a wide enough

Socioeconomic assessment of smart grids - Summary

International Nuclear Information System (INIS)

Janssen, Tanguy

2015-07-01

In September of 2013, the President of France identified smart grids as an important part of the country's industrial strategy, given the opportunities and advantages they can offer French industry, and asked the Chairman of the RTE Management Board to prepare a road-map outlining ways to support and accelerate smart grid development. This road-map, prepared in cooperation with stakeholders from the power and smart grids industries, identifies ten actions that can be taken in priority to consolidate the smart grids sector and help French firms play a leading role in the segment. These priorities were presented to the President of France on 7 May 2014. Action items 5 and 6 of the road-map on smart grid development relate, respectively, to the quantification of the value of smart grid functions from an economic, environmental and social (impact on employment) standpoint and to the large-scale deployment of some of the functions. Two tasks were set out in the 'Smart Grids' plan for action item 5: - Create a methodological framework that, for all advanced functions, allows the quantification of benefits and costs from an economic, environmental and social (effect on jobs) standpoint; - Quantify, based on this methodological framework, the potential benefits of a set of smart grid functions considered sufficiently mature to be deployed on a large scale in the near future. Having a methodology that can be applied in the same manner to all solutions, taking into account their impacts on the environment and employment in France, will considerably add to and complement the information drawn from demonstration projects. It will notably enable comparisons of benefits provided by smart grid functions and thus help give rise to a French smart grids industry that is competitive. At first, the smart grids industry was organised around demonstration projects testing different advanced functions within specific geographic areas. These projects covered a wide enough

Triple-layer smart grid business model

DEFF Research Database (Denmark)

Ma, Zheng; Lundgaard, Morten; Jørgensen, Bo Nørregaard

2016-01-01

Viewing the smart grid with the theory of business models may open opportunities in understanding and capturing values in new markets. This study tries to discover and map the smart grid ecosystem-based business model framework with two different environments (sub-Saharan Africa and Denmark......), and identifies the parameters for the smart grid solutions to the emerging markets. This study develops a triple-layer business model including the organizational (Niche), environmental (Intermediate), and global (Dominators) factors. The result uncovers an interface of market factors and stakeholders...... in a generic smart grid constellation. The findings contribute the transferability potential of the smart grid solutions between countries, and indicate the potential to export and import smart grid solutions based on the business modeling....

Impact of Considering 110 kV Grid Structures on the Congestion Management in the German Transmission Grid

Science.gov (United States)

Hoffrichter, André; Barrios, Hans; Massmann, Janek; Venkataramanachar, Bhavasagar; Schnettler, Armin

2018-02-01

The structural changes in the European energy system lead to an increase of renewable energy sources that are primarily connected to the distribution grid. Hence the stationary analysis of the transmission grid and the regionalization of generation capacities are strongly influenced by subordinate grid structures. To quantify the impact on the congestion management in the German transmission grid, a 110 kV grid model is derived using publicly available data delivered by Open Street Map and integrated into an existing model of the European transmission grid. Power flow and redispatch simulations are performed for three different regionalization methods and grid configurations. The results show a significant impact of the 110 kV system and prove an overestimation of power flows in the transmission grid when neglecting subordinate grids. Thus, the redispatch volume in Germany to dissolve bottlenecks in case of N-1 contingencies decreases by 38 % when considering the 110 kV grid.

A theory of causal learning in children: causal maps and Bayes nets.

Science.gov (United States)

Gopnik, Alison; Glymour, Clark; Sobel, David M; Schulz, Laura E; Kushnir, Tamar; Danks, David

2004-01-01

The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children construct new causal maps and that their learning is consistent with the Bayes net formalism.

Experimentation of cooperative learning model Numbered Heads Together (NHT) type by concept maps and Teams Games Tournament (TGT) by concept maps in terms of students logical mathematics intellegences

Science.gov (United States)

Irawan, Adi; Mardiyana; Retno Sari Saputro, Dewi

2017-06-01

This research is aimed to find out the effect of learning model towards learning achievement in terms of students’ logical mathematics intelligences. The learning models that were compared were NHT by Concept Maps, TGT by Concept Maps, and Direct Learning model. This research was pseudo experimental by factorial design 3×3. The population of this research was all of the students of class XI Natural Sciences of Senior High School in all regency of Karanganyar in academic year 2016/2017. The conclusions of this research were: 1) the students’ achievements with NHT learning model by Concept Maps were better than students’ achievements with TGT model by Concept Maps and Direct Learning model. The students’ achievements with TGT model by Concept Maps were better than the students’ achievements with Direct Learning model. 2) The students’ achievements that exposed high logical mathematics intelligences were better than students’ medium and low logical mathematics intelligences. The students’ achievements that exposed medium logical mathematics intelligences were better than the students’ low logical mathematics intelligences. 3) Each of student logical mathematics intelligences with NHT learning model by Concept Maps has better achievement than students with TGT learning model by Concept Maps, students with NHT learning model by Concept Maps have better achievement than students with the direct learning model, and the students with TGT by Concept Maps learning model have better achievement than students with Direct Learning model. 4) Each of learning model, students who have logical mathematics intelligences have better achievement then students who have medium logical mathematics intelligences, and students who have medium logical mathematics intelligences have better achievement than students who have low logical mathematics intelligences.

The Effect of Guided Inquiry Learning with Mind Map to Science Process Skills and Learning Outcomes of Natural Sciences

OpenAIRE

Hilman .

2015-01-01

Pengaruh Pembelajaran Inkuiri Terbimbing dengan Mind Map terhadap Keterampilan Proses Sains dan Hasil Belajar IPA   Abstract: Science learning in junior high school aims to enable students conducts scientific inquiry, improves knowledge, concepts, and science skills. Organization materials for students supports learning process so that needs to be explored techniques that allows students to enable it. This study aimed to determine the effect of guided inquiry learning with mind map on...

Enhanced Operation of Electricity Distribution Grids Through Smart Metering PLC Network Monitoring, Analysis and Grid Conditioning

Directory of Open Access Journals (Sweden)

Iker Urrutia

2013-01-01

Full Text Available Low Voltage (LV electricity distribution grid operations can be improved through a combination of new smart metering systems’ capabilities based on real time Power Line Communications (PLC and LV grid topology mapping. This paper presents two novel contributions. The first one is a new methodology developed for smart metering PLC network monitoring and analysis. It can be used to obtain relevant information from the grid, thus adding value to existing smart metering deployments and facilitating utility operational activities. A second contribution describes grid conditioning used to obtain LV feeder and phase identification of all connected smart electric meters. Real time availability of such information may help utilities with grid planning, fault location and a more accurate point of supply management.

Outcome Mapping Virtual Learning Community - Phase II | IDRC ...

International Development Research Centre (IDRC) Digital Library (Canada)

The first phase of the project (103520) focused on developing the Outcome ... as distance learning) and strategically communicating Outcome Mapping to key ... an organization based in India with South Asian reach, to facilitate exchange ...

ASSESSING STUDENTS’ COMPETENCE IN DEVELOPING CHOROPLETH MAPS COMBINED WITH DIAGRAM MAPS

Directory of Open Access Journals (Sweden)

GABRIELA OSACI-COSTACHE

2015-01-01

Full Text Available Choropleth maps combined with diagram maps are frequently used in geography. For this reason, based on the maps developed by students, the study aims at the following: identifying and analyzing the errors made by the students; establishing and analyzing the competence level of the students; identifying the causes that led to these errors; and finding the best solutions to improve both the educational process aiming at the formation of this kind of competences and the students’ results. The map assessment was accomplished during two academic years (2013-2014 and 2014-2015, in the aftermath of the activities meant to train the competence. We assessed 105 maps prepared by the students in Cartography (Faculty of Geography, University of Bucharest based on an analytical evaluation grid, with dichotomous scale, comprising 15 criteria. This tool helped us identify the errors made by the students, as well as their competence level. By applying a questionnaire, we identified the source of the errors from the students’ perspective, while by comparing the errors and the competence levels at the end of the two academic years we were able to come up with potential solutions for the improvement of the teaching and learning process.

Concept mapping as an empowering method to promote learning, thinking, teaching and research

Directory of Open Access Journals (Sweden)

Mauri Kalervo Åhlberg

2013-01-01

Full Text Available Results and underpinning of over twenty years of research and development program of concept mapping is presented. Different graphical knowledge presentation tools, especially concept mapping and mind mapping, are compared. There are two main dimensions that differentiate graphical knowledge presentation methods: The first dimension is conceptual explicitness: from mere concepts to flexibly named links and clear propositions in concept maps. The second dimension in the classification system I am suggesting is whether there are pictures or not. Åhlbergʼs and his research groupʼs applications and developments of Novakian concept maps are compared to traditional Novakian concept maps. The main innovations include always using arrowheads to show direction of reading the concept map. Centrality of each concept is estimated from number of links to other concepts. In our empirical research over two decades, number of relevant concepts, and number of relevant propositions in studentsʼ concept maps, have been found to be the best indicators and predictors of meaningful learning. This is used in assessment of learning. Improved concept mapping is presented as a tool to analyze texts. The main innovation is numbering the links to show order of reading the concept map and to make it possible to transform concept map back to the original prose text as closely as possible. In Åhlberg and his research groupʼs research, concept mapping has been tested in all main phases of research, teaching and learning.

Teaching Plate Tectonic Concepts using GeoMapApp Learning Activities

Science.gov (United States)

Goodwillie, A. M.; Kluge, S.

2012-12-01

GeoMapApp Learning Activities ( http://serc.carleton.edu/geomapapp/collection.html ) can help educators to expose undergraduate students to a range of earth science concepts using high-quality data sets in an easy-to-use map-based interface called GeoMapApp. GeoMapApp Learning Activities require students to interact with and analyse research-quality geoscience data as a means to explore and enhance their understanding of underlying content and concepts. Each activity is freely available through the SERC-Carleton web site and offers step-by-step student instructions and answer sheets. Also provided are annotated educator versions of the worksheets that include teaching tips, additional content and suggestions for further work. The activities can be used "off-the-shelf". Or, since the educator may require flexibility to tailor the activities, the documents are provided in Word format for easy modification. Examples of activities include one on the concept of seafloor spreading that requires students to analyse global seafloor crustal age data to calculate spreading rates in different ocean basins. Another activity has students explore hot spots using radiometric age dating of rocks along the Hawaiian-Emperor seamount chain. A third focusses upon the interactive use of contours and profiles to help students visualise 3-D topography on 2-D computer screens. A fourth activity provides a study of mass wasting as revealed through geomorphological evidence. The step-by-step instructions and guided inquiry approach reduce the need for teacher intervention whilst boosting the time that students can spend on productive exploration and learning. The activities can be used, for example, in a classroom lab with the educator present and as self-paced assignments in an out-of-class setting. GeoMapApp Learning Activities are funded through the NSF GeoEd program and are aimed at students in the introductory undergraduate, community college and high school levels. The activities are

Ontology Mapping Neural Network: An Approach to Learning and Inferring Correspondences among Ontologies

Science.gov (United States)

Peng, Yefei

2010-01-01

An ontology mapping neural network (OMNN) is proposed in order to learn and infer correspondences among ontologies. It extends the Identical Elements Neural Network (IENN)'s ability to represent and map complex relationships. The learning dynamics of simultaneous (interlaced) training of similar tasks interact at the shared connections of the…

MAP as a model for practice-based learning and improvement in child psychiatry training.

Science.gov (United States)

Kataoka, Sheryl H; Podell, Jennifer L; Zima, Bonnie T; Best, Karin; Sidhu, Shawn; Jura, Martha Bates

2014-01-01

Not only is there a growing literature demonstrating the positive outcomes that result from implementing evidence based treatments (EBTs) but also studies that suggest a lack of delivery of these EBTs in "usual care" practices. One way to address this deficit is to improve the quality of psychotherapy teaching for clinicians-in-training. The Accreditation Council for Graduate Medical Education (ACGME) requires all training programs to assess residents in a number of competencies including Practice-Based Learning and Improvements (PBLI). This article describes the piloting of Managing and Adapting Practice (MAP) for child psychiatry fellows, to teach them both EBT and PBLI skills. Eight child psychiatry trainees received 5 full days of MAP training and are delivering MAP in a year-long outpatient teaching clinic. In this setting, MAP is applied to the complex, multiply diagnosed psychiatric patients that present to this clinic. This article describes how MAP tools and resources assist in teaching trainees each of the eight required competency components of PBLI, including identifying deficits in expertise, setting learning goals, performing learning activities, conducting quality improvement methods in practice, incorporating formative feedback, using scientific studies to inform practice, using technology for learning, and participating in patient education. A case example illustrates the use of MAP in teaching PBLI. MAP provides a unique way to teach important quality improvement and practice-based learning skills to trainees while training them in important psychotherapy competence.

Temporal maps and informativeness in associative learning.

Science.gov (United States)

Balsam, Peter D; Gallistel, C Randy

2009-02-01

Neurobiological research on learning assumes that temporal contiguity is essential for association formation, but what constitutes temporal contiguity has never been specified. We review evidence that learning depends, instead, on learning a temporal map. Temporal relations between events are encoded even from single experiences. The speed with which an anticipatory response emerges is proportional to the informativeness of the encoded relation between a predictive stimulus or event and the event it predicts. This principle yields a quantitative account of the heretofore undefined, but theoretically crucial, concept of temporal pairing, an account in quantitative accord with surprising experimental findings. The same principle explains the basic results in the cue competition literature, which motivated the Rescorla-Wagner model and most other contemporary models of associative learning. The essential feature of a memory mechanism in this account is its ability to encode quantitative information.

Hungarian contribution to the Global Soil Organic Carbon Map (GSOC17) using advanced machine learning algorithms and geostatistics

Science.gov (United States)

Szatmári, Gábor; Laborczi, Annamária; Takács, Katalin; Pásztor, László

2017-04-01

The knowledge about soil organic carbon (SOC) baselines and changes, and the detection of vulnerable hot spots for SOC losses and gains under climate change and changed land management is still fairly limited. Thus Global Soil Partnership (GSP) has been requested to develop a global SOC mapping campaign by 2017. GSPs concept builds on official national data sets, therefore, a bottom-up (country-driven) approach is pursued. The elaborated Hungarian methodology suits the general specifications of GSOC17 provided by GSP. The input data for GSOC17@HU mapping approach has involved legacy soil data bases, as well as proper environmental covariates related to the main soil forming factors, such as climate, organisms, relief and parent material. Nowadays, digital soil mapping (DSM) highly relies on the assumption that soil properties of interest can be modelled as a sum of a deterministic and stochastic component, which can be treated and modelled separately. We also adopted this assumption in our methodology. In practice, multiple regression techniques are commonly used to model the deterministic part. However, this global (and usually linear) models commonly oversimplify the often complex and non-linear relationship, which has a crucial effect on the resulted soil maps. Thus, we integrated machine learning algorithms (namely random forest and quantile regression forest) in the elaborated methodology, supposing then to be more suitable for the problem in hand. This approach has enable us to model the GSOC17 soil properties in that complex and non-linear forms as the soil itself. Furthermore, it has enable us to model and assess the uncertainty of the results, which is highly relevant in decision making. The applied methodology has used geostatistical approach to model the stochastic part of the spatial variability of the soil properties of interest. We created GSOC17@HU map with 1 km grid resolution according to the GSPs specifications. The map contributes to the GSPs

Empirical evidence of the effectiveness of concept mapping as a learning intervention for nuclear medicine technology students in a distance learning radiation protection and biology course.

Science.gov (United States)

Passmore, Gregory G; Owen, Mary Anne; Prabakaran, Krishnan

2011-12-01

Metacognitive learning strategies are based on instructional learning theory, which promotes deep, meaningful learning. Educators in a baccalaureate-level nuclear medicine technology program demonstrated that students enrolled in an online, distance learning section of an introductory radiation protection and radiobiology course performed better when traditional instruction was supplemented with nontraditional metacognitive learning strategies. The metacognitive learning strategy that was used is best known as concept mapping. The concept map, in addition to the standard homework problem assignment and opportunity for question-answer sessions, became the template for misconception identification and remediation interactions between the instructor and the student. The control group relied on traditional homework problems and question-answer sessions alone. Because students in both the "treatment" groups (i.e., students who used concept mapping) and the control group were distance learning students, all personal communications were conducted via e-mail or telephone. The final examination of the course was used to facilitate a quantitative comparison of the performance of students who used concept mapping and the performance of students who did not use concept mapping. The results demonstrated a significantly higher median final examination score for the concept mapping group than for the non-concept mapping group (z = -2.0381, P = 0.0415), with an appropriately large effect size (2.65). Concept mapping is a cognitive learning intervention that effectively enables meaningful learning and is suitable for use in the independent learner-oriented distance learning environments used by some nuclear medicine technology programs.

Use of concept maps to promote electrocardiogram diagnosis learning in undergraduate medical students

Science.gov (United States)

Dong, Ruimin; Yang, Xiaoyan; Xing, Bangrong; Zou, Zihao; Zheng, Zhenda; Xie, Xujing; Zhu, Jieming; Chen, Lin; Zhou, Hanjian

2015-01-01

Concept mapping is an effective method in teaching and learning, however this strategy has not been evaluated among electrocardiogram (ECG) diagnosis learning. This study explored the use of concept maps to assist ECG study, and sought to analyze whether this method could improve undergraduate students’ ECG interpretation skills. There were 126 undergraduate medical students who were randomly selected and assigned to two groups, group A (n = 63) and group B (n = 63). Group A was taught to use concept maps to learn ECG diagnosis, while group B was taught by traditional methods. After the course, all of the students were assessed by having an ECG diagnostic test. Quantitative data which comprised test score and ECG features completion index was compared by using the unpaired Student’s t-test between the two groups. Further, a feedback questionnaire on concept maps used was also completed by group A, comments were evaluated by a five-point Likert scale. The test scores of ECGs interpretation was 7.36 ± 1.23 in Group A and 6.12 ± 1.39 in Group B. A significant advantage (P = 0.018) of concept maps was observed in ECG interpretation accuracy. No difference in the average ECG features completion index was observed between Group A (66.75 ± 15.35%) and Group B (62.93 ± 13.17%). According qualitative analysis, majority of students accepted concept maps as a helpful tool. Difficult to learn at the beginning and time consuming are the two problems in using this method, nevertheless most of the students indicated to continue using it. Concept maps could be a useful pedagogical tool in enhancing undergraduate medical students’ ECG interpretation skills. Furthermore, students indicated a positive attitude to it, and perceived it as a resource for learning. PMID:26221331

Feature combination analysis in smart grid based using SOM for Sudan national grid

Science.gov (United States)

Bohari, Z. H.; Yusof, M. A. M.; Jali, M. H.; Sulaima, M. F.; Nasir, M. N. M.

2015-12-01

In the investigation of power grid security, the cascading failure in multicontingency situations has been a test because of its topological unpredictability and computational expense. Both system investigations and burden positioning routines have their limits. In this project, in view of sorting toward Self Organizing Maps (SOM), incorporated methodology consolidating spatial feature (distance)-based grouping with electrical attributes (load) to evaluate the vulnerability and cascading impact of various part sets in the force lattice. Utilizing the grouping result from SOM, sets of overwhelming stacked beginning victimized people to perform assault conspires and asses the consequent falling impact of their failures, and this SOM-based approach viably distinguishes the more powerless sets of substations than those from the conventional burden positioning and other bunching strategies. The robustness of power grids is a central topic in the design of the so called "smart grid". In this paper, to analyze the measures of importance of the nodes in a power grid under cascading failure. With these efforts, we can distinguish the most vulnerable nodes and protect them, improving the safety of the power grid. Also we can measure if a structure is proper for power grids.

Making clinical case-based learning in veterinary medicine visible: analysis of collaborative concept-mapping processes and reflections.

Science.gov (United States)

Khosa, Deep K; Volet, Simone E; Bolton, John R

2014-01-01

The value of collaborative concept mapping in assisting students to develop an understanding of complex concepts across a broad range of basic and applied science subjects is well documented. Less is known about students' learning processes that occur during the construction of a concept map, especially in the context of clinical cases in veterinary medicine. This study investigated the unfolding collaborative learning processes that took place in real-time concept mapping of a clinical case by veterinary medical students and explored students' and their teacher's reflections on the value of this activity. This study had two parts. The first part investigated the cognitive and metacognitive learning processes of two groups of students who displayed divergent learning outcomes in a concept mapping task. Meaningful group differences were found in their level of learning engagement in terms of the extent to which they spent time understanding and co-constructing knowledge along with completing the task at hand. The second part explored students' and their teacher's views on the value of concept mapping as a learning and teaching tool. The students' and their teacher's perceptions revealed congruent and contrasting notions about the usefulness of concept mapping. The relevance of concept mapping to clinical case-based learning in veterinary medicine is discussed, along with directions for future research.

The effects of a concept map-based support tool on simulation-based inquiry learning

NARCIS (Netherlands)

Hagemans, M.G.; van der Meij, Hans; de Jong, Anthonius J.M.

2013-01-01

Students often need support to optimize their learning in inquiry learning environments. In 2 studies, we investigated the effects of adding concept-map-based support to a simulation-based inquiry environment on kinematics. The concept map displayed the main domain concepts and their relations,

Vocabulary learning in a Yorkshire terrier: slow mapping of spoken words.

Directory of Open Access Journals (Sweden)

Ulrike Griebel

Full Text Available Rapid vocabulary learning in children has been attributed to "fast mapping", with new words often claimed to be learned through a single presentation. As reported in 2004 in Science a border collie (Rico not only learned to identify more than 200 words, but fast mapped the new words, remembering meanings after just one presentation. Our research tests the fast mapping interpretation of the Science paper based on Rico's results, while extending the demonstration of large vocabulary recognition to a lap dog. We tested a Yorkshire terrier (Bailey with the same procedures as Rico, illustrating that Bailey accurately retrieved randomly selected toys from a set of 117 on voice command of the owner. Second we tested her retrieval based on two additional voices, one male, one female, with different accents that had never been involved in her training, again showing she was capable of recognition by voice command. Third, we did both exclusion-based training of new items (toys she had never seen before with names she had never heard before embedded in a set of known items, with subsequent retention tests designed as in the Rico experiment. After Bailey succeeded on exclusion and retention tests, a crucial evaluation of true mapping tested items previously successfully retrieved in exclusion and retention, but now pitted against each other in a two-choice task. Bailey failed on the true mapping task repeatedly, illustrating that the claim of fast mapping in Rico had not been proven, because no true mapping task had ever been conducted with him. It appears that the task called retention in the Rico study only demonstrated success in retrieval by a process of extended exclusion.

SmartGrids, Effectiveness for Everybody. State of the art and lessons learned from the past (Work package 1); Smart Grids. Rendement voor Iedereen. Stand van zaken en geleerde lessen uit het verleden (Werkpakket 1)

Energy Technology Data Exchange (ETDEWEB)

Van Melle, T.; Haaksma, V.; Van Breevoort, P.; Graveland, M.; Slingerland, E.; Winkel, T.; Hoen, V.; Noach, C. [Ecofys, Utrecht (Netherlands); Boerakker, Y.; Karatay, E.; Sanberg, T.; Faasen, C.; Mulder, W.; Huibers, M.; Maandag, M. [DNV KEMA, Arnhem (Netherlands); Milovanovic, M.; Bolderdijk, J.W.; Steg, L. [Rijksuniversiteit Groningen RUG, Groningen (Netherlands); Kapitein, A. [Cap Gemini Consulting, Utrecht (Netherlands); Bruning, F.; Berg, R. [LomboXnet, Utrecht (Netherlands); Boumans, F. [Hogeschool Utrecht, Utrecht (Netherlands)

2012-09-15

The aim of the title Smart Grids project is to improve accessibility of attractiveness of renewable energy for the Utrecht region for everyone. The project aims to develop, test and implement new business cases and service concepts for medium-sized smart grids in Utrecht and Amersfoort (both in the Netherlands). The project covers a total of two hundred houses and businesses. This report presents the results of Work Package 1: technical aspects of smart grids. Attention is also paid to consumer behavior with respect to smart grids and financial concepts for smart grids. Finally, an overview is given of the lessons learned from other similar pilots in the Netherlands and outside the Utrecht region [Dutch] Het Smart Grids project wil duurzame energie in de regio Utrecht bereikbaar en aantrekkelijk maken voor iedereen. Het project heeft tot doel nieuwe business cases en dienstverleningsconcepten te ontwikkelen, te testen en te realiseren voor middelgrote smart grids in Utrecht en Amersfoort. Het betreft in totaal tweehonderd woningen en bedrijven. In dit rapport worden de resultaten van Work Package 1 besproken: technische aspecten van smart grids. Daarnaast wordt aandacht besteed aan het consumentengedrag met betrekking tot smart grids, financieringsconstructies voor smart grids. Tenslotte wordt een overzicht gegeven van de lessen uit andere pilots in Nederland en daarbuiten op het gebied van smart grids.

Peningkatan Hasil Belajar Kompetensi Dasar Mengklasifikasikan Jenis Bisnis Ritel melalui Model Discovery Learning dengan Media Mind Mapping

Directory of Open Access Journals (Sweden)

Sri Lestari

2016-11-01

Full Text Available This research aimed to determine how is the implementation of discovery learning model with mind mapping media on the basic comptences of clasify kinds of retail business and whether the implementation of the discovery learning model with mind mapping media can increase learning outcomes of student. This research conducted using qualitative approach and quantitative in the planning of class action research by two cycles with research time for every cycle 2 meeting @ 3x45 minute. The result showed that by using discovery learning model with mind mapping media learning outcomes of student was good in the aspect of knowledge, skill, and the attitude have increased. Abstrak : Penelitian ini bertujuan untuk mengetahui bagaimana penerapan model discovery learning dengan menggunakan media mind mapping pada kompetensi dasar mengklasifikasikan jenis bisnis ritel dan apakah penerapan model discovery learning dengan menggunakan media mind mapping dapat meningkatkan hasil belajar siswa. Penelitian dilakukan dengan pendekatan kualitatif dan kuantitatif dalam rancangan penelitian tindakan kelas dengan dua siklus dengan waktu penelitian untuk masing-masing siklus 2 pertemuan @ 3 x 45 menit.  yang hasilnya menunjukkan bahwa melalui penggunaan model discovery learning dengan media mind mapping hasil belajar siswa baik dalam ranah pengetahuan, ketrampilan, maupun sikap mengalami peningkatan.

MAPCUMBA: A fast iterative multi-grid map-making algorithm for CMB experiments

Science.gov (United States)

Doré, O.; Teyssier, R.; Bouchet, F. R.; Vibert, D.; Prunet, S.

2001-07-01

The data analysis of current Cosmic Microwave Background (CMB) experiments like BOOMERanG or MAXIMA poses severe challenges which already stretch the limits of current (super-) computer capabilities, if brute force methods are used. In this paper we present a practical solution for the optimal map making problem which can be used directly for next generation CMB experiments like ARCHEOPS and TopHat, and can probably be extended relatively easily to the full PLANCK case. This solution is based on an iterative multi-grid Jacobi algorithm which is both fast and memory sparing. Indeed, if there are Ntod data points along the one dimensional timeline to analyse, the number of operations is of O (Ntod \\ln Ntod) and the memory requirement is O (Ntod). Timing and accuracy issues have been analysed on simulated ARCHEOPS and TopHat data, and we discuss as well the issue of the joint evaluation of the signal and noise statistical properties.

Integrating Concept Mapping into Information Systems Education for Meaningful Learning and Assessment

Science.gov (United States)

Wei, Wei; Yue, Kwok-Bun

2017-01-01

Concept map (CM) is a theoretically sound yet easy to learn tool and can be effectively used to represent knowledge. Even though many disciplines have adopted CM as a teaching and learning tool to improve learning effectiveness, its application in IS curriculum is sparse. Meaningful learning happens when one iteratively integrates new concepts and…

Utility-based Reinforcement Learning for Reactive Grids

OpenAIRE

Perez , Julien; Germain-Renaud , Cécile; Kégl , Balázs; Loomis , C.

2008-01-01

International audience; Large scale production grids are an important case for autonomic computing. They follow a mutualization paradigm: decision-making (human or automatic) is distributed and largely independent, and, at the same time, it must implement the highlevel goals of the grid management. This paper deals with the scheduling problem with two partially conflicting goals: fairshare and Quality of Service (QoS). Fair sharing is a wellknown issue motivated by return on investment for pa...

Data Compression of Hydrocarbon Reservoir Simulation Grids

KAUST Repository

Chavez, Gustavo Ivan

2015-05-28

A dense volumetric grid coming from an oil/gas reservoir simulation output is translated into a compact representation that supports desired features such as interactive visualization, geometric continuity, color mapping and quad representation. A set of four control curves per layer results from processing the grid data, and a complete set of these 3-dimensional surfaces represents the complete volume data and can map reservoir properties of interest to analysts. The processing results yield a representation of reservoir simulation results which has reduced data storage requirements and permits quick performance interaction between reservoir analysts and the simulation data. The degree of reservoir grid compression can be selected according to the quality required, by adjusting for different thresholds, such as approximation error and level of detail. The processions results are of potential benefit in applications such as interactive rendering, data compression, and in-situ visualization of large-scale oil/gas reservoir simulations.

Listening to Students: Customer Journey Mapping at Birmingham City University Library and Learning Resources

Science.gov (United States)

Andrews, Judith; Eade, Eleanor

2013-01-01

Birmingham City University's Library and Learning Resources' strategic aim is to improve student satisfaction. A key element is the achievement of the Customer Excellence Standard. An important component of the standard is the mapping of services to improve quality. Library and Learning Resources has developed a methodology to map these…

Using Hadoop MapReduce for Parallel Genetic Algorithms: A Comparison of the Global, Grid and Island Models.

Science.gov (United States)

Ferrucci, Filomena; Salza, Pasquale; Sarro, Federica

2017-06-29

The need to improve the scalability of Genetic Algorithms (GAs) has motivated the research on Parallel Genetic Algorithms (PGAs), and different technologies and approaches have been used. Hadoop MapReduce represents one of the most mature technologies to develop parallel algorithms. Based on the fact that parallel algorithms introduce communication overhead, the aim of the present work is to understand if, and possibly when, the parallel GAs solutions using Hadoop MapReduce show better performance than sequential versions in terms of execution time. Moreover, we are interested in understanding which PGA model can be most effective among the global, grid, and island models. We empirically assessed the performance of these three parallel models with respect to a sequential GA on a software engineering problem, evaluating the execution time and the achieved speedup. We also analysed the behaviour of the parallel models in relation to the overhead produced by the use of Hadoop MapReduce and the GAs' computational effort, which gives a more machine-independent measure of these algorithms. We exploited three problem instances to differentiate the computation load and three cluster configurations based on 2, 4, and 8 parallel nodes. Moreover, we estimated the costs of the execution of the experimentation on a potential cloud infrastructure, based on the pricing of the major commercial cloud providers. The empirical study revealed that the use of PGA based on the island model outperforms the other parallel models and the sequential GA for all the considered instances and clusters. Using 2, 4, and 8 nodes, the island model achieves an average speedup over the three datasets of 1.8, 3.4, and 7.0 times, respectively. Hadoop MapReduce has a set of different constraints that need to be considered during the design and the implementation of parallel algorithms. The overhead of data store (i.e., HDFS) accesses, communication, and latency requires solutions that reduce data store

How employees perceive organizational learning: construct validation of the 25-item short form of the strategic learning assessment map (SF-SLAM)

NARCIS (Netherlands)

Mainert, Jakob; Niepel, Christoph; Lans, T.; Greiff, Samuel

2018-01-01

Purpose: The Strategic Learning Assessment Map (SLAM) originally assessed organizational learning (OL) at the level of the firm by addressing managers, who rated OL in the SLAM on five dimensions of individual learning, group learning, organizational learning, feed-forward learning, and feedback

The comparative effect of individually-generated vs. collaboratively-generated computer-based concept mapping on science concept learning

Science.gov (United States)

Kwon, So Young

Using a quasi-experimental design, the researcher investigated the comparative effects of individually-generated and collaboratively-generated computer-based concept mapping on middle school science concept learning. Qualitative data were analyzed to explain quantitative findings. One hundred sixty-one students (74 boys and 87 girls) in eight, seventh grade science classes at a middle school in Southeast Texas completed the entire study. Using prior science performance scores to assure equivalence of student achievement across groups, the researcher assigned the teacher's classes to one of the three experimental groups. The independent variable, group, consisted of three levels: 40 students in a control group, 59 students trained to individually generate concept maps on computers, and 62 students trained to collaboratively generate concept maps on computers. The dependent variables were science concept learning as demonstrated by comprehension test scores, and quality of concept maps created by students in experimental groups as demonstrated by rubric scores. Students in the experimental groups received concept mapping training and used their newly acquired concept mapping skills to individually or collaboratively construct computer-based concept maps during study time. The control group, the individually-generated concept mapping group, and the collaboratively-generated concept mapping group had equivalent learning experiences for 50 minutes during five days, excepting that students in a control group worked independently without concept mapping activities, students in the individual group worked individually to construct concept maps, and students in the collaborative group worked collaboratively to construct concept maps during their study time. Both collaboratively and individually generated computer-based concept mapping had a positive effect on seventh grade middle school science concept learning but neither strategy was more effective than the other. However

FermiGrid - experience and future plans

International Nuclear Information System (INIS)

Chadwick, K.; Berman, E.; Canal, P.; Hesselroth, T.; Garzoglio, G.; Levshina, T.; Sergeev, V.; Sfiligoi, I.; Timm, S.; Yocum, D.

