WorldWideScience

Sample records for learning object model

  1. Learning models of activities involving interacting objects

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  2. Towards a semantic learning model fostering learning object reusability

    OpenAIRE

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

    2005-01-01

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

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

    African Journals Online (AJOL)

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

  4. A Convergent Participation Model for Evaluation of Learning Objects

    Directory of Open Access Journals (Sweden)

    John Nesbit

    2002-10-01

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

  5. Learning-based stochastic object models for characterizing anatomical variations

    Science.gov (United States)

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

    2018-03-01

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

  6. From Learning Object to Learning Cell: A Resource Organization Model for Ubiquitous Learning

    Science.gov (United States)

    Yu, Shengquan; Yang, Xianmin; Cheng, Gang; Wang, Minjuan

    2015-01-01

    This paper presents a new model for organizing learning resources: Learning Cell. This model is open, evolving, cohesive, social, and context-aware. By introducing a time dimension into the organization of learning resources, Learning Cell supports the dynamic evolution of learning resources while they are being used. In addition, by introducing a…

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

    Directory of Open Access Journals (Sweden)

    Noppamas Pukkhem

    2011-09-01

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

  8. An Investigation on the Correlation of Learner Styles and Learning Objects Characteristics in a Proposed Learning Objects Management Model (LOMM)

    Science.gov (United States)

    Wanapu, Supachanun; Fung, Chun Che; Kerdprasop, Nittaya; Chamnongsri, Nisachol; Niwattanakul, Suphakit

    2016-01-01

    The issues of accessibility, management, storage and organization of Learning Objects (LOs) in education systems are a high priority of the Thai Government. Incorporating personalized learning or learning styles in a learning object management system to improve the accessibility of LOs has been addressed continuously in the Thai education system.…

  9. Learning Object Repositories

    Science.gov (United States)

    Lehman, Rosemary

    2007-01-01

    This chapter looks at the development and nature of learning objects, meta-tagging standards and taxonomies, learning object repositories, learning object repository characteristics, and types of learning object repositories, with type examples. (Contains 1 table.)

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

    DEFF Research Database (Denmark)

    Aakerberg, Andreas; Nasrollahi, Kamal; Heder, Thomas

    2018-01-01

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

  11. Applying CIPP Model for Learning-Object Management

    Science.gov (United States)

    Morgado, Erla M. Morales; Peñalvo, Francisco J. García; Martín, Carlos Muñoz; Gonzalez, Miguel Ángel Conde

    Although knowledge management process needs to receive some evaluation in order to determine their suitable functionality. There is not a clear definition about the stages where LOs need to be evaluated and the specific metrics to continuously promote their quality. This paper presents a proposal for LOs evaluation during their management for e-learning systems. To achieve this, we suggest specific steps for LOs design, implementation and evaluation into the four stages proposed by CIPP model (Context, Input, Process, Product).

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

    Directory of Open Access Journals (Sweden)

    Ronaldo Lima Rocha Campos

    2012-07-01

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

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

    DEFF Research Database (Denmark)

    Hansen, Klaus Marius; Ratzer, Anne Vinter

    2002-01-01

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

  14. Repurposing learning object components

    NARCIS (Netherlands)

    Verbert, K.; Jovanovic, J.; Gasevic, D.; Duval, E.; Meersman, R.

    2005-01-01

    This paper presents an ontology-based framework for repurposing learning object components. Unlike the usual practice where learning object components are assembled manually, the proposed framework enables on-the-fly access and repurposing of learning object components. The framework supports two

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

    Science.gov (United States)

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

    2016-01-01

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

  16. Diagram, a Learning Environment for Initiation to Object-Oriented Modeling with UML Class Diagrams

    Science.gov (United States)

    Py, Dominique; Auxepaules, Ludovic; Alonso, Mathilde

    2013-01-01

    This paper presents Diagram, a learning environment for object-oriented modelling (OOM) with UML class diagrams. Diagram an open environment, in which the teacher can add new exercises without constraints on the vocabulary or the size of the diagram. The interface includes methodological help, encourages self-correcting and self-monitoring, and…

  17. Error-Driven Learning in Visual Categorization and Object Recognition: A Common-Elements Model

    Science.gov (United States)

    Soto, Fabian A.; Wasserman, Edward A.

    2010-01-01

    A wealth of empirical evidence has now accumulated concerning animals' categorizing photographs of real-world objects. Although these complex stimuli have the advantage of fostering rapid category learning, they are difficult to manipulate experimentally and to represent in formal models of behavior. We present a solution to the representation…

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

    Science.gov (United States)

    Fiorini, Rodolfo A.; Dacquino, Gianfranco

    2005-03-01

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

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

    CERN Document Server

    Spehr, Jens

    2015-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  1. Learning Objects Web

    DEFF Research Database (Denmark)

    Blåbjerg, Niels Jørgen

    2005-01-01

    Learning Objects Web er et DEFF projekt som Aalborg Universitetsbibliotek har initieret. Projektet tager afsæt i de resultater og erfaringer som er opnået med vores tidligere projekt Streaming Webbased Information Modules (SWIM). Vi har et internationalt netværk af interessenter som giver os...... sparring og feedback i forhold til udviklingskoncept både omkring de teoretiske rammer og i forhold til praktisk anvendelse af vores undervisningskoncept. Med disse rygstød og input har vi forfulgt ønsket om at videreudvikle SWIM i det nye projekt Learning Objects Web. Udgivelsesdato: juni...

  2. A Model for Semi-Automatic Composition of Educational Content from Open Repositories of Learning Objects

    Directory of Open Access Journals (Sweden)

    Paula Andrea Rodríguez Marín

    2014-04-01

    Full Text Available Learning objects (LOs repositories are important in building educational content and should allow search, retrieval and composition processes to be successfully developed to reach educational goals. However, such processes require so much time-consuming and not always provide the desired results. Thus, the aim of this paper is to propose a model for the semiautomatic composition of LOs, which are automatically recovered from open repositories. For the development of model, various text similarity measures are discussed, while for calibration and validation some comparison experiments were performed using the results obtained by teachers. Experimental results show that when using a value of k (number of LOs selected of at least 3, the percentage of similarities between the model and such made by experts exceeds 75%. To conclude, it can be established that the model proposed allows teachers to save time and effort for LOs selection by performing a pre-filter process.

  3. From learning objects to learning activities

    DEFF Research Database (Denmark)

    Dalsgaard, Christian

    2005-01-01

    This paper discusses and questions the current metadata standards for learning objects from a pedagogical point of view. From a social constructivist approach, the paper discusses how learning objects can support problem based, self-governed learning activities. In order to support this approach......, it is argued that it is necessary to focus on learning activities rather than on learning objects. Further, it is argued that descriptions of learning objectives and learning activities should be separated from learning objects. The paper presents a new conception of learning objects which supports problem...... based, self-governed activities. Further, a new way of thinking pedagogy into learning objects is introduced. It is argued that a lack of pedagogical thinking in learning objects is not solved through pedagogical metadata. Instead, the paper suggests the concept of references as an alternative...

  4. Integrating language and content learning objectives : the Bilkent University adjunct model

    OpenAIRE

    Doğan, Egemen Barış

    2003-01-01

    Cataloged from PDF version of article. In response to a global interest in learning English, many instructional approaches, methods, and techniques have been developed. Some have been short-lived, and others have sustained themselves for longer periods of time. Content-based instruction (CBI) — a particular approach to CBI involving a pairing of language and content classes with shared language and content learning objectives — have been considered as viable ways to teach la...

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

    Science.gov (United States)

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

    2012-06-01

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

  6. Authoring Systems Delivering Reusable Learning Objects

    Directory of Open Access Journals (Sweden)

    George Nicola Sammour

    2009-10-01

    Full Text Available A three layer e-learning course development model has been defined based on a conceptual model of learning content object. It starts by decomposing the learning content into small chunks which are initially placed in a hierarchic structure of units and blocks. The raw content components, being the atomic learning objects (ALO, were linked to the blocks and are structured in the database. We set forward a dynamic generation of LO's using re-usable e-learning raw materials or ALO’s In that view we need a LO authoring/ assembling system fitting the requirements of interoperability and reusability and starting from selecting the raw learning content from the learning materials content database. In practice authoring systems are used to develop e-learning courses. The company EDUWEST has developed an authoring system that is database based and will be SCORM compliant in the near future.

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

    Science.gov (United States)

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

    2017-04-01

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

  8. Elaborazione didattica di Learning Objects.

    Directory of Open Access Journals (Sweden)

    Luigi Guerra

    2006-01-01

    Full Text Available L’idea di un modello didattico problematico per la realizzazione di Learning Objects riprende i temi del problematicismo pedagogico e si impegna a definire un’ipotesi formativa complessa capace di valorizzare la possibile positiva compresenza integrata di strategie didattiche diverse (finanche antitetiche ma componibili in una logica appunto di matrice problematicista. Il punto di partenza del modello proposto è rappresentato dalla opportunità di definire tre tipologie fondamentali di Learning Objects, rispettivamente centrati sull’oggetto, sul processo e sul soggetto dell’apprendimento.

  9. Aligning Learning and Talent Development Performance Outcomes with Organizational Objectives: A Proposed Model

    Science.gov (United States)

    Ware, Iris

    2017-01-01

    The value proposition for learning and talent development (LTD) is often challenged due to human resources' inability to demonstrate meaningful outcomes in relation to organizational needs and return-on-investment. The primary role of human resources (HR) and the learning and talent development (LTD) function is to produce meaningful outcomes to…

  10. Dynamic Learning Objects to Teach Java Programming Language

    Science.gov (United States)

    Narasimhamurthy, Uma; Al Shawkani, Khuloud

    2010-01-01

    This article describes a model for teaching Java Programming Language through Dynamic Learning Objects. The design of the learning objects was based on effective learning design principles to help students learn the complex topic of Java Programming. Visualization was also used to facilitate the learning of the concepts. (Contains 1 figure and 2…

  11. BROA: An agent-based model to recommend relevant Learning Objects from Repository Federations adapted to learner profile

    Directory of Open Access Journals (Sweden)

    Paula A. Rodríguez

    2013-03-01

    Full Text Available Learning Objects (LOs are distinguished from traditional educational resources for their easy and quickly availability through Web-based repositories, from which they are accessed through their metadata. In addition, having a user profile allows an educational recommender system to help the learner to find the most relevant LOs based on their needs and preferences. The aim of this paper is to propose an agent-based model so-called BROA to recommend relevant LOs recovered from Repository Federations as well as LOs adapted to learner profile. The model proposed uses both role and service models of GAIA methodology, and the analysis models of the MAS-CommonKADS methodology. A prototype was built based on this model and validated to obtain some assessing results that are finally presented.

  12. Learning Deep Visual Object Models From Noisy Web Data: How to Make it Work

    OpenAIRE

    Massouh, Nizar; Babiloni, Francesca; Tommasi, Tatiana; Young, Jay; Hawes, Nick; Caputo, Barbara

    2017-01-01

    Deep networks thrive when trained on large scale data collections. This has given ImageNet a central role in the development of deep architectures for visual object classification. However, ImageNet was created during a specific period in time, and as such it is prone to aging, as well as dataset bias issues. Moving beyond fixed training datasets will lead to more robust visual systems, especially when deployed on robots in new environments which must train on the objects they encounter there...

  13. From Research Resources to Learning Objects: Process Model and Virtualization Experiences

    Science.gov (United States)

    Sierra, Jose Luis; Fernandez-Valmayor, Alfredo; Guinea, Mercedes; Hernanz, Hector

    2006-01-01

    Typically, most research and academic institutions own and archive a great amount of objects and research related resources that have been produced, used and maintained over long periods of time by different types of "domain experts" (e.g. lecturers and researchers). Although the potential educational value of these resources is very…

  14. Authoring of Learning Objects in Context

    Science.gov (United States)

    Specht, Marcus; Kravcik, Milos

    2006-01-01

    Learning objects and content interchange standards provide new possibilities for e-learning. Nevertheless the content often lacks context data to find appropriate use for adaptive learning on demand and personalized learning experiences. In the Remotely Accessible Field Trips (RAFT) project mobile authoring of learning content in context has shown…

  15. Database functionality for learning objects

    NARCIS (Netherlands)

    Sessink, O.D.T.; Beeftink, H.H.; Hartog, R.J.M.

    2005-01-01

    The development of student-activating digital learning material in six research projects revealed several shortcomings in the current learning management systems. Once the SCORM 2004 and the IMS Sharable State Persistence specifications are implemented in learning management systems, some of these

  16. Using Learning Games to Meet Learning Objectives

    DEFF Research Database (Denmark)

    Henriksen, Thomas Duus

    2013-01-01

    This paper addresses the question on how learning games can be used to meet with the different levels in Bloom’s and the SOLO taxonomy, which are commonly used for evaluating the learning outcome of educational activities. The paper discusses the quality of game-based learning outcomes based on a...... on a case study of the learning game 6Styles....

  17. Deep Learning through Reusable Learning Objects in an MBA Program

    Science.gov (United States)

    Rufer, Rosalyn; Adams, Ruifang Hope

    2013-01-01

    It has well been established that it is important to be able to leverage any organization's processes and core competencies to sustain its competitive advantage. Thus, one learning objective of an online MBA is to teach students how to apply the VRIO (value, rarity, inimitable, operationalized) model, developed by Barney and Hesterly (2006), in…

  18. Learning Ontology from Object-Relational Database

    Directory of Open Access Journals (Sweden)

    Kaulins Andrejs

    2015-12-01

    Full Text Available This article describes a method of transformation of object-relational model into ontology. The offered method uses learning rules for such complex data types as object tables and collections – arrays of a variable size, as well as nested tables. Object types and their transformation into ontologies are insufficiently considered in scientific literature. This fact served as motivation for the authors to investigate this issue and to write the article on this matter. In the beginning, we acquaint the reader with complex data types and object-oriented databases. Then we describe an algorithm of transformation of complex data types into ontologies. At the end of the article, some examples of ontologies described in the OWL language are given.

  19. Utopia2000: An Online Learning-Object Management Tool.

    Science.gov (United States)

    Aspillaga, Macarena

    2002-01-01

    Describes Utopia2002, a database that contains learning objects that enables faculty to design and develop interactive Web-based instruction. Topics include advanced distributed learning; sharable content objects (SCOs) and sharable content object reference model (SCORM); instructional systems design process; templates; and quality assurance. (LRW)

  20. LONS: Learning Object Negotiation System

    Science.gov (United States)

    García, Antonio; García, Eva; de-Marcos, Luis; Martínez, José-Javier; Gutiérrez, José-María; Gutiérrez, José-Antonio; Barchino, Roberto; Otón, Salvador; Hilera, José-Ramón

    This system comes up as a result of the increase of e-learning systems. It manages all relevant modules in this context, such as the association of digital rights with the contents (courses), management and payment processing on rights. There are three blocks:

  1. Constraints on reusability of learning objects

    DEFF Research Database (Denmark)

    May, Michael; Hussmann, Peter Munkebo; Jensen, Anne Skov

    2010-01-01

    It is the aim of this paper to discuss some didactic constraints on the use and reuse of digital modular learning objects. Engineering education is used as the specific context of use with examples from courses in introductory electronics and mathematics. Digital multimedia and modular learning....... Constraints on reuse arise from the nature of conceptual understanding in higher education and the functionality of learning objects within present technologies. We will need didactic as well as technical perspectives on learning objects in designing for understanding....

  2. Unifying Learning Object Repositories in MACE

    NARCIS (Netherlands)

    Prause, Christian; Ternier, Stefaan; De Jong, Tim; Apelt, Stefan; Scholten, Marius; Wolpers, Martin; Eisenhauer, Markus; Vandeputte, Bram; Specht, Marcus; Duval, Erik

    2007-01-01

    Prause, C., Ternier, S., De Jong, T., Apelt, S., Scholten, M., Wolpers, M., et al. (2007). Unifying Learning Object Repositories in MACE. In D. Massart, J.-N. Colin & F. V. Assche (Eds.). Proceedings of the First International Workshop on Learning Object Discovery & Exchange (LODE'07). September,

  3. Tagging the didactic functionality of learning objects

    DEFF Research Database (Denmark)

    Hansen, Per Skafte; Brostroem, Stig

    2002-01-01

    From a components-in-a-network point of view, the most important issues are: a didactically based typing of the learning objects themselves; the entire design superstructure, into which the learning objects must be fitted; and the symmetry of the interfaces, as seen by each pair of the triad...

  4. Transforming existing content into reusable Learning Objects

    NARCIS (Netherlands)

    Doorten, Monique; Giesbers, Bas; Janssen, José; Daniels, Jan; Koper, Rob

    2003-01-01

    Please cite as: Doorten, M., Giesbers, B., Janssen, J., Daniëls, J, & Koper, E.J.R., (2004). Transforming existing content into reusable learning objects. In R. McGreal, Online Education using Learning Objects (pp. 116-127). London: RoutledgeFalmer.

  5. Object recognition and concept learning with Confucius

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, B; Sammut, C

    1982-01-01

    A learning program produces, as its output, a Boolean function which describes a concept. The function returns true if and only if the argument is an object which satisfies the logical expression in the body of the function. The learning program's input is a set of objects which are instances of the concept to be learnt. The paper describes an algorithm devised to learn concept descriptions in this form. 15 references.

  6. ROBOT LEARNING OF OBJECT MANIPULATION TASK ACTIONS FROM HUMAN DEMONSTRATIONS

    Directory of Open Access Journals (Sweden)

    Maria Kyrarini

    2017-08-01

    Full Text Available Robot learning from demonstration is a method which enables robots to learn in a similar way as humans. In this paper, a framework that enables robots to learn from multiple human demonstrations via kinesthetic teaching is presented. The subject of learning is a high-level sequence of actions, as well as the low-level trajectories necessary to be followed by the robot to perform the object manipulation task. The multiple human demonstrations are recorded and only the most similar demonstrations are selected for robot learning. The high-level learning module identifies the sequence of actions of the demonstrated task. Using Dynamic Time Warping (DTW and Gaussian Mixture Model (GMM, the model of demonstrated trajectories is learned. The learned trajectory is generated by Gaussian mixture regression (GMR from the learned Gaussian mixture model.  In online working phase, the sequence of actions is identified and experimental results show that the robot performs the learned task successfully.

  7. Repurposeable Learning Objects Linked to Teaching and Learning Styles

    Directory of Open Access Journals (Sweden)

    Jeremy Dunning

    2004-02-01

    Full Text Available Multimedia learning objects are an essential component of high quality, technology-mediated instruction. Learning objects allow the student to use the content learned in a particular part of a course and; 1. demonstrate mastery of the content, 2. apply that knowledge to solving a problem, and 3. use the content in a critical thinking exercise that both demonstrates mastery and allows the student to place the content within the context of the larger topic of the course. The difficulty associated with the use of learning objects on a broad scale is that they require programming skills most professors and instructors do not possess. Learning objects also tend to be custom productions and are defined in terms of the programming and code terminology, further limiting the professor's ability to understand how they are created. Learning objects defined in terms of styles of learning and teaching allow professors and instructors to develop a deeper understanding of the learning objects and the design process. A set of learning objects has been created that are designed for some of the important styles of learning and teaching. They include; visual learning, writing skills, critical thinking, time-revealed scenarios, case studies and empirical observation. The learning objects are designed and described in terms that the average instructor can readily understand , redesign and incorporate into their own courses. They are also designed in such a way that they can readily be repurposed for new applications in other courses and subject areas, with little or no additional programming.

  8. Learning Object Retrieval and Aggregation Based on Learning Styles

    Science.gov (United States)

    Ramirez-Arellano, Aldo; Bory-Reyes, Juan; Hernández-Simón, Luis Manuel

    2017-01-01

    The main goal of this article is to develop a Management System for Merging Learning Objects (msMLO), which offers an approach that retrieves learning objects (LOs) based on students' learning styles and term-based queries, which produces a new outcome with a better score. The msMLO faces the task of retrieving LOs via two steps: The first step…

  9. Educational Rationale Metadata for Learning Objects

    Directory of Open Access Journals (Sweden)

    Tom Carey

    2002-10-01

    Full Text Available Instructors searching for learning objects in online repositories will be guided in their choices by the content of the object, the characteristics of the learners addressed, and the learning process embodied in the object. We report here on a feasibility study for metadata to record process-oriented information about instructional approaches for learning objects, though a set of Educational Rationale [ER] tags which would allow authors to describe the critical elements in their design intent. The prototype ER tags describe activities which have been demonstrated to be of value in learning, and authors select the activities whose support was critical in their design decisions. The prototype ER tag set consists descriptors of the instructional approach used in the design, plus optional sub-elements for Comments, Importance and Features which implement the design intent. The tag set was tested by creators of four learning object modules, three intended for post-secondary learners and one for K-12 students and their families. In each case the creators reported that the ER tag set allowed them to express succinctly the key instructional approaches embedded in their designs. These results confirmed the overall feasibility of the ER tag approach as a means of capturing design intent from creators of learning objects. Much work remains to be done before a usable ER tag set could be specified, including evaluating the impact of ER tags during design to improve instructional quality of learning objects.

  10. Generative Learning Objects Instantiated with Random Numbers Based Expressions

    Directory of Open Access Journals (Sweden)

    Ciprian Bogdan Chirila

    2015-12-01

    Full Text Available The development of interactive e-learning content requires special skills like programming techniques, web integration, graphic design etc. Generally, online educators do not possess such skills and their e-learning products tend to be static like presentation slides and textbooks. In this paper we propose a new interactive model of generative learning objects as a compromise betweenstatic, dull materials and dynamic, complex software e-learning materials developed by specialized teams. We find that random numbers based automatic initialization learning objects increases content diversity, interactivity thus enabling learners’ engagement. The resulted learning object model is at a limited level of complexity related to special e-learning software, intuitive and capable of increasing learners’ interactivity, engagement and motivation through dynamic content. The approach was applied successfully on several computer programing disciplines.

  11. THE BLENDED LEARNING OF ELECTRICITY USING LEARNING OBJECTS IN ENGINEERING

    Directory of Open Access Journals (Sweden)

    Lilia Maria Siqueira

    2010-09-01

    Full Text Available This work presents a proposal for the blended learning of Electricity education in Engineering, using resources called learning objects. The experience occurred with students enrolled on the Electrical Engineering and Computer Engineering courses at PUCPR University. It made possible the contact with interdisciplinary themes related to the study of electricity and the professional curriculum contents. The learning objects, offered during the semester, were anchored on PUCPR’s proprietary virtual educational environment, called Eureka. The students’ evaluation results showed that the study through learning objects in a virtual environment is significant for learning.

  12. Predictable Locations Aid Early Object Name Learning

    Science.gov (United States)

    Benitez, Viridiana L.; Smith, Linda B.

    2012-01-01

    Expectancy-based localized attention has been shown to promote the formation and retrieval of multisensory memories in adults. Three experiments show that these processes also characterize attention and learning in 16- to 18-month old infants and, moreover, that these processes may play a critical role in supporting early object name learning. The…

  13. Learning Objects, Repositories, Sharing and Reusability

    Science.gov (United States)

    Koppi, Tony; Bogle, Lisa; Bogle, Mike

    2005-01-01

    The online Learning Resource Catalogue (LRC) Project has been part of an international consortium for several years and currently includes 25 institutions worldwide. The LRC Project has evolved for several pragmatic reasons into an academic network whereby members can identify and share reusable learning objects as well as collaborate in a number…

  14. Methodology for Evaluating Quality and Reusability of Learning Objects

    Science.gov (United States)

    Kurilovas, Eugenijus; Bireniene, Virginija; Serikoviene, Silvija

    2011-01-01

    The aim of the paper is to present the scientific model and several methods for the expert evaluation of quality of learning objects (LOs) paying especial attention to LOs reusability level. The activities of eQNet Quality Network for a European Learning Resource Exchange (LRE) aimed to improve reusability of LOs of European Schoolnet's LRE…

  15. A Model for Concurrent Objects

    DEFF Research Database (Denmark)

    Sørensen, Morten U.

    1996-01-01

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

  16. Learn Objective-C for Java Developers

    CERN Document Server

    Bucanek, James

    2009-01-01

    Learn Objective-C for Java Developers will guide experienced Java developers into the world of Objective-C. It will show them how to take their existing language knowledge and design patterns and transfer that experience to Objective-C and the Cocoa runtime library. This is the express train to productivity for every Java developer who dreamt of developing for Mac OS X or iPhone, but felt that Objective-C was too intimidating. So hop on and enjoy the ride!

  17. Experimental Object-Oriented Modelling

    DEFF Research Database (Denmark)

    Hansen, Klaus Marius

    through, e.g., technical prototyping and active user involvement. We introduce and examine “experimental object-oriented modelling” as the intersection of these practices. The contributions of this thesis are expected to be within three perspectives on models and modelling in experimental system...... development: Grounding We develop an empirically based conceptualization of modelling and use of models in system development projects characterized by a high degree of uncertainty in requirements and point to implications for tools and techniques for modelling in such a setting. Techniques We introduce......This thesis examines object-oriented modelling in experimental system development. Object-oriented modelling aims at representing concepts and phenomena of a problem domain in terms of classes and objects. Experimental system development seeks active experimentation in a system development project...

  18. OBJECTIVES AND PROCESSES OF SECOND LANGUAGE LEARNING.

    Science.gov (United States)

    SIZEMORE, MAMIE

    THE OBJECTIVES OF SECOND LANGUAGE TEACHING, AND SPECIFIC DIRECTIONS FOR PRESENTING AND DRILLING STRUCTURES BY THE USE OF CERTAIN GESTURES, WERE PRESENTED. RECOMMENDATIONS FOR CONCENTRATING EFFORTS ON THE ESSENTIALS OF LANGUAGE LEARNING REVOLVED AROUND AN EMPHASIS ON THE TEACHING OF THE LANGUAGE ITSELF RATHER THAN ABOUT ITS HISTORY, VOCABULARY,…

  19. Learning in Organizations - an Object Relations Perspective

    DEFF Research Database (Denmark)

    Andersen, Anders Siig

    Learning in organizations – an object relations perspective As a researcher with a primary interest in the study of learning environments in organizations I have conducted a number of empirical research projects primarily concerning work places in the state sector. The aim of the research has been...... of organizations as learning environments for the employees. Theoretically I draw on object relations theory. Within this tradition the theoretical point of departure is twofold: the study of work conditions in hospitals carried out by Menzies (1975) and Hinschelwood & Skogstad (2000). With regard to the first...... positive and negative impact do they have with respect to the staff itself? With regard to Hinschelwood & Skogstad (2000) they are introduced to further develop and contrast Menzies’ theoretical ideas. Instead of only emphasizing the connection between the work organization and the defence techniques...

  20. Learning Faster by Discovering and Exploiting Object Similarities

    Directory of Open Access Journals (Sweden)

    Tadej Janež

    2013-03-01

    Full Text Available In this paper we explore the question: “Is it possible to speed up the learning process of an autonomous agent by performing experiments in a more complex environment (i.e., an environment with a greater number of different objects?” To this end, we use a simple robotic domain, where the robot has to learn a qualitative model predicting the change in the robot's distance to an object. To quantify the environment's complexity, we defined cardinal complexity as the number of objects in the robot's world, and behavioural complexity as the number of objects' distinct behaviours. We propose Error reduction merging (ERM, a new learning method that automatically discovers similarities in the structure of the agent's environment. ERM identifies different types of objects solely from the data measured and merges the observations of objects that behave in the same or similar way in order to speed up the agent's learning. We performed a series of experiments in worlds of increasing complexity. The results in our simple domain indicate that ERM was capable of discovering structural similarities in the data which indeed made the learning faster, clearly superior to conventional learning. This observed trend occurred with various machine learning algorithms used inside the ERM method.

  1. Intuitive modeling of vaporish objects

    International Nuclear Information System (INIS)

    Sokolov, Dmitry; Gentil, Christian

    2015-01-01

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

  2. Students’ Views on Different Learning Objects Types

    DEFF Research Database (Denmark)

    Natsis, Antonios; Hormova, Hara; Mikropoulos, Tassos

    2014-01-01

    of different type: an educational game, a dynamic simulation and a digital concept map. The basic difference among these three LOs is the fact that both dynamic simulation and concept map are lacking game-like characteristics. The educational game has as a learning goal to familiarize students......The paper attempts to compare students’ views on three different Learning Objects (LOs), also known as Web-Based Learning Tools (WBLTs), which are used for educational purposes aiming at natural disaster readiness. Following an iterative development process, 100 LOs of various types are being...... they will be protected during the earthquake. The educational game comprises of 9 levels of ascending difficulty that have to be completed so as the game to be ended. The dynamic simulation aims to familiarize students with the causes of fog. In that context, they move temperature, wind and humidity bars and thus...

  3. Intelligent Discovery for Learning Objects Using Semantic Web Technologies

    Science.gov (United States)

    Hsu, I-Ching

    2012-01-01

    The concept of learning objects has been applied in the e-learning field to promote the accessibility, reusability, and interoperability of learning content. Learning Object Metadata (LOM) was developed to achieve these goals by describing learning objects in order to provide meaningful metadata. Unfortunately, the conventional LOM lacks the…

  4. Checklist for Evaluating SREB-SCORE Learning Objects

    Science.gov (United States)

    Southern Regional Education Board (SREB), 2007

    2007-01-01

    This checklist is based on "Evaluation Criteria for SREB-SCORE Learning Objects" and is designed to help schools and colleges determine the quality and effectiveness of learning objects. It is suggested that each learning object be rated to the extent to which it meets the criteria and the SREB-SCORE definition of a learning object. A learning…

  5. The development of a National set of Physiology learning objectives ...

    African Journals Online (AJOL)

    International Journal of Medicine and Health Development ... engagement that can be utilized to design a national set of learning objectives towards improving learning ... Key words: Learning objectives, Nigeria, Medical education, curriculum ...

  6. A Learning Object Approach To Evidence based learning

    Directory of Open Access Journals (Sweden)

    Zabin Visram

    2005-06-01

    Full Text Available This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner's to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has meant increasingly, there is a desperate need to adopt wireless schemes, whereby bespoke courses can be developed to help practitioners keep up with expanding knowledge base. Evidently, without current best evidence, practice risks becoming rapidly out of date, to the detriment of the patient. There is a need to provide a tactical, operational and effective environment, which allows professional to update their education, and complete specialised training, just-in-time, in their own time and location. Following this demand in the marketplace the information engineering group, in combination with several medical and dental schools, set out to develop and design a conceptual framework which form the basis of pioneering research, which at last, enables practitioner's to adopt a philosophy of life long learning. The body and structure of this framework is subsumed under the term Object oriented approach to Evidence Based learning, Just-in-time, via Internet sustained by Reusable Learning Objects (The OEBJIRLO Progression. The technical pillars which permit this concept of life long learning are pivoted by the foundations of object oriented technology, Learning objects, Just-in-time education, Data Mining, intelligent Agent technology, Flash interconnectivity and remote wireless technology, which allow practitioners to update their professional skills, complete specialised training which leads to accredited qualifications. This paper sets out to develop and

  7. Concurrent Models for Object Execution

    OpenAIRE

    Diertens, Bob

    2012-01-01

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

  8. A Learning Object Approach To Evidence based learning

    OpenAIRE

    Zabin Visram; Bruce Elson; Patricia Reynolds

    2005-01-01

    This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner's to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has mea...

  9. Mere exposure alters category learning of novel objects

    Directory of Open Access Journals (Sweden)

    Jonathan R Folstein

    2010-08-01

    Full Text Available We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning.

  10. Mere exposure alters category learning of novel objects.

    Science.gov (United States)

    Folstein, Jonathan R; Gauthier, Isabel; Palmeri, Thomas J

    2010-01-01

    We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning.

  11. Learning Photometric Invariance for Object Detection

    NARCIS (Netherlands)

    Álvarez, J.M.; Gevers, T.; López, A.M.

    2010-01-01

    Color is a powerful visual cue in many computer vision applications such as image segmentation and object recognition. However, most of the existing color models depend on the imaging conditions that negatively affect the performance of the task at hand. Often, a reflection model (e.g., Lambertian

  12. Learning Spatial Object Localization from Vision on a Humanoid Robot

    Directory of Open Access Journals (Sweden)

    Jürgen Leitner

    2012-12-01

    Full Text Available We present a combined machine learning and computer vision approach for robots to localize objects. It allows our iCub humanoid to quickly learn to provide accurate 3D position estimates (in the centimetre range of objects seen. Biologically inspired approaches, such as Artificial Neural Networks (ANN and Genetic Programming (GP, are trained to provide these position estimates using the two cameras and the joint encoder readings. No camera calibration or explicit knowledge of the robot's kinematic model is needed. We find that ANN and GP are not just faster and have lower complexity than traditional techniques, but also learn without the need for extensive calibration procedures. In addition, the approach is localizing objects robustly, when placed in the robot's workspace at arbitrary positions, even while the robot is moving its torso, head and eyes.

  13. Constraints on Perceptual Learning: Objects and Dimensions.

    Science.gov (United States)

    Bedford, Felice L.

    1995-01-01

    Addresses two questions that may be unique to perceptual learning: What are the circumstances that produce learning? and What is the content of learning? Suggests a critical principle for each question. Provides a discussion of perceptual learning theory, how learning occurs, and what gets learned. Includes a 121-item bibliography. (DR)

  14. POMP - Pervasive Object Model Project

    DEFF Research Database (Denmark)

    Schougaard, Kari Rye; Schultz, Ulrik Pagh

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

  15. Elaboration of Statistics Learning Objects for Mobile Devices

    Directory of Open Access Journals (Sweden)

    Francisco Javier Tapia Moreno

    2012-04-01

    Full Text Available Mobile learning (m-learning allows a person to study using a mobile computer device anywhere and anytime. In this work we report the elaboration of learning objects for the teaching of introductory statistics using cellular phones.

