WorldWideScience

Sample records for learning grid maps

  1. Grids in topographic maps reduce distortions in the recall of learned object locations.

    Science.gov (United States)

    Edler, Dennis; Bestgen, Anne-Kathrin; Kuchinke, Lars; Dickmann, Frank

    2014-01-01

    To date, it has been shown that cognitive map representations based on cartographic visualisations are systematically distorted. The grid is a traditional element of map graphics that has rarely been considered in research on perception-based spatial distortions. Grids do not only support the map reader in finding coordinates or locations of objects, they also provide a systematic structure for clustering visual map information ("spatial chunks"). The aim of this study was to examine whether different cartographic kinds of grids reduce spatial distortions and improve recall memory for object locations. Recall performance was measured as both the percentage of correctly recalled objects (hit rate) and the mean distance errors of correctly recalled objects (spatial accuracy). Different kinds of grids (continuous lines, dashed lines, crosses) were applied to topographic maps. These maps were also varied in their type of characteristic areas (LANDSCAPE) and different information layer compositions (DENSITY) to examine the effects of map complexity. The study involving 144 participants shows that all experimental cartographic factors (GRID, LANDSCAPE, DENSITY) improve recall performance and spatial accuracy of learned object locations. Overlaying a topographic map with a grid significantly reduces the mean distance errors of correctly recalled map objects. The paper includes a discussion of a square grid's usefulness concerning object location memory, independent of whether the grid is clearly visible (continuous or dashed lines) or only indicated by crosses.

  2. Allegheny County Map Index Grid

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — Map Index Sheets from Block and Lot Grid of Property Assessment and based on aerial photography, showing 1983 datum with solid line and NAD 27 with 5 second grid...

  3. Spiking neurons in a hierarchical self-organizing map model can learn to develop spatial and temporal properties of entorhinal grid cells and hippocampal place cells.

    Directory of Open Access Journals (Sweden)

    Praveen K Pilly

    Full Text Available Medial entorhinal grid cells and hippocampal place cells provide neural correlates of spatial representation in the brain. A place cell typically fires whenever an animal is present in one or more spatial regions, or places, of an environment. A grid cell typically fires in multiple spatial regions that form a regular hexagonal grid structure extending throughout the environment. Different grid and place cells prefer spatially offset regions, with their firing fields increasing in size along the dorsoventral axes of the medial entorhinal cortex and hippocampus. The spacing between neighboring fields for a grid cell also increases along the dorsoventral axis. This article presents a neural model whose spiking neurons operate in a hierarchy of self-organizing maps, each obeying the same laws. This spiking GridPlaceMap model simulates how grid cells and place cells may develop. It responds to realistic rat navigational trajectories by learning grid cells with hexagonal grid firing fields of multiple spatial scales and place cells with one or more firing fields that match neurophysiological data about these cells and their development in juvenile rats. The place cells represent much larger spaces than the grid cells, which enable them to support navigational behaviors. Both self-organizing maps amplify and learn to categorize the most frequent and energetic co-occurrences of their inputs. The current results build upon a previous rate-based model of grid and place cell learning, and thus illustrate a general method for converting rate-based adaptive neural models, without the loss of any of their analog properties, into models whose cells obey spiking dynamics. New properties of the spiking GridPlaceMap model include the appearance of theta band modulation. The spiking model also opens a path for implementation in brain-emulating nanochips comprised of networks of noisy spiking neurons with multiple-level adaptive weights for controlling autonomous

  4. How entorhinal grid cells may learn multiple spatial scales from a dorsoventral gradient of cell response rates in a self-organizing map.

    Directory of Open Access Journals (Sweden)

    Stephen Grossberg

    Full Text Available Place cells in the hippocampus of higher mammals are critical for spatial navigation. Recent modeling clarifies how this may be achieved by how grid cells in the medial entorhinal cortex (MEC input to place cells. Grid cells exhibit hexagonal grid firing patterns across space in multiple spatial scales along the MEC dorsoventral axis. Signals from grid cells of multiple scales combine adaptively to activate place cells that represent much larger spaces than grid cells. But how do grid cells learn to fire at multiple positions that form a hexagonal grid, and with spatial scales that increase along the dorsoventral axis? In vitro recordings of medial entorhinal layer II stellate cells have revealed subthreshold membrane potential oscillations (MPOs whose temporal periods, and time constants of excitatory postsynaptic potentials (EPSPs, both increase along this axis. Slower (faster subthreshold MPOs and slower (faster EPSPs correlate with larger (smaller grid spacings and field widths. A self-organizing map neural model explains how the anatomical gradient of grid spatial scales can be learned by cells that respond more slowly along the gradient to their inputs from stripe cells of multiple scales, which perform linear velocity path integration. The model cells also exhibit MPO frequencies that covary with their response rates. The gradient in intrinsic rhythmicity is thus not compelling evidence for oscillatory interference as a mechanism of grid cell firing. A response rate gradient combined with input stripe cells that have normalized receptive fields can reproduce all known spatial and temporal properties of grid cells along the MEC dorsoventral axis. This spatial gradient mechanism is homologous to a gradient mechanism for temporal learning in the lateral entorhinal cortex and its hippocampal projections. Spatial and temporal representations may hereby arise from homologous mechanisms, thereby embodying a mechanistic "neural relativity" that

  5. 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...

  6. 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...

  7. Mapping of grid faults and grid codes[Wind turbines

    Energy Technology Data Exchange (ETDEWEB)

    Iov, F. [Aalborg Univ., Inst. of Energy Technology (Denmark); Hansen, Anca D.; Soerensen, Poul; Cutululis, N.A. [Risoe National Lab. - DTU, Wind Enegy Dept., Roskilde (Denmark)

    2007-06-15

    The objective of this project is to investigate into the consequences of the new grid connection requirements for the fatigue and extreme 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 for such investigations. The grid connection requirements for wind turbines have increased significantly during the last 5-10 years. Especially the requirements for wind turbines to stay connected to the grid during and after voltage sags, imply potential challenges in the design of wind turbines. These requirements pose 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' impact on the wind turbines' lifetime are defined. The goal of this report is to present a mapping of different grid fault types and their frequency in different countries. The report provides also a detailed overview of the Low Voltage Ride-Through Capabilities for wind turbines in different relevant countries. The most relevant study cases for the quantification of the loads' impact on the wind turbines' lifetime are defined. (au)

  8. Visual SLAM Using Variance Grid Maps

    Science.gov (United States)

    Howard, Andrew B.; Marks, Tim K.

    2011-01-01

    An algorithm denoted Gamma-SLAM performs further processing, in real time, of preprocessed digitized images acquired by a stereoscopic pair of electronic cameras aboard an off-road robotic ground vehicle to build accurate maps of the terrain and determine the location of the vehicle with respect to the maps. Part of the name of the algorithm reflects the fact that the process of building the maps and determining the location with respect to them is denoted simultaneous localization and mapping (SLAM). Most prior real-time SLAM algorithms have been limited in applicability to (1) systems equipped with scanning laser range finders as the primary sensors in (2) indoor environments (or relatively simply structured outdoor environments). The few prior vision-based SLAM algorithms have been feature-based and not suitable for real-time applications and, hence, not suitable for autonomous navigation on irregularly structured terrain. The Gamma-SLAM algorithm incorporates two key innovations: Visual odometry (in contradistinction to wheel odometry) is used to estimate the motion of the vehicle. An elevation variance map (in contradistinction to an occupancy or an elevation map) is used to represent the terrain. The Gamma-SLAM algorithm makes use of a Rao-Blackwellized particle filter (RBPF) from Bayesian estimation theory for maintaining a distribution over poses and maps. The core idea of the RBPF approach is that the SLAM problem can be factored into two parts: (1) finding the distribution over robot trajectories, and (2) finding the map conditioned on any given trajectory. The factorization involves the use of a particle filter in which each particle encodes both a possible trajectory and a map conditioned on that trajectory. The base estimate of the trajectory is derived from visual odometry, and the map conditioned on that trajectory is a Cartesian grid of elevation variances. In comparison with traditional occupancy or elevation grid maps, the grid elevation variance

  9. Dedicated Filter for Robust Occupancy Grid Mapping

    Directory of Open Access Journals (Sweden)

    KS Nagla

    2015-03-01

    Full Text Available Sensor based perception of the environment is an emerging area of the mobile robot research where sensors play a pivotal role. For autonomous mobile robots, the fundamental requirement is the convergent of the range information in to high level internal representation. Internal representation in the form of occupancy grid is commonly used in autonomous mobile robots due to its various advantages. There are several sensors such as vision sensor, laser rage finder, and ultrasonic and infrared sensors etc. play roles in mapping. However the sensor information failure, sensor inaccuracies, noise, and slow response are the major causes of an error in the mapping. To improve the reliability of the mobile robot mapping multisensory data fusion is considered as an optimal solution. This paper presents a novel architecture of sensor fusion frame work in which a dedicated filter (DF is proposed to increase the robustness of the occupancy grid for indoor environment. The technique has been experimentally verified for different indoor test environments. The proposed configuration shows improvement in the occupancy grid with the implementation of dedicated filters.

  10. Probabilistic Learning by Rodent Grid Cells.

    Science.gov (United States)

    Cheung, Allen

    2016-10-01

    Mounting evidence shows mammalian brains are probabilistic computers, but the specific cells involved remain elusive. Parallel research suggests that grid cells of the mammalian hippocampal formation are fundamental to spatial cognition but their diverse response properties still defy explanation. No plausible model exists which explains stable grids in darkness for twenty minutes or longer, despite being one of the first results ever published on grid cells. Similarly, no current explanation can tie together grid fragmentation and grid rescaling, which show very different forms of flexibility in grid responses when the environment is varied. Other properties such as attractor dynamics and grid anisotropy seem to be at odds with one another unless additional properties are assumed such as a varying velocity gain. Modelling efforts have largely ignored the breadth of response patterns, while also failing to account for the disastrous effects of sensory noise during spatial learning and recall, especially in darkness. Here, published electrophysiological evidence from a range of experiments are reinterpreted using a novel probabilistic learning model, which shows that grid cell responses are accurately predicted by a probabilistic learning process. Diverse response properties of probabilistic grid cells are statistically indistinguishable from rat grid cells across key manipulations. A simple coherent set of probabilistic computations explains stable grid fields in darkness, partial grid rescaling in resized arenas, low-dimensional attractor grid cell dynamics, and grid fragmentation in hairpin mazes. The same computations also reconcile oscillatory dynamics at the single cell level with attractor dynamics at the cell ensemble level. Additionally, a clear functional role for boundary cells is proposed for spatial learning. These findings provide a parsimonious and unified explanation of grid cell function, and implicate grid cells as an accessible neuronal population

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. The Construction of an Ontology-Based Ubiquitous Learning Grid

    Science.gov (United States)

    Liao, Ching-Jung; Chou, Chien-Chih; Yang, Jin-Tan David

    2009-01-01

    The purpose of this study is to incorporate adaptive ontology into ubiquitous learning grid to achieve seamless learning environment. Ubiquitous learning grid uses ubiquitous computing environment to infer and determine the most adaptive learning contents and procedures in anytime, any place and with any device. To achieve the goal, an…

  16. 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.

  17. Coordinated learning of grid cell and place cell spatial and temporal properties: multiple scales, attention and oscillations.

    Science.gov (United States)

    Grossberg, Stephen; Pilly, Praveen K

    2014-02-05

    A neural model proposes how entorhinal grid cells and hippocampal place cells may develop as spatial categories in a hierarchy of self-organizing maps (SOMs). The model responds to realistic rat navigational trajectories by learning both grid cells with hexagonal grid firing fields of multiple spatial scales, and place cells with one or more firing fields, that match neurophysiological data about their development in juvenile rats. Both grid and place cells can develop by detecting, learning and remembering the most frequent and energetic co-occurrences of their inputs. The model's parsimonious properties include: similar ring attractor mechanisms process linear and angular path integration inputs that drive map learning; the same SOM mechanisms can learn grid cell and place cell receptive fields; and the learning of the dorsoventral organization of multiple spatial scale modules through medial entorhinal cortex to hippocampus (HC) may use mechanisms homologous to those for temporal learning through lateral entorhinal cortex to HC ('neural relativity'). The model clarifies how top-down HC-to-entorhinal attentional mechanisms may stabilize map learning, simulates how hippocampal inactivation may disrupt grid cells, and explains data about theta, beta and gamma oscillations. The article also compares the three main types of grid cell models in the light of recent data.

  18. 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.

  19. A Hierarchical and Distributed Approach for Mapping Large Applications to Heterogeneous Grids using Genetic Algorithms

    Science.gov (United States)

    Sanyal, Soumya; Jain, Amit; Das, Sajal K.; Biswas, Rupak

    2003-01-01

    In this paper, we propose a distributed approach for mapping a single large application to a heterogeneous grid environment. To minimize the execution time of the parallel application, we distribute the mapping overhead to the available nodes of the grid. This approach not only provides a fast mapping of tasks to resources but is also scalable. We adopt a hierarchical grid model and accomplish the job of mapping tasks to this topology using a scheduler tree. Results show that our three-phase algorithm provides high quality mappings, and is fast and scalable.

  20. Digitizing geographic data with GRIDOT; a generalized program for drawing overlay grids in various map projections

    International Nuclear Information System (INIS)

    Edwards, R.G.; Durfee, R.C.

    1976-09-01

    The GRIDOT computer program draws overlay grids on a Calcomp plotter for use in digitizing information from maps, rectified aerial photographs, and other sources of spatially distributed data related to regional environmental problems. The options of the program facilitate use of the overlays with standard maps and map projections of the continental United States. The overlay grid may be defined as a latitude-longitude grid (geodetic grid), a Universal Transverse Mercator Grid, or one of the standard state-plane coordinate system grids. The map for which the overlay is intended may be in an Albers Equal Area projection, a Lambert Conformal projection, a Polyconic projection, a Transverse Mercator projection, a Universal Transverse Mercator projection, or any of the standard state-plane projections

  1. The smart grid research network: Road map for Smart Grid research, development and demonstration up to 2020

    Energy Technology Data Exchange (ETDEWEB)

    Troi, A. [Technical Univ. of Denmark. DTU Electrical Engineering, DTU Risoe Campus, Roskilde (Denmark); Noerregaard Joergensen, B. [Syddansk Univ. (SDU), Odense (Denmark); Mahler Larsen, E. [Technical Univ. of Denmark. DTU Electrical Engineering, Kgs. Lyngby (Denmark)] [and others

    2013-01-15

    This road map is a result of part-recommendation no. 25 in 'MAIN REPORT - The Smart Grid Network's recommendations', written by the Smart Grid Network for the Danish Ministry of Climate, Energy and Building in October 2011. This part-recommendation states: ''Part-recommendation 25 - A road map for Smart Grid research, development and demonstration It is recommended that the electricity sector invite the Ministry to participate in the creation of a road map to ensure that solutions are implemented and coordinated with related policy areas. The sector should also establish a fast-acting working group with representatives from universities, distribution companies and the electric industry, in order to produce a mutual, binding schedule for the RDD of the Smart Grid in Denmark. Time prioritisation of part-recommendation: 2011-2012 Responsibility for implementation of part-recommendation: Universities, along with relevant electric-industry actors, should establish a working group for the completion of a consolidated road map by the end of 2012.'' In its work on this report, the Smart Grid Research Network has focused particularly on part-recommendations 26, 27 and 28 in 'MAIN REPORT - The Smart Grid Network's recommendations', which relate to strengthening and marketing the research infrastructure that will position Denmark as the global hub for Smart Grid development; strengthening basic research into the complex relationships in electric systems with large quantities of independent parties; and improved understanding of consumer behaviour and social economics. Naturally the work has spread to related areas along the way. The work has been conducted by the Smart Grid Research Network. (Author)

  2. 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.

  3. True-3D accentuating of grids and streets in urban topographic maps enhances human object location memory.

    Directory of Open Access Journals (Sweden)

    Dennis Edler

    Full Text Available Cognitive representations of learned map information are subject to systematic distortion errors. Map elements that divide a map surface into regions, such as content-related linear symbols (e.g. streets, rivers, railway systems or additional artificial layers (coordinate grids, provide an orientation pattern that can help users to reduce distortions in their mental representations. In recent years, the television industry has started to establish True-3D (autostereoscopic displays as mass media. These modern displays make it possible to watch dynamic and static images including depth illusions without additional devices, such as 3D glasses. In these images, visual details can be distributed over different positions along the depth axis. Some empirical studies of vision research provided first evidence that 3D stereoscopic content attracts higher attention and is processed faster. So far, the impact of True-3D accentuating has not yet been explored concerning spatial memory tasks and cartography. This paper reports the results of two empirical studies that focus on investigations whether True-3D accentuating of artificial, regular overlaying line features (i.e. grids and content-related, irregular line features (i.e. highways and main streets in official urban topographic maps (scale 1/10,000 further improves human object location memory performance. The memory performance is measured as both the percentage of correctly recalled object locations (hit rate and the mean distances of correctly recalled objects (spatial accuracy. It is shown that the True-3D accentuating of grids (depth offset: 5 cm significantly enhances the spatial accuracy of recalled map object locations, whereas the True-3D emphasis of streets significantly improves the hit rate of recalled map object locations. These results show the potential of True-3D displays for an improvement of the cognitive representation of learned cartographic information.

  4. 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.

  5. Reinforcement Learning Based Novel Adaptive Learning Framework for Smart Grid Prediction

    Directory of Open Access Journals (Sweden)

    Tian Li

    2017-01-01

    Full Text Available Smart grid is a potential infrastructure to supply electricity demand for end users in a safe and reliable manner. With the rapid increase of the share of renewable energy and controllable loads in smart grid, the operation uncertainty of smart grid has increased briskly during recent years. The forecast is responsible for the safety and economic operation of the smart grid. However, most existing forecast methods cannot account for the smart grid due to the disabilities to adapt to the varying operational conditions. In this paper, reinforcement learning is firstly exploited to develop an online learning framework for the smart grid. With the capability of multitime scale resolution, wavelet neural network has been adopted in the online learning framework to yield reinforcement learning and wavelet neural network (RLWNN based adaptive learning scheme. The simulations on two typical prediction problems in smart grid, including wind power prediction and load forecast, validate the effectiveness and the scalability of the proposed RLWNN based learning framework and algorithm.

  6. 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.

  7. 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.

  8. 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...

  9. Integrated Multi-Scale Data Analytics and Machine Learning for the Distribution Grid and Building-to-Grid Interface

    Energy Technology Data Exchange (ETDEWEB)

    Stewart, Emma M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hendrix, Val [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chertkov, Michael [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Deka, Deepjyoti [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-03-16

    This white paper introduces the application of advanced data analytics to the modernized grid. In particular, we consider the field of machine learning and where it is both useful, and not useful, for the particular field of the distribution grid and buildings interface. While analytics, in general, is a growing field of interest, and often seen as the golden goose in the burgeoning distribution grid industry, its application is often limited by communications infrastructure, or lack of a focused technical application. Overall, the linkage of analytics to purposeful application in the grid space has been limited. In this paper we consider the field of machine learning as a subset of analytical techniques, and discuss its ability and limitations to enable the future distribution grid and the building-to-grid interface. To that end, we also consider the potential for mixing distributed and centralized analytics and the pros and cons of these approaches. Machine learning is a subfield of computer science that studies and constructs algorithms that can learn from data and make predictions and improve forecasts. Incorporation of machine learning in grid monitoring and analysis tools may have the potential to solve data and operational challenges that result from increasing penetration of distributed and behind-the-meter energy resources. There is an exponentially expanding volume of measured data being generated on the distribution grid, which, with appropriate application of analytics, may be transformed into intelligible, actionable information that can be provided to the right actors – such as grid and building operators, at the appropriate time to enhance grid or building resilience, efficiency, and operations against various metrics or goals – such as total carbon reduction or other economic benefit to customers. While some basic analysis into these data streams can provide a wealth of information, computational and human boundaries on performing the analysis

  10. 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

  11. Frequently updated noise threat maps created with use of supercomputing grid

    Directory of Open Access Journals (Sweden)

    Szczodrak Maciej

    2014-09-01

    Full Text Available An innovative supercomputing grid services devoted to noise threat evaluation were presented. The services described in this paper concern two issues, first is related to the noise mapping, while the second one focuses on assessment of the noise dose and its influence on the human hearing system. The discussed serviceswere developed within the PL-Grid Plus Infrastructure which accumulates Polish academic supercomputer centers. Selected experimental results achieved by the usage of the services proposed were presented. The assessment of the environmental noise threats includes creation of the noise maps using either ofline or online data, acquired through a grid of the monitoring stations. A concept of estimation of the source model parameters based on the measured sound level for the purpose of creating frequently updated noise maps was presented. Connecting the noise mapping grid service with a distributed sensor network enables to automatically update noise maps for a specified time period. Moreover, a unique attribute of the developed software is the estimation of the auditory effects evoked by the exposure to noise. The estimation method uses a modified psychoacoustic model of hearing and is based on the calculated noise level values and on the given exposure period. Potential use scenarios of the grid services for research or educational purpose were introduced. Presentation of the results of predicted hearing threshold shift caused by exposure to excessive noise can raise the public awareness of the noise threats.

  12. 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

  13. 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...

  14. Sparse Jacobian construction for mapped grid visco-resistive magnetohydrodynamics

    KAUST Repository

    Reynolds, Daniel R.; Samtaney, Ravi

    2012-01-01

    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

  15. Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

    Directory of Open Access Journals (Sweden)

    R. J. Andres

    2016-12-01

    Full Text Available Due to a current lack of physical measurements at appropriate spatial and temporal scales, all current global maps and distributions of fossil fuel carbon dioxide (FFCO2 emissions use one or more proxies to distribute those emissions. These proxies and distribution schemes introduce additional uncertainty into these maps. This paper examines the uncertainty associated with the magnitude of gridded FFCO2 emissions. This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughout this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty. The results of the uncertainty analysis reveal a range of 4–190 %, with an average of 120 % (2σ for populated and FFCO2-emitting grid spaces over annual timescales. This paper also describes a methodological change specific to the creation of the Carbon Dioxide Information Analysis Center (CDIAC FFCO2 emission maps: the change from a temporally fixed population proxy to a temporally varying population proxy.

  16. Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

    Science.gov (United States)

    Andres, Robert J.; Boden, Thomas A.; Higdon, David M.

    2016-12-01

    Due to a current lack of physical measurements at appropriate spatial and temporal scales, all current global maps and distributions of fossil fuel carbon dioxide (FFCO2) emissions use one or more proxies to distribute those emissions. These proxies and distribution schemes introduce additional uncertainty into these maps. This paper examines the uncertainty associated with the magnitude of gridded FFCO2 emissions. This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughout this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty. The results of the uncertainty analysis reveal a range of 4-190 %, with an average of 120 % (2σ) for populated and FFCO2-emitting grid spaces over annual timescales. This paper also describes a methodological change specific to the creation of the Carbon Dioxide Information Analysis Center (CDIAC) FFCO2 emission maps: the change from a temporally fixed population proxy to a temporally varying population proxy.

  17. 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.

  18. 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 ...

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Structure Mapping for Social Learning.

    Science.gov (United States)

    Christie, Stella

    2017-07-01

    Analogical reasoning is a foundational tool for human learning, allowing learners to recognize relational structures in new events and domains. Here I sketch some grounds for understanding and applying analogical reasoning in social learning. The social world is fundamentally characterized by relations between people, with common relational structures-such as kinships and social hierarchies-forming social units that dictate social behaviors. Just as young learners use analogical reasoning for learning relational structures in other domains-spatial relations, verbs, relational categories-analogical reasoning ought to be a useful cognitive tool for acquiring social relations and structures. Copyright © 2017 Cognitive Science Society, Inc.

  4. 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

  5. Learning to Map and Mapping to Learn Our Students' Worlds

    Science.gov (United States)

    Rubel, Laurie H.; Chu, Haiwen; Shookhoff, Lauren

    2011-01-01

    The National Council of Teachers of Mathematics (NCTM), through its Connections Standard, highlights the importance of "the opportunity for students to experience mathematics in a context." Seeing how mathematics can be used to describe real-world phenomena can motivate students to learn more mathematics. Connecting mathematics to the real world…

  6. Mapping the University Learning Environment.

    Science.gov (United States)

    Mitchell, Alice A.; Sergent, Marie T.; Sedlacek, William E.

    1997-01-01

    Demonstrates how perceptual mapping techniques can be used to examine campus perceptions of African American and White students at a predominantly White institution. Reports on data collection methods and influencing factors, such as familiar locations. Provides results of a survey of 411 students, detailing initial perceptions and the validity of…

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  17. 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.

  18. 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.

  19. 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...