2007-01-01

Fermilab supports a scientific program that includes experiments and scientists located across the globe. In order to better serve this community, Fermilab has placed its production computer resources in a Campus Grid infrastructure called 'FermiGrid'. The FermiGrid infrastructure allows the large experiments at Fermilab to have priority access to their own resources, enables sharing of these resources in an opportunistic fashion, and movement of work (jobs, data) between the Campus Grid and National Grids such as Open Science Grid and the WLCG. FermiGrid resources support multiple Virtual Organizations (VOs), including VOs from the Open Science Grid (OSG), EGEE and the Worldwide LHC Computing Grid Collaboration (WLCG). Fermilab also makes leading contributions to the Open Science Grid in the areas of accounting, batch computing, grid security, job management, resource selection, site infrastructure, storage management, and VO services. Through the FermiGrid interfaces, authenticated and authorized VOs and individuals may access our core grid services, the 10,000+ Fermilab resident CPUs, near-petabyte (including CMS) online disk pools and the multi-petabyte Fermilab Mass Storage System. These core grid services include a site wide Globus gatekeeper, VO management services for several VOs, Fermilab site authorization services, grid user mapping services, as well as job accounting and monitoring, resource selection and data movement services. Access to these services is via standard and well-supported grid interfaces. We will report on the user experience of using the FermiGrid campus infrastructure interfaced to a national cyberinfrastructure--the successes and the problems

The Effects of a Concept Map-Based Support Tool on Simulation-Based Inquiry Learning

Science.gov (United States)

Hagemans, Mieke G.; van der Meij, Hans; de Jong, Ton

2013-01-01

Students often need support to optimize their learning in inquiry learning environments. In 2 studies, we investigated the effects of adding concept-map-based support to a simulation-based inquiry environment on kinematics. The concept map displayed the main domain concepts and their relations, while dynamic color coding of the concepts displayed…

Behaviorism, latent learning, and cognitive maps: needed revisions in introductory psychology textbooks.

Science.gov (United States)

Jensen, Robert

2006-01-01

This paper critically assesses the scholarship in introductory psychology textbooks in relation to the topic of latent learning. A review of the treatment of latent learning in 48 introductory psychology textbooks published between 1948 and 2004, with 21 of these texts published since 1999, reveals that the scholarship on the topic of latent learning demonstrated in introductory textbooks warrants improvement. Errors that persist in textbooks include the assertion that the latent learning experiments demonstrate unequivocally that reinforcement was not necessary for learning to occur, that behavioral theories could not account for the results of the latent learning experiments, that B. F. Skinner was an S-R association behaviorist who argued that reinforcement is necessary for learning to occur, and that because behavioral theories (including that of B. F. Skinner) were unable explain the results of the latent learning experiments the cognitive map invoked by Edward Tolman is the only explanation for latent learning. Finally, the validity of the cognitive map is typically accepted without question. Implications of the presence of these errors for students and the discipline are considered. Lastly, remedies are offered to improve the scholarship found in introductory psychology textbooks.

Vocabulary Learning in a Yorkshire Terrier: Slow Mapping of Spoken Words

Science.gov (United States)

Griebel, Ulrike; Oller, D. Kimbrough

2012-01-01

Rapid vocabulary learning in children has been attributed to “fast mapping”, with new words often claimed to be learned through a single presentation. As reported in 2004 in Science a border collie (Rico) not only learned to identify more than 200 words, but fast mapped the new words, remembering meanings after just one presentation. Our research tests the fast mapping interpretation of the Science paper based on Rico's results, while extending the demonstration of large vocabulary recognition to a lap dog. We tested a Yorkshire terrier (Bailey) with the same procedures as Rico, illustrating that Bailey accurately retrieved randomly selected toys from a set of 117 on voice command of the owner. Second we tested her retrieval based on two additional voices, one male, one female, with different accents that had never been involved in her training, again showing she was capable of recognition by voice command. Third, we did both exclusion-based training of new items (toys she had never seen before with names she had never heard before) embedded in a set of known items, with subsequent retention tests designed as in the Rico experiment. After Bailey succeeded on exclusion and retention tests, a crucial evaluation of true mapping tested items previously successfully retrieved in exclusion and retention, but now pitted against each other in a two-choice task. Bailey failed on the true mapping task repeatedly, illustrating that the claim of fast mapping in Rico had not been proven, because no true mapping task had ever been conducted with him. It appears that the task called retention in the Rico study only demonstrated success in retrieval by a process of extended exclusion. PMID:22363421

Analyzing Grid Log Data with Affinity Propagation

NARCIS (Netherlands)

Modena, G.; van Someren, M.W.; Ali, M; Bosse, T.; Hindriks, K.V.; Hoogendoorn, M.; Jonker, C.M; Treur, J.

2013-01-01

In this paper we present an unsupervised learning approach to detect meaningful job traffic patterns in Grid log data. Manual anomaly detection on modern Grid environments is troublesome given their increasing complexity, the distributed, dynamic topology of the network and heterogeneity of the jobs

FermiGrid-experience and future plans

International Nuclear Information System (INIS)

Chadwick, K; Berman, E; Canal, P; Hesselroth, T; Garzoglio, G; Levshina, T; Sergeev, V; Sfiligoi, I; Sharma, N; Timm, S; Yocum, D R

2008-01-01

Fermilab supports a scientific program that includes experiments and scientists located across the globe. In order to better serve this community, Fermilab has placed its production computer resources in a Campus Grid infrastructure called 'FermiGrid'. The FermiGrid infrastructure allows the large experiments at Fermilab to have priority access to their own resources, enables sharing of these resources in an opportunistic fashion, and movement of work (jobs, data) between the Campus Grid and National Grids such as Open Science Grid (OSG) and the Worldwide LHC Computing Grid Collaboration (WLCG). FermiGrid resources support multiple Virtual Organizations (VOs), including VOs from the OSG, EGEE, and the WLCG. Fermilab also makes leading contributions to the Open Science Grid in the areas of accounting, batch computing, grid security, job management, resource selection, site infrastructure, storage management, and VO services. Through the FermiGrid interfaces, authenticated and authorized VOs and individuals may access our core grid services, the 10,000+ Fermilab resident CPUs, near-petabyte (including CMS) online disk pools and the multi-petabyte Fermilab Mass Storage System. These core grid services include a site wide Globus gatekeeper, VO management services for several VOs, Fermilab site authorization services, grid user mapping services, as well as job accounting and monitoring, resource selection and data movement services. Access to these services is via standard and well-supported grid interfaces. We will report on the user experience of using the FermiGrid campus infrastructure interfaced to a national cyberinfrastructure - the successes and the problems

Cloud vector mapping using MODIS 09 Climate Modeling Grid (CMG) for the year 2010 and 2011

International Nuclear Information System (INIS)

Jah, Asjad Asif; Farrukh, Yousaf Bin; Ali, Rao Muhammad Saeed

2013-01-01

An alternate use for MODIS images was sought by mapping cloud movement directions and dissipation time during the 2010 and 2011 floods. MODIS Level-02 daily CMG (Climate Modelling Grid) land-cover images were downloaded and subsequently rectified and clipped to the study area. These images were then put together to observe the direction of cloud movement and vectorize the observed paths. Initial findings suggest that usually cloud does not have a prolonged coverage period over the northern humid region of the country and dissipates within less than 24-hours. Additionally, this led to the development of a robust methodology for cloud motion analysis using FOSS and market leading GIS utilities

Concept Mapping as a Learning Tool for the Employment Relations Degree

Science.gov (United States)

Martinez-Canas, Ricardo; Ruiz-Palomino, Pablo

2011-01-01

Concept mapping is a technique to represent relationships between concepts that can help students to improve their meaningful learning. Using the cognitive theories proposed by Ausubel (1968), concept maps can help instructors and students to enhance their logical thinking and study skills by revealing connections among concepts that can simplify…

Basin and Range Province, Western US, USGS Grids #2

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These grid files were used to produce gravity and basin depth maps of the Basin and Range Province, western United States. The maps show gravity values and modeled...

Basin and Range Province, Western US, USGS Grids, #1

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These grid files were used to produce gravity and basin depth maps of the Basin and Range Province, western United States. The maps show gravity values and modeled...

Basin and Range Province, Western US, USGS Grids #3

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These grid files were used to produce gravity and basin depth maps of the Basin and Range Province, western United States. The maps show gravity values and modeled...

Basin and Range Province, Western US, USGS Grids #5

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These grid files were used to produce gravity and basin depth maps of the Basin and Range Province, western United States. The maps show gravity values and modeled...

Basin and Range Province, Western US, USGS Grids #4

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These grid files were used to produce gravity and basin depth maps of the Basin and Range Province, western United States. The maps show gravity values and modeled...

Distribution Integration | Grid Modernization | NREL

Science.gov (United States)

Distribution Integration Distribution Integration The goal of NREL's distribution integration research is to tackle the challenges facing the widespread integration of distributed energy resources NREL engineers mapping out a grid model on a whiteboard. NREL's research on the integration of

Mapping Civic Engagement: A Case Study of Service-Learning in Appalachia

Science.gov (United States)

Mann, Jessica; Casebeer, Daniel

2016-01-01

This study uses social cartography to map student perceptions of a co-curricular service-learning project in an impoverished rural community. As a complement to narrative discourse, mapping provides an opportunity to visualize not only the spatial nature of the educational experience but also, in this case, the benefits of civic engagement. The…

Maps and geographic information in a lifelong learning process

DEFF Research Database (Denmark)

Brande-Lavridsen, Hanne

2005-01-01

may be acquired through a systematic supplementary and further education. This article focuses on what universities -- especially Aalborg University - as well as alternative learning methods such as distance education via the Internet can offer to Map and Geodata people....

Method of Automatic Ontology Mapping through Machine Learning and Logic Mining

Institute of Scientific and Technical Information of China (English)

王英林

2004-01-01

Ontology mapping is the bottleneck of handling conflicts among heterogeneous ontologies and of implementing reconfiguration or interoperability of legacy systems. We proposed an ontology mapping method by using machine learning, type constraints and logic mining techniques. This method is able to find concept correspondences through instances and the result is optimized by using an error function; it is able to find attribute correspondence between two equivalent concepts and the mapping accuracy is enhanced by combining together instances learning, type constraints and the logic relations that are imbedded in instances; moreover, it solves the most common kind of categorization conflicts. We then proposed a merging algorithm to generate the shared ontology and proposed a reconfigurable architecture for interoperation based on multi agents. The legacy systems are encapsulated as information agents to participate in the integration system. Finally we give a simplified case study.

The Effect of Using Concept Maps in Elementary Linear Algebra Course on Students’ Learning

Science.gov (United States)

Syarifuddin, H.

2018-04-01

This paper presents the results of a classroom action research that was done in Elementary Linear Algebra course at Universitas Negeri Padang. The focus of the research want to see the effect of using concept maps in the course on students’ learning. Data in this study were collected through classroom observation, students’ reflective journal and concept maps that were created by students. The result of the study was the using of concept maps in Elementary Linera Algebra course gave positive effect on students’ learning.

FEDERAL USERS CONFERENCE PRODUCT LINE TOOL SET (PLTS) MAP PRODUCTION SYSTEM (MPS) ATLAS CUSTOM GRIDS [Rev 0 was draft

Energy Technology Data Exchange (ETDEWEB)

HAYENGA, J.L.

2006-12-19

Maps, and more importantly Atlases, are assisting the user community in managing a large land area with complex issues, the most complex of which is the management of nuclear waste. The techniques and experiences discussed herein were gained while developing several atlases for use at the US Department of Energy's Hanford Site. The user community requires the ability to locate not only waste sites, but other features as well. Finding a specific waste site on a map and in the field is a difficult task at a site the size of Hanford. To find a specific waste site, the user begins by locating the item or object in an index, then locating the feature on the corresponding map within an atlas. Locating features requires a method for indexing them. The location index and how to place it on a map or atlas is the central theme presented in this article. The user requirements for atlases forced the design team to develop new and innovative solutions for requirements that Product Line Tool Set (PLTS) Map Production System (MPS)-Atlas was not designed to handle. The layout of the most complex atlases includes custom reference grids, multiple data frames, multiple map series, and up to 250 maps. All of these functional requirements are at the extreme edge of the capabilities of PLTS MPS-Atlas. This document outlines the setup of an atlas using PLTS MPS-Atlas to meet these requirements.

FEDERAL USERS CONFERENCE PRODUCT LINE TOOL SET (PLTS) MAP PRODUCTION SYSTEM (MPS) ATLAS CUSTOM GRIDS [Rev 0 was draft

International Nuclear Information System (INIS)

HAYENGA, J.L.

2006-01-01

Maps, and more importantly Atlases, are assisting the user community in managing a large land area with complex issues, the most complex of which is the management of nuclear waste. The techniques and experiences discussed herein were gained while developing several atlases for use at the US Department of Energy's Hanford Site. The user community requires the ability to locate not only waste sites, but other features as well. Finding a specific waste site on a map and in the field is a difficult task at a site the size of Hanford. To find a specific waste site, the user begins by locating the item or object in an index, then locating the feature on the corresponding map within an atlas. Locating features requires a method for indexing them. The location index and how to place it on a map or atlas is the central theme presented in this article. The user requirements for atlases forced the design team to develop new and innovative solutions for requirements that Product Line Tool Set (PLTS) Map Production System (MPS)-Atlas was not designed to handle. The layout of the most complex atlases includes custom reference grids, multiple data frames, multiple map series, and up to 250 maps. All of these functional requirements are at the extreme edge of the capabilities of PLTS MPS-Atlas. This document outlines the setup of an atlas using PLTS MPS-Atlas to meet these requirements

Grid Integration of Offshore Wind | Wind | NREL

Science.gov (United States)

Grid Integration of Offshore Wind Grid Integration of Offshore Wind Much can be learned from the existing land-based integration research for handling the variability and uncertainty of the wind resource Arklow Bank offshore wind park consists of seven GE Wind 3.6-MW wind turbines. Integration and

Heat demand mapping and district heating grid expansion analysis: Case study of Velika Gorica

Directory of Open Access Journals (Sweden)

Dorotić Hrvoje

2017-01-01

Full Text Available Highly efficient cogeneration and district heating systems have a significant potential for primary energy savings and the reduction of greenhouse gas emissions through the utilization of a waste heat and renewable energy sources. These potentials are still highly underutilized in most European countries. They also play a key role in the planning of future energy systems due to their positive impact on the increase of integration of intermittent renewable energy sources, for example wind and solar in a combination with power to heat technologies. In order to ensure optimal levels of district heating penetration into an energy system, a comprehensive analysis is necessary to determine the actual demands and the potential energy supply. Economical analysis of the grid expansion by using the GIS based mapping methods hasn’t been demonstrated so far. This paper presents a heat demand mapping methodology and the use of its output for the district heating network expansion analysis. The result are showing that more than 59% of the heat demand could be covered by the district heating in the city of Velika Gorica, which is two times more than the present share. The most important reason of the district heating's unfulfilled potential is already existing natural gas infrastructure.

Heat demand mapping and district heating grid expansion analysis: Case study of Velika Gorica

Science.gov (United States)

Dorotić, Hrvoje; Novosel, Tomislav; Duić, Neven; Pukšec, Tomislav

2017-10-01

Highly efficient cogeneration and district heating systems have a significant potential for primary energy savings and the reduction of greenhouse gas emissions through the utilization of a waste heat and renewable energy sources. These potentials are still highly underutilized in most European countries. They also play a key role in the planning of future energy systems due to their positive impact on the increase of integration of intermittent renewable energy sources, for example wind and solar in a combination with power to heat technologies. In order to ensure optimal levels of district heating penetration into an energy system, a comprehensive analysis is necessary to determine the actual demands and the potential energy supply. Economical analysis of the grid expansion by using the GIS based mapping methods hasn't been demonstrated so far. This paper presents a heat demand mapping methodology and the use of its output for the district heating network expansion analysis. The result are showing that more than 59% of the heat demand could be covered by the district heating in the city of Velika Gorica, which is two times more than the present share. The most important reason of the district heating's unfulfilled potential is already existing natural gas infrastructure.

Mapping, Navigation, and Learning for Off-Road Traversal

DEFF Research Database (Denmark)

Konolige, Kurt; Agrawal, Motilal; Blas, Morten Rufus

2009-01-01

The challenge in the DARPA Learning Applied to Ground Robots (LAGR) project is to autonomously navigate a small robot using stereo vision as the main sensor. During this project, we demonstrated a complete autonomous system for off-road navigation in unstructured environments, using stereo vision......, online terrain traversability learning, visual odometry, map registration, planning, and control. At the end of 3 years, the system we developed outperformed all nine other teams in final blind tests over previously unseen terrain.......The challenge in the DARPA Learning Applied to Ground Robots (LAGR) project is to autonomously navigate a small robot using stereo vision as the main sensor. During this project, we demonstrated a complete autonomous system for off-road navigation in unstructured environments, using stereo vision...

Machine Learning Classification of Buildings for Map Generalization

Directory of Open Access Journals (Sweden)

Jaeeun Lee

2017-10-01

Full Text Available A critical problem in mapping data is the frequent updating of large data sets. To solve this problem, the updating of small-scale data based on large-scale data is very effective. Various map generalization techniques, such as simplification, displacement, typification, elimination, and aggregation, must therefore be applied. In this study, we focused on the elimination and aggregation of the building layer, for which each building in a large scale was classified as “0-eliminated,” “1-retained,” or “2-aggregated.” Machine-learning classification algorithms were then used for classifying the buildings. The data of 1:1000 scale and 1:25,000 scale digital maps obtained from the National Geographic Information Institute were used. We applied to these data various machine-learning classification algorithms, including naive Bayes (NB, decision tree (DT, k-nearest neighbor (k-NN, and support vector machine (SVM. The overall accuracies of each algorithm were satisfactory: DT, 88.96%; k-NN, 88.27%; SVM, 87.57%; and NB, 79.50%. Although elimination is a direct part of the proposed process, generalization operations, such as simplification and aggregation of polygons, must still be performed for buildings classified as retained and aggregated. Thus, these algorithms can be used for building classification and can serve as preparatory steps for building generalization.

Grids for Kids gives next-generation IT an early start

CERN Multimedia

2008-01-01

"Grids for Kids gives children a crash course in grid computing," explains co-organiser Anna Cook of the Enabling Grids for E-sciencE project. "We introduce them to concepts such as middleware, parallel processing and supercomputing, and give them opportunities for hands-on learning.

Concept mapping to promote meaningful learning, help relate theory to practice and improve learning self-efficacy in Asian mental health nursing students: A mixed-methods pilot study.

Science.gov (United States)

Bressington, Daniel T; Wong, Wai-Kit; Lam, Kar Kei Claire; Chien, Wai Tong

2018-01-01

Student nurses are provided with a great deal of knowledge within university, but they can find it difficult to relate theory to nursing practice. This study aimed to test the appropriateness and feasibility of assessing Novak's concept mapping as an educational strategy to strengthen the theory-practice link, encourage meaningful learning and enhance learning self-efficacy in nursing students. This pilot study utilised a mixed-methods quasi-experimental design. The study was conducted in a University school of Nursing in Hong Kong. A total of 40 third-year pre-registration Asian mental health nursing students completed the study; 12 in the concept mapping (CM) group and 28 in the usual teaching methods (UTM) group. The impact of concept mapping was evaluated thorough analysis of quantitative changes in students' learning self-efficacy, analysis of the structure and contents of the concept maps (CM group), a quantitative measure of students' opinions about their reflective learning activities and content analysis of qualitative data from reflective written accounts (CM group). There were no significant differences in self-reported learning self-efficacy between the two groups (p=0.38). The concept mapping helped students identify their current level of understanding, but the increased awareness may cause an initial drop in learning self-efficacy. The results highlight that most CM students were able to demonstrate meaningful learning and perceived that concept mapping was a useful reflective learning strategy to help them to link theory and practice. The results provide preliminary evidence that the concept mapping approach can be useful to help mental health nursing students visualise their learning progress and encourage the integration of theoretical knowledge with clinical knowledge. Combining concept mapping data with quantitative measures and qualitative reflective journal data appears to be a useful way of assessing and understanding the effectiveness of

Distributed Grid Experiences in CMS DC04

CERN Document Server

Fanfani, A; Grandi, C; Legrand, I; Suresh, S; Campana, S; Donno, F; Jank, W; Sinanis, N; Sciabà, A; García-Abia, P; Hernández, J; Ernst, M; Anzar, A; Fisk, I; Giacchetti, L; Graham, G; Heavey, A; Kaiser, J; Kuropatine, N; Perelmutov, T; Pordes, R; Ratnikova, N; Weigand, J; Wu, Y; Colling, D J; MacEvoy, B; Tallini, H; Wakefield, L; De Filippis, N; Donvito, G; Maggi, G; Bonacorsi, D; Dell'Agnello, L; Martelli, B; Biasotto, M; Fantinel, S; Corvo, M; Fanzago, F; Mazzucato, M; Tuura, L; Martin, T; Letts, J; Bockjoo, K; Prescott, C; Rodríguez, J; Zahn, A; Bradley, D

2005-01-01

In March-April 2004 the CMS experiment undertook a Data Challenge (DC04). During the previous 8 months CMS undertook a large simulated event production. The goal of the challenge was to run CMS reconstruction for sustained period at 25Hz in put rate, distribute the data to the CMS Tier-1 centers and analyze them at remote sites. Grid environments developed in Europe by the LHC Computing Grid (LCG) and in the US with Grid2003 were utilized to complete the aspects of the challenge. A description of the experiences, successes and lessons learned from both experiences with grid infrastructure is presented.

Successful Teaching, Learning, and Use of Digital Mapping Technology in Mazvihwa, Rural Zimbabwe

Science.gov (United States)

Eitzel Solera, M. V.; Madzoro, S.; Solera, J.; Mhike Hove, E.; Changarara, A.; Ndlovu, D.; Chirindira, A.; Ndlovu, A.; Gwatipedza, S.; Mhizha, M.; Ndlovu, M.

2016-12-01

Participatory mapping is now a staple of community-based work around the world. Particularly for indigenous and rural peoples, it can represent a new avenue for environmental justice and can be a tool for culturally appropriate management of local ecosystems. We present a successful example of teaching and learning digital mapping technology in rural Zimbabwe. Our digital mapping project is part of the long-term community-based participatory research of The Muonde Trust in Mazvihwa, Zimbabwe. By gathering and distributing local knowledge and also bringing in visitors to share knowledge, Muonde has been able to spread relevant information among rural farmers. The authors were all members of Muonde or were Muonde's visitors, and were mentors and learners of digital mapping technologies at different times. Key successful characteristics of participants included patience, compassion, openness, perseverance, respect, and humility. Important mentoring strategies included: 1) instruction in Shona and in English, 2) locally relevant examples, assignments, and analogies motivated by real needs, 3) using a variety of teaching methods for different learning modalities, 4) building on and modifying familiar teaching methods, and 5) paying attention to the social and relational aspects of teaching and learning. The Muonde mapping team has used their new skills for a wide variety of purposes, including: identifying, discussing, and acting on emerging needs; using digital mapping for land-use and agropastoral planning; and using mapping as a tool for recording and telling important historical and cultural stories. Digital mapping has built self-confidence as well as providing employable skills and giving Muonde more visibility to other local and national non-governmental organizations, utility companies, and educational institutions. Digital mapping, as taught in a bottom-up, collaborative way, has proven to be both accessible and of enormous practical use to rural Zimbabweans.

Neural network representation and learning of mappings and their derivatives

Science.gov (United States)

White, Halbert; Hornik, Kurt; Stinchcombe, Maxwell; Gallant, A. Ronald

1991-01-01

Discussed here are recent theorems proving that artificial neural networks are capable of approximating an arbitrary mapping and its derivatives as accurately as desired. This fact forms the basis for further results establishing the learnability of the desired approximations, using results from non-parametric statistics. These results have potential applications in robotics, chaotic dynamics, control, and sensitivity analysis. An example involving learning the transfer function and its derivatives for a chaotic map is discussed.

Efficient Pseudorecursive Evaluation Schemes for Non-adaptive Sparse Grids

KAUST Repository

Buse, Gerrit

2014-01-01

In this work we propose novel algorithms for storing and evaluating sparse grid functions, operating on regular (not spatially adaptive), yet potentially dimensionally adaptive grid types. Besides regular sparse grids our approach includes truncated grids, both with and without boundary grid points. Similar to the implicit data structures proposed in Feuersänger (Dünngitterverfahren für hochdimensionale elliptische partielle Differntialgleichungen. Diploma Thesis, Institut für Numerische Simulation, Universität Bonn, 2005) and Murarasu et al. (Proceedings of the 16th ACM Symposium on Principles and Practice of Parallel Programming. Cambridge University Press, New York, 2011, pp. 25–34) we also define a bijective mapping from the multi-dimensional space of grid points to a contiguous index, such that the grid data can be stored in a simple array without overhead. Our approach is especially well-suited to exploit all levels of current commodity hardware, including cache-levels and vector extensions. Furthermore, this kind of data structure is extremely attractive for today’s real-time applications, as it gives direct access to the hierarchical structure of the grids, while outperforming other common sparse grid structures (hash maps, etc.) which do not match with modern compute platforms that well. For dimensionality d ≤ 10 we achieve good speedups on a 12 core Intel Westmere-EP NUMA platform compared to the results presented in Murarasu et al. (Proceedings of the International Conference on Computational Science—ICCS 2012. Procedia Computer Science, 2012). As we show, this also holds for the results obtained on Nvidia Fermi GPUs, for which we observe speedups over our own CPU implementation of up to 4.5 when dealing with moderate dimensionality. In high-dimensional settings, in the order of tens to hundreds of dimensions, our sparse grid evaluation kernels on the CPU outperform any other known implementation.

Smart Grid Information Clearinghouse (SGIC)

Energy Technology Data Exchange (ETDEWEB)

Rahman, Saifur [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

2014-08-31

Since the Energy Independence and Security Act of 2007 was enacted, there has been a large number of websites that discusses smart grid and relevant information, including those from government, academia, industry, private sector and regulatory. These websites collect information independently. Therefore, smart grid information was quite scattered and dispersed. The objective of this work was to develop, populate, manage and maintain the public Smart Grid Information Clearinghouse (SGIC) web portal. The information in the SGIC website is comprehensive that includes smart grid information, research & development, demonstration projects, technical standards, costs & benefit analyses, business cases, legislation, policy & regulation, and other information on lesson learned and best practices. The content in the SGIC website is logically grouped to allow easily browse, search and sort. In addition to providing the browse and search feature, the SGIC web portal also allow users to share their smart grid information with others though our online content submission platform. The Clearinghouse web portal, therefore, serves as the first stop shop for smart grid information that collects smart grid information in a non-bias, non-promotional manner and can provide a missing link from information sources to end users and better serve users’ needs. The web portal is available at www.sgiclearinghouse.org. This report summarizes the work performed during the course of the project (September 2009 – August 2014). Section 2.0 lists SGIC Advisory Committee and User Group members. Section 3.0 discusses SGIC information architecture and web-based database application functionalities. Section 4.0 summarizes SGIC features and functionalities, including its search, browse and sort capabilities, web portal social networking, online content submission platform and security measures implemented. Section 5.0 discusses SGIC web portal contents, including smart grid 101, smart grid projects

How reduction of theta rhythm by medial septum inactivation may covary with disruption of entorhinal grid cell responses due to reduced cholinergic transmission

Directory of Open Access Journals (Sweden)

Praveen K. Pilly

2013-10-01

Full Text Available Oscillations in the coordinated firing of brain neurons have been proposed to play important roles in perception, cognition, attention, learning, navigation, and sensory-motor control. The network theta rhythm has been associated with properties of spatial navigation, as has the firing of entorhinal grid cells and hippocampal place cells. Two recent studies reduced the theta rhythm by inactivating the medial septum (MS and demonstrated a correlated reduction in the characteristic hexagonal spatial firing patterns of grid cells. These results, along with properties of intrinsic membrane potential oscillations (MPOs in slice preparations of entorhinal cells, have been interpreted to support oscillatory interference models of grid cell firing. The current article shows that an alternative self-organizing map model of grid cells can explain these data about intrinsic and network oscillations without invoking oscillatory interference. In particular, the adverse effects of MS inactivation on grid cells can be understood in terms of how the concomitant reduction in cholinergic inputs may increase the conductances of leak potassium (K+ and slow and medium after-hyperpolarization (sAHP and mAHP channels. This alternative model can also explain data that are problematic for oscillatory interference models, including how knockout of the HCN1 gene in mice, which flattens the dorsoventral gradient in MPO frequency and resonance frequency, does not affect the development of the grid cell dorsoventral gradient of spatial scales, and how hexagonal grid firing fields in bats can occur even in the absence of theta band modulation. These results demonstrate how models of grid cell self-organization can provide new insights into the relationship between brain learning, oscillatory dynamics, and navigational behaviors.

Wind Power Grid Connected Capacity Prediction Using LSSVM Optimized by the Bat Algorithm

Directory of Open Access Journals (Sweden)

Qunli Wu

2015-12-01

Full Text Available Given the stochastic nature of wind, wind power grid-connected capacity prediction plays an essential role in coping with the challenge of balancing supply and demand. Accurate forecasting methods make enormous contribution to mapping wind power strategy, power dispatching and sustainable development of wind power industry. This study proposes a bat algorithm (BA–least squares support vector machine (LSSVM hybrid model to improve prediction performance. In order to select input of LSSVM effectively, Stationarity, Cointegration and Granger causality tests are conducted to examine the influence of installed capacity with different lags, and partial autocorrelation analysis is employed to investigate the inner relationship of grid-connected capacity. The parameters in LSSVM are optimized by BA to validate the learning ability and generalization of LSSVM. Multiple model sufficiency evaluation methods are utilized. The research results reveal that the accuracy improvement of the present approach can reach about 20% compared to other single or hybrid models.

Mapping IMS Learning Design and Moodle. A first understanding

NARCIS (Netherlands)

Burgos, Daniel; Tattersall, Colin; Dougiamas, Martin; Vogten, Hubert; Koper, Rob

2006-01-01

Please, cite this publication as follows: Burgos, D., Tattersall, C., Dougiamas, M., Vogten, H., & Koper, E. J. R. (2006). Mapping IMS Learning Design and Moodle. A first understanding. Proceedings of Simposo Internacional de Informática Educativa (SIIE06), León, Spain: IEEE Technical Committee on

FastSLAM Using Compressed Occupancy Grids

Directory of Open Access Journals (Sweden)

Christopher Cain

2016-01-01

Full Text Available Robotic vehicles working in unknown environments require the ability to determine their location while learning about obstacles located around them. In this paper a method of solving the SLAM problem that makes use of compressed occupancy grids is presented. The presented approach is an extension of the FastSLAM algorithm which stores a compressed form of the occupancy grid to reduce the amount of memory required to store the set of occupancy grids maintained by the particle filter. The performance of the algorithm is presented using experimental results obtained using a small inexpensive ground vehicle equipped with LiDAR, compass, and downward facing camera that provides the vehicle with visual odometry measurements. The presented results demonstrate that although with our approach the occupancy grid maintained by each particle uses only 40% of the data needed to store the uncompressed occupancy grid, we can still achieve almost identical results to the approach where each particle filter stores the full occupancy grid.