  16. Improving learning of anatomy with reusable learning objects

    Directory of Open Access Journals (Sweden)

    P Rad

    2015-12-01

    Full Text Available Introduction: The use of modern educational technologies is useful for learning, durability, sociability, and upgrading professionalism. The aim of this study was evaluating the effect of reusable learning objects on improving learning of anatomy. Methods: This was a quasi-experimental study. Fourteen (reusable learning objects RLO from different parts of anatomy of human body including thorax, abdomen, and pelvis were prepared for medical student in Yasuj University of Medical Sciences in 2009. The length of the time for RLO was between 11-22 min. Because their capacities were low, so they were easy to use with cell phone or MP4. These materials were available to the students before the classes. The mean scores of students in anatomy of human body group were compared to the medical students who were not used this method and entered the university in 2008. A questionnaire was designed by the researcher to evaluate the effect of RLO and on, content, interest and motivation, participation, preparation and attitude. Result: The mean scores of anatomy of human body of medical student who were entered the university in 2009 have been increased compare to the students in 2008, but this difference was not significant. Based on the questionnaire data, it was shown that the RLO had a positive effect on improving learning anatomy of human body (75.5% and the effective relationship (60.6%. The students were interested in using RLO (74.6%, some students (54.2% believed that this method should be replaced by lecture. Conclusion: The use of RLO could promote interests and effective communication among the students and led to increasing self-learning motivation.

  17. Object interaction competence model v. 2.0

    DEFF Research Database (Denmark)

    Bennedsen, Jens; Schulte, C.

    2013-01-01

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

  18. Patterns of Learning Object Reuse in the Connexions Repository

    Science.gov (United States)

    Duncan, S. M.

    2009-01-01

    Since the term "learning object" was first published, there has been either an explicit or implicit expectation of reuse. There has also been a lot of speculation about why learning objects are, or are not, reused. This study quantitatively examined the actual amount and type of learning object use, to include reuse, modification, and translation,…

  19. Building a Smart E-Portfolio Platform for Optimal E-Learning Objects Acquisition

    Directory of Open Access Journals (Sweden)

    Chih-Kun Ke

    2013-01-01

    Full Text Available In modern education, an e-portfolio platform helps students in acquiring e-learning objects in a learning activity. Quality is an important consideration in evaluating the desirable e-learning object. Finding a means of determining a high quality e-learning object from a large number of candidate e-learning objects is an important requirement. To assist student learning in a modern e-portfolio platform, this work proposed an optimal selection approach determining a reasonable e-learning object from various candidate e-learning objects. An optimal selection approach which uses advanced information techniques is proposed. Each e-learning object undergoes a formalization process. An Information Retrieval (IR technique extracts and analyses key concepts from the student’s previous learning contexts. A context-based utility model computes the expected utility values of various e-learning objects based on the extracted key concepts. The expected utility values of e-learning objects are used in a multicriteria decision analysis to determine the optimal selection order of the candidate e-learning objects. The main contribution of this work is the demonstration of an effective e-learning object selection method which is easy to implement within an e-portfolio platform and which makes it smarter.

  20. Learning objects and interactive whiteboards: a evaluation proposal of learning objects for mathematics teaching

    Directory of Open Access Journals (Sweden)

    Silvio Henrique Fiscarelli

    2016-05-01

    Full Text Available The current conditions of the classroom learning tend to be a one-way process based in teacher exposition, this make a negative impact on learning make it a mechanical and not meaningful activity. One possibility to improve the quality of teaching is to innovate methodologies and varying forms of presenting information to students, such as the use of technology in the teaching process. The Interactive Whiteboard (IBW is one of the technologies that are being implemented in Brazilian schools. One of the promising possibilities to add value to the use of LDI in classroom are "learning objects" (LO. However, one problem is that often the LO are not fully suited to the dynamics of IWB, whether functional or pedagogical point of view. The objective of this study is to analyze and propose a set of indicators that evaluate the learning objects for use in conjunction with Interactive Whiteboards. The selection and definition of evaluation indicators was carried from the literature review on the subject and based on LDI experiences of use in Municipal Elementary School. After defining the set of indicators was conducted a evaluation of a sample of 30 OA utilized to teaching mathematics in 3rd grade of elementary school. The results of the evaluation indicate that the proposed indicators are suitable for a pre-analysis of OA and assisting in the process of selection of these.

  1. Object-oriented user interfaces for personalized mobile learning

    CERN Document Server

    Alepis, Efthimios

    2014-01-01

    This book presents recent research in mobile learning and advanced user interfaces. It is shown how the combination of this fields can result in personalized educational software that meets the requirements of state-of-the-art mobile learning software. This book provides a framework that is capable of incorporating the software technologies, exploiting a wide range of their current advances and additionally investigating ways to go even further by providing potential solutions to future challenges. The presented approach uses the well-known Object-Oriented method in order to address these challenges. Throughout this book, a general model is constructed using Object-Oriented Architecture. Each chapter focuses on the construction of a specific part of this model, while in the conclusion these parts are unified. This book will help software engineers build more sophisticated personalized software that targets in mobile education, while at the same time retaining a high level of adaptivity and user-friendliness w...

  2. Learning object repositories as knowledge management systems

    Directory of Open Access Journals (Sweden)

    Demetrios G. Sampson

    2013-06-01

    Full Text Available Over the past years, a number of international initiatives that recognize the importance of sharing and reusing digital educational resources among educational communities through the use of Learning Object Repositories (LORs have emerged. Typically, these initiatives focus on collecting digital educational resources that are offered by their creators for open access and potential reuse. Nevertheless, most of the existing LORs are designed more as digital repositories, rather than as Knowledge Management Systems (KMS. By exploiting KMSs functionalities in LORs would bare the potential to support the organization and sharing of educational communities’ explicit knowledge (depicted in digital educational resources constructed by teachers and/or instructional designers and tacit knowledge (depicted in teachers’ and students’ experiences and interactions of using digital educational resources available in LORs. Within this context, in this paper we study the design and the implementation of fourteen operating LORs from the KMSs’ perspective, so as to identify additional functionalities that can support the management of educational communities’ explicit and tacit knowledge. Thus, we propose a list of essential LORs’ functionalities, which aim to facilitate the organization and sharing of educational communities’ knowledge. Finally, we present the added value of these functionalities by identifying their importance towards addressing the current demands of web-facilitated educational communities, as well as the knowledge management activities that they execute.

  3. Vicarious Learning from Human Models in Monkeys

    OpenAIRE

    Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo

    2012-01-01

    We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was app...

  4. Educational Objectives and the Learning Domains: A New Formulation [And] Summary: Pierce-Gray Classification Model for the Cognitive, Affective and Psychomotor Domains.

    Science.gov (United States)

    Gray, Charles E.; Pierce, Walter D.

    This paper examines and summarizes the "Pierce-Gray Classification Model for the Cognitive, Affective, and Psychomotor Domains," a model developed for the classification of educational objectives. The classification system was developed to provide a framework that teachers could use as a guide when developing specific instructional objectives for…

  5. Participative Knowledge Production of Learning Objects for E-Books.

    Science.gov (United States)

    Dodero, Juan Manuel; Aedo, Ignacio; Diaz, Paloma

    2002-01-01

    Defines a learning object as any digital resource that can be reused to support learning and thus considers electronic books as learning objects. Highlights include knowledge management; participative knowledge production, i.e. authoring electronic books by a distributed group of authors; participative knowledge production architecture; and…

  6. Learning User Preferences for Sets of Objects

    Science.gov (United States)

    desJardins, Marie; Eaton, Eric; Wagstaff, Kiri L.

    2006-01-01

    Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of items. Our learning method takes as input a collection of positive examples--that is, one or more sets that have been identified by a user as desirable. Kernel density estimation is used to estimate the value function for individual items, and the desired set diversity is estimated from the average set diversity observed in the collection. Since this is a new learning problem, we introduce a new evaluation methodology and evaluate the learning method on two data collections: synthetic blocks-world data and a new real-world music data collection that we have gathered.

  7. Developing Learning Objectives for Accounting Ethics Using Bloom's Taxonomy

    Science.gov (United States)

    Kidwell, Linda A.; Fisher, Dann G.; Braun, Robert L.; Swanson, Diane L.

    2013-01-01

    The purpose of our article is to offer a set of core knowledge learning objectives for accounting ethics education. Using Bloom's taxonomy of educational objectives, we develop learning objectives in six content areas: codes of ethical conduct, corporate governance, the accounting profession, moral development, classical ethics theories, and…

  8. Design of Learning Objects for Concept Learning: Effects of Multimedia Learning Principles and an Instructional Approach

    Science.gov (United States)

    Chiu, Thomas K. F.; Churchill, Daniel

    2016-01-01

    Literature suggests using multimedia learning principles in the design of instructional material. However, these principles may not be sufficient for the design of learning objects for concept learning in mathematics. This paper reports on an experimental study that investigated the effects of an instructional approach, which includes two teaching…

  9. An Exploratory Study into the Efficacy of Learning Objects

    Directory of Open Access Journals (Sweden)

    Nicholas W. Farha, Ph.D.

    2009-07-01

    Full Text Available Learning objects have quickly become a widely accepted approach to instructional technology, particularly in on-line and computer-based learning environments. While there is a substantial body of literature concerning learning objects, very little of it verifies their efficacy. This research investigated the effectiveness of learning objects by comparing learning outcomes using a learning object with outcomes using a traditional textbook-based method of instruction. Participants were 327 undergraduate college students at a traditional public four-year coed institution, a private four-year women’s college, a private four-year engineering institution, and a public two-year community college. Through a series of independent samples t-tests and Analyses of Variance, results revealed mean scores for the learning object group that were nearly three times higher than the mean scores for the textbook-taught group. Gaming experience, age, gender, and learner preference were evaluated for their potential influence on the results; no statistically significant differences were found, implying that the learning object itself was central to the outcomes achieved. The future of learning objects is bright, and more empirical research is called for in the area of learning object effectiveness.

  10. Liberating Learning Object Design from the Learning Style of Student Instructional Designers

    Science.gov (United States)

    Akpinar, Yavuz

    2007-01-01

    Learning objects are a new form of learning resource, and the design of these digital environments has many facets. To investigate senior instructional design students' use of reflection tools in designing learning objects, a series of studies was conducted using the Reflective Action Instructional Design and Learning Object Review Instrument…

  11. Form over Substance: Learning Objectives in the Business Core

    Science.gov (United States)

    Stokes, Leonard; Rosetti, Joseph L.; King, Michelle

    2010-01-01

    While members of the business faculty community have been advocating active learning in the classroom, it appears that textbooks encourage learning from a passive perspective. A review of learning objectives from 16 textbooks used in Financial Accounting, Managerial Accounting, Finance, and Marketing demonstrates a focus on basically the same set…

  12. Things to Say: Future Applications of Smart Objects in Learning

    Science.gov (United States)

    Preis, Kevin

    2008-01-01

    Smart object technology allows users to know something in real time about the physical objects in their presence. Each object, from cereal boxes to skyscrapers, becomes a source of information with which users can interact. Through a series of usage scenarios, the article explores the potential impact of smart objects on learning in formal and…

  13. Learning Object-Orientation through ICT-mediated Apprenticeship

    DEFF Research Database (Denmark)

    Fjuk, A.; Berge, O.; Bennedsen, J.

    2004-01-01

    In this paper, we show how sociocultural theories inform the design of a course in object-oriented programming. An essential learning objective within this philosophy is the programming processes as such. To move toward this learning goal, the course design incorporates a combination of the so...

  14. Searching for and Positioning of Contextualized Learning Objects

    Science.gov (United States)

    Baldiris, Silvia; Graf, Sabine; Fabregat, Ramon; Mendez, Nestor Dario Duque

    2012-01-01

    Learning object economies are marketplaces for the sharing and reuse of learning objects (LO). There are many motivations for stimulating the development of the LO economy. The main reason is the possibility of providing the right content, at the right time, to the right learner according to adequate quality standards in the context of a lifelong…

  15. Guide to good practices for developing learning objectives. DOE guideline

    Energy Technology Data Exchange (ETDEWEB)

    1992-07-01

    This guide to good practices provides information and guidance on the types of, and the development of learning objectives in performance-based training system at reactor and nonreactor nuclear facilities. Contractors are encouraged to consider this guidance as a reference when developing new learning objectives or refining existing ones. Training managers, designers, developers, and instructors are the intended audiences.

  16. Guide to good practices for developing learning objectives. DOE Handbook

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1992-07-01

    This guide to good practices provides information and guidance on the types of and development of learning objectives in a systematic approach to training program. This document can serve as a reference during the development of new learning objectives or refinement of existing ones.

  17. On the Concepts of Usability and Reusability of Learning Objects

    Directory of Open Access Journals (Sweden)

    Miguel-Angel Sicilia

    2003-10-01

    Full Text Available “Reusable learning objects” oriented towards increasing their potential reusability are required to satisfy concerns about their granularity and their independence of concrete contexts of use. Such requirements also entail that the definition of learning object “usability,” and the techniques required to carry out their “usability evaluation” must be substantially different from those commonly used to characterize and evaluate the usability of conventional educational applications. In this article, a specific characterization of the concept of learning object usability is discussed, which places emphasis on “reusability,” the key property of learning objects residing in repositories. The concept of learning object reusability is described as the possibility and adequacy for the object to be usable in prospective educational settings, so that usability and reusability are considered two interrelated – and in many cases conflicting – properties of learning objects. Following the proposed characterization of two characteristics or properties of learning objects, a method to evaluate usability of specific learning objects will be presented.

  18. Learning Objectives for Master's theses at DTU Management Engineering

    DEFF Research Database (Denmark)

    Hansen, Claus Thorp; Rasmussen, Birgitte; Hinz, Hector Nøhr

    2010-01-01

    , different. The DTU Study Handbook states that:”Learning objectives are an integrated part of the supervision”, which provides you with the opportunity – naturally in cooperation with your supervisor – to formulate learning objectives for your Master's thesis. There are at least three good reasons for being...... that you formulate precise and useful learning objectives for your Master's thesis. These notes of inspiration have been written to help you do exactly this. The notes discuss the requirements for the learning objectives, examples of learning objectives and the assessment criteria defined by DTU Management...... Engineering as well as, but not least, some useful things to remember concerning your submission and the assessment of the Master's thesis. DTU Management Engineering Claus Thorp Hansen Birgitte Rasmussen Hector Nøhr Hinz © DTU Management Engineering 2010 ISBN nr. 978-87-90855-94-7 This document...

  19. A Critique of Stephen Downes' "Learning Objects": A Chinese perspective

    Directory of Open Access Journals (Sweden)

    Fuhua (Oscar Lin

    2001-07-01

    Full Text Available This paper by Stephen Downes recommends a way of sharing online teaching/ course materials to accelerate course development and make education more cost-effective. His paper is a review of basic information about learning objects (LOs and includes examples that illustrate such technical terms as XML and TML. His paper, however, does not identify several important issues such as: a the level of granularity of learning objects; b selection and integration of learning objects in an appropriate way to form higher level units of study; c training of professors in the use of learning objects; d appropriate use of metadata to facilitate composition of higher level units; and e the potential of computer agents to facilitate the dynamic composition of personalized lessons. An unorganized aggregate of learning objects simply does not constitute a course. In order to create a properly designed final course, student and instructor interaction must be built in.

  20. Assessing Complex Learning Objectives through Analytics

    Science.gov (United States)

    Horodyskyj, L.; Mead, C.; Buxner, S.; Semken, S. C.; Anbar, A. D.

    2016-12-01

    A significant obstacle to improving the quality of education is the lack of easy-to-use assessments of higher-order thinking. Most existing assessments focus on recall and understanding questions, which demonstrate lower-order thinking. Traditionally, higher-order thinking is assessed with practical tests and written responses, which are time-consuming to analyze and are not easily scalable. Computer-based learning environments offer the possibility of assessing such learning outcomes based on analysis of students' actions within an adaptive learning environment. Our fully online introductory science course, Habitable Worlds, uses an intelligent tutoring system that collects and responds to a range of behavioral data, including actions within the keystone project. This central project is a summative, game-like experience in which students synthesize and apply what they have learned throughout the course to identify and characterize a habitable planet from among hundreds of stars. Student performance is graded based on completion and accuracy, but two additional properties can be utilized to gauge higher-order thinking: (1) how efficient a student is with the virtual currency within the project and (2) how many of the optional milestones a student reached. In the project, students can use the currency to check their work and "unlock" convenience features. High-achieving students spend close to the minimum amount required to reach these goals, indicating a high-level of concept mastery and efficient methodology. Average students spend more, indicating effort, but lower mastery. Low-achieving students were more likely to spend very little, which indicates low effort. Differences on these metrics were statistically significant between all three of these populations. We interpret this as evidence that high-achieving students develop and apply efficient problem-solving skills as compared to lower-achieving student who use more brute-force approaches.

  1. Vicarious learning from human models in monkeys.

    Science.gov (United States)

    Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo

    2012-01-01

    We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.

  2. Vicarious learning from human models in monkeys.

    Directory of Open Access Journals (Sweden)

    Rossella Falcone

    Full Text Available We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.

  3. Learning Object Metadata in a Web-Based Learning Environment

    NARCIS (Netherlands)

    Avgeriou, Paris; Koutoumanos, Anastasios; Retalis, Symeon; Papaspyrou, Nikolaos

    2000-01-01

    The plethora and variance of learning resources embedded in modern web-based learning environments require a mechanism to enable their structured administration. This goal can be achieved by defining metadata on them and constructing a system that manages the metadata in the context of the learning

  4. Learning to Detect Human-Object Interactions

    KAUST Repository

    Chao, Yu-Wei; Liu, Yunfan; Liu, Xieyang; Zeng, Huayi; Deng, Jia

    2017-01-01

    In this paper we study the problem of detecting human-object interactions (HOI) in static images, defined as predicting a human and an object bounding box with an interaction class label that connects them. HOI detection is a fundamental problem in computer vision as it provides semantic information about the interactions among the detected objects. We introduce HICO-DET, a new large benchmark for HOI detection, by augmenting the current HICO classification benchmark with instance annotations. We propose Human-Object Region-based Convolutional Neural Networks (HO-RCNN), a novel DNN-based framework for HOI detection. At the core of our HO-RCNN is the Interaction Pattern, a novel DNN input that characterizes the spatial relations between two bounding boxes. We validate the effectiveness of our HO-RCNN using HICO-DET. Experiments demonstrate that our HO-RCNN, by exploiting human-object spatial relations through Interaction Patterns, significantly improves the performance of HOI detection over baseline approaches.

  5. Learning to Detect Human-Object Interactions

    KAUST Repository

    Chao, Yu-Wei

    2017-02-17

    In this paper we study the problem of detecting human-object interactions (HOI) in static images, defined as predicting a human and an object bounding box with an interaction class label that connects them. HOI detection is a fundamental problem in computer vision as it provides semantic information about the interactions among the detected objects. We introduce HICO-DET, a new large benchmark for HOI detection, by augmenting the current HICO classification benchmark with instance annotations. We propose Human-Object Region-based Convolutional Neural Networks (HO-RCNN), a novel DNN-based framework for HOI detection. At the core of our HO-RCNN is the Interaction Pattern, a novel DNN input that characterizes the spatial relations between two bounding boxes. We validate the effectiveness of our HO-RCNN using HICO-DET. Experiments demonstrate that our HO-RCNN, by exploiting human-object spatial relations through Interaction Patterns, significantly improves the performance of HOI detection over baseline approaches.

  6. Object feature extraction and recognition model

    International Nuclear Information System (INIS)

    Wan Min; Xiang Rujian; Wan Yongxing

    2001-01-01

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

  7. Creation of 'Ukrytie' objects computer model

    International Nuclear Information System (INIS)

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

    1999-01-01

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

  8. Analyzing the Quality of Students Interaction in a Distance Learning Object-Oriented Programming Discipline

    Science.gov (United States)

    Carvalho, Elizabeth Simão

    2015-01-01

    Teaching object-oriented programming to students in an in-classroom environment demands well-thought didactic and pedagogical strategies in order to guarantee a good level of apprenticeship. To teach it on a completely distance learning environment (e-learning) imposes possibly other strategies, besides those that the e-learning model of Open…

  9. Localization-Aware Active Learning for Object Detection

    OpenAIRE

    Kao, Chieh-Chi; Lee, Teng-Yok; Sen, Pradeep; Liu, Ming-Yu

    2018-01-01

    Active learning - a class of algorithms that iteratively searches for the most informative samples to include in a training dataset - has been shown to be effective at annotating data for image classification. However, the use of active learning for object detection is still largely unexplored as determining informativeness of an object-location hypothesis is more difficult. In this paper, we address this issue and present two metrics for measuring the informativeness of an object hypothesis,...

  10. Object based implicit contextual learning: a study of eye movements.

    Science.gov (United States)

    van Asselen, Marieke; Sampaio, Joana; Pina, Ana; Castelo-Branco, Miguel

    2011-02-01

    Implicit contextual cueing refers to a top-down mechanism in which visual search is facilitated by learned contextual features. In the current study we aimed to investigate the mechanism underlying implicit contextual learning using object information as a contextual cue. Therefore, we measured eye movements during an object-based contextual cueing task. We demonstrated that visual search is facilitated by repeated object information and that this reduction in response times is associated with shorter fixation durations. This indicates that by memorizing associations between objects in our environment we can recognize objects faster, thereby facilitating visual search.

  11. A Framework for the Flexible Content Packaging of Learning Objects and Learning Designs

    Science.gov (United States)

    Lukasiak, Jason; Agostinho, Shirley; Burnett, Ian; Drury, Gerrard; Goodes, Jason; Bennett, Sue; Lockyer, Lori; Harper, Barry

    2004-01-01

    This paper presents a platform-independent method for packaging learning objects and learning designs. The method, entitled a Smart Learning Design Framework, is based on the MPEG-21 standard, and uses IEEE Learning Object Metadata (LOM) to provide bibliographic, technical, and pedagogical descriptors for the retrieval and description of learning…

  12. An object-based visual attention model for robotic applications.

    Science.gov (United States)

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

    2010-10-01

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

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

    Science.gov (United States)

    Franz, A; Triesch, J

    2010-12-01

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

  14. Science Integrating Learning Objectives: A Cooperative Learning Group Process

    Science.gov (United States)

    Spindler, Matt

    2015-01-01

    The integration of agricultural and science curricular content that capitalizes on natural and inherent connections represents a challenge for secondary agricultural educators. The purpose of this case study was to create information about the employment of Cooperative Learning Groups (CLG) to enhance the science integrating learning objectives…

  15. Dew Point modelling using GEP based multi objective optimization

    OpenAIRE

    Shroff, Siddharth; Dabhi, Vipul

    2013-01-01

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

  16. Hierarchical image segmentation for learning object priors

    Energy Technology Data Exchange (ETDEWEB)

    Prasad, Lakshman [Los Alamos National Laboratory; Yang, Xingwei [TEMPLE UNIV.; Latecki, Longin J [TEMPLE UNIV.; Li, Nan [TEMPLE UNIV.

    2010-11-10

    The proposed segmentation approach naturally combines experience based and image based information. The experience based information is obtained by training a classifier for each object class. For a given test image, the result of each classifier is represented as a probability map. The final segmentation is obtained with a hierarchial image segmentation algorithm that considers both the probability maps and the image features such as color and edge strength. We also utilize image region hierarchy to obtain not only local but also semi-global features as input to the classifiers. Moreover, to get robust probability maps, we take into account the region context information by averaging the probability maps over different levels of the hierarchical segmentation algorithm. The obtained segmentation results are superior to the state-of-the-art supervised image segmentation algorithms.

  17. Probabilistic object and viewpoint models for active object recognition

    CSIR Research Space (South Africa)

    Govender, N

    2013-09-01

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

  18. ICT Competence-Based Learning Object Recommendations for Teachers

    Science.gov (United States)

    Sergis, Stylianos; Zervas, Panagiotis; Sampson, Demetrios G.

    2014-01-01

    Recommender Systems (RS) have been applied in the Technology enhanced Learning (TeL) field for facilitating, among others, Learning Object (LO) selection and retrieval. Most of the existing approaches, however, aim at accommodating the needs of learners and teacher-oriented RS are still an under-investigated field. Moreover, the systems that focus…

  19. An OWL Ontology for Metadata of Interactive Learning Objects

    Science.gov (United States)

    Luz, Bruno N.; Santos, Rafael; Alves, Bruno; Areão, Andreza S.; Yokoyama, Marcos H.; Guimarães, Marcelo P.

    2015-01-01

    The main purpose of this paper is to present the importance of Interactive Learning Objects (ILO) to improve the teaching-learning process by assuring a constant interaction among teachers and students, which in turn, allows students to be constantly supported by the teacher. The paper describes the ontology that defines the ILO available on the…

  20. Technology and human issues in reusing learning objects

    NARCIS (Netherlands)

    Collis, Betty; Strijker, A.

    2004-01-01

    Reusing learning objects is as old as retelling a story or making use of libraries and textbooks, and in electronic form has received an enormous new impetus because of the World Wide Web and Web technologies. Are we at the brink of changing the "shape and form of learning, ... of being able to

  1. Speckle-learning-based object recognition through scattering media.

    Science.gov (United States)

    Ando, Takamasa; Horisaki, Ryoichi; Tanida, Jun

    2015-12-28

    We experimentally demonstrated object recognition through scattering media based on direct machine learning of a number of speckle intensity images. In the experiments, speckle intensity images of amplitude or phase objects on a spatial light modulator between scattering plates were captured by a camera. We used the support vector machine for binary classification of the captured speckle intensity images of face and non-face data. The experimental results showed that speckles are sufficient for machine learning.

  2. How learning might strengthen existing visual object representations in human object-selective cortex.

    Science.gov (United States)

    Brants, Marijke; Bulthé, Jessica; Daniels, Nicky; Wagemans, Johan; Op de Beeck, Hans P

    2016-02-15

    Visual object perception is an important function in primates which can be fine-tuned by experience, even in adults. Which factors determine the regions and the neurons that are modified by learning is still unclear. Recently, it was proposed that the exact cortical focus and distribution of learning effects might depend upon the pre-learning mapping of relevant functional properties and how this mapping determines the informativeness of neural units for the stimuli and the task to be learned. From this hypothesis we would expect that visual experience would strengthen the pre-learning distributed functional map of the relevant distinctive object properties. Here we present a first test of this prediction in twelve human subjects who were trained in object categorization and differentiation, preceded and followed by a functional magnetic resonance imaging session. Specifically, training increased the distributed multi-voxel pattern information for trained object distinctions in object-selective cortex, resulting in a generalization from pre-training multi-voxel activity patterns to after-training activity patterns. Simulations show that the increased selectivity combined with the inter-session generalization is consistent with a training-induced strengthening of a pre-existing selectivity map. No training-related neural changes were detected in other regions. In sum, training to categorize or individuate objects strengthened pre-existing representations in human object-selective cortex, providing a first indication that the neuroanatomical distribution of learning effects depends upon the pre-learning mapping of visual object properties. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. The Composite OLAP-Object Data Model

    Energy Technology Data Exchange (ETDEWEB)

    Pourabbas, Elaheh; Shoshani, Arie

    2005-12-07

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

  4. Interactive Preference Learning of Utility Functions for Multi-Objective Optimization

    OpenAIRE

    Dewancker, Ian; McCourt, Michael; Ainsworth, Samuel

    2016-01-01

    Real-world engineering systems are typically compared and contrasted using multiple metrics. For practical machine learning systems, performance tuning is often more nuanced than minimizing a single expected loss objective, and it may be more realistically discussed as a multi-objective optimization problem. We propose a novel generative model for scalar-valued utility functions to capture human preferences in a multi-objective optimization setting. We also outline an interactive active learn...

  5. Object tracking using active appearance models

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2001-01-01

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

  6. Model United Nations and Deep Learning: Theoretical and Professional Learning

    Science.gov (United States)

    Engel, Susan; Pallas, Josh; Lambert, Sarah

    2017-01-01

    This article demonstrates that the purposeful subject design, incorporating a Model United Nations (MUN), facilitated deep learning and professional skills attainment in the field of International Relations. Deep learning was promoted in subject design by linking learning objectives to Anderson and Krathwohl's (2001) four levels of knowledge or…

  7. Learning object for teacher training aimed to develop communication skills

    Directory of Open Access Journals (Sweden)

    Norma Esmeralda RODRÍGUEZ RAMÍREZ

    2014-06-01

    Full Text Available This article presents the results and reflections obtained across a research aimed to analyze the quality criteria of an opened learning object oriented to develop communication skills in order to be able to report and validate it according to its content, pedagogic structure, technological structure, graphical and textual language and usability to teacher training, in order to base it theoretically, pedagogically and technologically. The research question was: Which are the quality criteria that a learning object aimed to develop communication skills must cover? Under a quantitative approach, there were electronic questionnaires applied to: 34 Technological University teachers, eight experts about of communicative competence, teaching, technology and graphic design. The results indicated that some of the quality criteria of learning object are: the effective managing of the learning content, the balanced composition of his pedagogic structure, the technological structure efficiency and the proper managing of graphical and textual language.

  8. EFFECTS OF INQUIRY TRAINING LEARNING MODEL BASED MULTIMEDIA AND MOTIVATION OF PHYSICS STUDENT LEARNING OUTCOMES

    OpenAIRE

    Hayati .; Retno Dwi Suyanti

    2013-01-01

    The objective in this research: (1) Determine a better learning model to improve learning outcomes physics students among learning model Inquiry Training based multimedia and Inquiry Training learning model. (2) Determine the level of motivation to learn in affects physics student learning outcomes. (3) Knowing the interactions between the model of learning and motivation in influencing student learning outcomes. This research is a quasi experimental. The population in this research was all s...

  9. Object tracking by occlusion detection via structured sparse learning

    KAUST Repository

    Zhang, Tianzhu

    2013-06-01

    Sparse representation based methods have recently drawn much attention in visual tracking due to good performance against illumination variation and occlusion. They assume the errors caused by image variations can be modeled as pixel-wise sparse. However, in many practical scenarios these errors are not truly pixel-wise sparse but rather sparsely distributed in a structured way. In fact, pixels in error constitute contiguous regions within the object\\'s track. This is the case when significant occlusion occurs. To accommodate for non-sparse occlusion in a given frame, we assume that occlusion detected in previous frames can be propagated to the current one. This propagated information determines which pixels will contribute to the sparse representation of the current track. In other words, pixels that were detected as part of an occlusion in the previous frame will be removed from the target representation process. As such, this paper proposes a novel tracking algorithm that models and detects occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that our tracker consistently outperforms the state-of-the-art. © 2013 IEEE.

  10. Individualized Learning Through Non-Linear use of Learning Objects: With Examples From Math and Stat

    DEFF Research Database (Denmark)

    Rootzén, Helle

    2015-01-01

    Our aim is to ensure individualized learning that is fun, inspiring and innovative. We believe that when you enjoy, your brain will open up and learning will be easier and more effective. The methods use a non-linear learning environment based on self-contained learning objects which are pieced t...

  11. Reinforcement active learning in the vibrissae system: optimal object localization.

    Science.gov (United States)

    Gordon, Goren; Dorfman, Nimrod; Ahissar, Ehud

    2013-01-01

    Rats move their whiskers to acquire information about their environment. It has been observed that they palpate novel objects and objects they are required to localize in space. We analyze whisker-based object localization using two complementary paradigms, namely, active learning and intrinsic-reward reinforcement learning. Active learning algorithms select the next training samples according to the hypothesized solution in order to better discriminate between correct and incorrect labels. Intrinsic-reward reinforcement learning uses prediction errors as the reward to an actor-critic design, such that behavior converges to the one that optimizes the learning process. We show that in the context of object localization, the two paradigms result in palpation whisking as their respective optimal solution. These results suggest that rats may employ principles of active learning and/or intrinsic reward in tactile exploration and can guide future research to seek the underlying neuronal mechanisms that implement them. Furthermore, these paradigms are easily transferable to biomimetic whisker-based artificial sensors and can improve the active exploration of their environment. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Learning while Babbling: Prelinguistic Object-Directed Vocalizations Indicate a Readiness to Learn

    Science.gov (United States)

    Goldstein, Michael H.; Schwade, Jennifer; Briesch, Jacquelyn; Syal, Supriya

    2010-01-01

    Two studies illustrate the functional significance of a new category of prelinguistic vocalizing--object-directed vocalizations (ODVs)--and show that these sounds are connected to learning about words and objects. Experiment 1 tested 12-month-old infants' perceptual learning of objects that elicited ODVs. Fourteen infants' vocalizations were…

  13. Moving objects management models, techniques and applications

    CERN Document Server

    Meng, Xiaofeng; Xu, Jiajie

    2014-01-01

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

  14. Learning Objects and Grasp Affordances through Autonomous Exploration

    DEFF Research Database (Denmark)

    Kraft, Dirk; Detry, Renaud; Pugeault, Nicolas

    2009-01-01

    We describe a system for autonomous learning of visual object representations and their grasp affordances on a robot-vision system. It segments objects by grasping and moving 3D scene features, and creates probabilistic visual representations for object detection, recognition and pose estimation...... image sequences as well as (3) a number of built-in behavioral modules on the one hand, and autonomous exploration on the other hand, the system is able to generate object and grasping knowledge through interaction with its environment....