  20. 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)

  1. An efficient cardiac mapping strategy for radiofrequency catheter ablation with active learning.

    Science.gov (United States)

    Feng, Yingjing; Guo, Ziyan; Dong, Ziyang; Zhou, Xiao-Yun; Kwok, Ka-Wai; Ernst, Sabine; Lee, Su-Lin

    2017-07-01

    A major challenge in radiofrequency catheter ablation procedures is the voltage and activation mapping of the endocardium, given a limited mapping time. By learning from expert interventional electrophysiologists (operators), while also making use of an active-learning framework, guidance on performing cardiac voltage mapping can be provided to novice operators or even directly to catheter robots. A learning from demonstration (LfD) framework, based upon previous cardiac mapping procedures performed by an expert operator, in conjunction with Gaussian process (GP) model-based active learning, was developed to efficiently perform voltage mapping over right ventricles (RV). The GP model was used to output the next best mapping point, while getting updated towards the underlying voltage data pattern as more mapping points are taken. A regularized particle filter was used to keep track of the kernel hyperparameter used by GP. The travel cost of the catheter tip was incorporated to produce time-efficient mapping sequences. The proposed strategy was validated on a simulated 2D grid mapping task, with leave-one-out experiments on 25 retrospective datasets, in an RV phantom using the Stereotaxis Niobe ® remote magnetic navigation system, and on a tele-operated catheter robot. In comparison with an existing geometry-based method, regression error was reduced and was minimized at a faster rate over retrospective procedure data. A new method of catheter mapping guidance has been proposed based on LfD and active learning. The proposed method provides real-time guidance for the procedure, as well as a live evaluation of mapping sufficiency.

  2. 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.

  3. 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.

  4. 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.…

  5. 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.

  6. 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.

  7. 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,

  8. 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...

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. 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…

  4. 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…

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

    Directory of Open Access Journals (Sweden)

    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.

  6. 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.

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  9. 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....

  10. 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 ...

  11. Global map of lithosphere thermal thickness on a 1 deg x 1 deg grid - digitally available

    Science.gov (United States)

    Artemieva, Irina

    2014-05-01

    This presentation reports a 1 deg ×1 deg global thermal model for the continental lithosphere (TC1). The model is digitally available from the author's web-site: www.lithosphere.info. Geotherms for continental terranes of different ages (early Archean to present) are constrained by reliable data on borehole heat flow measurements (Artemieva and Mooney, 2001), checked with the original publications for data quality, and corrected for paleo-temperature effects where needed. These data are supplemented by cratonic geotherms based on xenolith data. Since heat flow measurements cover not more than half of the continents, the remaining areas (ca. 60% of the continents) are filled by the statistical numbers derived from the thermal model constrained by borehole data. Continental geotherms are statistically analyzed as a function of age and are used to estimate lithospheric temperatures in continental regions with no or low quality heat flow data. This analysis requires knowledge of lithosphere age globally. A compilation of tectono-thermal ages of lithospheric terranes on a 1 deg × 1 deg grid forms the basis for the statistical analysis. It shows that, statistically, lithospheric thermal thickness z (in km) depends on tectono-thermal age t (in Ma) as: z=0.04t+93.6. This relationship formed the basis for a global thermal model of the continental lithosphere (TC1). Statistical analysis of continental geotherms also reveals that this relationship holds for the Archean cratons in general, but not in detail. Particularly, thick (more than 250 km) lithosphere is restricted solely to young Archean terranes (3.0-2.6 Ga), while in old Archean cratons (3.6-3.0 Ga) lithospheric roots do not extend deeper than 200-220 km. The TC1 model is presented by a set of maps, which show significant thermal heterogeneity within continental upper mantle. The strongest lateral temperature variations (as large as 800 deg C) are typical of the shallow mantle (depth less than 100 km). A map of the

  12. 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.

  13. 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

  14. 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.

  15. Mind Maps as a Lifelong Learning Tool

    Science.gov (United States)

    Erdem, Aliye

    2017-01-01

    Mind map, which was developed by Tony Buzan as a note-taking technique, is an application which has the power of uncovering the thoughts which the brain has about a subject from different viewpoints and which activate the right and left lobes of the brain together as an alternative to linear thought. It is known that mind maps have benefits such…

  16. 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.

  17. 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

  18. 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.

  19. 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 (Zeff), relative electron density (ρe), mean excitation energy (Ix), 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

  20. 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.

  1. 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...

  2. Learning concept mappings from instance similarity

    NARCIS (Netherlands)

    Wang, S.; Englebienne, G.; Schlobach, S.

    2008-01-01

    Finding mappings between compatible ontologies is an important but difficult open problem. Instance-based methods for solving this problem have the advantage of focusing on the most active parts of the ontologies and reflect concept semantics as they are actually being used. However such methods

  3. 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.

  4. 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

  5. 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.

  6. 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....

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  9. Learn to Lead: Mapping Workplace Learning of School Leaders

    Science.gov (United States)

    Hulsbos, Frank Arnoud; Evers, Arnoud Theodoor; Kessels, Joseph Willem Marie

    2016-01-01

    In recent years policy makers' interest in the professional development of school leaders has grown considerably. Although we know some aspect of formal educational programs for school leaders, little is known about school leaders' incidental and non-formal learning in the workplace. This study aims to grasp what workplace learning activities…

  10. Free Space Computation From Stochastic Occupancy Grids Based On Iconic Kalman Filtered Disparity Maps

    DEFF Research Database (Denmark)

    Høilund, Carsten; Moeslund, Thomas B.; Madsen, Claus B.

    2010-01-01

    This paper presents a method for determining the free space in a scene as viewed by a vehicle-mounted camera. Using disparity maps from a stereo camera and known camera motion, the disparity maps are first filtered by an iconic Kalman filter, operating on each pixel individually, thereby reducing...

  11. 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

  12. 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…

  13. 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.…

  14. Efficient Redundancy Techniques in Cloud and Desktop Grid Systems using MAP/G/c-type Queues

    Science.gov (United States)

    Chakravarthy, Srinivas R.; Rumyantsev, Alexander

    2018-03-01

    Cloud computing is continuing to prove its flexibility and versatility in helping industries and businesses as well as academia as a way of providing needed computing capacity. As an important alternative to cloud computing, desktop grids allow to utilize the idle computer resources of an enterprise/community by means of distributed computing system, providing a more secure and controllable environment with lower operational expenses. Further, both cloud computing and desktop grids are meant to optimize limited resources and at the same time to decrease the expected latency for users. The crucial parameter for optimization both in cloud computing and in desktop grids is the level of redundancy (replication) for service requests/workunits. In this paper we study the optimal replication policies by considering three variations of Fork-Join systems in the context of a multi-server queueing system with a versatile point process for the arrivals. For services we consider phase type distributions as well as shifted exponential and Weibull. We use both analytical and simulation approach in our analysis and report some interesting qualitative results.

  15. Efficient Redundancy Techniques in Cloud and Desktop Grid Systems using MAP/G/c-type Queues

    Directory of Open Access Journals (Sweden)

    Chakravarthy Srinivas R.

    2018-03-01

    Full Text Available Cloud computing is continuing to prove its flexibility and versatility in helping industries and businesses as well as academia as a way of providing needed computing capacity. As an important alternative to cloud computing, desktop grids allow to utilize the idle computer resources of an enterprise/community by means of distributed computing system, providing a more secure and controllable environment with lower operational expenses. Further, both cloud computing and desktop grids are meant to optimize limited resources and at the same time to decrease the expected latency for users. The crucial parameter for optimization both in cloud computing and in desktop grids is the level of redundancy (replication for service requests/workunits. In this paper we study the optimal replication policies by considering three variations of Fork-Join systems in the context of a multi-server queueing system with a versatile point process for the arrivals. For services we consider phase type distributions as well as shifted exponential and Weibull. We use both analytical and simulation approach in our analysis and report some interesting qualitative results.

  16. Mapping of the lateral flow field in typical subchannels of a support grid with vanes

    International Nuclear Information System (INIS)

    McClusky, Heather L.; Holloway, Mary V.; Conover, Timothy A.; Beasley, Donald E.; Conner, Michael E.; Smith III, L. David

    2003-01-01

    Lateral flow fields in four subchannels of a model rod bundle fuel assembly are measured using particle image velocimetry. Vanes (split-vane pairs) are located on the downstream edge of the support grids in the rod bundle fuel assembly and generate swirling flow. Measurements are acquired at a nominal Reynolds number of 28,000 and for seven streamwise locations ranging from 1.4 to 17.0 hydraulic diameters downstream of the grid. The streamwise development of the lateral flow field is divided into two regions based on the lateral flow structure. In Region I, multiple vortices are present in the flow field and vortex interactions occur. Either a single circular vortex or a hairpin shaped flow structure is formed in Region II. Lateral kinetic energy, maximum lateral velocity, centroid of vorticity, radial profiles of azimuthal velocity, and angular momentum are employed as measures of the streamwise development of the lateral flow field. The particle image velocimetry measurements of the present study are compared with laser doppler velocimetry measurements taken for the identical support grids and flow condition. (author)

  17. 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

  18. Construction of concept maps as tool for Biochemistry learning

    Directory of Open Access Journals (Sweden)

    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

  19. Concept maps and the meaningful learning of science

    Directory of Open Access Journals (Sweden)

    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.

  20. 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.

  1. 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...

  2. 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

  3. Global map of lithosphere thermal thickness on a 1 deg x 1 deg grid - digitally available

    DEFF Research Database (Denmark)

    Artemieva, Irina

    2014-01-01

    with no or low quality heat flow data. This analysis requires knowledge oflithosphere age globally.A compilation of tectono-thermal ages of lithospheric terranes on a 1 deg 1 deg grid forms the basis forthe statistical analysis. It shows that, statistically, lithospheric thermal thickness z (in km) depends......This presentation reports a 1 deg 1 deg global thermal model for the continental lithosphere (TC1). The modelis digitally available from the author’s web-site: www.lithosphere.info.Geotherms for continental terranes of different ages (early Archean to present) are constrained by reliabledata...... on borehole heat flow measurements (Artemieva and Mooney, 2001), checked with the original publicationsfor data quality, and corrected for paleo-temperature effects where needed. These data are supplemented bycratonic geotherms based on xenolith data.Since heat flow measurements cover not more than half...

  4. 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).

  5. 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.

  6. Topological schemas of cognitive maps and spatial learning

    Directory of Open Access Journals (Sweden)

    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.

  7. 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.

  8. Integrating collaborative concept mapping in case based learning

    Directory of Open Access Journals (Sweden)

    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.

  9. 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.

  10. 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

  11. 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...

  12. 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.

  13. 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

  14. 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.

    Directory of Open Access Journals (Sweden)

    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.

  15. Securing Metering Infrastructure of Smart Grid: A Machine Learning and Localization Based Key Management Approach

    Directory of Open Access Journals (Sweden)

    Imtiaz Parvez

    2016-08-01

    Full Text Available In smart cities, advanced metering infrastructure (AMI of the smart grid facilitates automated metering, control and monitoring of power distribution by employing a wireless network. Due to this wireless nature of communication, there exist potential threats to the data privacy in AMI. Decoding the energy consumption reading, injecting false data/command signals and jamming the networks are some hazardous measures against this technology. Since a smart meter possesses limited memory and computational capability, AMI demands a light, but robust security scheme. In this paper, we propose a localization-based key management system for meter data encryption. Data are encrypted by the key associated with the coordinate of the meter and a random key index. The encryption keys are managed and distributed by a trusted third party (TTP. Localization of the meter is proposed by a method based on received signal strength (RSS using the maximum likelihood estimator (MLE. The received packets are decrypted at the control center with the key mapped with the key index and the meter’s coordinates. Additionally, we propose the k-nearest neighbors (kNN algorithm for node/meter authentication, capitalizing further on data transmission security. Finally, we evaluate the security strength of a data packet numerically for our method.

  16. A Multianalyzer Machine Learning Model for Marine Heterogeneous Data Schema Mapping

    Directory of Open Access Journals (Sweden)

    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.

  17. 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

  18. 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.

  19. 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

  20. 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

  1. Multivariate Mapping of Environmental Data Using Extreme Learning Machines

    Science.gov (United States)

    Leuenberger, Michael; Kanevski, Mikhail

    2014-05-01

    In most real cases environmental data are multivariate, highly variable at several spatio-temporal scales, and are generated by nonlinear and complex phenomena. Mapping - spatial predictions of such data, is a challenging problem. Machine learning algorithms, being universal nonlinear tools, have demonstrated their efficiency in modelling of environmental spatial and space-time data (Kanevski et al. 2009). Recently, a new approach in machine learning - Extreme Learning Machine (ELM), has gained a great popularity. ELM is a fast and powerful approach being a part of the machine learning algorithm category. Developed by G.-B. Huang et al. (2006), it follows the structure of a multilayer perceptron (MLP) with one single-hidden layer feedforward neural networks (SLFNs). The learning step of classical artificial neural networks, like MLP, deals with the optimization of weights and biases by using gradient-based learning algorithm (e.g. back-propagation algorithm). Opposed to this optimization phase, which can fall into local minima, ELM generates randomly the weights between the input layer and the hidden layer and also the biases in the hidden layer. By this initialization, it optimizes just the weight vector between the hidden layer and the output layer in a single way. The main advantage of this algorithm is the speed of the learning step. In a theoretical context and by growing the number of hidden nodes, the algorithm can learn any set of training data with zero error. To avoid overfitting, cross-validation method or "true validation" (by randomly splitting data into training, validation and testing subsets) are recommended in order to find an optimal number of neurons. With its universal property and solid theoretical basis, ELM is a good machine learning algorithm which can push the field forward. The present research deals with an extension of ELM to multivariate output modelling and application of ELM to the real data case study - pollution of the sediments in

  2. 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…

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

    Directory of Open Access Journals (Sweden)

    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.

  4. 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...

  5. Machine learning modeling of plant phenology based on coupling satellite and gridded meteorological dataset

    Science.gov (United States)

    Czernecki, Bartosz; Nowosad, Jakub; Jabłońska, Katarzyna

    2018-04-01

    Changes in the timing of plant phenological phases are important proxies in contemporary climate research. However, most of the commonly used traditional phenological observations do not give any coherent spatial information. While consistent spatial data can be obtained from airborne sensors and preprocessed gridded meteorological data, not many studies robustly benefit from these data sources. Therefore, the main aim of this study is to create and evaluate different statistical models for reconstructing, predicting, and improving quality of phenological phases monitoring with the use of satellite and meteorological products. A quality-controlled dataset of the 13 BBCH plant phenophases in Poland was collected for the period 2007-2014. For each phenophase, statistical models were built using the most commonly applied regression-based machine learning techniques, such as multiple linear regression, lasso, principal component regression, generalized boosted models, and random forest. The quality of the models was estimated using a k-fold cross-validation. The obtained results showed varying potential for coupling meteorological derived indices with remote sensing products in terms of phenological modeling; however, application of both data sources improves models' accuracy from 0.6 to 4.6 day in terms of obtained RMSE. It is shown that a robust prediction of early phenological phases is mostly related to meteorological indices, whereas for autumn phenophases, there is a stronger information signal provided by satellite-derived vegetation metrics. Choosing a specific set of predictors and applying a robust preprocessing procedures is more important for final results than the selection of a particular statistical model. The average RMSE for the best models of all phenophases is 6.3, while the individual RMSE vary seasonally from 3.5 to 10 days. Models give reliable proxy for ground observations with RMSE below 5 days for early spring and late spring phenophases. For

  6. 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…

  7. 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…

  8. 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,

  9. 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…

  10. 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,…

  11. 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…

  12. 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…

  13. 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…

  14. 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.

  15. 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.

  16. Mining Concept Maps to Understand University Students' Learning

    Science.gov (United States)

    Yoo, Jin Soung; Cho, Moon-Heum

    2012-01-01

    Concept maps, visual representations of knowledge, are used in an educational context as a way to represent students' knowledge, and identify mental models of students; however there is a limitation of using concept mapping due to its difficulty to evaluate the concept maps. A concept map has a complex structure which is composed of concepts and…

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Unsupervised energy prediction in a smart grid context using reinforcement cross-buildings transfer learning

    NARCIS (Netherlands)

    Mocanu, E.; Nguyen, P.H.; Kling, W.L.; Gibescu, M.

    2016-01-01

    In a future Smart Grid context, increasing challenges in managing the stochastic local energy supply and demand are expected. This increased the need of more accurate energy prediction methods in order to support further complex decision-making processes. Although many methods aiming to predict the

  4. 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.

  5. 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.

  6. 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

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

    Directory of Open Access Journals (Sweden)

    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

  8. 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.

  9. Neural Model with Particle Swarm Optimization Kalman Learning for Forecasting in Smart Grids

    Directory of Open Access Journals (Sweden)

    Alma Y. Alanis

    2013-01-01

    Full Text Available This paper discusses a novel training algorithm for a neural network architecture applied to time series prediction with smart grids applications. The proposed training algorithm is based on an extended Kalman filter (EKF improved using particle swarm optimization (PSO to compute the design parameters. The EKF-PSO-based algorithm is employed to update the synaptic weights of the neural network. The size of the regression vector is determined by means of the Cao methodology. The proposed structure captures more efficiently the complex nature of the wind speed, energy generation, and electrical load demand time series that are constantly monitorated in a smart grid benchmark. The proposed model is trained and tested using real data values in order to show the applicability of the proposed scheme.

  10. 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.

  11. 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

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  14. 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…

  15. 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…

  16. 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…

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

    Directory of Open Access Journals (Sweden)

    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

  18. Semantic Maps Capturing Organization Knowledge in e-Learning

    Science.gov (United States)

    Mavridis, Androklis; Koumpis, Adamantios; Demetriadis, Stavros N.

    e-learning, shows much promise in accessibility and opportunity to learn, due to its asynchronous nature and its ability to transmit knowledge fast and effectively. However without a universal standard for online learning and teaching, many systems are proclaimed as “e-learning-compliant”, offering nothing more than automated services for delivering courses online, providing no additional enhancement to reusability and learner personalization. Hence, the focus is not on providing reusable and learner-centered content, but on developing the technology aspects of e-learning. This current trend has made it crucial to find a more refined definition of what constitutes knowledge in the e-learning context. We propose an e-learning system architecture that makes use of a knowledge model to facilitate continuous dialogue and inquiry-based knowledge learning, by exploiting the full benefits of the semantic web as a medium capable for supplying the web with formalized knowledge.

  19. 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.

  20. Mapping Students Use of Technologies in Problem Based Learning Environments

    DEFF Research Database (Denmark)

    Rongbutsri, Nikorn; Khalid, Md. Saifuddin; Ryberg, Thomas

    2011-01-01

    This paper aims to understand how students use technology to enhance their learning in problem-based learning environments. The research methodology is based on both qualitative and quantitative studies. The results are based on students’ interviews, a survey and students’ reflections in course......-related blog posts; they show that students have positive perceptions toward using technologies in problem-based learning environments....

  1. 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.

  2. 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…

  3. 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…

  4. A Description Grid to Support the Design of Learning Role-Play Games

    Science.gov (United States)

    Mariais, Christelle; Michau, Florence; Pernin, Jean-Philippe

    2012-01-01

    To strengthen the motivation of learners, the professional training sector is focusing more and more on game-based learning. In this context, the authors have become interested in the design of Learning Role-Play Game (LRPG) scenarios. The aim of this article is to improve the designers' confidence in the validity of the game-based learning…

  5. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  7. 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.

  8. 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

  9. A new automatic synthetic aperture radar-based flood mapping application hosted on the European Space Agency's Grid Processing of Demand Fast Access to Imagery environment

    Science.gov (United States)

    Matgen, Patrick; Giustarini, Laura; Hostache, Renaud

    2012-10-01

    This paper introduces an automatic flood mapping application that is hosted on the Grid Processing on Demand (GPOD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver operationally flooded areas using both recent and historical acquisitions of SAR data. Having as a short-term target the flooding-related exploitation of data generated by the upcoming ESA SENTINEL-1 SAR mission, the flood mapping application consists of two building blocks: i) a set of query tools for selecting the "crisis image" and the optimal corresponding "reference image" from the G-POD archive and ii) an algorithm for extracting flooded areas via change detection using the previously selected "crisis image" and "reference image". Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate reference image. Potential users will also be able to apply the implemented flood delineation algorithm. The latter combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. Both algorithms are computationally efficient and operate with minimum data requirements. The case study of the high magnitude flooding event that occurred in July 2007 on the Severn River, UK, and that was observed with a moderateresolution SAR sensor as well as airborne photography highlights the performance of the proposed online application. The flood mapping application on G-POD can be used sporadically, i.e. whenever a major flood event occurs and there is a demand for SAR-based flood extent maps. In the long term, a potential extension of the application could consist in systematically extracting flooded areas from all SAR images acquired on a daily, weekly or monthly basis.

  10. 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.

  11. 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...

  12. Mapping Learning Outcomes and Assignment Tasks for SPIDER Activities

    Directory of Open Access Journals (Sweden)

    Lyn Brodie

    2011-05-01

    Full Text Available Modern engineering programs have to address rapidly changing technical content and have to enable students to develop transferable skills such as critical evaluation, communication skills and lifelong learning. This paper introduces a combined learning and assessment activity that provides students with opportunities to develop and practice their soft skills, but also extends their theoretical knowledge base. Key tasks included self directed inquiry, oral and written communication as well as peer assessment. To facilitate the SPIDER activities (Select, Prepare and Investigate, Discuss, Evaluate, Reflect, a software tool has been implemented in the learning management system Moodle. Evidence shows increased student engagement and better learning outcomes for both transferable as well as technical skills. The study focuses on generalising the relationship between learning outcomes and assignment tasks as well as activities that drive these tasks. Trail results inform the approach. Staff evaluations and their views of assignments and intended learning outcomes also supported this analysis.

  13. 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...

  14. Transferring Road Maps for Learning and Assessment Procedures to Marketing

    Science.gov (United States)

    Salzberger, Thomas

    2011-01-01

    Learning is a lifelong process. It is therefore worthwhile looking at instances where learning takes place outside educational institutions and see how educational principles can be applied there. In a market economy companies have to quest for profit to ensure their long-term survival. In the end, their educational goals have to serve themselves.…

  15. Mobile English Vocabulary Learning Based on Concept-Mapping Strategy

    Science.gov (United States)

    Liu, Pei-Lin

    2016-01-01

    Numerous researchers in education recognize that vocabulary is essential in foreign language learning. However, students often encounter vocabulary that is difficult to remember. Providing effective vocabulary learning strategies is therefore more valuable than teaching students a large amount of vocabulary. The purpose of this study was to…

  16. A Mobile Learning Overview by Timeline and Mind Map

    Science.gov (United States)

    Parsons, David

    2014-01-01

    Mobile learning has been a research topic for some 20 years. Over that time it has encompassed a wide range of concepts, theories, designs, experiments and evaluations. With increasing interest in mobile learning from researchers and practitioners, an accessible overview of this area of research that encapsulates its many facets and features can…

  17. 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.

  18. 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.

  19. Motivating Students' Learning Using Word Association Test and Concept Maps

    Directory of Open Access Journals (Sweden)

    Z. Kostova

    2010-06-01

    Full Text Available The paper presents the effect of a free word association test, content analysis and concept mapping on students’ achievements in human biology. The free word association test was used for revealing the scientific conceptual structures of 8th grade and 12th grade students, around a stimulus word – human being – and for motivating them to study human biology. The stimulus word retrieved a cluster of associations most of which were based on science education and experience. Associations with the stimulus word were analyzed and classified according to predetermined criteria and structured by means of a concept map. The stimulus word ‘human being’ was quantitatively assessed in order to find out the balance between the associations with its different aspects. On the basis of the results some connections between biology and other sciences studying the human being, were worked out. Each new topic in human biology was studied by using content analysis of the textbook and concept mapping as study tools and thus maintaining students’ motivation. Achievements of students were assessed by means of tests, observation and concept maps evaluation. The obtained data was also valuable in clarifying the complex nature of the human being, and confirming the statement that biology cannot answer all questions, concerning human nature. Inferences were made about the word association test combined with content analysis and concept map construction as an educational strategy.

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

    Directory of Open Access Journals (Sweden)

    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.

  1. Learning process mapping heuristics under stochastic sampling overheads

    Science.gov (United States)

    Ieumwananonthachai, Arthur; Wah, Benjamin W.

    1991-01-01

    A statistical method was developed previously for improving process mapping heuristics. The method systematically explores the space of possible heuristics under a specified time constraint. Its goal is to get the best possible heuristics while trading between the solution quality of the process mapping heuristics and their execution time. The statistical selection method is extended to take into consideration the variations in the amount of time used to evaluate heuristics on a problem instance. The improvement in performance is presented using the more realistic assumption along with some methods that alleviate the additional complexity.

  2. 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.