Grid occupancy estimation for environment perception based on belief functions and PCR6

Science.gov (United States)

Moras, Julien; Dezert, Jean; Pannetier, Benjamin

2015-05-01

In this contribution, we propose to improve the grid map occupancy estimation method developed so far based on belief function modeling and the classical Dempster's rule of combination. Grid map offers a useful representation of the perceived world for mobile robotics navigation. It will play a major role for the security (obstacle avoidance) of next generations of terrestrial vehicles, as well as for future autonomous navigation systems. In a grid map, the occupancy of each cell representing a small piece of the surrounding area of the robot must be estimated at first from sensors measurements (typically LIDAR, or camera), and then it must also be classified into different classes in order to get a complete and precise perception of the dynamic environment where the robot moves. So far, the estimation and the grid map updating have been done using fusion techniques based on the probabilistic framework, or on the classical belief function framework thanks to an inverse model of the sensors. Mainly because the latter offers an interesting management of uncertainties when the quality of available information is low, and when the sources of information appear as conflicting. To improve the performances of the grid map estimation, we propose in this paper to replace Dempster's rule of combination by the PCR6 rule (Proportional Conflict Redistribution rule #6) proposed in DSmT (Dezert-Smarandache) Theory. As an illustrating scenario, we consider a platform moving in dynamic area and we compare our new realistic simulation results (based on a LIDAR sensor) with those obtained by the probabilistic and the classical belief-based approaches.

Reporting emissions on EMEP grid. Methods and principles; Rapportering af luftemissioner paa grid. Metoder og principper

Energy Technology Data Exchange (ETDEWEB)

Tranekjaer Jensen, M.; Nielsen, Ole-Kenneth; Hjorth Mikkelsen, M.; Winther, M.; Gyldenkaerne, S.; Viuf OErby, P.; Boll Illerup, J.

2008-03-15

This report explains methods for reporting emissions on EMEP grid with a resolution of 50km x 50km for the reporting years 1990, 1995, 2000 an 2005. The applied and geographical distributed emission data on grid represents the latest delivery (per March 2007) to UNECE LRTAP (United Nations Economic Commission for Europe Long-range Transboundary Air Pollution). Thus data represents the latest recalculation of historical values. The reporting of emissions on EMEP grid with a resolution of 50km x 50km is a part of the Danish submission under the above mentioned convention (UNECE LRTAP). Emission inventories on grid are reported every fifth year and involves all sectors under UNECE LRTAP. The reporting of emissions on grid includes 14 mandatory emission components, which are: SO{sub 2}, NOx NH{sub 3}, NMVOC, CO, TSP, PM{sub 10}, PM{sub 2.5}, Pb, Cd, Hg, Dioxin, PAH and HCB. It is furthermore possible to make additional reporting for a range of components. The report summarizes the most crucial principles and considerations according to work with distributing air emissions on grid within predefined categories for gridding defined by the United Nations (UN 2003). For each of the reported categories, the report gives a detailed explanation of the specific level for distributing emissions spatially. For most reporting categories the process of distributing emissions has been carried out at the highly detailed SNAP level, whereas for others it has been a necessity to make aggregates of several SNAP categories for spatial distribution. The report present final maps for selected air pollutants (SOx, NOx and NH{sub 3}) and discuss shortly possible reasons for variations within time and space. Based on current experience, the report finally gives some recommendations for improving future reporting of gridded emission data. The recommendations pin point, that the EMEP program should provide harmonized and well-documented basic spatial data sets for gridding, to encourage each

Security on the US Fusion Grid

Energy Technology Data Exchange (ETDEWEB)

Burruss, Justin R.; Fredian, Tom W.; Thompson, Mary R.

2005-06-01

The National Fusion Collaboratory project is developing and deploying new distributed computing and remote collaboration technologies with the goal of advancing magnetic fusion energy research. This work has led to the development of the US Fusion Grid (FusionGrid), a computational grid composed of collaborative, compute, and data resources from the three large US fusion research facilities and with users both in the US and in Europe. Critical to the development of FusionGrid was the creation and deployment of technologies to ensure security in a heterogeneous environment. These solutions to the problems of authentication, authorization, data transfer, and secure data storage, as well as the lessons learned during the development of these solutions, may be applied outside of FusionGrid and scale to future computing infrastructures such as those for next-generation devices like ITER.

Security on the US Fusion Grid

International Nuclear Information System (INIS)

Burruss, Justin R.; Fredian, Tom W.; Thompson, Mary R.

2005-01-01

The National Fusion Collaboratory project is developing and deploying new distributed computing and remote collaboration technologies with the goal of advancing magnetic fusion energy research. This work has led to the development of the US Fusion Grid (FusionGrid), a computational grid composed of collaborative, compute, and data resources from the three large US fusion research facilities and with users both in the US and in Europe. Critical to the development of FusionGrid was the creation and deployment of technologies to ensure security in a heterogeneous environment. These solutions to the problems of authentication, authorization, data transfer, and secure data storage, as well as the lessons learned during the development of these solutions, may be applied outside of FusionGrid and scale to future computing infrastructures such as those for next-generation devices like ITER

Security on the US fusion grid

International Nuclear Information System (INIS)

Burruss, J.R.; Fredian, T.W.; Thompson, M.R.

2006-01-01

The National Fusion Collaboratory project is developing and deploying new distributed computing and remote collaboration technologies with the goal of advancing magnetic fusion energy research. This has led to the development of the U.S. fusion grid (FusionGrid), a computational grid composed of collaborative, compute, and data resources from the three large U.S. fusion research facilities and with users both in the U.S. and in Europe. Critical to the development of FusionGrid was the creation and deployment of technologies to ensure security in a heterogeneous environment. These solutions to the problems of authentication, authorization, data transfer, and secure data storage, as well as the lessons learned during the development of these solutions, may be applied outside of FusionGrid and scale to future computing infrastructures such as those for next-generation devices like ITER

Mapping the HISS Dipole

International Nuclear Information System (INIS)

McParland, C.; Bieser, F.

1984-01-01

The principal component of the Bevalac HISS facility is a large super-conducting 3 Tesla dipole. The facility's need for a large magnetic volume spectrometer resulted in a large gap geometry - a 2 meter pole tip diameter and a 1 meter pole gap. Obviously, the field required detailed mapping for effective use as a spectrometer. The mapping device was designed with several major features in mind. The device would measure field values on a grid which described a closed rectangular solid. The grid would be a regular with the exact measurement intervals adjustable by software. The device would function unattended over the long period of time required to complete a field map. During this time, the progress of the map could be monitored by anyone with access to the HISS VAX computer. Details of the mechanical, electrical, and control design follow

Progress of Grid technology in Argentina: Lessons learned from EELA

International Nuclear Information System (INIS)

Dova, M. T.; Grunfeld, C.; Monticelli, F.; Tripiana, M.; Veiga, A.; Ambrosi, V.; Barbieri, A.; Diaz, J.; Luengo, M.; Macia, M.; Molinari, L.; Veonosa, P.; Zabaljauregui, M.

2007-01-01

The EELA project aimed to create a collaboration network between Europe and Latin American for training in Grid technologies and the deployment of a pilot Grid infrastructure for e-science applications. Grid computing has emerged as an important new field, and its development in Argentina is particularly important for a number of reasons, such as that Argentina has recently joined the ATLAS collaboration at CERN and the increasing interest in future biomedical applications. The potential of GRID technology is well known, however, its adoption is not a trivial task as it requires significant investment in several areas. In this paper, the achievements and progress in Argentina through close collaboration with EELA are presented. Among these are the deployment of a Grid Certification Authority infrastructure that is a crucial component in the activities of the e-Science community in the country; the deployment, integration and validation of a small local EELA node; installation and running of an analysis ATLAS application on the EELA infrastructure. The experience gained in participating in EELA dissemination events also allowed us to actively promote the GRID and training for its use different target audiences in Argentina and in LA. (Author)

Developing survey grids to substantiate freedom from exotic pests

Science.gov (United States)

John W. Coulston; Frank H. Koch; William D. Smith

2009-01-01

Systematic, hierarchical intensification of the Environmental Monitoring and Assessment Program hexagon for North America yields a simple procedure for developing national-scale survey grids. In this article, we describe the steps to create a national-scale survey grid using a risk map as the starting point. We illustrate the steps using an exotic pest example in which...

Coverage map of gridded multibeam and lidar bathymetry of the US Territory of Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded lidar bathymetry. Gridded (5 m cell size) multibeam bathymetry were collected aboard NOAA Ship Hiialaka'i and...

Matching soil grid unit resolutions with polygon unit scales for DNDC modelling of regional SOC pool

Science.gov (United States)

Zhang, H. D.; Yu, D. S.; Ni, Y. L.; Zhang, L. M.; Shi, X. Z.

2015-03-01

Matching soil grid unit resolution with polygon unit map scale is important to minimize uncertainty of regional soil organic carbon (SOC) pool simulation as their strong influences on the uncertainty. A series of soil grid units at varying cell sizes were derived from soil polygon units at the six map scales of 1:50 000 (C5), 1:200 000 (D2), 1:500 000 (P5), 1:1 000 000 (N1), 1:4 000 000 (N4) and 1:14 000 000 (N14), respectively, in the Tai lake region of China. Both format soil units were used for regional SOC pool simulation with DeNitrification-DeComposition (DNDC) process-based model, which runs span the time period 1982 to 2000 at the six map scales, respectively. Four indices, soil type number (STN) and area (AREA), average SOC density (ASOCD) and total SOC stocks (SOCS) of surface paddy soils simulated with the DNDC, were attributed from all these soil polygon and grid units, respectively. Subjecting to the four index values (IV) from the parent polygon units, the variation of an index value (VIV, %) from the grid units was used to assess its dataset accuracy and redundancy, which reflects uncertainty in the simulation of SOC. Optimal soil grid unit resolutions were generated and suggested for the DNDC simulation of regional SOC pool, matching with soil polygon units map scales, respectively. With the optimal raster resolution the soil grid units dataset can hold the same accuracy as its parent polygon units dataset without any redundancy, when VIV indices was assumed as criteria to the assessment. An quadratic curve regression model y = -8.0 × 10-6x2 + 0.228x + 0.211 (R2 = 0.9994, p < 0.05) was revealed, which describes the relationship between optimal soil grid unit resolution (y, km) and soil polygon unit map scale (1:x). The knowledge may serve for grid partitioning of regions focused on the investigation and simulation of SOC pool dynamics at certain map scale.

iMindMap as an Innovative Tool in Teaching and Learning Accounting: An Exploratory Study

Science.gov (United States)

Wan Jusoh, Wan Noor Hazlina; Ahmad, Suraya

2016-01-01

Purpose: The purpose of this study is to explore the use of iMindMap software as an interactive tool in the teaching and learning method and also to be able to consider iMindMap as an alternative instrument in achieving the ultimate learning outcome. Design/Methodology/Approach: Out of 268 students of the management accounting at the University of…

Effects of a Computer-Assisted Concept Mapping Learning Strategy on EFL College Students' English Reading Comprehension

Science.gov (United States)

Liu, Pei-Lin; Chen, Chiu-Jung; Chang, Yu-Ju

2010-01-01

The purpose of this research was to investigate the effects of a computer-assisted concept mapping learning strategy on EFL college learners' English reading comprehension. The research questions were: (1) what was the influence of the computer-assisted concept mapping learning strategy on different learners' English reading comprehension? (2) did…

[Exploratory study of clinical reasoning in nursing students with concept mapping].

Science.gov (United States)

Paucard-Dupont, Sylvie; Marchand, Claire

2014-06-01

The training reference leading to the state nursing diploma places the learning of clinical reasoning at the center of the training. We have been wondering about the possibilities of making visible the student nurse's mental processes when they provide nursing care in order to identify their strategies and reasoning difficulties. It turns out that concept mapping is a research tool capable of showing these two aspects. The aim of this study is to verify a concept mapping made during an interview and built from the speech of a nursing student when analyzing a simulated clinical situation, is able to make visible its strategies clinical reasoning and reasoning difficulties. In a second phase of it, is to explore how the concept map once elaborated allows students to identify their own intellectual reasoning. 12 nursing second year students have participated in the study. Concept maps were constructed by the trainer/researcher as the students analyzed aloud a simulated clinical situation written. Concept maps were analyzed from a reference grid. Interviews were conducted following the elaboration of concept maps and student's comments were analyzed. Students reasoning strategies were either mixed inductive dominant (5/12) or hypothetical-deductive dominant (5/12). Reasoning difficulties identified are related to the lack of identification of important information, the lack of analysis of data, lack of connection or the existence of faulty links. Analysis of the comments highlights that concept mapping contributed to the development of metacognitive skills. The concept mapping has shown benefits in contributing to a diagnostic assessment of clinical reasoning learning. It is an additional resource tool to facilitate the development of metacognitive skills for students. This tool can be useful to implement support learning strategies in clinical reasoning.

Data Compression of Hydrocarbon Reservoir Simulation Grids

KAUST Repository

Chavez, Gustavo Ivan; Harbi, Badr M.

2015-01-01

A dense volumetric grid coming from an oil/gas reservoir simulation output is translated into a compact representation that supports desired features such as interactive visualization, geometric continuity, color mapping and quad representation. A

A Theory of Causal Learning in Children: Causal Maps and Bayes Nets

Science.gov (United States)

Gopnik, Alison; Glymour, Clark; Sobel, David M.; Schulz, Laura E.; Kushnir, Tamar; Danks, David

2004-01-01

The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously…

Analogy Mapping Development for Learning Programming

Science.gov (United States)

Sukamto, R. A.; Prabawa, H. W.; Kurniawati, S.

2017-02-01

Programming skill is an important skill for computer science students, whereas nowadays, there many computer science students are lack of skills and information technology knowledges in Indonesia. This is contrary with the implementation of the ASEAN Economic Community (AEC) since the end of 2015 which is the qualified worker needed. This study provided an effort for nailing programming skills by mapping program code to visual analogies as learning media. The developed media was based on state machine and compiler principle and was implemented in C programming language. The state of every basic condition in programming were successful determined as analogy visualization.

Visualizing complex processes using a cognitive-mapping tool to support the learning of clinical reasoning.

Science.gov (United States)

Wu, Bian; Wang, Minhong; Grotzer, Tina A; Liu, Jun; Johnson, Janice M

2016-08-22

Practical experience with clinical cases has played an important role in supporting the learning of clinical reasoning. However, learning through practical experience involves complex processes difficult to be captured by students. This study aimed to examine the effects of a computer-based cognitive-mapping approach that helps students to externalize the reasoning process and the knowledge underlying the reasoning process when they work with clinical cases. A comparison between the cognitive-mapping approach and the verbal-text approach was made by analyzing their effects on learning outcomes. Fifty-two third-year or higher students from two medical schools participated in the study. Students in the experimental group used the computer-base cognitive-mapping approach, while the control group used the verbal-text approach, to make sense of their thinking and actions when they worked with four simulated cases over 4 weeks. For each case, students in both groups reported their reasoning process (involving data capture, hypotheses formulation, and reasoning with justifications) and the underlying knowledge (involving identified concepts and the relationships between the concepts) using the given approach. The learning products (cognitive maps or verbal text) revealed that students in the cognitive-mapping group outperformed those in the verbal-text group in the reasoning process, but not in making sense of the knowledge underlying the reasoning process. No significant differences were found in a knowledge posttest between the two groups. The computer-based cognitive-mapping approach has shown a promising advantage over the verbal-text approach in improving students' reasoning performance. Further studies are needed to examine the effects of the cognitive-mapping approach in improving the construction of subject-matter knowledge on the basis of practical experience.

Development and Operation of the D-Grid Infrastructure

Science.gov (United States)

Fieseler, Thomas; Gűrich, Wolfgang

D-Grid is the German national grid initiative, granted by the German Federal Ministry of Education and Research. In this paper we present the Core D-Grid which acts as a condensation nucleus to build a production grid and the latest developments of the infrastructure. The main difference compared to other international grid initiatives is the support of three middleware systems, namely LCG/gLite, Globus, and UNICORE for compute resources. Storage resources are connected via SRM/dCache and OGSA-DAI. In contrast to homogeneous communities, the partners in Core D-Grid have different missions and backgrounds (computing centres, universities, research centres), providing heterogeneous hardware from single processors to high performance supercomputing systems with different operating systems. We present methods to integrate these resources and services for the DGrid infrastructure like a point of information, centralized user and virtual organization management, resource registration, software provision, and policies for the implementation (firewalls, certificates, user mapping).

Fast Mapping Across Time: Memory Processes Support Children's Retention of Learned Words

Directory of Open Access Journals (Sweden)

Haley eVlach

2012-02-01

Full Text Available Children's remarkable ability to map linguistic labels to objects in the world is referred to as fast mapping. The current study examined children's (N = 216 and adults’ (N = 54 retention of fast-mapped words over time (immediately, after a 1 week delay, and after a 1 month delay. The fast mapping literature often characterizes children's retention of words as consistently high across timescales. However, the current study demonstrates that learners forget word mappings at a rapid rate. Moreover, these patterns of forgetting parallel forgetting functions of domain general memory processes. Memory processes are critical to children's word learning and the role of one such process, forgetting, is discussed in detail—forgetting supports both word mapping and the generalization of words and categories.

Fast Mapping Across Time: Memory Processes Support Children's Retention of Learned Words.

Science.gov (United States)

Vlach, Haley A; Sandhofer, Catherine M

2012-01-01

Children's remarkable ability to map linguistic labels to referents in the world is commonly called fast mapping. The current study examined children's (N = 216) and adults' (N = 54) retention of fast-mapped words over time (immediately, after a 1-week delay, and after a 1-month delay). The fast mapping literature often characterizes children's retention of words as consistently high across timescales. However, the current study demonstrates that learners forget word mappings at a rapid rate. Moreover, these patterns of forgetting parallel forgetting functions of domain-general memory processes. Memory processes are critical to children's word learning and the role of one such process, forgetting, is discussed in detail - forgetting supports extended mapping by promoting the memory and generalization of words and categories.

Mapping of Supply Chain Learning: A Framework for SMEs

Science.gov (United States)

Thakkar, Jitesh; Kanda, Arun; Deshmukh, S. G.

2011-01-01

Purpose: The aim of this paper is to propose a mapping framework for evaluating supply chain learning potential for the context of small- to medium-sized enterprises (SMEs). Design/methodology/approach: The extracts of recently completed case based research for ten manufacturing SME units and facts reported in the previous research are utilized…

E-Learning Content Design Standards Based on Interactive Digital Concepts Maps in the Light of Meaningful and Constructivist Learning Theory

Science.gov (United States)

Afify, Mohammed Kamal

2018-01-01

The present study aims to identify standards of interactive digital concepts maps design and their measurement indicators as a tool to develop, organize and administer e-learning content in the light of Meaningful Learning Theory and Constructivist Learning Theory. To achieve the objective of the research, the author prepared a list of E-learning…

Error sensitivity to refinement: a criterion for optimal grid adaptation

Science.gov (United States)

Luchini, Paolo; Giannetti, Flavio; Citro, Vincenzo

2017-12-01

Most indicators used for automatic grid refinement are suboptimal, in the sense that they do not really minimize the global solution error. This paper concerns with a new indicator, related to the sensitivity map of global stability problems, suitable for an optimal grid refinement that minimizes the global solution error. The new criterion is derived from the properties of the adjoint operator and provides a map of the sensitivity of the global error (or its estimate) to a local mesh refinement. Examples are presented for both a scalar partial differential equation and for the system of Navier-Stokes equations. In the last case, we also present a grid-adaptation algorithm based on the new estimator and on the FreeFem++ software that improves the accuracy of the solution of almost two order of magnitude by redistributing the nodes of the initial computational mesh.

THE EFFECT OF CONCEPT MAPPING ON CONCEPT LEARNING IN SCIENCE

OpenAIRE

岡, 直樹; 今永, 久美子

2012-01-01

An experiment was conducted to investigate the effects of concept map completion tasks on concept learning in the primary schoolchildren. The participants were to insert some of the suitable concepts (concept group) or link labeles (link label group) or both of them (concept/link label group) into the blanks to make up the map wholly. It was revealed that the results of the concept group and the concept/link label group were better than the link label group. These results were discussed in te...

Mapping Nearby Terrain in 3D by Use of a Grid of Laser Spots

Science.gov (United States)

Padgett, Curtis; Liebe, Carl; Chang, Johnny; Brown, Kenneth

2007-01-01

A proposed optoelectronic system, to be mounted aboard an exploratory robotic vehicle, would be used to generate a three-dimensional (3D) map of nearby terrain and obstacles for purposes of navigating the vehicle across the terrain and avoiding the obstacles. The difference between this system and the other systems would lie in the details of implementation. In this system, the illumination would be provided by a laser. The beam from the laser would pass through a two-dimensional diffraction grating, which would divide the beam into multiple beams propagating in different, fixed, known directions. These beams would form a grid of bright spots on the nearby terrain and obstacles. The centroid of each bright spot in the image would be computed. For each such spot, the combination of (1) the centroid, (2) the known direction of the light beam that produced the spot, and (3) the known baseline would constitute sufficient information for calculating the 3D position of the spot.

A theory of causal learning in children: Causal maps and Bayes nets

OpenAIRE

Gopnik, A; Glymour, C; Sobel, D M; Schulz, L E; Kushnir, T; Danks, D

2004-01-01

The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computatio...

An effective self-assessment based on concept map extraction from test-sheet for personalized learning

Science.gov (United States)

Liew, Keng-Hou; Lin, Yu-Shih; Chang, Yi-Chun; Chu, Chih-Ping

2013-12-01

Examination is a traditional way to assess learners' learning status, progress and performance after a learning activity. Except the test grade, a test sheet hides some implicit information such as test concepts, their relationships, importance, and prerequisite. The implicit information can be extracted and constructed a concept map for considering (1) the test concepts covered in the same question means these test concepts have strong relationships, and (2) questions in the same test sheet means the test concepts are relative. Concept map has been successfully employed in many researches to help instructors and learners organize relationships among concepts. However, concept map construction depends on experts who need to take effort and time for the organization of the domain knowledge. In addition, the previous researches regarding to automatic concept map construction are limited to consider all learners of a class, which have not considered personalized learning. To cope with this problem, this paper proposes a new approach to automatically extract and construct concept map based on implicit information in a test sheet. Furthermore, the proposed approach also can help learner for self-assessment and self-diagnosis. Finally, an example is given to depict the effectiveness of proposed approach.

Joining the Pieces: Using Concept Maps for Integrated Learning and Assessment in an Introductory Management Course

Science.gov (United States)

Connolly, Heather; Spiller, Dorothy

2016-01-01

This paper reports on and evaluates the use of concept mapping as a learning tool in a large first year Management course. The goal was to help students make personal sense of course learning and to build their understanding of links and relationships between key course ideas. Concept mapping was used for three summative assessment pieces,…

Unpacking the cognitive map: the parallel map theory of hippocampal function.

Science.gov (United States)

Jacobs, Lucia F; Schenk, Françoise

2003-04-01

In the parallel map theory, the hippocampus encodes space with 2 mapping systems. The bearing map is constructed primarily in the dentate gyrus from directional cues such as stimulus gradients. The sketch map is constructed within the hippocampus proper from positional cues. The integrated map emerges when data from the bearing and sketch maps are combined. Because the component maps work in parallel, the impairment of one can reveal residual learning by the other. Such parallel function may explain paradoxes of spatial learning, such as learning after partial hippocampal lesions, taxonomic and sex differences in spatial learning, and the function of hippocampal neurogenesis. By integrating evidence from physiology to phylogeny, the parallel map theory offers a unified explanation for hippocampal function.

A pilot study on conducting mobile learning activities for clinical nursing courses based on the repertory grid approach.

Science.gov (United States)

Wu, Po-Han; Hwang, Gwo-Jen; Tsai, Chin-Chung; Chen, Ya-Chun; Huang, Yueh-Min

2011-11-01

In clinical nursing courses, students are trained to identify the status of the target patients. The mastery of such ability and skills is very important since patients frequently need to be cared for immediately. In this pilot study, a repertory grid-oriented clinical mobile learning system is developed for a nursing training program. With the assistance of the mobile learning system, the nursing school students are able to learn in an authentic learning scenario, in which they can physically face the target patients, with the personal guidance and supplementary materials from the learning system to support them. To show the effectiveness of this innovative approach, an experiment has been conducted on the "respiratory system" unit of a nursing course. The experimental results show that the innovative approach is helpful to students in improving their learning achievements. Moreover, from the questionnaire surveys, it was found that most students showed favorable attitudes toward the usage of the mobile learning system and their participation in the training program. Copyright © 2010 Elsevier Ltd. All rights reserved.

Wavefront cellular learning automata.

Science.gov (United States)

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

Wavefront cellular learning automata

Science.gov (United States)

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

Cognitive Radio for Smart Grid with Security Considerations

Directory of Open Access Journals (Sweden)

Khaled Shuaib

2016-04-01

Full Text Available In this paper, we investigate how Cognitive Radio as a means of communication can be utilized to serve a smart grid deployment end to end, from a home area network to power generation. We show how Cognitive Radio can be mapped to integrate the possible different communication networks within a smart grid large scale deployment. In addition, various applications in smart grid are defined and discussed showing how Cognitive Radio can be used to fulfill their communication requirements. Moreover, information security issues pertained to the use of Cognitive Radio in a smart grid environment at different levels and layers are discussed and mitigation techniques are suggested. Finally, the well-known Role-Based Access Control (RBAC is integrated with the Cognitive Radio part of a smart grid communication network to protect against unauthorized access to customer’s data and to the network at large.

A comparative analysis of three metaheuristic methods applied to fuzzy cognitive maps learning

Directory of Open Access Journals (Sweden)

Bruno A. Angélico

2013-12-01

Full Text Available This work analyses the performance of three different population-based metaheuristic approaches applied to Fuzzy cognitive maps (FCM learning in qualitative control of processes. Fuzzy cognitive maps permit to include the previous specialist knowledge in the control rule. Particularly, Particle Swarm Optimization (PSO, Genetic Algorithm (GA and an Ant Colony Optimization (ACO are considered for obtaining appropriate weight matrices for learning the FCM. A statistical convergence analysis within 10000 simulations of each algorithm is presented. In order to validate the proposed approach, two industrial control process problems previously described in the literature are considered in this work.

Mental Maps: A new instrument for teaching-learning-evaluation of engineering students

Science.gov (United States)

Oleschko, K.

2009-04-01

The use of interactive mind maps for teaching-learning-evaluation of postgraduate students is still not very common in Geosciences. Notwithstanding, these maps allow students to organize the huge volumes of information and data they are faced with (www.spinscape.com) for efficient research project elaboration and for understanding of basic anzatz and conjectures (Singer, 2009). The elaboration of mind maps is introduced as a principle teaching-learning-evaluation instrument (Cruza and Fierros, 2006) in my Research Methodology Seminar. Each student should to construct three types of multiscale mind maps before to write the formal proposal (Curiel and Radvansky, 2004; Zimmer, 2004). The main goal is to show how useful is to manage the physical, mathematical and linguistic information on the same structured way (Montibeller and Belton, 2009; Chu et al., 2009). The mental representation of the spatially and time organized physical world (physical map) is combined with the design of hierarchical tree of mathematical models used to describe it in mathematical terms (the map composed only by mathematical symbols), visualizing this tree branches by corresponding images inside the third map consisting on images. This three-faced representation of each research project helps the participant to perceive the complex nature of studied systems and visualize their features of universality and scale invariance. The maṕs elaboration is considered to be finished when any student of other specialties become able to present it in acceptable scientific way. Some examples of recent mental maps elaborated by the master degree students of Queretaro University, Mexico will be presented and discussed. Based on my experience I recommend this education technique in order to pass from sustainable engineer teaching to educate the engineers of Sustainability. References 1. Chu, H.-Ch., Chen, M.-Y., Chen, Y.-M., 2009. A semantic-based approach to content abstraction and annotation for content

Biomass energy inventory and mapping system

Energy Technology Data Exchange (ETDEWEB)

Kasile, J.D. [Ohio State Univ., Columbus, OH (United States)

1993-12-31

A four-stage biomass energy inventory and mapping system was conducted for the entire State of Ohio. The product is a set of maps and an inventory of the State of Ohio. The set of amps and an inventory of the State`s energy biomass resource are to a one kilometer grid square basis on the Universal Transverse Mercator (UTM) system. Each square kilometer is identified and mapped showing total British Thermal Unit (BTU) energy availability. Land cover percentages and BTU values are provided for each of nine biomass strata types for each one kilometer grid square. LANDSAT satellite data was used as the primary stratifier. The second stage sampling was the photointerpretation of randomly selected one kilometer grid squares that exactly corresponded to the LANDSAT one kilometer grid square classification orientation. Field sampling comprised the third stage of the energy biomass inventory system and was combined with the fourth stage sample of laboratory biomass energy analysis using a Bomb calorimeter and was then used to assign BTU values to the photointerpretation and to adjust the LANDSAT classification. The sampling error for the whole system was 3.91%.

A Road Map for Learning Progressions Research in Geography

Science.gov (United States)

Huynh, Niem Tu; Solem, Michael; Bednarz, Sarah Witham

2015-01-01

This article provides an overview of learning progressions (LP) and assesses the potential of this line of research to improve geography education. It presents the merits and limitations of three of the most common approaches used to conduct LP research and draws on one approach to propose a first draft of a LP on map reading and interpretation.…

Data security on the national fusion grid

Energy Technology Data Exchange (ETDEWEB)

Burruss, Justine R.; Fredian, Tom W.; Thompson, Mary R.

2005-06-01

The National Fusion Collaboratory project is developing and deploying new distributed computing and remote collaboration technologies with the goal of advancing magnetic fusion energy research. This work has led to the development of the US Fusion Grid (FusionGrid), a computational grid composed of collaborative, compute, and data resources from the three large US fusion research facilities and with users both in the US and in Europe. Critical to the development of FusionGrid was the creation and deployment of technologies to ensure security in a heterogeneous environment. These solutions to the problems of authentication, authorization, data transfer, and secure data storage, as well as the lessons learned during the development of these solutions, may be applied outside of FusionGrid and scale to future computing infrastructures such as those for next-generation devices like ITER.

Data security on the national fusion grid

International Nuclear Information System (INIS)

Burruss, Justine R.; Fredian, Tom W.; Thompson, Mary R.

2005-01-01

The National Fusion Collaboratory project is developing and deploying new distributed computing and remote collaboration technologies with the goal of advancing magnetic fusion energy research. This work has led to the development of the US Fusion Grid (FusionGrid), a computational grid composed of collaborative, compute, and data resources from the three large US fusion research facilities and with users both in the US and in Europe. Critical to the development of FusionGrid was the creation and deployment of technologies to ensure security in a heterogeneous environment. These solutions to the problems of authentication, authorization, data transfer, and secure data storage, as well as the lessons learned during the development of these solutions, may be applied outside of FusionGrid and scale to future computing infrastructures such as those for next-generation devices like ITER

Concept Maps as Instructional Tools for Improving Learning of Phase Transitions in Object-Oriented Analysis and Design

Science.gov (United States)

Shin, Shin-Shing

2016-01-01

Students attending object-oriented analysis and design (OOAD) courses typically encounter difficulties transitioning from requirements analysis to logical design and then to physical design. Concept maps have been widely used in studies of user learning. The study reported here, based on the relationship of concept maps to learning theory and…

Developing a grid infrastructure in Cuba

Energy Technology Data Exchange (ETDEWEB)

Lopez Aldama, D.; Dominguez, M.; Ricardo, H.; Gonzalez, A.; Nolasco, E.; Fernandez, E.; Fernandez, M.; Sanchez, M.; Suarez, F.; Nodarse, F.; Moreno, N.; Aguilera, L.