  15. Object recognition in images via a factor graph model

    Science.gov (United States)

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

    2018-04-01

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

  16. An Initial Approach for Learning Objects from Experience

    Science.gov (United States)

    2018-05-02

    algorithm to delineate objects which are then fed to a simple feed-forward neural network without any other processes in the pipeline. Our neural network...These are the basic requirements for the pipeline and are discussed in more detail below. Additionally, we are interested in testing various parts...that continuously learning objects from experience requires mechanisms to do the following: 1) Focus attention on things and stuff of interest . 2

  17. Incremental online object learning in a vehicular radar-vision fusion framework

    Energy Technology Data Exchange (ETDEWEB)

    Ji, Zhengping [Los Alamos National Laboratory; Weng, Juyang [Los Alamos National Laboratory; Luciw, Matthew [IEEE; Zeng, Shuqing [IEEE

    2010-10-19

    In this paper, we propose an object learning system that incorporates sensory information from an automotive radar system and a video camera. The radar system provides a coarse attention for the focus of visual analysis on relatively small areas within the image plane. The attended visual areas are coded and learned by a 3-layer neural network utilizing what is called in-place learning, where every neuron is responsible for the learning of its own signal processing characteristics within its connected network environment, through inhibitory and excitatory connections with other neurons. The modeled bottom-up, lateral, and top-down connections in the network enable sensory sparse coding, unsupervised learning and supervised learning to occur concurrently. The presented work is applied to learn two types of encountered objects in multiple outdoor driving settings. Cross validation results show the overall recognition accuracy above 95% for the radar-attended window images. In comparison with the uncoded representation and purely unsupervised learning (without top-down connection), the proposed network improves the recognition rate by 15.93% and 6.35% respectively. The proposed system is also compared with other learning algorithms favorably. The result indicates that our learning system is the only one to fit all the challenging criteria for the development of an incremental and online object learning system.

  18. Development and assessment of learning objects about intramuscular medication administration

    Directory of Open Access Journals (Sweden)

    Lilian Mayumi Chinen Tamashiro

    2014-10-01

    Full Text Available OBJECTIVES: to develop and assess a learning object about intramuscular medication administration for nursing undergraduates and nurses.METHOD: a random, intentional and non-probabilistic sample was selected of nurses from a Brazilian social network of nursing and students from the Undergraduate Program at the University of São Paulo School of Nursing to serve as research subjects and assess the object.RESULTS: the participants, 8 nurses and 8 students, studied the object and answered an assessment instrument that included the following criteria: educational aspects (relevance of the theme, objectives and texts/hypertexts, interface of the environment (navigation, accessibility and screen design and didactic resources (interactivity and presentation of resources. In total, 128 significant answers were obtained, 124 (97% of which were positive, assessed as excellent and satisfactory, considered as a flexible, dynamic, objective resources that is appropriate to the nursing learning process.CONCLUSION: the educational technology shows a clear and easily understandable language and the teaching method could be applied in other themes, contributing to the education and training of nursing professionals, positively affecting nursing teaching, stimulating the knowledge, autonomous and independent learning, aligned with the new professional education requirements.

  19. Moving object detection in video satellite image based on deep learning

    Science.gov (United States)

    Zhang, Xueyang; Xiang, Junhua

    2017-11-01

    Moving object detection in video satellite image is studied. A detection algorithm based on deep learning is proposed. The small scale characteristics of remote sensing video objects are analyzed. Firstly, background subtraction algorithm of adaptive Gauss mixture model is used to generate region proposals. Then the objects in region proposals are classified via the deep convolutional neural network. Thus moving objects of interest are detected combined with prior information of sub-satellite point. The deep convolution neural network employs a 21-layer residual convolutional neural network, and trains the network parameters by transfer learning. Experimental results about video from Tiantuo-2 satellite demonstrate the effectiveness of the algorithm.

  20. #gottacatchemall: Exploring Pokemon Go in Search of Learning Enhancement Objects

    Science.gov (United States)

    Cacchione, Annamaria; Procter-Legg, Emma; Petersen, Sobah Abbas

    2017-01-01

    The Augmented Reality Game, Pokemon Go, took the world by storm in the summer of 2016. City landscapes were decorated with amusing, colourful objects called Pokemon, and the holiday activities were enhanced by catching these wonderful creatures. In light of this, it is inevitable for mobile language learning researchers to reflect on the impact of…

  1. Evaluating the Use of Learning Objects for Improving Calculus Readiness

    Science.gov (United States)

    Kay, Robin; Kletskin, Ilona

    2010-01-01

    Pre-calculus concepts such as working with functions and solving equations are essential for students to explore limits, rates of change, and integrals. Yet many students have a weak understanding of these key concepts which impedes performance in their first year university Calculus course. A series of online learning objects was developed to…

  2. Semantic Linking of Learning Object Repositories to DBpedia

    Science.gov (United States)

    Lama, Manuel; Vidal, Juan C.; Otero-Garcia, Estefania; Bugarin, Alberto; Barro, Senen

    2012-01-01

    Large-sized repositories of learning objects (LOs) are difficult to create and also to maintain. In this paper we propose a way to reduce this drawback by improving the classification mechanisms of the LO repositories. Specifically, we present a solution to automate the LO classification of the Universia repository, a collection of more than 15…

  3. Exploring Characterizations of Learning Object Repositories Using Data Mining Techniques

    Science.gov (United States)

    Segura, Alejandra; Vidal, Christian; Menendez, Victor; Zapata, Alfredo; Prieto, Manuel

    Learning object repositories provide a platform for the sharing of Web-based educational resources. As these repositories evolve independently, it is difficult for users to have a clear picture of the kind of contents they give access to. Metadata can be used to automatically extract a characterization of these resources by using machine learning techniques. This paper presents an exploratory study carried out in the contents of four public repositories that uses clustering and association rule mining algorithms to extract characterizations of repository contents. The results of the analysis include potential relationships between different attributes of learning objects that may be useful to gain an understanding of the kind of resources available and eventually develop search mechanisms that consider repository descriptions as a criteria in federated search.

  4. [Learning objectives achievement in ethics education for medical school students].

    Science.gov (United States)

    Chae, Sujin; Lim, Kiyoung

    2015-06-01

    This study aimed to examine the necessity for research ethics and learning objectives in ethics education at the undergraduate level. A total of 393 fourth-year students, selected from nine medical schools, participated in a survey about learning achievement and the necessity for it. It was found that the students had very few chances to receive systematic education in research ethics and that they assumed that research ethics education was provided during graduate school or residency programs. Moreover, the students showed a relatively high learning performance in life ethics, while learning achievement was low in research ethics. Medical school students revealed low interest in and expectations of research ethics in general; therefore, it is necessary to develop guidelines for research ethics in the present situation, in which medical education mainly focuses on life ethics.

  5. Comparing L2 Word Learning through a Tablet or Real Objects: What Benefits Learning Most?

    NARCIS (Netherlands)

    Vlaar, M.A.J.; Verhagen, J.; Oudgenoeg-Paz, O.; Leseman, P.P.M.

    2017-01-01

    In child-robot interactions focused on language learning, tablets are often used to structure the interaction between the robot and the child. However, it is not clear how tablets affect children’s learning gains. Real-life objects are thought to benefit children’s word learning, but it is not clear

  6. Visual object tracking by correlation filters and online learning

    Science.gov (United States)

    Zhang, Xin; Xia, Gui-Song; Lu, Qikai; Shen, Weiming; Zhang, Liangpei

    2018-06-01

    Due to the complexity of background scenarios and the variation of target appearance, it is difficult to achieve high accuracy and fast speed for object tracking. Currently, correlation filters based trackers (CFTs) show promising performance in object tracking. The CFTs estimate the target's position by correlation filters with different kinds of features. However, most of CFTs can hardly re-detect the target in the case of long-term tracking drifts. In this paper, a feature integration object tracker named correlation filters and online learning (CFOL) is proposed. CFOL estimates the target's position and its corresponding correlation score using the same discriminative correlation filter with multi-features. To reduce tracking drifts, a new sampling and updating strategy for online learning is proposed. Experiments conducted on 51 image sequences demonstrate that the proposed algorithm is superior to the state-of-the-art approaches.

  7. Creating Objects and Object Categories for Studying Perception and Perceptual Learning

    Science.gov (United States)

    Hauffen, Karin; Bart, Eugene; Brady, Mark; Kersten, Daniel; Hegdé, Jay

    2012-01-01

    In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created

  8. An Analysis on Usage Preferences of Learning Objects and Learning Object Repositories among Pre-Service Teachers

    Science.gov (United States)

    Yeni, Sabiha; Ozdener, Nesrin

    2014-01-01

    The purpose of the study is to investigate how pre-service teachers benefit from learning objects repositories while preparing course content. Qualitative and quantitative data collection methods were used in a mixed methods approach. This study was carried out with 74 teachers from the Faculty of Education. In the first phase of the study,…

  9. Personalised Learning Object System Based on Self-Regulated Learning Theories

    Directory of Open Access Journals (Sweden)

    Ali Alharbi

    2014-06-01

    Full Text Available Self-regulated learning has become an important construct in education research in the last few years. Selfregulated learning in its simple form is the learner’s ability to monitor and control the learning process. There is increasing research in the literature on how to support students become more self-regulated learners. However, the advancement in the information technology has led to paradigm changes in the design and development of educational content. The concept of learning object instructional technology has emerged as a result of this shift in educational technology paradigms. This paper presents the results of a study that investigated the potential educational effectiveness of a pedagogical framework based on the self-regulated learning theories to support the design of learning object systems to help computer science students. A prototype learning object system was developed based on the contemporary research on self-regulated learning. The system was educationally evaluated in a quasi-experimental study over two semesters in a core programming languages concepts course. The evaluation revealed that a learning object system that takes into consideration contemporary research on self-regulated learning can be an effective learning environment to support computer science education.

  10. Learning with hierarchical-deep models.

    Science.gov (United States)

    Salakhutdinov, Ruslan; Tenenbaum, Joshua B; Torralba, Antonio

    2013-08-01

    We introduce HD (or “Hierarchical-Deep”) models, a new compositional learning architecture that integrates deep learning models with structured hierarchical Bayesian (HB) models. Specifically, we show how we can learn a hierarchical Dirichlet process (HDP) prior over the activities of the top-level features in a deep Boltzmann machine (DBM). This compound HDP-DBM model learns to learn novel concepts from very few training example by learning low-level generic features, high-level features that capture correlations among low-level features, and a category hierarchy for sharing priors over the high-level features that are typical of different kinds of concepts. We present efficient learning and inference algorithms for the HDP-DBM model and show that it is able to learn new concepts from very few examples on CIFAR-100 object recognition, handwritten character recognition, and human motion capture datasets.

  11. Real time natural object modeling framework

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  12. How do newcomers learn to use an object?

    DEFF Research Database (Denmark)

    Kjær, Malene

    in the daily practice of assessing how a patient is doing. Learning how to operate it in situ is thus an important task.I will present an empirical example from clinical nursing education in a Danish hospital, where students learn to use specific medical objects (a sphygmomanometer) in the setting...... status and stance (Heritage, 2012) epistemic, cooperative and instrumental stance (Goodwin, 2007) is important, as is the understanding of situated embodied cognition in the workplace practice: the knowledge ‘understanding and use of objects’ that has been limited to the nurse, translates through...

  13. The IRMIS object model and services API

    International Nuclear Information System (INIS)

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

    2005-01-01

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

  14. Critically Important Object Security System Element Model

    Directory of Open Access Journals (Sweden)

    I. V. Khomyackov

    2012-03-01

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

  15. Mobile Authoring of Open Educational Resources as Reusable Learning Objects

    Directory of Open Access Journals (Sweden)

    Dr Kinshuk

    2013-06-01

    Full Text Available E-learning technologies have allowed authoring and playback of standardized reusable learning objects (RLO for several years. Effective mobile learning requires similar functionality at both design time and runtime. Mobile devices can play RLO using applications like SMILE, mobile access to a learning management system (LMS, or other systems which deploy content to mobile learners (Castillo & Ayala, 2008; Chu, Hwang, & Tseng, 2010; Hsu & Chen, 2010; Nakabayashi, 2009; Zualkernan, Nikkhah, & Al-Sabah, 2009. However, implementations which author content in a mobile context do not typically permit reuse across multiple contexts due to a lack of standardization. Standards based (IMS and SCORM authoring implementations exist for non-mobile platforms (Gonzalez-Barbone & Anido-Rifon, 2008; Griffiths, Beauvoir, Liber, & Barrett-Baxendale, 2009; Téllez, 2010; Yang, Chiu, Tsai, & Wu, 2004. However, this paradigm precludes capturing learning where and when it occurs. Consequently, RLO authored for e-learning lack learner generated content, especially with timely, relevant, and location aware examples.

  16. Object Oriented Modelling and Dynamical Simulation

    DEFF Research Database (Denmark)

    Wagner, Falko Jens; Poulsen, Mikael Zebbelin

    1998-01-01

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

  17. An object model for beamline descriptions

    International Nuclear Information System (INIS)

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

    1997-01-01

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

  18. ROBUSTNESS AND PREDICTION ACCURACY OF MACHINE LEARNING FOR OBJECTIVE VISUAL QUALITY ASSESSMENT

    OpenAIRE

    Hines, Andrew; Kendrick, Paul; Barri, Adriaan; Narwaria, Manish; Redi, Judith A.

    2014-01-01

    Machine Learning (ML) is a powerful tool to support the development of objective visual quality assessment metrics, serving as a substitute model for the perceptual mechanisms acting in visual quality appreciation. Nevertheless, the reliability of ML-based techniques within objective quality assessment metrics is often questioned. In this study, the robustness of ML in supporting objective quality assessment is investigated, specifically when the feature set adopted for prediction is suboptim...

  19. Robustness and prediction accuracy of machine learning for objective visual quality assessment

    OpenAIRE

    HINES, ANDREW

    2014-01-01

    PUBLISHED Lisbon, Portugal Machine Learning (ML) is a powerful tool to support the development of objective visual quality assessment metrics, serving as a substitute model for the perceptual mechanisms acting in visual quality appreciation. Nevertheless, the reli- ability of ML-based techniques within objective quality as- sessment metrics is often questioned. In this study, the ro- bustness of ML in supporting objective quality assessment is investigated, specific...

  20. Virtual learning object and environment: a concept analysis.

    Science.gov (United States)

    Salvador, Pétala Tuani Candido de Oliveira; Bezerril, Manacés Dos Santos; Mariz, Camila Maria Santos; Fernandes, Maria Isabel Domingues; Martins, José Carlos Amado; Santos, Viviane Euzébia Pereira

    2017-01-01

    To analyze the concept of virtual learning object and environment according to Rodgers' evolutionary perspective. Descriptive study with a mixed approach, based on the stages proposed by Rodgers in his concept analysis method. Data collection occurred in August 2015 with the search of dissertations and theses in the Bank of Theses of the Coordination for the Improvement of Higher Education Personnel. Quantitative data were analyzed based on simple descriptive statistics and the concepts through lexicographic analysis with support of the IRAMUTEQ software. The sample was made up of 161 studies. The concept of "virtual learning environment" was presented in 99 (61.5%) studies, whereas the concept of "virtual learning object" was presented in only 15 (9.3%) studies. A virtual learning environment includes several and different types of virtual learning objects in a common pedagogical context. Analisar o conceito de objeto e de ambiente virtual de aprendizagem na perspectiva evolucionária de Rodgers. Estudo descritivo, de abordagem mista, realizado a partir das etapas propostas por Rodgers em seu modelo de análise conceitual. A coleta de dados ocorreu em agosto de 2015 com a busca de dissertações e teses no Banco de Teses e Dissertações da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior. Os dados quantitativos foram analisados a partir de estatística descritiva simples e os conceitos pela análise lexicográfica com suporte do IRAMUTEQ. A amostra é constituída de 161 estudos. O conceito de "ambiente virtual de aprendizagem" foi apresentado em 99 (61,5%) estudos, enquanto o de "objeto virtual de aprendizagem" em apenas 15 (9,3%). Concluiu-se que um ambiente virtual de aprendizagem reúne vários e diferentes tipos de objetos virtuais de aprendizagem em um contexto pedagógico comum.

  1. Depth Value Pre-Processing for Accurate Transfer Learning Based RGB-D Object Recognition

    DEFF Research Database (Denmark)

    Aakerberg, Andreas; Nasrollahi, Kamal; Rasmussen, Christoffer Bøgelund

    2017-01-01

    of an existing deeplearning based RGB-D object recognition model, namely the FusionNet proposed by Eitel et al. First, we showthat encoding the depth values as colorized surface normals is beneficial, when the model is initialized withweights learned from training on ImageNet data. Additionally, we show...

  2. Bayesian feature weighting for unsupervised learning, with application to object recognition

    OpenAIRE

    Carbonetto , Peter; De Freitas , Nando; Gustafson , Paul; Thompson , Natalie

    2003-01-01

    International audience; We present a method for variable selection/weighting in an unsupervised learning context using Bayesian shrinkage. The basis for the model parameters and cluster assignments can be computed simultaneous using an efficient EM algorithm. Applying our Bayesian shrinkage model to a complex problem in object recognition (Duygulu, Barnard, de Freitas and Forsyth 2002), our experiments yied good results.

  3. Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

    Science.gov (United States)

    Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

    2017-06-21

    In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

  4. Modeling business objects with XML schema

    CERN Document Server

    Daum, Berthold

    2003-01-01

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

  5. Smart learning objects for smart education in computer science theory, methodology and robot-based implementation

    CERN Document Server

    Stuikys, Vytautas

    2015-01-01

    This monograph presents the challenges, vision and context to design smart learning objects (SLOs) through Computer Science (CS) education modelling and feature model transformations. It presents the latest research on the meta-programming-based generative learning objects (the latter with advanced features are treated as SLOs) and the use of educational robots in teaching CS topics. The introduced methodology includes the overall processes to develop SLO and smart educational environment (SEE) and integrates both into the real education setting to provide teaching in CS using constructivist a

  6. Information model of the 'Ukryttya' object

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  7. Large-scale weakly supervised object localization via latent category learning.

    Science.gov (United States)

    Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

    2015-04-01

    Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

  8. Algorithms for Learning Preferences for Sets of Objects

    Science.gov (United States)

    Wagstaff, Kiri L.; desJardins, Marie; Eaton, Eric

    2010-01-01

    A method is being developed that provides for an artificial-intelligence system to learn a user's preferences for sets of objects and to thereafter automatically select subsets of objects according to those preferences. The method was originally intended to enable automated selection, from among large sets of images acquired by instruments aboard spacecraft, of image subsets considered to be scientifically valuable enough to justify use of limited communication resources for transmission to Earth. The method is also applicable to other sets of objects: examples of sets of objects considered in the development of the method include food menus, radio-station music playlists, and assortments of colored blocks for creating mosaics. The method does not require the user to perform the often-difficult task of quantitatively specifying preferences; instead, the user provides examples of preferred sets of objects. This method goes beyond related prior artificial-intelligence methods for learning which individual items are preferred by the user: this method supports a concept of setbased preferences, which include not only preferences for individual items but also preferences regarding types and degrees of diversity of items in a set. Consideration of diversity in this method involves recognition that members of a set may interact with each other in the sense that when considered together, they may be regarded as being complementary, redundant, or incompatible to various degrees. The effects of such interactions are loosely summarized in the term portfolio effect. The learning method relies on a preference representation language, denoted DD-PREF, to express set-based preferences. In DD-PREF, a preference is represented by a tuple that includes quality (depth) functions to estimate how desired a specific value is, weights for each feature preference, the desired diversity of feature values, and the relative importance of diversity versus depth. The system applies statistical

  9. Evaluation of a Learning Object Based Learning Environment in Different Dimensions

    Directory of Open Access Journals (Sweden)

    Ünal Çakıroğlu

    2009-11-01

    Full Text Available Learning Objects (LOs are web based learning resources presented by Learning Object Repositories (LOR. For recent years LOs have begun to take place on web and it is suggested that appropriate design of LOs can make positive impact on learning. In order to support learning, research studies recommends LOs should have been evaluated pedagogically and technologically, and the content design created by using LOs should have been designed through appropriate instructional models. Since the use of LOs have recently begun, an exact pedagogical model about efficient use of LOs has not been developed. In this study a LOR is designed in order to be used in mathematics education. The LOs in this LOR have been evaluated pedagogically and technologically by mathematics teachers and field experts. In order to evaluate the designed LO based environment, two different questionnaires have been used. These questionnaires are developed by using the related literature about web based learning environments evaluation criteria and also the items are discussed with the field experts for providing the validity. The reliability of the questionnaires is calculated cronbach alpha = 0.715 for the design properties evaluation survey and cronbach alpha =0.726 for pedagogic evaluation. Both of two questionnaires are five point Likert type. The first questionnaire has the items about “Learning Support of LOs, Competency of LOR, The importance of LOs in mathematics education, the usability of LOs by students”. “The activities on LOs are related to outcomes of subjects, there are activities for students have different learning styles. There are activities for wondering students.” are examples for items about learning support of LOs. “System helps for exploration of mathematical relations”, “I think teaching mathematics with this system will be enjoyable.” are example items for importance of LOs in mathematics education. In the competency of LOR title,

  10. Space Objects Maneuvering Detection and Prediction via Inverse Reinforcement Learning

    Science.gov (United States)

    Linares, R.; Furfaro, R.

    This paper determines the behavior of Space Objects (SOs) using inverse Reinforcement Learning (RL) to estimate the reward function that each SO is using for control. The approach discussed in this work can be used to analyze maneuvering of SOs from observational data. The inverse RL problem is solved using the Feature Matching approach. This approach determines the optimal reward function that a SO is using while maneuvering by assuming that the observed trajectories are optimal with respect to the SO's own reward function. This paper uses estimated orbital elements data to determine the behavior of SOs in a data-driven fashion.

  11. Online Feature Transformation Learning for Cross-Domain Object Category Recognition.

    Science.gov (United States)

    Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold

    2017-06-09

    In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.

  12. Employing Machine-Learning Methods to Study Young Stellar Objects

    Science.gov (United States)

    Moore, Nicholas

    2018-01-01

    Vast amounts of data exist in the astronomical data archives, and yet a large number of sources remain unclassified. We developed a multi-wavelength pipeline to classify infrared sources. The pipeline uses supervised machine learning methods to classify objects into the appropriate categories. The program is fed data that is already classified to train it, and is then applied to unknown catalogues. The primary use for such a pipeline is the rapid classification and cataloging of data that would take a much longer time to classify otherwise. While our primary goal is to study young stellar objects (YSOs), the applications extend beyond the scope of this project. We present preliminary results from our analysis and discuss future applications.

  13. Mosaic model for sensorimotor learning and control.

    Science.gov (United States)

    Haruno, M; Wolpert, D M; Kawato, M

    2001-10-01

    Humans demonstrate a remarkable ability to generate accurate and appropriate motor behavior under many different and often uncertain environmental conditions. We previously proposed a new modular architecture, the modular selection and identification for control (MOSAIC) model, for motor learning and control based on multiple pairs of forward (predictor) and inverse (controller) models. The architecture simultaneously learns the multiple inverse models necessary for control as well as how to select the set of inverse models appropriate for a given environment. It combines both feedforward and feedback sensorimotor information so that the controllers can be selected both prior to movement and subsequently during movement. This article extends and evaluates the MOSAIC architecture in the following respects. The learning in the architecture was implemented by both the original gradient-descent method and the expectation-maximization (EM) algorithm. Unlike gradient descent, the newly derived EM algorithm is robust to the initial starting conditions and learning parameters. Second, simulations of an object manipulation task prove that the architecture can learn to manipulate multiple objects and switch between them appropriately. Moreover, after learning, the model shows generalization to novel objects whose dynamics lie within the polyhedra of already learned dynamics. Finally, when each of the dynamics is associated with a particular object shape, the model is able to select the appropriate controller before movement execution. When presented with a novel shape-dynamic pairing, inappropriate activation of modules is observed followed by on-line correction.

  14. Learning Mathematics by Designing, Programming, and Investigating with Interactive, Dynamic Computer-Based Objects

    Science.gov (United States)

    Marshall, Neil; Buteau, Chantal

    2014-01-01

    As part of their undergraduate mathematics curriculum, students at Brock University learn to create and use computer-based tools with dynamic, visual interfaces, called Exploratory Objects, developed for the purpose of conducting pure or applied mathematical investigations. A student's Development Process Model of creating and using an Exploratory…

  15. Learning object-to-class kernels for scene classification.

    Science.gov (United States)

    Zhang, Lei; Zhen, Xiantong; Shao, Ling

    2014-08-01

    High-level image representations have drawn increasing attention in visual recognition, e.g., scene classification, since the invention of the object bank. The object bank represents an image as a response map of a large number of pretrained object detectors and has achieved superior performance for visual recognition. In this paper, based on the object bank representation, we propose the object-to-class (O2C) distances to model scene images. In particular, four variants of O2C distances are presented, and with the O2C distances, we can represent the images using the object bank by lower-dimensional but more discriminative spaces, called distance spaces, which are spanned by the O2C distances. Due to the explicit computation of O2C distances based on the object bank, the obtained representations can possess more semantic meanings. To combine the discriminant ability of the O2C distances to all scene classes, we further propose to kernalize the distance representation for the final classification. We have conducted extensive experiments on four benchmark data sets, UIUC-Sports, Scene-15, MIT Indoor, and Caltech-101, which demonstrate that the proposed approaches can significantly improve the original object bank approach and achieve the state-of-the-art performance.

  16. Creating Usage Context-Based Object Similarities to Boost Recommender Systems in Technology Enhanced Learning

    Science.gov (United States)

    Niemann, Katja; Wolpers, Martin

    2015-01-01

    In this paper, we introduce a new way of detecting semantic similarities between learning objects by analysing their usage in web portals. Our approach relies on the usage-based relations between the objects themselves rather then on the content of the learning objects or on the relations between users and learning objects. We then take this new…

  17. Assessing Program Learning Objectives to Improve Undergraduate Physics Education

    Science.gov (United States)

    Menke, Carrie

    2014-03-01

    Our physics undergraduate program has five program learning objectives (PLOs) focusing on (1) physical principles, (2) mathematical expertise, (3) experimental technique, (4) communication and teamwork, and (5) research proficiency. One PLO is assessed each year, with the results guiding modifications in our curriculum and future assessment practices; we have just completed our first cycle of assessing all PLOs. Our approach strives to maximize the ease and applicability of our assessment practices while maintaining faculty's flexibility in course design and delivery. Objectives are mapped onto our core curriculum with identified coursework collected as direct evidence. We've utilized mostly descriptive rubrics, applying them at the course and program levels as well as sharing them with the students. This has resulted in more efficient assessment that is also applicable to reaccreditation efforts, higher inter-rater reliability than with other rubric types, and higher quality capstone projects. We've also found that the varied quality of student writing can interfere with our assessment of other objectives. This poster outlines our processes, resources, and how we have used PLO assessment to strengthen our undergraduate program.

  18. Delivery of Learning Knowledge Objects Using Fuzzy Clustering

    Science.gov (United States)

    Sabitha, A. Sai; Mehrotra, Deepti; Bansal, Abhay

    2016-01-01

    e-Learning industry is rapidly changing and the current learning trends are based on personalized, social and mobile learning, content reusability, cloud-based and talent management. The learning systems have attained a significant growth catering to the needs of a wide range of learners, having different approaches and styles of learning. Objects…

  19. Web based Interactive 3D Learning Objects for Learning Management Systems

    Directory of Open Access Journals (Sweden)

    Stefan Hesse

    2012-02-01

    Full Text Available In this paper, we present an approach to create and integrate interactive 3D learning objects of high quality for higher education into a learning management system. The use of these resources allows to visualize topics, such as electro-technical and physical processes in the interior of complex devices. This paper addresses the challenge of combining rich interactivity and adequate realism with 3D exercise material for distance elearning.

  20. Learning objects as coadjuvants in the human physiology teaching-learning process

    Directory of Open Access Journals (Sweden)

    Marcus Vinícius Lara

    2014-08-01

    Full Text Available The use of Information and Communication Technologies (ICTs in the academic environment of biomedical area has gained much importance, both for their ability to complement the understanding of the subject obtained in the classroom, is the ease of access, or makes more pleasure the learning process, since these tools are present in everyday of the students and use a simple language. Considering that, this study aims to report the experience of building learning objects in human physiology as a tool for learning facilitation, and discuss the impact of this teaching methodology

  1. The Inclusion Potential of Student Production of Digital Learning Objects

    DEFF Research Database (Denmark)

    Levinsen, Karin Tweddell; Sørensen, Birgitte Holm

    2016-01-01

    This account of the inclusion potential of students’ digital production is based on the large-scale research and development project Students’ Digital Production and Students as Learning Designers (2013–2015), funded by the Danish Ministry of Education. The target groups were primary and lower......-designed framework that accommodates and empowers students’ agency. The Danish parliament passed the Law of Inclusion In 2012 with the objective that by 2015, 96% of all students would be included in normal classes. Inclusion was not part of the initial research agenda, but this changed unexpectedly during...... the project. Specifically, students who did not participate or participated only sporadically in everyday school activities at the beginning of the project adopted new positions as participants and agents. We understand these changes as inclusive processes initiated by the combination of teacher...

  2. I learning object: la condivisione dei materiali didattici come naturale evoluzione del web

    Directory of Open Access Journals (Sweden)

    Corrado Petrucco

    2004-01-01

    Full Text Available Discussion of Learning Objects (LO and sharing of educational materials. In addition to the standards that exist today, some issues are dealt with the emergence of these new objects of learning.

  3. Discriminative object tracking via sparse representation and online dictionary learning.

    Science.gov (United States)

    Xie, Yuan; Zhang, Wensheng; Li, Cuihua; Lin, Shuyang; Qu, Yanyun; Zhang, Yinghua

    2014-04-01

    We propose a robust tracking algorithm based on local sparse coding with discriminative dictionary learning and new keypoint matching schema. This algorithm consists of two parts: the local sparse coding with online updated discriminative dictionary for tracking (SOD part), and the keypoint matching refinement for enhancing the tracking performance (KP part). In the SOD part, the local image patches of the target object and background are represented by their sparse codes using an over-complete discriminative dictionary. Such discriminative dictionary, which encodes the information of both the foreground and the background, may provide more discriminative power. Furthermore, in order to adapt the dictionary to the variation of the foreground and background during the tracking, an online learning method is employed to update the dictionary. The KP part utilizes refined keypoint matching schema to improve the performance of the SOD. With the help of sparse representation and online updated discriminative dictionary, the KP part are more robust than the traditional method to reject the incorrect matches and eliminate the outliers. The proposed method is embedded into a Bayesian inference framework for visual tracking. Experimental results on several challenging video sequences demonstrate the effectiveness and robustness of our approach.

  4. Real-world visual statistics and infants' first-learned object names.

    Science.gov (United States)

    Clerkin, Elizabeth M; Hart, Elizabeth; Rehg, James M; Yu, Chen; Smith, Linda B

    2017-01-05

    We offer a new solution to the unsolved problem of how infants break into word learning based on the visual statistics of everyday infant-perspective scenes. Images from head camera video captured by 8 1/2 to 10 1/2 month-old infants at 147 at-home mealtime events were analysed for the objects in view. The images were found to be highly cluttered with many different objects in view. However, the frequency distribution of object categories was extremely right skewed such that a very small set of objects was pervasively present-a fact that may substantially reduce the problem of referential ambiguity. The statistical structure of objects in these infant egocentric scenes differs markedly from that in the training sets used in computational models and in experiments on statistical word-referent learning. Therefore, the results also indicate a need to re-examine current explanations of how infants break into word learning.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

  5. Personalized Learning Objects Recommendation Based on the Semantic-Aware Discovery and the Learner Preference Pattern

    Science.gov (United States)

    Wang, Tzone I; Tsai, Kun Hua; Lee, Ming Che; Chiu, Ti Kai

    2007-01-01

    With vigorous development of the Internet, especially the web page interaction technology, distant E-learning has become more and more realistic and popular. Digital courses may consist of many learning units or learning objects and, currently, many learning objects are created according to SCORM standard. It can be seen that, in the near future,…

  6. 中小學行動學習準備度探究與分析 Support-Object-Personnel Mobile-Learning Readiness Model for Primary and Secondary Schools

    Directory of Open Access Journals (Sweden)

    游雅婷 Ya-Ting Yu

    2016-12-01

    Full Text Available 有效整合行動學習資源並在執行行動學習前完成充分準備,是學校創新並達到成功的第一步,然而,當前並無相關準備度評估工具能提供給學校參考。本研究目的在發展行動學習準備度以作為學校實施行動學習前的自我檢核評估工具,並依此分析中小學行動學習準備度現況。研究透過文獻檢閱、焦點團體座談、問卷調查等歷程,以探索性因素分析、單一樣本t檢定、弗里曼等級平均數與卡方檢定等統計方法進行分析,最後由正在進行行動學習的71 所中小學(11 所國中、60 所國小)填寫本研究編製的行動學習準備度線上問卷。研究對象有焦點團體座談4人、問卷調查198 人,以及代表學校填寫行動學習準備度問卷71 人,皆為執行過資訊融入教學的教育人員。研究結果顯示:一、行動學習準備度可分為S:「支持系統」、O:「物件設備」、P:「參與人員」三大面向,以及10 個指標、30 個子指標。二、中小學行動學習準備度填寫結果,在三大面向的成績尚屬平均,其中以「領導者能力」指標成績最高、「校務平台」指標成績最低。 Efficiently integrating mobile learning resources is an essential step in developing a successful innovative education system that can enhance perceptions and stimulate preparations for M-learning among school administrators and faculty members. Currently, tools for measuring M-learning readiness and instruments that can productively evaluate M-learning readiness are extremely limited. This study proposed the support-object-personnel (SOP m-learning readiness model to assess the capacity for m-learning readiness in primary and secondary schools in Taiwan. Through a literature review and focus group interviews (N = 4, several standards were identified. Questionnaires (N =198 were developed and then implemented to conduct a valid survey

  7. From brain synapses to systems for learning and memory: Object recognition, spatial navigation, timed conditioning, and movement control.