  3. Revisiting the extended spring indices using gridded weather data and machine learning

    Science.gov (United States)

    Mehdipoor, Hamed; Izquierdo-Verdiguier, Emma; Zurita-Milla, Raul

    2016-04-01

    The extended spring indices or SI-x [1] have been successfully used to predict the timing of spring onset at continental scales. The SI-x models were created by combining lilac and honeysuckle volunteered phenological observations, temperature data (from weather stations) and latitudinal information. More precisely, these models use a linear regression to predict the day of year of first leaf and first bloom for these two indicator species. In this contribution we revisit both the data and the method used to calibrate the SI-x models to check whether the addition of new input data or the use of non-linear regression methods could lead to improments in the model outputs. In particular, we use a recently published dataset [2] of volunteered observations on cloned and common lilac over longer period of time (1980-2014) and we replace the weather station data by 54 features derived from Daymet [3], which provides 1 by 1 km gridded estimates of daily weather parameters (maximum and minimum temperatures, precipitation, water vapor pressure, solar radiation, day length, snow water equivalent) for North America. These features consist of both daily weather values and their long- and short-term accumulations and elevation. we also replace the original linear regression by a non-linear method. Specifically, we use random forests to both identify the most important features and to predict the day of year of the first leaf of cloned and common lilacs. Preliminary results confirm the importance of the SI-x features (maximum and minimum temperatures and day length). However, our results show that snow water equivalent and water vapor pressure are also necessary to properly model leaf onset. Regarding the predictions, our results indicate that Random Forests yield comparable results to those produced by the SI-x models (in terms of root mean square error -RMSE). For cloned and common lilac, the models predict the day of year of leafing with 16 and 15 days of accuracy respectively

  4. Using Brain Electrical Activity Mapping to Diagnose Learning Disabilities.

    Science.gov (United States)

    Torello, Michael, W.; Duffy, Frank H.

    1985-01-01

    Cognitive neuroscience assumes that measurement of brain electrical activity should relate to cognition. Brain Electrical Activity Mapping (BEAM), a non-invasive technique, is used to record changes in activity from one brain area to another and is 80 to 90 percent successful in classifying subjects as dyslexic or normal. (MT)

  5. Digital Soil Mapping – A platform for enhancing soil learning.

    Science.gov (United States)

    The expansion of digital infrastructure and tools has generated massive data and information as well as a need for reliable processing and accurate interpretations. Digital Soil Mapping is no exception in that it has provided opportunities for professionals and the public to interact at field and tr...

  6. PERKAM: Personalized Knowledge Awareness Map for Computer Supported Ubiquitous Learning

    Science.gov (United States)

    El-Bishouty, Moushir M.; Ogata, Hiroaki; Yano, Yoneo

    2007-01-01

    This paper introduces a ubiquitous computing environment in order to support the learners while doing tasks; this environment is called PERKAM (PERsonalized Knowledge Awareness Map). PERKAM allows the learners to share knowledge, interact, collaborate, and exchange individual experiences. It utilizes the RFID ubiquities technology to detect the…

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Mapping learning and game mechanics for serious games analysis

    NARCIS (Netherlands)

    Arnab, S.; Lim, T.; Brandao Carvalho, M.; Bellotti, F.; De Freitas, S.; Louchart, S.; Suttie, N.; Berta, R.; De Gloria, A.

    2015-01-01

    Although there is a consensus on the instructional potential of Serious Games (SGs), there is still a lack of methodologies and tools not only for design but also to support analysis and assessment. Filling this gap is one of the main aims of the Games and Learning Alliance (http://www.galanoe.eu)

  16. Automated mapping of building facades by machine learning

    DEFF Research Database (Denmark)

    Höhle, Joachim

    2014-01-01

    Facades of buildings contain various types of objects which have to be recorded for information systems. The article describes a solution for this task focussing on automated classification by means of machine learning techniques. Stereo pairs of oblique images are used to derive 3D point clouds...

  17. Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics

    NARCIS (Netherlands)

    Strickert, M.; Schneider, P.; Keilwagen, J.; Villmann, T.; Biehl, M.; Hammer, B.

    2008-01-01

    Supervised attribute relevance detection using cross-comparisons (SARDUX), a recently proposed method for data-driven metric learning, is extended from dimension-weighted Minkowski distances to metrics induced by a data transformation matrix Ω for modeling mutual attribute dependence. Given class

  18. Mapping Learning and Game Mechanics for Serious Games Analysis

    Science.gov (United States)

    Arnab, Sylvester; Lim, Theodore; Carvalho, Maira B.; Bellotti, Francesco; de Freitas, Sara; Louchart, Sandy; Suttie, Neil; Berta, Riccardo; De Gloria, Alessandro

    2015-01-01

    Although there is a consensus on the instructional potential of Serious Games (SGs), there is still a lack of methodologies and tools not only for design but also to support analysis and assessment. Filling this gap is one of the main aims of the Games and Learning Alliance (http://www.galanoe.eu) European Network of Excellence on Serious Games,…

  19. A new automatic SAR-based flood mapping application hosted on the European Space Agency's grid processing on demand fast access to imagery environment

    Science.gov (United States)

    Hostache, Renaud; Chini, Marco; Matgen, Patrick; Giustarini, Laura

    2013-04-01

    There is a clear need for developing innovative processing chains based on earth observation (EO) data to generate products supporting emergency response and flood management at a global scale. Here an automatic flood mapping application is introduced. The latter is currently hosted on the Grid Processing on Demand (G-POD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver flooded areas using both recent and historical acquisitions of SAR data in an operational framework. It is worth mentioning that the method can be applied to both medium and high resolution SAR images. The flood mapping application consists of two main blocks: 1) A set of query tools for selecting the "crisis image" and the optimal corresponding pre-flood "reference image" from the G-POD archive. 2) An algorithm for extracting flooded areas using the previously selected "crisis image" and "reference image". The proposed method is a hybrid methodology, which combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. The method is based on the calibration of a statistical distribution of "open water" backscatter values inferred from SAR images of floods. Change detection with respect to a pre-flood reference image helps reducing over-detection of inundated areas. The algorithms are computationally efficient and operate with minimum data requirements, considering as input data a flood image and a reference image. Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate pre-flood reference image. Potential users will also be able to apply the implemented flood delineation algorithm. Case studies of several recent high magnitude flooding events (e.g. July 2007 Severn River flood

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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...

  5. A New Concept Map Model for E-Learning Environments

    Science.gov (United States)

    Dattolo, Antonina; Luccio, Flaminia L.

    Web-based education enables learners and teachers to access a wide quantity of continuously updated educational sources. In order to support the learning process, a system has to provide some fundamental features, such as simple mechanisms for the identification of the collection of “interesting” documents, adequate structures for storing, organizing and visualizing these documents, and appropriate mechanisms for creating personalized adaptive paths and views for learners.

  6. 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…

  7. 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…

  8. 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…

  9. CERISE - Combining energy and spatial information standards as enabler for smart grids - TKI smart grid project : TKISG01010 - D4.1 Semantic mappings to harmonize energy, geo and government-related information models. Work package 40

    NARCIS (Netherlands)

    Steen, M.; Knibbe, F.; Quak, C.W.; Janssen, P.; Stap, R.; Daniele, L.

    2015-01-01

    Version 1.0 - Final The CERISE-SG project (Combining Energy and Geo information standards as enabler for Smart Grids) focuses on interoperability with a special interest in the information exchanges between smart grids and their surroundings. We hereby focus on the exchange of information to and

  10. The Role of IQ in the Use of Cognitive Strategies to Learn Information from a Map

    Science.gov (United States)

    Cho, Seokhee

    2010-01-01

    The role of IQ in individual differences in real-life problem solving and strategies use was explored. Repeated trials of learning and recall of information from a map were analyzed with high IQ and average IQ Korean students. IQ correlated with the selection and use of strategies in recall. However, the performance and strategic behaviors of…

  11. 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.

  12. 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…

  13. A Road Map for Empowering Undergraduates to Practice Service Leadership through Service-Learning in Teams

    Science.gov (United States)

    Snell, Robin Stanley; Chan, Maureen Yin Lee; Ma, Carol Hok Ka; Chan, Carman Ka Man

    2015-01-01

    We present a road map for providing course-embedded service-learning team projects as opportunities for undergraduates to practice as service leaders in Asia and beyond. Basic foundations are that projects address authentic problems or needs, partner organization representatives (PORs) indicate availability for ongoing consultation, students…

  14. Orthographic Mapping in the Acquisition of Sight Word Reading, Spelling Memory, and Vocabulary Learning

    Science.gov (United States)

    Ehri, Linnea C.

    2014-01-01

    Orthographic mapping (OM) involves the formation of letter-sound connections to bond the spellings, pronunciations, and meanings of specific words in memory. It explains how children learn to read words by sight, to spell words from memory, and to acquire vocabulary words from print. This development is portrayed by Ehri (2005a) as a sequence of…

  15. 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…

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Spatial mapping of wind parks in Republic of Macedonia from aspect of power generation and connection to power grid

    International Nuclear Information System (INIS)

    Janchevska, Melita

    2012-01-01

    The master thesis “Spatial mapping of wind parks in Republic of Macedonia from aspect of power generation and connection to power grid” presents spatial aspects for setting of wind parks at favourable locations. The thesis presents a comprehensive analysis how to carry out the administrative procedures that are in force in Republic of Macedonia, a range of minimum allowed distances in setting of each of the wind plants within a wind parks, but also requirements for fulfilling the basic human rights in preserving quality of life of the people in rural areas where the wind parks are build. As a result, a compromise in setting of wind parks and a suitable solution of sustainable development should be reached. Therefore, the decision making process should be based on the following key factors: environmental, social and economic development of the area of concern. The production of wind power is strongly influenced by meteorological conditions and has an average factor of utilization of up to 30%. This low factor of utilization cannot be used for planning of the basic energy needs of the country, but it can contribute certainly towards the reduction of the participation of conventional power plants. Republic of Macedonia introduced feed-in tariffs as a subsiding mechanism for building and strong penetration of wind parks. Additional funding mechanisms include carbon financing and green-field credits, through development of projects in the framework of Clean Development Mechanism, which improves the economic feasibility of the project and increases the interest of the investors. The analysis of the relevant spatial aspects of setting wind parks in Republic of Macedonia based on balanced and sustainable spatial development is made with regards to the following thematic areas: exploiting the potential of wind energy, climate issues, geo morphological and geo seismically aspects, rational use of land, protection of agricultural land and forests, spatial allocation of

  1. 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.

  2. 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,…

  3. 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.

  4. 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...

  5. Learning, Working and Living. Mapping the terrain of Working Life Learning

    DEFF Research Database (Denmark)

    In recent years, learning and knowing have emerged as key issues in understanding work organizations. Identifying ways in which learning can be supported in the workplace has been a long standing cercern for organization studies and education. What is particularly interesting is that the debate...... about organization and workplace learning has moved, from a fokus on formal and informal ways of supporting learning to ways in which learning ca become a part of working lifeWith contributions from a diverse range of international authorities in the area of management and education ass well...

  6. 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…

  7. 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

  8. 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…

  9. 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

  10. 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

  11. 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.

  12. Does the mind map learning strategy facilitate information retrieval and critical thinking in medical students?

    Science.gov (United States)

    D'Antoni, Anthony V; Zipp, Genevieve Pinto; Olson, Valerie G; Cahill, Terrence F

    2010-09-16

    A learning strategy underutilized in medical education is mind mapping. Mind maps are multi-sensory tools that may help medical students organize, integrate, and retain information. Recent work suggests that using mind mapping as a note-taking strategy facilitates critical thinking. The purpose of this study was to investigate whether a relationship existed between mind mapping and critical thinking, as measured by the Health Sciences Reasoning Test (HSRT), and whether a relationship existed between mind mapping and recall of domain-based information. In this quasi-experimental study, 131 first-year medical students were randomly assigned to a standard note-taking (SNT) group or mind map (MM) group during orientation. Subjects were given a demographic survey and pre-HSRT. They were then given an unfamiliar text passage, a pre-quiz based upon the passage, and a 30-minute break, during which time subjects in the MM group were given a presentation on mind mapping. After the break, subjects were given the same passage and wrote notes based on their group (SNT or MM) assignment. A post-quiz based upon the passage was administered, followed by a post-HSRT. Differences in mean pre- and post-quiz scores between groups were analyzed using independent samples t-tests, whereas differences in mean pre- and post-HSRT total scores and subscores between groups were analyzed using ANOVA. Mind map depth was assessed using the Mind Map Assessment Rubric (MMAR). There were no significant differences in mean scores on both the pre- and post-quizzes between note-taking groups. And, no significant differences were found between pre- and post-HSRT mean total scores and subscores. Although mind mapping was not found to increase short-term recall of domain-based information or critical thinking compared to SNT, a brief introduction to mind mapping allowed novice MM subjects to perform similarly to SNT subjects. This demonstrates that medical students using mind maps can successfully

  13. 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.

  14. 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.

  15. 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

  16. 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...

  17. Mapping Burned Areas in Tropical Forests Using a Novel Machine Learning Framework

    OpenAIRE

    Varun Mithal; Guruprasad Nayak; Ankush Khandelwal; Vipin Kumar; Ramakrishna Nemani; Nikunj C. Oza

    2018-01-01

    This paper presents an application of a novel machine-learning framework on MODIS (moderate-resolution imaging spectroradiometer) data to map burned areas over tropical forests of South America and South-east Asia. The RAPT (RAre Class Prediction in the absence of True labels) framework is able to build data adaptive classification models using noisy training labels. It is particularly suitable when expert annotated training samples are difficult to obtain as in the case of wild fires in the ...

  18. Design, Qualification and Lessons Learned of the Shutter Calibration Mechanism for EnMAP Mission

    Science.gov (United States)

    Schmidt, Tilo; Muller, Silvio; Bergander, Arvid; Zajac, Kai; Seifart, Klaus

    2015-09-01

    The Shutter Calibration Mechanism (SCM) Assembly is one of three mechanisms which are developed by HTS for the EnMAP instrument in subcontract to OHB System AG Munich. EnMAP is the Environmental Mapping and Analysis Program of the German Space Agency DLR.The binary rotary encoder of the SCM using hall-effect sensors was already presented during ESMATS 2011. This paper summarizes the main functions and design features of the Hardware and focuses on qualification testing which has finished successfully in 2014. Of particular interest is the functional testing of the main drive including the precise hall-effect position sensing system and the test of the fail safe mechanism. In addition to standard test campaign required for QM also a shock emission measurement of the fail safe mechanism activation was conducted.Test conduction and results will be presented with focus on deviations from the expected behaviour, mitigation measures and on lessons learned.

  19. 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

  20. 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.

  1. 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

  2. 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.

  3. The Concept Maps as a Didactic Resource Tool of Meaningful Learning in Astronomy Themes

    Science.gov (United States)

    Silveira, Felipa Pacífico Ribeiro de Assis; Mendonça, Conceição Aparecida Soares

    2015-07-01

    This article presents the results of an investigation that sought to understand the performance of the conceptual map (MC) as a teaching resource facilitator of meaningful learning of scientific concepts on astronomical themes, developed with elementary school students. The methodology employed to obtain and process the data was based on a quantitative and qualitative approach. On the quantitative level we designed a quasi-experimental research with a control group that did not use the MC and an experimental group that used the MC, both being evaluated in the beginning and end of the process. In this case, the performance of both groups is displayed in a descriptive and analytical study. In the qualitative approach, the MCs were interpreted using the structuring and assigned meanings shared by the student during his/her presentation. The results demonstrated through the improvement of qualifications that the MC made a difference in conceptual learning and in certain skills revealed by learning indicators.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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

  12. 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.

  13. 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…

  14. 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.

  15. 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.

  16. On a learning curve for shared decision making: Interviews with clinicians using the knee osteoarthritis Option Grid.

    Science.gov (United States)

    Elwyn, Glyn; Rasmussen, Julie; Kinsey, Katharine; Firth, Jill; Marrin, Katy; Edwards, Adrian; Wood, Fiona

    2018-02-01

    Tools used in clinical encounters to illustrate to patients the risks and benefits of treatment options have been shown to increase shared decision making. However, we do not have good information about how these tools are viewed by clinicians and how clinicians think patients would react to their use. Our aim was to examine clinicians' views about the possible and actual use of tools designed to support patients and clinicians to collaborate and deliberate about treatment options, namely, Option Grid decision aids. We conducted a thematic analysis of qualitative interviews embedded in the intervention phase of a trial of an Option Grid decision aid for osteoarthritis of the knee. Interviews were conducted with 6 participating clinicians before they used the tool and again after clinicians had used the tool with 6 patients. In the first interview, clinicians voiced concerns that the tool would lead to an increase in encounter duration, patient resistance regarding involvement in decision making, and potential information overload. At the second interview, after minimal training, the clinicians reported that the tool had changed their usual way of communicating, and it was generally acceptable and helpful to integrate it into practice. After experiencing the use of Option Grids, clinicians became more willing to use the tools in their clinical encounters with patients. How best to introduce Option Grids to clinicians and adopt their use into practice will need careful consideration of context, workflow, and clinical pathways. © 2016 John Wiley & Sons, Ltd.

  17. Reaching for the cloud: on the lessons learned from grid computing technology transfer process to the biomedical community.

    Science.gov (United States)

    Mohammed, Yassene; Dickmann, Frank; Sax, Ulrich; von Voigt, Gabriele; Smith, Matthew; Rienhoff, Otto

    2010-01-01

    Natural scientists such as physicists pioneered the sharing of computing resources, which led to the creation of the Grid. The inter domain transfer process of this technology has hitherto been an intuitive process without in depth analysis. Some difficulties facing the life science community in this transfer can be understood using the Bozeman's "Effectiveness Model of Technology Transfer". Bozeman's and classical technology transfer approaches deal with technologies which have achieved certain stability. Grid and Cloud solutions are technologies, which are still in flux. We show how Grid computing creates new difficulties in the transfer process that are not considered in Bozeman's model. We show why the success of healthgrids should be measured by the qualified scientific human capital and the opportunities created, and not primarily by the market impact. We conclude with recommendations that can help improve the adoption of Grid and Cloud solutions into the biomedical community. These results give a more concise explanation of the difficulties many life science IT projects are facing in the late funding periods, and show leveraging steps that can help overcoming the "vale of tears".

  18. Grid Security

    CERN Multimedia

    CERN. Geneva

    2004-01-01

    The aim of Grid computing is to enable the easy and open sharing of resources between large and highly distributed communities of scientists and institutes across many independent administrative domains. Convincing site security officers and computer centre managers to allow this to happen in view of today's ever-increasing Internet security problems is a major challenge. Convincing users and application developers to take security seriously is equally difficult. This paper will describe the main Grid security issues, both in terms of technology and policy, that have been tackled over recent years in LCG and related Grid projects. Achievements to date will be described and opportunities for future improvements will be addressed.

  19. 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.

  20. 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.

  1. How do task characteristics affect learning and performance? The roles of variably mapped and dynamic tasks.

    Science.gov (United States)

    Macnamara, Brooke N; Frank, David J

    2018-05-01

    For well over a century, scientists have investigated individual differences in performance. The majority of studies have focused on either differences in practice, or differences in cognitive resources. However, the predictive ability of either practice or cognitive resources varies considerably across tasks. We are the first to examine task characteristics' impact on learning and performance in a complex task while controlling for other task characteristics. In 2 experiments we test key theoretical task characteristic thought to moderate the relationship between practice, cognitive resources, and performance. We devised a task where each of several key task characteristics can be manipulated independently. Participants played 5 rounds of a game similar to the popular tower defense videogame Plants vs. Zombies where both cognitive load and game characteristics were manipulated. In Experiment 1, participants either played a consistently mapped version-the stimuli and the associated meaning of their properties were constant across the 5 rounds-or played a variably mapped version-the stimuli and the associated meaning of their properties changed every few minutes. In Experiment 2, participants either played a static version-that is, turn taking with no time pressure-or played a dynamic version-that is, the stimuli moved regardless of participants' response rates. In Experiment 1, participants' accuracy and efficiency were substantially hindered in the variably mapped conditions. In Experiment 2, learning and performance accuracy were hindered in the dynamic conditions, especially when under cognitive load. Our results suggest that task characteristics impact the relative importance of cognitive resources and practice on predicting learning and performance. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  2. 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.

  3. Grid Computing

    Indian Academy of Sciences (India)

    A computing grid interconnects resources such as high performancecomputers, scientific databases, and computercontrolledscientific instruments of cooperating organizationseach of which is autonomous. It precedes and is quitedifferent from cloud computing, which provides computingresources by vendors to customers ...

  4. Grid Computing

    Indian Academy of Sciences (India)

    IAS Admin

    emergence of supercomputers led to the use of computer simula- tion as an .... Scientific and engineering applications (e.g., Tera grid secure gate way). Collaborative ... Encryption, privacy, protection from malicious software. Physical Layer.

  5. 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.

  6. Geography Map Knowledge Acquisition by Solving a Jigsaw Map Compared to Self-Study: Investigating Game Based Learning

    Science.gov (United States)

    Dang, Srishti; Ved, Arunima; Vemuri, Kavita

    2018-01-01

    Efficacy of games as learning medium is of interest to researchers and the gaming industry. A critical metric for learning is knowledge retention and very few studies have conducted in-depth comparisons of: a) game versus no-game learning, b) collaborative versus individual learning. Towards this, the study reported in this article will present…

  7. Combining Human and Machine Learning to Map Cropland in the 21st Century's Major Agricultural Frontier

    Science.gov (United States)

    Estes, L. D.; Debats, S. R.; Caylor, K. K.; Evans, T. P.; Gower, D.; McRitchie, D.; Searchinger, T.; Thompson, D. R.; Wood, E. F.; Zeng, L.

    2016-12-01

    In the coming decades, large areas of new cropland will be created to meet the world's rapidly growing food demands. Much of this new cropland will be in sub-Saharan Africa, where food needs will increase most and the area of remaining potential farmland is greatest. If we are to understand the impacts of global change, it is critical to accurately identify Africa's existing croplands and how they are changing. Yet the continent's smallholder-dominated agricultural systems are unusually challenging for remote sensing analyses, making accurate area estimates difficult to obtain, let alone important details related to field size and geometry. Fortunately, the rapidly growing archives of moderate to high-resolution satellite imagery hosted on open servers now offer an unprecedented opportunity to improve landcover maps. We present a system that integrates two critical components needed to capitalize on this opportunity: 1) human image interpretation and 2) machine learning (ML). Human judgment is needed to accurately delineate training sites within noisy imagery and a highly variable cover type, while ML provides the ability to scale and to interpret large feature spaces that defy human comprehension. Because large amounts of training data are needed (a major impediment for analysts), we use a crowdsourcing platform that connects amazon.com's Mechanical Turk service to satellite imagery hosted on open image servers. Workers map visible fields at pre-assigned sites, and are paid according to their mapping accuracy. Initial tests show overall high map accuracy and mapping rates >1800 km2/hour. The ML classifier uses random forests and randomized quasi-exhaustive feature selection, and is highly effective in classifying diverse agricultural types in southern Africa (AUC > 0.9). We connect the ML and crowdsourcing components to make an interactive learning framework. The ML algorithm performs an initial classification using a first batch of crowd-sourced maps, using

  8. Preliminary hard and soft bottom seafloor substrate map (5m grid) derived from an unsupervised classification of gridded backscatter and bathymetry derivatives at Rose Atoll Lagoon, Territory of American Samoa, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from an unsupervised classification of multibeam backscatter and bathymetry derivatives at Rose Atoll...

  9. Preliminary hard and soft bottom seafloor substrate map (40m grid) derived from an unsupervised classification of gridded backscatter and bathymetry derivatives at Rose Atoll, Territory of American Samoa, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from an unsupervised classification of multibeam backscatter and bathymetry derivatives at Rose Atoll,...

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. Mapping epistemic cultures and learning potential of participants in citizen science projects.

    Science.gov (United States)

    Vallabh, Priya; Lotz-Sisitka, Heila; O'Donoghue, Rob; Schudel, Ingrid

    2016-06-01

    The ever-widening scope and range of global change and interconnected systemic risks arising from people-environment relationships (social-ecological risks) appears to be increasing concern among, and involvement of, citizens in an increasingly diversified number of citizen science projects responding to these risks. We examined the relationship between epistemic cultures in citizen science projects and learning potential related to matters of concern. We then developed a typology of purposes and a citizen science epistemic-cultures heuristic and mapped 56 projects in southern Africa using this framework. The purpose typology represents the range of knowledge-production purposes, ranging from laboratory science to social learning, whereas the epistemic-cultures typology is a relational representation of scientist and citizen participation and their approach to knowledge production. Results showed an iterative relationship between matters of fact and matters of concern across the projects; the nexus of citizens' engagement in knowledge-production activities varied. The knowledge-production purposes informed and shaped the epistemic cultures of all the sampled citizen science projects, which in turn influenced the potential for learning within each project. Through a historical review of 3 phases in a long-term river health-monitoring project, we found that it is possible to evolve the learning curve of citizen science projects. This evolution involved the development of scientific water monitoring tools, the parallel development of pedagogic practices supporting monitoring activities, and situated engagement around matters of concern within social activism leading to learning-led change. We conclude that such evolutionary processes serve to increase potential for learning and are necessary if citizen science is to contribute to wider restructuring of the epistemic culture of science under conditions of expanding social-ecological risk. © 2016 Society for

  15. 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

  16. 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.