2007-07-01

A grid infrastructure was deployed at Centro de Gestion de la Informacion y Desarrollo de la Energia (CUBAENERGIA) in the frame of EELA project and of a national initiative for developing a Cuban Network for Science. A stand-alone model was adopted to overcome connectivity limitations. The e-infrastructure is based on gLite-3.0 middleware and is fully compatible with EELA-infrastructure. Afterwards, the work was focused on grid applications. The application GATE was deployed from the early beginning for biomedical users. Further, two applications were deployed on the local grid infrastructure: MOODLE for e-learning and AERMOD for assessment of local dispersion of atmospheric pollutants. Additionally, our local grid infrastructure was made interoperable with a Java based distributed system for bioinformatics calculations. This experience could be considered as a suitable approach for national networks with weak Internet connections. (Author)

Gridded Data in the Arctic; Benefits and Perils of Publicly Available Grids

Science.gov (United States)

Coakley, B.; Forsberg, R.; Gabbert, R.; Beale, J.; Kenyon, S. C.

2015-12-01

Our understanding of the Arctic Ocean has been hugely advanced by release of gridded bathymetry and potential field anomaly grids. The Arctic Gravity Project grid achieves excellent, near-isotropic coverage of the earth north of 64˚N by combining land, satellite, airborne, submarine, surface ship and ice set-out measurements of gravity anomalies. Since the release of the V 2.0 grid in 2008, there has been extensive icebreaker activity across the Amerasia Basin due to mapping of the Arctic coastal nation's Extended Continental Shelves (ECS). While grid resolution has been steadily improving over time, addition of higher resolution and better navigated data highlights some distortions in the grid that may influence interpretation. In addition to the new ECS data sets, gravity anomaly data has been collected from other vessels; notably the Korean Icebreaker Araon, the Japanese icebreaker Mirai and the German icebreaker Polarstern. Also the GRAV-D project of the US National Geodetic Survey has flown airborne surveys over much of Alaska. These data will be Included in the new AGP grid, which will result in a much improved product when version 3.0 is released in 2015. To make use of these measurements, it is necessary to compile them into a continuous spatial representation. Compilation is complicated by differences in survey parameters, gravimeter sensitivity and reduction methods. Cross-over errors are the classic means to assess repeatability of track measurements. Prior to the introduction of near-universal GPS positioning, positional uncertainty was evaluated by cross-over analysis. GPS positions can be treated as more or less true, enabling evaluation of differences due to contrasting sensitivity, reference and reduction techniques. For the most part, cross-over errors for racks of gravity anomaly data collected since 2008 are less than 0.5 mGals, supporting the compilation of these data with only slight adjustments. Given the different platforms used for various

Effects of Concept Mapping Strategy on Learning Performance in Business and Economics Statistics

Science.gov (United States)

Chiou, Chei-Chang

2009-01-01

A concept map (CM) is a hierarchically arranged, graphic representation of the relationships among concepts. Concept mapping (CMING) is the process of constructing a CM. This paper examines whether a CMING strategy can be useful in helping students to improve their learning performance in a business and economics statistics course. A single…

sUAS Facility Map - Download dataset

Data.gov (United States)

Department of Transportation — sUAS Facility Maps (UASFM) that indicate “pre-approved fly altitudes.” Within each grid on the map, FAA would identify maximum altitudes at which flight is permitted...

Player Types, Play Styles, and Play Complexity: Updating the Entertainment Grid

Science.gov (United States)

Rademacher Mena, Ricardo Javier

2012-01-01

In a previous work the author created the Education and Entertainment Grid by combining various taxonomies from the fields of play and learning. In this paper, a section of this grid known as the Entertainment Grid will be extended by including previously unused elements of Richard Bartle's online player types and Robert Caillois' play complexity.…

Stochastic simulation of large grids using free and public domain software

NARCIS (Netherlands)

Bruin, de S.; Wit, de A.J.W.

2005-01-01

This paper proposes a tiled map procedure enabling sequential indicator simulation on grids consisting of several tens of millions of cells, without putting excessive memory requirements. Spatial continuity across map tiles is handled by conditioning adjacent tiles on their shared boundaries. Tiles

Immune Genetic Learning of Fuzzy Cognitive Map

Institute of Scientific and Technical Information of China (English)

LIN Chun-mei; HE Yue; TANG Bing-yong

2006-01-01

This paper presents a hybrid methodology of automatically constructing fuzzy cognitive map (FCM). The method uses immune genetic algorithm to learn the connection matrix of FCM. In the algorithm, the DNA coding method is used and an immune operator based on immune mechanism is constructed. The characteristics of the system and the experts' knowledge are abstracted as vaccine for restraining the degenerative phenomena during evolution so as to improve the algorithmic efficiency. Finally, an illustrative example is provided, and its results suggest that the method is capable of automatically generating FCM model.

[A Study on the Cognitive Learning Effectiveness of Scenario-Based Concept Mapping in a Neurological Nursing Course].

Science.gov (United States)

Pan, Hui-Ching; Hsieh, Suh-Ing; Hsu, Li-Ling

2015-12-01

The multiple levels of knowledge related to the neurological system deter many students from pursuing studies on this topic. Thus, in facing complicated and uncertain medical circumstances, nursing students have diffi-culty adjusting and using basic neurological-nursing knowledge and skills. Scenario-based concept-mapping teaching has been shown to promote the integration of complicated data, clarify related concepts, and increase the effectiveness of cognitive learning. To investigate the effect on the neurological-nursing cognition and learning attitude of nursing students of a scenario-based concept-mapping strategy that was integrated into the neurological nursing unit of a medical and surgical nursing course. This quasi-experimental study used experimental and control groups and a pre-test / post-test design. Sopho-more (2nd year) students in a four-year program at a university of science and technology in Taiwan were convenience sampled using cluster randomization that was run under SPSS 17.0. Concept-mapping lessons were used as the intervention for the experimental group. The control group followed traditional lesson plans only. The cognitive learning outcome was measured using the neurological nursing-learning examination. Both concept-mapping and traditional lessons significantly improved post-test neurological nursing learning scores (p learning attitude with regard to the teaching material. Furthermore, a significant number in the experimental group expressed the desire to add more lessons on anatomy, physiology, and pathology. These results indicate that this intervention strategy may help change the widespread fear and refusal of nursing students with regard to neurological lessons and may facilitate interest and positively affect learning in this important subject area. Integrating the concept-mapping strategy and traditional clinical-case lessons into neurological nursing lessons holds the potential to increase post-test scores significantly

Grid Mapping for Spatial Pattern Analyses of Recurrent Urban Traffic Congestion Based on Taxi GPS Sensing Data

Directory of Open Access Journals (Sweden)

Yang Liu

2017-03-01

Full Text Available Traffic congestion is one of the most serious problems that impact urban transportation efficiency, especially in big cities. Identifying traffic congestion locations and occurring patterns is a prerequisite for urban transportation managers in order to take proper countermeasures for mitigating traffic congestion. In this study, the historical GPS sensing data of about 12,000 taxi floating cars in Beijing were used for pattern analyses of recurrent traffic congestion based on the grid mapping method. Through the use of ArcGIS software, 2D and 3D maps of the road network congestion were generated for traffic congestion pattern visualization. The study results showed that three types of traffic congestion patterns were identified, namely: point type, stemming from insufficient capacities at the nodes of the road network; line type, caused by high traffic demand or bottleneck issues in the road segments; and region type, resulting from multiple high-demand expressways merging and connecting to each other. The study illustrated that the proposed method would be effective for discovering traffic congestion locations and patterns and helpful for decision makers to take corresponding traffic engineering countermeasures in order to relieve the urban traffic congestion issues.

Sharp wave/ripple network oscillations and learning-associated hippocampal maps.

Science.gov (United States)

Csicsvari, Jozsef; Dupret, David

2014-02-05

Sharp wave/ripple (SWR, 150-250 Hz) hippocampal events have long been postulated to be involved in memory consolidation. However, more recent work has investigated SWRs that occur during active waking behaviour: findings that suggest that SWRs may also play a role in cell assembly strengthening or spatial working memory. Do such theories of SWR function apply to animal learning? This review discusses how general theories linking SWRs to memory-related function may explain circuit mechanisms related to rodent spatial learning and to the associated stabilization of new cognitive maps.

Improving learning with science and social studies text using computer-based concept maps for students with disabilities.

Science.gov (United States)

Ciullo, Stephen; Falcomata, Terry S; Pfannenstiel, Kathleen; Billingsley, Glenna

2015-01-01

Concept maps have been used to help students with learning disabilities (LD) improve literacy skills and content learning, predominantly in secondary school. However, despite increased access to classroom technology, no previous studies have examined the efficacy of computer-based concept maps to improve learning from informational text for students with LD in elementary school. In this study, we used a concurrent delayed multiple probe design to evaluate the interactive use of computer-based concept maps on content acquisition with science and social studies texts for Hispanic students with LD in Grades 4 and 5. Findings from this study suggest that students improved content knowledge during intervention relative to a traditional instruction baseline condition. Learning outcomes and social validity information are considered to inform recommendations for future research and the feasibility of classroom implementation. © The Author(s) 2014.

Formative use of select-and-fill-in concept maps in online instruction: Implications for students of different learning styles

Science.gov (United States)

Kaminski, Charles William

The purpose of this research was to investigate the formative use of Select and Fill-In (SAFI) maps in online instruction and the cognitive, metacognitive, and affective responses of students to their use. In particular, the implications of their use with students of different learning styles was considered. The research question investigated in this qualitative study was: How do students of different learning styles respond to online instruction in which SAFI maps are utilized? This question was explored by using an emergent, collective case study. Each case consisted of community college students who shared a dominant learning style and were enrolled in an online course in environmental studies. Cases in the study were determined using Kolb's Learning Style Inventory (LSI). Seven forms of data were collected during the study. During the first phase of data collection, dominant learning style and background information on student experience with concept mapping and online instruction was determined. In the second phase of data collection, participants completed SAFI maps and quiz items that corresponded to the content of the maps. Achievement data on the map activities and quiz and student responses to a post-SAFI survey and questionnaire were recorded to identify learner cognitive, metacognitive, and affective responses to the tasks. Upon completion of data collection, cases were constructed and compared across learning styles. Cases are presented using the trends, across participants sharing the same dominant learning style, in achievement, behaviors and attitudes as seen in the evidence present in the data. Triangulation of multiple data sources increased reliability and validity, through cross-case analyses, and produced a thick description of the relationship between the cases for each learning style. Evidence suggesting a cognitive response to the SAFI tasks was inconsistent across cases. However, learners with an affinity towards reflective learning

Analysis of a power grid using a Kuramoto-like model

DEFF Research Database (Denmark)

Filatrella, G.; Nielsen, Arne Hejde; Pedersen, Niels Falsig

2008-01-01

We show that there is a link between the Kuramoto paradigm and another system of synchronized oscillators, namely an electrical power distribution grid of generators and consumers. The purpose of this work is to show both the formal analogy and some practical consequences. The mapping can be made...... quantitative, and under some necessary approximations a class of Kuramoto-like models, those with bimodal distribution of the frequencies, is most appropriate for the power-grid. In fact in the power-grid there are two kinds of oscillators: the “sources" delivering power to the “consumers"....

Getting Smart? Climate Change and the Electric Grid

Directory of Open Access Journals (Sweden)

James Meadowcroft

2013-09-01

Full Text Available Interest in the potential of smart grid to transform the way societies generate, distribute, and use electricity has increased dramatically over the past decade. A smarter grid could contribute to both climate change mitigation and adaptation by increasing low-carbon electricity production and enhancing system reliability and resilience. However, climate goals are not necessarily essential for smart grid. Climate change is only one of many considerations motivating innovation in electricity systems, and depending on the path of grid modernization, a future smart grid might do little to reduce, or could even exacerbate, risks associated with climate change. This paper identifies tensions within a shared smart grid vision and illustrates how competing societal priorities are influencing electricity system innovation. Co-existing but divergent priorities among key actors’ are mapped across two critical dimensions: centralized versus decentralized energy systems and radical versus incremental change. Understanding these tensions provides insights on how climate change objectives can be integrated to shape smart grid development. Electricity system change is context-specific and path-dependent, so specific strategies linking smart grid and climate change need to be developed at local, regional, and national levels. And while incremental improvements may bring short term gains, a radical transformation is needed to realize climate objectives.

Map as a tool for independent learning in geography teaching

Directory of Open Access Journals (Sweden)

Živković Ljiljana

2012-01-01

Full Text Available There are different views on self-regulation in the learning process, how it has to be monitored, controlled, which are the circumstances and external factors that affect independent learning. Dominant are the opinions in which the self-regulation is treated as interaction of processes related to the personality, behavioural and contextual processes. Special attention has been given to motivational strategies and students’ desire to focus on goals. By enabling students to make decisions, set their own goals, make a choice, plan and organize activities, the development of self-learning and student autonomy is being encouraged. If students are given the opportunity of independent activities, effect of self-control in the process of learning and self-regulation becomes more pronounced. The paper will explain the factors that influence the process of self-learning that takes place in regular teaching with the help of map as the basic geographic media. [Projekat Ministarstva nauke Republike Srbije, br. 17008

gLExec: gluing grid computing to the Unix world

Science.gov (United States)

Groep, D.; Koeroo, O.; Venekamp, G.

2008-07-01

The majority of compute resources in todays scientific grids are based on Unix and Unix-like operating systems. In this world, user and user-group management are based around the concepts of a numeric 'user ID' and 'group ID' that are local to the resource. In contrast, grid concepts of user and group management are centered around globally assigned identifiers and VO membership, structures that are independent of any specific resource. At the fabric boundary, these 'grid identities' have to be translated to Unix user IDs. New job submission methodologies, such as job-execution web services, community-deployed local schedulers, and the late binding of user jobs in a grid-wide overlay network of 'pilot jobs', push this fabric boundary ever further down into the resource. gLExec, a light-weight (and thereby auditable) credential mapping and authorization system, addresses these issues. It can be run both on fabric boundary, as part of an execution web service, and on the worker node in a late-binding scenario. In this contribution we describe the rationale for gLExec, how it interacts with the site authorization and credential mapping frameworks such as LCAS, LCMAPS and GUMS, and how it can be used to improve site control and traceability in a pilot-job system.

gLExec: gluing grid computing to the Unix world

International Nuclear Information System (INIS)

Groep, D; Koeroo, O; Venekamp, G

2008-01-01

The majority of compute resources in todays scientific grids are based on Unix and Unix-like operating systems. In this world, user and user-group management are based around the concepts of a numeric 'user ID' and 'group ID' that are local to the resource. In contrast, grid concepts of user and group management are centered around globally assigned identifiers and VO membership, structures that are independent of any specific resource. At the fabric boundary, these 'grid identities' have to be translated to Unix user IDs. New job submission methodologies, such as job-execution web services, community-deployed local schedulers, and the late binding of user jobs in a grid-wide overlay network of 'pilot jobs', push this fabric boundary ever further down into the resource. gLExec, a light-weight (and thereby auditable) credential mapping and authorization system, addresses these issues. It can be run both on fabric boundary, as part of an execution web service, and on the worker node in a late-binding scenario. In this contribution we describe the rationale for gLExec, how it interacts with the site authorization and credential mapping frameworks such as LCAS, LCMAPS and GUMS, and how it can be used to improve site control and traceability in a pilot-job system

Improving accuracy of simultaneously reconstructed activity and attenuation maps using deep learning.

Science.gov (United States)

Hwang, Donghwi; Kim, Kyeong Yun; Kang, Seung Kwan; Seo, Seongho; Paeng, Jin Chul; Lee, Dong Soo; Lee, Jae Sung

2018-02-15

Simultaneous reconstruction of activity and attenuation using the maximum likelihood reconstruction of activity and attenuation (MLAA) augmented by time-of-flight (TOF) information is a promising method for positron emission tomography (PET) attenuation correction. However, it still suffers from several problems, including crosstalk artifacts, slow convergence speed, and noisy attenuation maps (μ-maps). In this work, we developed deep convolutional neural networks (CNNs) to overcome these MLAA limitations, and we verified their feasibility using a clinical brain PET data set. Methods: We applied the proposed method to one of the most challenging PET cases for simultaneous image reconstruction ( 18 F-FP-CIT PET scans with highly specific binding to striatum of the brain). Three different CNN architectures (convolutional autoencoder (CAE), U-net, hybrid of CAE and U-net) were designed and trained to learn x-ray computed tomography (CT) derived μ-map (μ-CT) from the MLAA-generated activity distribution and μ-map (μ-MLAA). PET/CT data of 40 patients with suspected Parkinson's disease were employed for five-fold cross-validation. For the training of CNNs, 800,000 transverse PET slices and CTs augmented from 32 patient data sets were used. The similarity to μ-CT of the CNN-generated μ-maps (μ-CAE, μ-Unet, and μ-Hybrid) and μ-MLAA was compared using Dice similarity coefficients. In addition, we compared the activity concentration of specific (striatum) and non-specific binding regions (cerebellum and occipital cortex) and the binding ratios in the striatum in the PET activity images reconstructed using those μ-maps. Results: The CNNs generated less noisy and more uniform μ-maps than original μ-MLAA. Moreover, the air cavities and bones were better resolved in the proposed CNN outputs. In addition, the proposed deep learning approach was useful for mitigating the crosstalk problem in the MLAA reconstruction. The hybrid network of CAE and U-net yielded the

Designing problem-based curricula: The role of concept mapping in scaffolding learning for the health sciences

Directory of Open Access Journals (Sweden)

Susan M. Bridges

2015-03-01

Full Text Available While the utility of concept mapping has been widely reported in primary and secondary educational contexts, its application in the health sciences in higher education has been less frequently noted. Two case studies of the application of concept mapping in undergraduate and postgraduate health sciences are detailed in this paper. The case in undergraduate dental education examines the role of concept mapping in supporting problem-based learning and explores how explicit induction into the principles and practices of CM has add-on benefits to learning in an inquiry-based curriculum. The case in postgraduate medical education describes the utility of concept mapping in an online inquiry-based module design. Specific attention is given to applications of CMapTools™ software to support the implementation of Novakian concept mapping in both inquiry-based curricular contexts.

Integrasi concise learning method dengan mind mapping dalam pembelajaran matematika di perguruan tinggi

Directory of Open Access Journals (Sweden)

Ciptianingsari Ayu Vitantri

2017-11-01

Full Text Available [Bahasa]: Penelitian ini bertujuan untuk mendeskripsikan penerapan, pemahaman konsep, dan respon mahasiswa terhadap pembelajaran CLM  yang diintegrasikan dengan mind mapping pada mata kuliah aljabar linier elementer I. Penelitian ini termasuk dalam penelitian deskriptif kualitatif, dengan subjek penelitian adalah mahasiswa prodi matematika dan pendidikan matematika semester gasal tahun ajaran 2016/2017 yang mengambil mata kuliah aljabar linier elementer I. Instrumen utama dalam penelitian ini adalah peneliti sendiri dengan instrumen pendukung yaitu lembar observasi, tes pemahaman konsep, angket respon, dan pedoman wawancara. Hasil penelitian menunjukkan: 1 Langkah-langkah pembelajaran CLM yang diintegrasikan dengan mind mapping meliputi preview, participate, process (mengolah informasi dalam bentuk mind mapping, practice, dan produce. 2 Pemahaman konsep mahasiswa mengalami peningkatan setelah pembelajaran. Dan 3 Mahasiswa memberikan respon positif terhadap pelaksanaan pembelajaran CLM yang diintegrasikan dengan mind mapping. Kata kunci: Concise Learning Method; Mind Mapping; Pemahaman Konsep; Respon; Aljabar Linier Elementer. [English]: This research aimed to describe the implementation, students’ understanding and their responses on CLM integrated with mind mapping on Linear Elementary Algebra I course,  This research was qualitative descriptive research with the subjects involved were students of mathematics and mathematics education on 2016/2017 academic year who took Linear Elementary Algebra I course. The main instrument in this research was the researcher and the supporting instruments used are observation sheet, test, response questionnaire, and interview guide. The results showed that: 1 The steps of CLM integrated with mind mapping include preview, participate, process (process all information into mind mapping, practice, and produce. 2 The students’ understanding of the mathematics concept of were developed. And 3 the students

JColorGrid: software for the visualization of biological measurements.

OpenAIRE

Joachimiak, Marcin P; Weisman, Jennifer L; May, Barnaby Ch

2006-01-01

Abstract Background Two-dimensional data colourings are an effective medium by which to represent three-dimensional data in two dimensions. Such "color-grid" representations have found increasing use in the biological sciences (e.g. microarray 'heat maps' and bioactivity data) as they are particularly suited to complex data sets and offer an alternative to the graphical representations included in traditional statistical software packages. The effectiveness of color-grids lies in their graphi...

Trends in life science grid: from computing grid to knowledge grid

Directory of Open Access Journals (Sweden)

Konagaya Akihiko

2006-12-01

Full Text Available Abstract Background Grid computing has great potential to become a standard cyberinfrastructure for life sciences which often require high-performance computing and large data handling which exceeds the computing capacity of a single institution. Results This survey reviews the latest grid technologies from the viewpoints of computing grid, data grid and knowledge grid. Computing grid technologies have been matured enough to solve high-throughput real-world life scientific problems. Data grid technologies are strong candidates for realizing "resourceome" for bioinformatics. Knowledge grids should be designed not only from sharing explicit knowledge on computers but also from community formulation for sharing tacit knowledge among a community. Conclusion Extending the concept of grid from computing grid to knowledge grid, it is possible to make use of a grid as not only sharable computing resources, but also as time and place in which people work together, create knowledge, and share knowledge and experiences in a community.

Grid interoperability: joining grid information systems

International Nuclear Information System (INIS)

Flechl, M; Field, L

2008-01-01

A grid is defined as being 'coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organizations'. Over recent years a number of grid projects, many of which have a strong regional presence, have emerged to help coordinate institutions and enable grids. Today, we face a situation where a number of grid projects exist, most of which are using slightly different middleware. Grid interoperation is trying to bridge these differences and enable Virtual Organizations to access resources at the institutions independent of their grid project affiliation. Grid interoperation is usually a bilateral activity between two grid infrastructures. Recently within the Open Grid Forum, the Grid Interoperability Now (GIN) Community Group is trying to build upon these bilateral activities. The GIN group is a focal point where all the infrastructures can come together to share ideas and experiences on grid interoperation. It is hoped that each bilateral activity will bring us one step closer to the overall goal of a uniform grid landscape. A fundamental aspect of a grid is the information system, which is used to find available grid services. As different grids use different information systems, interoperation between these systems is crucial for grid interoperability. This paper describes the work carried out to overcome these differences between a number of grid projects and the experiences gained. It focuses on the different techniques used and highlights the important areas for future standardization

[Utility of conceptual schemes and mental maps on the teaching-learning process of residents in pediatrics].

Science.gov (United States)

Cruza, Norberto Sotelo; Fierros, Luis E

2006-01-01

The present study was done at the internal medicine service oft he Hospital lnfantil in the State of Sonora, Mexico. We tried to address the question of the use of conceptual schemes and mind maps and its impact on the teaching-learning-evaluation process among medical residents. Analyze the effects of conceptual schemes, and mind maps as a teaching and evaluation tool and compare them with multiple choice exams among Pediatric residents. Twenty two residents (RI, RII, RIII)on service rotation during six months were assessed initially, followed by a lecture on a medical subject. Conceptual schemes and mind maps were then introduced as a teaching-learning-evaluation instrument. Comprehension impact and comparison with a standard multiple choice evaluation was done. The statistical package (JMP version 5, SAS inst. 2004) was used. We noted that when we used conceptual schemes and mind mapping, learning improvement was noticeable among the three groups of residents (P evaluation tool when compared with multiple choice exams (P < 0.0005). Based on our experience we recommend the use of this educational technique for medical residents in training.

Mapping robust parallel multigrid algorithms to scalable memory architectures

Science.gov (United States)

Overman, Andrea; Vanrosendale, John

1993-01-01

The convergence rate of standard multigrid algorithms degenerates on problems with stretched grids or anisotropic operators. The usual cure for this is the use of line or plane relaxation. However, multigrid algorithms based on line and plane relaxation have limited and awkward parallelism and are quite difficult to map effectively to highly parallel architectures. Newer multigrid algorithms that overcome anisotropy through the use of multiple coarse grids rather than relaxation are better suited to massively parallel architectures because they require only simple point-relaxation smoothers. In this paper, we look at the parallel implementation of a V-cycle multiple semicoarsened grid (MSG) algorithm on distributed-memory architectures such as the Intel iPSC/860 and Paragon computers. The MSG algorithms provide two levels of parallelism: parallelism within the relaxation or interpolation on each grid and across the grids on each multigrid level. Both levels of parallelism must be exploited to map these algorithms effectively to parallel architectures. This paper describes a mapping of an MSG algorithm to distributed-memory architectures that demonstrates how both levels of parallelism can be exploited. The result is a robust and effective multigrid algorithm for distributed-memory machines.

Using Repertory Grids to Explore Musical Skills and Attitudes in a Mature-Age Adult at the Early Stages of Learning for Self-Fulfilment: A Case Study of James

Science.gov (United States)

Taylor, Angela

2012-01-01

Repertory grids were used as a research tool to explore 73-year-old James' musical development over two years. Choosing two music learning cultures for his instrumental learning, James learned the piano in a college workshop and the Appalachian dulcimer in his local folk group. There were clear changes in his musical skills and attitudes,…

The Effectiveness of Concept Maps in Teaching Physics Concepts Applied to Engineering Education: Experimental Comparison of the Amount of Learning Achieved With and Without Concept Maps

Science.gov (United States)

Martínez, Guadalupe; Pérez, Ángel Luis; Suero, María Isabel; Pardo, Pedro J.

2013-04-01

A study was conducted to quantify the effectiveness of concept maps in learning physics in engineering degrees. The following research question was posed: What was the difference in learning results from the use of concept maps to study a particular topic in an engineering course? The study design was quasi-experimental and used a post-test as a measuring instrument. The sample included 114 university students from the School of Industrial Engineering who were divided into two equivalent homogeneous groups of 57 students each. The amount of learning attained by the students in each group was compared, with the independent variable being the teaching method; the experimental group (E.G.) used concept maps, while the control group (C.G.) did not. We performed a crossover study with the two groups of students, with one group acting as the E.G. for the topic of optical fibers and as the C.G. for the topic of the fundamental particles of matter and vice versa for the other group. For each of the two topics studied, the evaluation instrument was a test of 100 dichotomous items. The resulting data were subjected to a comparative statistical analysis, which revealed a significant difference in the amount of learning attained by the E.G. students as compared with the C.G. students. The results allow us to state that for the use of concept maps, the average increment in the E.G. students' learning was greater than 19 percentage points.

AQUAGRID: The subsurface hydrology Grid service of the Sardinian regional Grid infrastructure

International Nuclear Information System (INIS)

Lecca, G.; Murgia, F.; Maggi, P.; Perias, A.

2007-01-01

AQUAGRID is the subsurface hydrology service of the Sardinian regional Grid infrastructure, designed to deliver complex environmental applications via a user-friendly Web portal. The service is oriented towards the needs of water professionals providing them a flexible and powerful tool to solve water resources management problems and aid decision between different remediation options for contaminated soil and groundwater. In this paper, the AQUAGRID application concept and the enabling technologies are illustrated. The heart of the service is the CODESA-3D hydrogeological model to simulate complex and large groundwater flow and contaminant transport problems. The relevant experience gained from the porting of the CODESA-3D application on the EGEE infrastructure, via the GILDA test bed (https://gilda.ct.infn.it), has contributed to the service prototype. AQUAGRID is built on top of compute-Grid technologies by means of the EnginFrame Grid portal. The portal enables the interaction with the underlying Grid infrastructure and manages the computational requirements of the whole application system. Data management, distribution and visualization mechanisms are based on the tools provided by the DatacroSSing Decision Support System (http://datacrossing.crs4.it). The DSS, built on top of the SRB data-Grid middleware, is based on Web-GIS and relational database technologies. The resulting production environment allows the end-user to visualize and interact with the results of the performed analyses, using graphs, annotated maps and 3D objects. Such a set of graphical widgets increases enormously the number of AQUAGRID potential users because it does not require any specific expertise of the physical model and technological background to be understood. (Author)

Macedonian transmission grid capability and development

International Nuclear Information System (INIS)

Naumoski, K.; Achkoska, E.; Paunoski, A.

2015-01-01

The main task of the transmission grid is to guarantee evacuation of electricity from production facilities and, at the same time, supply the electricity to all customers, in a secure, reliable and qualitative manner. During the last years, transmission grid goes through the period of fast and important development, as a result of implementation of renewable and new technologies and creation of internal European electricity market. Due to these reasons, capacity of the existing grid needs to be upgraded either with optimization of existing infrastructure or constructing the new transmission projects. Among the various solutions for strengthening the grid, the one with the minimal investment expenses for construction is selected. While planning the national transmission grid, MEPSO planners apply multi-scenarios analyses, in order to handle all uncertainties, particularly in the forecasts on loads, production and exchange of electricity, location and size of the new power plants, hydrological conditions, integration of renewable sources and the evolution of the electricity market. Visions for development of European transmission grid are also considered. Special attention in the development plan is paid to modelling of power systems in the region of South-Eastern Europe and covering a wider area of the regional transmission grid with simulations of various market transactions. Macedonian transmission grid is developed to satisfy all requirements for electricity production/supply and transits, irrespective which scenario will be realized on long-term basis. Transmission development plan gives the road map for grid evolution from short-term and mid-term period towards long-term horizons (15-20 years ahead). While creating long-term visions, a big challenge in front of transmission planners is implementation of NPP. The paper gives overview of the planning process of Macedonian transmission grid,comprising: definition of scenarios,planning methodology and assessment of

Modeling speech imitation and ecological learning of auditory-motor maps

Directory of Open Access Journals (Sweden)

Claudia eCanevari

2013-06-01

Full Text Available Classical models of speech consider an antero-posterior distinction between perceptive and productive functions. However, the selective alteration of neural activity in speech motor centers, via transcranial magnetic stimulation, was shown to affect speech discrimination. On the automatic speech recognition (ASR side, the recognition systems have classically relied solely on acoustic data, achieving rather good performance in optimal listening conditions. The main limitations of current ASR are mainly evident in the realistic use of such systems. These limitations can be partly reduced by using normalization strategies that minimize inter-speaker variability by either explicitly removing speakers’ peculiarities or adapting different speakers to a reference model. In this paper we aim at modeling a motor-based imitation learning mechanism in ASR. We tested the utility of a speaker normalization strategy that uses motor representations of speech and compare it with strategies that ignore the motor domain. Specifically, we first trained a regressor through state-of-the-art machine learning techniques to build an auditory-motor mapping, in a sense mimicking a human learner that tries to reproduce utterances produced by other speakers. This auditory-motor mapping maps the speech acoustics of a speaker into the motor plans of a reference speaker. Since, during recognition, only speech acoustics are available, the mapping is necessary to recover motor information. Subsequently, in a phone classification task, we tested the system on either one of the speakers that was used during training or a new one. Results show that in both cases the motor-based speaker normalization strategy almost always outperforms all other strategies where only acoustics is taken into account.

OBLIMAP 2.0: a fast climate model-ice sheet model coupler including online embeddable mapping routines

Science.gov (United States)

Reerink, Thomas J.; van de Berg, Willem Jan; van de Wal, Roderik S. W.