    Science.gov (United States)

    Grossberg, Stephen

    2015-09-24

    This article provides an overview of neural models of synaptic learning and memory whose expression in adaptive behavior depends critically on the circuits and systems in which the synapses are embedded. It reviews Adaptive Resonance Theory, or ART, models that use excitatory matching and match-based learning to achieve fast category learning and whose learned memories are dynamically stabilized by top-down expectations, attentional focusing, and memory search. ART clarifies mechanistic relationships between consciousness, learning, expectation, attention, resonance, and synchrony. ART models are embedded in ARTSCAN architectures that unify processes of invariant object category learning, recognition, spatial and object attention, predictive remapping, and eye movement search, and that clarify how conscious object vision and recognition may fail during perceptual crowding and parietal neglect. The generality of learned categories depends upon a vigilance process that is regulated by acetylcholine via the nucleus basalis. Vigilance can get stuck at too high or too low values, thereby causing learning problems in autism and medial temporal amnesia. Similar synaptic learning laws support qualitatively different behaviors: Invariant object category learning in the inferotemporal cortex; learning of grid cells and place cells in the entorhinal and hippocampal cortices during spatial navigation; and learning of time cells in the entorhinal-hippocampal system during adaptively timed conditioning, including trace conditioning. Spatial and temporal processes through the medial and lateral entorhinal-hippocampal system seem to be carried out with homologous circuit designs. Variations of a shared laminar neocortical circuit design have modeled 3D vision, speech perception, and cognitive working memory and learning. A complementary kind of inhibitory matching and mismatch learning controls movement. This article is part of a Special Issue entitled SI: Brain and Memory

  8. Learning to Appraise the Quality of Qualitative Research Articles: A Contextualized Learning Object for Constructing Knowledge

    Science.gov (United States)

    Chenail, Ronald J.

    2011-01-01

    Helping beginning qualitative researchers critically appraise qualitative research articles is a common learning objective for introductory methodology courses. To aid students in achieving competency in appraising the quality of qualitative research articles, a multi-part activity incorporating the Critical Appraisal Skills Programme's (CASP)…

  9. Student Modeling and Machine Learning

    OpenAIRE

    Sison , Raymund; Shimura , Masamichi

    1998-01-01

    After identifying essential student modeling issues and machine learning approaches, this paper examines how machine learning techniques have been used to automate the construction of student models as well as the background knowledge necessary for student modeling. In the process, the paper sheds light on the difficulty, suitability and potential of using machine learning for student modeling processes, and, to a lesser extent, the potential of using student modeling techniques in machine le...

  10. Resident Space Object Characterization and Behavior Understanding via Machine Learning and Ontology-based Bayesian Networks

    Science.gov (United States)

    Furfaro, R.; Linares, R.; Gaylor, D.; Jah, M.; Walls, R.

    2016-09-01

    In this paper, we present an end-to-end approach that employs machine learning techniques and Ontology-based Bayesian Networks (BN) to characterize the behavior of resident space objects. State-of-the-Art machine learning architectures (e.g. Extreme Learning Machines, Convolutional Deep Networks) are trained on physical models to learn the Resident Space Object (RSO) features in the vectorized energy and momentum states and parameters. The mapping from measurements to vectorized energy and momentum states and parameters enables behavior characterization via clustering in the features space and subsequent RSO classification. Additionally, Space Object Behavioral Ontologies (SOBO) are employed to define and capture the domain knowledge-base (KB) and BNs are constructed from the SOBO in a semi-automatic fashion to execute probabilistic reasoning over conclusions drawn from trained classifiers and/or directly from processed data. Such an approach enables integrating machine learning classifiers and probabilistic reasoning to support higher-level decision making for space domain awareness applications. The innovation here is to use these methods (which have enjoyed great success in other domains) in synergy so that it enables a "from data to discovery" paradigm by facilitating the linkage and fusion of large and disparate sources of information via a Big Data Science and Analytics framework.

  11. Activities Joining Learning Objectives to Assessments in Introductory Astronomy

    Science.gov (United States)

    Palen, Stacy E.; Larson, Ana M.

    2015-01-01

    In recent years, accreditation boards and other governing bodies have been pushing hard for explicit learning goals and quantitative measures of assessment for general education courses such as Astronomy 101. This added assessment burden can be problematic, especially for harried adjuncts teaching multiple courses at multiple institutions. It would be helpful to have a field-tested set of combined hands-on activities and assessment tools that help instructors meet these assessment requirements. The authors have produced just such a set. We have been using hands-on activities in our classrooms for more than 15 years. These activities require no special equipment or preparation and can be completed within an hour by most students working in groups of two or three. The sections of each activity are arranged in steps, guiding the students from initial knowledge-level questions or practice to a final evaluation or synthesis of what they have just accomplished. Students thus get practice thinking at higher cognitive levels. A recent addition to these activities is the inclusion of formalized learning objectives and accompanying pre- and post-activity questions. The pre-activity questions address common misconceptions, relate familiar analogous terrestrial examples to the activity, and act as a brief refresher meta-concepts like scale factors, measurements, and basic mathematics review. The post-activity questions review the most important concepts introduced in the activity. We present a number of examples as well as a summary as to how we have initiated their use in a large lecture setting of 300 students, in smaller classrooms of 15 students, and in a community college online course.

  12. Developing Goals and Objectives for Gameplay and Learning

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2014-01-01

    This chapter introduces goals in games and then potential differences between learning goals and goalsin games, as well as the difficulties that may occur when implementing learning goals in games....

  13. EDUCATEE'S THESAURUS AS AN OBJECT OF MEASURING LEARNED MATERIAL OF THE DISTANCE LEARNING COURSE

    Directory of Open Access Journals (Sweden)

    Alexander Aleksandrovich RYBANOV

    2013-10-01

    Full Text Available Monitoring and control over the process of studying the distance learning course are based on solving the problem of making out an adequate integral mark to the educatee for mastering entire study course, by testing results. It is suggested to use the degree of correspondence between educatee's thesaurus and the study course thesaurus as an integral mark for the degree of mastering the distance learning course. Study course thesaurus is a set of the course objects with relations between them specified. The article considers metrics of the study course thesaurus complexity, made on the basis of the graph theory and the information theory. It is suggested to use the amount of information contained in the study course thesaurus graph as the metrics of the study course thesaurus complexity. Educatee's thesaurus is considered as an object of measuring educational material learned at the semantic level and is assessed on the basis of amount of information contained in its graph, taking into account the factors of learning the thesaurus objects.

  14. Visual Perceptual Learning and Models.

    Science.gov (United States)

    Dosher, Barbara; Lu, Zhong-Lin

    2017-09-15

    Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.

  15. Data quality objectives lessons learned for tank waste characterization

    International Nuclear Information System (INIS)

    Eberlein, S.J.

    1996-01-01

    The tank waste characterization process is an integral part of the overall effort to control the hazards associated with radioactive wastes stored in underground tanks at the Hanford Reservation. The programs involved in the characterization of the wastes are employing Data Quality Objective (DQO) process in all information and data collection activities. The DQO process is used by the programs to address an issue or problem rather than a specific sampling event. Practical limits do not always allow for precise characterization of a tank or the implementation of the DQO process. Because of the flexibility of the DQO process, it can be used as a tool for sampling and analysis of the underground waste storage tanks. The iterative nature of the DQO process allows it to be used as additional information is claimed or lessons are learned concerning an issue or problem requiring sampling and analysis of tank waste. In addition, the application of DQO process forces alternative actions to be considered when precise characterization of a tank or the full implementation of the DQO process is not practical

  16. Occlusion detection via structured sparse learning for robust object tracking

    KAUST Repository

    Zhang, Tianzhu

    2014-01-01

    Sparse representation based methods have recently drawn much attention in visual tracking due to good performance against illumination variation and occlusion. They assume the errors caused by image variations can be modeled as pixel-wise sparse. However, in many practical scenarios, these errors are not truly pixel-wise sparse but rather sparsely distributed in a structured way. In fact, pixels in error constitute contiguous regions within the object’s track. This is the case when significant occlusion occurs. To accommodate for nonsparse occlusion in a given frame, we assume that occlusion detected in previous frames can be propagated to the current one. This propagated information determines which pixels will contribute to the sparse representation of the current track. In other words, pixels that were detected as part of an occlusion in the previous frame will be removed from the target representation process. As such, this paper proposes a novel tracking algorithm that models and detects occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Extensive experimental results show that our proposed tracker consistently outperforms the state-of-the-art trackers.

  17. EFFECTS OF INQUIRY TRAINING LEARNING MODEL BASED MULTIMEDIA AND MOTIVATION OF PHYSICS STUDENT LEARNING OUTCOMES

    Directory of Open Access Journals (Sweden)

    Hayati .

    2013-06-01

    Full Text Available The objective in this research: (1 Determine a better learning model to improve learning outcomes physics students among learning model Inquiry Training based multimedia and Inquiry Training learning model. (2 Determine the level of motivation to learn in affects physics student learning outcomes. (3 Knowing the interactions between the model of learning and motivation in influencing student learning outcomes. This research is a quasi experimental. The population in this research was all students in class XI SMA Negeri 1 T.P Sunggal Semester I 2012/2013. The sample of this research was consisted of two classes with a sample of 70 peoples who are determined by purposive sampling, the IPA XI-2 as a class experiment using a model-based multimedia learning Training Inquiry as many as 35 peoples and XI IPA-3 as a control class using learning model Inquiry Training 35 peoples. Hypotheses were analyzed using the GLM at significant level of 0.05 using SPSS 17.0 for Windows. Based on data analysis and hypothesis testing conducted found that: (1 Training Inquiry-based multimedia learning model in improving student learning outcomes rather than learning model physics Inquiry Training. (2 The results of studying physics students who have high motivation to learn better than students who have a low learning motivation. (3 From this research there was an interaction between learning model inquiry-based multimedia training and motivation to study on learning outcomes of students.

  18. Learning from Objects: A Future for 21st Century Urban Arts Education

    Science.gov (United States)

    Lasky, Dorothea

    2009-01-01

    In this technological age, where mind and body are increasingly disconnected in the classroom, object-based learning--along with strong museum-school partnerships--provide many benefits for student learning. In this article, the author first outlines some of the special mind-body connections that object-based learning in museums affords learners…

  19. Advanced technology for the reuse of learning objects in a course-management system

    NARCIS (Netherlands)

    Strijker, A.; Collis, Betty

    2005-01-01

    The creation, labelling, use, and re-use of learning objects is an important area of development involving learning technology. In the higher education context, instructors typically use a course management system (CMS) to organize and manage their own learning objects. The needs and practices of

  20. Object-oriented biomedical system modelling--the language.

    Science.gov (United States)

    Hakman, M; Groth, T

    1999-11-01

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

  1. Models for predicting objective function weights in prostate cancer IMRT

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  2. Models for predicting objective function weights in prostate cancer IMRT

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-04-15

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

  3. Conformance Testing, the Elixer within the Chain for Learning Scenarios and Objects

    NARCIS (Netherlands)

    Nadolski, Rob; O'Neill, Owen; Vegt van der, Wim; Koper, Rob

    2006-01-01

    The chain for learning scenarios and learning objects includes five iterative links: (i) development, (ii) publication, (iii) making resources searchable and reusable and (iv) facilitating their arrangement (v) towards a runnable unit of learning. The use of e-learning specifications and

  4. Active Learning with Statistical Models.

    Science.gov (United States)

    1995-01-01

    Active Learning with Statistical Models ASC-9217041, NSF CDA-9309300 6. AUTHOR(S) David A. Cohn, Zoubin Ghahramani, and Michael I. Jordan 7. PERFORMING...TERMS 15. NUMBER OF PAGES Al, MIT, Artificial Intelligence, active learning , queries, locally weighted 6 regression, LOESS, mixtures of gaussians...COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES A.I. Memo No. 1522 January 9. 1995 C.B.C.L. Paper No. 110 Active Learning with

  5. Efficient Exact Inference With Loss Augmented Objective in Structured Learning.

    Science.gov (United States)

    Bauer, Alexander; Nakajima, Shinichi; Muller, Klaus-Robert

    2016-08-19

    Structural support vector machine (SVM) is an elegant approach for building complex and accurate models with structured outputs. However, its applicability relies on the availability of efficient inference algorithms--the state-of-the-art training algorithms repeatedly perform inference to compute a subgradient or to find the most violating configuration. In this paper, we propose an exact inference algorithm for maximizing nondecomposable objectives due to special type of a high-order potential having a decomposable internal structure. As an important application, our method covers the loss augmented inference, which enables the slack and margin scaling formulations of structural SVM with a variety of dissimilarity measures, e.g., Hamming loss, precision and recall, Fβ-loss, intersection over union, and many other functions that can be efficiently computed from the contingency table. We demonstrate the advantages of our approach in natural language parsing and sequence segmentation applications.

  6. DROpS: an object of learning in computer simulation of discrete events

    Directory of Open Access Journals (Sweden)

    Hugo Alves Silva Ribeiro

    2015-09-01

    Full Text Available This work presents the “Realistic Dynamics Of Simulated Operations” (DROpS, the name given to the dynamics using the “dropper” device as an object of teaching and learning. The objective is to present alternatives for professors teaching content related to simulation of discrete events to graduate students in production engineering. The aim is to enable students to develop skills related to data collection, modeling, statistical analysis, and interpretation of results. This dynamic has been developed and applied to the students by placing them in a situation analogous to a real industry, where various concepts related to computer simulation were discussed, allowing the students to put these concepts into practice in an interactive manner, thus facilitating learning

  7. Modelling object typicality in description logics

    CSIR Research Space (South Africa)

    Britz, K

    2009-12-01

    Full Text Available in the context under consideration, than those lower down. For any given class C, we assume that all objects in the appli- cation domain that are in (the interpretation of) C are more typical of C than those not in C. This is a technical construction which... to be modular partial orders, i.e. reflexive, transitive, anti- symmetric relations such that, for all a, b, c in ∆I , if a and b are incomparable and a is strictly below c, then b is also strictly below c. Modular partial orders have the effect...

  8. Portal and repository for sharing mathematical learning objects

    NARCIS (Netherlands)

    Zanden, van der A.H.W.; Cuypers, H.; Luca, J.; Weippl, E.R.

    2008-01-01

    Now that Virtual Learning Environments are common within higher education in the Netherlands it is time to work with online validated informational resources. Technologies such as repositories are the systems to manage learning content but are most inconvenient in use. The national project NKBW aims

  9. The Development of the Virtual Learning Media of the Sacred Object Artwork

    Science.gov (United States)

    Nuanmeesri, Sumitra; Jamornmongkolpilai, Saran

    2018-01-01

    This research aimed to develop the virtual learning media of the sacred object artwork by applying the concept of the virtual technology in order to publicize knowledge on the cultural wisdom of the sacred object artwork. It was done by designing and developing the virtual learning media of the sacred object artwork for the virtual presentation.…

  10. Using Model to Plan of Strategic Objectives

    OpenAIRE

    Terezie Bartusková; Jitka Baňařová; Zuzana Kusněřová

    2012-01-01

    Importance of strategic planning is unquestionable. However, the practical implementation of a strategic plan faces too many obstacles. The aim of the article is explained the importance of strategic planning and to find how companies in Moravian-Silesian Region deal with strategic planning, and to introduce the model, which helps to set strategic goals in financial indicators area. This model should be part of the whole process of strategic planning and can be use to predict the future value...

  11. A model of objective weighting for EIA.

    Science.gov (United States)

    Ying, L G; Liu, Y C

    1995-06-01

    In spite of progress achieved in the research of environmental impact assessment (EIA), the problem of weight distribution for a set of parameters has not as yet, been properly solved. This paper presents an approach of objective weighting by using a procedure of P ij principal component-factor analysis (P ij PCFA), which suits specifically those parameters measured directly by physical scales. The P ij PCFA weighting procedure reforms the conventional weighting practice in two aspects: first, the expert subjective judgment is replaced by the standardized measure P ij as the original input of weight processing and, secondly, the principal component-factor analysis is introduced to approach the environmental parameters for their respective contributions to the totality of the regional ecosystem. Not only is the P ij PCFA weighting logical in theoretical reasoning, it also suits practically all levels of professional routines in natural environmental assessment and impact analysis. Having been assured of objectivity and accuracy in the EIA case study of the Chuansha County in Shanghai, China, the P ij PCFA weighting procedure has the potential to be applied in other geographical fields that need assigning weights to parameters that are measured by physical scales.

  12. Active learning in the lecture theatre using 3D printed objects [version 2; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    David P. Smith

    2016-06-01

    Full Text Available The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme’s active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student.

  13. Active learning in the lecture theatre using 3D printed objects.

    Science.gov (United States)

    Smith, David P

    2016-01-01

    The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme's active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student.

  14. Evaluation of a digital learning object (DLO) to support the learning process in radiographic dental diagnosis.

    Science.gov (United States)

    Busanello, F H; da Silveira, P F; Liedke, G S; Arús, N A; Vizzotto, M B; Silveira, H E D; Silveira, H L D

    2015-11-01

    Studies have shown that inappropriate therapeutic strategies may be adopted if crown and root changes are misdiagnosed, potentially leading to undesirable consequences. Therefore, the aim of this study was to evaluate a digital learning object, developed to improve skills in diagnosing radiographic dental changes. The object was developed using the Visual Basic Application (VBA) software and evaluated by 62 undergraduate students (male: 24 and female: 38) taking an imaging diagnosis course. Participants were divided in two groups: test group, which used the object and control group, which attended conventional classes. After 3 weeks, students answered a 10-question test and took a practice test to diagnose 20 changes in periapical radiographs. The results show that test group performed better that control group in both tests, with statistically significant difference (P = 0.004 and 0.003, respectively). In overall, female students were better than male students. Specific aspects of object usability were assessed using a structured questionnaire based on the System Usability Scale (SUS), with a score of 90.5 and 81.6 by male and female students, respectively. The results obtained in this study suggest that students who used the DLO performed better than those who used conventional methods. This suggests that the DLO may be a useful teaching tool for dentistry undergraduates, on distance learning courses and as a complementary tool in face-to-face teaching. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  15. The Initial Development of Object Knowledge by a Learning Robot.

    Science.gov (United States)

    Modayil, Joseph; Kuipers, Benjamin

    2008-11-30

    We describe how a robot can develop knowledge of the objects in its environment directly from unsupervised sensorimotor experience. The object knowledge consists of multiple integrated representations: trackers that form spatio-temporal clusters of sensory experience, percepts that represent properties for the tracked objects, classes that support efficient generalization from past experience, and actions that reliably change object percepts. We evaluate how well this intrinsically acquired object knowledge can be used to solve externally specified tasks including object recognition and achieving goals that require both planning and continuous control.

  16. Object learning improves feature extraction but does not improve feature selection.

    Directory of Open Access Journals (Sweden)

    Linus Holm

    Full Text Available A single glance at your crowded desk is enough to locate your favorite cup. But finding an unfamiliar object requires more effort. This superiority in recognition performance for learned objects has at least two possible sources. For familiar objects observers might: 1 select more informative image locations upon which to fixate their eyes, or 2 extract more information from a given eye fixation. To test these possibilities, we had observers localize fragmented objects embedded in dense displays of random contour fragments. Eight participants searched for objects in 600 images while their eye movements were recorded in three daily sessions. Performance improved as subjects trained with the objects: The number of fixations required to find an object decreased by 64% across the 3 sessions. An ideal observer model that included measures of fragment confusability was used to calculate the information available from a single fixation. Comparing human performance to the model suggested that across sessions information extraction at each eye fixation increased markedly, by an amount roughly equal to the extra information that would be extracted following a 100% increase in functional field of view. Selection of fixation locations, on the other hand, did not improve with practice.

  17. The Game Enhanced Learning Model

    DEFF Research Database (Denmark)

    Reng, Lars; Schoenau-Fog, Henrik

    2016-01-01

    will describe the levels of the model, which is based on our experience in teaching professional game development at university level. Furthermore, we have been using the model to inspire numerous educators to improve their students’ motivation and skills. The model presents various game-based learning...... activities, and depicts their required planning and expected outcome through eight levels. At its lower levels, the model contains the possibilities of using stand-alone analogue and digital games as teachers, utilizing games as a facilitator of learning activities, exploiting gamification and motivating......In this paper, we will introduce the Game Enhanced learning Model (GEM), which describes a range of gameoriented learning activities. The model is intended to give an overview of the possibilities of game-based learning in general and all the way up to purposive game productions. In the paper, we...

  18. The Deflector Selector: A machine learning framework for prioritizing hazardous object deflection technology development

    Science.gov (United States)

    Nesvold, E. R.; Greenberg, A.; Erasmus, N.; van Heerden, E.; Galache, J. L.; Dahlstrom, E.; Marchis, F.

    2018-05-01

    Several technologies have been proposed for deflecting a hazardous Solar System object on a trajectory that would otherwise impact the Earth. The effectiveness of each technology depends on several characteristics of the given object, including its orbit and size. The distribution of these parameters in the likely population of Earth-impacting objects can thus determine which of the technologies are most likely to be useful in preventing a collision with the Earth. None of the proposed deflection technologies has been developed and fully tested in space. Developing every proposed technology is currently prohibitively expensive, so determining now which technologies are most likely to be effective would allow us to prioritize a subset of proposed deflection technologies for funding and development. We present a new model, the Deflector Selector, that takes as its input the characteristics of a hazardous object or population of such objects and predicts which technology would be able to perform a successful deflection. The model consists of a machine-learning algorithm trained on data produced by N-body integrations simulating the deflections. We describe the model and present the results of tests of the effectiveness of nuclear explosives, kinetic impactors, and gravity tractors on three simulated populations of hazardous objects.

  19. The Deflector Selector: A Machine Learning Framework for Prioritizing Hazardous Object Deflection Technology Development

    Science.gov (United States)

    Nesvold, Erika; Greenberg, Adam; Erasmus, Nicolas; Van Heerden, Elmarie; Galache, J. L.; Dahlstrom, Eric; Marchis, Franck

    2018-01-01

    Several technologies have been proposed for deflecting a hazardous Solar System object on a trajectory that would otherwise impact the Earth. The effectiveness of each technology depends on several characteristics of the given object, including its orbit and size. The distribution of these parameters in the likely population of Earth-impacting objects can thus determine which of the technologies are most likely to be useful in preventing a collision with the Earth. None of the proposed deflection technologies has been developed and fully tested in space. Developing every proposed technology is currently prohibitively expensive, so determining now which technologies are most likely to be effective would allow us to prioritize a subset of proposed deflection technologies for funding and development. We will present a new model, the Deflector Selector, that takes as its input the characteristics of a hazardous object or population of such objects and predicts which technology would be able to perform a successful deflection. The model consists of a machine-learning algorithm trained on data produced by N-body integrations simulating the deflections. We will describe the model and present the results of tests of the effectiveness of nuclear explosives, kinetic impactors, and gravity tractors on three simulated populations of hazardous objects.

  20. Special issue on multi-objective reinforcement learning

    NARCIS (Netherlands)

    Drugan, Madalina; Wiering, Marco; Vamplew, Peter; Chetty, Madhu

    2017-01-01

    Many real-life problems involve dealing with multiple objectives. For example, in network routing the criteria may consist of energy consumption, latency, and channel capacity, which are in essence conflicting objectives. As in many problems there may be multiple (conflicting) objectives, there

  1. Occlusion detection via structured sparse learning for robust object tracking

    KAUST Repository

    Zhang, Tianzhu; Ghanem, Bernard; Xu, Changsheng; Ahuja, Narendra

    2014-01-01

    occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Extensive experimental results show that our

  2. Object tracking by occlusion detection via structured sparse learning

    KAUST Repository

    Zhang, Tianzhu; Ghanem, Bernard; Xu, Changsheng; Ahuja, Narendra

    2013-01-01

    occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that our tracker

  3. Annihilation model of quasi-stellar objects

    International Nuclear Information System (INIS)

    Alfven, H.

    1979-01-01

    The possibility that annihilation is a major source of energy in cosmic physics is discussed. Since Klein suggested that the Universe might be matter-antimatter symmetric over two decades ago, there have been a significant number of papers developing the consequences of this view. These, however, have been largely ignored in the general literature. There have also been a number of papers claiming to prove that there cannot be antimatter anywhere in the observable Universe. In the first part of this paper an assessment of the differing views is given, and it is shown that none of the arguments against antimatter is convincing. The existence of antimatter is not in conflict with any observational fact. The reason for the negative attitude towards the existence of antimatter seems to be that this view is in conflict with a number of speculative but 'generally accepted' theories. However, recent magnetospheric and heliospheric research, including in situ measurements of cosmic plasmas, is now drastically changing cosmic plasma physics in a way that leads to growing scepticism about quite a few of the speculative theories. An attempt is made to develop a simple phenomenological model of QSOs based on star-antistar collisions. This model can account for such basic observational properties as the acceleration to very large (non-cosmological) velocities, the existence of broad emission lines, and at the same time narrow absorption lines with different redshifts. The absence of blueshifts is also explained. The model predicts that relatively young QSOs should be at cosmological distances whereas the old ones may very well be much closer to us than indicated by their redshift. (Auth.)

  4. CASTOR detector. Model, objectives and simulated performance

    International Nuclear Information System (INIS)

    Angelis, A. L. S.; Mavromanolakis, G.; Panagiotou, A. D.; Aslanoglou, X.; Nicolis, N.; Lobanov, M.; Erine, S.; Kharlov, Y. V.; Bogolyubsky, M. Y.; Kurepin, A. B.; Chileev, K.; Wlodarczyk, Z.

    2001-01-01

    It is presented a phenomenological model describing the formation and evolution of a Centauro fireball in the baryon-rich region in nucleus-nucleus interactions in the upper atmosphere and at the LHC. The small particle multiplicity and imbalance of electromagnetic and hadronic content characterizing a Centauro event and also the strongly penetrating particles (assumed to be strangelets) frequently accompanying them can be naturally explained. It is described the CASTOR calorimeter, a sub detector of the ALICE experiment dedicated to the search for Centauro in the very forward, baryon-rich region of central Pb+Pb collisions at the LHC. The basic characteristics and simulated performance of the calorimeter are presented

  5. PARTICULARITIES OF EDUCATIONAL OBJECTS IN COMPUTER-ASSISTED LEARNING FOR PERSONS WITH DISABILITIES

    Directory of Open Access Journals (Sweden)

    Narcisa ISĂILĂ

    2010-12-01

    Full Text Available The current trend in computer-assisted learning is the creation of reusable learning objects. They can be used independently or can be coupled to make lessons that best fit the users' learning needs. From this perspective, the specific of learning objects for people with disabilities is to ensure accessibility and usability. Using standards in the process of creating learning objects provide flexibility in achieving lessons, thus being helpful for educational content creators (teachers. Metadata have an essential role in achieving interoperability and provide standardized information about the learning objects, allowing the searching, accessing and their finding. The compliance of eLearning standards ensures the compatibility and portability of materials from one system to another, which reduces the time and cost of development.

  6. Object Oriented Learning Objects in Online Education: A Framework and Example.

    Science.gov (United States)

    Rincon, Lilian; Parker, Drew

    Online learning is coming of age in both postsecondary education and industry. The courses now offered online range from kinesiology to mathematics to complete M.B.A. programs. The growing popularity of online education has created a need to reduce costs without diminishing the value of the edification. In response to this need, an instructional…

  7. Digital learning object for diagnostic reasoning in nursing applied to the integumentary system

    Directory of Open Access Journals (Sweden)

    Cecília Passos Vaz da Costa

    Full Text Available Objective: To describe the creation of a digital learning object for diagnostic reasoning in nursing applied to the integumentary system at a public university of Piaui. Method: A methodological study applied to technological production based on the pedagogical framework of problem-based learning. The methodology for creating the learning object observed the stages of analysis, design, development, implementation and evaluation recommended for contextualized instructional design. The revised taxonomy of Bloom was used to list the educational goals. Results: The four modules of the developed learning object were inserted into the educational platform Moodle. The theoretical assumptions allowed the design of an important online resource that promotes effective learning in the scope of nursing education. Conclusion: This study should add value to nursing teaching practices through the use of digital learning objects for teaching diagnostic reasoning applied to skin and skin appendages.

  8. Model-based machine learning.

    Science.gov (United States)

    Bishop, Christopher M

    2013-02-13

    Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

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

    Science.gov (United States)

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

    2016-09-15

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

  10. Active Prior Tactile Knowledge Transfer for Learning Tactual Properties of New Objects

    Directory of Open Access Journals (Sweden)

    Di Feng

    2018-02-01

    Full Text Available Reusing the tactile knowledge of some previously-explored objects (prior objects helps us to easily recognize the tactual properties of new objects. In this paper, we enable a robotic arm equipped with multi-modal artificial skin, like humans, to actively transfer the prior tactile exploratory action experiences when it learns the detailed physical properties of new objects. These experiences, or prior tactile knowledge, are built by the feature observations that the robot perceives from multiple sensory modalities, when it applies the pressing, sliding, and static contact movements on objects with different action parameters. We call our method Active Prior Tactile Knowledge Transfer (APTKT, and systematically evaluated its performance by several experiments. Results show that the robot improved the discrimination accuracy by around 10 % when it used only one training sample with the feature observations of prior objects. By further incorporating the predictions from the observation models of prior objects as auxiliary features, our method improved the discrimination accuracy by over 20 % . The results also show that the proposed method is robust against transferring irrelevant prior tactile knowledge (negative knowledge transfer.

  11. Balance between calibration objectives in a conceptual hydrological model

    NARCIS (Netherlands)

    Booij, Martijn J.; Krol, Martinus S.

    2010-01-01

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

  12. LEARNING CREATIVE WRITING MODEL BASED ON NEUROLINGUISTIC PROGRAMMING

    OpenAIRE

    Rustan, Edhy

    2017-01-01

    The objectives of the study are to determine: (1) condition on learning creative writing at high school students in Makassar, (2) requirement of learning model in creative writing, (3) program planning and design model in ideal creative writing, (4) feasibility of model study based on creative writing in neurolinguistic programming, and (5) the effectiveness of the learning model based on creative writing in neurolinguisticprogramming.The method of this research uses research development of L...

  13. Field Model: An Object-Oriented Data Model for Fields

    Science.gov (United States)

    Moran, Patrick J.

    2001-01-01

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

  14. Conceptual Modeling of Events as Information Objects and Change Agents

    DEFF Research Database (Denmark)

    Bækgaard, Lars

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

  15. Refitting existing simulations to meet with new learning objectives

    DEFF Research Database (Denmark)

    Lainema, Timo; Henriksen, Thomas Duus; Saarinen, Eeli

    2012-01-01

    This paper discusses the application possibilities of business simulation games in teaching. By application possibilities we mean the different ways of arranging the learning sessions using the one and same simulation game. Thus, we are not discussing what kind of games should be built for certain...

  16. A critique of Stephen Downes' article, "Learning Objects" -- A perspective from Bahrain

    Directory of Open Access Journals (Sweden)

    Muain H. Jamlan

    2001-07-01

    Full Text Available With the availability of technology, hardware, and software, learning objects become fundamental to the learning process and change the way in which learning materials are designed. The vast development of technology forces both teacher and learner to modify their roles. Teachers become facilitators, while learners became active and responsible for selecting modes and styles of learning. Assuming this attitude of implementing technology in the learning process and seeking new methods of facilitating learning, universities and colleges have to adopt new techniques. One of these new techniques is the use of learning objects. Although learning objects are considered products of technology developed in the USA, Japan, and European countries, universities in the Middle East have been influenced by this development. While there are differences in the quantity and quality of these technologies available in many Middle East countries, computer applications, especially those that deploy the Internet, have now become available. Educational authorities in Middle East countries are now turning to the availability of learning objects. Let me clarify some of the issues Downes discusses in his article on learning objects, Vol. 2, No. 1 of the International Review of Research in Open and Distance Learning.

  17. Memory for Object Locations: Priority Effect and Sex Differences in Associative Spatial Learning

    Science.gov (United States)

    Cinan, Sevtap; Atalay, Deniz; Sisman, Simge; Basbug, Gokce; Dervent-Ozbek, Sevinc; Teoman, Dalga D.; Karagoz, Ayca; Karadeniz, A. Yezdan; Beykurt, Sinem; Suleyman, Hediye; Memis, H. Ozge; Yurtsever, Ozgur D.