  17. An Approach for Predicting Essential Genes Using Multiple Homology Mapping and Machine Learning Algorithms.

    Science.gov (United States)

    Hua, Hong-Li; Zhang, Fa-Zhan; Labena, Abraham Alemayehu; Dong, Chuan; Jin, Yan-Ting; Guo, Feng-Biao

    Investigation of essential genes is significant to comprehend the minimal gene sets of cell and discover potential drug targets. In this study, a novel approach based on multiple homology mapping and machine learning method was introduced to predict essential genes. We focused on 25 bacteria which have characterized essential genes. The predictions yielded the highest area under receiver operating characteristic (ROC) curve (AUC) of 0.9716 through tenfold cross-validation test. Proper features were utilized to construct models to make predictions in distantly related bacteria. The accuracy of predictions was evaluated via the consistency of predictions and known essential genes of target species. The highest AUC of 0.9552 and average AUC of 0.8314 were achieved when making predictions across organisms. An independent dataset from Synechococcus elongatus , which was released recently, was obtained for further assessment of the performance of our model. The AUC score of predictions is 0.7855, which is higher than other methods. This research presents that features obtained by homology mapping uniquely can achieve quite great or even better results than those integrated features. Meanwhile, the work indicates that machine learning-based method can assign more efficient weight coefficients than using empirical formula based on biological knowledge.

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

    Directory of Open Access Journals (Sweden)

    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.

  19. A learning heuristic for space mapping and searching self-organizing systems using adaptive mesh refinement

    Science.gov (United States)

    Phillips, Carolyn L.

    2014-09-01

    In a complex self-organizing system, small changes in the interactions between the system's components can result in different emergent macrostructures or macrobehavior. In chemical engineering and material science, such spontaneously self-assembling systems, using polymers, nanoscale or colloidal-scale particles, DNA, or other precursors, are an attractive way to create materials that are precisely engineered at a fine scale. Changes to the interactions can often be described by a set of parameters. Different contiguous regions in this parameter space correspond to different ordered states. Since these ordered states are emergent, often experiment, not analysis, is necessary to create a diagram of ordered states over the parameter space. By issuing queries to points in the parameter space (e.g., performing a computational or physical experiment), ordered states can be discovered and mapped. Queries can be costly in terms of resources or time, however. In general, one would like to learn the most information using the fewest queries. Here we introduce a learning heuristic for issuing queries to map and search a two-dimensional parameter space. Using a method inspired by adaptive mesh refinement, the heuristic iteratively issues batches of queries to be executed in parallel based on past information. By adjusting the search criteria, different types of searches (for example, a uniform search, exploring boundaries, sampling all regions equally) can be flexibly implemented. We show that this method will densely search the space, while preferentially targeting certain features. Using numerical examples, including a study simulating the self-assembly of complex crystals, we show how this heuristic can discover new regions and map boundaries more accurately than a uniformly distributed set of queries.

  20. 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.

  1. Building resilient power grids from integrated risk governance perspective: A lesson learned from china's 2008 Ice-Snow Storm disaster

    Science.gov (United States)

    Ye, Qian

    2014-10-01

    In the past three decades, the electric energy industry made great contribution to support rapid social and economic development in China, and meanwhile has been grown at the highest rate in the human history owing to the economic reform. In its new national development plan, more investment has been put into installation of both electricity generating capacity and transmitting capacity in order to meet fast growing demand of electric energy. However, energy resources, both fossil fuel and renewable types, and energy consumption and load centers in China are not evenly distributed in both spatial and temporal dimensions. Moreover, dominated by coal as its primary energy source, the whole eastern China is now entering an environmental crisis in which pollutants emitted by coal power plants contribute a large part. To balance the regional differences in energy sources and energy consumption while meeting the steadily increasing demands for electric energy for the whole country, in addition to increase electric generating capacity, building large-scale, long-distance ultra high voltage power grids is the top priority for next five years. China is a country prone to almost all kinds of natural disasters due to its vast, complex geographical and climatic conditions. In recent years, frequent natural disasters, especially extreme weather and climate events, have threatened the safety, reliability and stability of electric energy system in China. Unfortunately, with fast growth rate but lacking of risk assessing and prevention mechanism, many infrastructure constructions, including national power grids, are facing integrated and complex economic, social, institutional and ecological risks. In this paper, based on a case analysis of the Great Ice Storm in southern China in January 2008, risks of building a resilient power grid to deal with increasing threats from extreme weathers are discussed. The paper recommends that a systematic approach based on the social

  2. 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

  3. Social interaction facilitates word learning in preverbal infants: Word-object mapping and word segmentation.

    Science.gov (United States)

    Hakuno, Yoko; Omori, Takahide; Yamamoto, Jun-Ichi; Minagawa, Yasuyo

    2017-08-01

    In natural settings, infants learn spoken language with the aid of a caregiver who explicitly provides social signals. Although previous studies have demonstrated that young infants are sensitive to these signals that facilitate language development, the impact of real-life interactions on early word segmentation and word-object mapping remains elusive. We tested whether infants aged 5-6 months and 9-10 months could segment a word from continuous speech and acquire a word-object relation in an ecologically valid setting. In Experiment 1, infants were exposed to a live tutor, while in Experiment 2, another group of infants were exposed to a televised tutor. Results indicate that both younger and older infants were capable of segmenting a word and learning a word-object association only when the stimuli were derived from a live tutor in a natural manner, suggesting that real-life interaction enhances the learning of spoken words in preverbal infants. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. Concept Maps as a strategy to asses learning in biochemistry using educational softwares

    Directory of Open Access Journals (Sweden)

    A. M. P. Azevedo

    2005-07-01

    Full Text Available This abstract reports  the  use of concept  maps applied  to the evaluation of concepts  learned  through the use of an educational software to study  metabolic  pathways called Diagrama Metabolico Dinamico Virtual  do Ciclo de Krebs (DMDV.  Experience  with the use of this method  was carried  through  with two distinct groups  of students.  The  first  group  was composed  by 24 students (in  2003 who used DMDV during  the  classes (computer room.  The second group was formed by 36 students (in 2004 who could access DMDV software anytime  through  the intranet. The construction of the conceptual map by the student permits  the representation of knowledge, the mental  processes that were absorved and the adaptation during the study,  building new mental schemes that could be related to the concept of reflexioning  abstraction (Piaget, 1995 during  the  process of operation  with  these  concepts.   The evaluation of knowlegde was made by the analysis  of three conceptual  maps constructed by each one of them:   (a  one map  before initiating the  study  with  DMDV,  (b  the  second just  after  the  study and (c the third  one two months  later.  We used the following criteria  for the analysis:  predominance of associative  over classificatory  character; correct concepts  and  relationships; coherence;  number  of relationships;  creativity and  logic.   The  initial  maps  showed  that all  students had  some  previous mental scheme  about  the proposed  concept.    All final  concept maps  showed  an  expansion  of the concepts  as compared  to the initial  maps, something  which can be seen even by a mere glance at the size of graphics.  A purely visual comparison  between the maps indicated  that new elements have been added.   The  associative  character has been shown to predominate as compared  to the  classificatory one.  The

  6. Power grids

    International Nuclear Information System (INIS)

    Viterbo, J.

    2012-01-01

    The implementation of renewable energies represents new challenges for electrical systems. The objective: making power grids smarter so they can handle intermittent production. The advent of smart grids will allow flexible operations like distributing energy in a multidirectional manner instead of just one way and it will make electrical systems capable of integrating actions by different users, consumers and producers in order to maintain efficient, sustainable, economical and secure power supplies. Practically speaking, they associate sensors, instrumentation and controls with information processing and communication systems in order to create massively automated networks. Smart grids require huge investments: for example more than 7 billion dollars have been invested in China and in the Usa in 2010 and France is ranked 9. worldwide with 265 million dollars invested. It is expected that smart grids will promote the development of new business models and a change in the value chain for energy. Decentralized production combined with the probable introduction of more or less flexible rates for sales or purchases and of new supplier-customer relationships will open the way to the creation of new businesses. (A.C.)

  7. 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.

  8. Fuzzy cognitive maps for applied sciences and engineering from fundamentals to extensions and learning algorithms

    CERN Document Server

    2014-01-01

    Fuzzy Cognitive Maps (FCM) constitute cognitive models in the form of fuzzy directed graphs consisting of two basic elements: the nodes, which basically correspond to “concepts” bearing different states of activation depending on the knowledge they represent, and the “edges” denoting the causal effects that each source node exercises on the receiving concept expressed through weights. Weights take values in the interval [-1,1], which denotes the positive, negative or neutral causal relationship between two concepts. An FCM can be typically obtained through linguistic terms, inherent to fuzzy systems, but with a structure similar to the neural networks, which facilitates data processing, and has capabilities for training and adaptation. During the last 10 years, an exponential growth of published papers in FCMs was followed showing great impact potential. Different FCM structures and learning schemes have been developed, while numerous studies report their use in many contexts with highly successful m...

  9. Evaluation of different machine learning models for predicting and mapping the susceptibility of gully erosion

    Science.gov (United States)

    Rahmati, Omid; Tahmasebipour, Nasser; Haghizadeh, Ali; Pourghasemi, Hamid Reza; Feizizadeh, Bakhtiar

    2017-12-01

    Gully erosion constitutes a serious problem for land degradation in a wide range of environments. The main objective of this research was to compare the performance of seven state-of-the-art machine learning models (SVM with four kernel types, BP-ANN, RF, and BRT) to model the occurrence of gully erosion in the Kashkan-Poldokhtar Watershed, Iran. In the first step, a gully inventory map consisting of 65 gully polygons was prepared through field surveys. Three different sample data sets (S1, S2, and S3), including both positive and negative cells (70% for training and 30% for validation), were randomly prepared to evaluate the robustness of the models. To model the gully erosion susceptibility, 12 geo-environmental factors were selected as predictors. Finally, the goodness-of-fit and prediction skill of the models were evaluated by different criteria, including efficiency percent, kappa coefficient, and the area under the ROC curves (AUC). In terms of accuracy, the RF, RBF-SVM, BRT, and P-SVM models performed excellently both in the degree of fitting and in predictive performance (AUC values well above 0.9), which resulted in accurate predictions. Therefore, these models can be used in other gully erosion studies, as they are capable of rapidly producing accurate and robust gully erosion susceptibility maps (GESMs) for decision-making and soil and water management practices. Furthermore, it was found that performance of RF and RBF-SVM for modelling gully erosion occurrence is quite stable when the learning and validation samples are changed.

  10. 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.

  11. Evaluation of Multiple Kernel Learning Algorithms for Crop Mapping Using Satellite Image Time-Series Data

    Science.gov (United States)

    Niazmardi, S.; Safari, A.; Homayouni, S.

    2017-09-01

    Crop mapping through classification of Satellite Image Time-Series (SITS) data can provide very valuable information for several agricultural applications, such as crop monitoring, yield estimation, and crop inventory. However, the SITS data classification is not straightforward. Because different images of a SITS data have different levels of information regarding the classification problems. Moreover, the SITS data is a four-dimensional data that cannot be classified using the conventional classification algorithms. To address these issues in this paper, we presented a classification strategy based on Multiple Kernel Learning (MKL) algorithms for SITS data classification. In this strategy, initially different kernels are constructed from different images of the SITS data and then they are combined into a composite kernel using the MKL algorithms. The composite kernel, once constructed, can be used for the classification of the data using the kernel-based classification algorithms. We compared the computational time and the classification performances of the proposed classification strategy using different MKL algorithms for the purpose of crop mapping. The considered MKL algorithms are: MKL-Sum, SimpleMKL, LPMKL and Group-Lasso MKL algorithms. The experimental tests of the proposed strategy on two SITS data sets, acquired by SPOT satellite sensors, showed that this strategy was able to provide better performances when compared to the standard classification algorithm. The results also showed that the optimization method of the used MKL algorithms affects both the computational time and classification accuracy of this strategy.

  12. Manifold Learning with Self-Organizing Mapping for Feature Extraction of Nonlinear Faults in Rotating Machinery

    Directory of Open Access Journals (Sweden)

    Lin Liang

    2015-01-01

    Full Text Available A new method for extracting the low-dimensional feature automatically with self-organization mapping manifold is proposed for the detection of rotating mechanical nonlinear faults (such as rubbing, pedestal looseness. Under the phase space reconstructed by single vibration signal, the self-organization mapping (SOM with expectation maximization iteration algorithm is used to divide the local neighborhoods adaptively without manual intervention. After that, the local tangent space alignment algorithm is adopted to compress the high-dimensional phase space into low-dimensional feature space. The proposed method takes advantages of the manifold learning in low-dimensional feature extraction and adaptive neighborhood construction of SOM and can extract intrinsic fault features of interest in two dimensional projection space. To evaluate the performance of the proposed method, the Lorenz system was simulated and rotation machinery with nonlinear faults was obtained for test purposes. Compared with the holospectrum approaches, the results reveal that the proposed method is superior in identifying faults and effective for rotating machinery condition monitoring.

  13. 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

  14. A novel multi-agent decentralized win or learn fast policy hill-climbing with eligibility trace algorithm for smart generation control of interconnected complex power grids

    International Nuclear Information System (INIS)

    Xi, Lei; Yu, Tao; Yang, Bo; Zhang, Xiaoshun

    2015-01-01

    Highlights: • Proposing a decentralized smart generation control scheme for the automatic generation control coordination. • A novel multi-agent learning algorithm is developed to resolve stochastic control problems in power systems. • A variable learning rate are introduced base on the framework of stochastic games. • A simulation platform is developed to test the performance of different algorithms. - Abstract: This paper proposes a multi-agent smart generation control scheme for the automatic generation control coordination in interconnected complex power systems. A novel multi-agent decentralized win or learn fast policy hill-climbing with eligibility trace algorithm is developed, which can effectively identify the optimal average policies via a variable learning rate under various operation conditions. Based on control performance standards, the proposed approach is implemented in a flexible multi-agent stochastic dynamic game-based smart generation control simulation platform. Based on the mixed strategy and average policy, it is highly adaptive in stochastic non-Markov environments and large time-delay systems, which can fulfill automatic generation control coordination in interconnected complex power systems in the presence of increasing penetration of decentralized renewable energy. Two case studies on both a two-area load–frequency control power system and the China Southern Power Grid model have been done. Simulation results verify that multi-agent smart generation control scheme based on the proposed approach can obtain optimal average policies thus improve the closed-loop system performances, and can achieve a fast convergence rate with significant robustness compared with other methods

  15. [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

  16. Preliminary hard and soft bottom seafloor substrate map derived from an unsupervised classification of gridded backscatter and bathymetry derivatives of Ni'ihau Island, Hawaii, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from an unsupervised classification of multibeam backscatter and bathymety derivatives of Ni'ihau Island,...

  17. CRED Preliminary hard and soft bottom seafloor substrate map derived from an unsupervised classification of gridded backscatter and bathymetry derivatives at the U.S. Territory of Guam.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from an unsupervised classification of multibeam backscatter and bathymety derivatives at the U.S. Territory...

  18. Preliminary hard and soft bottom seafloor substrate map derived from an unsupervised classification of gridded backscatter and bathymetry derivatives at Swains Island, Territory of American Samoa, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from an unsupervised classification of multibeam backscatter and bathymetry derivatives at Swains Island,...

  19. Preliminary hard and soft bottom seafloor substrate map derived from an unsupervised classification of gridded backscatter and bathymetry derivatives at Tutuila Island, American Samoa, South Pacific.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from an unsupervised classification of multibeam backscatter and bathymety derivatives at Tutuila Island,...

  20. Preliminary hard and soft bottom seafloor substrate map derived from gridded sidescan and bathymetry derivatives at Apra Harbor, Guam U.S. Territory.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map classified from sidescan data and bathymetric derivatives at Apra Harbor, Guam U.S. Territory. The dataset was...

  1. 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.

  2. Grid pulser

    International Nuclear Information System (INIS)

    Jansweijer, P.P.M.; Es, J.T. van.

    1990-01-01

    This report describes a fast pulse generator. This generator delivers a high-voltage pulse of at most 6000 V with a rise time being smaller than 50 nS. this results in a slew rate of more than 120.000 volts per μS. The pulse generator is used to control the grid of the injector of the electron accelerator MEA. The capacity of this grid is about 60 pF. In order to charge this capacity up to 6000 volts in 50 nS a current of 8 ampere is needed. The maximal pulse length is 50 μS with a repeat frequency of 500 Hz. During this 50 μS the stability of the pulse amplitude is better than 0.1%. (author). 20 figs

  3. Applied learning-based color tone mapping for face recognition in video surveillance system

    Science.gov (United States)

    Yew, Chuu Tian; Suandi, Shahrel Azmin

    2012-04-01

    In this paper, we present an applied learning-based color tone mapping technique for video surveillance system. This technique can be applied onto both color and grayscale surveillance images. The basic idea is to learn the color or intensity statistics from a training dataset of photorealistic images of the candidates appeared in the surveillance images, and remap the color or intensity of the input image so that the color or intensity statistics match those in the training dataset. It is well known that the difference in commercial surveillance cameras models, and signal processing chipsets used by different manufacturers will cause the color and intensity of the images to differ from one another, thus creating additional challenges for face recognition in video surveillance system. Using Multi-Class Support Vector Machines as the classifier on a publicly available video surveillance camera database, namely SCface database, this approach is validated and compared to the results of using holistic approach on grayscale images. The results show that this technique is suitable to improve the color or intensity quality of video surveillance system for face recognition.

  4. Probing High School Students' Cognitive Structures and Key Areas of Learning Difficulties on Ethanoic Acid Using the Flow Map Method

    Science.gov (United States)

    Zhou, Qing; Wang, Tingting; Zheng, Qi

    2015-01-01

    The purpose of this study was primarily to explore high school students' cognitive structures and to identify their learning difficulties on ethanoic acid through the flow map method. The subjects of this study were 30 grade 1 students from Dong Yuan Road Senior High School in Xi'an, China. The interviews were conducted a week after the students…

  5. Developing Pre-Service Teachers' Subject Matter Knowledge of Electromagnetism by Integrating Concept Maps and Collaborative Learning

    Science.gov (United States)

    Govender, Nadaraj

    2015-01-01

    This case study explored the development of two pre-service teachers' subject matter knowledge (SMK) of electromagnetism while integrating the use of concept maps (CM) and collaborative learning (CL) strategies. The study aimed at capturing how these pre-service teachers' SMK in electromagnetism was enhanced after having been taught SMK in a…

  6. 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.

  7. Story Mapping and Its Effects on the Writing Fluency and Word Diversity of Students with Learning Disabilities

    Science.gov (United States)

    Li, Daqi

    2007-01-01

    Students with learning disabilities (LD) often experience difficulties in writing fluently and using a diversity of words. To help these students, specific and effective writing strategies must be incorporated into instruction and demonstrated to them through modeling. This study examined the effectiveness of using a story map and story map…

  8. Incorporating Mind Maps into Teaching and Learning in Higher Education: My Experience as an International University Lecturer

    Science.gov (United States)

    Guo, Xin

    2014-01-01

    This article seeks to share the author's teaching experience as an international lecturer in a UK university and in particular promote the use of Mind Maps (MM) in teaching and learning in higher education. The audience to whom the article could be beneficial is university lecturers who either are in their early teaching career or face challenges…

  9. The Effect of Mind Mapping on EFL Students' Idea Development in Argumentative Writing across Gender Differences and Learning Styles

    Science.gov (United States)

    Ningrum, Ary Setya Budhi; Latief, Mohammad Adnan; Sulistyo, Gunadi Harry

    2016-01-01

    The purpose of the study was to determine the impact of mind mapping as a strategy in generating ideas before writing on the EFL students' idea development in argumentative writing as perceived from their gender differences and learning styles. By conducting an experimental investigation at university level in Indonesia, two existing TOEFL classes…

  10. Enhancing Learning Outcomes through New E-Textbooks: A Desirable Combination of Presentation Methods and Concept Maps

    Science.gov (United States)

    Huang, Kuo-Liang; Chen, Kuo-Hsiang; Ho, Chun-Heng

    2014-01-01

    It is possible that e-textbook readers and tablet PC's will become mainstream reading devices in the future. However, knowledge about instructional design in this field of learning sciences is inadequate. This study aimed to analyse how two factors, that is, presentation methods and concept maps, interact with cognitive load and learning…

  11. The grid

    OpenAIRE

    Morrad, Annie; McArthur, Ian

    2018-01-01

    Project Anywhere Project title: The Grid   Artists: Annie Morrad: Artist/Senior Lecturer, University of Lincoln, School of Film and Media, Lincoln, UK   Dr Ian McArthur: Hybrid Practitioner/Senior Lecturer, UNSW Art & Design, UNSW Australia, Sydney, Australia   Annie Morrad is a London-based artist and musician and senior lecturer at the University of Lincoln, UK. Dr Ian McArthur is a Sydney-based hybrid practitione...

  12. 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.

  13. Machine Learning for Mapping Groundwater Salinity with Oil Well Log Data

    Science.gov (United States)

    Chang, W. H.; Shimabukuro, D.; Gillespie, J. M.; Stephens, M.

    2016-12-01

    An oil field may have thousands of wells with detailed petrophysical logs, and far fewer direct measurements of groundwater salinity. Can the former be used to extrapolate the latter into a detailed map of groundwater salinity? California Senate Bill 4, with its requirement to identify Underground Sources of Drinking Water, makes this a question worth answering. A well-known obstacle is that the basic petrophysical equations describe ideal scenarios ("clean wet sand") and even these equations contain many parameters that may vary with location and depth. Accounting for other common scenarios such as high-conductivity shaly sands or low-permeability diatomite (both characteristic of California's Central Valley) causes parameters to proliferate to the point where the model is underdetermined by the data. When parameters outnumber data points, however, is when machine learning methods are most advantageous. We present a method for modeling a generic oil field, where groundwater salinity and lithology are depth series parameters, and the constants in petrophysical equations are scalar parameters. The data are well log measurements (resistivity, porosity, spontaneous potential, and gamma ray) and a small number of direct groundwater salinity measurements. Embedded in the model are petrophysical equations that account for shaly sand and diatomite formations. As a proof of concept, we feed in well logs and salinity measurements from the Lost Hills Oil Field in Kern County, California, and show that with proper regularization and validation the model makes reasonable predictions of groundwater salinity despite the large number of parameters. The model is implemented using Tensorflow, which is an open-source software released by Google in November, 2015 that has been rapidly and widely adopted by machine learning researchers. The code will be made available on Github, and we encourage scrutiny and modification by machine learning researchers and hydrogeologists alike.

  14. 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

  15. 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

  16. The MAPS-based vertex detector for the STAR experiment: Lessons learned and performance

    Energy Technology Data Exchange (ETDEWEB)

    Contin, Giacomo, E-mail: gcontin@lbl.gov

    2016-09-21

    The PiXeL detector (PXL) of the STAR experiment at RHIC is the first application of the state-of-the-art thin Monolithic Active Pixel Sensors (MAPS) technology in a collider environment. The PXL, together with the Intermediate Silicon Tracker (IST) and the Silicon Strip Detector (SSD), form the Heavy Flavor Tracker (HFT), which has been designed to improve the vertex resolution and extend the STAR measurement capabilities in the heavy flavor domain, providing a clean probe for studying the Quark–Gluon Plasma. The two PXL layers are placed at a radius of 2.8 and 8 cm from the beam line, respectively, and is based on ultra-thin high resolution MAPS sensors. The sensor features 20.7 μm pixel pitch, 185.6 μs readout time and 170 mW/cm{sup 2} power dissipation. The detector is air-cooled, allowing a global material budget of 0.4% radiation length on the innermost layer. A novel mechanical approach to detector insertion allows for fast installation and integration of the pixel sub detector. The HFT took data in Au+Au collisions at 200 GeV during the 2014 RHIC run. Modified during the RHIC shutdown to improve its reliability, material budget, and tracking capabilities, the HFT took data in p+p and p+Au collisions at √s{sub NN}=200 GeV in the 2015 RHIC run. In this paper we present detector specifications, experience from the construction and operations, and lessons learned. We also show preliminary results from 2014 Au+Au data analyses, demonstrating the capabilities of charm reconstruction with the HFT. - Highlights: • First MAPS-based vertex detector in a collider experiment. • Achieved low material budget of 0.39% of radiation length per detector layer. • Track pointing resolution to the primary vertex better than 10⊕24 GeV/p×c μm. • Gain in significance for the topological reconstruction of the D{sup 0}−>K+π decay in STAR. • Observed latch-up induced damage of MAPS sensors.