2016-11-01

This paper accompanies the second OBLIMAP open-source release. The package is developed to map climate fields between a general circulation model (GCM) and an ice sheet model (ISM) in both directions by using optimal aligned oblique projections, which minimize distortions. The curvature of the surfaces of the GCM and ISM grid differ, both grids may be irregularly spaced and the ratio of the grids is allowed to differ largely. OBLIMAP's stand-alone version is able to map data sets that differ in various aspects on the same ISM grid. Each grid may either coincide with the surface of a sphere, an ellipsoid or a flat plane, while the grid types might differ. Re-projection of, for example, ISM data sets is also facilitated. This is demonstrated by relevant applications concerning the major ice caps. As the stand-alone version also applies to the reverse mapping direction, it can be used as an offline coupler. Furthermore, OBLIMAP 2.0 is an embeddable GCM-ISM coupler, suited for high-frequency online coupled experiments. A new fast scan method is presented for structured grids as an alternative for the former time-consuming grid search strategy, realising a performance gain of several orders of magnitude and enabling the mapping of high-resolution data sets with a much larger number of grid nodes. Further, a highly flexible masked mapping option is added. The limitation of the fast scan method with respect to unstructured and adaptive grids is discussed together with a possible future parallel Message Passing Interface (MPI) implementation.

OBLIMAP 2.0: a fast climate model–ice sheet model coupler including online embeddable mapping routines

Directory of Open Access Journals (Sweden)

T. J. Reerink

2016-11-01

Full Text Available This paper accompanies the second OBLIMAP open-source release. The package is developed to map climate fields between a general circulation model (GCM and an ice sheet model (ISM in both directions by using optimal aligned oblique projections, which minimize distortions. The curvature of the surfaces of the GCM and ISM grid differ, both grids may be irregularly spaced and the ratio of the grids is allowed to differ largely. OBLIMAP's stand-alone version is able to map data sets that differ in various aspects on the same ISM grid. Each grid may either coincide with the surface of a sphere, an ellipsoid or a flat plane, while the grid types might differ. Re-projection of, for example, ISM data sets is also facilitated. This is demonstrated by relevant applications concerning the major ice caps. As the stand-alone version also applies to the reverse mapping direction, it can be used as an offline coupler. Furthermore, OBLIMAP 2.0 is an embeddable GCM–ISM coupler, suited for high-frequency online coupled experiments. A new fast scan method is presented for structured grids as an alternative for the former time-consuming grid search strategy, realising a performance gain of several orders of magnitude and enabling the mapping of high-resolution data sets with a much larger number of grid nodes. Further, a highly flexible masked mapping option is added. The limitation of the fast scan method with respect to unstructured and adaptive grids is discussed together with a possible future parallel Message Passing Interface (MPI implementation.

Michigan Magnetic and Gravity Maps and Data: A Website for the Distribution of Data

Science.gov (United States)

Daniels, David L.; Kucks, Robert P.; Hill, Patricia L.; Snyder, Stephen L.

2009-01-01

This web site provides the best available, public-domain, aeromagnetic and gravity data in the State of Michigan and merges these data into composite grids that are available for downloading. The magnetic grid is compiled from 25 separate magnetic surveys that have been knit together to form a single composite digital grid and map. The magnetic survey grids have been continued to 305 meters (1,000 feet) above ground and merged together to form the State compilation. A separate map shows the location of the aeromagnetic surveys, color-coded to the survey flight-line spacing. In addition, a complete Bouguer gravity anomaly grid and map were generated from more than 20,000 gravity station measurements from 33 surveys. A table provides the facts about each gravity survey where known.

A Subdivision Method to Unify the Existing Latitude and Longitude Grids

Directory of Open Access Journals (Sweden)

Chengqi Cheng

2016-09-01

Full Text Available As research on large regions of earth progresses, many geographical subdivision grids have been established for various spatial applications by different industries and disciplines. However, there is no clear relationship between the different grids and no consistent spatial reference grid that allows for information exchange and comprehensive application. Sharing and exchange of data across departments and applications are still at a bottleneck. It would represent a significant step forward to build a new grid model that is inclusive of or compatible with most of the existing geodesic grids and that could support consolidation and exchange within existing data services. This study designs a new geographical coordinate global subdividing grid with one dimension integer coding on a 2n tree (GeoSOT that has 2n coordinate subdivision characteristics (global longitude and latitude subdivision and can form integer hierarchies at degree, minute, and second levels. This grid has the multi-dimensional quadtree hierarchical characteristics of a digital earth grid, but also provides good consistency with applied grids, such as those used in mapping, meteorology, oceanography and national geographical, and three-dimensional digital earth grids. No other existing grid codes possess these characteristics.

Projecting pipeline construction by AutoDesk Map; Projektierung von Rohrleitungsbaumassnahmen mit AutoDesk Map

Energy Technology Data Exchange (ETDEWEB)

Taschendorf, M.; Voigtlaender, M. [Hamburger Wasserwerke GmbH, Hamburg (Germany)

2005-12-15

Presented is AutoDesk Map, which enables the construction and planning of big grids for water- and gas supply. In this example industrial equipment is driven as objects in AutoDesk Map. Therefore the consistence of the data is guaranted and comprehensive CAD functions are available for industrial equipment and topologies. (GL)

GeoMapApp Learning Activities: A Virtual Lab Environment for Student-Centred Engagement with Geoscience Data

Science.gov (United States)

Kluge, S.; Goodwillie, A. M.

2012-12-01

As STEM learning requirements enter the mainstream, there is benefit to providing the tools necessary for students to engage with research-quality geoscience data in a cutting-edge, easy-to-use map-based interface. Funded with an NSF GeoEd award, GeoMapApp Learning Activities ( http://serc.carleton.edu/geomapapp/collection.html ) are being created to help in that endeavour. GeoMapApp Learning Activities offer step-by-step instructions within a guided inquiry approach that enables students to dictate the pace of learning. Based upon GeoMapApp (http://www.geomapapp.org), a free, easy-to-use map-based data exploration and visualisation tool, each activity furnishes the educator with an efficient package of downloadable documents. This includes step-by-step student instructions and answer sheet; an educator's annotated worksheet containing teaching tips, additional content and suggestions for further work; and, quizzes for use before and after the activity to assess learning. Examples of activities so far created involve calculation and analysis of the rate of seafloor spreading; compilation of present-day evidence for huge ancient landslides on the seafloor around the Hawaiian islands; a study of radiometrically-dated volcanic rocks to help understand the concept of hotspots; and, the optimisation of contours as a means to aid visualisation of 3-D data sets on a computer screen. The activities are designed for students at the introductory undergraduate, community college and high school levels, and present a virtual lab-like environment to expose students to content and concepts typically found in those educational settings. The activities can be used in the classroom or out of class, and their guided nature means that the requirement for teacher intervention is reduced thus allowing students to spend more time analysing and understanding geoscience data, content and concepts. Each activity is freely available through the SERC-Carleton web site.

Concept Mapping in the Humanities to Facilitate Reflection: Externalizing the Relationship between Public and Personal Learning

Science.gov (United States)

Kandiko, Camille; Hay, David; Weller, Saranne

2013-01-01

This article discusses how mapping techniques were used in university teaching in a humanities subject. The use of concept mapping was expanded as a pedagogical tool, with a focus on reflective learning processes. Data were collected through a longitudinal study of concept mapping in a university-level Classics course. This was used to explore how…

Smart grid demonstrators and experiments in France: Economic assessments of smart grids. Challenges, methods, progress status and demonstrators; Contribution of 'smart grid' demonstrators to electricity transport and market architectures; Challenges and contributions of smart grid demonstrators to the distribution network. Focus on the integration of decentralised production; Challenges and contributions of smart grid demonstrators to the evolution of providing-related professions and to consumption practices

International Nuclear Information System (INIS)

Sudret, Thierry; Belhomme, Regine; Nekrassov, Andrei; Chartres, Sophie; Chiappini, Florent; Drouineau, Mathilde; Hadjsaid, Nouredine; Leonard, Cedric; Bena, Michel; Buhagiar, Thierry; Lemaitre, Christian; Janssen, Tanguy; Guedou, Benjamin; Viana, Maria Sebastian; Malarange, Gilles; Hadjsaid, Nouredine; Petit, Marc; Lehec, Guillaume; Jahn, Rafael; Gehain, Etienne

2015-01-01

This publication proposes a set of four articles which give an overview of challenges and contributions of smart grid demonstrators for the French electricity system according to different perspectives and different stakeholders. These articles present the first lessons learned from these demonstrators in terms of technical and technological innovations, of business and regulation models, and of customer behaviour and acceptance. More precisely, the authors discuss economic assessments of smart grids with an overview of challenges, methods, progress status and existing smart grid programs in the World, comment the importance of the introduction of intelligence at hardware, software and market level, highlight the challenges and contributions of smart grids for the integration of decentralised production, and discuss how smart grid demonstrators impact providing-related professions and customer consumption practices

The extended RBAC model based on grid computing

Institute of Scientific and Technical Information of China (English)

CHEN Jian-gang; WANG Ru-chuan; WANG Hai-yan

2006-01-01

This article proposes the extended role-based access control (RBAC) model for solving dynamic and multidomain problems in grid computing, The formulated description of the model has been provided. The introduction of context and the mapping relations of context-to-role and context-to-permission help the model adapt to dynamic property in grid environment.The multidomain role inheritance relation by the authorization agent service realizes the multidomain authorization amongst the autonomy domain. A function has been proposed for solving the role inheritance conflict during the establishment of the multidomain role inheritance relation.

Neurophysiological evidence for the interplay of speech segmentation and word-referent mapping during novel word learning.

Science.gov (United States)

François, Clément; Cunillera, Toni; Garcia, Enara; Laine, Matti; Rodriguez-Fornells, Antoni

2017-04-01

Learning a new language requires the identification of word units from continuous speech (the speech segmentation problem) and mapping them onto conceptual representation (the word to world mapping problem). Recent behavioral studies have revealed that the statistical properties found within and across modalities can serve as cues for both processes. However, segmentation and mapping have been largely studied separately, and thus it remains unclear whether both processes can be accomplished at the same time and if they share common neurophysiological features. To address this question, we recorded EEG of 20 adult participants during both an audio alone speech segmentation task and an audiovisual word-to-picture association task. The participants were tested for both the implicit detection of online mismatches (structural auditory and visual semantic violations) as well as for the explicit recognition of words and word-to-picture associations. The ERP results from the learning phase revealed a delayed learning-related fronto-central negativity (FN400) in the audiovisual condition compared to the audio alone condition. Interestingly, while online structural auditory violations elicited clear MMN/N200 components in the audio alone condition, visual-semantic violations induced meaning-related N400 modulations in the audiovisual condition. The present results support the idea that speech segmentation and meaning mapping can take place in parallel and act in synergy to enhance novel word learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of publically available Moho depth and crustal thickness grids with newly derived grids by 3D gravity inversion for the High Arctic region.

Science.gov (United States)

Lebedeva-Ivanova, Nina; Gaina, Carmen; Minakov, Alexander; Kashubin, Sergey

2016-04-01

We derived Moho depth and crustal thickness for the High Arctic region by 3D forward and inverse gravity modelling method in the spectral domain (Minakov et al. 2012) using lithosphere thermal gravity anomaly correction (Alvey et al., 2008); a vertical density variation for the sedimentary layer and lateral crustal variation density. Recently updated grids of bathymetry (Jakobsson et al., 2012), gravity anomaly (Gaina et al, 2011) and dynamic topography (Spasojevic & Gurnis, 2012) were used as input data for the algorithm. TeMAr sedimentary thickness grid (Petrov et al., 2013) was modified according to the most recently published seismic data, and was re-gridded and utilized as input data. Other input parameters for the algorithm were calibrated using seismic crustal scale profiles. The results are numerically compared with publically available grids of the Moho depth and crustal thickness for the High Arctic region (CRUST 1 and GEMMA global grids; the deep Arctic Ocean grids by Glebovsky et al., 2013) and seismic crustal scale profiles. The global grids provide coarser resolution of 0.5-1.0 geographic degrees and not focused on the High Arctic region. Our grids better capture all main features of the region and show smaller error in relation to the seismic crustal profiles compare to CRUST 1 and GEMMA grids. Results of 3D gravity modelling by Glebovsky et al. (2013) with separated geostructures approach show also good fit with seismic profiles; however these grids cover the deep part of the Arctic Ocean only. Alvey A, Gaina C, Kusznir NJ, Torsvik TH (2008). Integrated crustal thickness mapping and plate recon-structions for the high Arctic. Earth Planet Sci Lett 274:310-321. Gaina C, Werner SC, Saltus R, Maus S (2011). Circum-Arctic mapping project: new magnetic and gravity anomaly maps of the Arctic. Geol Soc Lond Mem 35, 39-48. Glebovsky V.Yu., Astafurova E.G., Chernykh A.A., Korneva M.A., Kaminsky V.D., Poselov V.A. (2013). Thickness of the Earth's crust in the

Prevalence of Mind Mapping as a Teaching and Learning Strategy in Physical Therapy Curricula

Science.gov (United States)

Zipp, Genevieve; Maher, Catherine

2013-01-01

Background and Purpose: Regardless of our discipline educators seek to create environments that actively engage students in their learning journey. One teaching and learning strategy that has emerged in higher education is mind mapping (MM). The purpose of this exploratory study was to determine the prevalence of MM usage in a health science…

Concept Maps for Assessing Change in Learning: A Study of Undergraduate Business Students in First-Year Marketing in China

Science.gov (United States)

von der Heidt, Tania

2015-01-01

This paper explains the application of concept mapping to help foster a learning-centred approach. It investigates how concept maps are used to measure the change in learning following a two-week intensive undergraduate Marketing Principles course delivered to 162 Chinese students undertaking a Bachelor of Business Administration programme in…

Preexposure effects in spatial learning: From gestaltic to associative and attentional cognitive maps

Directory of Open Access Journals (Sweden)

Edward S. Redhead

2002-01-01

Full Text Available In this paper a series of studies and theoretical proposals about how preexposure to environmental cues affects subsequent spatial learning are reviewed. Traditionally, spatial learning had been thought to depend on gestaltic non-associative processes, and well established phenomena such as latent learning or instantaneous transfer have been taken to provide evidence for this sort of cognitive mapping. However, reviewing the literature examining these effects reveals that there is no need to advocate for gestaltic processes since standard associative learning theory provides an adequate framework for accounting for navigation skills. Recent studies reveal that attentional processes play a role in spatial learning. The need for an integrated attentional and associative approach to explain spatial learning is discussed.

Authoring Tool for Identifying Learning Styles, Using Self-Organizing Maps on Mobile Devices

Directory of Open Access Journals (Sweden)

Ramón Zatarain Cabada

2011-05-01

Full Text Available This work explores a methodological proposal whose main objective is the identification of learning styles using a method of self-organizing maps designed to work, for the most part, on mobile devices. These maps can work in real time and without direct student interaction, which implies the absence of prior information. The results generated are an authoring tool for adaptive courses in Web 2.0 environments.

Effect of Software Designed by Computer Conceptual Map Method in Mobile Environment on Learning Level of Nursing Students

Directory of Open Access Journals (Sweden)

Salmani N

2015-12-01

Full Text Available Aims: In order to preserve its own progress, nursing training has to be utilized new training methods, in such a case that the teaching methods used by the nursing instructors enhance significant learning via preventing superficial learning in the students. Conceptual Map Method is one of the new training strategies playing important roles in the field. The aim of this study was to investigate the effectiveness of the designed software based on the mobile phone computer conceptual map on the learning level of the nursing students. Materials & Methods: In the semi-experimental study with pretest-posttest plan, 60 students, who were studying at the 5th semester, were studied at the 1st semester of 2015-16. Experimental group (n=30 from Meibod Nursing Faculty and control group (n=30 from Yazd Shahid Sadoughi Nursing Faculty were trained during the first 4 weeks of the semester, using computer conceptual map method and computer conceptual map method in mobile phone environment. Data was collected, using a researcher-made academic progress test including “knowledge” and “significant learning”. Data was analyzed in SPSS 21 software using Independent T, Paired T, and Fisher tests. Findings: There were significant increases in the mean scores of knowledge and significant learning in both groups before and after the intervention (p0.05. Nevertheless, the process of change of the scores of significant learning level between the groups was statistically significant (p<0.05.   Conclusion: Presenting the course content as conceptual map in mobile phone environment positively affects the significant learning of the nursing students.

Topographical memory for newly-learned maps is differentially affected by route-based versus landmark-based learning

DEFF Research Database (Denmark)

Beatty, Erin L.; Muller-Gass, Alexandra; Wojtarowicz, Dorothy

2018-01-01

on their ability to distinguish previously studied 'old' maps from completely unfamiliar 'new' maps under conditions of high and low working memory load in the functional MRI scanner. Viewing old versus new maps was associated with relatively greater activation in a distributed set of regions including bilateral...... inferior temporal gyrus - an important region for recognizing visual objects. Critically, whereas the performance of participants who had followed a route-based strategy dropped to chance level under high working memory load, participants who had followed a landmark-based strategy performed at above chance...... levels under both high and low working memory load - reflected by relatively greater activation in the left inferior parietal lobule (i.e. rostral part of the supramarginal gyrus known as area PFt). Our findings suggest that landmark-based learning may buffer against the effects of working memory load...

Self-enhancement learning: target-creating learning and its application to self-organizing maps.

Science.gov (United States)

Kamimura, Ryotaro

2011-05-01

In this article, we propose a new learning method called "self-enhancement learning." In this method, targets for learning are not given from the outside, but they can be spontaneously created within a neural network. To realize the method, we consider a neural network with two different states, namely, an enhanced and a relaxed state. The enhanced state is one in which the network responds very selectively to input patterns, while in the relaxed state, the network responds almost equally to input patterns. The gap between the two states can be reduced by minimizing the Kullback-Leibler divergence between the two states with free energy. To demonstrate the effectiveness of this method, we applied self-enhancement learning to the self-organizing maps, or SOM, in which lateral interactions were added to an enhanced state. We applied the method to the well-known Iris, wine, housing and cancer machine learning database problems. In addition, we applied the method to real-life data, a student survey. Experimental results showed that the U-matrices obtained were similar to those produced by the conventional SOM. Class boundaries were made clearer in the housing and cancer data. For all the data, except for the cancer data, better performance could be obtained in terms of quantitative and topological errors. In addition, we could see that the trustworthiness and continuity, referring to the quality of neighborhood preservation, could be improved by the self-enhancement learning. Finally, we used modern dimensionality reduction methods and compared their results with those obtained by the self-enhancement learning. The results obtained by the self-enhancement were not superior to but comparable with those obtained by the modern dimensionality reduction methods.

GridiLoc: A Backtracking Grid Filter for Fusing the Grid Model with PDR Using Smartphone Sensors

Directory of Open Access Journals (Sweden)

Jianga Shang

2016-12-01

Full Text Available Although map filtering-aided Pedestrian Dead Reckoning (PDR is capable of largely improving indoor localization accuracy, it becomes less efficient when coping with highly complex indoor spaces. For instance, indoor spaces with a few close corners or neighboring passages can lead to particles entering erroneous passages, which can further cause the failure of subsequent tracking. To address this problem, we propose GridiLoc, a reliable and accurate pedestrian indoor localization method through the fusion of smartphone sensors and a grid model. The key novelty of GridiLoc is the utilization of a backtracking grid filter for improving localization accuracy and for handling dead ending issues. In order to reduce the time consumption of backtracking, a topological graph is introduced for representing candidate backtracking points, which are the expected locations at the starting time of the dead ending. Furthermore, when the dead ending is caused by the erroneous step length model of PDR, our solution can automatically calibrate the model by using the historical tracking data. Our experimental results show that GridiLoc achieves a higher localization accuracy and reliability compared with the commonly-used map filtering approach. Meanwhile, it maintains an acceptable computational complexity.

Smart Grid Risk Management

Science.gov (United States)

Abad Lopez, Carlos Adrian

, dynamic learning methods for scheduling the maintenance of direct load control switches whose operating state is not directly observable and can only be inferred from the metered electricity consumption, and machine learning methods for accurately forecasting the load of hundreds of thousands of residential, commercial and industrial customers. These algorithms have been implemented in the software system provided by AutoGrid, Inc., and this system has helped several utilities in the Pacific Northwest, Oklahoma, California and Texas, provide more reliable power to their customers at significantly reduced prices. Providing power to widely spread out communities in developing countries using the conventional power grid is not economically feasible. The most attractive alternative source of affordable energy for these communities is solar micro-grids. We discuss risk-aware robust methods to optimally size and operate solar micro-grids in the presence of uncertain demand and uncertain renewable generation. These algorithms help system operators to increase their revenue while making their systems more resilient to inclement weather conditions.

Developing nurses' intercultural/intraprofessional communication skills using the EXCELLence in Cultural Experiential Learning and Leadership Social Interaction Maps.

Science.gov (United States)

Henderson, Saras; Barker, Michelle

2017-09-27

To examine how the use of Social Interaction Maps, a tool in the EXCELLence in Cultural Experiential Learning and Leadership Program, can enhance the development of nurses' intercultural/intraprofessional communication skills. Nurses face communication challenges when interacting with others from similar background as well as those from a culturally and linguistically diverse background. We used the EXCELLence in Cultural Experiential Learning and Leadership Program's Social Interaction Maps tool to foster intercultural/intraprofessional communication skills in nurses. Social Interaction Maps describe verbal and nonverbal communication behaviours that model ways of communicating in a culturally appropriate manner. The maps include four stages of an interaction, namely Approach, Bridging, Communicating and Departing using the acronym ABCD. Qualitative approach was used with a purposeful sample of nurses enrolled in a postgraduate course. Fifteen participants were recruited. The Social Interaction Map tool was taught to participants in a workshop where they engaged in sociocultural communication activities using scenarios. Participants were asked to apply Social Interaction Maps in their workplaces. Six weeks later, participants completed a semistructured open-ended questionnaire and participated in a discussion forum on their experience of using Social Interaction Maps. Data were content-analysed. Four themes identified in the use of the Social Interaction Maps were (i) enhancing self-awareness of communication skills; (ii) promoting skills in being nonconfrontational during difficult interactions; (iii) highlighting the importance of A (Approach) and B (Bridging) in interaction with others; and (iv) awareness of how others interpret what is said C (Communicating) and discussing to resolve issues before closure D (Departing). Application of the EXCELLence in Cultural Experiential Learning and Leadership Social Interaction Mapping tool was shown to be useful in

The Effect of Semantic Mapping as a Vocabulary Instruction Technique on EFL Learners with Different Perceptual Learning Styles

Directory of Open Access Journals (Sweden)

Esmaeel Abdollahzadeh

2009-05-01

Full Text Available Traditional and modern vocabulary instruction techniques have been introduced in the past few decades to improve the learners’ performance in reading comprehension. Semantic mapping, which entails drawing learners’ attention to the interrelationships among lexical items through graphic organizers, is claimed to enhance vocabulary learning significantly. However, whether this technique suits all types of learners has not been adequately investigated. This study examines the effectiveness of employing semantic mapping versus traditional approaches in vocabulary instruction to EFL learners with different perceptual modalities. A modified version of Reid’s (1987 perceptual learning style questionnaire was used to determine the learners’ modality types. The results indicate that semantic mapping in comparison to the traditional approaches significantly enhances vocabulary learning of EFL learners. However, although visual learners slightly outperformed other types of learners on the post-test, no significant differences were observed among intermediate learners with different perceptual modalities employing semantic mapping for vocabulary practice.

On applications of chimera grid schemes to store separation

Science.gov (United States)

Cougherty, F. C.; Benek, J. A.; Steger, J. L.

1985-01-01

A finite difference scheme which uses multiple overset meshes to simulate the aerodynamics of aircraft/store interaction and store separation is described. In this chimera, or multiple mesh, scheme, a complex configuration is mapped using a major grid about the main component of the configuration, and minor overset meshes are used to map each additional component such as a store. As a first step in modeling the aerodynamics of store separation, two dimensional inviscid flow calculations were carried out in which one of the minor meshes is allowed to move with respect to the major grid. Solutions of calibrated two dimensional problems indicate that allowing one mesh to move with respect to another does not adversely affect the time accuracy of an unsteady solution. Steady, inviscid three dimensional computations demonstrate the capability to simulate complex configurations, including closely packed multiple bodies.

Spatiotemporal chaos in coupled logistic maps

International Nuclear Information System (INIS)

Varella Guedes, Andre; Amorim Savi, Marcelo

2010-01-01

The objective of this work is to investigate the spatiotemporal dynamics of coupled logistic maps. These maps are prototypes of high-dimensional dynamical systems and have been used to describe the evolution and pattern formation in different systems. Here, the logistic map lattice is coupled by a power law and, therefore, each map is influenced by other maps in its neighborhood. The Kolmogorov-Sinai entropy density is employed to quantify the complexity of system behavior, permitting a general qualitative understanding of different aspects of system dynamics. Three kinds of boundary conditions are treated and the influence of initial conditions is also of concern. Non-homogeneous maps are investigated, showing interesting aspects of spatiotemporal dynamics. The idea is to analyze the spatial interaction between two qualitative different types of behavior from a grid that is split into two parts. Numerical simulations show what types of conditions present a greater tendency to develop chaotic, periodic and synchronized responses. It should be highlighted that non-homogeneous grids have situations where a chaotic pattern can emerge from two periodic responses and also situations where a periodic pattern can emerge from chaos.

Retrieval Practice, with or without Mind Mapping, Boosts Fact Learning in Primary School Children

Science.gov (United States)

Ritchie, Stuart J.; Della Sala, Sergio; McIntosh, Robert D.

2013-01-01

Retrieval practice is a method of study in which testing is incorporated into the learning process. This method is known to facilitate recall for facts in adults and in secondary-school-age children, but existing studies in younger children are somewhat limited in their practical applicability. In two studies of primary school-age children of 8–12 years, we tested retrieval practice along with another study technique, mind mapping, which is more widely-used, but less well-evidenced. Children studied novel geographical facts, with or without retrieval practice and with or without mind mapping, in a crossed-factorial between-subjects design. In Experiment 1, children in the retrieval practice condition recalled significantly more facts four days later. In Experiment 2, this benefit was replicated at one and five weeks in a different, larger sample of schoolchildren. No consistent effects of mind mapping were observed. These results underline the effectiveness of retrieval practice for fact learning in young children. PMID:24265738

Multi-temporal Land Use Mapping of Coastal Wetlands Area using Machine Learning in Google Earth Engine

Science.gov (United States)

Farda, N. M.

2017-12-01

Coastal wetlands provide ecosystem services essential to people and the environment. Changes in coastal wetlands, especially on land use, are important to monitor by utilizing multi-temporal imagery. The Google Earth Engine (GEE) provides many machine learning algorithms (10 algorithms) that are very useful for extracting land use from imagery. The research objective is to explore machine learning in Google Earth Engine and its accuracy for multi-temporal land use mapping of coastal wetland area. Landsat 3 MSS (1978), Landsat 5 TM (1991), Landsat 7 ETM+ (2001), and Landsat 8 OLI (2014) images located in Segara Anakan lagoon are selected to represent multi temporal images. The input for machine learning are visible and near infrared bands, PCA band, invers PCA bands, bare soil index, vegetation index, wetness index, elevation from ASTER GDEM, and GLCM (Harralick) texture, and also polygon samples in 140 locations. There are 10 machine learning algorithms applied to extract coastal wetlands land use from Landsat imagery. The algorithms are Fast Naive Bayes, CART (Classification and Regression Tree), Random Forests, GMO Max Entropy, Perceptron (Multi Class Perceptron), Winnow, Voting SVM, Margin SVM, Pegasos (Primal Estimated sub-GrAdient SOlver for Svm), IKPamir (Intersection Kernel Passive Aggressive Method for Information Retrieval, SVM). Machine learning in Google Earth Engine are very helpful in multi-temporal land use mapping, the highest accuracy for land use mapping of coastal wetland is CART with 96.98 % Overall Accuracy using K-Fold Cross Validation (K = 10). GEE is particularly useful for multi-temporal land use mapping with ready used image and classification algorithms, and also very challenging for other applications.

Classification of fMRI resting-state maps using machine learning techniques: A comparative study

Science.gov (United States)

Gallos, Ioannis; Siettos, Constantinos

2017-11-01

We compare the efficiency of Principal Component Analysis (PCA) and nonlinear learning manifold algorithms (ISOMAP and Diffusion maps) for classifying brain maps between groups of schizophrenia patients and healthy from fMRI scans during a resting-state experiment. After a standard pre-processing pipeline, we applied spatial Independent component analysis (ICA) to reduce (a) noise and (b) spatial-temporal dimensionality of fMRI maps. On the cross-correlation matrix of the ICA components, we applied PCA, ISOMAP and Diffusion Maps to find an embedded low-dimensional space. Finally, support-vector-machines (SVM) and k-NN algorithms were used to evaluate the performance of the algorithms in classifying between the two groups.

Concurrent Cognitive Mapping and Localization Using Expectation Maximization

National Research Council Canada - National Science Library

Laviers, Kennard

2004-01-01

...) views the world as a series of connected spaces. These spaces are initially mapped as an occupancy grid in a room-by-room fashion using a modified version of the Histogram In Motion Mapping (HIMM...

Near-Body Grid Adaption for Overset Grids

Science.gov (United States)

Buning, Pieter G.; Pulliam, Thomas H.

2016-01-01

A solution adaption capability for curvilinear near-body grids has been implemented in the OVERFLOW overset grid computational fluid dynamics code. The approach follows closely that used for the Cartesian off-body grids, but inserts refined grids in the computational space of original near-body grids. Refined curvilinear grids are generated using parametric cubic interpolation, with one-sided biasing based on curvature and stretching ratio of the original grid. Sensor functions, grid marking, and solution interpolation tasks are implemented in the same fashion as for off-body grids. A goal-oriented procedure, based on largest error first, is included for controlling growth rate and maximum size of the adapted grid system. The adaption process is almost entirely parallelized using MPI, resulting in a capability suitable for viscous, moving body simulations. Two- and three-dimensional examples are presented.

Evaluating meaningful learning using concept mapping in dental hygiene education: a pilot study.

Science.gov (United States)

Canasi, Dina M; Amyot, Cynthia; Tira, Daniel

2014-02-01

Concept mapping, as a teaching strategy, has been shown to promote critical thinking and problem solving in educational settings. Dental clinicians must distinguish between critical and irrelevant characteristics in the delivery of care, thus necessitating reasoning skills to do so. One of the aims of the American Dental Education Association Commission on Change and Innovation (ADEA-CCI) is to identify deficiencies in curriculum which were meant to improve critical thinking and problem solving skills necessary in clinical practice. The purpose of this study was to compare 2 teaching strategies, traditional lecture and lecture supported by concept mapping exercises within collaborative working groups, to determine if there is a beneficial effect on meaningful learning. For this pilot study, the study population consisted of students from 2 geographically separated associate level dental hygiene programs in the southeastern U.S. A quasi-experimental control group pre- and post-test design was used. The degree of meaningful learning achieved by both programs was assessed by comparing pre- and post-test results. Both programs experienced a significant degree of meaningful learning from pre- to post-test. However, there was no statistically significant difference between the programs on the post-test. These results were in direct contrast to research in other disciplines on concept mapping and its effect on promoting meaningful learning. Further investigation into the study's outcome was obtained through a follow-up focus group. In spite of careful attention to methodology in the development of this research project, the focus group illuminated methodological failings that potentially impacted the outcome of the study. Recommendations are underscored for future conduct of educational research of this kind.

Effectiveness of mind mapping as a learning tool among dental students

Directory of Open Access Journals (Sweden)

Mohnish Muchhal

2018-01-01

Full Text Available Introduction: The foremost goal of our education system is to develop the students' skills to reach information rather than transferring the present information. Instead of understanding and applying the concepts (meaningful learning, students used to memorize the facts. Therefore, long-term independent learning process is required for the students. Aim: This study aims to evaluate the effectiveness of mind mapping as a learning tool and to assess its information retrieval potential among dental students over conventional system of learning. Materials and Methods: An interventional study was conducted among 90 students of BDS 3rd year students. A questionnaire consisting of questions related to oral hygiene index (OHI and OHI-simplified (OHI-S was distributed to them. Data were analyzed using Statistical Package for Social Sciences (SPSS 18.0 (SPSS Inc., Chicago, IL, USA and descriptive and analytical tests including mean, standard deviation, and Chi-square test. Results: Of the 90 students, only 82 students responded to the questionnaire generating a response rate of 89.5%. The mean score of students in the mind map (MM group was significantly higher than the conventional group (posttest – 13.60 ± 0.99 vs 8.73 ± 2.13, P = 0.001. Gain in knowledge score was 7.74 vs. 3.43; statistically significant difference was found between the two groups for the gain in knowledge score as well as in mean percentage gain in knowledge score. Conclusion: Specific and prudent thinking with self-efficacy should be the purpose of education system rather than making the students literate only. This requires shifting of traditional teaching method with innovative method, and MM is one of the innovative as well as attractive processes of teaching which further help the students to learn the subject more effectively in a creative way.