    2007-01-01

    This paper reports two experiments conducted to examine priority effects and sex differences in object location memory. A new task of paired position-learning was designed, based on the A-B A-C paradigm, which was used in paired word learning. There were three different paired position-learning conditions: (1) positions of several different…

  18. The role of professional objects in technology-enhanced learning environments in higher education

    NARCIS (Netherlands)

    Zitter, I.I.; Bruijn, E. de; Simons, P.R.J.; Cate, Th.J. ten

    2010-01-01

    We study project-based, technology-enhanced learning environments in higher education, which should produce, by means of specific mechanisms, learning outcomes in terms of transferable knowledge and learning-, thinking-, collaboration- and regulation-skills. Our focus is on the role of objects from

  19. Holistic Approach to Learning and Teaching Introductory Object-Oriented Programming

    Science.gov (United States)

    Thota, Neena; Whitfield, Richard

    2010-01-01

    This article describes a holistic approach to designing an introductory, object-oriented programming course. The design is grounded in constructivism and pedagogy of phenomenography. We use constructive alignment as the framework to align assessments, learning, and teaching with planned learning outcomes. We plan learning and teaching activities,…

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

    Science.gov (United States)

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

    2015-12-01

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

  1. ATTITUDES OF STUDENTS TOWARDS LEARNING OBJECTS IN WEB-BASED LANGUAGE LEARNING

    Directory of Open Access Journals (Sweden)

    Ahmet BASAL

    2012-01-01

    Full Text Available Language education is important in the rapidly changing world. Every year much effort has spent on preparing teaching materials for language education. Since positive attitudes of learners towards a teaching material enhance the effectiveness of that material, it is important to determine the attitudes of learners towards the material used. Learning objects (LOs are a new type of material on which many studies have been conducted in recent years. The aim of this study is to determine the attitudes of students towards LOs in web-based language learning. To this end, the study was conducted in English I Course at the Department of Computer Programming in Kırıkkale University in 2010-2011 Fall Semester. Seventy LOs appropriate for six-week long lecture program were integrated into the Learning Management System (LMS of Kırıkkale University. The study group consisted of 38 students. After the six weeks long implementation period of the study, an attitude scale was administered to the students. The findings indicated that students in web based language education have positive attitudes towards LOs.

  2. INST7150 - Advanced Topics in Learning Object Design and Reuse, Fall 2005

    OpenAIRE

    Wiley, David

    2005-01-01

    This course is designed to help you understand and apply advanced topics in the design, creation, and reuse of learning objects. The course is structured around a practical, hands-on project using learning objects, intermingled with readings and discussion on a variety of topics.

  3. Cortical Dynamics of Contextually Cued Attentive Visual Learning and Search: Spatial and Object Evidence Accumulation

    Science.gov (United States)

    Huang, Tsung-Ren; Grossberg, Stephen

    2010-01-01

    How do humans use target-predictive contextual information to facilitate visual search? How are consistently paired scenic objects and positions learned and used to more efficiently guide search in familiar scenes? For example, humans can learn that a certain combination of objects may define a context for a kitchen and trigger a more efficient…

  4. The Sloan-C Pillars and Boundary Objects As a Framework for Evaluating Blended Learning

    Science.gov (United States)

    Laumakis, Mark; Graham, Charles; Dziuban, Chuck

    2009-01-01

    The authors contend that blended learning represents a boundary object; a construct that brings together constituencies from a variety of backgrounds with each of these cohorts defining the object somewhat differently. The Sloan-C Pillars (learning effectiveness, access, cost effectiveness, student satisfaction, and faculty satisfaction) provide…

  5. APA's Learning Objectives for Research Methods and Statistics in Practice: A Multimethod Analysis

    Science.gov (United States)

    Tomcho, Thomas J.; Rice, Diana; Foels, Rob; Folmsbee, Leah; Vladescu, Jason; Lissman, Rachel; Matulewicz, Ryan; Bopp, Kara

    2009-01-01

    Research methods and statistics courses constitute a core undergraduate psychology requirement. We analyzed course syllabi and faculty self-reported coverage of both research methods and statistics course learning objectives to assess the concordance with APA's learning objectives (American Psychological Association, 2007). We obtained a sample of…

  6. An Assistant for Loading Learning Object Metadata: An Ontology Based Approach

    Science.gov (United States)

    Casali, Ana; Deco, Claudia; Romano, Agustín; Tomé, Guillermo

    2013-01-01

    In the last years, the development of different Repositories of Learning Objects has been increased. Users can retrieve these resources for reuse and personalization through searches in web repositories. The importance of high quality metadata is key for a successful retrieval. Learning Objects are described with metadata usually in the standard…

  7. Teaching and Assessing Ethics as a Learning Objective: One School's Journey

    Science.gov (United States)

    Templin, Carl R.; Christensen, David

    2009-01-01

    This paper reports the results of a ten-year effort to establish ethics as a learning objective for all business students, to assess the effectiveness in achieving that learning objective and to incorporate ethical conduct as a part of the school's organizational culture. First, it addresses the importance of ethics instruction for all business…

  8. Learning to Model in Engineering

    Science.gov (United States)

    Gainsburg, Julie

    2013-01-01

    Policymakers and education scholars recommend incorporating mathematical modeling into mathematics education. Limited implementation of modeling instruction in schools, however, has constrained research on how students learn to model, leaving unresolved debates about whether modeling should be reified and explicitly taught as a competence, whether…

  9. [Digital learning object for diagnostic reasoning in nursing applied to the integumentary system].

    Science.gov (United States)

    da Costa, Cecília Passos Vaz; Luz, Maria Helena Barros Araújo

    2015-12-01

    To describe the creation of a digital learning object for diagnostic reasoning in nursing applied to the integumentary system at a public university of Piaui. A methodological study applied to technological production based on the pedagogical framework of problem-based learning. The methodology for creating the learning object observed the stages of analysis, design, development, implementation and evaluation recommended for contextualized instructional design. The revised taxonomy of Bloom was used to list the educational goals. The four modules of the developed learning object were inserted into the educational platform Moodle. The theoretical assumptions allowed the design of an important online resource that promotes effective learning in the scope of nursing education. This study should add value to nursing teaching practices through the use of digital learning objects for teaching diagnostic reasoning applied to skin and skin appendages.

  10. Definition of a Learning Object from Perspectives of In-Service Teachers (Case of Duzce Province

    Directory of Open Access Journals (Sweden)

    Kürşat ARSLAN

    2016-08-01

    Full Text Available Learning objects, as a relatively new technological concept, have drawn much attention from educators because these dijital resources are easily accessible, relatively easy to use due to their limited size and focus, interactive, and adaptable to many different educational contexts. Despite the fact that learning objects have the great potential to improve teaching and learning experiences by providing teachers reusable learning materials and reducing costs, the lack of a “working and clear” definition of these materials has restricted their effective and efficient use. This study aimed to explore elementary school teacher perceptions of their use of learning objects from a qualitative research paradigm in order to reveal the extent to which teachers understand concept of learning object and its instruction approach. The method of the study was based on descriptive phenomenology. Data were collected using multiple methods, including the semi-structured interview, field observation reports, and photos from nine in-service elementary school teachers from different departments in Duzce, Turkey. Methods of data analysis were based on Giorgi’s method of descriptive phenomenology including four stages of content analysis: data coding, developing themes, organizing code and themes, describing findings. Overall findings of the study indicate that teachers use learning objects in their lesson activities without explicit recognition; however they generally fail to understand the exact meaning of a learning object approach and its applications in the classroom. Participants understood different properties of learning objects. Almost all participants perceive objectivity as the most important characteristic of the learning object.  In addition, a majority of the teachers recognized the value of a learning object’s reusability. In-service teachers’ vague perceptions of the definition and usage of learning objects indicated that they used these

  11. Possibility of object recognition using Altera's model based design approach

    International Nuclear Information System (INIS)

    Tickle, A J; Harvey, P K; Smith, J S; Wu, F

    2009-01-01

    Object recognition is an image processing task of finding a given object in a selected image or video sequence. Object recognition can be divided into two areas: one of these is decision-theoretic and deals with patterns described by quantitative descriptors, for example such as length, area, shape and texture. With this Graphical User Interface Circuitry (GUIC) methodology employed here being relatively new for object recognition systems, the aim of this work is to identify if the developed circuitry can detect certain shapes or strings within the target image. A much smaller reference image feeds the preset data for identification, tests are conducted for both binary and greyscale and the additional mathematical morphology to highlight the area within the target image with the object(s) are located is also presented. This then provides proof that basic recognition methods are valid and would allow the progression to developing decision-theoretical and learning based approaches using GUICs for use in multidisciplinary tasks.

  12. Objectivity

    CERN Document Server

    Daston, Lorraine

    2010-01-01

    Objectivity has a history, and it is full of surprises. In Objectivity, Lorraine Daston and Peter Galison chart the emergence of objectivity in the mid-nineteenth-century sciences--and show how the concept differs from its alternatives, truth-to-nature and trained judgment. This is a story of lofty epistemic ideals fused with workaday practices in the making of scientific images. From the eighteenth through the early twenty-first centuries, the images that reveal the deepest commitments of the empirical sciences--from anatomy to crystallography--are those featured in scientific atlases, the compendia that teach practitioners what is worth looking at and how to look at it. Galison and Daston use atlas images to uncover a hidden history of scientific objectivity and its rivals. Whether an atlas maker idealizes an image to capture the essentials in the name of truth-to-nature or refuses to erase even the most incidental detail in the name of objectivity or highlights patterns in the name of trained judgment is a...

  13. Abstraction ability as an indicator of success for learning object-oriented programming?

    DEFF Research Database (Denmark)

    Bennedsen, Jens Benned; Caspersen, Michael Edelgaard

    2006-01-01

    ability is operationalized as stages of cognitive development (for which validated tests exist). Programming ability is operationalized as grade in the final assessment of a model-based objects-first CS1. The validity of the operationalizations is discussed. Surprisingly, our study shows......Computer science educators generally agree that abstract thinking is a crucial component for learning computer science in general and programming in particular. We report on a study to confirm the hypothesis that general abstraction ability has a positive impact on programming ability. Abstraction...... that there is no correlation between stage of cognitive development (abstraction ability) and final grade in CS1 (programming ability). Possible explanations are identified....

  14. Using IMS Learning Design to model collaborative learning activities

    NARCIS (Netherlands)

    Tattersall, Colin

    2006-01-01

    IMS Learning Design provides a counter to the trend towards designing for lone-learners reading from screens. It guides staff and educational developers to start not with content, but with learning activities and the achievement of learning objectives. It recognises that learning can happen without

  15. The company objects keep: Linking referents together during cross-situational word learning.

    Science.gov (United States)

    Zettersten, Martin; Wojcik, Erica; Benitez, Viridiana L; Saffran, Jenny

    2018-04-01

    Learning the meanings of words involves not only linking individual words to referents but also building a network of connections among entities in the world, concepts, and words. Previous studies reveal that infants and adults track the statistical co-occurrence of labels and objects across multiple ambiguous training instances to learn words. However, it is less clear whether, given distributional or attentional cues, learners also encode associations amongst the novel objects. We investigated the consequences of two types of cues that highlighted object-object links in a cross-situational word learning task: distributional structure - how frequently the referents of novel words occurred together - and visual context - whether the referents were seen on matching backgrounds. Across three experiments, we found that in addition to learning novel words, adults formed connections between frequently co-occurring objects. These findings indicate that learners exploit statistical regularities to form multiple types of associations during word learning.

  16. Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

    Science.gov (United States)

    Xue, Ming; Yang, Hua; Zheng, Shibao; Zhou, Yi; Yu, Zhenghua

    2014-01-01

    To tackle robust object tracking for video sensor-based applications, an online discriminative algorithm based on incremental discriminative structured dictionary learning (IDSDL-VT) is presented. In our framework, a discriminative dictionary combining both positive, negative and trivial patches is designed to sparsely represent the overlapped target patches. Then, a local update (LU) strategy is proposed for sparse coefficient learning. To formulate the training and classification process, a multiple linear classifier group based on a K-combined voting (KCV) function is proposed. As the dictionary evolves, the models are also trained to timely adapt the target appearance variation. Qualitative and quantitative evaluations on challenging image sequences compared with state-of-the-art algorithms demonstrate that the proposed tracking algorithm achieves a more favorable performance. We also illustrate its relay application in visual sensor networks. PMID:24549252

  17. Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

    Directory of Open Access Journals (Sweden)

    Ming Xue

    2014-02-01

    Full Text Available To tackle robust object tracking for video sensor-based applications, an online discriminative algorithm based on incremental discriminative structured dictionary learning (IDSDL-VT is presented. In our framework, a discriminative dictionary combining both positive, negative and trivial patches is designed to sparsely represent the overlapped target patches. Then, a local update (LU strategy is proposed for sparse coefficient learning. To formulate the training and classification process, a multiple linear classifier group based on a K-combined voting (KCV function is proposed. As the dictionary evolves, the models are also trained to timely adapt the target appearance variation. Qualitative and quantitative evaluations on challenging image sequences compared with state-of-the-art algorithms demonstrate that the proposed tracking algorithm achieves a more favorable performance. We also illustrate its relay application in visual sensor networks.

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

    Directory of Open Access Journals (Sweden)

    Jui-Yuan Su

    2015-04-01

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

  19. e-Learning objects in the cloud: SCORM compliance, creation and deployment options

    Directory of Open Access Journals (Sweden)

    Stephanie Day

    2017-12-01

    Full Text Available In the field of education, cloud computing is changing the way learning is delivered and experienced, by providing software, storage, teaching resources, artefacts, and knowledge that can be shared by educators on a global scale. In this paper, the first objective is to understand the general trends in educational use of the cloud, particularly the provision of large scale education opportunities, use of open and free services, and interoperability of learning objects. A review of current literature reveals the opportunities and issues around managing learning and teaching related knowledge in the cloud. The educational use of the cloud will continue to grow as the services, pedagogies, personalization, and standardization of learning are refined and adopted. Secondly, the paper presents an example of how the cloud can support learning opportunities using SCORM interoperable learning objects. The case study findings show that, while the use of SCORM enables a variety of trackable learning opportunities, the constraints of maintaining the currency of the learning also need to be considered. It is recommended that the SCORM content are combined with cloud based student activities. These learning objects can be used to support alternative learning opportunities within blended and online learning environments.

  20. Deep Learning for Detection of Object-Based Forgery in Advanced Video

    Directory of Open Access Journals (Sweden)

    Ye Yao

    2017-12-01

    Full Text Available Passive video forensics has drawn much attention in recent years. However, research on detection of object-based forgery, especially for forged video encoded with advanced codec frameworks, is still a great challenge. In this paper, we propose a deep learning-based approach to detect object-based forgery in the advanced video. The presented deep learning approach utilizes a convolutional neural network (CNN to automatically extract high-dimension features from the input image patches. Different from the traditional CNN models used in computer vision domain, we let video frames go through three preprocessing layers before being fed into our CNN model. They include a frame absolute difference layer to cut down temporal redundancy between video frames, a max pooling layer to reduce computational complexity of image convolution, and a high-pass filter layer to enhance the residual signal left by video forgery. In addition, an asymmetric data augmentation strategy has been established to get a similar number of positive and negative image patches before the training. The experiments have demonstrated that the proposed CNN-based model with the preprocessing layers has achieved excellent results.

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

    Directory of Open Access Journals (Sweden)

    Akihiro eEguchi

    2015-08-01

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

  2. Exploring emerging learning needs: a UK-wide consultation on environmental sustainability learning objectives for medical education.

    Science.gov (United States)

    Walpole, Sarah C; Mortimer, Frances; Inman, Alice; Braithwaite, Isobel; Thompson, Trevor

    2015-12-24

    This study aimed to engage wide-ranging stakeholders and develop consensus learning objectives for undergraduate and postgraduate medical education. A UK-wide consultation garnered opinions of healthcare students, healthcare educators and other key stakeholders about environmental sustainability in medical education. The policy Delphi approach informed this study. Draft learning objectives were revised iteratively during three rounds of consultation: online questionnaire or telephone interview, face-to-face seminar and email consultation. Twelve draft learning objectives were developed based on review of relevant literature. In round one, 64 participants' median ratings of the learning objectives were 3.5 for relevance and 3.0 for feasibility on a Likert scale of one to four. Revisions were proposed, e.g. to highlight relevance to public health and professionalism. Thirty three participants attended round two. Conflicting opinions were explored. Added content areas included health benefits of sustainable behaviours. To enhance usability, restructuring provided three overarching learning objectives, each with subsidiary points. All participants from rounds one and two were contacted in round three, and no further edits were required. This is the first attempt to define consensus learning objectives for medical students about environmental sustainability. Allowing a wide range of stakeholders to comment on multiple iterations of the document stimulated their engagement with the issues raised and ownership of the resulting learning objectives.

  3. Сontrol systems using mathematical models of technological objects ...

    African Journals Online (AJOL)

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

  4. Application of Multi-Objective Human Learning Optimization Method to Solve AC/DC Multi-Objective Optimal Power Flow Problem

    Science.gov (United States)

    Cao, Jia; Yan, Zheng; He, Guangyu

    2016-06-01

    This paper introduces an efficient algorithm, multi-objective human learning optimization method (MOHLO), to solve AC/DC multi-objective optimal power flow problem (MOPF). Firstly, the model of AC/DC MOPF including wind farms is constructed, where includes three objective functions, operating cost, power loss, and pollutant emission. Combining the non-dominated sorting technique and the crowding distance index, the MOHLO method can be derived, which involves individual learning operator, social learning operator, random exploration learning operator and adaptive strategies. Both the proposed MOHLO method and non-dominated sorting genetic algorithm II (NSGAII) are tested on an improved IEEE 30-bus AC/DC hybrid system. Simulation results show that MOHLO method has excellent search efficiency and the powerful ability of searching optimal. Above all, MOHLO method can obtain more complete pareto front than that by NSGAII method. However, how to choose the optimal solution from pareto front depends mainly on the decision makers who stand from the economic point of view or from the energy saving and emission reduction point of view.

  5. Oscillating shells: A model for a variable cosmic object

    OpenAIRE

    Nunez, Dario

    1997-01-01

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

  6. Apricot - An Object-Oriented Modeling Language for Hybrid Systems

    OpenAIRE

    Fang, Huixing; Zhu, Huibiao; Shi, Jianqi

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Edmund T eRolls

    2012-06-01

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

  8. Digital learning objects in nursing consultation: technology assessment by undergraduate students.

    Science.gov (United States)

    Silveira, DeniseTolfo; Catalan, Vanessa Menezes; Neutzling, Agnes Ludwig; Martinato, Luísa Helena Machado

    2010-01-01

    This study followed the teaching-learning process about the nursing consultation, based on digital learning objects developed through the active Problem Based Learning method. The goals were to evaluate the digital learning objects about nursing consultation, develop cognitive skills on the subject using problem based learning and identify the students' opinions on the use of technology. This is an exploratory and descriptive study with a quantitative approach. The sample consisted of 71 students in the sixth period of the nursing program at the Federal University of Rio Grande do Sul. The data was collected through a questionnaire to evaluate the learning objects. The results showed positive agreement (58%) on the content, usability and didactics of the proposed computer-mediated activity regarding the nursing consultation. The application of materials to the students is considered positive.

  9. AN ANALYSIS ON USAGE PREFERENCES OF LEARNING OBJECTS AND LEARNING OBJECT REPOSITORIES AMONG PRE-SERVICE TEACHERS

    Directory of Open Access Journals (Sweden)

    Amirul ISLAM

    2014-04-01

    Full Text Available This study draws on the experience of a cohort of 22 students from 09 tutorial centers enrolled in a Master of Education (M Ed distance learning program administered by the Bangladesh Open University (BOU. It's purpose is to locate the aims and philosophies of distance learning within the experiences of actual distance learners in order to see if learners' needs were being met by the program and to obtain a fuller understanding of core aspects of distance education. The study found that students were, on the whole, satisfied with the course materials, the choice of modules, assignment feedback, and length of time given to complete the assignments, but significant problems surfaced regarding issues of student support, and access to and provision of resource materials. Arguably, these are issues intrinsic to the successful provision of distance learning courses, and the results both concord with aspects of the research literature (Burge & Howard, 1990; Chen, 1997; Hyland, 2001; Morgan, 1995; Robinson, 1995; Simpson, 2000; Tait, 2000 and raise some interesting questions regarding the provision of distance education and its ability to meet the needs of learners

  10. An object-oriented approach to energy-economic modeling

    Energy Technology Data Exchange (ETDEWEB)

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

    1993-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Smith Nicholas

    2012-12-01

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

  12. The development of learning material using learning cycle 5E model based stem to improve students’ learning outcomes in Thermochemistry

    Science.gov (United States)

    sugiarti, A. C.; suyatno, S.; Sanjaya, I. G. M.

    2018-04-01

    The objective of this study is describing the feasibility of Learning Cycle 5E STEM (Science, Technology, Engineering, and Mathematics) based learning material which is appropriate to improve students’ learning achievement in Thermochemistry. The study design used 4-D models and one group pretest-posttest design to obtain the information about the improvement of sudents’ learning outcomes. The subject was learning cycle 5E based STEM learning materials which the data were collected from 30 students of Science class at 11th Grade. The techniques used in this study were validation, observation, test, and questionnaire. Some result attain: (1) all the learning materials contents were valid, (2) the practicality and the effectiveness of all the learning materials contents were classified as good. The conclution of this study based on those three condition, the Learnig Cycle 5E based STEM learning materials is appropriate to improve students’ learning outcomes in studying Thermochemistry.

  13. Tracking Multiple Statistics: Simultaneous Learning of Object Names and Categories in English and Mandarin Speakers.

    Science.gov (United States)

    Chen, Chi-Hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen

    2017-08-01

    Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories based on the commonalities across training stimuli. Experiment 2 replicated the first experiment and further examined whether speakers of Mandarin, a language in which final syllables of object names are more predictive of category membership than English, were able to learn words and form object categories when trained with the same type of structures. The results indicate that both groups of learners successfully extracted multiple levels of co-occurrence and used them to learn words and object categories simultaneously. However, marked individual differences in performance were also found, suggesting possible interference and competition in processing the two concurrent streams of regularities. Copyright © 2016 Cognitive Science Society, Inc.

  14. Effect of tDCS on task relevant and irrelevant perceptual learning of complex objects.

    Science.gov (United States)

    Van Meel, Chayenne; Daniels, Nicky; de Beeck, Hans Op; Baeck, Annelies

    2016-01-01

    During perceptual learning the visual representations in the brain are altered, but these changes' causal role has not yet been fully characterized. We used transcranial direct current stimulation (tDCS) to investigate the role of higher visual regions in lateral occipital cortex (LO) in perceptual learning with complex objects. We also investigated whether object learning is dependent on the relevance of the objects for the learning task. Participants were trained in two tasks: object recognition using a backward masking paradigm and an orientation judgment task. During both tasks, an object with a red line on top of it were presented in each trial. The crucial difference between both tasks was the relevance of the object: the object was relevant for the object recognition task, but not for the orientation judgment task. During training, half of the participants received anodal tDCS stimulation targeted at the lateral occipital cortex (LO). Afterwards, participants were tested on how well they recognized the trained objects, the irrelevant objects presented during the orientation judgment task and a set of completely new objects. Participants stimulated with tDCS during training showed larger improvements of performance compared to participants in the sham condition. No learning effect was found for the objects presented during the orientation judgment task. To conclude, this study suggests a causal role of LO in relevant object learning, but given the rather low spatial resolution of tDCS, more research on the specificity of this effect is needed. Further, mere exposure is not sufficient to train object recognition in our paradigm.

  15. Rapid Object Detection Systems, Utilising Deep Learning and Unmanned Aerial Systems (uas) for Civil Engineering Applications

    Science.gov (United States)

    Griffiths, D.; Boehm, J.

    2018-05-01

    With deep learning approaches now out-performing traditional image processing techniques for image understanding, this paper accesses the potential of rapid generation of Convolutional Neural Networks (CNNs) for applied engineering purposes. Three CNNs are trained on 275 UAS-derived and freely available online images for object detection of 3m2 segments of railway track. These includes two models based on the Faster RCNN object detection algorithm (Resnet and Incpetion-Resnet) as well as the novel onestage Focal Loss network architecture (Retinanet). Model performance was assessed with respect to three accuracy metrics. The first two consisted of Intersection over Union (IoU) with thresholds 0.5 and 0.1. The last assesses accuracy based on the proportion of track covered by object detection proposals against total track length. In under six hours of training (and two hours of manual labelling) the models detected 91.3 %, 83.1 % and 75.6 % of track in the 500 test images acquired from the UAS survey Retinanet, Resnet and Inception-Resnet respectively. We then discuss the potential for such applications of such systems within the engineering field for a range of scenarios.

  16. Application of object modeling technique to medical image retrieval system

    International Nuclear Information System (INIS)

    Teshima, Fumiaki; Abe, Takeshi

    1993-01-01

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

  17. A Bayesian alternative for multi-objective ecohydrological model specification

    Science.gov (United States)

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

    2018-01-01

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

  18. Design Guide for Earth System Science Education: Common Student Learning Objectives and Special Pedagogical Approaches

    Science.gov (United States)

    Baker, D.

    2006-12-01

    As part of the NASA-supported undergraduate Earth System Science Education (ESSE) program, fifty-seven institutions have developed and implemented a wide range of Earth system science (ESS) courses, pedagogies, and evaluation tools. The Teaching, Learning, and Evaluation section of USRA's online ESSE Design Guide showcases these ESS learning environments. This Design Guide section also provides resources for faculty who wish to develop ESS courses. It addresses important course design issues including prior student knowledge and interests, student learning objectives, learning resources, pedagogical approaches, and assessments tied to student learning objectives. The ESSE Design Guide provides links to over 130 ESS course syllabi at introductory, senior, and graduate levels. ESS courses over the past 15 years exhibit common student learning objectives and unique pedagogical approaches. From analysis of ESS course syllabi, seven common student learning objectives emerged: 1) demonstrate systems thinking, 2) develop an ESS knowledge base, 3) apply ESS to the human dimension, 4) expand and apply analytical skills, 5) improve critical thinking skills, 6) build professional/career skills, and 7) acquire an enjoyment and appreciation for science. To meet these objectives, ESSE often requires different ways of teaching than in traditional scientific disciplines. This presentation will highlight some especially successful pedagogical approaches for creating positive and engaging ESS learning environments.

  19. Active Learning for Player Modeling

    DEFF Research Database (Denmark)

    Shaker, Noor; Abou-Zleikha, Mohamed; Shaker, Mohammad

    2015-01-01

    Learning models of player behavior has been the focus of several studies. This work is motivated by better understanding of player behavior, a knowledge that can ultimately be employed to provide player-adapted or personalized content. In this paper, we propose the use of active learning for player...... experience modeling. We use a dataset from hundreds of players playing Infinite Mario Bros. as a case study and we employ the random forest method to learn mod- els of player experience through the active learning approach. The results obtained suggest that only part of the dataset (up to half the size...... that the method can be used online during the content generation process where the mod- els can improve and better content can be presented as the game is being played....

  20. Different Modes of Digital Learning Object Use in School Settings: Do We Design for Individual or Collaborative Learning?

    Science.gov (United States)

    Akpinar, Yavuz

    2014-01-01

    The aim of the studies reported in this paper is to gain classroom based empirical evidence on the learning effectiveness of learning objects used in two types of study settings: Collaborative and individual. A total of 127 seventh and ninth grade students participated in the experiments. They were assigned into one of the study modes and worked…

  1. How does the brain rapidly learn and reorganize view-invariant and position-invariant object representations in the inferotemporal cortex?

    Science.gov (United States)

    Cao, Yongqiang; Grossberg, Stephen; Markowitz, Jeffrey

    2011-12-01

    All primates depend for their survival on being able to rapidly learn about and recognize objects. Objects may be visually detected at multiple positions, sizes, and viewpoints. How does the brain rapidly learn and recognize objects while scanning a scene with eye movements, without causing a combinatorial explosion in the number of cells that are needed? How does the brain avoid the problem of erroneously classifying parts of different objects together at the same or different positions in a visual scene? In monkeys and humans, a key area for such invariant object category learning and recognition is the inferotemporal cortex (IT). A neural model is proposed to explain how spatial and object attention coordinate the ability of IT to learn invariant category representations of objects that are seen at multiple positions, sizes, and viewpoints. The model clarifies how interactions within a hierarchy of processing stages in the visual brain accomplish this. These stages include the retina, lateral geniculate nucleus, and cortical areas V1, V2, V4, and IT in the brain's What cortical stream, as they interact with spatial attention processes within the parietal cortex of the Where cortical stream. The model builds upon the ARTSCAN model, which proposed how view-invariant object representations are generated. The positional ARTSCAN (pARTSCAN) model proposes how the following additional processes in the What cortical processing stream also enable position-invariant object representations to be learned: IT cells with persistent activity, and a combination of normalizing object category competition and a view-to-object learning law which together ensure that unambiguous views have a larger effect on object recognition than ambiguous views. The model explains how such invariant learning can be fooled when monkeys, or other primates, are presented with an object that is swapped with another object during eye movements to foveate the original object. The swapping procedure is

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

    Science.gov (United States)

    Sundstrøm, Martin

    2011-07-01

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

  3. Early age-dependent impairments of context-dependent extinction learning, object recognition, and object-place learning occur in rats.

    Science.gov (United States)

    Wiescholleck, Valentina; Emma André, Marion Agnès; Manahan-Vaughan, Denise

    2014-03-01

    The hippocampus is vulnerable to age-dependent memory decline. Multiple forms of memory depend on adequate hippocampal function. Extinction learning comprises active inhibition of no longer relevant learned information concurrent with suppression of a previously learned reaction. It is highly dependent on context, and evidence exists that it requires hippocampal activation. In this study, we addressed whether context-based extinction as well as hippocampus-dependent tasks, such as object recognition and object-place recognition, are equally affected by moderate aging. Young (7-8 week old) and older (7-8 month old) Wistar rats were used. For the extinction study, animals learned that a particular floor context indicated that they should turn into one specific arm (e.g., left) to receive a food reward. On the day after reaching the learning criterion of 80% correct choices, the floor context was changed, no reward was given and animals were expected to extinguish the learned response. Both, young and older rats managed this first extinction trial in the new context with older rats showing a faster extinction performance. One day later, animals were returned to the T-maze with the original floor context and renewal effects were assessed. In this case, only young but not older rats showed the expected renewal effect (lower extinction ratio as compared to the day before). To assess general memory abilities, animals were tested in the standard object recognition and object-place memory tasks. Evaluations were made at 5 min, 1 h and 7 day intervals. Object recognition memory was poor at short-term and intermediate time-points in older but not young rats. Object-place memory performance was unaffected at 5 min, but impaired at 1 h in older but not young rats. Both groups were impaired at 7 days. These findings support that not only aspects of general memory, but also context-dependent extinction learning, are affected by moderate aging. This may reflect less flexibility in

  4. Object Recognition in Clutter: Cortical Responses Depend on the Type of Learning

    Directory of Open Access Journals (Sweden)

    Jay eHegdé

    2012-06-01

    Full Text Available Theoretical studies suggest that the visual system uses prior knowledge of visual objects to recognize them in visual clutter, and posit that the strategies for recognizing objects in clutter may differ depending on whether or not the object was learned in clutter to begin with. We tested this hypothesis using functional magnetic resonance imaging (fMRI of human subjects. We trained subjects to recognize naturalistic, yet novel objects in strong or weak clutter. We then tested subjects’ recognition performance for both sets of objects in strong clutter. We found many brain regions that were differentially responsive to objects during object recognition depending on whether they were learned in strong or weak clutter. In particular, the responses of the left fusiform gyrus reliably reflected, on a trial-to-trial basis, subjects’ object recognition performance for objects learned in the presence of strong clutter. These results indicate that the visual system does not use a single, general-purpose mechanism to cope with clutter. Instead, there are two distinct spatial patterns of activation whose responses are attributable not to the visual context in which the objects were seen, but to the context in which the objects were learned.

  5. A Visual Detection Learning Model

    Science.gov (United States)

    Beard, Bettina L.; Ahumada, Albert J., Jr.; Trejo, Leonard (Technical Monitor)

    1998-01-01

    Our learning model has memory templates representing the target-plus-noise and noise-alone stimulus sets. The best correlating template determines the response. The correlations and the feedback participate in the additive template updating rule. The model can predict the relative thresholds for detection in random, fixed and twin noise.

  6. Sound Synthesis of Objects Swinging through Air Using Physical Models

    Directory of Open Access Journals (Sweden)

    Rod Selfridge

    2017-11-01

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

  7. On the effect of model parameters on forecast objects

    Science.gov (United States)

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

    2018-04-01

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

  8. A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

    Science.gov (United States)

    Ingram, James N; Howard, Ian S; Flanagan, J Randall; Wolpert, Daniel M

    2011-09-01

    Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics

  9. A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

    Directory of Open Access Journals (Sweden)

    James N Ingram

    2011-09-01

    Full Text Available Motor learning has been extensively studied using dynamic (force-field perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar

  10. Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics.

    Science.gov (United States)

    Chen, Chi-Hsin; Zhang, Yayun; Yu, Chen

    2018-05-01

    Objects in the world usually have names at different hierarchical levels (e.g., beagle, dog, animal). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use co-occurrence information to learn hierarchical labels in contexts where the labels for individual objects and labels for categories were presented in completely separated blocks, in interleaved blocks, or mixed in the same trial. Temporal presentation schedules significantly affected the learning of individual object labels, but not the learning of category labels. Learners' subsequent generalization of category labels indicated sensitivity to the structure of statistical input. Copyright © 2017 Cognitive Science Society, Inc.

  11. Duo: A Human/Wearable Hybrid for Learning About Common Manipulate Objects

    National Research Council Canada - National Science Library

    Kemp, Charles C

    2002-01-01

    ... with them. Duo is a human/wearable hybrid that is designed to learn about this important domain of human intelligence by interacting with natural manipulable objects in unconstrained environments...

  12. Using Epistemic Network Analysis to understand core topics as planned learning objectives

    DEFF Research Database (Denmark)

    Allsopp, Benjamin Brink; Dreyøe, Jonas; Misfeldt, Morten

    Epistemic Network Analysis is a tool developed by the epistemic games group at the University of Wisconsin Madison for tracking the relations between concepts in students discourse (Shaffer 2017). In our current work we are applying this tool to learning objectives in teachers digital preparation....... The danish mathematics curriculum is organised in six competencies and three topics. In the recently implemented learning platforms teacher choose which of the mathematical competencies that serves as objective for a specific lesson or teaching sequence. Hence learning objectives for lessons and teaching...... sequences are defining a network of competencies, where two competencies are closely related of they often are part of the same learning objective or teaching sequence. We are currently using Epistemic Network Analysis to study these networks. In the poster we will include examples of different networks...