  17. Using Repertory Grid Techniques to Measure Change Following Dialectical Behaviour Therapy with Adults with Learning Disabilities: Two Case Studies

    Science.gov (United States)

    McNair, Louisa; Woodrow, Ceri; Hare, Dougal

    2016-01-01

    Background: Government strategy indicates that individuals with learning disabilities should have access to adapted psychological therapies. Dialectical behaviour therapy (DBT) is recommended for the treatment of borderline personality disorder (BPD); however, there is little published research regarding whether it can be appropriately adapted for…

  18. Safe Grid

    Science.gov (United States)

    Chow, Edward T.; Stewart, Helen; Korsmeyer, David (Technical Monitor)

    2003-01-01

    The biggest users of GRID technologies came from the science and technology communities. These consist of government, industry and academia (national and international). The NASA GRID is moving into a higher technology readiness level (TRL) today; and as a joint effort among these leaders within government, academia, and industry, the NASA GRID plans to extend availability to enable scientists and engineers across these geographical boundaries collaborate to solve important problems facing the world in the 21 st century. In order to enable NASA programs and missions to use IPG resources for program and mission design, the IPG capabilities needs to be accessible from inside the NASA center networks. However, because different NASA centers maintain different security domains, the GRID penetration across different firewalls is a concern for center security people. This is the reason why some IPG resources are been separated from the NASA center network. Also, because of the center network security and ITAR concerns, the NASA IPG resource owner may not have full control over who can access remotely from outside the NASA center. In order to obtain organizational approval for secured remote access, the IPG infrastructure needs to be adapted to work with the NASA business process. Improvements need to be made before the IPG can be used for NASA program and mission development. The Secured Advanced Federated Environment (SAFE) technology is designed to provide federated security across NASA center and NASA partner's security domains. Instead of one giant center firewall which can be difficult to modify for different GRID applications, the SAFE "micro security domain" provide large number of professionally managed "micro firewalls" that can allow NASA centers to accept remote IPG access without the worry of damaging other center resources. The SAFE policy-driven capability-based federated security mechanism can enable joint organizational and resource owner approved remote

  19. 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.

  20. 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

  1. 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.

  2. Saliency U-Net: A regional saliency map-driven hybrid deep learning network for anomaly segmentation

    Science.gov (United States)

    Karargyros, Alex; Syeda-Mahmood, Tanveer

    2018-02-01

    Deep learning networks are gaining popularity in many medical image analysis tasks due to their generalized ability to automatically extract relevant features from raw images. However, this can make the learning problem unnecessarily harder requiring network architectures of high complexity. In case of anomaly detection, in particular, there is often sufficient regional difference between the anomaly and the surrounding parenchyma that could be easily highlighted through bottom-up saliency operators. In this paper we propose a new hybrid deep learning network using a combination of raw image and such regional maps to more accurately learn the anomalies using simpler network architectures. Specifically, we modify a deep learning network called U-Net using both the raw and pre-segmented images as input to produce joint encoding (contraction) and expansion paths (decoding) in the U-Net. We present results of successfully delineating subdural and epidural hematomas in brain CT imaging and liver hemangioma in abdominal CT images using such network.

  3. 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.

  4. 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

  5. Direct Quantum Dynamics Using Grid-Based Wave Function Propagation and Machine-Learned Potential Energy Surfaces.

    Science.gov (United States)

    Richings, Gareth W; Habershon, Scott

    2017-09-12

    We describe a method for performing nuclear quantum dynamics calculations using standard, grid-based algorithms, including the multiconfiguration time-dependent Hartree (MCTDH) method, where the potential energy surface (PES) is calculated "on-the-fly". The method of Gaussian process regression (GPR) is used to construct a global representation of the PES using values of the energy at points distributed in molecular configuration space during the course of the wavepacket propagation. We demonstrate this direct dynamics approach for both an analytical PES function describing 3-dimensional proton transfer dynamics in malonaldehyde and for 2- and 6-dimensional quantum dynamics simulations of proton transfer in salicylaldimine. In the case of salicylaldimine we also perform calculations in which the PES is constructed using Hartree-Fock calculations through an interface to an ab initio electronic structure code. In all cases, the results of the quantum dynamics simulations are in excellent agreement with previous simulations of both systems yet do not require prior fitting of a PES at any stage. Our approach (implemented in a development version of the Quantics package) opens a route to performing accurate quantum dynamics simulations via wave function propagation of many-dimensional molecular systems in a direct and efficient manner.

  6. Multivariate Statistics and Supervised Learning for Predictive Detection of Unintentional Islanding in Grid-Tied Solar PV Systems

    Directory of Open Access Journals (Sweden)

    Shashank Vyas

    2016-01-01

    Full Text Available Integration of solar photovoltaic (PV generation with power distribution networks leads to many operational challenges and complexities. Unintentional islanding is one of them which is of rising concern given the steady increase in grid-connected PV power. This paper builds up on an exploratory study of unintentional islanding on a modeled radial feeder having large PV penetration. Dynamic simulations, also run in real time, resulted in exploration of unique potential causes of creation of accidental islands. The resulting voltage and current data underwent dimensionality reduction using principal component analysis (PCA which formed the basis for the application of Q statistic control charts for detecting the anomalous currents that could island the system. For reducing the false alarm rate of anomaly detection, Kullback-Leibler (K-L divergence was applied on the principal component projections which concluded that Q statistic based approach alone is not reliable for detection of the symptoms liable to cause unintentional islanding. The obtained data was labeled and a K-nearest neighbor (K-NN binomial classifier was then trained for identification and classification of potential islanding precursors from other power system transients. The three-phase short-circuit fault case was successfully identified as statistically different from islanding symptoms.

  7. 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...

  8. A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

    Directory of Open Access Journals (Sweden)

    Joseph Mascaro

    Full Text Available Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus. The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including--in the latter case--x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag", which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha(-1 when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

  9. A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

    Science.gov (United States)

    Mascaro, Joseph; Asner, Gregory P; Knapp, David E; Kennedy-Bowdoin, Ty; Martin, Roberta E; Anderson, Christopher; Higgins, Mark; Chadwick, K Dana

    2014-01-01

    Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including--in the latter case--x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag"), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha(-1) when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

  10. [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.

  11. Altering spatial priority maps via statistical learning of target selection and distractor filtering.

    Science.gov (United States)

    Ferrante, Oscar; Patacca, Alessia; Di Caro, Valeria; Della Libera, Chiara; Santandrea, Elisa; Chelazzi, Leonardo

    2018-05-01

    The cognitive system has the capacity to learn and make use of environmental regularities - known as statistical learning (SL), including for the implicit guidance of attention. For instance, it is known that attentional selection is biased according to the spatial probability of targets; similarly, changes in distractor filtering can be triggered by the unequal spatial distribution of distractors. Open questions remain regarding the cognitive/neuronal mechanisms underlying SL of target selection and distractor filtering. Crucially, it is unclear whether the two processes rely on shared neuronal machinery, with unavoidable cross-talk, or they are fully independent, an issue that we directly addressed here. In a series of visual search experiments, participants had to discriminate a target stimulus, while ignoring a task-irrelevant salient distractor (when present). We systematically manipulated spatial probabilities of either one or the other stimulus, or both. We then measured performance to evaluate the direct effects of the applied contingent probability distribution (e.g., effects on target selection of the spatial imbalance in target occurrence across locations) as well as its indirect or "transfer" effects (e.g., effects of the same spatial imbalance on distractor filtering across locations). By this approach, we confirmed that SL of both target and distractor location implicitly bias attention. Most importantly, we described substantial indirect effects, with the unequal spatial probability of the target affecting filtering efficiency and, vice versa, the unequal spatial probability of the distractor affecting target selection efficiency across locations. The observed cross-talk demonstrates that SL of target selection and distractor filtering are instantiated via (at least partly) shared neuronal machinery, as further corroborated by strong correlations between direct and indirect effects at the level of individual participants. Our findings are compatible

  12. Self-organizing adaptive map: autonomous learning of curves and surfaces from point samples.

    Science.gov (United States)

    Piastra, Marco

    2013-05-01

    Competitive Hebbian Learning (CHL) (Martinetz, 1993) is a simple and elegant method for estimating the topology of a manifold from point samples. The method has been adopted in a number of self-organizing networks described in the literature and has given rise to related studies in the fields of geometry and computational topology. Recent results from these fields have shown that a faithful reconstruction can be obtained using the CHL method only for curves and surfaces. Within these limitations, these findings constitute a basis for defining a CHL-based, growing self-organizing network that produces a faithful reconstruction of an input manifold. The SOAM (Self-Organizing Adaptive Map) algorithm adapts its local structure autonomously in such a way that it can match the features of the manifold being learned. The adaptation process is driven by the defects arising when the network structure is inadequate, which cause a growth in the density of units. Regions of the network undergo a phase transition and change their behavior whenever a simple, local condition of topological regularity is met. The phase transition is eventually completed across the entire structure and the adaptation process terminates. In specific conditions, the structure thus obtained is homeomorphic to the input manifold. During the adaptation process, the network also has the capability to focus on the acquisition of input point samples in critical regions, with a substantial increase in efficiency. The behavior of the network has been assessed experimentally with typical data sets for surface reconstruction, including suboptimal conditions, e.g. with undersampling and noise. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. 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.

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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.

  20. Whole-Brain Mapping of Neuronal Activity in the Learned Helplessness Model of Depression.

    Science.gov (United States)

    Kim, Yongsoo; Perova, Zinaida; Mirrione, Martine M; Pradhan, Kith; Henn, Fritz A; Shea, Stephen; Osten, Pavel; Li, Bo

    2016-01-01

    Some individuals are resilient, whereas others succumb to despair in repeated stressful situations. The neurobiological mechanisms underlying such divergent behavioral responses remain unclear. Here, we employed an automated method for mapping neuronal activity in search of signatures of stress responses in the entire mouse brain. We used serial two-photon tomography to detect expression of c-FosGFP - a marker of neuronal activation - in c-fosGFP transgenic mice subjected to the learned helplessness (LH) procedure, a widely used model of stress-induced depression-like phenotype in laboratory animals. We found that mice showing "helpless" behavior had an overall brain-wide reduction in the level of neuronal activation compared with mice showing "resilient" behavior, with the exception of a few brain areas, including the locus coeruleus, that were more activated in the helpless mice. In addition, the helpless mice showed a strong trend of having higher similarity in whole-brain activity profile among individuals, suggesting that helplessness is represented by a more stereotypic brain-wide activation pattern. This latter effect was confirmed in rats subjected to the LH procedure, using 2-deoxy-2[18F]fluoro-D-glucose positron emission tomography to assess neural activity. Our findings reveal distinct brain activity markings that correlate with adaptive and maladaptive behavioral responses to stress, and provide a framework for further studies investigating the contribution of specific brain regions to maladaptive stress responses.

  1. Whole-brain mapping of neuronal activity in the learned helplessness model of depression

    Directory of Open Access Journals (Sweden)

    Yongsoo eKim

    2016-02-01

    Full Text Available Some individuals are resilient, whereas others succumb to despair in repeated stressful situations. The neurobiological mechanisms underlying such divergent behavioral responses remain unclear. Here, we employed an automated method for mapping neuronal activity in search of signatures of stress responses in the entire mouse brain. We used serial two-photon tomography to detect expression of c-FosGFP – a marker of neuronal activation – in c-fosGFP transgenic mice subjected to the learned helplessness (LH procedure, a widely used model of stress-induced depression-like phenotype in laboratory animals. We found that mice showing helpless behavior had an overall brain-wide reduction in the level of neuronal activation compared with mice showing resilient behavior, with the exception of a few brain areas, including the locus coeruleus, that were more activated in the helpless mice. In addition, the helpless mice showed a strong trend of having higher similarity in whole brain activity profile among individuals, suggesting that helplessness is represented by a more stereotypic brain-wide activation pattern. This latter effect was confirmed in rats subjected to the LH procedure, using 2-deoxy-2[18F]fluoro-D-glucose positron emission tomography to assess neural activity. Our findings reveal distinct brain activity markings that correlate with adaptive and maladaptive behavioral responses to stress, and provide a framework for further studies investigating the contribution of specific brain regions to maladaptive stress responses.

  2. Model of Peatland Vegetation Species using HyMap Image and Machine Learning

    Science.gov (United States)

    Dayuf Jusuf, Muhammad; Danoedoro, Projo; Muljo Sukojo, Bangun; Hartono

    2017-12-01

    Species Tumih / Parepat (Combretocarpus-rotundatus Mig. Dancer) family Anisophylleaceae and Meranti (Shorea Belangerang, Shorea Teysmanniana Dyer ex Brandis) family Dipterocarpaceae is a group of vegetation species distribution model. Species pioneer is predicted as an indicator of the succession of ecosystem restoration of tropical peatland characteristics and extremely fragile (unique) in the endemic hot spot of Sundaland. Climate change projections and conservation planning are hot topics of current discussion, analysis of alternative approaches and the development of combinations of species projection modelling algorithms through geospatial information systems technology. Approach model to find out the research problem of vegetation level based on the machine learning hybrid method, wavelet and artificial neural networks. Field data are used as a reference collection of natural resource field sample objects and biodiversity assessment. The testing and training ANN data set iterations times 28, achieve a performance value of 0.0867 MSE value is smaller than the ANN training data, above 50%, and spectral accuracy 82.1 %. Identify the location of the sample point position of the Tumih / Parepat vegetation species using HyMap Image is good enough, at least the modelling, design of the species distribution can reach the target in this study. The computation validation rate above 90% proves the calculation can be considered.

  3. 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.

  4. 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

  5. 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

  6. Modelling risk of tick exposure in southern Scandinavia using machine learning techniques, satellite imagery, and human population density maps

    DEFF Research Database (Denmark)

    Kjær, Lene Jung; Korslund, L.; Kjelland, V.

    30 sites (forests and meadows) in each of Denmark, southern Norway and south-eastern Sweden. At each site we measured presence/absence of ticks, and used the data obtained along with environmental satellite images to run Boosted Regression Tree machine learning algorithms to predict overall spatial...... and Sweden), areas with high population densities tend to overlap with these zones.Machine learning techniques allow us to predict for larger areas without having to perform extensive sampling all over the region in question, and we were able to produce models and maps with high predictive value. The results...

  7. Systematically reviewing the potential of concept mapping technologies to promote self-regulated learning in primary and secondary science education

    DEFF Research Database (Denmark)

    Stevenson, Matt P.; Hartmeyer, Rikke; Bentsen, Peter

    2017-01-01

    We systematically searched five databases to assess the potential of concept mapping-based technologies to promote self-regulated learning in science education. Our search uncovered 17 relevant studies that investigated seven different types of learning technologies. We performed a narrative....... Computer software was particularly useful for developing cognitive strategies through ease of use. Teaching agents were particularly useful for developing metacognitive strategies by coupling visualisation of knowledge patterns with performance monitoring, aided by a teaching metaphor. Finally, mobile...... devices and teaching agents were most effective in enhancing motivation. Effects on knowledge gains remain unclear due to small sample sizes....

  8. 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....

  9. Impacts of Integrating the Repertory Grid into an Augmented Reality-Based Learning Design on Students' Learning Achievements, Cognitive Load and Degree of Satisfaction

    Science.gov (United States)

    Wu, Po-Han; Hwang, Gwo-Jen; Yang, Mei-Ling; Chen, Chih-Hung

    2018-01-01

    Augmented reality (AR) offers potential advantages for intensifying environmental context awareness and augmenting students' experiences in real-world environments by dynamically overlapping digital materials with a real-world environment. However, some challenges to AR learning environments have been described, such as participants' cognitive…

  10. 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.

  11. Symposium 20 - PABMB: Teaching biochemistry in a connected world: How Apps-Embedded Assessment can contribute to learning outcomes mapping

    Directory of Open Access Journals (Sweden)

    Eduardo Galembeck

    2015-08-01

    Full Text Available Symposium 20 - PABMB: Teaching biochemistry in a connected world Chair: Miguel Castanho, Universidade de Lisboa, PortugalAbstract:Apps can be designed to provide usage data, and most of them do. These usage data are usually used to map users interests and to deliver more effective ads that are more likely to result in clicks, and sales. We have applied some of these metrics to understand how it can be used to map students’ behavior using educational software. We tested both Google Analytics, and a system we have developed to map learning outcomes and students engagement. Embedded assessment were implemented in app used to teach: 1 Metabolic Pathways; 2 Protein Synthesis, 3 Cell Structure, and 4 Concepts from techniques used in a Biochemistry Lab course. Our preliminary results show that this approach provides valuable information about class outcomes that can be used for both summative and formative assessments.

  12. 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.

  13. The Evolution of the Internet Community and the"Yet-to-Evolve" Smart Grid Community: Parallels and Lessons-to-be-Learned

    Energy Technology Data Exchange (ETDEWEB)

    McParland, Charles

    2009-11-06

    The Smart Grid envisions a transformed US power distribution grid that enables communicating devices, under human supervision, to moderate loads and increase overall system stability and security. This vision explicitly promotes increased participation from a community that, in the past, has had little involvement in power grid operations -the consumer. The potential size of this new community and its member's extensive experience with the public Internet prompts an analysis of the evolution and current state of the Internet as a predictor for best practices in the architectural design of certain portions of the Smart Grid network. Although still evolving, the vision of the Smart Grid is that of a community of communicating and cooperating energy related devices that can be directed to route power and modulate loads in pursuit of an integrated, efficient and secure electrical power grid. The remaking of the present power grid into the Smart Grid is considered as fundamentally transformative as previous developments such as modern computing technology and high bandwidth data communications. However, unlike these earlier developments, which relied on the discovery of critical new technologies (e.g. the transistor or optical fiber transmission lines), the technologies required for the Smart Grid currently exist and, in many cases, are already widely deployed. In contrast to other examples of technical transformations, the path (and success) of the Smart Grid will be determined not by its technology, but by its system architecture. Fortunately, we have a recent example of a transformative force of similar scope that shares a fundamental dependence on our existing communications infrastructure - namely, the Internet. We will explore several ways in which the scale of the Internet and expectations of its users have shaped the present Internet environment. As the presence of consumers within the Smart Grid increases, some experiences from the early growth of the

  14. A Sharing Mind Map-Oriented Approach to Enhance Collaborative Mobile Learning with Digital Archiving Systems

    Science.gov (United States)

    Chang, Jui-Hung; Chiu, Po-Sheng; Huang, Yueh-Min

    2018-01-01

    With the advances in mobile network technology, the use of portable devices and mobile networks for learning is not limited by time and space. Such use, in combination with appropriate learning strategies, can achieve a better effect. Despite the effectiveness of mobile learning, students' learning direction, progress, and achievement may differ.…

  15. 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.

  16. Interpreting map art with a perspective learned from J.M. Blaut

    Science.gov (United States)

    Varanka, D.

    2006-01-01

    Map art has been mentioned only briefly in geographic or cartographic literature, and has been analyzed almost entirely at the interpretive level. This paper attempts to define and evaluate the cartographic value of contemporary map-like art by placing the body of work as a whole in the theoretical concepts proposed by J.M. Blaut and his colleagues about mapping as a cognitive and cultural universal. This paper discusses how map art resembles mapping characteristics similar to those observed empirically in very young children as described in the publications of Blaut and others. The theory proposes that these early mapping skills are later structured and refined by their social context and practice. Diverse cultural contexts account for the varieties, types, and degrees of mapping behavior documented with time and geographic place. The dynamics of early mapping are compared to mapping techniques employed by artists. The discipline of fine art serves as the context surrounding map artists and their work. My visual analysis, research about the art and the artists, and interviews with artists and curators form the basis of my interpretation of these works within varied and multiple contexts of late 20th century map art.

  17. 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...

  18. Cart'Eaux: an automatic mapping procedure for wastewater networks using machine learning and data mining

    Science.gov (United States)

    Bailly, J. S.; Delenne, C.; Chahinian, N.; Bringay, S.; Commandré, B.; Chaumont, M.; Derras, M.; Deruelle, L.; Roche, M.; Rodriguez, F.; Subsol, G.; Teisseire, M.

    2017-12-01

    In France, local government institutions must establish a detailed description of wastewater networks. The information should be available, but it remains fragmented (different formats held by different stakeholders) and incomplete. In the "Cart'Eaux" project, a multidisciplinary team, including an industrial partner, develops a global methodology using Machine Learning and Data Mining approaches applied to various types of large data to recover information in the aim of mapping urban sewage systems for hydraulic modelling. Deep-learning is first applied using a Convolution Neural Network to localize manhole covers on 5 cm resolution aerial RGB images. The detected manhole covers are then automatically connected using a tree-shaped graph constrained by industry rules. Based on a Delaunay triangulation, connections are chosen to minimize a cost function depending on pipe length, slope and possible intersection with roads or buildings. A stochastic version of this algorithm is currently being developed to account for positional uncertainty and detection errors, and generate sets of probable networks. As more information is required for hydraulic modeling (slopes, diameters, materials, etc.), text data mining is used to extract network characteristics from data posted on the Web or available through governmental or specific databases. Using an appropriate list of keywords, the web is scoured for documents which are saved in text format. The thematic entities are identified and linked to the surrounding spatial and temporal entities. The methodology is developed and tested on two towns in southern France. The primary results are encouraging: 54% of manhole covers are detected with few false detections, enabling the reconstruction of probable networks. The data mining results are still being investigated. It is clear at this stage that getting numerical values on specific pipes will be challenging. Thus, when no information is found, decision rules will be used to

  19. Lessons learned from a pilot implementation of the UMLS information sources map.

    Science.gov (United States)

    Miller, P L; Frawley, S J; Wright, L; Roderer, N K; Powsner, S M

    1995-01-01

    OBJECTIVE: To explore the software design issues involved in implementing an operational information sources map (ISM) knowledge base (KB) and system of navigational tools that can help medical users access network-based information sources relevant to a biomedical question. DESIGN: A pilot biomedical ISM KB and associated client-server software (ISM/Explorer) have been developed to help students, clinicians, researchers, and staff access network-based information sources, as part of the National Library of Medicine's (NLM) multi-institutional Unified Medical Language System (UMLS) project. The system allows the user to specify and constrain a search for a biomedical question of interest. The system then returns a list of sources matching the search. At this point the user may request 1) further information about a source, 2) that the list of sources be regrouped by different criteria to allow the user to get a better overall appreciation of the set of retrieved sources as a whole, or 3) automatic connection to a source. RESULTS: The pilot system operates in client-server mode and currently contains coded information for 121 sources. It is in routine use from approximately 40 workstations at the Yale School of Medicine. The lessons that have been learned are that: 1) it is important to make access to different versions of a source as seamless as possible, 2) achieving seamless, cross-platform access to heterogeneous sources is difficult, 3) significant differences exist between coding the subject content of an electronic information resource versus that of an article or a book, 4) customizing the ISM to multiple institutions entails significant complexities, and 5) there are many design trade-offs between specifying searches and viewing sets of retrieved sources that must be taken into consideration. CONCLUSION: An ISM KB and navigational tools have been constructed. In the process, much has been learned about the complexities of development and evaluation in this

  20. Lessons learned from a pilot implementation of the UMLS information sources map.

    Science.gov (United States)

    Miller, P L; Frawley, S J; Wright, L; Roderer, N K; Powsner, S M

    1995-01-01

    To explore the software design issues involved in implementing an operational information sources map (ISM) knowledge base (KB) and system of navigational tools that can help medical users access network-based information sources relevant to a biomedical question. A pilot biomedical ISM KB and associated client-server software (ISM/Explorer) have been developed to help students, clinicians, researchers, and staff access network-based information sources, as part of the National Library of Medicine's (NLM) multi-institutional Unified Medical Language System (UMLS) project. The system allows the user to specify and constrain a search for a biomedical question of interest. The system then returns a list of sources matching the search. At this point the user may request 1) further information about a source, 2) that the list of sources be regrouped by different criteria to allow the user to get a better overall appreciation of the set of retrieved sources as a whole, or 3) automatic connection to a source. The pilot system operates in client-server mode and currently contains coded information for 121 sources. It is in routine use from approximately 40 workstations at the Yale School of Medicine. The lessons that have been learned are that: 1) it is important to make access to different versions of a source as seamless as possible, 2) achieving seamless, cross-platform access to heterogeneous sources is difficult, 3) significant differences exist between coding the subject content of an electronic information resource versus that of an article or a book, 4) customizing the ISM to multiple institutions entails significant complexities, and 5) there are many design trade-offs between specifying searches and viewing sets of retrieved sources that must be taken into consideration. An ISM KB and navigational tools have been constructed. In the process, much has been learned about the complexities of development and evaluation in this new environment, which are different

  1. 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...