Machine-learning classifiers applied to habitat and geological substrate mapping offshore South Carolina

Science.gov (United States)

White, S. M.; Maschmeyer, C.; Anderson, E.; Knapp, C. C.; Brantley, D.

2017-12-01

classification as the classifier confused flat parts with relatively flat sand data. 100% of testing data representing rocky portions of the seafloor were correctly classified. The use of machine-learning classifiers to determine seafloor-type provides a new solution to habitat mapping and offshore engineering problems.

Grid generation method to calculate the flow field in a three-dimensional cascade of blades. Sanjigen yokuretsu nagare keisan no tame no koshi keisei

Energy Technology Data Exchange (ETDEWEB)

Inoue, K [National Aerospace Laboratory, Tokyo (Japan)

1992-05-01

For the purpose of developing a fan for an engine with ultra-high by-pass ratio, the design code of three-dimensional cascade of blades based on the Navier-Stokes equation has already been developed. This paper describes a method created by calculation grids which are part of this design code. This method is to generate boundary fitted grids to calculate the flow field across a cascade of blades placed radially in the axially symmetric space between hub and casing. In this method, one-period domain of the cascade of blades is mapped on a box in computational space by a series of combined streching transformation and conformal mapping. The grid in physical space is then obtained by successive inverse conformal mapping on the grid points in computational space. The grid obtained in this method is H-type and has a periodicity which includes the inclination of grid lines at the periodic boundary. As an example of the grid generated by this method, grids for primary and secondary models of the fan with ultra-high by-pass ratio are shown. 6 refs., 12 figs.

Grid generation method to calculate the flow field in a three-dimensional cascade of blades; Sanjigen yokuretsu nagare keisan no tame no koshi keisei

Energy Technology Data Exchange (ETDEWEB)

Inoue, K [National Aerospace Laboratory, Tokyo (Japan)

1992-05-01

For the purpose of developing a fan for an engine with ultra-high by-pass ratio, the design code of three-dimensional cascade of blades based on the Navier-Stokes equation has already been developed. This paper describes a method created by calculation grids which are part of this design code. This method is to generate boundary fitted grids to calculate the flow field across a cascade of blades placed radially in the axially symmetric space between hub and casing. In this method, one-period domain of the cascade of blades is mapped on a box in computational space by a series of combined streching transformation and conformal mapping. The grid in physical space is then obtained by successive inverse conformal mapping on the grid points in computational space. The grid obtained in this method is H-type and has a periodicity which includes the inclination of grid lines at the periodic boundary. As an example of the grid generated by this method, grids for primary and secondary models of the fan with ultra-high by-pass ratio are shown. 6 refs., 12 figs.

Brain-wide maps of Fos expression during fear learning and recall.

Science.gov (United States)

Cho, Jin-Hyung; Rendall, Sam D; Gray, Jesse M

2017-04-01

Fos induction during learning labels neuronal ensembles in the hippocampus that encode a specific physical environment, revealing a memory trace. In the cortex and other regions, the extent to which Fos induction during learning reveals specific sensory representations is unknown. Here we generate high-quality brain-wide maps of Fos mRNA expression during auditory fear conditioning and recall in the setting of the home cage. These maps reveal a brain-wide pattern of Fos induction that is remarkably similar among fear conditioning, shock-only, tone-only, and fear recall conditions, casting doubt on the idea that Fos reveals auditory-specific sensory representations. Indeed, novel auditory tones lead to as much gene induction in visual as in auditory cortex, while familiar (nonconditioned) tones do not appreciably induce Fos anywhere in the brain. Fos expression levels do not correlate with physical activity, suggesting that they are not determined by behavioral activity-driven alterations in sensory experience. In the thalamus, Fos is induced more prominently in limbic than in sensory relay nuclei, suggesting that Fos may be most sensitive to emotional state. Thus, our data suggest that Fos expression during simple associative learning labels ensembles activated generally by arousal rather than specifically by a particular sensory cue. © 2017 Cho et al.; Published by Cold Spring Harbor Laboratory Press.

The MammoGrid Project Grids Architecture

CERN Document Server

McClatchey, Richard; Hauer, Tamas; Estrella, Florida; Saiz, Pablo; Rogulin, Dmitri; Buncic, Predrag; Clatchey, Richard Mc; Buncic, Predrag; Manset, David; Hauer, Tamas; Estrella, Florida; Saiz, Pablo; Rogulin, Dmitri

2003-01-01

The aim of the recently EU-funded MammoGrid project is, in the light of emerging Grid technology, to develop a European-wide database of mammograms that will be used to develop a set of important healthcare applications and investigate the potential of this Grid to support effective co-working between healthcare professionals throughout the EU. The MammoGrid consortium intends to use a Grid model to enable distributed computing that spans national borders. This Grid infrastructure will be used for deploying novel algorithms as software directly developed or enhanced within the project. Using the MammoGrid clinicians will be able to harness the use of massive amounts of medical image data to perform epidemiological studies, advanced image processing, radiographic education and ultimately, tele-diagnosis over communities of medical "virtual organisations". This is achieved through the use of Grid-compliant services [1] for managing (versions of) massively distributed files of mammograms, for handling the distri...

Conservative Initial Mapping For Multidimensional Simulations of Stellar Explosions

International Nuclear Information System (INIS)

Chen, Ke-Jung; Heger, Alexander; Almgren, Ann

2012-01-01

Mapping one-dimensional stellar profiles onto multidimensional grids as initial conditions for hydrodynamics calculations can lead to numerical artifacts, one of the most severe of which is the violation of conservation laws for physical quantities such as energy and mass. Here we introduce a numerical scheme for mapping one-dimensional spherically-symmetric data onto multidimensional meshes so that these physical quantities are conserved. We validate our scheme by porting a realistic 1D Lagrangian stellar profile to the new multidimensional Eulerian hydro code CASTRO. Our results show that all important features in the profiles are reproduced on the new grid and that conservation laws are enforced at all resolutions after mapping.

Software, component, and service deployment in computational Grids

International Nuclear Information System (INIS)

von Laszewski, G.; Blau, E.; Bletzinger, M.; Gawor, J.; Lane, P.; Martin, S.; Russell, M.

2002-01-01

Grids comprise an infrastructure that enables scientists to use a diverse set of distributed remote services and resources as part of complex scientific problem-solving processes. We analyze some of the challenges involved in deploying software and components transparently in Grids. We report on three practical solutions used by the Globus Project. Lessons learned from this experience lead us to believe that it is necessary to support a variety of software and component deployment strategies. These strategies are based on the hosting environment

Multisensor On-The-Go Mapping of Soil Organic Carbon Content

DEFF Research Database (Denmark)

Knadel, Maria; Thomsen, Anton Gårde; Greve, Mogens Humlekrog

2011-01-01

resulted in values as follows: root mean square error of prediction = 5.94; R2 = 0.84; and ratio of standard error of prediction to SD [RPD] = 2.3. This study showed that the quality of those maps can be improved and spatial sampling intensities can be reduced by incorporating auxiliary data as a source...... mapping SOC using a mobile sensor platform (MSP) and conventional grid sampling on a highly variable agricultural field in Denmark. Sixty-four samples collected on a 25-m grid were used to generate a reference map of SOC distribution using kriging. Mobile sensory data (visible–near infrared spectra...

Using Mind Maps to Make Student Questioning Effective: Learning Outcomes of a Principle-Based Scenario for Teacher Guidance

Science.gov (United States)

Stokhof, Harry; de Vries, Bregje; Bastiaens, Theo; Martens, Rob

2018-01-01

Student questioning is an important learning strategy, but rare in many classrooms, because teachers have concerns if these questions contribute to attaining curricular objectives. Teachers face the challenge of making student questioning effective for learning the curriculum. To address this challenge, a principle-based scenario for guiding effective student questioning was developed and tested for its relevance and practicality in two previous studies. In the scenario, which consists of a sequence of pedagogical activities, mind maps support teachers and students to explore and elaborate upon a core curriculum, by raising, investigating, and exchanging student questions. In this paper, a follow-up study is presented that tested the effectiveness of the scenario on student outcomes in terms of attainment of curricular objectives. Ten teachers and their 231 students participated in the study. Pre- and posttest mind maps were used to measure individual and collective learning outcomes of student questioning. Findings show that a majority of students progressed in learning the core curriculum and elaborated upon it. The findings suggest that visualizing knowledge construction in a shared mind map supports students to learn a core curriculum and to refine their knowledge structures.

Smart electric vehicle (EV) charging and grid integration apparatus and methods

Science.gov (United States)

Gadh, Rajit; Mal, Siddhartha; Prabhu, Shivanand; Chu, Chi-Cheng; Sheikh, Omar; Chung, Ching-Yen; He, Lei; Xiao, Bingjun; Shi, Yiyu

2015-05-05

An expert system manages a power grid wherein charging stations are connected to the power grid, with electric vehicles connected to the charging stations, whereby the expert system selectively backfills power from connected electric vehicles to the power grid through a grid tie inverter (if present) within the charging stations. In more traditional usage, the expert system allows for electric vehicle charging, coupled with user preferences as to charge time, charge cost, and charging station capabilities, without exceeding the power grid capacity at any point. A robust yet accurate state of charge (SOC) calculation method is also presented, whereby initially an open circuit voltage (OCV) based on sampled battery voltages and currents is calculated, and then the SOC is obtained based on a mapping between a previously measured reference OCV (ROCV) and SOC. The OCV-SOC calculation method accommodates likely any battery type with any current profile.

A Data Colocation Grid Framework for Big Data Medical Image Processing: Backend Design

Science.gov (United States)

Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J.; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A.

2018-01-01

When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework’s performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop & HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative

Using concept mapping to measure changes in interdisciplinary learning during high school

Directory of Open Access Journals (Sweden)

Priit Reiska

2018-03-01

Full Text Available How, when and what kind of learning takes place are key questions in all educational environments. School graduates are expected to have reached a development level whereby they have, among many fundamental skills, the ability to think critically, to plan their studies and their future, and to integrate knowledge across disciplines. However, it is challenging to develop these skills in schools. Following existing curricula, disciplines are often taught separately and by different teachers, making it difficult for students to connect knowledge studied and learned from one discipline to that of another discipline. The Next Generation Science Standards on teaching and learning natural science in the United States point out important crosscutting concepts in science education (NGSS, 2013. In Estonia, similar trends are leading to an emphasis on the need to further develop scientific literacy skills and interdisciplinary learning in students. The changing environment around us must be reflected in changes in our school system. In this paper, we report on research that intends to answer the questions: (a “How much do Estonian students develop an interdisciplinary understanding of science throughout their high school education?”, and (b “Is their thinking more interdisciplinary after two years of studies in an Estonian high school?” Additionally, we analyzed the results based on the type of school the students attended, and we examined the use concept mapping to assess interdisciplinary learning. This research is part of an overall study that involved students from 44 Estonian high schools taking a science test similar to the three-dimensional Programme for International Student Assessment (PISA test (hereafter called PISA-like multidimensional test as well as constructing concept maps, while in 10th and 12th grade. In this paper, we report on the analysis of the results for 182 of the students, concentrating on the analysis of the concept maps

Modeling and Mapping Personal Learning Environment of Thai International Higher Education Students

Science.gov (United States)

Sharafuddin, Mohamed Ali; Sawad, Buncha Panacharoen; Wongwai, Sarun

2018-01-01

This research article is part of a periodic study conducted to understand, model, map and to develop an integrated approach for effective and interactive self-learning phases of Thai International Hospitality and Tourism higher education students. Questionnaire containing both qualitative and quantitative questions was distributed at the beginning…

Structured feedback on students' concept maps: the proverbial path to learning?

Science.gov (United States)

Joseph, Conran; Conradsson, David; Nilsson Wikmar, Lena; Rowe, Michael

2017-05-25

Good conceptual knowledge is an essential requirement for health professions students, in that they are required to apply concepts learned in the classroom to a variety of different contexts. However, the use of traditional methods of assessment limits the educator's ability to correct students' conceptual knowledge prior to altering the educational context. Concept mapping (CM) is an educational tool for evaluating conceptual knowledge, but little is known about its use in facilitating the development of richer knowledge frameworks. In addition, structured feedback has the potential to develop good conceptual knowledge. The purpose of this study was to use Kinchin's criteria to assess the impact of structured feedback on the graphical complexity of CM's by observing the development of richer knowledge frameworks. Fifty-eight physiotherapy students created CM's targeting the integration of two knowledge domains within a case-based teaching paradigm. Each student received one round of structured feedback that addressed correction, reinforcement, forensic diagnosis, benchmarking, and longitudinal development on their CM's prior to the final submission. The concept maps were categorized according to Kinchin's criteria as either Spoke, Chain or Net representations, and then evaluated against defined traits of meaningful learning. The inter-rater reliability of categorizing CM's was good. Pre-feedback CM's were predominantly Chain structures (57%), with Net structures appearing least often. There was a significant reduction of the basic Spoke- structured CMs (P = 0.002) and a significant increase of Net-structured maps (P student development.

USGS US Topo Map Collection

Data.gov (United States)

U.S. Geological Survey, Department of the Interior — Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other...

Sharing lessons learned on developing and operating smart grid pilots with households

NARCIS (Netherlands)

Kobus, C.B.A.; Klaassen, E.A.M.; Kohlmann, J.; Knigge, J.D.; Boots, S.

2013-01-01

Today, technology is still leading Smart Grid development. Nevertheless, the awareness that it should be a multidisciplinary effort to foster public acceptance and even desirability of Smart Grids is increasing. This paper illustrates the added value of a multidisciplinary approach by sharing the

Implementation of grid-connected to/from off-grid transference for micro-grid inverters

OpenAIRE

Heredero Peris, Daniel; Chillón Antón, Cristian; Pages Gimenez, Marc; Gross, Gabriel Igor; Montesinos Miracle, Daniel

2013-01-01

This paper presents the transfer of a microgrid converter from/to on-grid to/from off-grid when the converter is working in two different modes. In the first transfer presented method, the converter operates as a Current Source Inverter (CSI) when on-grid and as a Voltage Source Inverter (VSI) when off-grid. In the second transfer method, the converter is operated as a VSI both, when operated on-grid and off-grid. The two methods are implemented successfully in a real pla...

Kids at CERN Grids for Kids programme leads to advanced computing knowledge.

CERN Multimedia

2008-01-01

Children as young as 10 are learning computing skills, such as middleware, parallel processing and supercomputing, at CERN, the European Organisation for Nuclear Research, last week. The initiative for 10 to 12 years olds is part of the Grids for Kids programme, which aims to introduce Grid computing as a tool for research.

Mapping 1995 global anthropogenic emissions of mercury

NARCIS (Netherlands)

Pacyna, Jozef M.; Pacyna, Elisabeth G.; Steenhuisen, Frits; Wilson, Simon

2003-01-01

This paper presents maps of anthropogenic Hg emissions worldwide within a 1degrees x 1degrees latitude/longitude grid system in 1995. As such, the paper is designed for modelers simulating the Hg transport within air masses and Hg deposition to aquatic and terrestrial ecosystems. Maps of total Hg

Capturing the Integration of Practice-Based Learning with Beliefs, Values, and Attitudes using Modified Concept Mapping.

Science.gov (United States)

Mcnaughton, Susan; Barrow, Mark; Bagg, Warwick; Frielick, Stanley

2016-01-01

Practice-based learning integrates the cognitive, psychomotor, and affective domains and is influenced by students' beliefs, values, and attitudes. Concept mapping has been shown to effectively demonstrate students' changing concepts and knowledge structures. This article discusses how concept mapping was modified to capture students' perceptions of the connections between the domains of thinking and knowing, emotions, behavior, attitudes, values, and beliefs and the specific experiences related to these, over a period of eight months of practice-based clinical learning. The findings demonstrate that while some limitations exist, modified concept mapping is a manageable way to gather rich data about students' perceptions of their clinical practice experiences. These findings also highlight the strong integrating influence of beliefs and values on other areas of practice, suggesting that these need to be attended to as part of a student's educational program.

Acquiring concepts and features of novel words by two types of learning: direct mapping and inference.

Science.gov (United States)

Chen, Shuang; Wang, Lin; Yang, Yufang

2014-04-01

This study examined the semantic representation of novel words learnt in two conditions: directly mapping a novel word to a concept (Direct mapping: DM) and inferring the concept from provided features (Inferred learning: IF). A condition where no definite concept could be inferred (No basic-level meaning: NM) served as a baseline. The semantic representation of the novel word was assessed via a semantic-relatedness judgment task. In this task, the learned novel word served as a prime, while the corresponding concept, an unlearned feature of the concept, and an unrelated word served as targets. ERP responses to the targets, primed by the novel words in the three learning conditions, were compared. For the corresponding concept, smaller N400s were elicited in the DM and IF conditions than in the NM condition, indicating that the concept could be obtained in both learning conditions. However, for the unlearned feature, the targets in the IF condition produced an N400 effect while in the DM condition elicited an LPC effect relative to the NM learning condition. No ERP difference was observed among the three learning conditions for the unrelated words. The results indicate that conditions of learning affect the semantic representation of novel word, and that the unlearned feature was only activated by the novel word in the IF learning condition. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mapping filmmaking

DEFF Research Database (Denmark)

Gilje, Øystein; Frølunde, Lisbeth; Lindstrand, Fredrik

2010-01-01

This chapter concerns mapping patterns in regards to how young filmmakers (age 15 – 20) in the Scandinavian countries learn about filmmaking. To uncover the patterns, we present portraits of four young filmmakers who participated in the Scandinavian research project Making a filmmaker. The focus ...... is on their learning practices and how they create ‘learning paths’ in relation to resources in diverse learning contexts, whether formal, non-formal and informal contexts.......This chapter concerns mapping patterns in regards to how young filmmakers (age 15 – 20) in the Scandinavian countries learn about filmmaking. To uncover the patterns, we present portraits of four young filmmakers who participated in the Scandinavian research project Making a filmmaker. The focus...

Flipped Learning, MOOCs and Learning Analytics: Lessons learnt from a Web Map Design course redesign

Science.gov (United States)

Treves, R.

2013-12-01

Five weeks content of a 12 week course in web map design were converted to 'flipped learning': Lecture sessions were replaced by online short video lectures and multiple choice questions to be completed outside class. Class time was taken up with activities and exercises linked to the online learning. Students use of the online content was carefully tracked and detailed student feedback gathered. The response from students was good, 90% of them completed all the out of class activities and their feedback was very positive. The format has the advantage of being easily repurposed as a MOOC or scaled up in other ways. Lessons learnt from the implementation of the materials and the analysis of the VLE logs will be discussed as will ongoing efforts to reuse the materials in a MOOC.

Memfasilitasi Penalaran Geometri Transformasi Siswa Melalui Eksplorasi Motif Melayu dengan Bantuan Grid

Directory of Open Access Journals (Sweden)

Febrian Febrian

2017-10-01

Full Text Available Geometri transformasi merupakan pengetahuan yang krusial dalam geometri yang dapat membangun banyak kemampuan lainnya seperti penalaran matematis. Oleh karena itu, geometri transformasi disarankan untuk diberikan pada pebelajar mulai dari usia dini. Penelitian terdahulu menunjukkan bahwa anak-anak memiliki sense untuk melihat karakteristik kedinamisan pada benda, oleh karena itu memfasilitasi pembelajaran yang dapat memanfaatkan sense ini menjadi sangat penting untuk membangun pemahaman geometri transformasi. Penelitian design research ini bertujuan untuk memfasilitasi siswa sekolah dasar untuk dapat mengembangkan pengetahuan awal mereka mengenai komposisi transformasi. Subjek penelitian adalah siswa kelas IV Sekolah Dasar Negeri 001 Toapaya, Kabupaten Bintan, Kepulauan Riau. Pendekatan pembelajaran yang digunakan adalah PMRI dengan konteks motif melayu itik pulang petang dengan bantuan grid. Hasil menunjukkan bahwa setting pembelajaran dapat memfasilitasi penalaran geometri transformasi melalui kegiatan eksplorasi motif dengan bantuan grid. Kata Kunci: komposisi transformasi, penalaran, motif melayu, grid, PMRI Transformation geometry is a crucial knowledge in geometry that can emerge many skills especially mathematical reasoning. Therefore, transformation geometry is suggested to be taught to children especially the young learners. Existing research implies that children have particular sense to see dynamic characteristic of an object or others. On the behalf of this statement, facilitating students in learning process that makes use of this students sense becomes important to undertake to help develop students reasoning of transformation geometry. The subtopic being highlighted is the composition of transformation. This design research aims to facilitate this situation. The subject of the research is fourth graders of the State Elementary School of 001 at Toapaya, Kabupaten Bintan, Kepulauan Riau. The learning approach used was PMRI by using

Concept maps: A tool for knowledge management and synthesis in web-based conversational learning.

Science.gov (United States)

Joshi, Ankur; Singh, Satendra; Jaswal, Shivani; Badyal, Dinesh Kumar; Singh, Tejinder

2016-01-01

Web-based conversational learning provides an opportunity for shared knowledge base creation through collaboration and collective wisdom extraction. Usually, the amount of generated information in such forums is very huge, multidimensional (in alignment with the desirable preconditions for constructivist knowledge creation), and sometimes, the nature of expected new information may not be anticipated in advance. Thus, concept maps (crafted from constructed data) as "process summary" tools may be a solution to improve critical thinking and learning by making connections between the facts or knowledge shared by the participants during online discussion This exploratory paper begins with the description of this innovation tried on a web-based interacting platform (email list management software), FAIMER-Listserv, and generated qualitative evidence through peer-feedback. This process description is further supported by a theoretical construct which shows how social constructivism (inclusive of autonomy and complexity) affects the conversational learning. The paper rationalizes the use of concept map as mid-summary tool for extracting information and further sense making out of this apparent intricacy.

A Novel Transfer Learning Method Based on Common Space Mapping and Weighted Domain Matching

KAUST Repository

Liang, Ru-Ze; Xie, Wei; Li, Weizhi; Wang, Hongqi; Wang, Jim Jing-Yan; Taylor, Lisa

2017-01-01

In this paper, we propose a novel learning framework for the problem of domain transfer learning. We map the data of two domains to one single common space, and learn a classifier in this common space. Then we adapt the common classifier to the two domains by adding two adaptive functions to it respectively. In the common space, the target domain data points are weighted and matched to the target domain in term of distributions. The weighting terms of source domain data points and the target domain classification responses are also regularized by the local reconstruction coefficients. The novel transfer learning framework is evaluated over some benchmark cross-domain data sets, and it outperforms the existing state-of-the-art transfer learning methods.

A Novel Transfer Learning Method Based on Common Space Mapping and Weighted Domain Matching

KAUST Repository

Liang, Ru-Ze

2017-01-17

In this paper, we propose a novel learning framework for the problem of domain transfer learning. We map the data of two domains to one single common space, and learn a classifier in this common space. Then we adapt the common classifier to the two domains by adding two adaptive functions to it respectively. In the common space, the target domain data points are weighted and matched to the target domain in term of distributions. The weighting terms of source domain data points and the target domain classification responses are also regularized by the local reconstruction coefficients. The novel transfer learning framework is evaluated over some benchmark cross-domain data sets, and it outperforms the existing state-of-the-art transfer learning methods.

GridCom, Grid Commander: graphical interface for Grid jobs and data management

International Nuclear Information System (INIS)

Galaktionov, V.V.

2011-01-01

GridCom - the software package for maintenance of automation of access to means of distributed system Grid (jobs and data). The client part, executed in the form of Java-applets, realises the Web-interface access to Grid through standard browsers. The executive part Lexor (LCG Executor) is started by the user in UI (User Interface) machine providing performance of Grid operations

Landslide Susceptibility Mapping Using GIS-based Vector Grid File (VGF Validating with InSAR Techniques: Three Gorges, Yangtze River (China

Directory of Open Access Journals (Sweden)

Cem Kıncal

2017-04-01

Full Text Available A landslide susceptibility assessment for the Three Gorges (TG region (China was performed in a Geographical Information System (GIS environment and Persistent Scatterer (PS InSAR derived displacements were used for validation purposes. Badong County of TG was chosen as case study field. Landslide parameters were derived from two datasets. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER Global Digital Elevation Map (GDEM was used to calculate slope geometry parameters (slope, aspect, drainage, and lineament, while geology and vegetation cover were obtained from Landsat and ASTER data. The majority of historical landslides occurred in the sandstone-shale-claystone intercalations. It appears that slope gradients are more critical than other parameters such as aspect and drainage. The susceptibility assessment was based on a summation of assigned susceptibility scores (points for each 30×30 m unit in a database of a Vector Grid File (VGF composed of ‘vector pixels’. A landslide susceptibility map (LSM was generated using VGF and classified with low, moderate and high landslide susceptibility zones. The comparison between the LSM and PS InSAR derived displacements suggests that landslides only account for parts of the observed surface movements.

Systems and methods that generate height map models for efficient three dimensional reconstruction from depth information

Science.gov (United States)

Frahm, Jan-Michael; Pollefeys, Marc Andre Leon; Gallup, David Robert

2015-12-08

Methods of generating a three dimensional representation of an object in a reference plane from a depth map including distances from a reference point to pixels in an image of the object taken from a reference point. Weights are assigned to respective voxels in a three dimensional grid along rays extending from the reference point through the pixels in the image based on the distances in the depth map from the reference point to the respective pixels, and a height map including an array of height values in the reference plane is formed based on the assigned weights. An n-layer height map may be constructed by generating a probabilistic occupancy grid for the voxels and forming an n-dimensional height map comprising an array of layer height values in the reference plane based on the probabilistic occupancy grid.

Energy management of internet data centers in smart grid

CERN Document Server

Jiang, Tao; Cao, Yang

2015-01-01

This book reports the latest findings on intelligent energy management of Internet data centers in smart-grid environments. The book gathers novel research ideas in Internet data center energy management, especially scenarios with cyber-related vulnerabilities, power outages and carbon emission constraints. The book will be of interest to university researchers, R&D engineers and graduate students in communication and networking areas who wish to learn the core principles, methods, algorithms, and applications of energy management of Internet data centers in smart grids.

Mapping Trends in Pedagogical Approaches and Learning Technologies: Perspectives from the Canadian, International, and Military Education Contexts

Science.gov (United States)

Scoppio, Grazia; Covell, Leigha

2016-01-01

Increased technological advances, coupled with new learners' needs, have created new realities for higher education contexts. This study explored and mapped trends in pedagogical approaches and learning technologies in postsecondary education and identified how these innovations are affecting teaching and learning practices in higher education…

An adaptive multi-agent-based approach to smart grids control and optimization

Energy Technology Data Exchange (ETDEWEB)

Carvalho, Marco [Florida Institute of Technology, Melbourne, FL (United States); Perez, Carlos; Granados, Adrian [Institute for Human and Machine Cognition, Ocala, FL (United States)

2012-03-15

In this paper, we describe a reinforcement learning-based approach to power management in smart grids. The scenarios we consider are smart grid settings where renewable power sources (e.g. Photovoltaic panels) have unpredictable variations in power output due, for example, to weather or cloud transient effects. Our approach builds on a multi-agent system (MAS)-based infrastructure for the monitoring and coordination of smart grid environments with renewable power sources and configurable energy storage devices (battery banks). Software agents are responsible for tracking and reporting power flow variations at different points in the grid, and to optimally coordinate the engagement of battery banks (i.e. charge/idle/discharge modes) to maintain energy requirements to end-users. Agents are able to share information and coordinate control actions through a parallel communications infrastructure, and are also capable of learning, from experience, how to improve their response strategies for different operational conditions. In this paper we describe our approach and address some of the challenges associated with the communications infrastructure for distributed coordination. We also present some preliminary results of our first simulations using the GridLAB-D simulation environment, created by the US Department of Energy (DoE) at Pacific Northwest National Laboratory (PNNL). (orig.)

Cognitive Radio for Smart Grid: Theory, Algorithms, and Security

Directory of Open Access Journals (Sweden)

Raghuram Ranganathan

2011-01-01

Full Text Available Recently, cognitive radio and smart grid are two areas which have received considerable research impetus. Cognitive radios are intelligent software defined radios (SDRs that efficiently utilize the unused regions of the spectrum, to achieve higher data rates. The smart grid is an automated electric power system that monitors and controls grid activities. In this paper, the novel concept of incorporating a cognitive radio network as the communications infrastructure for the smart grid is presented. A brief overview of the cognitive radio, IEEE 802.22 standard and smart grid, is provided. Experimental results obtained by using dimensionality reduction techniques such as principal component analysis (PCA, kernel PCA, and landmark maximum variance unfolding (LMVU on Wi-Fi signal measurements are presented in a spectrum sensing context. Furthermore, compressed sensing algorithms such as Bayesian compressed sensing and the compressed sensing Kalman filter is employed for recovering the sparse smart meter transmissions. From the power system point of view, a supervised learning method called support vector machine (SVM is used for the automated classification of power system disturbances. The impending problem of securing the smart grid is also addressed, in addition to the possibility of applying FPGA-based fuzzy logic intrusion detection for the smart grid.

A scalable hybrid multi-robot SLAM method for highly detailed maps

NARCIS (Netherlands)

Pfingsthorn, M.; Slamet, B.; Visser, A.

2008-01-01

Recent successful SLAM methods employ hybrid map representations combining the strengths of topological maps and occupancy grids. Such representations often facilitate multi-agent mapping. In this paper, a successful SLAM method is presented, which is inspired by the manifold data structure by

Enabling Campus Grids with Open Science Grid Technology

International Nuclear Information System (INIS)

Weitzel, Derek; Fraser, Dan; Pordes, Ruth; Bockelman, Brian; Swanson, David

2011-01-01

The Open Science Grid is a recognized key component of the US national cyber-infrastructure enabling scientific discovery through advanced high throughput computing. The principles and techniques that underlie the Open Science Grid can also be applied to Campus Grids since many of the requirements are the same, even if the implementation technologies differ. We find five requirements for a campus grid: trust relationships, job submission, resource independence, accounting, and data management. The Holland Computing Center's campus grid at the University of Nebraska-Lincoln was designed to fulfill the requirements of a campus grid. A bridging daemon was designed to bring non-Condor clusters into a grid managed by Condor. Condor features which make it possible to bridge Condor sites into a multi-campus grid have been exploited at the Holland Computing Center as well.

Challenges and weaknesses in the use of concept maps as a learning strategy in undergraduate health programs

Directory of Open Access Journals (Sweden)

Enios Carlos Duarte

2017-09-01

Full Text Available This paper considers the analysis of concept maps utilized as a learning tool in disciplines dealing with immunological responses in two undergraduate Health programs. In total, 48 concept maps were assessed regarding their propositions and structure. The clarity of the propositions was analyzed by using the Propositional Clarity Table and they were classified as adequate propositions (AP and inadequate propositions (IP. In 48 concept maps, 648 propositions were analyzed in order to determine semantic clarity and conceptual mistakes. Assessments revealed that 69 % of the propositions were classified as adequate and 31 % as inadequate. All the maps analyzed were categorized as showing a network structure. However, when correlating the connections established among the several types of response by the immune system, it was found that despite being structured as a network, only 31.2 % of the concept maps indicated conceptual relationships between the modes of immune response. 27% of the concept maps were made with a high rate of proficiency. Upon the results of our analysis, we realized that there is still a long way in developing the mapping strategy. For us, this low percentage is related to the way undergraduates assimilate the mapping processes. This is a challenge which also reveals limits and weaknesses that may be addressed in future studies. It was noted that results bring into focus that the undergraduates’ learning of concepts associated with the bases of the immunological responses occurred in a meaningful way.

Acid Deposition Maps in Spain

International Nuclear Information System (INIS)

Artinano, B.; Cabal, H.; Garcia, C.