  13. Data quality objectives lessons learned for tank waste characterization

    International Nuclear Information System (INIS)

    Eberlein, S.J.; Banning, D.L.

    1996-01-01

    The tank waste characterization process is an integral part of the overall effort to control the hazards associated with radioactive wastes stored in underground tanks at the Hanford Reservation. The programs involved in the characterization of the waste are employing the Data Quality Objective (DQO) process in all information and data collection activities. The DQO process is used by the programs to address an issue or problem rather than a specific sampling event. Practical limits (e.g., limited number and location of sampling points) do not always allow for precise characterization of a tank or the full implementation of the DQO process. Because of the flexibility of the DQO process, it can be used as a planning tool for sampling and analysis of the underground waste storage tanks. The iterative nature of the DQO process allows it to be used as additional information is obtained or open-quotes lessons are learnedclose quotes concerning an issue or problem requiring sampling and analysis of tank waste. In addition, the application of the DQO process forces alternative actions to be considered when precise characterization of a tank or the fall implementation of the DQO process is not practical

  14. Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking.

    Science.gov (United States)

    Bae, Seung-Hwan; Yoon, Kuk-Jin

    2018-03-01

    Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a difficult problem in complex scenes, because of the large ambiguity in associating multiple objects in consecutive frames and the low discriminability between objects appearances. In this paper, we propose a robust online multi-object tracking method that can handle these difficulties effectively. We first define the tracklet confidence using the detectability and continuity of a tracklet, and decompose a multi-object tracking problem into small subproblems based on the tracklet confidence. We then solve the online multi-object tracking problem by associating tracklets and detections in different ways according to their confidence values. Based on this strategy, tracklets sequentially grow with online-provided detections, and fragmented tracklets are linked up with others without any iterative and expensive association steps. For more reliable association between tracklets and detections, we also propose a deep appearance learning method to learn a discriminative appearance model from large training datasets, since the conventional appearance learning methods do not provide rich representation that can distinguish multiple objects with large appearance variations. In addition, we combine online transfer learning for improving appearance discriminability by adapting the pre-trained deep model during online tracking. Experiments with challenging public datasets show distinct performance improvement over other state-of-the-arts batch and online tracking methods, and prove the effect and usefulness of the proposed methods for online multi-object tracking.

  15. Ego-Motion and Tracking for Continuous Object Learning: A Brief Survey

    Science.gov (United States)

    2017-09-01

    past research related to the tasks of ego-motion estimation and object tracking from the viewpoint of their role in continuous object learning...in visual object tracking, competitions are held each year to identify the most accurate and robust tracking implementations. Over recent competitions...information should they share) or vice versa? These are just some of the questions that must be addressed in future research toward continuous object

  16. Fast automated segmentation of multiple objects via spatially weighted shape learning

    Science.gov (United States)

    Chandra, Shekhar S.; Dowling, Jason A.; Greer, Peter B.; Martin, Jarad; Wratten, Chris; Pichler, Peter; Fripp, Jurgen; Crozier, Stuart

    2016-11-01

    Active shape models (ASMs) have proved successful in automatic segmentation by using shape and appearance priors in a number of areas such as prostate segmentation, where accurate contouring is important in treatment planning for prostate cancer. The ASM approach however, is heavily reliant on a good initialisation for achieving high segmentation quality. This initialisation often requires algorithms with high computational complexity, such as three dimensional (3D) image registration. In this work, we present a fast, self-initialised ASM approach that simultaneously fits multiple objects hierarchically controlled by spatially weighted shape learning. Prominent objects are targeted initially and spatial weights are progressively adjusted so that the next (more difficult, less visible) object is simultaneously initialised using a series of weighted shape models. The scheme was validated and compared to a multi-atlas approach on 3D magnetic resonance (MR) images of 38 cancer patients and had the same (mean, median, inter-rater) Dice’s similarity coefficients of (0.79, 0.81, 0.85), while having no registration error and a computational time of 12-15 min, nearly an order of magnitude faster than the multi-atlas approach.

  17. A Meta-Relational Approach for the Definition and Management of Hybrid Learning Objects

    Science.gov (United States)

    Navarro, Antonio; Fernandez-Pampillon, Ana Ma.; Fernandez-Chamizo, Carmen; Fernandez-Valmayor, Alfredo

    2013-01-01

    Electronic learning objects (LOs) are commonly conceived of as digital units of information used for teaching and learning. To facilitate their classification for pedagogical planning and retrieval purposes, LOs are complemented with metadata (e.g., the author). These metadata are usually restricted by a set of predetermined tags to which the…

  18. iLOG: A Framework for Automatic Annotation of Learning Objects with Empirical Usage Metadata

    Science.gov (United States)

    Miller, L. D.; Soh, Leen-Kiat; Samal, Ashok; Nugent, Gwen

    2012-01-01

    Learning objects (LOs) are digital or non-digital entities used for learning, education or training commonly stored in repositories searchable by their associated metadata. Unfortunately, based on the current standards, such metadata is often missing or incorrectly entered making search difficult or impossible. In this paper, we investigate…

  19. An Achievement Degree Analysis Approach to Identifying Learning Problems in Object-Oriented Programming

    Science.gov (United States)

    Allinjawi, Arwa A.; Al-Nuaim, Hana A.; Krause, Paul

    2014-01-01

    Students often face difficulties while learning object-oriented programming (OOP) concepts. Many papers have presented various assessment methods for diagnosing learning problems to improve the teaching of programming in computer science (CS) higher education. The research presented in this article illustrates that although max-min composition is…

  20. Simplified production of multimedia based radiological learning objects using the flash format

    International Nuclear Information System (INIS)

    Jedrusik, P.; Preisack, M.; Dammann, F.

    2005-01-01

    Purpose: evaluation of the applicability of the flash format for the production of radiological learning objects used in an e-learning environment. Material and methods: five exemplary learning objects with different didactic purposes referring to radiological diagnostics are presented. They have been intended for the use within the multimedia, internet-based e-learning environment LaMedica. Interactive learning objects were composed using the Flash 5.0 software (Macromedia, San Francisco, USA) on the basis of digital CT and MR images, digitized conventional radiographs and different graphical elements prepared as TIFF files or in a vector graphics format. Results: after a short phase of initial skill adaptation training, a radiologist author was soon able to create independently all learning objects. The import of different types of images and graphical elements was carried out without complications. Despite manifold design options, handling of the program is easy due to clear arrangement and structure, thus enabling the creation of simple as well as complex learning objects that provided a high degree of attractiveness and interaction. Data volume and bandwidth demand for online use was significantly reduced by the flash format compression without a substantial loss of visual quality. (orig.)

  1. Time-dependent inhomogeneous jet models for BL Lac objects

    Science.gov (United States)

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

    1992-05-01

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

  2. Learn Objective-C on the Mac for OS X and iOS

    CERN Document Server

    Knaster, Scott; Malik, Waqar

    2012-01-01

    Learn to write apps for some of today's hottest technologies, including the iPhone and iPad (using iOS), as well as the Mac (using OS X). It starts with Objective-C, the base language on which the native iOS software development kit (SDK) and the OS X are based. Learn Objective-C on the Mac: For OS X and iOS, Second Edition updates a best selling book and is an extensive, newly updated guide to Objective-C. Objective-C is a powerful, object-oriented extension of C, making this update the perfect follow-up to Dave Mark's bestselling Learn C on the Mac. Whether you're an experienced C programmer

  3. Information Recovery Algorithm for Ground Objects in Thin Cloud Images by Fusing Guide Filter and Transfer Learning

    Directory of Open Access Journals (Sweden)

    HU Gensheng

    2018-03-01

    Full Text Available Ground object information of remote sensing images covered with thin clouds is obscure. An information recovery algorithm for ground objects in thin cloud images is proposed by fusing guide filter and transfer learning. Firstly, multi-resolution decomposition of thin cloud target images and cloud-free guidance images is performed by using multi-directional nonsubsampled dual-tree complex wavelet transform. Then the decomposed low frequency subbands are processed by using support vector guided filter and transfer learning respectively. The decomposed high frequency subbands are enhanced by using modified Laine enhancement function. The low frequency subbands output by guided filter and those predicted by transfer learning model are fused by the method of selection and weighting based on regional energy. Finally, the enhanced high frequency subbands and the fused low frequency subbands are reconstructed by using inverse multi-directional nonsubsampled dual-tree complex wavelet transform to obtain the ground object information recovery images. Experimental results of Landsat-8 OLI multispectral images show that, support vector guided filter can effectively preserve the detail information of the target images, domain adaptive transfer learning can effectively extend the range of available multi-source and multi-temporal remote sensing images, and good effects for ground object information recover are obtained by fusing guide filter and transfer learning to remove thin cloud on the remote sensing images.

  4. Towards a Standards-Based Approach to E-Learning Personalization Using Reusable Learning Objects.

    Science.gov (United States)

    Conlan, Owen; Dagger, Declan; Wade, Vincent

    E-Learning systems that produce personalized course offerings for the learner are often expensive, both from a time and financial perspective, to develop and maintain. Learning content personalized to a learners' cognitive preferences has been shown to produce more effective learning, however many approaches to realizing this form of…

  5. Rapid e-Learning Tools Selection Process for Cognitive and Psychomotor Learning Objectives

    Science.gov (United States)

    Ku, David Tawei; Huang, Yung-Hsin

    2012-01-01

    This study developed a decision making process for the selection of rapid e-learning tools that could match different learning domains. With the development of the Internet, the speed of information updates has become faster than ever. E-learning has rapidly become the mainstream for corporate training and academic instruction. In order to reduce…

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

    Science.gov (United States)

    Rolls, Edmund T

    2012-01-01

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

  7. Computational modeling of epiphany learning.

    Science.gov (United States)

    Chen, Wei James; Krajbich, Ian

    2017-05-02

    Models of reinforcement learning (RL) are prevalent in the decision-making literature, but not all behavior seems to conform to the gradual convergence that is a central feature of RL. In some cases learning seems to happen all at once. Limited prior research on these "epiphanies" has shown evidence of sudden changes in behavior, but it remains unclear how such epiphanies occur. We propose a sequential-sampling model of epiphany learning (EL) and test it using an eye-tracking experiment. In the experiment, subjects repeatedly play a strategic game that has an optimal strategy. Subjects can learn over time from feedback but are also allowed to commit to a strategy at any time, eliminating all other options and opportunities to learn. We find that the EL model is consistent with the choices, eye movements, and pupillary responses of subjects who commit to the optimal strategy (correct epiphany) but not always of those who commit to a suboptimal strategy or who do not commit at all. Our findings suggest that EL is driven by a latent evidence accumulation process that can be revealed with eye-tracking data.

  8. Modellus: Learning Physics with Mathematical Modelling

    Science.gov (United States)

    Teodoro, Vitor

    Computers are now a major tool in research and development in almost all scientific and technological fields. Despite recent developments, this is far from true for learning environments in schools and most undergraduate studies. This thesis proposes a framework for designing curricula where computers, and computer modelling in particular, are a major tool for learning. The framework, based on research on learning science and mathematics and on computer user interface, assumes that: 1) learning is an active process of creating meaning from representations; 2) learning takes place in a community of practice where students learn both from their own effort and from external guidance; 3) learning is a process of becoming familiar with concepts, with links between concepts, and with representations; 4) direct manipulation user interfaces allow students to explore concrete-abstract objects such as those of physics and can be used by students with minimal computer knowledge. Physics is the science of constructing models and explanations about the physical world. And mathematical models are an important type of models that are difficult for many students. These difficulties can be rooted in the fact that most students do not have an environment where they can explore functions, differential equations and iterations as primary objects that model physical phenomena--as objects-to-think-with, reifying the formal objects of physics. The framework proposes that students should be introduced to modelling in a very early stage of learning physics and mathematics, two scientific areas that must be taught in very closely related way, as they were developed since Galileo and Newton until the beginning of our century, before the rise of overspecialisation in science. At an early stage, functions are the main type of objects used to model real phenomena, such as motions. At a later stage, rates of change and equations with rates of change play an important role. This type of equations

  9. A PDP model of the simultaneous perception of multiple objects

    Science.gov (United States)

    Henderson, Cynthia M.; McClelland, James L.

    2011-06-01

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

  10. Learning Analytics for Networked Learning Models

    Science.gov (United States)

    Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan

    2014-01-01

    Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…

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

    Science.gov (United States)

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

    2016-02-01

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

  12. [Requirements imposed on model objects in microevolutionary investigations].

    Science.gov (United States)

    Mina, M V

    2015-01-01

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

  13. Ferromanganese Furnace Modelling Using Object-Oriented Principles

    Energy Technology Data Exchange (ETDEWEB)

    Wasboe, S.O.

    1996-12-31

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

  14. Behavioral models as theoretical frames to analyze the business objective

    Directory of Open Access Journals (Sweden)

    Hernán Alonso Bafico

    2015-12-01

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

  15. Multi-objective group scheduling with learning effect in the cellular manufacturing system

    Directory of Open Access Journals (Sweden)

    Mohammad Taghi Taghavi-fard

    2011-01-01

    Full Text Available Group scheduling problem in cellular manufacturing systems consists of two major steps. Sequence of parts in each part-family and the sequence of part-family to enter the cell to be processed. This paper presents a new method for group scheduling problems in flow shop systems where it minimizes makespan (Cmax and total tardiness. In this paper, a position-based learning model in cellular manufacturing system is utilized where processing time for each part-family depends on the entrance sequence of that part. The problem of group scheduling is modeled by minimizing two objectives of position-based learning effect as well as the assumption of setup time depending on the sequence of parts-family. Since the proposed problem is NP-hard, two meta heuristic algorithms are presented based on genetic algorithm, namely: Non-dominated sorting genetic algorithm (NSGA-II and non-dominated rank genetic algorithm (NRGA. The algorithms are tested using randomly generated problems. The results include a set of Pareto solutions and three different evaluation criteria are used to compare the results. The results indicate that the proposed algorithms are quite efficient to solve the problem in a short computational time.

  16. A New Mobile Learning Adaptation Model

    OpenAIRE

    Mohamd Hassan Hassan; Jehad Al-Sadi

    2009-01-01

    This paper introduces a new model for m- Learning context adaptation due to the need of utilizing mobile technology in education. Mobile learning; m-Learning for short; in considered to be one of the hottest topics in the educational community, many researches had been done to conceptualize this new form of learning. We are presenting a promising design for a model to adapt the learning content in mobile learning applications in order to match the learner context, preferences and the educatio...

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

    Directory of Open Access Journals (Sweden)

    Heras Evangelio Rubén

    2011-01-01

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

  18. Design, Implementation and Evaluation of a Learning Object that Supports the Mathematics Learning in Children with Autism Spectrum Disorders

    Directory of Open Access Journals (Sweden)

    Roberto Munoz

    2018-04-01

    Full Text Available Information technologies have been widely used for entertainment and learning purposes by children with Autism Spectrum Disorders (ASD. Nonetheless, learning objects aiming at specific skills development in children with ASD require both a well bounded learning domain and a user-centered design process, considering skill levels of the users and the local geographical context and language. “Proyect@ Matemáticas” is a multi-touch based app designed for developing pre-calculus and functional mathematical skills in children with ASD, according to the Chilean regulations of learning goals for children with special educational necessities. This paper presents the User-centered design process conducted in order to develop the learning object, which included the evaluation by 15 experts in special educational needs, testing by 10 ASD-diagnosed children with different functional levels, and a multidisciplinary development team that also included a graphic designer diagnosed with ASD of high functionality. The development process yields to a validated learning object in terms of interactivity, design, engagement, and usability, from the point of view of the experts, and successful usage tests with ASD diagnosed children in terms of performance and achievement of learning outcomes. The application is currently available for download in the Google Play store for free, and currently has more than 15,000 downloads and an average rating of 4.2 out of 5 points.

  19. A Mobile Service Oriented Multiple Object Tracking Augmented Reality Architecture for Education and Learning Experiences

    Science.gov (United States)

    Rattanarungrot, Sasithorn; White, Martin; Newbury, Paul

    2014-01-01

    This paper describes the design of our service-oriented architecture to support mobile multiple object tracking augmented reality applications applied to education and learning scenarios. The architecture is composed of a mobile multiple object tracking augmented reality client, a web service framework, and dynamic content providers. Tracking of…

  20. Autonomous learning of robust visual object detection and identification on a humanoid

    NARCIS (Netherlands)

    Leitner, J.; Chandrashekhariah, P.; Harding, S.; Frank, M.; Spina, G.; Förster, A.; Triesch, J.; Schmidhuber, J.

    2012-01-01

    In this work we introduce a technique for a humanoid robot to autonomously learn the representations of objects within its visual environment. Our approach involves an attention mechanism in association with feature based segmentation that explores the environment and provides object samples for

  1. Behavioral Objectives, the Cult of Efficiency, and Foreign Language Learning: Are They Compatible?

    Science.gov (United States)

    Tumposky, Nancy Rennau

    1984-01-01

    Surveys the literature regarding the use of behavioral objectives in education and in foreign language instruction and examines the roots of the behavioral objectives movement in behaviorist psychology and the scientific management movement of the 1920s. Discusses implications for foreign and second language learning and provides suggestions for…

  2. Aspects on Teaching/Learning with Object Oriented Programming for Entry Level Courses of Engineering.

    Science.gov (United States)

    de Oliveira, Clara Amelia; Conte, Marcos Fernando; Riso, Bernardo Goncalves

    This work presents a proposal for Teaching/Learning, on Object Oriented Programming for Entry Level Courses of Engineering and Computer Science, on University. The philosophy of Object Oriented Programming comes as a new pattern of solution for problems, where flexibility and reusability appears over the simple data structure and sequential…

  3. GSMNet: A Hierarchical Graph Model for Moving Objects in Networks

    Directory of Open Access Journals (Sweden)

    Hengcai Zhang

    2017-03-01

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

  4. Individual Learning Accounts and Other Models of Financing Lifelong Learning

    Science.gov (United States)

    Schuetze, Hans G.

    2007-01-01

    To answer the question "Financing what?" this article distinguishes several models of lifelong learning as well as a variety of lifelong learning activities. Several financing methods are briefly reviewed, however the principal focus is on Individual Learning Accounts (ILAs) which were seen by some analysts as a promising model for…

  5. Urban Studies: A Learning Model.

    Science.gov (United States)

    Cooper, Terry L.; Sundeen, Richard

    1979-01-01

    The urban studies learning model described in this article was found to increase students' self-esteem, imbue a more flexible and open perspective, contribute to the capacity for self-direction, produce increases on the feeling reactivity, spontaneity, and acceptance of aggression scales, and expand interpersonal competence. (Author/WI)

  6. Model-Based Software Testing for Object-Oriented Software

    Science.gov (United States)

    Biju, Soly Mathew

    2008-01-01

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

  7. A General Polygon-based Deformable Model for Object Recognition

    DEFF Research Database (Denmark)

    Jensen, Rune Fisker; Carstensen, Jens Michael

    1999-01-01

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

  8. Archive Design Based on Planets Inspired Logical Object Model

    DEFF Research Database (Denmark)

    Zierau, Eld; Johansen, Anders

    2008-01-01

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

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

    International Nuclear Information System (INIS)

    Podbereznyj, S.S.

    2001-01-01

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

  10. Constructing Multidatabase Collections Using Extended ODMG Object Model

    Directory of Open Access Journals (Sweden)

    Adrian Skehill Mark Roantree

    1999-11-01

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

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

    International Nuclear Information System (INIS)

    Zhou, Z; Folkert, M; Wang, J

    2016-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-06-15

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

  13. Validation of virtual learning object to support the teaching of nursing care systematization

    Directory of Open Access Journals (Sweden)

    Pétala Tuani Candido de Oliveira Salvador

    Full Text Available ABSTRACT Objective: to describe the content validation process of a Virtual Learning Object to support the teaching of nursing care systematization to nursing professionals. Method: methodological study, with quantitative approach, developed according to the methodological reference of Pasquali's psychometry and conducted from March to July 2016, from two-stage Delphi procedure. Results: in the Delphi 1 stage, eight judges evaluated the Virtual Object; in Delphi 2 stage, seven judges evaluated it. The seven screens of the Virtual Object were analyzed as to the suitability of its contents. The Virtual Learning Object to support the teaching of nursing care systematization was considered valid in its content, with a Total Content Validity Coefficient of 0.96. Conclusion: it is expected that the Virtual Object can support the teaching of nursing care systematization in light of appropriate and effective pedagogical approaches.

  14. Attribute conjunctions and the part configuration advantage in object category learning.

    Science.gov (United States)

    Saiki, J; Hummel, J E

    1996-07-01

    Five experiments demonstrated that in object category learning people are particularly sensitive to conjunctions of part shapes and relative locations. Participants learned categories defined by a part's shape and color (part-color conjunctions) or by a part's shape and its location relative to another part (part-location conjunctions). The statistical properties of the categories were identical across these conditions, as were the salience of color and relative location. Participants were better at classifying objects defined by part-location conjunctions than objects defined by part-color conjunctions. Subsequent experiments revealed that this effect was not due to the specific color manipulation or the role of location per se. These results suggest that the shape bias in object categorization is at least partly due to sensitivity to part-location conjunctions and suggest a new processing constraint on category learning.

  15. Teaching Economics: A Cooperative Learning Model.

    Science.gov (United States)

    Caropreso, Edward J.; Haggerty, Mark

    2000-01-01

    Describes an alternative approach to introductory economics based on a cooperative learning model, "Learning Together." Discussion of issues in economics education and cooperative learning in higher education leads to explanation of how to adapt the Learning Together Model to lesson planning in economics. A flow chart illustrates the process for a…

  16. Learning from erroneous models using SCYDynamics

    NARCIS (Netherlands)

    Mulder, Y.G.; Bollen, Lars; de Jong, Anthonius J.M.

    2014-01-01

    Dynamic phenomena are common in science education. Students can learn about such system dynamic processes through model based learning activities. This paper describes a study on the effects of a learning from erroneous models approach using the learning environment SCYDynamics. The study compared

  17. Fuzzy object models for newborn brain MR image segmentation

    Science.gov (United States)

    Kobashi, Syoji; Udupa, Jayaram K.

    2013-03-01

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

  18. Selective bilateral amygdala lesions in rhesus monkeys fail to disrupt object reversal learning.

    Science.gov (United States)

    Izquierdo, Alicia; Murray, Elisabeth A

    2007-01-31

    Neuropsychological studies in nonhuman primates have led to the view that the amygdala plays an essential role in stimulus-reward association. The main evidence in support of this idea is that bilateral aspirative or radiofrequency lesions of the amygdala yield severe impairments on object reversal learning, a task that assesses the ability to shift choices of objects based on the presence or absence of food reward (i.e., reward contingency). The behavioral effects of different lesion techniques, however, can vary. The present study therefore evaluated the effects of selective, excitotoxic lesions of the amygdala in rhesus monkeys on object reversal learning. For comparison, we tested the same monkeys on a task known to be sensitive to amygdala damage, the reinforcer devaluation task. Contrary to previous results based on less selective lesion techniques, monkeys with complete excitotoxic amygdala lesions performed object reversal learning as quickly as controls. As predicted, however, the same operated monkeys were impaired in making object choices after devaluation of the associated food reinforcer. The results suggest two conclusions. First, the results demonstrate that the amygdala makes a selective contribution to stimulus-reward association; the amygdala is critical for guiding object choices after changes in reward value but not after changes in reward contingency. Second, the results implicate a critical contribution to object reversal learning of structures nearby the amygdala, perhaps the subjacent rhinal cortex.

  19. Bio-Inspired Neural Model for Learning Dynamic Models

    Science.gov (United States)

    Duong, Tuan; Duong, Vu; Suri, Ronald

    2009-01-01

    A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.

  20. The Aalborg Model and management by objectives and resources

    DEFF Research Database (Denmark)

    Qvist, Palle; Spliid, Claus Monrad

    2010-01-01

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

  1. Safe robot execution in model-based reinforcement learning

    OpenAIRE

    Martínez Martínez, David; Alenyà Ribas, Guillem; Torras, Carme

    2015-01-01

    Task learning in robotics requires repeatedly executing the same actions in different states to learn the model of the task. However, in real-world domains, there are usually sequences of actions that, if executed, may produce unrecoverable errors (e.g. breaking an object). Robots should avoid repeating such errors when learning, and thus explore the state space in a more intelligent way. This requires identifying dangerous action effects to avoid including such actions in the generated plans...

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

    Directory of Open Access Journals (Sweden)

    Masoud eGhodrati

    2014-07-01

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

  3. A Coterminous Collaborative Learning Model: Interconnectivity of Leadership and Learning

    Directory of Open Access Journals (Sweden)

    Ilana Margolin

    2012-05-01

    Full Text Available This qualitative ethnographic study examines a collaborative leadership model focused on learning and socially just practices within a change context of a wide educational partnership. The study analyzes a range of perspectives of novice teachers, mentor teachers, teacher educators and district superintendents on leadership and learning. The findings reveal the emergence of a coalition of leaders crossing borders at all levels of the educational system: local school level, district level and teacher education level who were involved in coterminous collaborative learning. Four categories of learning were identified as critical to leading a change in the educational system: learning in professional communities, learning from practice, learning through theory and research and learning from and with leaders. The implications of the study for policy makers as well as for practitioners are to adopt a holistic approach to the educational environment and plan a collaborative learning continuum from initial pre-service programs through professional development learning at all levels.

  4. Turbulence and Self-Organization Modeling Astrophysical Objects

    CERN Document Server

    Marov, Mikhail Ya

    2013-01-01

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

  5. An Interactive Learning Environment for Teaching the Imperative and Object-Oriented Programming Techniques in Various Learning Contexts

    Science.gov (United States)

    Xinogalos, Stelios

    The acquisition of problem-solving and programming skills in the era of knowledge society seems to be particularly important. Due to the intrinsic difficulty of acquiring such skills various educational tools have been developed. Unfortunately, most of these tools are not utilized. In this paper we present the programming microworlds Karel and objectKarel that support the procedural-imperative and Object-Oriented Programming (OOP) techniques and can be used for supporting the teaching and learning of programming in various learning contexts and audiences. The paper focuses on presenting the pedagogical features that are common to both environments and mainly on presenting the potential uses of these environments.

  6. It's all connected: Pathways in visual object recognition and early noun learning.

    Science.gov (United States)

    Smith, Linda B

    2013-11-01

    A developmental pathway may be defined as the route, or chain of events, through which a new structure or function forms. For many human behaviors, including object name learning and visual object recognition, these pathways are often complex and multicausal and include unexpected dependencies. This article presents three principles of development that suggest the value of a developmental psychology that explicitly seeks to trace these pathways and uses empirical evidence on developmental dependencies among motor development, action on objects, visual object recognition, and object name learning in 12- to 24-month-old infants to make the case. The article concludes with a consideration of the theoretical implications of this approach. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

  7. Internal attention to features in visual short-term memory guides object learning.

    Science.gov (United States)

    Fan, Judith E; Turk-Browne, Nicholas B

    2013-11-01

    Attending to objects in the world affects how we perceive and remember them. What are the consequences of attending to an object in mind? In particular, how does reporting the features of a recently seen object guide visual learning? In three experiments, observers were presented with abstract shapes in a particular color, orientation, and location. After viewing each object, observers were cued to report one feature from visual short-term memory (VSTM). In a subsequent test, observers were cued to report features of the same objects from visual long-term memory (VLTM). We tested whether reporting a feature from VSTM: (1) enhances VLTM for just that feature (practice-benefit hypothesis), (2) enhances VLTM for all features (object-based hypothesis), or (3) simultaneously enhances VLTM for that feature and suppresses VLTM for unreported features (feature-competition hypothesis). The results provided support for the feature-competition hypothesis, whereby the representation of an object in VLTM was biased towards features reported from VSTM and away from unreported features (Experiment 1). This bias could not be explained by the amount of sensory exposure or response learning (Experiment 2) and was amplified by the reporting of multiple features (Experiment 3). Taken together, these results suggest that selective internal attention induces competitive dynamics among features during visual learning, flexibly tuning object representations to align with prior mnemonic goals. Copyright © 2013 Elsevier B.V. All rights reserved.

  8. Object-Oriented Approach to Modeling Units of Pneumatic Systems

    Directory of Open Access Journals (Sweden)

    Yu. V. Kyurdzhiev

    2014-01-01

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

  9. Development of Learning Virtual Objects as a Strategy to Foster Student Retention in Higher Education

    OpenAIRE

    Yois S. Pascuas Rengifo; César Omar Jaramillo Morales; Fredy Antonio Verástegui González

    2015-01-01

    Rev.esc.adm.neg One of the problems that the Colombian higher education system is facing is the problem of student desertion, shwoing that a great amount of students leave their university studies during the first semesters. For this reason, the National Education Ministry and Universidad de la Amazonia implement a new strategy to foster student retention and graduation through academic levelling. This paper shows eight learning virtual objects from different learning áreas, applying tech...

  10. Storytelling in the digital world: achieving higher-level learning objectives.

    Science.gov (United States)

    Schwartz, Melissa R

    2012-01-01

    Nursing students are not passive media consumers but instead live in a technology ecosystem where digital is the language they speak. To prepare the next generation of nurses, educators must incorporate multiple technologies to improve higher-order learning. The author discusses the evolution and use of storytelling as part of the digital world and how digital stories can be aligned with Bloom's Taxonomy so that students achieve higher-level learning objectives.

  11. Creative Generation of 3D Objects with Deep Learning and Innovation Engines

    DEFF Research Database (Denmark)

    Lehman, Joel Anthony; Risi, Sebastian; Clune, Jeff

    2016-01-01

    Advances in supervised learning with deep neural networks have enabled robust classification in many real world domains. An interesting question is if such advances can also be leveraged effectively for computational creativity. One insight is that because evolutionary algorithms are free from st...... creativity. The results of this automated process are interesting and recognizable 3D-printable objects, demonstrating the creative potential for combining evolutionary computation and deep learning in this way....

  12. Multi-objective optimization of GENIE Earth system models.

    Science.gov (United States)

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

    2009-07-13

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

  13. Problem-Based Learning Associated by Action-Process-Object-Schema (APOS) Theory to Enhance Students' High Order Mathematical Thinking Ability

    Science.gov (United States)

    Mudrikah, Achmad

    2016-01-01

    The research has shown a model of learning activities that can be used to stimulate reflective abstraction in students. Reflective abstraction as a method of constructing knowledge in the Action-Process-Object-Schema theory, and is expected to occur when students are in learning activities, will be able to encourage students to make the process of…

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

    Science.gov (United States)

    Farris, A.

    1992-01-01

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

  15. Proof of Economic Viability of Blended Learning Business Models

    Science.gov (United States)

    Druhmann, Carsten; Hohenberg, Gregor

    2014-01-01

    The discussion on economically sustainable business models with respect to information technology is lacking in many aspects of proven approaches. In the following contribution the economic viability is valued based on a procedural model for design and evaluation of e-learning business models in the form of a case study. As a case study object a…

  16. The perceptual effects of learning object categories that predict perceptual goals

    Science.gov (United States)

    Van Gulick, Ana E.; Gauthier, Isabel

    2014-01-01

    In classic category learning studies, subjects typically learn to assign items to one of two categories, with no further distinction between how items on each side of the category boundary should be treated. In real life, however, we often learn categories that dictate further processing goals, for instance with objects in only one category requiring further individuation. Using methods from category learning and perceptual expertise, we studied the perceptual consequences of experience with objects in tasks that rely on attention to different dimensions in different parts of the space. In two experiments, subjects first learned to categorize complex objects from a single morphspace into two categories based on one morph dimension, and then learned to perform a different task, either naming or a local feature judgment, for each of the two categories. A same-different discrimination test before and after each training measured sensitivity to feature dimensions of the space. After initial categorization, sensitivity increased along the category-diagnostic dimension. After task association, sensitivity increased more for the category that was named, especially along the non-diagnostic dimension. The results demonstrate that local attentional weights, associated with individual exemplars as a function of task requirements, can have lasting effects on perceptual representations. PMID:24820671

  17. Object Oriented Toolbox for Modelling and Simulation of Dynamical Systems

    DEFF Research Database (Denmark)

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

    1998-01-01

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

  18. Multi-documents summarization based on clustering of learning object using hierarchical clustering

    Science.gov (United States)

    Mustamiin, M.; Budi, I.; Santoso, H. B.

    2018-03-01

    The Open Educational Resources (OER) is a portal of teaching, learning and research resources that is available in public domain and freely accessible. Learning contents or Learning Objects (LO) are granular and can be reused for constructing new learning materials. LO ontology-based searching techniques can be used to search for LO in the Indonesia OER. In this research, LO from search results are used as an ingredient to create new learning materials according to the topic searched by users. Summarizing-based grouping of LO use Hierarchical Agglomerative Clustering (HAC) with the dependency context to the user’s query which has an average value F-Measure of 0.487, while summarizing by K-Means F-Measure only has an average value of 0.336.