  2. Mapping membrane activity in undiscovered peptide sequence space using machine learning.

    Science.gov (United States)

    Lee, Ernest Y; Fulan, Benjamin M; Wong, Gerard C L; Ferguson, Andrew L

    2016-11-29

    There are some ∼1,100 known antimicrobial peptides (AMPs), which permeabilize microbial membranes but have diverse sequences. Here, we develop a support vector machine (SVM)-based classifier to investigate ⍺-helical AMPs and the interrelated nature of their functional commonality and sequence homology. SVM is used to search the undiscovered peptide sequence space and identify Pareto-optimal candidates that simultaneously maximize the distance σ from the SVM hyperplane (thus maximize its "antimicrobialness") and its ⍺-helicity, but minimize mutational distance to known AMPs. By calibrating SVM machine learning results with killing assays and small-angle X-ray scattering (SAXS), we find that the SVM metric σ correlates not with a peptide's minimum inhibitory concentration (MIC), but rather its ability to generate negative Gaussian membrane curvature. This surprising result provides a topological basis for membrane activity common to AMPs. Moreover, we highlight an important distinction between the maximal recognizability of a sequence to a trained AMP classifier (its ability to generate membrane curvature) and its maximal antimicrobial efficacy. As mutational distances are increased from known AMPs, we find AMP-like sequences that are increasingly difficult for nature to discover via simple mutation. Using the sequence map as a discovery tool, we find a unexpectedly diverse taxonomy of sequences that are just as membrane-active as known AMPs, but with a broad range of primary functions distinct from AMP functions, including endogenous neuropeptides, viral fusion proteins, topogenic peptides, and amyloids. The SVM classifier is useful as a general detector of membrane activity in peptide sequences.

  3. Learning from Nature - Mapping of Complex Hydrological and Geomorphological Process Systems for More Realistic Modelling of Hazard-related Maps

    Science.gov (United States)

    Chifflard, Peter; Tilch, Nils

    2010-05-01

    Introduction Hydrological or geomorphological processes in nature are often very diverse and complex. This is partly due to the regional characteristics which vary over time and space, as well as changeable process-initiating and -controlling factors. Despite being aware of this complexity, such aspects are usually neglected in the modelling of hazard-related maps due to several reasons. But particularly when it comes to creating more realistic maps, this would be an essential component to consider. The first important step towards solving this problem would be to collect data relating to regional conditions which vary over time and geographical location, along with indicators of complex processes. Data should be acquired promptly during and after events, and subsequently digitally combined and analysed. Study area In June 2009, considerable damage occurred in the residential area of Klingfurth (Lower Austria) as a result of great pre-event wetness and repeatedly heavy rainfall, leading to flooding, debris flow deposit and gravitational mass movement. One of the causes is the fact that the meso-scale watershed (16 km²) of the Klingfurth stream is characterised by adverse geological and hydrological conditions. Additionally, the river system network with its discharge concentration within the residential zone contributes considerably to flooding, particularly during excessive rainfall across the entire region, as the flood peaks from different parts of the catchment area are superposed. First results of mapping Hydro(geo)logical surveys across the entire catchment area have shown that - over 600 gravitational mass movements of various type and stage have occurred. 516 of those have acted as a bed load source, while 325 mass movements had not reached the final stage yet and could thus supply bed load in the future. It should be noted that large mass movements in the initial or intermediate stage were predominately found in clayey-silty areas and weathered material

  4. 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.

  5. 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...

  6. Concept mapping to improve team work, team learning and care of the person with dementia and behavioural and psychological symptoms.

    Science.gov (United States)

    Aberdeen, Suzanne M; Byrne, Graeme

    2018-04-01

    The incidence of behavioural and psychological symptoms of dementia in residential aged care facilities is high. Effective team work and knowledgeable staff are cited as important facilitators of appropriate care responses to clients with these symptoms, but to achieve this within a resource-poor workplace can be challenging. In the study reported in this paper, concept mapping was trialled to enhance multifocal person-centred assessment and care planning as well as team learning. The outcomes of team concept mapping were evaluated using a quasi-experimental design with pre- and post-testing in 11 selected Australian residential aged care facilities , including two control residential aged care facilities , over a nine-month period. It was demonstrated that use of concept mapping improved team function, measured as effectiveness of care planning, as well as enhancing learning, with increased knowledge of dementia care even amongst staff who were not directly involved with the process. It is suggested that these results may be generalizable to other countries and care settings.

  7. Evaluating maps produced by urban search and rescue robots: Lessons learned from RoboCup

    NARCIS (Netherlands)

    Balaguer, B.; Balakirsky, S.; Carpin, S.; Visser, A.

    2009-01-01

    This paper presents the map evaluation methodology developed for the Virtual Robots Rescue competition held as part of RoboCup. The procedure aims to evaluate the quality of maps produced by multi-robot systems with respect to a number of factors, including usability, exploration, annotation and

  8. Learning about a Level Physics Students' Understandings of Particle Physics Using Concept Mapping

    Science.gov (United States)

    Gourlay, H.

    2017-01-01

    This paper describes a small-scale piece of research using concept mapping to elicit A level students' understandings of particle physics. Fifty-nine year 12 (16- and 17 year-old) students from two London schools participated. The exercise took place during school physics lessons. Students were instructed how to make a concept map and were…

  9. 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

  10. The Effect of Mind Mapping on EFL Students’ Idea Development in Argumentative Writing across Gender Differences and Learning Styles

    Directory of Open Access Journals (Sweden)

    Ary Setya Budhi Ningrum

    2016-06-01

    Full Text Available The purpose of the study was to determine the impact of mind mapping as a strategy in generating ideas before writing on the EFL students’ idea development in argumentative writing as perceived from their gender differences and learning styles. By conducting an experimental investigation at university level in Indonesia, two existing TOEFL classes at the State Islamic Studies (STAIN in Kediri were selected by a lottery to group 1: using linear notes (N=41, and group 2: using mind mapping (N=41. For analyzing the data, Analysis of covariance (ANCOVA were utilized by using students’ TOEFL score as the covariate variable. The result findings indicated that there is no significant difference on the students’ idea developments in writing between the control and the experimental groups. These result also revealed that there is no significant difference on the students’ idea development in writing between gender differences, and among the students’ learning styles. Furthermore, there is no significant interaction between treatment and gender differences, and there is no significant interaction between treatment and learning styles.

  11. Grid Integration Research | Wind | NREL

    Science.gov (United States)

    Grid Integration Research Grid Integration Research Researchers study grid integration of wind three wind turbines with transmission lines in the background. Capabilities NREL's grid integration electric power system operators to more efficiently manage wind grid system integration. A photo of

  12. 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

  13. Meter-scale Urban Land Cover Mapping for EPA EnviroAtlas Using Machine Learning and OBIA Remote Sensing Techniques

    Science.gov (United States)

    Pilant, A. N.; Baynes, J.; Dannenberg, M.; Riegel, J.; Rudder, C.; Endres, K.

    2013-12-01

    US EPA EnviroAtlas is an online collection of tools and resources that provides geospatial data, maps, research, and analysis on the relationships between nature, people, health, and the economy (http://www.epa.gov/research/enviroatlas/index.htm). Using EnviroAtlas, you can see and explore information related to the benefits (e.g., ecosystem services) that humans receive from nature, including clean air, clean and plentiful water, natural hazard mitigation, biodiversity conservation, food, fuel, and materials, recreational opportunities, and cultural and aesthetic value. EPA developed several urban land cover maps at very high spatial resolution (one-meter pixel size) for a portion of EnviroAtlas devoted to urban studies. This urban mapping effort supported analysis of relations among land cover, human health and demographics at the US Census Block Group level. Supervised classification of 2010 USDA NAIP (National Agricultural Imagery Program) digital aerial photos produced eight-class land cover maps for several cities, including Durham, NC, Portland, ME, Tampa, FL, New Bedford, MA, Pittsburgh, PA, Portland, OR, and Milwaukee, WI. Semi-automated feature extraction methods were used to classify the NAIP imagery: genetic algorithms/machine learning, random forest, and object-based image analysis (OBIA). In this presentation we describe the image processing and fuzzy accuracy assessment methods used, and report on some sustainability and ecosystem service metrics computed using this land cover as input (e.g., carbon sequestration from USFS iTREE model; health and demographics in relation to road buffer forest width). We also discuss the land cover classification schema (a modified Anderson Level 1 after the National Land Cover Data (NLCD)), and offer some observations on lessons learned. Meter-scale urban land cover in Portland, OR overlaid on NAIP aerial photo. Streets, buildings and individual trees are identifiable.

  14. Ischemia Detection Using Supervised Learning for Hierarchical Neural Networks Based on Kohonen-Maps

    National Research Council Canada - National Science Library

    Vladutu, L

    2001-01-01

    .... The motivation for developing the Supervising Network - Self Organizing Map (sNet-SOM) model is to design computationally effective solutions for the particular problem of ischemia detection and other similar applications...

  15. Parallel grid population

    Science.gov (United States)

    Wald, Ingo; Ize, Santiago

    2015-07-28

    Parallel population of a grid with a plurality of objects using a plurality of processors. One example embodiment is a method for parallel population of a grid with a plurality of objects using a plurality of processors. The method includes a first act of dividing a grid into n distinct grid portions, where n is the number of processors available for populating the grid. The method also includes acts of dividing a plurality of objects into n distinct sets of objects, assigning a distinct set of objects to each processor such that each processor determines by which distinct grid portion(s) each object in its distinct set of objects is at least partially bounded, and assigning a distinct grid portion to each processor such that each processor populates its distinct grid portion with any objects that were previously determined to be at least partially bounded by its distinct grid portion.

  16. Thorough statistical comparison of machine learning regression models and their ensembles for sub-pixel imperviousness and imperviousness change mapping

    Directory of Open Access Journals (Sweden)

    Drzewiecki Wojciech

    2017-12-01

    Full Text Available We evaluated the performance of nine machine learning regression algorithms and their ensembles for sub-pixel estimation of impervious areas coverages from Landsat imagery. The accuracy of imperviousness mapping in individual time points was assessed based on RMSE, MAE and R2. These measures were also used for the assessment of imperviousness change intensity estimations. The applicability for detection of relevant changes in impervious areas coverages at sub-pixel level was evaluated using overall accuracy, F-measure and ROC Area Under Curve. The results proved that Cubist algorithm may be advised for Landsat-based mapping of imperviousness for single dates. Stochastic gradient boosting of regression trees (GBM may be also considered for this purpose. However, Random Forest algorithm is endorsed for both imperviousness change detection and mapping of its intensity. In all applications the heterogeneous model ensembles performed at least as well as the best individual models or better. They may be recommended for improving the quality of sub-pixel imperviousness and imperviousness change mapping. The study revealed also limitations of the investigated methodology for detection of subtle changes of imperviousness inside the pixel. None of the tested approaches was able to reliably classify changed and non-changed pixels if the relevant change threshold was set as one or three percent. Also for fi ve percent change threshold most of algorithms did not ensure that the accuracy of change map is higher than the accuracy of random classifi er. For the threshold of relevant change set as ten percent all approaches performed satisfactory.

  17. Thorough statistical comparison of machine learning regression models and their ensembles for sub-pixel imperviousness and imperviousness change mapping

    Science.gov (United States)

    Drzewiecki, Wojciech

    2017-12-01

    We evaluated the performance of nine machine learning regression algorithms and their ensembles for sub-pixel estimation of impervious areas coverages from Landsat imagery. The accuracy of imperviousness mapping in individual time points was assessed based on RMSE, MAE and R2. These measures were also used for the assessment of imperviousness change intensity estimations. The applicability for detection of relevant changes in impervious areas coverages at sub-pixel level was evaluated using overall accuracy, F-measure and ROC Area Under Curve. The results proved that Cubist algorithm may be advised for Landsat-based mapping of imperviousness for single dates. Stochastic gradient boosting of regression trees (GBM) may be also considered for this purpose. However, Random Forest algorithm is endorsed for both imperviousness change detection and mapping of its intensity. In all applications the heterogeneous model ensembles performed at least as well as the best individual models or better. They may be recommended for improving the quality of sub-pixel imperviousness and imperviousness change mapping. The study revealed also limitations of the investigated methodology for detection of subtle changes of imperviousness inside the pixel. None of the tested approaches was able to reliably classify changed and non-changed pixels if the relevant change threshold was set as one or three percent. Also for fi ve percent change threshold most of algorithms did not ensure that the accuracy of change map is higher than the accuracy of random classifi er. For the threshold of relevant change set as ten percent all approaches performed satisfactory.

  18. Logging Student Learning via a Puerto Rico-based Geologic Mapping Game on the Google Earth Virtual Globe

    Science.gov (United States)

    Gobert, J.; Toto, E.; Wild, S. C.; Dordevic, M. M.; De Paor, D. G.

    2013-12-01

    A hindrance to migrating undergraduate geoscience courses online is the challenge of giving students a quasi-authentic field experience. As part of an NSF TUES Type 2 project (# NSF-DUE 1022755), we addressed this challenge by designing a Google Earth (GE) mapping game centered on Puerto Rico, a place we chose in order to connect with underrepresented minorities but also because its simple geologic divisions minimized map complexity. The game invites student groups to explore the island and draw a geological map with these divisions: Rugged Volcanic Terrain, Limestone Karst Topography, and Surficial Sands & Gravels. Students, represented as avatars via COLLADA models and the GE browser plugin, can move about, text fellow students, and click a 'drill here' button that tells them what lies underground. They need to learn to read the topography because the number of holes they can drill is limited to 30. Then using the GE Polygon tool, they create a map, aided by a custom 'snapping' algorithm that stitches adjacent contacts, preventing gaps and overlaps, and they submit this map for evaluation by their instructor, an evaluation we purposefully did not automate. Initially we assigned students to groups of 4 and gave each group a field vehicle avatar with a designated driver, however students hated the experience unless they were the designated driver, so we revised the game to allow all students to roam independently, however we retained the mutual texting feature amongst students in groups. We implemented the activity with undergraduates from a university in South East USA. All student movements and actions on the GE terrain were logged. We wrote algorithms to evaluate student learning processes via log files, including, but not limited to, number of places drilled and their locations. Pre-post gains were examined, as well as correlations between data from log files and pre-post data. There was a small but statistically significant post-pre gain including a positive

  19. Hunting and Gathering: New Imperatives in Mapping and Collecting Student Learning Data to Assure Quality Outcomes

    Science.gov (United States)

    Lawson, Romy; Taylor, Tracy; French, Erica; Fallshaw, Eveline; Hall, Cathy; Kinash, Shelley; Summers, Jane

    2015-01-01

    Assurance of learning (AOL) is a quality enhancement and quality assurance process used in higher education. It involves a process of determining programme learning outcomes and standards, and systematically gathering evidence to measure students' performance on these. The systematic assessment of whole-of-programme outcomes provides a basis for…

  20. Mapping Remote and Multidisciplinary Learning Barriers: Lessons from "Challenge-Based Innovation" at CERN

    Science.gov (United States)

    Jensen, Matilde Bisballe; Utriainen, Tuuli Maria; Steinert, Martin

    2018-01-01

    This paper presents the experienced difficulties of students participating in the multidisciplinary, remote collaborating engineering design course challenge-based innovation at CERN. This is with the aim to identify learning barriers and improve future learning experiences. We statistically analyse the rated differences between distinct design…

  1. Participatory Evaluation and Learning: A Case Example Involving Ripple Effects Mapping of a Tourism Assessment Program

    Science.gov (United States)

    Bhattacharyya, Rani; Templin, Elizabeth; Messer, Cynthia; Chazdon, Scott

    2017-01-01

    Engaging communities through research-based participatory evaluation and learning methods can be rewarding for both a community and Extension. A case study of a community tourism development program evaluation shows how participatory evaluation and learning can be mutually reinforcing activities. Many communities value the opportunity to reflect…

  2. Cognitive Maps and the Structure of Observed Learning Outcome Assessment of Physiotherapy Students' Ethical Reasoning Knowledge

    Science.gov (United States)

    Jones, Mark; van Kessel, Gisela; Swisher, Laura; Beckstead, Jason; Edwards, Ian

    2014-01-01

    Assessment of student learning in complex areas is challenging, particularly when there is interest in students' deeper understanding and connectivity of concepts. Assessment of ethics learning has been limited by lack of consensus regarding what is effective and an overfocus on quantification at the expense of clinical or ethical relevance.…

  3. Brain-Wide Maps of "Fos" Expression during Fear Learning and Recall

    Science.gov (United States)

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

    2017-01-01

    "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…

  4. Perceptual Learning in Early Mathematics: Interacting with Problem Structure Improves Mapping, Solving and Fluency

    Science.gov (United States)

    Thai, Khanh-Phuong; Son, Ji Y.; Hoffman, Jessica; Devers, Christopher; Kellman, Philip J.

    2014-01-01

    Mathematics is the study of structure but students think of math as solving problems according to rules. Students can learn procedures, but they often have trouble knowing when to apply learned procedures, especially to problems unlike those they trained with. In this study, the authors rely on the psychological mechanism of perceptual learning…

  5. INDUSTRY PARTNERSHIPS LEARNING MODELS FOR SURVEYING AND MAPPING OF VOCATIONAL HIGH SCHOOLS

    Directory of Open Access Journals (Sweden)

    Sunar Rochmadi

    2016-09-01

    Full Text Available This study aims to identify a learning involving the world of work, to formulate the learning model, and to evaluate the learning model. This study used a qualitative approach for design and development research, consisting of the development and validation steps. The study concludes as follows. (1 the learning through partnerships having been conducted in all vocational high schools were industrial practice and vocational practice examination. (2 the constraints of learning through partnerships were mainly the far distance and the industry schedules that did not always match with the school’s. (3 the model development could be done by improving the learning quality by industrial practices in the private companies and with adding the learning model by industry visits, guest teaching, and up-to-date technology training. (4 the implementation of the developed model showed the feasibility and the effectiveness to prepare the students with the competencies required by the world of work. (5 the learning models through partnerships that could be practiced were guest teaching, orientation for industrial practice, industrial practices, students’ industry visits, up-to-date technology training, and vocational practice examination.

  6. A knowledge representation approach using fuzzy cognitive maps for better navigation support in an adaptive learning system.

    Science.gov (United States)

    Chrysafiadi, Konstantina; Virvou, Maria

    2013-12-01

    In this paper a knowledge representation approach of an adaptive and/or personalized tutoring system is presented. The domain knowledge should be represented in a more realistic way in order to allow the adaptive and/or personalized tutoring system to deliver the learning material to each individual learner dynamically taking into account her/his learning needs and her/his different learning pace. To succeed this, the domain knowledge representation has to depict the possible increase or decrease of the learner's knowledge. Considering that the domain concepts that constitute the learning material are not independent from each other, the knowledge representation approach has to allow the system to recognize either the domain concepts that are already partly or completely known for a learner, or the domain concepts that s/he has forgotten, taking into account the learner's knowledge level of the related concepts. In other words, the system should be informed about the knowledge dependencies that exist among the domain concepts of the learning material, as well as the strength on impact of each domain concept on others. Fuzzy Cognitive Maps (FCMs) seem to be an ideal way for representing graphically this kind of information. The suggested knowledge representation approach has been implemented in an e-learning adaptive system for teaching computer programming. The particular system was used by the students of a postgraduate program in the field of Informatics in the University of Piraeus and was compared with a corresponding system, in which the domain knowledge was represented using the most common used technique of network of concepts. The results of the evaluation were very encouraging.

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. 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

  12. Smart grid security

    CERN Document Server

    Goel, Sanjay; Papakonstantinou, Vagelis; Kloza, Dariusz

    2015-01-01

    This book on smart grid security is meant for a broad audience from managers to technical experts. It highlights security challenges that are faced in the smart grid as we widely deploy it across the landscape. It starts with a brief overview of the smart grid and then discusses some of the reported attacks on the grid. It covers network threats, cyber physical threats, smart metering threats, as well as privacy issues in the smart grid. Along with the threats the book discusses the means to improve smart grid security and the standards that are emerging in the field. The second part of the b

  13. 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

  14. Mapping Woodland Cover in the Miombo Ecosystem: A Comparison of Machine Learning Classifiers

    Directory of Open Access Journals (Sweden)

    Courage Kamusoko

    2014-06-01

    Full Text Available Miombo woodlands in Southern Africa are experiencing accelerated changes due to natural and anthropogenic disturbances. In order to formulate sustainable woodland management strategies in the Miombo ecosystem, timely and up-to-date land cover information is required. Recent advances in remote sensing technology have improved land cover mapping in tropical evergreen ecosystems. However, woodland cover mapping remains a challenge in the Miombo ecosystem. The objective of the study was to evaluate the performance of decision trees (DT, random forests (RF, and support vector machines (SVM in the context of improving woodland and non-woodland cover mapping in the Miombo ecosystem in Zimbabwe. We used Multidate Landsat 8 spectral and spatial dependence (Moran’s I variables to map woodland and non-woodland cover. Results show that RF classifier outperformed the SVM and DT classifiers by 4% and 15%, respectively. The RF importance measures show that multidate Landsat 8 spectral and spatial variables had the greatest influence on class-separability in the study area. Therefore, the RF classifier has potential to improve woodland cover mapping in the Miombo ecosystem.

  15. The Effect of Mnemonic and Mapping Techniques on L2 Vocabulary Learning

    Directory of Open Access Journals (Sweden)

    Abbas Ali Zarei

    2016-01-01

    Full Text Available The present study investigated the effects of selected presentation techniques including the keyword method, the peg word method, the loci method, argument mapping, concept mapping and mind mapping on L2 vocabulary comprehension and production. To this end, a sample of 151 Iranian female students from a public pre-university school in Islam Shahr was selected. They were assigned to six groups. Each group was randomly assigned to one of the afore-mentioned treatment conditions. After the experimental period, two post-tests in multiple choice and fill-in-the-blanks formats were administered to assess the participants’ vocabulary comprehension and production. Two independent One-Way ANOVA procedures were used to analyze the obtained data. The results showed that the differences among the effects of the above-mentioned techniques were statistically significant in both vocabulary comprehension and production. These findings can have implications for learners, teachers, and materials’ developers.

  16. Mapping remote and multidisciplinary learning barriers: lessons from challenge-based innovation at CERN

    Science.gov (United States)

    Jensen, Matilde Bisballe; Utriainen, Tuuli Maria; Steinert, Martin

    2018-01-01

    This paper presents the experienced difficulties of students participating in the multidisciplinary, remote collaborating engineering design course challenge-based innovation at CERN. This is with the aim to identify learning barriers and improve future learning experiences. We statistically analyse the rated differences between distinct design activities, educational background and remote vs. co-located collaboration. The analysis is based on a quantitative and qualitative questionnaire (N = 37). Our analysis found significant ranking differences between remote and co-located activities. This questions whether the remote factor might be a barrier for the originally intended learning goals. Further a correlation between analytical and converging design phases was identified. Hence, future facilitators are suggested to help students in the transition from one design phase to the next rather than only teaching methods in the individual design phases. Finally, we discuss how educators address the identified learning barriers when designing future courses including multidisciplinary or remote collaboration.

  17. 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

  18. Grid generation methods

    CERN Document Server

    Liseikin, Vladimir D

    2010-01-01

    This book is an introduction to structured and unstructured grid methods in scientific computing, addressing graduate students, scientists as well as practitioners. Basic local and integral grid quality measures are formulated and new approaches to mesh generation are reviewed. In addition to the content of the successful first edition, a more detailed and practice oriented description of monitor metrics in Beltrami and diffusion equations is given for generating adaptive numerical grids. Also, new techniques developed by the author are presented, in particular a technique based on the inverted form of Beltrami’s partial differential equations with respect to control metrics. This technique allows the generation of adaptive grids for a wide variety of computational physics problems, including grid clustering to given function values and gradients, grid alignment with given vector fields, and combinations thereof. Applications of geometric methods to the analysis of numerical grid behavior as well as grid ge...

  19. Historical maintenance relevant information road-map for a self-learning maintenance prediction procedural approach

    Science.gov (United States)

    Morales, Francisco J.; Reyes, Antonio; Cáceres, Noelia; Romero, Luis M.; Benitez, Francisco G.; Morgado, Joao; Duarte, Emanuel; Martins, Teresa

    2017-09-01

    A large percentage of transport infrastructures are composed of linear assets, such as roads and rail tracks. The large social and economic relevance of these constructions force the stakeholders to ensure a prolonged health/durability. Even though, inevitable malfunctioning, breaking down, and out-of-service periods arise randomly during the life cycle of the infrastructure. Predictive maintenance techniques tend to diminish the appearance of unpredicted failures and the execution of needed corrective interventions, envisaging the adequate interventions to be conducted before failures show up. This communication presents: i) A procedural approach, to be conducted, in order to collect the relevant information regarding the evolving state condition of the assets involved in all maintenance interventions; this reported and stored information constitutes a rich historical data base to train Machine Learning algorithms in order to generate reliable predictions of the interventions to be carried out in further time scenarios. ii) A schematic flow chart of the automatic learning procedure. iii) Self-learning rules from automatic learning from false positive/negatives. The description, testing, automatic learning approach and the outcomes of a pilot case are presented; finally some conclusions are outlined regarding the methodology proposed for improving the self-learning predictive capability.