1998-01-01

Animal and monthly deposition velocity and total sulfur deposition maps have been performed for the peninsular Spain for 1992 by using the inferential method. To do this, updated databases with high space and time resolution, for land uses (CORINE) and meteorological information from analysis modelling for the same year, have been utilized. The final result are deposition maps in a 5x5 Km 2 grid which allow to assess the methodology used in Europe to obtain the maps of excedances over the critical loads of pollutants. (Author) 32 refs

Grid for Meso american Archaeology

International Nuclear Information System (INIS)

Lucet, G.

2007-01-01

Meso american archaeology works with large amounts of disperse and diverse information, thus the importance of including new methods that optimise the acquisition, conservation, retrieval, and analysis of data to generate knowledge more efficiently and create a better understanding of history. Further, this information --which includes texts, coordinates, raster graphs, and vector graphs-- comes from a considerable geographical area --parts of Mexico, Nicaragua, Honduras and Costa Rica as well as Guatemala, El Salvador and Belize-- is constantly expanding. This information includes elements like shards, buildings, mural paintings, high and low reliefs, topography, maps, and information about the fauna and soil. Grid computing offers a solution to handle all this information: it respects researchers' need for independence while supplying a platform to share, process and compare the data obtained. Additionally, the Grid can enhance space-time analyses with remote visualisation techniques that can, in turn, incorporate geographical information systems and virtual reality. (Author)

Assessment of grid optimisation measures for the German transmission grid using open source grid data

Science.gov (United States)

Böing, F.; Murmann, A.; Pellinger, C.; Bruckmeier, A.; Kern, T.; Mongin, T.

2018-02-01

The expansion of capacities in the German transmission grid is a necessity for further integration of renewable energy sources into the electricity sector. In this paper, the grid optimisation measures ‘Overhead Line Monitoring’, ‘Power-to-Heat’ and ‘Demand Response in the Industry’ are evaluated and compared against conventional grid expansion for the year 2030. Initially, the methodical approach of the simulation model is presented and detailed descriptions of the grid model and the used grid data, which partly originates from open-source platforms, are provided. Further, this paper explains how ‘Curtailment’ and ‘Redispatch’ can be reduced by implementing grid optimisation measures and how the depreciation of economic costs can be determined considering construction costs. The developed simulations show that the conventional grid expansion is more efficient and implies more grid relieving effects than the evaluated grid optimisation measures.

GRID-BASED EXPLORATION OF COSMOLOGICAL PARAMETER SPACE WITH SNAKE

International Nuclear Information System (INIS)

Mikkelsen, K.; Næss, S. K.; Eriksen, H. K.

2013-01-01

We present a fully parallelized grid-based parameter estimation algorithm for investigating multidimensional likelihoods called Snake, and apply it to cosmological parameter estimation. The basic idea is to map out the likelihood grid-cell by grid-cell according to decreasing likelihood, and stop when a certain threshold has been reached. This approach improves vastly on the 'curse of dimensionality' problem plaguing standard grid-based parameter estimation simply by disregarding grid cells with negligible likelihood. The main advantages of this method compared to standard Metropolis-Hastings Markov Chain Monte Carlo methods include (1) trivial extraction of arbitrary conditional distributions; (2) direct access to Bayesian evidences; (3) better sampling of the tails of the distribution; and (4) nearly perfect parallelization scaling. The main disadvantage is, as in the case of brute-force grid-based evaluation, a dependency on the number of parameters, N par . One of the main goals of the present paper is to determine how large N par can be, while still maintaining reasonable computational efficiency; we find that N par = 12 is well within the capabilities of the method. The performance of the code is tested by comparing cosmological parameters estimated using Snake and the WMAP-7 data with those obtained using CosmoMC, the current standard code in the field. We find fully consistent results, with similar computational expenses, but shorter wall time due to the perfect parallelization scheme

An Informatics Approach to Demand Response Optimization in Smart Grids

Energy Technology Data Exchange (ETDEWEB)

Simmhan, Yogesh; Aman, Saima; Cao, Baohua; Giakkoupis, Mike; Kumbhare, Alok; Zhou, Qunzhi; Paul, Donald; Fern, Carol; Sharma, Aditya; Prasanna, Viktor K

2011-03-03

Power utilities are increasingly rolling out “smart” grids with the ability to track consumer power usage in near real-time using smart meters that enable bidirectional communication. However, the true value of smart grids is unlocked only when the veritable explosion of data that will become available is ingested, processed, analyzed and translated into meaningful decisions. These include the ability to forecast electricity demand, respond to peak load events, and improve sustainable use of energy by consumers, and are made possible by energy informatics. Information and software system techniques for a smarter power grid include pattern mining and machine learning over complex events and integrated semantic information, distributed stream processing for low latency response,Cloud platforms for scalable operations and privacy policies to mitigate information leakage in an information rich environment. Such an informatics approach is being used in the DoE sponsored Los Angeles Smart Grid Demonstration Project, and the resulting software architecture will lead to an agile and adaptive Los Angeles Smart Grid.

Enabling campus grids with open science grid technology

Energy Technology Data Exchange (ETDEWEB)

Weitzel, Derek [Nebraska U.; Bockelman, Brian [Nebraska U.; Swanson, David [Nebraska U.; Fraser, Dan [Argonne; Pordes, Ruth [Fermilab

2011-01-01

The Open Science Grid is a recognized key component of the US national cyber-infrastructure enabling scientific discovery through advanced high throughput computing. The principles and techniques that underlie the Open Science Grid can also be applied to Campus Grids since many of the requirements are the same, even if the implementation technologies differ. We find five requirements for a campus grid: trust relationships, job submission, resource independence, accounting, and data management. The Holland Computing Center's campus grid at the University of Nebraska-Lincoln was designed to fulfill the requirements of a campus grid. A bridging daemon was designed to bring non-Condor clusters into a grid managed by Condor. Condor features which make it possible to bridge Condor sites into a multi-campus grid have been exploited at the Holland Computing Center as well.

Effect of Co-segregating Markers on High-Density Genetic Maps and Prediction of Map Expansion Using Machine Learning Algorithms.

Science.gov (United States)

N'Diaye, Amidou; Haile, Jemanesh K; Fowler, D Brian; Ammar, Karim; Pozniak, Curtis J

2017-01-01

Advances in sequencing and genotyping methods have enable cost-effective production of high throughput single nucleotide polymorphism (SNP) markers, making them the choice for linkage mapping. As a result, many laboratories have developed high-throughput SNP assays and built high-density genetic maps. However, the number of markers may, by orders of magnitude, exceed the resolution of recombination for a given population size so that only a minority of markers can accurately be ordered. Another issue attached to the so-called 'large p, small n' problem is that high-density genetic maps inevitably result in many markers clustering at the same position (co-segregating markers). While there are a number of related papers, none have addressed the impact of co-segregating markers on genetic maps. In the present study, we investigated the effects of co-segregating markers on high-density genetic map length and marker order using empirical data from two populations of wheat, Mohawk × Cocorit (durum wheat) and Norstar × Cappelle Desprez (bread wheat). The maps of both populations consisted of 85% co-segregating markers. Our study clearly showed that excess of co-segregating markers can lead to map expansion, but has little effect on markers order. To estimate the inflation factor (IF), we generated a total of 24,473 linkage maps (8,203 maps for Mohawk × Cocorit and 16,270 maps for Norstar × Cappelle Desprez). Using seven machine learning algorithms, we were able to predict with an accuracy of 0.7 the map expansion due to the proportion of co-segregating markers. For example in Mohawk × Cocorit, with 10 and 80% co-segregating markers the length of the map inflated by 4.5 and 16.6%, respectively. Similarly, the map of Norstar × Cappelle Desprez expanded by 3.8 and 11.7% with 10 and 80% co-segregating markers. With the increasing number of markers on SNP-chips, the proportion of co-segregating markers in high-density maps will continue to increase making map expansion

Effect of Co-segregating Markers on High-Density Genetic Maps and Prediction of Map Expansion Using Machine Learning Algorithms

Directory of Open Access Journals (Sweden)

Amidou N’Diaye

2017-08-01

Full Text Available Advances in sequencing and genotyping methods have enable cost-effective production of high throughput single nucleotide polymorphism (SNP markers, making them the choice for linkage mapping. As a result, many laboratories have developed high-throughput SNP assays and built high-density genetic maps. However, the number of markers may, by orders of magnitude, exceed the resolution of recombination for a given population size so that only a minority of markers can accurately be ordered. Another issue attached to the so-called ‘large p, small n’ problem is that high-density genetic maps inevitably result in many markers clustering at the same position (co-segregating markers. While there are a number of related papers, none have addressed the impact of co-segregating markers on genetic maps. In the present study, we investigated the effects of co-segregating markers on high-density genetic map length and marker order using empirical data from two populations of wheat, Mohawk × Cocorit (durum wheat and Norstar × Cappelle Desprez (bread wheat. The maps of both populations consisted of 85% co-segregating markers. Our study clearly showed that excess of co-segregating markers can lead to map expansion, but has little effect on markers order. To estimate the inflation factor (IF, we generated a total of 24,473 linkage maps (8,203 maps for Mohawk × Cocorit and 16,270 maps for Norstar × Cappelle Desprez. Using seven machine learning algorithms, we were able to predict with an accuracy of 0.7 the map expansion due to the proportion of co-segregating markers. For example in Mohawk × Cocorit, with 10 and 80% co-segregating markers the length of the map inflated by 4.5 and 16.6%, respectively. Similarly, the map of Norstar × Cappelle Desprez expanded by 3.8 and 11.7% with 10 and 80% co-segregating markers. With the increasing number of markers on SNP-chips, the proportion of co-segregating markers in high-density maps will continue to increase

Experiences with the GLUE information schema in the LCG/EGEE production grid

International Nuclear Information System (INIS)

Burke, S; Andreozzi, S; Field, L

2008-01-01

A common information schema for the description of Grid resources and services is an essential requirement for interoperating Grid infrastructures, and its implementation interacts with every Grid component. In this context, the GLUE information schema was originally defined in 2002 as a joint project between the European DataGrid and DataTAG projects and the US iVDGL. The schema has major components to describe Computing and Storage Elements, and also generic Service and Site information. It has been used extensively in the LCG/EGEE Grid, for job submission, data management, service discovery and monitoring. In this paper we present the experience gained over the last five years, highlighting both successes and problems. In particular, we consider the importance of having a clear definition of schema attributes; the construction of standard information providers and difficulties encountered in mapping an abstract schema to diverse real systems; the configuration of publication in a way which suits system managers and the varying characteristics of Grid sites; the validation of published information; the ways in which information can be used (and misused) by Grid services and users; and issues related to managing schema upgrades in a large distributed system

Diviner lunar radiometer gridded brightness temperatures from geodesic binning of modeled fields of view

Science.gov (United States)

Sefton-Nash, E.; Williams, J.-P.; Greenhagen, B. T.; Aye, K.-M.; Paige, D. A.

2017-12-01

An approach is presented to efficiently produce high quality gridded data records from the large, global point-based dataset returned by the Diviner Lunar Radiometer Experiment aboard NASA's Lunar Reconnaissance Orbiter. The need to minimize data volume and processing time in production of science-ready map products is increasingly important with the growth in data volume of planetary datasets. Diviner makes on average >1400 observations per second of radiance that is reflected and emitted from the lunar surface, using 189 detectors divided into 9 spectral channels. Data management and processing bottlenecks are amplified by modeling every observation as a probability distribution function over the field of view, which can increase the required processing time by 2-3 orders of magnitude. Geometric corrections, such as projection of data points onto a digital elevation model, are numerically intensive and therefore it is desirable to perform them only once. Our approach reduces bottlenecks through parallel binning and efficient storage of a pre-processed database of observations. Database construction is via subdivision of a geodesic icosahedral grid, with a spatial resolution that can be tailored to suit the field of view of the observing instrument. Global geodesic grids with high spatial resolution are normally impractically memory intensive. We therefore demonstrate a minimum storage and highly parallel method to bin very large numbers of data points onto such a grid. A database of the pre-processed and binned points is then used for production of mapped data products that is significantly faster than if unprocessed points were used. We explore quality controls in the production of gridded data records by conditional interpolation, allowed only where data density is sufficient. The resultant effects on the spatial continuity and uncertainty in maps of lunar brightness temperatures is illustrated. We identify four binning regimes based on trades between the

Using Cloud-to-Ground Lightning Climatologies to Initialize Gridded Lightning Threat Forecasts for East Central Florida

Science.gov (United States)

Lambert, Winnie; Sharp, David; Spratt, Scott; Volkmer, Matthew

2005-01-01

Each morning, the forecasters at the National Weather Service in Melbourn, FL (NWS MLB) produce an experimental cloud-to-ground (CG) lightning threat index map for their county warning area (CWA) that is posted to their web site (http://www.srh.weather.gov/mlb/ghwo/lightning.shtml) . Given the hazardous nature of lightning in central Florida, especially during the warm season months of May-September, these maps help users factor the threat of lightning, relative to their location, into their daily plans. The maps are color-coded in five levels from Very Low to Extreme, with threat level definitions based on the probability of lightning occurrence and the expected amount of CG activity. On a day in which thunderstorms are expected, there are typically two or more threat levels depicted spatially across the CWA. The locations of relative lightning threat maxima and minima often depend on the position and orientation of the low-level ridge axis, forecast propagation and interaction of sea/lake/outflow boundaries, expected evolution of moisture and stability fields, and other factors that can influence the spatial distribution of thunderstorms over the CWA. The lightning threat index maps are issued for the 24-hour period beginning at 1200 UTC (0700 AM EST) each day with a grid resolution of 5 km x 5 km. Product preparation is performed on the AWIPS Graphical Forecast Editor (GFE), which is the standard NWS platform for graphical editing. Currently, the forecasters create each map manually, starting with a blank map. To improve efficiency of the forecast process, NWS MLB requested that the Applied Meteorology Unit (AMU) create gridded warm season lightning climatologies that could be used as first-guess inputs to initialize lightning threat index maps. The gridded values requested included CG strike densities and frequency of occurrence stratified by synoptic-scale flow regime. The intent is to increase consistency between forecasters while enabling them to focus on

A New Fuzzy Cognitive Map Learning Algorithm for Speech Emotion Recognition

Directory of Open Access Journals (Sweden)

Wei Zhang

2017-01-01

Full Text Available Selecting an appropriate recognition method is crucial in speech emotion recognition applications. However, the current methods do not consider the relationship between emotions. Thus, in this study, a speech emotion recognition system based on the fuzzy cognitive map (FCM approach is constructed. Moreover, a new FCM learning algorithm for speech emotion recognition is proposed. This algorithm includes the use of the pleasure-arousal-dominance emotion scale to calculate the weights between emotions and certain mathematical derivations to determine the network structure. The proposed algorithm can handle a large number of concepts, whereas a typical FCM can handle only relatively simple networks (maps. Different acoustic features, including fundamental speech features and a new spectral feature, are extracted to evaluate the performance of the proposed method. Three experiments are conducted in this paper, namely, single feature experiment, feature combination experiment, and comparison between the proposed algorithm and typical networks. All experiments are performed on TYUT2.0 and EMO-DB databases. Results of the feature combination experiments show that the recognition rates of the combination features are 10%–20% better than those of single features. The proposed FCM learning algorithm generates 5%–20% performance improvement compared with traditional classification networks.

The effectiveness of concept mapping and retrieval practice as learning strategies in an undergraduate physiology course.

Science.gov (United States)

Burdo, Joseph; O'Dwyer, Laura

2015-12-01

Concept mapping and retrieval practice are both educational methods that have separately been reported to provide significant benefits for learning in diverse settings. Concept mapping involves diagramming a hierarchical representation of relationships between distinct pieces of information, whereas retrieval practice involves retrieving information that was previously coded into memory. The relative benefits of these two methods have never been tested against each other in a classroom setting. Our study was designed to investigate whether or not concept mapping or retrieval practice produced a significant learning benefit in an undergraduate physiology course as measured by exam performance and, if so, was the benefit of one method significantly greater than the other. We found that there was a trend toward increased exam scores for the retrieval practice group compared with both the control group and concept mapping group, and that trend achieved statistical significance for one of the four module exams in the course. We also found that women performed statistically better than men on the module exam that contained a substantial amount of material relating to female reproductive physiology. Copyright © 2015 The American Physiological Society.

Radiofrequency Electromagnetic Field Map of Timisoara

Science.gov (United States)

Stefu, N.; Solyom, I.; Arama, A.

2015-12-01

There are many electromagnetic field (EMF) sources nowadays acting simultaneously, especially in urban areas, making the theoretical estimation of electromagnetic power at ground level very difficult. This paper reports on EMF maps built with measurements collected in Timisoara, at various radiofrequencies. A grid of 15×15 squares was built (approximate resolution 400m x 400m) and measurements of the average and maximum values of the electric field E, magnetic field H and total power density S at 0.9, 1.8 and 2.4 GHz were collected in every node of the grid. Positions of the nodes in terms of latitude and longitude were also collected. Maps were built presenting the spatial distribution of the measured quantities over Timisoara. Potential influences of EMF on public health are discussed.

Shortest path problem on a grid network with unordered intermediate points

Science.gov (United States)

Saw, Veekeong; Rahman, Amirah; Eng Ong, Wen

2017-10-01

We consider a shortest path problem with single cost factor on a grid network with unordered intermediate points. A two stage heuristic algorithm is proposed to find a feasible solution path within a reasonable amount of time. To evaluate the performance of the proposed algorithm, computational experiments are performed on grid maps of varying size and number of intermediate points. Preliminary results for the problem are reported. Numerical comparisons against brute forcing show that the proposed algorithm consistently yields solutions that are within 10% of the optimal solution and uses significantly less computation time.

A New Fuzzy Cognitive Map Learning Algorithm for Speech Emotion Recognition

OpenAIRE

Zhang, Wei; Zhang, Xueying; Sun, Ying

2017-01-01

Selecting an appropriate recognition method is crucial in speech emotion recognition applications. However, the current methods do not consider the relationship between emotions. Thus, in this study, a speech emotion recognition system based on the fuzzy cognitive map (FCM) approach is constructed. Moreover, a new FCM learning algorithm for speech emotion recognition is proposed. This algorithm includes the use of the pleasure-arousal-dominance emotion scale to calculate the weights between e...

An Overview of the Smart Grid in Great Britain

Directory of Open Access Journals (Sweden)

Nick Jenkins

2015-12-01

Full Text Available This paper presents an overview of the current status of the development of the smart grid in Great Britain (GB. The definition, policy and technical drivers, incentive mechanisms, technological focus, and the industry's progress in developing the smart grid are described. In particular, the Low Carbon Networks Fund and Electricity Network Innovation Competition projects, together with the rollout of smart metering, are detailed. A more observable, controllable, automated, and integrated electricity network will be supported by these investments in conjunction with smart meter installation. It is found that the focus has mainly been on distribution networks as well as on real-time flows of information and interaction between suppliers and consumers facilitated by improved information and communications technology, active power flow management, demand management, and energy storage. The learning from the GB smart grid initiatives will provide valuable guidelines for future smart grid development in GB and other countries.

Real Time Mapping and Dynamic Navigation for Mobile Robots

Directory of Open Access Journals (Sweden)

Maki K. Habib

2008-11-01

Full Text Available This paper discusses the importance, the complexity and the challenges of mapping mobile robot?s unknown and dynamic environment, besides the role of sensors and the problems inherited in map building. These issues remain largely an open research problems in developing dynamic navigation systems for mobile robots. The paper presenst the state of the art in map building and localization for mobile robots navigating within unknown environment, and then introduces a solution for the complex problem of autonomous map building and maintenance method with focus on developing an incremental grid based mapping technique that is suitable for real-time obstacle detection and avoidance. In this case, the navigation of mobile robots can be treated as a problem of tracking geometric features that occur naturally in the environment of the robot. The robot maps its environment incrementally using the concept of occupancy grids and the fusion of multiple ultrasonic sensory information while wandering in it and stay away from all obstacles. To ensure real-time operation with limited resources, as well as to promote extensibility, the mapping and obstacle avoidance modules are deployed in parallel and distributed framework. Simulation based experiments has been conducted and illustrated to show the validity of the developed mapping and obstacle avoidance approach.

Real Time Monitor of Grid job executions

International Nuclear Information System (INIS)

Colling, D J; Martyniak, J; McGough, A S; Krenek, A; Sitera, J; Mulac, M; Dvorak, F

2010-01-01

In this paper we describe the architecture and operation of the Real Time Monitor (RTM), developed by the Grid team in the HEP group at Imperial College London. This is arguably the most popular dissemination tool within the EGEE [1] Grid. Having been used, on many occasions including GridFest and LHC inauguration events held at CERN in October 2008. The RTM gathers information from EGEE sites hosting Logging and Bookkeeping (LB) services. Information is cached locally at a dedicated server at Imperial College London and made available for clients to use in near real time. The system consists of three main components: the RTM server, enquirer and an apache Web Server which is queried by clients. The RTM server queries the LB servers at fixed time intervals, collecting job related information and storing this in a local database. Job related data includes not only job state (i.e. Scheduled, Waiting, Running or Done) along with timing information but also other attributes such as Virtual Organization and Computing Element (CE) queue - if known. The job data stored in the RTM database is read by the enquirer every minute and converted to an XML format which is stored on a Web Server. This decouples the RTM server database from the client removing the bottleneck problem caused by many clients simultaneously accessing the database. This information can be visualized through either a 2D or 3D Java based client with live job data either being overlaid on to a 2 dimensional map of the world or rendered in 3 dimensions over a globe map using OpenGL.

GridCom, Grid Commander: graphical interface for Grid jobs and data management; GridCom, Grid Commander: graficheskij interfejs dlya raboty s zadachami i dannymi v gride

Energy Technology Data Exchange (ETDEWEB)

Galaktionov, V V

2011-07-01

GridCom - the software package for maintenance of automation of access to means of distributed system Grid (jobs and data). The client part, executed in the form of Java-applets, realises the Web-interface access to Grid through standard browsers. The executive part Lexor (LCG Executor) is started by the user in UI (User Interface) machine providing performance of Grid operations

Concept Mapping as an Innovative Tool for the Assessment of Learning: An Experimental Experience among Business Management Degree Students

Science.gov (United States)

Ruiz-Palomino, Pablo; Martinez-Canas, Ricardo

2013-01-01

In the search to improve the quality of education at the university level, the use of concept mapping is becoming an important instructional technique for enhancing the teaching-learning process. This educational tool is based on cognitive theories by making a distinction between learning by rote (memorizing) and learning by meaning, where…

Progress in Grid Generation: From Chimera to DRAGON Grids

Science.gov (United States)

Liou, Meng-Sing; Kao, Kai-Hsiung

1994-01-01

Hybrid grids, composed of structured and unstructured grids, combines the best features of both. The chimera method is a major stepstone toward a hybrid grid from which the present approach is evolved. The chimera grid composes a set of overlapped structured grids which are independently generated and body-fitted, yielding a high quality grid readily accessible for efficient solution schemes. The chimera method has been shown to be efficient to generate a grid about complex geometries and has been demonstrated to deliver accurate aerodynamic prediction of complex flows. While its geometrical flexibility is attractive, interpolation of data in the overlapped regions - which in today's practice in 3D is done in a nonconservative fashion, is not. In the present paper we propose a hybrid grid scheme that maximizes the advantages of the chimera scheme and adapts the strengths of the unstructured grid while at the same time keeps its weaknesses minimal. Like the chimera method, we first divide up the physical domain by a set of structured body-fitted grids which are separately generated and overlaid throughout a complex configuration. To eliminate any pure data manipulation which does not necessarily follow governing equations, we use non-structured grids only to directly replace the region of the arbitrarily overlapped grids. This new adaptation to the chimera thinking is coined the DRAGON grid. The nonstructured grid region sandwiched between the structured grids is limited in size, resulting in only a small increase in memory and computational effort. The DRAGON method has three important advantages: (1) preserving strengths of the chimera grid; (2) eliminating difficulties sometimes encountered in the chimera scheme, such as the orphan points and bad quality of interpolation stencils; and (3) making grid communication in a fully conservative and consistent manner insofar as the governing equations are concerned. To demonstrate its use, the governing equations are

Cooperation-Controlled Learning for Explicit Class Structure in Self-Organizing Maps

Science.gov (United States)

Kamimura, Ryotaro

2014-01-01

We attempt to demonstrate the effectiveness of multiple points of view toward neural networks. By restricting ourselves to two points of view of a neuron, we propose a new type of information-theoretic method called “cooperation-controlled learning.” In this method, individual and collective neurons are distinguished from one another, and we suppose that the characteristics of individual and collective neurons are different. To implement individual and collective neurons, we prepare two networks, namely, cooperative and uncooperative networks. The roles of these networks and the roles of individual and collective neurons are controlled by the cooperation parameter. As the parameter is increased, the role of cooperative networks becomes more important in learning, and the characteristics of collective neurons become more dominant. On the other hand, when the parameter is small, individual neurons play a more important role. We applied the method to the automobile and housing data from the machine learning database and examined whether explicit class boundaries could be obtained. Experimental results showed that cooperation-controlled learning, in particular taking into account information on input units, could be used to produce clearer class structure than conventional self-organizing maps. PMID:25309950

Cooperation-Controlled Learning for Explicit Class Structure in Self-Organizing Maps

Directory of Open Access Journals (Sweden)

Ryotaro Kamimura

2014-01-01

Full Text Available We attempt to demonstrate the effectiveness of multiple points of view toward neural networks. By restricting ourselves to two points of view of a neuron, we propose a new type of information-theoretic method called “cooperation-controlled learning.” In this method, individual and collective neurons are distinguished from one another, and we suppose that the characteristics of individual and collective neurons are different. To implement individual and collective neurons, we prepare two networks, namely, cooperative and uncooperative networks. The roles of these networks and the roles of individual and collective neurons are controlled by the cooperation parameter. As the parameter is increased, the role of cooperative networks becomes more important in learning, and the characteristics of collective neurons become more dominant. On the other hand, when the parameter is small, individual neurons play a more important role. We applied the method to the automobile and housing data from the machine learning database and examined whether explicit class boundaries could be obtained. Experimental results showed that cooperation-controlled learning, in particular taking into account information on input units, could be used to produce clearer class structure than conventional self-organizing maps.

A neurocomputational account of taxonomic responding and fast mapping in early word learning.

Science.gov (United States)

Mayor, Julien; Plunkett, Kim

2010-01-01

We present a neurocomputational model with self-organizing maps that accounts for the emergence of taxonomic responding and fast mapping in early word learning, as well as a rapid increase in the rate of acquisition of words observed in late infancy. The quality and efficiency of generalization of word-object associations is directly related to the quality of prelexical, categorical representations in the model. We show how synaptogenesis supports coherent generalization of word-object associations and show that later synaptic pruning minimizes metabolic costs without being detrimental to word learning. The role played by joint-attentional activities is identified in the model, both at the level of selecting efficient cross-modal synapses and at the behavioral level, by accelerating and refining overall vocabulary acquisition. The model can account for the qualitative shift in the way infants use words, from an associative to a referential-like use, for the pattern of overextension errors in production and comprehension observed during early childhood and typicality effects observed in lexical development. Interesting by-products of the model include a potential explanation of the shift from prototype to exemplar-based effects reported for adult category formation, an account of mispronunciation effects in early lexical development, and extendability to include accounts of individual differences in lexical development and specific disorders such as Williams syndrome. The model demonstrates how an established constraint on lexical learning, which has often been regarded as domain-specific, can emerge from domain-general learning principles that are simultaneously biologically, psychologically, and socially plausible.

Diagnosis of inconsistencies in multi-year gridded precipitation data over mountainous areas and related impacts on hydrologic simulations

Science.gov (United States)

Mizukami, N.; Smith, M. B.

2010-12-01

It is common for the error characteristics of long-term precipitation data to change over time due to various factors such as gauge relocation and changes in data processing methods. The temporal consistency of precipitation data error characteristics is as important as data accuracy itself for hydrologic model calibration and subsequent use of the calibrated model for streamflow prediction. In mountainous areas, the generation of precipitation grids relies on sparse gage networks, the makeup of which often varies over time. This causes a change in error characteristics of the long-term precipitation data record. We will discuss the diagnostic analysis of the consistency of gridded precipitation time series and illustrate the adverse effect of inconsistent precipitation data on a hydrologic model simulation. We used hourly 4 km gridded precipitation time series over a mountainous basin in the Sierra Nevada Mountains of California from October 1988 through September 2006. The basin is part of the broader study area that served as the focus of the second phase of the Distributed Model Intercomparison Project (DMIP-2), organized by the U.S. National Weather Service (NWS) of the National Oceanographic and Atmospheric Administration (NOAA). To check the consistency of the gridded precipitation time series, double mass analysis was performed using single pixel and basin mean areal precipitation (MAP) values derived from gridded DMIP-2 and Parameter-Elevation Regressions on Independent Slopes Model (PRISM) precipitation data. The analysis leads to the conclusion that over the entire study time period, a clear change in error characteristics in the DMIP-2 data occurred in the beginning of 2003. This matches the timing of one of the major gage network changes. The inconsistency of two MAP time series computed from the gridded precipitation fields over two elevation zones was corrected by adjusting hourly values based on the double mass analysis. We show that model

Vision-based mapping with cooperative robots

Science.gov (United States)

Little, James J.; Jennings, Cullen; Murray, Don

1998-10-01

Two stereo-vision-based mobile robots navigate and autonomously explore their environment safely while building occupancy grid maps of the environment. The robots maintain position estimates within a global coordinate frame using landmark recognition. This allows them to build a common map by sharing position information and stereo data. Stereo vision processing and map updates are done at 3 Hz and the robots move at speeds of 200 cm/s. Cooperative mapping is achieved through autonomous exploration of unstructured and dynamic environments. The map is constructed conservatively, so as to be useful for collision-free path planning. Each robot maintains a separate copy of a shared map, and then posts updates to the common map when it returns to observe a landmark at home base. Issues include synchronization, mutual localization, navigation, exploration, registration of maps, merging repeated views (fusion), centralized vs decentralized maps.

Practical indoor mobile robot navigation using hybrid maps

DEFF Research Database (Denmark)

Özkil, Ali Gürcan; Fan, Zhun; Xiao, Jizhong

2011-01-01

This paper presents a practical navigation scheme for indoor mobile robots using hybrid maps. The method makes use of metric maps for local navigation and a topological map for global path planning. Metric maps are generated as 2D occupancy grids by a range sensor to represent local information...... about partial areas. The global topological map is used to indicate the connectivity of the 'places-of-interests' in the environment and the interconnectivity of the local maps. Visual tags on the ceiling to be detected by the robot provide valuable information and contribute to reliable localization...... robot and evaluated in a hospital environment....

Compact data structure and scalable algorithms for the sparse grid technique

KAUST Repository

Murarasu, Alin

2011-01-01

The sparse grid discretization technique enables a compressed representation of higher-dimensional functions. In its original form, it relies heavily on recursion and complex data structures, thus being far from well-suited for GPUs. In this paper, we describe optimizations that enable us to implement compression and decompression, the crucial sparse grid algorithms for our application, on Nvidia GPUs. The main idea consists of a bijective mapping between the set of points in a multi-dimensional sparse grid and a set of consecutive natural numbers. The resulting data structure consumes a minimum amount of memory. For a 10-dimensional sparse grid with approximately 127 million points, it consumes up to 30 times less memory than trees or hash tables which are typically used. Compared to a sequential CPU implementation, the speedups achieved on GPU are up to 17 for compression and up to 70 for decompression, respectively. We show that the optimizations are also applicable to multicore CPUs. Copyright © 2011 ACM.