  19. Development of a cultural heritage object BIM model

    Science.gov (United States)

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

    2017-10-01

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

  20. Space Object Radiometric Modeling for Hardbody Optical Signature Database Generation

    Science.gov (United States)

    2009-09-01

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

  1. Distribution majorization of corner points by reinforcement learning for moving object detection

    Science.gov (United States)

    Wu, Hao; Yu, Hao; Zhou, Dongxiang; Cheng, Yongqiang

    2018-04-01

    Corner points play an important role in moving object detection, especially in the case of free-moving camera. Corner points provide more accurate information than other pixels and reduce the computation which is unnecessary. Previous works only use intensity information to locate the corner points, however, the information that former and the last frames provided also can be used. We utilize the information to focus on more valuable area and ignore the invaluable area. The proposed algorithm is based on reinforcement learning, which regards the detection of corner points as a Markov process. In the Markov model, the video to be detected is regarded as environment, the selections of blocks for one corner point are regarded as actions and the performance of detection is regarded as state. Corner points are assigned to be the blocks which are seperated from original whole image. Experimentally, we select a conventional method which uses marching and Random Sample Consensus algorithm to obtain objects as the main framework and utilize our algorithm to improve the result. The comparison between the conventional method and the same one with our algorithm show that our algorithm reduce 70% of the false detection.

  2. Learning of perceptual grouping for object segmentation on RGB-D data.

    Science.gov (United States)

    Richtsfeld, Andreas; Mörwald, Thomas; Prankl, Johann; Zillich, Michael; Vincze, Markus

    2014-01-01

    Object segmentation of unknown objects with arbitrary shape in cluttered scenes is an ambitious goal in computer vision and became a great impulse with the introduction of cheap and powerful RGB-D sensors. We introduce a framework for segmenting RGB-D images where data is processed in a hierarchical fashion. After pre-clustering on pixel level parametric surface patches are estimated. Different relations between patch-pairs are calculated, which we derive from perceptual grouping principles, and support vector machine classification is employed to learn Perceptual Grouping. Finally, we show that object hypotheses generation with Graph-Cut finds a globally optimal solution and prevents wrong grouping. Our framework is able to segment objects, even if they are stacked or jumbled in cluttered scenes. We also tackle the problem of segmenting objects when they are partially occluded. The work is evaluated on publicly available object segmentation databases and also compared with state-of-the-art work of object segmentation.

  3. Learning Graphical Models With Hubs.

    Science.gov (United States)

    Tan, Kean Ming; London, Palma; Mohan, Karthik; Lee, Su-In; Fazel, Maryam; Witten, Daniela

    2014-10-01

    We consider the problem of learning a high-dimensional graphical model in which there are a few hub nodes that are densely-connected to many other nodes. Many authors have studied the use of an ℓ 1 penalty in order to learn a sparse graph in the high-dimensional setting. However, the ℓ 1 penalty implicitly assumes that each edge is equally likely and independent of all other edges. We propose a general framework to accommodate more realistic networks with hub nodes, using a convex formulation that involves a row-column overlap norm penalty. We apply this general framework to three widely-used probabilistic graphical models: the Gaussian graphical model, the covariance graph model, and the binary Ising model. An alternating direction method of multipliers algorithm is used to solve the corresponding convex optimization problems. On synthetic data, we demonstrate that our proposed framework outperforms competitors that do not explicitly model hub nodes. We illustrate our proposal on a webpage data set and a gene expression data set.

  4. Learning based particle filtering object tracking for visible-light systems.

    Science.gov (United States)

    Sun, Wei

    2015-10-01

    We propose a novel object tracking framework based on online learning scheme that can work robustly in challenging scenarios. Firstly, a learning-based particle filter is proposed with color and edge-based features. We train a. support vector machine (SVM) classifier with object and background information and map the outputs into probabilities, then the weight of particles in a particle filter can be calculated by the probabilistic outputs to estimate the state of the object. Secondly, the tracking loop starts with Lucas-Kanade (LK) affine template matching and follows by learning-based particle filter tracking. Lucas-Kanade method estimates errors and updates object template in the positive samples dataset, and learning-based particle filter tracker will start if the LK tracker loses the object. Finally, SVM classifier evaluates every tracked appearance to update the training set or restart the tracking loop if necessary. Experimental results show that our method is robust to challenging light, scale and pose changing, and test on eButton image sequence also achieves satisfactory tracking performance.

  5. Humanoid infers Archimedes' principle: understanding physical relations and object affordances through cumulative learning experiences.

    Science.gov (United States)

    Bhat, Ajaz Ahmad; Mohan, Vishwanathan; Sandini, Giulio; Morasso, Pietro

    2016-07-01

    Emerging studies indicate that several species such as corvids, apes and children solve 'The Crow and the Pitcher' task (from Aesop's Fables) in diverse conditions. Hidden beneath this fascinating paradigm is a fundamental question: by cumulatively interacting with different objects, how can an agent abstract the underlying cause-effect relations to predict and creatively exploit potential affordances of novel objects in the context of sought goals? Re-enacting this Aesop's Fable task on a humanoid within an open-ended 'learning-prediction-abstraction' loop, we address this problem and (i) present a brain-guided neural framework that emulates rapid one-shot encoding of ongoing experiences into a long-term memory and (ii) propose four task-agnostic learning rules (elimination, growth, uncertainty and status quo) that correlate predictions from remembered past experiences with the unfolding present situation to gradually abstract the underlying causal relations. Driven by the proposed architecture, the ensuing robot behaviours illustrated causal learning and anticipation similar to natural agents. Results further demonstrate that by cumulatively interacting with few objects, the predictions of the robot in case of novel objects converge close to the physical law, i.e. the Archimedes principle: this being independent of both the objects explored during learning and the order of their cumulative exploration. © 2016 The Author(s).

  6. Interaction between the Learners' Initial Grasp of the Object of Learning and the Learning Resource Afforded

    Science.gov (United States)

    Pang, Ming Fai; Marton, Ference

    2013-01-01

    Two studies are reported in this paper. The object of learning in both is the economic principle of changes in price as a function of changes in the relative magnitude of changes in demand and supply. The patterns of variation and invariance, defining the conditions compared were built into pedagogical tools (text, graphs, and worksheets). The…

  7. Assuring the Quality of Agricultural Learning Repositories: Issues for the Learning Object Metadata Creation Process of the CGIAR

    Science.gov (United States)

    Zschocke, Thomas; Beniest, Jan

    The Consultative Group on International Agricultural Re- search (CGIAR) has established a digital repository to share its teaching and learning resources along with descriptive educational information based on the IEEE Learning Object Metadata (LOM) standard. As a critical component of any digital repository, quality metadata are critical not only to enable users to find more easily the resources they require, but also for the operation and interoperability of the repository itself. Studies show that repositories have difficulties in obtaining good quality metadata from their contributors, especially when this process involves many different stakeholders as is the case with the CGIAR as an international organization. To address this issue the CGIAR began investigating the Open ECBCheck as well as the ISO/IEC 19796-1 standard to establish quality protocols for its training. The paper highlights the implications and challenges posed by strengthening the metadata creation workflow for disseminating learning objects of the CGIAR.

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

    Science.gov (United States)

    Wang, Panqu; Gauthier, Isabel; Cottrell, Garrison

    2016-04-01

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

  9. RANCANGAN DATABASE SUBSISTEM PRODUKSI DENGAN PENDEKATAN SEMANTIC OBJECT MODEL

    Directory of Open Access Journals (Sweden)

    Oviliani Yenty Yuliana

    2002-01-01

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

  10. Creating Learning Objects to Enhance the Educational Experiences of American Sign Language Learners: An Instructional Development Report

    Directory of Open Access Journals (Sweden)

    Simone Conceição

    2002-10-01

    Full Text Available Little attention has been given to involving the deaf community in distance teaching and learning or in designing courses that relate to their language and culture. This article reports on the design and development of video-based learning objects created to enhance the educational experiences of American Sign Language (ASL hearing participants in a distance learning course and, following the course, the creation of several new applications for use of the learning objects. The learning objects were initially created for the web, as a course component for review and rehearsal. The value of the web application, as reported by course participants, led us to consider ways in which the learning objects could be used in a variety of delivery formats: CD-ROM, web-based knowledge repository, and handheld device. The process to create the learning objects, the new applications, and lessons learned are described.

  11. Modeling Dynamic Objects in Monte Carlo Particle Transport Calculations

    International Nuclear Information System (INIS)

    Yegin, G.

    2008-01-01

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

  12. An ODP computational model of a cooperative binding object

    Science.gov (United States)

    Logé, Christophe; Najm, Elie; Chen, Ken

    1997-12-01

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

  13. Modeling and Simulation of Grasping of Deformable Objects

    DEFF Research Database (Denmark)

    Fugl, Andreas Rune

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

  14. An object-oriented approach to evaluating multiple spectral models

    International Nuclear Information System (INIS)

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

    1995-01-01

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

  15. Semantic Web, Reusable Learning Objects, Personal Learning Networks in Health: Key Pieces for Digital Health Literacy.

    Science.gov (United States)

    Konstantinidis, Stathis Th; Wharrad, Heather; Windle, Richard; Bamidis, Panagiotis D

    2017-01-01

    The knowledge existing in the World Wide Web is exponentially expanding, while continuous advancements in health sciences contribute to the creation of new knowledge. There are a lot of efforts trying to identify how the social connectivity can endorse patients' empowerment, while other studies look at the identification and the quality of online materials. However, emphasis has not been put on the big picture of connecting the existing resources with the patients "new habits" of learning through their own Personal Learning Networks. In this paper we propose a framework for empowering patients' digital health literacy adjusted to patients' currents needs by utilizing the contemporary way of learning through Personal Learning Networks, existing high quality learning resources and semantics technologies for interconnecting knowledge pieces. The framework based on the concept of knowledge maps for health as defined in this paper. Health Digital Literacy needs definitely further enhancement and the use of the proposed concept might lead to useful tools which enable use of understandable health trusted resources tailored to each person needs.

  16. Learning Rich Features from RGB-D Images for Object Detection and Segmentation

    OpenAIRE

    Gupta, Saurabh; Girshick, Ross; Arbeláez, Pablo; Malik, Jitendra

    2014-01-01

    In this paper we study the problem of object detection for RGB-D images using semantically rich image and depth features. We propose a new geocentric embedding for depth images that encodes height above ground and angle with gravity for each pixel in addition to the horizontal disparity. We demonstrate that this geocentric embedding works better than using raw depth images for learning feature representations with convolutional neural networks. Our final object detection system achieves an av...

  17. Catalogue of Interactive Learning Objectives to improve an Integrated Medical and Dental Curriculum.

    Science.gov (United States)

    Mahmoodi, Benjamin; Sagheb, K; Sagheb, Ka; Schulz, P; Willershausen, B; Al-Nawas, B; Walter, C

    2016-12-01

    Online learning media are increasingly being incorporated into medical and dental education. However, the coordination between obligatory and facultative teaching domains still remains unsatisfying. The Catalogue of Interactive Learning Objectives of the University Clinic of Mainz (ILKUM), aims to offer knowledge transfer for students while being mindful of their individual qualifications. Its hierarchical structure is designed according to the Association for Dental Education in Europe (ADEE) levels of competence. The ILKUM was designed to establish a stronger interconnection between already existing and prospective learning strategies. All contents are linked to the current lectures as well as to e-learning modules, e.g., clinical case studies and OR videos. Students can conduct self-examinations regarding specific learning objectives. Since 2007, ILKUM has been developed and analyzed regarding its acceptance among dental students. These improved e-learning techniques foster time and location-independent access to study materials and allow an estimation of the knowledge achieved by students. Surveys of our students clearly show a large demand for upgrading ILKUM content (89%; n = 172) with integrated self-testing (89%; n = 174). In parallel to the advancement of our e-learning offering, a portion of internet-based learning is constantly rising among students. The broad acceptance and demand for the development of ILKUM show its potential. Moreover, ILKUM grants fast, topic-oriented querying of learning content without time and locale limitations as well as direct determination of the individually needed knowledge conditions. The long-term goal of the ILKUM project is to be a sustainable, important additional modality of teaching and training for dental and medical students.

  18. Development of national competency-based learning objectives "Medical Informatics" for undergraduate medical education.

    Science.gov (United States)

    Röhrig, R; Stausberg, J; Dugas, M

    2013-01-01

    The aim of this project is to develop a catalogue of competency-based learning objectives "Medical Informatics" for undergraduate medical education (abbreviated NKLM-MI in German). The development followed a multi-level annotation and consensus process. For each learning objective a reason why a physician needs this competence was required. In addition, each objective was categorized according to the competence context (A = covered by medical informatics, B = core subject of medical informatics, C = optional subject of medical informatics), the competence level (1 = referenced knowledge, 2 = applied knowledge, 3 = routine knowledge) and a CanMEDS competence role (medical expert, communicator, collaborator, manager, health advocate, professional, scholar). Overall 42 objectives in seven areas (medical documentation and information processing, medical classifications and terminologies, information systems in healthcare, health telematics and telemedicine, data protection and security, access to medical knowledge and medical signal-/image processing) were identified, defined and consented. With the NKLM-MI the competences in the field of medical informatics vital to a first year resident physician are identified, defined and operationalized. These competencies are consistent with the recommendations of the International Medical Informatics Association (IMIA). The NKLM-MI will be submitted to the National Competence-Based Learning Objectives for Undergraduate Medical Education. The next step is implementation of these objectives by the faculties.

  19. Learning to Act: Qualitative Learning of Deterministic Action Models

    DEFF Research Database (Denmark)

    Bolander, Thomas; Gierasimczuk, Nina

    2017-01-01

    In this article we study learnability of fully observable, universally applicable action models of dynamic epistemic logic. We introduce a framework for actions seen as sets of transitions between propositional states and we relate them to their dynamic epistemic logic representations as action...... in the limit (inconclusive convergence to the right action model). We show that deterministic actions are finitely identifiable, while arbitrary (non-deterministic) actions require more learning power—they are identifiable in the limit. We then move on to a particular learning method, i.e. learning via update......, which proceeds via restriction of a space of events within a learning-specific action model. We show how this method can be adapted to learn conditional and unconditional deterministic action models. We propose update learning mechanisms for the afore mentioned classes of actions and analyse...

  20. RuleML-Based Learning Object Interoperability on the Semantic Web

    Science.gov (United States)

    Biletskiy, Yevgen; Boley, Harold; Ranganathan, Girish R.

    2008-01-01

    Purpose: The present paper aims to describe an approach for building the Semantic Web rules for interoperation between heterogeneous learning objects, namely course outlines from different universities, and one of the rule uses: identifying (in)compatibilities between course descriptions. Design/methodology/approach: As proof of concept, a rule…

  1. A Conceptual Framework for Error Remediation with Multiple External Representations Applied to Learning Objects

    Science.gov (United States)

    Leite, Maici Duarte; Marczal, Diego; Pimentel, Andrey Ricardo; Direne, Alexandre Ibrahim

    2014-01-01

    This paper presents the application of some concepts of Intelligent Tutoring Systems (ITS) to elaborate a conceptual framework that uses the remediation of errors with Multiple External Representations (MERs) in Learning Objects (LO). To this is demonstrated a development of LO for teaching the Pythagorean Theorem through this framework. This…

  2. Object-based implicit learning in visual search: perceptual segmentation constrains contextual cueing.

    Science.gov (United States)

    Conci, Markus; Müller, Hermann J; von Mühlenen, Adrian

    2013-07-09

    In visual search, detection of a target is faster when it is presented within a spatial layout of repeatedly encountered nontarget items, indicating that contextual invariances can guide selective attention (contextual cueing; Chun & Jiang, 1998). However, perceptual regularities may interfere with contextual learning; for instance, no contextual facilitation occurs when four nontargets form a square-shaped grouping, even though the square location predicts the target location (Conci & von Mühlenen, 2009). Here, we further investigated potential causes for this interference-effect: We show that contextual cueing can reliably occur for targets located within the region of a segmented object, but not for targets presented outside of the object's boundaries. Four experiments demonstrate an object-based facilitation in contextual cueing, with a modulation of context-based learning by relatively subtle grouping cues including closure, symmetry, and spatial regularity. Moreover, the lack of contextual cueing for targets located outside the segmented region was due to an absence of (latent) learning of contextual layouts, rather than due to an attentional bias towards the grouped region. Taken together, these results indicate that perceptual segmentation provides a basic structure within which contextual scene regularities are acquired. This in turn argues that contextual learning is constrained by object-based selection.

  3. Category Specificity in Normal Episodic Learning: Applications to Object Recognition and Category-Specific Agnosia

    Science.gov (United States)

    Bukach, Cindy M.; Bub, Daniel N.; Masson, Michael E. J.; Lindsay, D. Stephen

    2004-01-01

    Studies of patients with category-specific agnosia (CSA) have given rise to multiple theories of object recognition, most of which assume the existence of a stable, abstract semantic memory system. We applied an episodic view of memory to questions raised by CSA in a series of studies examining normal observers' recall of newly learned attributes…

  4. An Analysis of Learning Objectives and Content Coverage in Introductory Psychology Syllabi

    Science.gov (United States)

    Homa, Natalie; Hackathorn, Jana; Brown, Carrie M.; Garczynski, Amy; Solomon, Erin D.; Tennial, Rachel; Sanborn, Ursula A.; Gurung, Regan A. R.

    2013-01-01

    Introductory psychology is one of the most popular undergraduate courses and often serves as the gateway to choosing psychology as an academic major. However, little research has examined the typical structure of introductory psychology courses. The current study examined student learning objectives (SLOs) and course content in introductory…

  5. Joint Attention and Object Learning in 5- and 7-Month-Old Infants

    Science.gov (United States)

    Cleveland, Allison; Schug, Mariah; Striano, Tricia

    2007-01-01

    We examined the effects of joint attention for object learning in 5- and 7-month-old infants. Infants interacted with an adult social partner who taught them about a novel toy in two conditions. In the "Joint Attention" condition, the adult spoke about the toy while alternating gaze between the infant and the toy, while in the…

  6. Design and Use of a Learning Object for Finding Complex Polynomial Roots

    Science.gov (United States)

    Benitez, Julio; Gimenez, Marcos H.; Hueso, Jose L.; Martinez, Eulalia; Riera, Jaime

    2013-01-01

    Complex numbers are essential in many fields of engineering, but students often fail to have a natural insight of them. We present a learning object for the study of complex polynomials that graphically shows that any complex polynomials has a root and, furthermore, is useful to find the approximate roots of a complex polynomial. Moreover, we…

  7. Development and Factor Analysis of an Instrument to Measure Preservice Teachers' Perceptions of Learning Objects

    Science.gov (United States)

    Sahin, Sami

    2010-01-01

    The purpose of this study was to develop a questionnaire to measure student teachers' perception of digital learning objects. The participants included 308 voluntary senior students attending courses in a college of education of a public university in Turkey. The items were extracted to their related factors by the principal axis factoring method.…

  8. Examining the Use of Web-Based Reusable Learning Objects by Animal and Veterinary Nursing Students

    Science.gov (United States)

    Chapman-Waterhouse, Emily; Silva-Fletcher, Ayona; Whittlestone, Kim David

    2016-01-01

    This intervention study examined the interaction of animal and veterinary nursing students with reusable learning objects (RLO) in the context of preparing for summative assessment. Data was collected from 199 undergraduates using quantitative and qualitative methods. Students accessed RLO via personal devices in order to reinforce taught…

  9. Development and Implementation Costs of Student Learning Objectives: Considerations for TIF Grantees

    Science.gov (United States)

    Fermanich, Mark; Carl, Brad; Finster, Matthew

    2015-01-01

    This brief explores the costs of developing and implementing Student Learning Objectives (SLOs) in order to help Teacher Incentive Fund (TIF) grantees interested in adopting SLOs anticipate and understand the costs of implementing them in a district or school. The brief focuses on the costs involved with the initial design and implementation of an…

  10. Experiences with Reusable E-Learning Objects: From Theory to Practice.

    Science.gov (United States)

    Muzio, Jeanette A.; Heins, Tanya; Mundell, Roger

    2002-01-01

    Explains reusable electronic learning objects (ELOs) that are stored in a database and discusses the practical application of creating and reusing ELOs at Royal Roads University (Canada). Highlights include ELOs and the instructional design of online courses; and examples of using templates to develop interactive ELOs. (Author/LRW)

  11. Practicing doctors' perceptions on new learning objectives for Vietnamese medical schools

    NARCIS (Netherlands)

    Hoat, L; Dung, DV; Wright, E.P.

    2008-01-01

    Background. As part of the process to develop more community-oriented medical teaching in Vietnam, eight medical schools prepared a set of standard learning objectives with attention to the needs of a doctor working with the community. Because they were prepared based on government documents and the

  12. A Learning Research Informed Design and Evaluation of a Web-Enhanced Object Oriented Programming Seminar

    Science.gov (United States)

    Georgantaki, Stavroula C.; Retalis, Symeon D.

    2007-01-01

    "Object-Oriented Programming" subject is included in the ACM Curriculum Guidelines for Undergraduate and Graduate Degree Programs in Computer Science as well as in Curriculum for K-12 Computer Science. In a few research studies learning problems and difficulties have been recorded, and therefore, specific pedagogical guidelines and…

  13. Designing Learning Object Repositories as Systems for Managing Educational Communities Knowledge

    Science.gov (United States)

    Sampson, Demetrios G.; Zervas, Panagiotis

    2013-01-01

    Over the past years, a number of international initiatives that recognize the importance of sharing and reusing digital educational resources among educational communities through the use of Learning Object Repositories (LORs) have emerged. Typically, these initiatives focus on collecting digital educational resources that are offered by their…

  14. Cloud Computing and Multi Agent System to improve Learning Object Paradigm

    Directory of Open Access Journals (Sweden)

    Ana B. Gil

    2015-05-01

    Full Text Available The paradigm of Learning Object provides Educators and Learners with the ability to access an extensive number of learning resources. To do so, this paradigm provides different technologies and tools, such as federated search platforms and storage repositories, in order to obtain information ubiquitously and on demand. However, the vast amount and variety of educational content, which is distributed among several repositories, and the existence of various and incompatible standards, technologies and interoperability layers among repositories, constitutes a real problem for the expansion of this paradigm. This study presents an agent-based architecture that uses the advantages provided by Cloud Computing platforms to deal with the open issues on the Learning Object paradigm.

  15. Students’ mathematical learning in modelling activities

    DEFF Research Database (Denmark)

    Kjeldsen, Tinne Hoff; Blomhøj, Morten

    2013-01-01

    Ten years of experience with analyses of students’ learning in a modelling course for first year university students, led us to see modelling as a didactical activity with the dual goal of developing students’ modelling competency and enhancing their conceptual learning of mathematical concepts i...... create and help overcome hidden cognitive conflicts in students’ understanding; that reflections within modelling can play an important role for the students’ learning of mathematics. These findings are illustrated with a modelling project concerning the world population....

  16. Farm Planning by Fuzzy Multi Objective Programming Model

    Directory of Open Access Journals (Sweden)

    m Raei Jadidi

    2010-05-01

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

  17. Challenges of Transitioning to an e-Learning System with Learning Objects Capabilities

    Science.gov (United States)

    Raspopovic, Miroslava; Cvetanovic, Svetlana; Jankulovic, Aleksandar

    2016-01-01

    In order for higher education institutions, which implements blended and/or online learning to remain competitive and innovative it needs to keep up with the cutting edge technological and educational advances. This task is usually very difficult, keeping in mind the budget constraints that many institutions have. This usually implies that…

  18. Learning Object Repositories in e-Learning: Challenges for Learners in Saudi Arabia

    Science.gov (United States)

    AlMegren, Abdullah; Yassin, Siti Zuraiyni

    2013-01-01

    The advent of the millennium has seen the introduction of a new paradigm for ICT-enhanced education. Advances in ICT have led to the emergence of learning networks comprising people who want to discover and share various innovative technologies on a global scale. Over the past decade, there has been tremendous worldwide interest in the concept of…

  19. Group-Based Active Learning of Classification Models.

    Science.gov (United States)

    Luo, Zhipeng; Hauskrecht, Milos

    2017-05-01

    Learning of classification models from real-world data often requires additional human expert effort to annotate the data. However, this process can be rather costly and finding ways of reducing the human annotation effort is critical for this task. The objective of this paper is to develop and study new ways of providing human feedback for efficient learning of classification models by labeling groups of examples. Briefly, unlike traditional active learning methods that seek feedback on individual examples, we develop a new group-based active learning framework that solicits label information on groups of multiple examples. In order to describe groups in a user-friendly way, conjunctive patterns are used to compactly represent groups. Our empirical study on 12 UCI data sets demonstrates the advantages and superiority of our approach over both classic instance-based active learning work, as well as existing group-based active-learning methods.

  20. Peer-to-Peer Learning and the Army Learning Model

    Science.gov (United States)

    2012-06-08

    education will be delivered to the current and future force. This thesis examined the salient areas proposed by the ALM and its impact on P2P learning ...The Army Learning Model is the new educational model that develops adaptive leaders in an era of persistent conflict. Life-long, individual

  1. Inquiry based learning as didactic model in distant learning

    NARCIS (Netherlands)

    Rothkrantz, L.J.M.

    2015-01-01

    Recent years many universities are involved in development of Massive Open Online Courses (MOOCs). Unfortunately an appropriate didactic model for cooperated network learning is lacking. In this paper we introduce inquiry based learning as didactic model. Students are assumed to ask themselves

  2. Remote object authentication: confidence model, cryptosystem and protocol

    Science.gov (United States)

    Lancrenon, Jean; Gillard, Roland; Fournel, Thierry

    2009-04-01

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

  3. Special Aspects of Learning Objectives Design for Disciplines in Engineering Education

    Directory of Open Access Journals (Sweden)

    Yu. B. Tsvetkov

    2015-01-01

    Full Text Available The article is devoted to a problem of learning objectives design for disciplines in engineering education. It is shown that the system of well defined objectives can form a basis of discipline content analysis, acquisition control and improvement.The detailed defining of clear objectives and designing forms and content of objectives which allow to estimate their achievement are considered.For this purpose the objectives should consider the level of learners, to designate result which they will be able to show after training, conditions and how well they will be able to make it.Some examples of objective formulations are provided which allow to show in an explicit form the results reached by a learner.It is shown that cognitive process dimension can be divided into groups of initial level of thinking (to remember, understand, apply and thinking of high level (to analyze, estimate, create.Thus knowledge dimension include the factual, conceptual, procedural and metacognitive knowledges.On the basis of cognitive process dimension and knowledge dimension in engineering education it is offered to form system of learning objectives on the basis of their twodimensional classification - taxonomy.Objectives examples for engineering discipline are given. They consider conditions of their achievement and criteria of execution for various combinations of cognitive process dimension and levels of knowledge dimension.For some engineering disciplines examples of learning objectives are formulated including their achievement and criterion of execution of the corresponding actions.The given results can form a basis for design of learning objectives at realization of a competence approach in modern engineering education.Further work in this direction preplan the analysis and approbation of two-dimensional matrix applicability for objectives design on examples of various engineering disciplines.It is of profound importance to use matrixes of well defined

  4. MODELING OF CONVECTIVE STREAMS IN PNEUMOBASIC OBJECTS (Part 2

    Directory of Open Access Journals (Sweden)

    B. M. Khroustalev

    2015-01-01

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

  5. THE INVESTMENT MODEL OF THE CONSTRUCTION OF PUBLIC OBJECTS

    Directory of Open Access Journals (Sweden)

    Reperger Šandor

    2009-11-01

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

  6. Wind field and trajectory models for tornado-propelled objects

    International Nuclear Information System (INIS)

    Anon

    1978-01-01

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

  7. Humanoid infers Archimedes' principle: understanding physical relations and object affordances through cumulative learning experiences

    Science.gov (United States)

    2016-01-01

    Emerging studies indicate that several species such as corvids, apes and children solve ‘The Crow and the Pitcher’ task (from Aesop's Fables) in diverse conditions. Hidden beneath this fascinating paradigm is a fundamental question: by cumulatively interacting with different objects, how can an agent abstract the underlying cause–effect relations to predict and creatively exploit potential affordances of novel objects in the context of sought goals? Re-enacting this Aesop's Fable task on a humanoid within an open-ended ‘learning–prediction–abstraction’ loop, we address this problem and (i) present a brain-guided neural framework that emulates rapid one-shot encoding of ongoing experiences into a long-term memory and (ii) propose four task-agnostic learning rules (elimination, growth, uncertainty and status quo) that correlate predictions from remembered past experiences with the unfolding present situation to gradually abstract the underlying causal relations. Driven by the proposed architecture, the ensuing robot behaviours illustrated causal learning and anticipation similar to natural agents. Results further demonstrate that by cumulatively interacting with few objects, the predictions of the robot in case of novel objects converge close to the physical law, i.e. the Archimedes principle: this being independent of both the objects explored during learning and the order of their cumulative exploration. PMID:27466440

  8. Learning object location predictors with boosting and grammar-guided feature extraction

    Energy Technology Data Exchange (ETDEWEB)

    Eads, Damian Ryan [Los Alamos National Laboratory; Rosten, Edward [UNIV OF CAMBRIDGE; Helmbold, David [UC/SANTA CRUZ

    2009-01-01

    The authors present BEAMER: a new spatially exploitative approach to learning object detectors which shows excellent results when applied to the task of detecting objects in greyscale aerial imagery in the presence of ambiguous and noisy data. There are four main contributions used to produce these results. First, they introduce a grammar-guided feature extraction system, enabling the exploration of a richer feature space while constraining the features to a useful subset. This is specified with a rule-based generative grammer crafted by a human expert. Second, they learn a classifier on this data using a newly proposed variant of AdaBoost which takes into account the spatially correlated nature of the data. Third, they perform another round of training to optimize the method of converting the pixel classifications generated by boosting into a high quality set of (x,y) locations. lastly, they carefully define three common problems in object detection and define two evaluation criteria that are tightly matched to these problems. Major strengths of this approach are: (1) a way of randomly searching a broad feature space, (2) its performance when evaluated on well-matched evaluation criteria, and (3) its use of the location prediction domain to learn object detectors as well as to generate detections that perform well on several tasks: object counting, tracking, and target detection. They demonstrate the efficacy of BEAMER with a comprehensive experimental evaluation on a challenging data set.

  9. Alignment of learning objectives and assessments in therapeutics courses to foster higher-order thinking.

    Science.gov (United States)

    FitzPatrick, Beverly; Hawboldt, John; Doyle, Daniel; Genge, Terri

    2015-02-17

    To determine whether national educational outcomes, course objectives, and classroom assessments for 2 therapeutics courses were aligned for curricular content and cognitive processes, and if they included higher-order thinking. Document analysis and student focus groups were used. Outcomes, objectives, and assessment tasks were matched for specific therapeutics content and cognitive processes. Anderson and Krathwohl's Taxonomy was used to define higher-order thinking. Students discussed whether assessments tested objectives and described their thinking when responding to assessments. There were 7 outcomes, 31 objectives, and 412 assessment tasks. The alignment for content and cognitive processes was not satisfactory. Twelve students participated in the focus groups. Students thought more short-answer questions than multiple choice questions matched the objectives for content and required higher-order thinking. The alignment analysis provided data that could be used to reveal and strengthen the enacted curriculum and improve student learning.

  10. DEVELOPMENT OF SCIENCE PROCESS SKILLS STUDENTS WITH PROJECT BASED LEARNING MODEL- BASED TRAINING IN LEARNING PHYSICS

    Directory of Open Access Journals (Sweden)

    Ratna Malawati

    2016-06-01

    Full Text Available This study aims to improve the physics Science Process Skills Students on cognitive and psychomotor aspects by using model based Project Based Learning training.The object of this study is the Project Based Learning model used in the learning process of Computationa Physics.The method used is classroom action research through two learning cycles, each cycle consisting of the stages of planning, implementation, observation and reflection. In the first cycle of treatment with their emphasis given training in the first phase up to third in the model Project Based Learning, while the second cycle is given additional treatment with emphasis discussion is collaboration in achieving the best results for each group of products. The results of data analysis showed increased ability to think Students on cognitive and Science Process Skills in the psychomotor.

  11. The Computer Book of the Internal Medicine Resident: competence acquisition and achievement of learning objectives.

    Science.gov (United States)

    Oristrell, J; Oliva, J C; Casanovas, A; Comet, R; Jordana, R; Navarro, M

    2014-01-01

    The Computer Book of the Internal Medicine resident (CBIMR) is a computer program that was validated to analyze the acquisition of competences in teams of Internal Medicine residents. To analyze the characteristics of the rotations during the Internal Medicine residency and to identify the variables associated with the acquisition of clinical and communication skills, the achievement of learning objectives and resident satisfaction. All residents of our service (n=20) participated in the study during a period of 40 months. The CBIMR consisted of 22 self-assessment questionnaires specific for each rotation, with items on services (clinical workload, disease protocolization, resident responsibilities, learning environment, service organization and teamwork) and items on educational outcomes (acquisition of clinical and communication skills, achievement of learning objectives, overall satisfaction). Associations between services features and learning outcomes were analyzed using bivariate and multivariate analysis. An intense clinical workload, high resident responsibilities and disease protocolization were associated with the acquisition of clinical skills. High clinical competence and teamwork were both associated with better communication skills. Finally, an adequate learning environment was associated with increased clinical competence, the achievement of educational goals and resident satisfaction. Potentially modifiable variables related with the operation of clinical services had a significant impact on the acquisition of clinical and communication skills, the achievement of educational goals, and resident satisfaction during the specialized training in Internal Medicine. Copyright © 2013 Elsevier España, S.L. All rights reserved.