  20. 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)

  1. Floodplain Mapping for the Continental United States Using Machine Learning Techniques and Watershed Characteristics

    Science.gov (United States)

    Jafarzadegan, K.; Merwade, V.; Saksena, S.

    2017-12-01

    Using conventional hydrodynamic methods for floodplain mapping in large-scale and data-scarce regions is problematic due to the high cost of these methods, lack of reliable data and uncertainty propagation. In this study a new framework is proposed to generate 100-year floodplains for any gauged or ungauged watershed across the United States (U.S.). This framework uses Flood Insurance Rate Maps (FIRMs), topographic, climatic and land use data which are freely available for entire U.S. for floodplain mapping. The framework consists of three components, including a Random Forest classifier for watershed classification, a Probabilistic Threshold Binary Classifier (PTBC) for generating the floodplains, and a lookup table for linking the Random Forest classifier to the PTBC. The effectiveness and reliability of the proposed framework is tested on 145 watersheds from various geographical locations in the U.S. The validation results show that around 80 percent of total watersheds are predicted well, 14 percent have acceptable fit and less than five percent are predicted poorly compared to FIRMs. Another advantage of this framework is its ability in generating floodplains for all small rivers and tributaries. Due to the high accuracy and efficiency of this framework, it can be used as a preliminary decision making tool to generate 100-year floodplain maps for data-scarce regions and all tributaries where hydrodynamic methods are difficult to use.

  2. 3-D Mind Maps: Placing Young Children in the Centre of Their Own Learning

    Science.gov (United States)

    Howitt, Christine

    2009-01-01

    Three-dimensional mind maps are a highly effective tool for providing engaging, kinaesthetic and sensory experiences for young children, with real objects used to promote the sharing of knowledge and the creation of connections. The use of real objects allows children the opportunity to connect with those objects at a personal level, thus placing…

  3. Chimera Grid Tools

    Science.gov (United States)

    Chan, William M.; Rogers, Stuart E.; Nash, Steven M.; Buning, Pieter G.; Meakin, Robert

    2005-01-01

    Chimera Grid Tools (CGT) is a software package for performing computational fluid dynamics (CFD) analysis utilizing the Chimera-overset-grid method. For modeling flows with viscosity about geometrically complex bodies in relative motion, the Chimera-overset-grid method is among the most computationally cost-effective methods for obtaining accurate aerodynamic results. CGT contains a large collection of tools for generating overset grids, preparing inputs for computer programs that solve equations of flow on the grids, and post-processing of flow-solution data. The tools in CGT include grid editing tools, surface-grid-generation tools, volume-grid-generation tools, utility scripts, configuration scripts, and tools for post-processing (including generation of animated images of flows and calculating forces and moments exerted on affected bodies). One of the tools, denoted OVERGRID, is a graphical user interface (GUI) that serves to visualize the grids and flow solutions and provides central access to many other tools. The GUI facilitates the generation of grids for a new flow-field configuration. Scripts that follow the grid generation process can then be constructed to mostly automate grid generation for similar configurations. CGT is designed for use in conjunction with a computer-aided-design program that provides the geometry description of the bodies, and a flow-solver program.

  4. Bayesian grid matching

    DEFF Research Database (Denmark)

    Hartelius, Karsten; Carstensen, Jens Michael

    2003-01-01

    A method for locating distorted grid structures in images is presented. The method is based on the theories of template matching and Bayesian image restoration. The grid is modeled as a deformable template. Prior knowledge of the grid is described through a Markov random field (MRF) model which r...

  5. Smart grid in China

    DEFF Research Database (Denmark)

    Sommer, Simon; Ma, Zheng; Jørgensen, Bo Nørregaard

    2015-01-01

    China is planning to transform its traditional power grid in favour of a smart grid, since it allows a more economically efficient and a more environmentally friendly transmission and distribution of electricity. Thus, a nationwide smart grid is likely to save tremendous amounts of resources...

  6. Evaluation of Four Supervised Learning Methods for Benthic Habitat Mapping Using Backscatter from Multi-Beam Sonar

    Directory of Open Access Journals (Sweden)

    Jacquomo Monk

    2012-11-01

    Full Text Available An understanding of the distribution and extent of marine habitats is essential for the implementation of ecosystem-based management strategies. Historically this had been difficult in marine environments until the advancement of acoustic sensors. This study demonstrates the applicability of supervised learning techniques for benthic habitat characterization using angular backscatter response data. With the advancement of multibeam echo-sounder (MBES technology, full coverage datasets of physical structure over vast regions of the seafloor are now achievable. Supervised learning methods typically applied to terrestrial remote sensing provide a cost-effective approach for habitat characterization in marine systems. However the comparison of the relative performance of different classifiers using acoustic data is limited. Characterization of acoustic backscatter data from MBES using four different supervised learning methods to generate benthic habitat maps is presented. Maximum Likelihood Classifier (MLC, Quick, Unbiased, Efficient Statistical Tree (QUEST, Random Forest (RF and Support Vector Machine (SVM were evaluated to classify angular backscatter response into habitat classes using training data acquired from underwater video observations. Results for biota classifications indicated that SVM and RF produced the highest accuracies, followed by QUEST and MLC, respectively. The most important backscatter data were from the moderate incidence angles between 30° and 50°. This study presents initial results for understanding how acoustic backscatter from MBES can be optimized for the characterization of marine benthic biological habitats.

  7. Mapping Judicial Dialogue across National Borders: An Exploratory Network Study of Learning from Lobbying among European Intellectual Property Judges

    Directory of Open Access Journals (Sweden)

    Emmanuel Lazega

    2012-05-01

    Full Text Available This paper looks at dialogue and collective learning across borders through personal networks of judges. We focus on judges participating in the Venice Forum, bringing together European patent judges involved in institutional lobbying for the construction of a European Patent Court. Empirical observation shows that personal networks of discussion with foreign judges, reading of their work and references to their decisions do exist in this milieu and can be mapped. Our network study shows that judges from some European countries are more active in this dialogue than judges from other countries. The learning process is driven, to some extent, by a small subset of super-central judges who frame this dialogue and can be considered to be opinion leaders in this social milieu. We measure a strong level of consensus among the judges on several controversial issues surrounding the procedure of a possible future European Patent Court. But strong differences between them remain. Dialogue and collective learning do not, by themselves, lead to convergence towards a uniform position in these controversies.

  8. RLAM: A Dynamic and Efficient Reinforcement Learning-Based Adaptive Mapping Scheme in Mobile WiMAX Networks

    Directory of Open Access Journals (Sweden)

    M. Louta

    2014-01-01

    Full Text Available WiMAX (Worldwide Interoperability for Microwave Access constitutes a candidate networking technology towards the 4G vision realization. By adopting the Orthogonal Frequency Division Multiple Access (OFDMA technique, the latest IEEE 802.16x amendments manage to provide QoS-aware access services with full mobility support. A number of interesting scheduling and mapping schemes have been proposed in research literature. However, they neglect a considerable asset of the OFDMA-based wireless systems: the dynamic adjustment of the downlink-to-uplink width ratio. In order to fully exploit the supported mobile WiMAX features, we design, develop, and evaluate a rigorous adaptive model, which inherits its main aspects from the reinforcement learning field. The model proposed endeavours to efficiently determine the downlink-to-uplinkwidth ratio, on a frame-by-frame basis, taking into account both the downlink and uplink traffic in the Base Station (BS. Extensive evaluation results indicate that the model proposed succeeds in providing quite accurate estimations, keeping the average error rate below 15% with respect to the optimal sub-frame configurations. Additionally, it presents improved performance compared to other learning methods (e.g., learning automata and notable improvements compared to static schemes that maintain a fixed predefined ratio in terms of service ratio and resource utilization.

  9. 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...

  10. Mapping of Students’ Learning Progression Based on Mental Model in Magnetic Induction Concepts

    Science.gov (United States)

    Hamid, R.; Pabunga, D. B.

    2017-09-01

    The progress of student learning in a learning process has not been fully optimally observed by the teacher. The concept being taught is judged only at the end of learning as a product of thinking, and does not assess the mental processes that occur in students’ thinking. Facilitating students’ thinking through new phenomena can reveal students’ variation in thinking as a mental model of a concept, so that students who are assimilative and or accommodative can be identified in achieving their equilibrium of thought as well as an indicator of progressiveness in the students’ thinking stages. This research data is obtained from the written documents and interviews of students who were learned about the concept of magnetic induction through Constructivist Teaching Sequences (CTS) models. The results of this study indicate that facilitating the students’ thinking processes on the concept of magnetic induction contributes to increasing the number of students thinking within the "progressive change" category, and it can be said that the progress of student learning is more progressive after their mental models were facilitated through a new phenomena by teacher.

  11. Elemental representation and configural mappings: combining elemental and configural theories of associative learning.

    Science.gov (United States)

    McLaren, I P L; Forrest, C L; McLaren, R P

    2012-09-01

    In this article, we present our first attempt at combining an elemental theory designed to model representation development in an associative system (based on McLaren, Kaye, & Mackintosh, 1989) with a configural theory that models associative learning and memory (McLaren, 1993). After considering the possible advantages of such a combination (and some possible pitfalls), we offer a hybrid model that allows both components to produce the phenomena that they are capable of without introducing unwanted interactions. We then successfully apply the model to a range of phenomena, including latent inhibition, perceptual learning, the Espinet effect, and first- and second-order retrospective revaluation. In some cases, we present new data for comparison with our model's predictions. In all cases, the model replicates the pattern observed in our experimental results. We conclude that this line of development is a promising one for arriving at general theories of associative learning and memory.

  12. 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.

  13. 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...

  14. Supporting Students' Learning and Socioscientific Reasoning About Climate Change—the Effect of Computer-Based Concept Mapping Scaffolds

    Science.gov (United States)

    Eggert, Sabina; Nitsch, Anne; Boone, William J.; Nückles, Matthias; Bögeholz, Susanne

    2017-02-01

    Climate change is one of the most challenging problems facing today's global society (e.g., IPCC 2013). While climate change is a widely covered topic in the media, and abundant information is made available through the internet, the causes and consequences of climate change in its full complexity are difficult for individuals, especially non-scientists, to grasp. Science education is a field which can play a crucial role in fostering meaningful education of students to become climate literate citizens (e.g., NOAA 2009; Schreiner et al., 41, 3-50, 2005). If students are, at some point, to participate in societal discussions about the sustainable development of our planet, their learning with respect to such issues needs to be supported. This includes the ability to think critically, to cope with complex scientific evidence, which is often subject to ongoing inquiry, and to reach informed decisions on the basis of factual information as well as values-based considerations. The study presented in this paper focused on efforts to advance students in (1) their conceptual understanding about climate change and (2) their socioscientific reasoning and decision making regarding socioscientific issues in general. Although there is evidence that "knowledge" does not guarantee pro-environmental behavior (e.g. Schreiner et al., 41, 3-50, 2005; Skamp et al., 97(2), 191-217, 2013), conceptual, interdisciplinary understanding of climate change is an important prerequisite to change individuals' attitudes towards climate change and thus to eventually foster climate literate citizens (e.g., Clark et al. 2013). In order to foster conceptual understanding and socioscientific reasoning, a computer-based learning environment with an embedded concept mapping tool was utilized to support senior high school students' learning about climate change and possible solution strategies. The evaluation of the effect of different concept mapping scaffolds focused on the quality of student

  15. Grid Architecture 2

    Energy Technology Data Exchange (ETDEWEB)

    Taft, Jeffrey D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2016-01-01

    The report describes work done on Grid Architecture under the auspices of the Department of Electricity Office of Electricity Delivery and Reliability in 2015. As described in the first Grid Architecture report, the primary purpose of this work is to provide stakeholder insight about grid issues so as to enable superior decision making on their part. Doing this requires the creation of various work products, including oft-times complex diagrams, analyses, and explanations. This report provides architectural insights into several important grid topics and also describes work done to advance the science of Grid Architecture as well.

  16. An Open Source Web Map Server Implementation For California and the Digital Earth: Lessons Learned

    Science.gov (United States)

    Sullivan, D. V.; Sheffner, E. J.; Skiles, J. W.; Brass, J. A.; Condon, Estelle (Technical Monitor)

    2000-01-01

    This paper describes an Open Source implementation of the Open GIS Consortium's Web Map interface. It is based on the very popular Apache WWW Server, the Sun Microsystems Java ServIet Development Kit, and a C language shared library interface to a spatial datastore. This server was initially written as a proof of concept, to support a National Aeronautics and Space Administration (NASA) Digital Earth test bed demonstration. It will also find use in the California Land Science Information Partnership (CaLSIP), a joint program between NASA and the state of California. At least one WebMap enabled server will be installed in every one of the state's 58 counties. This server will form a basis for a simple, easily maintained installation for those entities that do not yet require one of the larger, more expensive, commercial offerings.

  17. MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2015-01-01

    Full Text Available Artificial neural networks (ANNs have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing model to facilitate data intensive applications. Three data intensive scenarios are considered in the parallelization process in terms of the volume of classification data, the size of the training data, and the number of neurons in the neural network. The performance of the parallelized neural networks is evaluated in an experimental MapReduce computer cluster from the aspects of accuracy in classification and efficiency in computation.

  18. MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning.

    Science.gov (United States)

    Liu, Yang; Yang, Jie; Huang, Yuan; Xu, Lixiong; Li, Siguang; Qi, Man

    2015-01-01

    Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing model to facilitate data intensive applications. Three data intensive scenarios are considered in the parallelization process in terms of the volume of classification data, the size of the training data, and the number of neurons in the neural network. The performance of the parallelized neural networks is evaluated in an experimental MapReduce computer cluster from the aspects of accuracy in classification and efficiency in computation.

  19. Mapping the Evolution of eLearning from 1977–2005 to Inform Understandings of eLearning Historical Trends

    Directory of Open Access Journals (Sweden)

    Pei Chen Sun

    2014-03-01

    Full Text Available While there have been very limited studies of the educational computing literature to analyze the research trends since the early emergence of educational computing technologies, the authors argue that it is important for both researchers and educators to understand the major, historical educational computing trends in order to inform understandings of current and future eLearning trends. This study provides the findings of an analysis of 2,694 journal articles published between 1977 and 2005 in four major, international educational computing journals. It provides the platform for a subsequent analysis for the period 2006–2014 and beyond, as future educational computing research is published. The journal articles analyzed were categorized according to their research themes. Subsequently, clustering analysis, multi-dimension scale analysis, and research diversity analysis were performed on the categorized results to explore the research trends. The research literature analysis confirmed that there were identifiable evolutionary trends dating from 1977, and, importantly, the analysis highlighted that each key breakthrough in technology was accompanied by increased educational research about those technologies to inform educational practices. Importantly, two major driving forces of the historical trends identified were technologies and pedagogical approaches. The paper concludes with explanations of how these trends from 1977–2005 have shaped the current focus on Technological Pedagogical Content Knowledge (TPACK needed for effective current and future eLearning.

  20. Walk and learn: an empirical framework for assessing spatial knowledge acquisition during mobile map use

    OpenAIRE

    Brügger, Annina; Richter, Kai-Florian; Fabrikant, Sara I

    2016-01-01

    We gladly use automated technology (e.g., smart devices) to extend our hard working minds. But what if such technology turns into mind crutches we cannot do without? Understanding how varying levels of automation in mobile maps might impact navigation performance and spatial knowledge acquisition will provide important insights for the ongoing debate on the potentially detrimental effects of using navigation systems on human spatial cognition. We need to identify the right balance between sys...

  1. 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.

  2. 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...

  3. Use of Concept Mapping and Visual Learning Software in Education at Kuwait University

    Science.gov (United States)

    Safar, Ammar H.; Alqudsi-Ghabra, Taghreed M.; Qabazard, Nedaa M.

    2012-01-01

    Information and communication technology (ICT) has been integrated as an educational tool in the late 1950's and the beginnings of 1960's. Many research and conceptual papers over the past decades have documented its importance on enhancing students' education and learning across all subject areas and grade levels. Our twenty-first century modern…

  4. The Instructed Learning of Form-Function Mappings in the English Article System

    Science.gov (United States)

    Zhao, Helen; MacWhinney, Brian

    2018-01-01

    This article analyzes the instructed learning of the English article system by second language (L2) learners. The Competition Model (MacWhinney, 1987, 2012) was adopted as the theoretical framework for analyzing the cues to article usage and for designing effective computer-based article instruction. Study 1 found that article cues followed a…

  5. Creating a Cell Map as an Active-Learning Tool in a Biochemistry Course

    Science.gov (United States)

    Del Bianco, Cristina

    2010-01-01

    Teaching metabolism to a biochemistry class with diverse academic backgrounds is a challenging task. Often students lack the global perspective that is needed to understand how different metabolic pathways are reciprocally regulated. The classroom activity presented in this article is designed to facilitate the learning of metabolism by having the…

  6. The App Map: A Tool for Systematic Evaluation of Apps for Early Literacy Learning

    Science.gov (United States)

    Israelson, Madeleine Heins

    2015-01-01

    As portable devices become increasingly available in elementary classrooms teachers are expected to use these new technologies to engage students in both traditional print-based literacy learning and digital literacies practices, such as multimodal composing. Teachers face the daunting task of integrating apps into their current research-based…

  7. Using a Dialogue System Based on Dialogue Maps for Computer Assisted Second Language Learning

    Science.gov (United States)

    Choi, Sung-Kwon; Kwon, Oh-Woog; Kim, Young-Kil; Lee, Yunkeun

    2016-01-01

    In order to use dialogue systems for computer assisted second-language learning systems, one of the difficult issues in such systems is how to construct large-scale dialogue knowledge that matches the dialogue modelling of a dialogue system. This paper describes how we have accomplished the short-term construction of large-scale and…

  8. Learning Movement Culture: Mapping the Landscape between Physical Education and School Sport

    Science.gov (United States)

    Ward, Gavin

    2014-01-01

    This article examines Movement Culture as an approach to support teachers in exploring the integration of Sport as a medium for learning within Physical Education. By avoiding the need to draw clearly defined lines between Physical Education and Sport, Movement Culture embraces both. It acknowledges the need for subject matter in Physical…

  9. Mapping a sustainable future: Community learning in dialogue at the science-society interface

    Science.gov (United States)

    Barth, Matthias; Lang, Daniel J.; Luthardt, Philip; Vilsmaier, Ulli

    2017-12-01

    In 2015, the German Federal Ministry of Education and Research (BMBF) announced that the Science Year 2015 would focus on the "City of the Future". It called for innovative projects from cities and communities in Germany dedicated to exploring future options and scenarios for sustainable development. Among the successful respondents was the city of Lüneburg, located in the north of Germany, which was awarded funding to establish a community learning project to envision a sustainable future ("City of the Future Lüneburg 2030+"). What made Lüneburg's approach unique was that the city itself initiated the project and invited a broad range of stakeholders to participate in a community learning process for sustainable development. The authors of this article use the project as a blueprint for sustainable city development. Presenting a reflexive case study, they report on the process and outcomes of the project and investigate community learning processes amongst different stakeholders as an opportunity for transformative social learning. They discuss outputs and outcomes (intended as well as unintended) in relation to the specific starting points of the project to provide a context-sensitive yet rich narrative of the case and to overcome typical criticisms of case studies in the field.

  10. Smart grid technologies in local electric grids

    Science.gov (United States)

    Lezhniuk, Petro D.; Pijarski, Paweł; Buslavets, Olga A.

    2017-08-01

    The research is devoted to the creation of favorable conditions for the integration of renewable sources of energy into electric grids, which were designed to be supplied from centralized generation at large electric power stations. Development of distributed generation in electric grids influences the conditions of their operation - conflict of interests arises. The possibility of optimal functioning of electric grids and renewable sources of energy, when complex criterion of the optimality is balance reliability of electric energy in local electric system and minimum losses of electric energy in it. Multilevel automated system for power flows control in electric grids by means of change of distributed generation of power is developed. Optimization of power flows is performed by local systems of automatic control of small hydropower stations and, if possible, solar power plants.

  11. 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...

  12. 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

  13. 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.

  14. Smart grid security

    Energy Technology Data Exchange (ETDEWEB)

    Cuellar, Jorge (ed.) [Siemens AG, Muenchen (Germany). Corporate Technology

    2013-11-01

    The engineering, deployment and security of the future smart grid will be an enormous project requiring the consensus of many stakeholders with different views on the security and privacy requirements, not to mention methods and solutions. The fragmentation of research agendas and proposed approaches or solutions for securing the future smart grid becomes apparent observing the results from different projects, standards, committees, etc, in different countries. The different approaches and views of the papers in this collection also witness this fragmentation. This book contains the following papers: 1. IT Security Architecture Approaches for Smart Metering and Smart Grid. 2. Smart Grid Information Exchange - Securing the Smart Grid from the Ground. 3. A Tool Set for the Evaluation of Security and Reliability in Smart Grids. 4. A Holistic View of Security and Privacy Issues in Smart Grids. 5. Hardware Security for Device Authentication in the Smart Grid. 6. Maintaining Privacy in Data Rich Demand Response Applications. 7. Data Protection in a Cloud-Enabled Smart Grid. 8. Formal Analysis of a Privacy-Preserving Billing Protocol. 9. Privacy in Smart Metering Ecosystems. 10. Energy rate at home Leveraging ZigBee to Enable Smart Grid in Residential Environment.

  15. A Preliminary Study on the Use of Mind Mapping as a Visual-Learning Strategy in General Education Science Classes for Arabic Speakers in the United Arab Emirates

    Science.gov (United States)

    Wilson, Kenesha; Copeland-Solas, Eddia; Guthrie-Dixon, Natalie

    2016-01-01

    Mind mapping was introduced as a culturally relevant pedagogy aimed at enhancing the teaching and learning experience in a general education, Environmental Science class for mostly Emirati English Language Learners (ELL). Anecdotal evidence suggests that the students are very artistic and visual and enjoy group-based activities. It was decided to…

  16. New machine learning tools for predictive vegetation mapping after climate change: Bagging and Random Forest perform better than Regression Tree Analysis

    Science.gov (United States)

    L.R. Iverson; A.M. Prasad; A. Liaw

    2004-01-01

    More and better machine learning tools are becoming available for landscape ecologists to aid in understanding species-environment relationships and to map probable species occurrence now and potentially into the future. To thal end, we evaluated three statistical models: Regression Tree Analybib (RTA), Bagging Trees (BT) and Random Forest (RF) for their utility in...

  17. The Effect of Mind-Mapping Applications on Upper Primary Students' Success and Inquiry-Learning Skills in Science and Environment Education

    Science.gov (United States)

    Balim, Ali Günay

    2013-01-01

    This study aims at identifying the effects of the mind-mapping technique upon students' perceptions of inquiry-learning skills, academic achievement, and retention of knowledge. The study was carried out in the Science and Technology course. A quasi-experimental research design with a pre-test and post-test control group, which was selected from…

  18. The Effects of a Story-Mapping Procedure to Improve the Comprehension Skills of Expository Text Passages for Elementary Students with Learning Disabilities

    Science.gov (United States)

    Stagliano, Christina; Boon, Richard T.

    2009-01-01

    The purpose of this study was to examine the effects of using a story-mapping procedure to improve and enhance the reading comprehension skills using expository text passages for 3 fourth-grade students with learning disabilities (LD). The study was conducted in the resource classroom in which the participants regularly received reading…

  19. Which Teaching Strategy Is Better for Enhancing Anti-Phishing Learning Motivation and Achievement? The Concept Maps on Tablet PCs or Worksheets?

    Science.gov (United States)

    Sun, Jerry Chih-Yuan; Lee, Kuan-Hsien

    2016-01-01

    The purpose of this study is to evaluate the feasibility of the integration of concept maps and tablet PCs in anti-phishing education for enhancing students' learning motivation and achievement. The subjects were 155 students from grades 8 and 9. They were divided into an experimental group (77 students) and a control group (78 students). To begin…

  20. Development and Evaluation of a Web Map Mind Tool Environment with the Theory of Spatial Thinking and Project-Based Learning Strategy

    Science.gov (United States)

    Hou, Huei-Tse; Yu, Tsai-Fang; Wu, Yi-Xuan; Sung, Yao-Ting; Chang, Kuo-En

    2016-01-01

    The theory of spatial thinking is relevant to the learning and teaching of many academic domains. One promising method to facilitate learners' higher-order thinking is to utilize a web map mind tool to assist learners in applying spatial thinking to cooperative problem solving. In this study, an environment is designed based on the theory of…

  1. Artificial Intelligence-Based Student Learning Evaluation: A Concept Map-Based Approach for Analyzing a Student's Understanding of a Topic

    Science.gov (United States)

    Jain, G. Panka; Gurupur, Varadraj P.; Schroeder, Jennifer L.; Faulkenberry, Eileen D.