GRID-BASED EXPLORATION OF COSMOLOGICAL PARAMETER SPACE WITH SNAKE

Energy Technology Data Exchange (ETDEWEB)

Mikkelsen, K.; Næss, S. K.; Eriksen, H. K., E-mail: kristin.mikkelsen@astro.uio.no [Institute of Theoretical Astrophysics, University of Oslo, P.O. Box 1029, Blindern, NO-0315 Oslo (Norway)

2013-11-10

We present a fully parallelized grid-based parameter estimation algorithm for investigating multidimensional likelihoods called Snake, and apply it to cosmological parameter estimation. The basic idea is to map out the likelihood grid-cell by grid-cell according to decreasing likelihood, and stop when a certain threshold has been reached. This approach improves vastly on the 'curse of dimensionality' problem plaguing standard grid-based parameter estimation simply by disregarding grid cells with negligible likelihood. The main advantages of this method compared to standard Metropolis-Hastings Markov Chain Monte Carlo methods include (1) trivial extraction of arbitrary conditional distributions; (2) direct access to Bayesian evidences; (3) better sampling of the tails of the distribution; and (4) nearly perfect parallelization scaling. The main disadvantage is, as in the case of brute-force grid-based evaluation, a dependency on the number of parameters, N{sub par}. One of the main goals of the present paper is to determine how large N{sub par} can be, while still maintaining reasonable computational efficiency; we find that N{sub par} = 12 is well within the capabilities of the method. The performance of the code is tested by comparing cosmological parameters estimated using Snake and the WMAP-7 data with those obtained using CosmoMC, the current standard code in the field. We find fully consistent results, with similar computational expenses, but shorter wall time due to the perfect parallelization scheme.

Mapping the work-based learning of novice teachers: charting some rich terrain.

Science.gov (United States)

Cook, Vivien

2009-12-01

Work-based non-formal learning plays a key role in faculty development yet these processes are yet to be described in detail in medical education. This study sets out to illuminate these processes so that potential benefits for new and inexperienced medical educators and their mentors can be realised. The non-formal learning processes of 12 novice teachers were investigated across hospital, general practice and medical school settings. The research sought to describe 'what' and 'how' non-formal learning takes place, and whether these processes differ across teaching sites. Both clinical and non-clinical teachers of medical undergraduates from one inner city medical school were recruited for the study. Through semi-structured interviews and a 'concept map', participants were asked to identify the people and tasks which they considered central to helping them become more expert as educators. Results identified non-formal learning across a number of key dimensions, including personal development, task and role performance, and optimising clinical teaching. This learning takes place as an outcome of experience, observation, reflection and student feedback. Non-formal learning is a significant aspect of the development of novice teachers and as such it needs to be placed more firmly upon the agenda of faculty development.

MICROARRAY IMAGE GRIDDING USING GRID LINE REFINEMENT TECHNIQUE

Directory of Open Access Journals (Sweden)

V.G. Biju

2015-05-01

Full Text Available An important stage in microarray image analysis is gridding. Microarray image gridding is done to locate sub arrays in a microarray image and find co-ordinates of spots within each sub array. For accurate identification of spots, most of the proposed gridding methods require human intervention. In this paper a fully automatic gridding method which enhances spot intensity in the preprocessing step as per a histogram based threshold method is used. The gridding step finds co-ordinates of spots from horizontal and vertical profile of the image. To correct errors due to the grid line placement, a grid line refinement technique is proposed. The algorithm is applied on different image databases and results are compared based on spot detection accuracy and time. An average spot detection accuracy of 95.06% depicts the proposed method’s flexibility and accuracy in finding the spot co-ordinates for different database images.

Joined up Thinking? Evaluating the Use of Concept-Mapping to Develop Complex System Learning

Science.gov (United States)

Stewart, Martyn

2012-01-01

In the physical and natural sciences, the complexity of natural systems and their interactions is becoming better understood. With increased emphasis on learning about complex systems, students will be encountering concepts that are dynamic, ill-structured and interconnected. Concept-mapping is a method considered particularly valuable for…

Grid3: An Application Grid Laboratory for Science

CERN Multimedia

CERN. Geneva

2004-01-01

level services required by the participating experiments. The deployed infrastructure has been operating since November 2003 with 27 sites, a peak of 2800 processors, work loads from 10 different applications exceeding 1300 simultaneous jobs, and data transfers among sites of greater than 2 TB/day. The Grid3 infrastructure was deployed from grid level services provided by groups and applications within the collaboration. The services were organized into four distinct "grid level services" including: Grid3 Packaging, Monitoring and Information systems, User Authentication and the iGOC Grid Operatio...

GeoMapApp Learning Activities: Grab-and-go inquiry-based geoscience activities that bring cutting-edge technology to the classroom

Science.gov (United States)

Goodwillie, A. M.; Kluge, S.

2011-12-01

NSF-funded GeoMapApp Learning Activities (http://serc.carleton.edu/geomapapp) provide self-contained learning opportunities that are centred around the principles of guided inquiry. The activities allow students to interact with and analyse research-quality geoscience data to explore and enhance student understanding of underlying geoscience content and concepts. Each activity offers ready-to-use step-by-step student instructions and answer sheets that can be downloaded from the web page. Also provided are annotated teacher versions of the worksheets that include teaching tips, additional content and suggestions for further work. Downloadable pre- and post- quizzes tied to each activity help educators gauge the learning progression of their students. Short multimedia tutorials and details on content alignment with state and national teaching standards round out the package of material that comprises each "grab-and-go" activity. GeoMapApp Learning Activities expose students to content and concepts typically found at the community college, high school and introductory undergraduate levels. The activities are based upon GeoMapApp (http://www.geomapapp.org), a free, easy-to-use map-based data exploration and visualisation tool that allows students to access a wide range of geoscience data sets in a virtual lab-like environment. Activities that have so far been created under this project include student exploration of seafloor spreading rates, a study of mass wasting as revealed through geomorphological evidence, and an analysis of plate motion and hotspot traces. The step-by-step instructions and guided inquiry approach lead students through each activity, thus reducing the need for teacher intervention whilst also boosting the time that students can spend on productive exploration and learning. The activities can be used, for example, in a classroom lab with the educator present and as self-paced assignments in an out-of-class setting. GeoMapApp Learning Activities

The effects of using concept mapping as an artifact to engender metacognitive thinking in first-year medical students' problem-based learning discussions: A mixed-methods investigation

Science.gov (United States)

Shoop, Glenda Hostetter

Attention in medical education is turning toward instruction that not only focuses on knowledge acquisition, but on developing the medical students' clinical problem-solving skills, and their ability to critically think through complex diseases. Metacognition is regarded as an important consideration in how we teach medical students these higher-order, critical thinking skills. This study used a mixed-methods research design to investigate if concept mapping as an artifact may engender metacognitive thinking in the medical student population. Specifically the purpose of the study is twofold: (1) to determine if concept mapping, functioning as an artifact during problem-based learning, improves learning as measured by scores on test questions; and (2) to explore if the process of concept mapping alters the problem-based learning intragroup discussion in ways that show medical students are engaged in metacognitive thinking. The results showed that students in the problem-based learning concept-mapping groups used more metacognitive thinking patterns than those in the problem-based learning discussion-only group, particularly in the monitoring component. These groups also engaged in a higher level of cognitive thinking associated with reasoning through mechanisms-of-action and breaking down complex biochemical and physiologic principals. The students disclosed in focus-group interviews that concept mapping was beneficial to help them understand how discrete pieces of information fit together in a bigger structure of knowledge. They also stated that concept mapping gave them some time to think through these concepts in a larger conceptual framework. There was no significant difference in the exam-question scores between the problem-based learning concept-mapping groups and the problem-based learning discussion-only group.

Grid-connected to/from off-grid transference for micro-grid inverters

OpenAIRE

Heredero Peris, Daniel; Chillón Antón, Cristian; Pages Gimenez, Marc; Gross, Gabriel Igor; Montesinos Miracle, Daniel

2013-01-01

This paper compares two methods for controlling the on-line transference from connected to stand-alone mode and vice versa in converters for micro-grids. The first proposes a method where the converter changes from CSI (Current Source Inverter) in grid-connected mode to VSI (Voltage Source Inverter) in off-grid. In the second method, the inverter always works as a non-ideal voltage source, acting as VSI, using AC droop control strategy.

Gaussian Multiple Instance Learning Approach for Mapping the Slums of the World Using Very High Resolution Imagery

Energy Technology Data Exchange (ETDEWEB)

Vatsavai, Raju [ORNL

2013-01-01

In this paper, we present a computationally efficient algo- rithm based on multiple instance learning for mapping infor- mal settlements (slums) using very high-resolution remote sensing imagery. From remote sensing perspective, infor- mal settlements share unique spatial characteristics that dis- tinguish them from other urban structures like industrial, commercial, and formal residential settlements. However, regular pattern recognition and machine learning methods, which are predominantly single-instance or per-pixel classi- fiers, often fail to accurately map the informal settlements as they do not capture the complex spatial patterns. To overcome these limitations we employed a multiple instance based machine learning approach, where groups of contigu- ous pixels (image patches) are modeled as generated by a Gaussian distribution. We have conducted several experi- ments on very high-resolution satellite imagery, represent- ing four unique geographic regions across the world. Our method showed consistent improvement in accurately iden- tifying informal settlements.

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid.

Science.gov (United States)

Li, Yuancheng; Qiu, Rixuan; Jing, Sitong

2018-01-01

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

The GridSite Web/Grid security system

International Nuclear Information System (INIS)

McNab, Andrew; Li Yibiao

2010-01-01

We present an overview of the current status of the GridSite toolkit, describing the security model for interactive and programmatic uses introduced in the last year. We discuss our experiences of implementing these internal changes and how they and previous rounds of improvements have been prompted by requirements from users and wider security trends in Grids (such as CSRF). Finally, we explain how these have improved the user experience of GridSite-based websites, and wider implications for portals and similar web/grid sites.

Current Grid operation and future role of the Grid

Science.gov (United States)

Smirnova, O.

2012-12-01

Grid-like technologies and approaches became an integral part of HEP experiments. Some other scientific communities also use similar technologies for data-intensive computations. The distinct feature of Grid computing is the ability to federate heterogeneous resources of different ownership into a seamless infrastructure, accessible via a single log-on. Like other infrastructures of similar nature, Grid functioning requires not only technologically sound basis, but also reliable operation procedures, monitoring and accounting. The two aspects, technological and operational, are closely related: weaker is the technology, more burden is on operations, and other way around. As of today, Grid technologies are still evolving: at CERN alone, every LHC experiment uses an own Grid-like system. This inevitably creates a heavy load on operations. Infrastructure maintenance, monitoring and incident response are done on several levels, from local system administrators to large international organisations, involving massive human effort worldwide. The necessity to commit substantial resources is one of the obstacles faced by smaller research communities when moving computing to the Grid. Moreover, most current Grid solutions were developed under significant influence of HEP use cases, and thus need additional effort to adapt them to other applications. Reluctance of many non-HEP researchers to use Grid negatively affects the outlook for national Grid organisations, which strive to provide multi-science services. We started from the situation where Grid organisations were fused with HEP laboratories and national HEP research programmes; we hope to move towards the world where Grid will ultimately reach the status of generic public computing and storage service provider and permanent national and international Grid infrastructures will be established. How far will we be able to advance along this path, depends on us. If no standardisation and convergence efforts will take place

Current Grid operation and future role of the Grid

International Nuclear Information System (INIS)

Smirnova, O

2012-01-01

Grid-like technologies and approaches became an integral part of HEP experiments. Some other scientific communities also use similar technologies for data-intensive computations. The distinct feature of Grid computing is the ability to federate heterogeneous resources of different ownership into a seamless infrastructure, accessible via a single log-on. Like other infrastructures of similar nature, Grid functioning requires not only technologically sound basis, but also reliable operation procedures, monitoring and accounting. The two aspects, technological and operational, are closely related: weaker is the technology, more burden is on operations, and other way around. As of today, Grid technologies are still evolving: at CERN alone, every LHC experiment uses an own Grid-like system. This inevitably creates a heavy load on operations. Infrastructure maintenance, monitoring and incident response are done on several levels, from local system administrators to large international organisations, involving massive human effort worldwide. The necessity to commit substantial resources is one of the obstacles faced by smaller research communities when moving computing to the Grid. Moreover, most current Grid solutions were developed under significant influence of HEP use cases, and thus need additional effort to adapt them to other applications. Reluctance of many non-HEP researchers to use Grid negatively affects the outlook for national Grid organisations, which strive to provide multi-science services. We started from the situation where Grid organisations were fused with HEP laboratories and national HEP research programmes; we hope to move towards the world where Grid will ultimately reach the status of generic public computing and storage service provider and permanent national and international Grid infrastructures will be established. How far will we be able to advance along this path, depends on us. If no standardisation and convergence efforts will take place

Intrusion Prevention and Detection in Grid Computing - The ALICE Case

Science.gov (United States)

Gomez, Andres; Lara, Camilo; Kebschull, Udo

2015-12-01

Grids allow users flexible on-demand usage of computing resources through remote communication networks. A remarkable example of a Grid in High Energy Physics (HEP) research is used in the ALICE experiment at European Organization for Nuclear Research CERN. Physicists can submit jobs used to process the huge amount of particle collision data produced by the Large Hadron Collider (LHC). Grids face complex security challenges. They are interesting targets for attackers seeking for huge computational resources. Since users can execute arbitrary code in the worker nodes on the Grid sites, special care should be put in this environment. Automatic tools to harden and monitor this scenario are required. Currently, there is no integrated solution for such requirement. This paper describes a new security framework to allow execution of job payloads in a sandboxed context. It also allows process behavior monitoring to detect intrusions, even when new attack methods or zero day vulnerabilities are exploited, by a Machine Learning approach. We plan to implement the proposed framework as a software prototype that will be tested as a component of the ALICE Grid middleware.

ARC Cache: A solution for lightweight Grid sites in ATLAS

CERN Document Server

Garonne, Vincent; The ATLAS collaboration

2016-01-01

Many Grid sites have the need to reduce operational manpower, and running a storage element consumes a large amount of effort. In addition, setting up a new Grid site including a storage element involves a steep learning curve and large investment of time. For these reasons so-called storage-less sites are becoming more popular as a way to provide Grid computing resources with less operational overhead. ARC CE is a widely-used and mature Grid middleware which was designed from the start to be used on sites with no persistent storage element. Instead, it maintains a local self-managing cache of data which retains popular data for future jobs. As the cache is simply an area on a local posix shared filesystem with no external-facing service, it requires no extra maintenance. The cache can be scaled up as required by increasing the size of the filesystem or adding new filesystems. This paper describes how ARC CE and its cache are an ideal solution for lightweight Grid sites in the ATLAS experiment, and the integr...

Intrusion Prevention and Detection in Grid Computing - The ALICE Case

International Nuclear Information System (INIS)

Gomez, Andres; Lara, Camilo; Kebschull, Udo

2015-01-01

Grids allow users flexible on-demand usage of computing resources through remote communication networks. A remarkable example of a Grid in High Energy Physics (HEP) research is used in the ALICE experiment at European Organization for Nuclear Research CERN. Physicists can submit jobs used to process the huge amount of particle collision data produced by the Large Hadron Collider (LHC). Grids face complex security challenges. They are interesting targets for attackers seeking for huge computational resources. Since users can execute arbitrary code in the worker nodes on the Grid sites, special care should be put in this environment. Automatic tools to harden and monitor this scenario are required. Currently, there is no integrated solution for such requirement. This paper describes a new security framework to allow execution of job payloads in a sandboxed context. It also allows process behavior monitoring to detect intrusions, even when new attack methods or zero day vulnerabilities are exploited, by a Machine Learning approach. We plan to implement the proposed framework as a software prototype that will be tested as a component of the ALICE Grid middleware. (paper)

LA TITUDE-LONGITUDE GRID MAPS OF AFRICA (CCTA ...

African Journals Online (AJOL)

of mapping see de Meillon, B., Davis, D. H. S., and Hardy, F., Plague in Southern Mrica. I. The Siphonaptera. Government Printer, Pretoria, 1961, or consult CCTAjCSA Publication. No. 29, referred to above. * Climatological Atlas of Africa, compiled and edited in the African Climatology Unit, University of the. Witwatersrand ...

Semi-Cooperative Learning in Smart Grid Agents

Science.gov (United States)

2013-12-01

this PhD program , but watching you grow has only made me realize how much more awesome human learning is. You have been a source of profound joy and...which should alleviate concern for scala - bility along this dimension. • Learning the negotiation model: Figure 6.23 shows single-episode results that...for Semi-cooperative Multi-agent Coordination. In IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning . [Prendergast, 1999

A Social Learning Space Grid for MOOCs: Exploring a FutureLearn Case

OpenAIRE

Manathunga, Kalpani; Hernández-Leo, Davinia; Sharples, Mike

2017-01-01

Collaborative and social engagement promote active learning through knowledge intensive interactions. Massive Open Online Courses (MOOCs) are dynamic and diversified learning spaces with varying factors like flexible time frames, student count, demographics requiring higher engagement and motivation to continue learning and for designers to implement novel pedagogies including collaborative learning activities. This paper looks into available and potential collaborative and social learning sp...

The Mapping of On-Line Learning to Flipped Classroom: Small Private Online Course

Directory of Open Access Journals (Sweden)

Muqiang Zheng

2018-03-01

Full Text Available This study uses an integrated pedagogical tool for knowledge learning as an on-line tool for flipped classroom activities and as an off-line capability training tool. Theoretically, the Experiential Learning Cycle (ELC plays a critical role in promoting students learning effectiveness and performance. However, a dearth of research has applied M-learning and flipped classroom in combination with the ELC stages such as concrete experience, reflective observation, abstract conceptualization, and active experimentation to examine the knowledge and ability learning outcomes for students. This study integrates the On line to Off line (O2O classroom development and usage derived from the four stages of ELC based on on-line knowledge learning and off-line ability training in Microeconomics courses. The results revealed significant improvements in students learning outcomes after O2O mode was implemented. In comparison with traditional teaching methods, not only does O2O teaching significantly improve the students’ learning result of professional knowledge, but O2O teaching also significantly enhanced the capabilities of the students. Furthermore, this study reports the findings from major activities of each ELC stage in O2O classroom practice along with the mapping of on-line learning and off-line training included in the aforementioned stages. Finally, the study provides pedagogical implications and future research directions.

Scalable, incremental learning with MapReduce parallelization for cell detection in high-resolution 3D microscopy data

KAUST Repository

Sung, Chul

2013-08-01

Accurate estimation of neuronal count and distribution is central to the understanding of the organization and layout of cortical maps in the brain, and changes in the cell population induced by brain disorders. High-throughput 3D microscopy techniques such as Knife-Edge Scanning Microscopy (KESM) are enabling whole-brain survey of neuronal distributions. Data from such techniques pose serious challenges to quantitative analysis due to the massive, growing, and sparsely labeled nature of the data. In this paper, we present a scalable, incremental learning algorithm for cell body detection that can address these issues. Our algorithm is computationally efficient (linear mapping, non-iterative) and does not require retraining (unlike gradient-based approaches) or retention of old raw data (unlike instance-based learning). We tested our algorithm on our rat brain Nissl data set, showing superior performance compared to an artificial neural network-based benchmark, and also demonstrated robust performance in a scenario where the data set is rapidly growing in size. Our algorithm is also highly parallelizable due to its incremental nature, and we demonstrated this empirically using a MapReduce-based implementation of the algorithm. We expect our scalable, incremental learning approach to be widely applicable to medical imaging domains where there is a constant flux of new data. © 2013 IEEE.

A Run-Time Verification Framework for Smart Grid Applications Implemented on Simulation Frameworks

Energy Technology Data Exchange (ETDEWEB)

Ciraci, Selim; Sozer, Hasan; Tekinerdogan, Bedir

2013-05-18

Smart grid applications are implemented and tested with simulation frameworks as the developers usually do not have access to large sensor networks to be used as a test bed. The developers are forced to map the implementation onto these frameworks which results in a deviation between the architecture and the code. On its turn this deviation makes it hard to verify behavioral constraints that are de- scribed at the architectural level. We have developed the ConArch toolset to support the automated verification of architecture-level behavioral constraints. A key feature of ConArch is programmable mapping for architecture to the implementation. Here, developers implement queries to identify the points in the target program that correspond to architectural interactions. ConArch generates run- time observers that monitor the flow of execution between these points and verifies whether this flow conforms to the behavioral constraints. We illustrate how the programmable mappings can be exploited for verifying behavioral constraints of a smart grid appli- cation that is implemented with two simulation frameworks.

PENERAPAN METODE MIND MAPPING PADA PEMBELAJARAN MATEMATIKA

Directory of Open Access Journals (Sweden)

Rahma Faelasofi

2016-09-01

Full Text Available The objectives of this research was to solve how to increase students learning mathematic achievments on the subject of statistic. This study aims to determine whether the students learning mathematic achievments of the student SMP Muhammadiyah 1 Gadingrejo in the academic year of 2014-2015 using learning method mind mapping on the subject of statistics can be higher than the students’ learning mathematic achievments without using learning method mind mapping. This research is a quantitative approach. The population was all of the students in first grade of the SMP Muhammadiyah 1 Gadingrejo in the academic year of 2014- 2015. The samples of the research were taken by using the cluster random sampling technique. Based on hypothesis test, it can be included that there are differences in the average student learning achievments between using learning method mind mapping and learning method lecture on the subject of Statistics of the student in first grade of the SMP Muhammadiyah 1 Gadingrejo in the academic year of 2014-2015. Keywords: learning method mind mapping, students’ learning mathematic achievments

Teamwork: improved eQTL mapping using combinations of machine learning methods.

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Marit Ackermann

Full Text Available Expression quantitative trait loci (eQTL mapping is a widely used technique to uncover regulatory relationships between genes. A range of methodologies have been developed to map links between expression traits and genotypes. The DREAM (Dialogue on Reverse Engineering Assessments and Methods initiative is a community project to objectively assess the relative performance of different computational approaches for solving specific systems biology problems. The goal of one of the DREAM5 challenges was to reverse-engineer genetic interaction networks from synthetic genetic variation and gene expression data, which simulates the problem of eQTL mapping. In this framework, we proposed an approach whose originality resides in the use of a combination of existing machine learning algorithms (committee. Although it was not the best performer, this method was by far the most precise on average. After the competition, we continued in this direction by evaluating other committees using the DREAM5 data and developed a method that relies on Random Forests and LASSO. It achieved a much higher average precision than the DREAM best performer at the cost of slightly lower average sensitivity.

caGrid 1.0: a Grid enterprise architecture for cancer research.

Science.gov (United States)

Oster, Scott; Langella, Stephen; Hastings, Shannon; Ervin, David; Madduri, Ravi; Kurc, Tahsin; Siebenlist, Frank; Covitz, Peter; Shanbhag, Krishnakant; Foster, Ian; Saltz, Joel

2007-10-11

caGrid is the core Grid architecture of the NCI-sponsored cancer Biomedical Informatics Grid (caBIG) program. The current release, caGrid version 1.0, is developed as the production Grid software infrastructure of caBIG. Based on feedback from adopters of the previous version (caGrid 0.5), it has been significantly enhanced with new features and improvements to existing components. This paper presents an overview of caGrid 1.0, its main components, and enhancements over caGrid 0.5.

The map: An essential tool in the teaching-learning process of the Marxism-Leninism and History curriculum

Directory of Open Access Journals (Sweden)

Montero, Martiza Isabel

2012-05-01

Full Text Available This paper evaluates the use of maps in teaching Geography by a sample of professor at “José Marti” College of Education. A systematic use of maps constitutes one of the major problems in the teaching-learning process in the Marxism-Leninism and History Curriculum. Likewise, it has been identify as a shortcoming in graduates and in-service trainees. It would be recommendable to highlight the value and importance of maps in teaching, consequently a number of suggestions are given to lead, reflection and discussion by the teacher’s.

Real-time Social Media Data Analytics for Situational Awareness of the Electric Grid

Science.gov (United States)

Mao, H.; Chinthavali, S.; Lee, S.; Shankar, M.; Thiagarajan, S.

2016-12-01

With the increasing frequency of extreme events due to climate change, wide area situational awareness (SA) of the electric grid has become a primary need for federal agencies like DOE,FEMA etc. for emergency preparedness and recovery purposes. While several sensor feeds from Genscape, GridEye, PMUs provide a comprehensive view of the transmission grid, national-scale situational awareness tools are still relying on utility websites for outage information at a distribution level. The inconsistency and the variety in outage website's data formats makes this approach unreliable and also incurs huge software maintenance costs. Social media has emerged as a great medium for the utilities to share outage information with their customers. Despite their potential usefulness, extracting relevant data from these social media data-streams is challenging due to the inherent noise and irrelevant information such as tips to customers during storms, marketing, etc. In this study, we implement a practical and novel machine learning based data-analytics pipeline (Fig 1) for SA, which extracts real-time tweets from around 300 utility companies, processes these tweets using keyword filtering and Naïve-Bayes text classifier trained using supervised learning techniques to detect only relevant tweets. We validated the results by comparing it with the results identified by a human analyst for a period of 48 hours, and it showed around 98.3% accuracy. In addition to the tweets posted by utility companies, millions of twitter users, who are considered as human "social sensors", report power outages online. Therefore, we use Twitter Streaming API to extract real-time tweets containing keywords such as "power outage", "blackout", and "power cuts". An advanced natural language processing technique is proposed to identify the geo-locations associated with this power outage data. The detected tweets are visualized as a color-coded state and a county US map based on the number of outage tweets

Monitoring and optimization of ATLAS Tier 2 center GoeGrid

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00219638; Quadt, Arnulf; Yahyapour, Ramin

The demand on computational and storage resources is growing along with the amount of information that needs to be processed and preserved. In order to ease the provisioning of the digital services to the growing number of consumers, more and more distributed computing systems and platforms are actively developed and employed. The building block of the distributed computing infrastructure are single computing centers, similar to the Worldwide LHC Computing Grid, Tier 2 centre GoeGrid. The main motivation of this thesis was the optimization of GoeGrid performance by efficient monitoring. The goal has been achieved by means of the GoeGrid monitoring information analysis. The data analysis approach was based on the adaptive-network-based fuzzy inference system (ANFIS) and machine learning algorithm such as Linear Support Vector Machine (SVM). The main object of the research was the digital service, since availability, reliability and serviceability of the computing platform can be measured according to the const...

RGB–D terrain perception and dense mapping for legged robots

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Belter Dominik

2016-03-01

Full Text Available This paper addresses the issues of unstructured terrain modeling for the purpose of navigation with legged robots. We present an improved elevation grid concept adopted to the specific requirements of a small legged robot with limited perceptual capabilities. We propose an extension of the elevation grid update mechanism by incorporating a formal treatment of the spatial uncertainty. Moreover, this paper presents uncertainty models for a structured light RGB-D sensor and a stereo vision camera used to produce a dense depth map. The model for the uncertainty of the stereo vision camera is based on uncertainty propagation from calibration, through undistortion and rectification algorithms, allowing calculation of the uncertainty of measured 3D point coordinates. The proposed uncertainty models were used for the construction of a terrain elevation map using the Videre Design STOC stereo vision camera and Kinect-like range sensors. We provide experimental verification of the proposed mapping method, and a comparison with another recently published terrain mapping method for walking robots.

Integrating decentralized electrically powered thermal supply systems into a Smart Grid

OpenAIRE

Hasselmann, Maike; Beier, Carsten

2015-01-01

The goal of the project “Smart Region Pellworm” is the establishment and operation of a smart grid with a hybrid energy storage system on the German island of Pellworm. One part of the project is the integration of power-to-heat appliances into the smart grid for demand side management purposes. This paper deals with the prerequisites and lessons learned from the integration of electric night storage heaters into Pellworm's energy management system. Special focus lies on the development of a ...

A design approach for improving the performance of single-grid planar retarding potential analyzers

International Nuclear Information System (INIS)

Davidson, R. L.; Earle, G. D.

2011-01-01

Planar retarding potential analyzers (RPAs) have a long flight history and have been included on numerous spaceflight missions including Dynamics Explorer, the Defense Meteorological Satellite Program, and the Communications/Navigation Outage Forecast System. RPAs allow for simultaneous measurement of plasma composition, density, temperature, and the component of the velocity vector normal to the aperture plane. Internal conductive grids are used to approximate ideal potential planes within the instrument, but these grids introduce perturbations to the potential map inside the RPA and cause errors in the measurement of the parameters listed above. A numerical technique is presented herein for minimizing these grid errors for a specific mission by varying the depth and spacing of the grid wires. The example mission selected concentrates on plasma dynamics near the sunset terminator in the equatorial region. The international reference ionosphere model is used to discern the average conditions expected for this mission, and a numerical model of the grid-particle interaction is used to choose a grid design that will best fulfill the mission goals.

Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data

Science.gov (United States)

Montesano, P. M.; Cook, B. D.; Sun, G.; Simard, M.; Zhang, Z.; Nelson, R. F.; Ranson, K. J.; Lutchke, S.; Blair, J. B.

2012-01-01

The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM in advanced metering infrastructure of smart grid.

Directory of Open Access Journals (Sweden)

Yuancheng Li

Full Text Available Advanced Metering Infrastructure (AMI realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

Gridded Species Distribution, Version 1: Global Amphibians Presence Grids

Data.gov (United States)

National Aeronautics and Space Administration — The Global Amphibians Presence Grids of the Gridded Species Distribution, Version 1 is a reclassified version of the original grids of amphibian species distribution...

Brain mapping in tumors: intraoperative or extraoperative?

Science.gov (United States)

Duffau, Hugues

2013-12-01

In nontumoral epilepsy surgery, the main goal for all preoperative investigation is to first determine the epileptogenic zone, and then to analyze its relation to eloquent cortex, in order to control seizures while avoiding adverse postoperative neurologic outcome. To this end, in addition to neuropsychological assessment, functional neuroimaging and scalp electroencephalography, extraoperative recording, and electrical mapping, especially using subdural strip- or grid-electrodes, has been reported extensively. Nonetheless, in tumoral epilepsy surgery, the rationale is different. Indeed, the first aim is rather to maximize the extent of tumor resection while minimizing postsurgical morbidity, in order to increase the median survival as well as to preserve quality of life. As a consequence, as frequently seen in infiltrating tumors such as gliomas, where these lesions not only grow but also migrate along white matter tracts, the resection should be performed according to functional boundaries both at cortical and subcortical levels. With this in mind, extraoperative mapping by strips/grids is often not sufficient in tumoral surgery, since in essence, it allows study of the cortex but cannot map subcortical pathways. Therefore, intraoperative electrostimulation mapping, especially in awake patients, is more appropriate in tumor surgery, because this technique allows real-time detection of areas crucial for cerebral functions--eloquent cortex and fibers--throughout the resection. In summary, rather than choosing one or the other of different mapping techniques, methodology should be adapted to each pathology, that is, extraoperative mapping in nontumoral epilepsy surgery and intraoperative mapping in tumoral surgery. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.

A methodology toward manufacturing grid-based virtual enterprise operation platform

Science.gov (United States)

Tan, Wenan; Xu, Yicheng; Xu, Wei; Xu, Lida; Zhao, Xianhua; Wang, Li; Fu, Liuliu

2010-08-01

Virtual enterprises (VEs) have become one of main types of organisations in the manufacturing sector through which the consortium companies organise their manufacturing activities. To be competitive, a VE relies on the complementary core competences among members through resource sharing and agile manufacturing capacity. Manufacturing grid (M-Grid) is a platform in which the production resources can be shared. In this article, an M-Grid-based VE operation platform (MGVEOP) is presented as it enables the sharing of production resources among geographically distributed enterprises. The performance management system of the MGVEOP is based on the balanced scorecard and has the capacity of self-learning. The study shows that a MGVEOP can make a semi-automated process possible for a VE, and the proposed MGVEOP is efficient and agile.

Influence Model Assisted Learning Cycle Mind Map to Achievement Physics Laboratory Judging from the performance Grade VIII SMPN 1 Rejoso Pasuruan

OpenAIRE

Ary Analisa Rahma

2014-01-01

Pengaruh Model Siklus Belajar Berbantuan Mind Map terhadap Prestasi Belajar Fisika Ditinjau dari Kinerja Laboratorium Siswa Kelas VIII SMPN 1 Rejoso Kabupaten Pasuruan Abstract: This study aimed to examine the effect of the learning cycle models aided the mind map on the learning achievement in terms of the performance of laboratory physics class VIII student on light material in SMP Negeri 1 Rejoso Pasuruan. This study is a quasi-experimental research. The research design used is a 2 x 2...