    2014-01-01

    In this paper, we describe a tool coined as artificial intelligence-based student learning evaluation tool (AISLE). The main purpose of this tool is to improve the use of artificial intelligence techniques in evaluating a student's understanding of a particular topic of study using concept maps. Here, we calculate the probability distribution of…

  2. 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)

  3. LHC computing grid

    International Nuclear Information System (INIS)

    Novaes, Sergio

    2011-01-01

    Full text: We give an overview of the grid computing initiatives in the Americas. High-Energy Physics has played a very important role in the development of grid computing in the world and in Latin America it has not been different. Lately, the grid concept has expanded its reach across all branches of e-Science, and we have witnessed the birth of the first nationwide infrastructures and its use in the private sector. (author)

  4. Urban micro-grids

    International Nuclear Information System (INIS)

    Faure, Maeva; Salmon, Martin; El Fadili, Safae; Payen, Luc; Kerlero, Guillaume; Banner, Arnaud; Ehinger, Andreas; Illouz, Sebastien; Picot, Roland; Jolivet, Veronique; Michon Savarit, Jeanne; Strang, Karl Axel

    2017-02-01

    ENEA Consulting published the results of a study on urban micro-grids conducted in partnership with the Group ADP, the Group Caisse des Depots, ENEDIS, Omexom, Total and the Tuck Foundation. This study offers a vision of the definition of an urban micro-grid, the value brought by a micro-grid in different contexts based on real case studies, and the upcoming challenges that micro-grid stakeholders will face (regulation, business models, technology). The electric production and distribution system, as the backbone of an increasingly urbanized and energy dependent society, is urged to shift towards a more resilient, efficient and environment-friendly infrastructure. Decentralisation of electricity production into densely populated areas is a promising opportunity to achieve this transition. A micro-grid enhances local production through clustering electricity producers and consumers within a delimited electricity network; it has the ability to disconnect from the main grid for a limited period of time, offering an energy security service to its customers during grid outages for example. However: The islanding capability is an inherent feature of the micro-grid concept that leads to a significant premium on electricity cost, especially in a system highly reliant on intermittent electricity production. In this case, a smart grid, with local energy production and no islanding capability, can be customized to meet relevant sustainability and cost savings goals at lower costs For industrials, urban micro-grids can be economically profitable in presence of high share of reliable energy production and thermal energy demand micro-grids face strong regulatory challenges that should be overcome for further development Whether islanding is or is not implemented into the system, end-user demand for a greener, more local, cheaper and more reliable energy, as well as additional services to the grid, are strong drivers for local production and consumption. In some specific cases

  5. High density grids

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, Aina E.; Baxter, Elizabeth L.

    2018-01-16

    An X-ray data collection grid device is provided that includes a magnetic base that is compatible with robotic sample mounting systems used at synchrotron beamlines, a grid element fixedly attached to the magnetic base, where the grid element includes at least one sealable sample window disposed through a planar synchrotron-compatible material, where the planar synchrotron-compatible material includes at least one automated X-ray positioning and fluid handling robot fiducial mark.

  6. Application of Mind Map-based abstracting technique in pedagogical strategy for ESP teaching/learning

    Directory of Open Access Journals (Sweden)

    Ekaterina Choporova

    2014-09-01

    Full Text Available The work presents some theoretical and practical results of the abstracting practice carried out by the teachers and cadets of Voronezh Institute of the Ministry of Interior of Russia. The sources used in the experiment were of British and American origin, equally authentic, and were mainly of engineering content because of the cadets’ speciality. The main purpose of the experiment was focused on the primary source adequate abstract making as a product of a keen understanding of social and professional aspects, views, and anticipations of English-speaking nations. The authors analyzed a number of current approaches towards abstract making procedures and offered an original system of the education strategy by means of Mind Map building technique.

  7. Micro grids toward the smart grid

    International Nuclear Information System (INIS)

    Guerrero, J.

    2011-01-01

    Worldwide electrical grids are expecting to become smarter in the near future, with interest in Microgrids likely to grow. A microgrid can be defined as a part of the grid with elements of prime energy movers, power electronics converters, distributed energy storage systems and local loads, that can operate autonomously but also interacting with main grid. Thus, the ability of intelligent Microgrids to operate in island mode or connected to the grid will be a keypoint to cope with new functionalities and the integration of renewable energy resources. The functionalities expected for these small grids are: black start operation, frequency and voltage stability, active and reactive power flow control, active power filter capabilities, and storage energy management. In this presentation, a review of the main concepts related to flexible Microgrids will be introduced, with examples of real Microgrids. AC and DC Microgrids to integrate renewable and distributed energy resources will also be presented, as well as distributed energy storage systems, and standardization issues of these Microgrids. Finally, Microgrid hierarchical control will be analyzed looking at three different levels: i) a primary control based on the droop method, including an output impedance virtual loop; ii) a secondary control, which enables restoring any deviations produced by the primary control; and iii) a tertiary control to manage the power flow between the microgrid and the external electrical distribution system.

  8. 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...

  9. Challenges facing production grids

    Energy Technology Data Exchange (ETDEWEB)

    Pordes, Ruth; /Fermilab

    2007-06-01

    Today's global communities of users expect quality of service from distributed Grid systems equivalent to that their local data centers. This must be coupled to ubiquitous access to the ensemble of processing and storage resources across multiple Grid infrastructures. We are still facing significant challenges in meeting these expectations, especially in the underlying security, a sustainable and successful economic model, and smoothing the boundaries between administrative and technical domains. Using the Open Science Grid as an example, I examine the status and challenges of Grids operating in production today.

  10. One-Shot Learning of Human Activity With an MAP Adapted GMM and Simplex-HMM.

    Science.gov (United States)

    Rodriguez, Mario; Orrite, Carlos; Medrano, Carlos; Makris, Dimitrios

    2016-05-10

    This paper presents a novel activity class representation using a single sequence for training. The contribution of this representation lays on the ability to train an one-shot learning recognition system, useful in new scenarios where capturing and labeling sequences is expensive or impractical. The method uses a universal background model of local descriptors obtained from source databases available on-line and adapts it to a new sequence in the target scenario through a maximum a posteriori adaptation. Each activity sample is encoded in a sequence of normalized bag of features and modeled by a new hidden Markov model formulation, where the expectation-maximization algorithm for training is modified to deal with observations consisting in vectors in a unit simplex. Extensive experiments in recognition have been performed using one-shot learning over the public datasets Weizmann, KTH, and IXMAS. These experiments demonstrate the discriminative properties of the representation and the validity of application in recognition systems, achieving state-of-the-art results.

  11. Insightful Workflow For Grid Computing

    Energy Technology Data Exchange (ETDEWEB)

    Dr. Charles Earl

    2008-10-09

    We developed a workflow adaptation and scheduling system for Grid workflow. The system currently interfaces with and uses the Karajan workflow system. We developed machine learning agents that provide the planner/scheduler with information needed to make decisions about when and how to replan. The Kubrick restructures workflow at runtime, making it unique among workflow scheduling systems. The existing Kubrick system provides a platform on which to integrate additional quality of service constraints and in which to explore the use of an ensemble of scheduling and planning algorithms. This will be the principle thrust of our Phase II work.

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. Learning strategy refinement reverses early sensory cortical map expansion but not behavior: Support for a theory of directed cortical substrates of learning and memory.

    Science.gov (United States)

    Elias, Gabriel A; Bieszczad, Kasia M; Weinberger, Norman M

    2015-12-01

    Primary sensory cortical fields develop highly specific associative representational plasticity, notably enlarged area of representation of reinforced signal stimuli within their topographic maps. However, overtraining subjects after they have solved an instrumental task can reduce or eliminate the expansion while the successful behavior remains. As the development of this plasticity depends on the learning strategy used to solve a task, we asked whether the loss of expansion is due to the strategy used during overtraining. Adult male rats were trained in a three-tone auditory discrimination task to bar-press to the CS+ for water reward and refrain from doing so during the CS- tones and silent intertrial intervals; errors were punished by a flashing light and time-out penalty. Groups acquired this task to a criterion within seven training sessions by relying on a strategy that was "bar-press from tone-onset-to-error signal" ("TOTE"). Three groups then received different levels of overtraining: Group ST, none; Group RT, one week; Group OT, three weeks. Post-training mapping of their primary auditory fields (A1) showed that Groups ST and RT had developed significantly expanded representational areas, specifically restricted to the frequency band of the CS+ tone. In contrast, the A1 of Group OT was no different from naïve controls. Analysis of learning strategy revealed this group had shifted strategy to a refinement of TOTE in which they self-terminated bar-presses before making an error ("iTOTE"). Across all animals, the greater the use of iTOTE, the smaller was the representation of the CS+ in A1. Thus, the loss of cortical expansion is attributable to a shift or refinement in strategy. This reversal of expansion was considered in light of a novel theoretical framework (CONCERTO) highlighting four basic principles of brain function that resolve anomalous findings and explaining why even a minor change in strategy would involve concomitant shifts of involved brain

  17. LEARNING STRATEGY REFINEMENT REVERSES EARLY SENSORY CORTICAL MAP EXPANSION BUT NOT BEHAVIOR: SUPPORT FOR A THEORY OF DIRECTED CORTICAL SUBSTRATES OF LEARNING AND MEMORY

    Science.gov (United States)

    Elias, Gabriel A.; Bieszczad, Kasia M.; Weinberger, Norman M.

    2015-01-01

    Primary sensory cortical fields develop highly specific associative representational plasticity, notably enlarged area of representation of reinforced signal stimuli within their topographic maps. However, overtraining subjects after they have solved an instrumental task can reduce or eliminate the expansion while the successful behavior remains. As the development of this plasticity depends on the learning strategy used to solve a task, we asked whether the loss of expansion is due to the strategy used during overtraining. Adult male rats were trained in a three-tone auditory discrimination task to bar-press to the CS+ for water reward and refrain from doing so during the CS− tones and silent intertrial intervals; errors were punished by a flashing light and time-out penalty. Groups acquired this task to a criterion within seven training sessions by relying on a strategy that was “bar-press from tone-onset-to-error signal” (“TOTE”). Three groups then received different levels of overtraining: Group ST, none; Group RT, one week; Group OT, three weeks. Post-training mapping of their primary auditory fields (A1) showed that Groups ST and RT had developed significantly expanded representational areas, specifically restricted to the frequency band of the CS+ tone. In contrast, the A1 of Group OT was no different from naïve controls. Analysis of learning strategy revealed this group had shifted strategy to a refinement of TOTE in which they self-terminated bar-presses before making an error (“iTOTE”). Across all animals, the greater the use of iTOTE, the smaller was the representation of the CS+ in A1. Thus, the loss of cortical expansion is attributable to a shift or refinement in strategy. This reversal of expansion was considered in light of a novel theoretical framework (CONCERTO) highlighting four basic principles of brain function that resolve anomalous findings and explaining why even a minor change in strategy would involve concomitant shifts of

  18. GridOrbit public display

    DEFF Research Database (Denmark)

    Ramos, Juan David Hincapie; Tabard, Aurélien; Bardram, Jakob

    2010-01-01

    We introduce GridOrbit, a public awareness display that visualizes the activity of a community grid used in a biology laboratory. This community grid executes bioin-formatics algorithms and relies on users to donate CPU cycles to the grid. The goal of GridOrbit is to create a shared awareness about...

  19. 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).

  20. Security for grids

    Energy Technology Data Exchange (ETDEWEB)

    Humphrey, Marty; Thompson, Mary R.; Jackson, Keith R.

    2005-08-14

    Securing a Grid environment presents a distinctive set of challenges. This paper groups the activities that need to be secured into four categories: naming and authentication; secure communication; trust, policy, and authorization; and enforcement of access control. It examines the current state of the art in securing these processes and introduces new technologies that promise to meet the security requirements of Grids more completely.

  1. The LHCb Grid Simulation

    CERN Multimedia

    Baranov, Alexander

    2016-01-01

    The LHCb Grid access if based on the LHCbDirac system. It provides access to data and computational resources to researchers with different geographical locations. The Grid has a hierarchical topology with multiple sites distributed over the world. The sites differ from each other by their number of CPUs, amount of disk storage and connection bandwidth. These parameters are essential for the Grid work. Moreover, job scheduling and data distribution strategy have a great impact on the grid performance. However, it is hard to choose an appropriate algorithm and strategies as they need a lot of time to be tested on the real grid. In this study, we describe the LHCb Grid simulator. The simulator reproduces the LHCb Grid structure with its sites and their number of CPUs, amount of disk storage and bandwidth connection. We demonstrate how well the simulator reproduces the grid work, show its advantages and limitations. We show how well the simulator reproduces job scheduling and network anomalies, consider methods ...

  2. The play grid

    DEFF Research Database (Denmark)

    Fogh, Rune; Johansen, Asger

    2013-01-01

    In this paper we propose The Play Grid, a model for systemizing different play types. The approach is psychological by nature and the actual Play Grid is based, therefore, on two pairs of fundamental and widely acknowledged distinguishing characteristics of the ego, namely: extraversion vs. intro...

  3. Planning in Smart Grids

    NARCIS (Netherlands)

    Bosman, M.G.C.

    2012-01-01

    The electricity supply chain is changing, due to increasing awareness for sustainability and an improved energy efficiency. The traditional infrastructure where demand is supplied by centralized generation is subject to a transition towards a Smart Grid. In this Smart Grid, sustainable generation

  4. 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...

  5. The GRID seminar

    CERN Multimedia

    CERN. Geneva HR-RFA

    2006-01-01

    The Grid infrastructure is a key part of the computing environment for the simulation, processing and analysis of the data of the LHC experiments. These experiments depend on the availability of a worldwide Grid infrastructure in several aspects of their computing model. The Grid middleware will hide much of the complexity of this environment to the user, organizing all the resources in a coherent virtual computer center. The general description of the elements of the Grid, their interconnections and their use by the experiments will be exposed in this talk. The computational and storage capability of the Grid is attracting other research communities beyond the high energy physics. Examples of these applications will be also exposed during the presentation.

  6. The Making of a Tsunami Hazard Map: Lessons Learned from the TSUMAPS-NEAM Project

    Science.gov (United States)

    Basili, R.

    2017-12-01

    Following the worldwide surge of awareness toward tsunami hazard and risk in the last decade, Europe has promoted a better understanding of the tsunami phenomenon through research projects (e.g. TRANSFER, ASTARTE) and started programs for preventing the tsunami impact along the coastlines of the North-East Atlantic, the Mediterranean, and connected Seas (NEAM) region (e.g. the Tsunami Early Warning and Mitigation System, NEAMTWS, coordinated by IOC/UNESCO). An indispensable tool toward long-term coastal planning and an effective design and subsequent use of TWS is the availability of a comprehensive Probabilistic Tsunami Hazard Assessment (PTHA). The TSUMAPS-NEAM project took the pledge of producing the first region-wide long-term homogenous PTHA map from earthquake sources. The hazard assessment was built upon state-of-the-art procedures and standards, enriched by some rather innovative/experimental approaches such as: (1) the statistical treatment of potential seismic sources, combining all the available information (seismicity, moment tensors, tectonics), and considering earthquakes occurring on major crustal faults and subduction interfaces; (2) an intensive computational approach to tsunami generation and linear propagation across the sea up to an offshore fixed depth; (3) the use of approximations for shoaling and inundation, based on local bathymetry, and for tidal stages; and (4) the exploration of several alternatives for the basic input data and their parameters which produces a number of models that are treated through an ensemble uncertainty quantification. This presentation will summarize the TSUMAPS-NEAM project goals, implementation, and achieved results, as well as the humps and bumps we run into during its development. The TSUMAPS-NEAM Project (http://www.tsumaps-neam.eu/) is co-financed by the European Union Civil Protection Mechanism, Agreement Number: ECHO/SUB/2015/718568/PREV26.

  7. 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

  8. 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.

  9. 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

  10. Connecting People to Place: Stories, Science, Deep Maps, and Geo-Quests for Place-Based Learning

    Science.gov (United States)

    Hagley, C. A.; Silbernagel, J.; Host, G.; Hart, D. A.; Axler, R.; Fortner, R. W.; Axler, M.; Smith, V.; Drewes, A.; Bartsch, W.; Danz, N.; Mathews, J.; Wagler, M.

    2016-02-01

    The St. Louis River Estuary project (stlouisriverestuary.org) is about connecting the stories with the science of this special place to enhance spatial awareness and stewardship of the estuary. The stories, or spatial narratives, are told through vignettes of local resource activities, framed by perspectives of local people. The spatial narratives, developed through interviews and research, target six key activities of the estuary. The science is based on stressor gradients research, incorporating factors such as population and road density, pollutant point source density, and land use. The stressor gradient developed based on these factors was used as a basis for sampling water quality and plant and macroinvertebrate communities, with the intent of quantifying relationships between land-based stressors and aquatic ecosystem indicators of condition. The stories and science are interwoven, located in place on a Deep Map, and played out in GeoQuests to illustrate the complexity and multiple perspectives within the estuary's social, economic and ecological systems. Students, decision-makers, and Lake Superior enthusiasts can engage more deeply in the complexity of the stories and science by challenging themselves with these GeoQuests played on mobile devices. We hope these place-based learning tools will be valuable in advancing spatial literacy and conversation around environmental sustainability in coastal communities.

  11. Comparison of Three Supervised Learning Methods for Digital Soil Mapping: Application to a Complex Terrain in the Ecuadorian Andes

    Directory of Open Access Journals (Sweden)

    Martin Hitziger

    2014-01-01

    Full Text Available A digital soil mapping approach is applied to a complex, mountainous terrain in the Ecuadorian Andes. Relief features are derived from a digital elevation model and used as predictors for topsoil texture classes sand, silt, and clay. The performance of three statistical learning methods is compared: linear regression, random forest, and stochastic gradient boosting of regression trees. In linear regression, a stepwise backward variable selection procedure is applied and overfitting is controlled by minimizing Mallow’s Cp. For random forest and boosting, the effect of predictor selection and tuning procedures is assessed. 100-fold repetitions of a 5-fold cross-validation of the selected modelling procedures are employed for validation, uncertainty assessment, and method comparison. Absolute assessment of model performance is achieved by comparing the prediction error of the selected method and the mean. Boosting performs best, providing predictions that are reliably better than the mean. The median reduction of the root mean square error is around 5%. Elevation is the most important predictor. All models clearly distinguish ridges and slopes. The predicted texture patterns are interpreted as result of catena sequences (eluviation of fine particles on slope shoulders and landslides (mixing up mineral soil horizons on slopes.

  12. Decentral Smart Grid Control

    Science.gov (United States)

    Schäfer, Benjamin; Matthiae, Moritz; Timme, Marc; Witthaut, Dirk

    2015-01-01

    Stable operation of complex flow and transportation networks requires balanced supply and demand. For the operation of electric power grids—due to their increasing fraction of renewable energy sources—a pressing challenge is to fit the fluctuations in decentralized supply to the distributed and temporally varying demands. To achieve this goal, common smart grid concepts suggest to collect consumer demand data, centrally evaluate them given current supply and send price information back to customers for them to decide about usage. Besides restrictions regarding cyber security, privacy protection and large required investments, it remains unclear how such central smart grid options guarantee overall stability. Here we propose a Decentral Smart Grid Control, where the price is directly linked to the local grid frequency at each customer. The grid frequency provides all necessary information about the current power balance such that it is sufficient to match supply and demand without the need for a centralized IT infrastructure. We analyze the performance and the dynamical stability of the power grid with such a control system. Our results suggest that the proposed Decentral Smart Grid Control is feasible independent of effective measurement delays, if frequencies are averaged over sufficiently large time intervals.

  13. Decentral Smart Grid Control

    International Nuclear Information System (INIS)

    Schäfer, Benjamin; Matthiae, Moritz; Timme, Marc; Witthaut, Dirk

    2015-01-01

    Stable operation of complex flow and transportation networks requires balanced supply and demand. For the operation of electric power grids—due to their increasing fraction of renewable energy sources—a pressing challenge is to fit the fluctuations in decentralized supply to the distributed and temporally varying demands. To achieve this goal, common smart grid concepts suggest to collect consumer demand data, centrally evaluate them given current supply and send price information back to customers for them to decide about usage. Besides restrictions regarding cyber security, privacy protection and large required investments, it remains unclear how such central smart grid options guarantee overall stability. Here we propose a Decentral Smart Grid Control, where the price is directly linked to the local grid frequency at each customer. The grid frequency provides all necessary information about the current power balance such that it is sufficient to match supply and demand without the need for a centralized IT infrastructure. We analyze the performance and the dynamical stability of the power grid with such a control system. Our results suggest that the proposed Decentral Smart Grid Control is feasible independent of effective measurement delays, if frequencies are averaged over sufficiently large time intervals. (paper)

  14. The open science grid

    International Nuclear Information System (INIS)

    Pordes, R.

    2004-01-01

    The U.S. LHC Tier-1 and Tier-2 laboratories and universities are developing production Grids to support LHC applications running across a worldwide Grid computing system. Together with partners in computer science, physics grid projects and active experiments, we will build a common national production grid infrastructure which is open in its architecture, implementation and use. The Open Science Grid (OSG) model builds upon the successful approach of last year's joint Grid2003 project. The Grid3 shared infrastructure has for over eight months provided significant computational resources and throughput to a range of applications, including ATLAS and CMS data challenges, SDSS, LIGO, and biology analyses, and computer science demonstrators and experiments. To move towards LHC-scale data management, access and analysis capabilities, we must increase the scale, services, and sustainability of the current infrastructure by an order of magnitude or more. Thus, we must achieve a significant upgrade in its functionalities and technologies. The initial OSG partners will build upon a fully usable, sustainable and robust grid. Initial partners include the US LHC collaborations, DOE and NSF Laboratories and Universities and Trillium Grid projects. The approach is to federate with other application communities in the U.S. to build a shared infrastructure open to other sciences and capable of being modified and improved to respond to needs of other applications, including CDF, D0, BaBar, and RHIC experiments. We describe the application-driven, engineered services of the OSG, short term plans and status, and the roadmap for a consortium, its partnerships and national focus

  15. The effects of concept and vee mappings under three learning modes on Jamaican eighth graders' knowledge of nutrition and plant reproduction

    Science.gov (United States)

    Ugwu, Okechukwu; Soyibo, Kola

    2004-01-01

    The first objective of this study was to investigate if the experimental students' post-test knowledge of nutrition and plant reproduction would be improved more significantly than that of their control group counterparts based on their treatment, attitudes to science, self-esteem, gender and socio-economic background. Treatment involved teaching the experimental students under three learning modes--pure cooperative, cooperative-competitive and individualistic whole class interpersonal competitive condition--using concept and vee mappings and the lecture method. The control groups received the same treatment but were not exposed to concept and vee mappings. This study's second objective was to determine which of the three learning modes would produce the highest post-test mean gain in the subjects' knowledge of the two biology concepts. The study's sample comprised 932 eighth graders (12-13-year-olds) in 14 co-educational comprehensive high schools randomly selected from two Jamaican parishes. An integrated science performance test, an attitudes to science questionnaire and a self-esteem questionnaire were used to collect data. The results indicated that the experimental students (a) under the three learning modes, (b) with high, moderate, and low attitudes to science, and (c) with high, moderate, and low self-esteem, performed significantly better than their control group counterparts. The individualist whole class learning mode engendered the highest mean gain on the experimental students' knowledge, while the cooperative-competitive learning mode generated the highest mean gain for the control group students.

  16. Desktop grid computing

    CERN Document Server

    Cerin, Christophe

    2012-01-01

    Desktop Grid Computing presents common techniques used in numerous models, algorithms, and tools developed during the last decade to implement desktop grid computing. These techniques enable the solution of many important sub-problems for middleware design, including scheduling, data management, security, load balancing, result certification, and fault tolerance. The book's first part covers the initial ideas and basic concepts of desktop grid computing. The second part explores challenging current and future problems. Each chapter presents the sub-problems, discusses theoretical and practical

  17. Transmission grid security

    CERN Document Server

    Haarla, Liisa; Hirvonen, Ritva; Labeau, Pierre-Etienne

    2011-01-01

    In response to the growing importance of power system security and reliability, ""Transmission Grid Security"" proposes a systematic and probabilistic approach for transmission grid security analysis. The analysis presented uses probabilistic safety assessment (PSA) and takes into account the power system dynamics after severe faults. In the method shown in this book the power system states (stable, not stable, system breakdown, etc.) are connected with the substation reliability model. In this way it is possible to: estimate the system-wide consequences of grid faults; identify a chain of eve

  18. 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.

  19. 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.…

  20. 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.