  12. E-learning teaches attendings "how to" objectively assess pediatric urology trainees' surgery skills for orchiopexy.

    Science.gov (United States)

    Fernandez, Nicolas; Maizels, Max; Farhat, Walid; Smith, Edwin; Liu, Dennis; Chua, Michael; Bhanji, Yasin

    2018-04-01

    Established methods to train pediatric urology surgery by residency training programs require updating in response to administrative changes such as new, reduced trainee duty hours. Therefore, new objective methods must be developed to teach trainees. We approached this need by creating e-learning to teach attendings objective assessment of trainee skills using the Zwisch scale, an established assessment tool. The aim of this study was to identify whether or not e-learning is an appropriate platform for effective teaching of this assessment tool, by assessing inter-rater correlation of assessments made by the attendings after participation in the e-learning. Pediatric orchiopexy was used as the index case. An e-learning tool was created to teach attending surgeons objective assessment of trainees' surgical skills. First, e-learning content was created which showed the assessment method videotape of resident surgery done in the operating room. Next, attendings were enrolled to e-learn this method. Finally, the ability of enrollees to assess resident surgery skill performance was tested. Namely, test video was made showing a trainee performing inguinal orchiopexy. All enrollees viewed the same online videos. Assessments of surgical skills (Zwisch scale) were entered into an online survey. Data were analyzed by intercorrelation coefficient kappa analysis (strong correlation was ICC ≥ 0.7). A total of 11 attendings were enrolled. All accessed the online learning and then made assessments of surgical skills trainees showed on videotapes. The e-learning comprised three modules: 1. "Core concepts," in which users learned the assessment tool methods; 2. "Learn to assess," in which users learned how to assess by watching video clips, explaining the assessment method; and 3. "Test," in which users tested their skill at making assessments by watching video clips and then actively inputting their ratings of surgical and global skills as viewed in the video clips (Figure

  13. Model-observer similarity, error modeling and social learning in rhesus macaques.

    Directory of Open Access Journals (Sweden)

    Elisabetta Monfardini

    Full Text Available Monkeys readily learn to discriminate between rewarded and unrewarded items or actions by observing their conspecifics. However, they do not systematically learn from humans. Understanding what makes human-to-monkey transmission of knowledge work or fail could help identify mediators and moderators of social learning that operate regardless of language or culture, and transcend inter-species differences. Do monkeys fail to learn when human models show a behavior too dissimilar from the animals' own, or when they show a faultless performance devoid of error? To address this question, six rhesus macaques trained to find which object within a pair concealed a food reward were successively tested with three models: a familiar conspecific, a 'stimulus-enhancing' human actively drawing the animal's attention to one object of the pair without actually performing the task, and a 'monkey-like' human performing the task in the same way as the monkey model did. Reward was manipulated to ensure that all models showed equal proportions of errors and successes. The 'monkey-like' human model improved the animals' subsequent object discrimination learning as much as a conspecific did, whereas the 'stimulus-enhancing' human model tended on the contrary to retard learning. Modeling errors rather than successes optimized learning from the monkey and 'monkey-like' models, while exacerbating the adverse effect of the 'stimulus-enhancing' model. These findings identify error modeling as a moderator of social learning in monkeys that amplifies the models' influence, whether beneficial or detrimental. By contrast, model-observer similarity in behavior emerged as a mediator of social learning, that is, a prerequisite for a model to work in the first place. The latter finding suggests that, as preverbal infants, macaques need to perceive the model as 'like-me' and that, once this condition is fulfilled, any agent can become an effective model.

  14. Development of Learning Virtual Objects as a Strategy to Foster Student Retention in Higher Education

    Directory of Open Access Journals (Sweden)

    Yois S. Pascuas Rengifo

    2015-12-01

    Full Text Available Rev.esc.adm.neg One of the problems that the Colombian higher education system is facing is the problem of student desertion, shwoing that a great amount of students leave their university studies during the first semesters. For this reason, the National Education Ministry and Universidad de la Amazonia implement a new strategy to foster student retention and graduation through academic levelling. This paper shows eight learning virtual objects from different learning áreas, applying technological tolos to design didactic interactive and creative environments.

  15. The effect of learning models and emotional intelligence toward students learning outcomes on reaction rate

    Science.gov (United States)

    Sutiani, Ani; Silitonga, Mei Y.

    2017-08-01

    This research focused on the effect of learning models and emotional intelligence in students' chemistry learning outcomes on reaction rate teaching topic. In order to achieve the objectives of the research, with 2x2 factorial research design was used. There were two factors tested, namely: the learning models (factor A), and emotional intelligence (factor B) factors. Then, two learning models were used; problem-based learning/PBL (A1), and project-based learning/PjBL (A2). While, the emotional intelligence was divided into higher and lower types. The number of population was six classes containing 243 grade X students of SMAN 10 Medan, Indonesia. There were 15 students of each class were chosen as the sample of the research by applying purposive sampling technique. The data were analyzed by applying two-ways analysis of variance (2X2) at the level of significant α = 0.05. Based on hypothesis testing, there was the interaction between learning models and emotional intelligence in students' chemistry learning outcomes. Then, the finding of the research showed that students' learning outcomes in reaction rate taught by using PBL with higher emotional intelligence is higher than those who were taught by using PjBL. There was no significant effect between students with lower emotional intelligence taught by using both PBL and PjBL in reaction rate topic. Based on the finding, the students with lower emotional intelligence were quite hard to get in touch with other students in group discussion.

  16. Advertising Model of Residential Real Estate Object in Lithuania

    Directory of Open Access Journals (Sweden)

    Jelena Mazaj

    2012-07-01

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

  17. Objective Characterization of Snow Microstructure for Microwave Emission Modeling

    Science.gov (United States)

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

    2012-01-01

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

  18. A Model for Learning Development

    Science.gov (United States)

    Kilfoil, W. R.

    2008-01-01

    This article looks at the way in which people perceive learning and the impact of these perceptions on teaching methods within the context of learning development in distance education. The context could, in fact, be any type of teaching and learning environment. The point is to balance approaches to teaching and learning depending on student…

  19. AVIATION SECURITY AS AN OBJECT OF MATHEMATICAL MODELING

    Directory of Open Access Journals (Sweden)

    N. Elisov Lev

    2017-01-01

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

  20. Toward a Dexter-based model for open hypermedia: Unifying embedded references and link objects

    DEFF Research Database (Denmark)

    Grønbæk, Kaj; Trigg, Randall Hagner

    1996-01-01

    Nominated for the Doug Engelbart best paper award. This paper discusses experiences and lessons learned from the design of an open hypermedia system, one that integrates applications and data not ''owned'' by the hypermedia. The Dexter Hypertext Reference Model was used as the basis for the design....... Though our experiences were generally positive, we found the model constraining in certain ways and underdeveloped in others. For instance, Dexter argues against dangling links, but we found several situations where permitting and supporting dangling links was advisable. In Dexter, the data objects...

  1. Learning Clinical Procedures Through Internet Digital Objects: Experience of Undergraduate Students Across Clinical Faculties.

    Science.gov (United States)

    Li, Tse Yan; Gao, Xiaoli; Wong, Kin; Tse, Christine Shuk Kwan; Chan, Ying Yee

    2015-04-14

    Various digital learning objects (DLOs) are available via the World Wide Web, showing the flow of clinical procedures. It is unclear to what extent these freely accessible Internet DLOs facilitate or hamper students' acquisition of clinical competence. This study aimed to understand the experience of undergraduate students across clinical disciplines-medicine, dentistry, and nursing-in using openly accessible Internet DLOs, and to investigate the role of Internet DLOs in facilitating their clinical learning. Mid-year and final-year groups were selected from each undergraduate clinical degree program of the University of Hong Kong-Bachelor of Medicine and Bachelor of Surgery (MBBS), Bachelor of Dental Surgery (BDS), and Bachelor of Nursing (BNurs). All students were invited to complete a questionnaire on their personal and educational backgrounds, and their experiences and views on using Internet DLOs in learning clinical procedures. The questionnaire design was informed by the findings of six focus groups. Among 439 respondents, 97.5% (428/439) learned a variety of clinical procedures through Internet DLOs. Most nursing students (107/122, 87.7%) learned preventive measures through Internet DLOs, with a lower percentage of medical students (99/215, 46.0%) and dental students (43/96, 45%) having learned them this way (both Plearning in the planned curriculum. This trend calls for a transformation of the educator's role from dispensing knowledge to guidance and support.

  2. Linking actions and objects: Context-specific learning of novel weight priors.

    Science.gov (United States)

    Trewartha, Kevin M; Flanagan, J Randall

    2017-06-01

    Distinct explicit and implicit memory processes support weight predictions used when lifting objects and making perceptual judgments about weight, respectively. The first time that an object is encountered weight is predicted on the basis of learned associations, or priors, linking size and material to weight. A fundamental question is whether the brain maintains a single, global representation of priors, or multiple representations that can be updated in a context specific way. A second key question is whether the updating of priors, or the ability to scale lifting forces when repeatedly lifting unusually weighted objects requires focused attention. To investigate these questions we compared the adaptability of weight predictions used when lifting objects and judging their weights in different groups of participants who experienced size-weight inverted objects passively (with the objects placed on the hands) or actively (where participants lift the objects) under full or divided attention. To assess weight judgments we measured the size-weight illusion after every 20 trials of experience with the inverted objects both passively and actively. The attenuation of the illusion that arises when lifting inverted object was found to be context-specific such that the attenuation was larger when the mode of interaction with the inverted objects matched the method of assessment of the illusion. Dividing attention during interaction with the inverted objects had no effect on attenuation of the illusion, but did slow the rate at which lifting forces were scaled to the weight inverted objects. These findings suggest that the brain stores multiple representations of priors that are context specific, and that focused attention is important for scaling lifting forces, but not for updating weight predictions used when judging object weight. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Blended learning models for directing the self-learning activity of “Software Engineering” specialty students

    Directory of Open Access Journals (Sweden)

    Vera V. Lyubchenko

    2014-12-01

    Full Text Available The adoption of Law of Ukraine “On Higher Education” (2014 involves the increase in students’ self-learning activity part in the curriculum. Therefore the self-learning activities’ arrangement in a way augmenting the result quality becomes a top priority task. This research objective consists in elaborating the scenario for organization of the students’ qualitative self-study, based on blended learning models. The author analyzes four blended learning models: the rotation model, flex-model, self-blend model and online driver model, and gives examples of their use. It is shown that first two models are the most suitable for full-time students. A general scenario for the use of blended learning models is described. Although the use of blended learning models causes several difficulties, it also essentially contributes into students’ self-study monitoring and control support.

  4. Modeling of Geological Objects and Geophysical Fields Using Haar Wavelets

    Directory of Open Access Journals (Sweden)

    A. S. Dolgal

    2014-12-01

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

  5. Quantum superposition of massive objects and collapse models

    International Nuclear Information System (INIS)

    Romero-Isart, Oriol

    2011-01-01

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

  6. Quantum superposition of massive objects and collapse models

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-11-15

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

  7. The Proposed Model of Collaborative Virtual Learning Environment for Introductory Programming Course

    Science.gov (United States)

    Othman, Mahfudzah; Othman, Muhaini

    2012-01-01

    This paper discusses the proposed model of the collaborative virtual learning system for the introductory computer programming course which uses one of the collaborative learning techniques known as the "Think-Pair-Share". The main objective of this study is to design a model for an online learning system that facilitates the…

  8. Hierarchical Bayesian Models of Subtask Learning

    Science.gov (United States)

    Anglim, Jeromy; Wynton, Sarah K. A.

    2015-01-01

    The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…

  9. Connected Component Model for Multi-Object Tracking.

    Science.gov (United States)

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

    2016-08-01

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

  10. Interactive object modelling based on piecewise planar surface patches.

    Science.gov (United States)

    Prankl, Johann; Zillich, Michael; Vincze, Markus

    2013-06-01

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

  11. Interactive object modelling based on piecewise planar surface patches☆

    Science.gov (United States)

    Prankl, Johann; Zillich, Michael; Vincze, Markus

    2013-01-01

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

  12. A knowledge discovery object model API for Java

    Directory of Open Access Journals (Sweden)

    Jones Steven JM

    2003-10-01

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

  13. Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors

    Directory of Open Access Journals (Sweden)

    Monica Villaverde

    2015-11-01

    Full Text Available The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

  14. Construction and validation of a virtual learning object on intestinal elimination stoma

    Directory of Open Access Journals (Sweden)

    Cecílio Soares Rodrigues Braga

    Full Text Available Objective.To construct and validate a virtual learning object (VLO on intestinal elimination stoma. Methods. Applied, descriptive and quantitative study. In 2014, eight stoma therapists and eight experts in computer science took part of the research. The VLO included four steps: i planning, ii construction of VLO and changes of content; iii development of dynamic, and iv conclusion and analysis. The VLO was inserted into the Moodle virtual learning environment. The ergonomic and pedagogical validation of the VLO was performed. Results. The experts appreciated the VLO satisfactorily, and scored it between good and full agreement. Conclusion. The VLO on intestinal elimination stoma is a tool that can be implemented at undergraduate programs in nursing and continuing education programs for nurses in clinical practice, contributing significantly to improve the theoretical skills necessary for the care of ostomized people safely, with quality and enabling self-care.

  15. Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

    Science.gov (United States)

    Villaverde, Monica; Perez, David; Moreno, Felix

    2015-11-17

    The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

  16. Multi-agent system for Knowledge-based recommendation of Learning Objects

    Directory of Open Access Journals (Sweden)

    Paula Andrea RODRÍGUEZ MARÍN

    2015-12-01

    Full Text Available Learning Object (LO is a content unit being used within virtual learning environments, which -once found and retrieved- may assist students in the teaching - learning process. Such LO search and retrieval are recently supported and enhanced by data mining techniques. In this sense, clustering can be used to find groups holding similar LOs so that from obtained groups, knowledge-based recommender systems (KRS can recommend more adapted and relevant LOs. In particular, prior knowledge come from LOs previously selected, liked and ranked by the student to whom the recommendation will be performed. In this paper, we present a KRS for LOs, which uses a conventional clustering technique, namely K-means, aimed at finding similar LOs and delivering resources adapted to a specific student. Obtained promising results show that proposed KRS is able to both retrieve relevant LO and improve the recommendation precision.Learning Object (LO is a content unit being used within virtual learning environments, which -once found and retrieved- may assist students in the teaching - learning process. Such LO search and retrieval are recently supported and enhanced by data mining techniques. In this sense, clustering can be used to find groups holding similar LOs so that from obtained groups, knowledge-based recommender systems (KRS can recommend more adapted and relevant LOs. In particular, prior knowledge come from LOs previously selected, liked and ranked by the student to whom the recommendation will be performed. In this paper, we present a KRS for LOs, which uses a conventional clustering technique, namely K-means, aimed at finding similar LOs and delivering resources adapted to a specific student. Obtained promising results show that proposed KRS is able to both retrieve relevant LO and improve the recommendation precision.

  17. SED Modeling of 20 Massive Young Stellar Objects

    Science.gov (United States)

    Tanti, Kamal Kumar

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

  18. Mathematical model of innovative sustainability “green” construction object

    Directory of Open Access Journals (Sweden)

    Slesarev Michail

    2016-01-01

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

  19. Objective models of compressed breast shapes undergoing mammography

    Science.gov (United States)

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

    2013-01-01

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

  20. Objective models of compressed breast shapes undergoing mammography

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-03-15

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

  1. Objective models of compressed breast shapes undergoing mammography

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  2. The Role of Reusable Learning Objects in Occupational Therapy Entry-Level Education

    Directory of Open Access Journals (Sweden)

    Bryan M. Gee

    2014-10-01

    Full Text Available Out of early research, Cisco Systems (1999 have built an impressive foundation that advocates for reusable learning objects (RLOs. As the need for online methods for delivering both formal and informal educational content has increased, the prospect of greater influence through carefully constructed RLOs has grown. RLOs are any digital resource that can be used and reused to enhance online learning. RLOs typically are small, discrete, self-contained digital objects that may be sequenced, combined, and used within a variety of instructional activities. RLOs have been implemented in nursing, pharmacy, and physician assistant programs. However, there is a lack of literature regarding RLOs in occupational therapy education. An attitudinal survey was administered to occupational therapy students after they had used an RLO focused on goal writing. Student preferences toward RLO content, instructional design, and eLearning were generally positive. Nearly three-quarters of the students who responded to the survey indicated that the RLO presented was beneficial. All respondents noted that they would use the RLO for future occupational therapy courses. It is argued that incorporating RLOs offers a cost-effective, efficient learning tool, and also adds credibility to the given curriculum program as being innovative with instructing occupational-therapy related concepts.

  3. Embedded or linked learning objects: Implications for content development, course design and classroom use

    Directory of Open Access Journals (Sweden)

    Gail Kopp

    2007-06-01

    Full Text Available This research explores the idea of embedding and linking to existing content in learning object repositories and investigates teacher-designer use of learning objects within one high school mathematics course in an online school. This qualitative case study supports and extends the learning object literature, and brings forward context-specific examples of issues around repository design, autonomy and self-containment, technical support and granularity. Moreover, these findings have implications for building learning objects and repositories that could better support teachers in their instructional design and pedagogical decision-making. Résumé : La présente recherche étudie la possibilité d’effectuer un emboîtement et d’établir des liens avec le contenu existant dans les référentiels sur les objets d’apprentissage et explore l’utilisation par les enseignants-concepteurs des objets d’apprentissage au sein d’un cours de mathématique du secondaire donné dans une école en ligne. Cette étude de cas qualitative appuie et vise la littérature sur les objets d’apprentissage et met en avant plan des exemples de questions touchant la conception de référentiels, l’autonomie et l’indépendance, le soutien technique et la granularité propres au contexte. De plus, ces conclusions ont des répercussions sur l’élaboration d’objets et de référentiels d’apprentissage qui pourraient mieux appuyer les enseignants dans le cadre de leur conception pédagogique et de leur prise de décision touchant l’enseignement.

  4. Learning Markov Decision Processes for Model Checking

    DEFF Research Database (Denmark)

    Mao, Hua; Chen, Yingke; Jaeger, Manfred

    2012-01-01

    . The proposed learning algorithm is adapted from algorithms for learning deterministic probabilistic finite automata, and extended to include both probabilistic and nondeterministic transitions. The algorithm is empirically analyzed and evaluated by learning system models of slot machines. The evaluation......Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed for automatically learning system models based on observed system behaviors. In this paper we extend the algorithm...... on learning probabilistic automata to reactive systems, where the observed system behavior is in the form of alternating sequences of inputs and outputs. We propose an algorithm for automatically learning a deterministic labeled Markov decision process model from the observed behavior of a reactive system...

  5. 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.

  6. Object instance recognition using motion cues and instance specific appearance models

    Science.gov (United States)

    Schumann, Arne

    2014-03-01

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

  7. Machine learning in infrared object classification - an all-sky selection of YSO candidates

    Science.gov (United States)

    Marton, Gabor; Zahorecz, Sarolta; Toth, L. Viktor; Magnus McGehee, Peregrine; Kun, Maria

    2015-08-01

    Object classification is a fundamental and challenging problem in the era of big data. I will discuss up-to-date methods and their application to classify infrared point sources.We analysed the ALLWISE catalogue, the most recent public source catalogue of the Wide-field Infrared Survey Explorer (WISE) to compile a reliable list of Young Stellar Object (YSO) candidates. We tested and compared classical and up-to-date statistical methods as well, to discriminate source types like extragalactic objects, evolved stars, main sequence stars, objects related to the interstellar medium and YSO candidates by using their mid-IR WISE properties and associated near-IR 2MASS data.In the particular classification problem the Support Vector Machines (SVM), a class of supervised learning algorithm turned out to be the best tool. As a result we classify Class I and II YSOs with >90% accuracy while the fraction of contaminating extragalactic objects remains well below 1%, based on the number of known objects listed in the SIMBAD and VizieR databases. We compare our results to other classification schemes from the literature and show that the SVM outperforms methods that apply linear cuts on the colour-colour and colour-magnitude space. Our homogenous YSO candidate catalog can serve as an excellent pathfinder for future detailed observations of individual objects and a starting point of statistical studies that aim to add pieces to the big picture of star formation theory.

  8. 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.

  9. Caka E-Learning Model

    Science.gov (United States)

    Gorsev, Gonca; Turkmen, Ugur; Askin, Cihat

    2017-01-01

    In today's world, in order to obtain the information in education, various approaches, methods and devices have been developed. Like many developing countries, e-learning and distance learning (internet based learning) are used today in many areas of education in Turkey. This research aims to contribute to education systems and develop a…

  10. Polarimetry of Solar System Objects: Observations vs. Models

    Science.gov (United States)

    Yanamandra-Fisher, P. A.

    2014-04-01

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

  11. Learning Bayesian Dependence Model for Student Modelling

    Directory of Open Access Journals (Sweden)

    Adina COCU

    2008-12-01

    Full Text Available Learning a Bayesian network from a numeric set of data is a challenging task because of dual nature of learning process: initial need to learn network structure, and then to find out the distribution probability tables. In this paper, we propose a machine-learning algorithm based on hill climbing search combined with Tabu list. The aim of learning process is to discover the best network that represents dependences between nodes. Another issue in machine learning procedure is handling numeric attributes. In order to do that, we must perform an attribute discretization pre-processes. This discretization operation can influence the results of learning network structure. Therefore, we make a comparative study to find out the most suitable combination between discretization method and learning algorithm, for a specific data set.

  12. Small Schools Student Learning Objectives, 9-12: Mathematics, Reading, Reading in the Content Areas, Language Arts.

    Science.gov (United States)

    Nelson, JoAnne, Ed.; Hartl, David, Ed.

    Designed by Washington curriculum specialists and secondary teachers to assist teachers in small schools with the improvement of curriculum and instruction and to aid smaller districts lacking curriculum personnel to comply with Washington's Student Learning Objectives Law, this handbook contains learning objectives in the areas of language arts,…

  13. Video Cases in Teacher Education: A review study on intended and achieved learning objectives by video cases

    NARCIS (Netherlands)

    Geerts, Walter; Van der Werff, Anne; Hummel, Hans; Van Geert, Paul

    2014-01-01

    This literature review focuses on the use of video cases in the education of preservice teachers as a means of achieving higher order learning objectives that are necessary for gaining situated knowledge. An overview of both intended and achieved learning objectives in relevant studies involving

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

    Science.gov (United States)

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

    2012-12-01

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

  15. Integrated Model for E-Learning Acceptance

    Science.gov (United States)

    Ramadiani; Rodziah, A.; Hasan, S. M.; Rusli, A.; Noraini, C.

    2016-01-01

    E-learning is not going to work if the system is not used in accordance with user needs. User Interface is very important to encourage using the application. Many theories had discuss about user interface usability evaluation and technology acceptance separately, actually why we do not make it correlation between interface usability evaluation and user acceptance to enhance e-learning process. Therefore, the evaluation model for e-learning interface acceptance is considered important to investigate. The aim of this study is to propose the integrated e-learning user interface acceptance evaluation model. This model was combined some theories of e-learning interface measurement such as, user learning style, usability evaluation, and the user benefit. We formulated in constructive questionnaires which were shared at 125 English Language School (ELS) students. This research statistics used Structural Equation Model using LISREL v8.80 and MANOVA analysis.

  16. Learning objects? Nurse educators' views on using patients for student learning : ethics and consent.

    Science.gov (United States)

    Torrance, C; Mansell, I; Wilson, C

    2012-11-01

    This study explored the views of nursing lecturers concerning the use of patients in nursing education, particularly in light of the development of additional learning opportunities such as clinical simulation. Focus group interviews involving 19 educators from one school of nursing in the United Kingdom were held. An interview schedule was developed by the study team from the findings of a focused literature review of the area. The focus groups were audio-taped and transcribed into NVivo (version 8) for analysis and identification of emergent themes. Four major categories emerged from the data analysis: clinical placement; patient consent; educator conflict; and developing competency. The themes of clinical placement and patient consent are presented in this paper. Clinical placement revealed two sub-themes: historical custom and practice and safety. Four sub-themes emerged from the theme of patient consent: informed consent; implied consent; capacity to consent; and patients' value of student involvement in their care. Educators believed that patients benefit from being cared for by well-qualified nurses and to achieve this it is necessary for patients to participate in clinical training. The predominant view seemed to be one of historical necessity; essentially, it has always been done that way so it has to continue that way. There was an awareness of the need for staff and students to consider the patient's rights and wishes, but the prevailing sentiment seemed to be that informed consent and choice were secondary to patient safety and the need to train student nurses. There is some conflict between the need for educating health professions and the Kantian view of never using the patients as a means to an end. Using patients for nursing education may be ethical as long as the patient is fully informed and involved in the decision-making process.

  17. Object-Location-Aware Hashing for Multi-Label Image Retrieval via Automatic Mask Learning.

    Science.gov (United States)

    Huang, Chang-Qin; Yang, Shang-Ming; Pan, Yan; Lai, Han-Jiang

    2018-09-01

    Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep supervised hashing method for multi-label image retrieval, in which we propose to learn a binary "mask" map that can identify the approximate locations of objects in an image, so that we use this binary "mask" map to obtain length-limited hash codes which mainly focus on an image's objects but ignore the background. The proposed deep architecture consists of four parts: 1) a convolutional sub-network to generate effective image features; 2) a binary "mask" sub-network to identify image objects' approximate locations; 3) a weighted average pooling operation based on the binary "mask" to obtain feature representations and hash codes that pay most attention to foreground objects but ignore the background; and 4) the combination of a triplet ranking loss designed to preserve relative similarities among images and a cross entropy loss defined on image labels. We conduct comprehensive evaluations on four multi-label image data sets. The results indicate that the proposed hashing method achieves superior performance gains over the state-of-the-art supervised or unsupervised hashing baselines.

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

    Directory of Open Access Journals (Sweden)

    Giulia Vezzani

    2017-11-01

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

  19. Visuo-motor coordination and internal models for object interception.

    Science.gov (United States)

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

    2009-02-01

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

  20. Improving Student Learning Outcomes Marketing Strategy Lesson By Applying SFAE Learning Model

    Directory of Open Access Journals (Sweden)

    Winda Nur Rohmawati

    2017-11-01

    Full Text Available Research objectives for improving student learning outcomes on the subjects of marketing strategy through the implementation of model learning SFAE. This type of research this is a class action research using a qualitative approach which consists of two cycles with the subject Marketing X grade SMK YPI Darussalam 2 Cerme Gresik Regency. This research consists of four stages: (1 the Planning Act, (2 the implementation of the action, (3 observations (observation, and (4 Reflection. The result of the research shows that cognitive and affective learning outcomes of students have increased significantly.

  1. The Kinematic Learning Model using Video and Interfaces Analysis

    Science.gov (United States)

    Firdaus, T.; Setiawan, W.; Hamidah, I.

    2017-09-01

    An educator currently in demand to apply the learning to not be separated from the development of technology. Educators often experience difficulties when explaining kinematics material, this is because kinematics is one of the lessons that often relate the concept to real life. Kinematics is one of the courses of physics that explains the cause of motion of an object, Therefore it takes the thinking skills and analytical skills in understanding these symptoms. Technology is one that can bridge between conceptual relationship with real life. A framework of technology-based learning models has been developed using video and interfaces analysis on kinematics concept. By using this learning model, learners will be better able to understand the concept that is taught by the teacher. This learning model is able to improve the ability of creative thinking, analytical skills, and problem-solving skills on the concept of kinematics.

  2. SUSTAIN: a network model of category learning.

    Science.gov (United States)

    Love, Bradley C; Medin, Douglas L; Gureckis, Todd M

    2004-04-01

    SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told that a bat is a mammal instead of a bird), SUSTAIN recruits an additional cluster to represent the surprising event. Newly recruited clusters are available to explain future events and can themselves evolve into prototypes-attractors-rules. SUSTAIN's discovery of category substructure is affected not only by the structure of the world but by the nature of the learning task and the learner's goals. SUSTAIN successfully extends category learning models to studies of inference learning, unsupervised learning, category construction, and contexts in which identification learning is faster than classification learning.

  3. Learning and Control Model of the Arm for Loading

    Science.gov (United States)

    Kim, Kyoungsik; Kambara, Hiroyuki; Shin, Duk; Koike, Yasuharu

    We propose a learning and control model of the arm for a loading task in which an object is loaded onto one hand with the other hand, in the sagittal plane. Postural control during object interactions provides important points to motor control theories in terms of how humans handle dynamics changes and use the information of prediction and sensory feedback. For the learning and control model, we coupled a feedback-error-learning scheme with an Actor-Critic method used as a feedback controller. To overcome sensory delays, a feedforward dynamics model (FDM) was used in the sensory feedback path. We tested the proposed model in simulation using a two-joint arm with six muscles, each with time delays in muscle force generation. By applying the proposed model to the loading task, we showed that motor commands started increasing, before an object was loaded on, to stabilize arm posture. We also found that the FDM contributes to the stabilization by predicting how the hand changes based on contexts of the object and efferent signals. For comparison with other computational models, we present the simulation results of a minimum-variance model.

  4. OBJECTIVE STRUCTURED PRACTICAL EXAMINATION AS A LEARNING AND EVALUATION TOOL FOR BIOCHEMISTRY- FIRST EXPERIENCE

    Directory of Open Access Journals (Sweden)

    Vidyabati Devi Rajkumari

    2017-06-01

    Full Text Available BACKGROUND Assessment plays an important role in helping learners identify their own learning needs. The objective structured practical examination assesses practical skills in an objective and structured manner with direct observation of the students’ performance during planned clinical test. The aim of the study is to evaluate OSPE as a method of learning and formative assessment to the practical skill and to explore faculty perception of OSPE as a learning and assessment tool. MATERIALS AND METHODS A total of 98 students of first year MBBS student admitted for 2015-16 batch of Jawaharlal Nehru Institute of Medical Sciences, Imphal, were the subjects for the study. Day one- Group A (1-50 students were evaluated by OSPE method of assessment. Day two- Group B (51-98 were evaluated by standard practical examination. To avoid examiners Bias on Day 3- Group C (51- 98 who were evaluated by SPE were evaluated by OSPE with minor variations. Group A underwent OSPE. Questionnaire was given to students after the assessment on the fourth day to get the feedback. RESULTS Independent sample t-test comparing mean percent scores of OSPE and SPE between the groups. There is no statistically significant difference in the mean percent scores for OSPE and SPE among the two groups. Paired sample t-test comparing mean percent scores of OSPE and SPE of group B students. The mean percentage score for OSPE is higher than the percentage scores obtained in SPE among the group B students, but the difference was not found to be statistically significant. The feedback from the students showed that more than 80% agreed that OSPE was less stressful to perform that it was a more objective assessment. CONCLUSION In conclusion, OSPE has several distinct advantages. From our first experience, we found that OSPE was more objective, measured practical skills better and eliminated examiner bias.

  5. Digital Competence Model of Distance Learning Students

    Science.gov (United States)

    da Silva, Ketia Kellen A.; Behar, Patricia A.

    2017-01-01

    This article presents the development of a digital competency model of Distance Learning (DL) students in Brazil called CompDigAl_EAD. The following topics were addressed in this study: Educational Competences, Digital Competences, and Distance Learning students. The model was developed between 2015 and 2016 and is being validated in 2017. It was…

  6. Team learning: building shared mental models

    NARCIS (Netherlands)

    Bossche, van den P.; Gijselaers, W.; Segers, M.; Woltjer, G.B.; Kirschner, P.

    2011-01-01

    To gain insight in the social processes that underlie knowledge sharing in teams, this article questions which team learning behaviors lead to the construction of a shared mental model. Additionally, it explores how the development of shared mental models mediates the relation between team learning

  7. Modelling and Optimizing Mathematics Learning in Children

    Science.gov (United States)

    Käser, Tanja; Busetto, Alberto Giovanni; Solenthaler, Barbara; Baschera, Gian-Marco; Kohn, Juliane; Kucian, Karin; von Aster, Michael; Gross, Markus

    2013-01-01

    This study introduces a student model and control algorithm, optimizing mathematics learning in children. The adaptive system is integrated into a computer-based training system for enhancing numerical cognition aimed at children with developmental dyscalculia or difficulties in learning mathematics. The student model consists of a dynamic…

  8. Exploring the impact of learning objects in middle school mathematics and science classrooms: A formative analysis

    Directory of Open Access Journals (Sweden)

    Robin H. Kay

    2008-12-01

    Full Text Available The current study offers a formative analysis of the impact of learning objects in middle school mathematics and science classrooms. Five reliable and valid measure of effectiveness were used to examine the impact of learning objects from the perspective of 262 students and 8 teachers (14 classrooms in science or mathematics. The results indicate that teachers typically spend 1-2 hours finding and preparing for learning-object based lesson plans that focus on the review of previous concepts. Both teachers and students are positive about the learning benefits, quality, and engagement value of learning objects, although teachers are more positive than students. Student performance increased significantly, over 40%, when learning objects were used in conjunction with a variety of teaching strategies. It is reasonable to conclude that learning objects have potential as a teaching tool in a middle school environment. L’impacte des objets d’apprentissage dans les classes de mathématique et de sciences à l’école intermédiaire : une analyse formative Résumé : Cette étude présente une analyse formative de l’impacte des objets d’apprentissage dans les classes de mathématique et de sciences à l’école intermédiaire. Cinq mesures de rendement fiables et valides ont été exploitées pour examiner l’effet des objets d’apprentissage selon 262 élèves et 8 enseignants (414 classes en science ou mathématiques. Les résultats indiquent que les enseignants passent typiquement 1-2 heures pour trouver des objets d’apprentissage et préparer les leçons associées qui seraient centrées sur la revue de concepts déjà vus en classe. Quoique les enseignants aient répondu de façon plus positive que les élèves, les deux groupes ont répondu positivement quant aux avantages au niveau de l’apprentissage, à la qualité ainsi qu’à la valeur motivationnelle des objets d’apprentissage. Le rendement des élèves aurait aussi augment

  9. Cross-Situational Learning with Bayesian Generative Models for Multimodal Category and Word Learning in Robots

    Directory of Open Access Journals (Sweden)

    Akira Taniguchi

    2017-12-01

    Full Text Available In this paper, we propose a Bayesian generative model that can form multiple categories based on each sensory-channel and can associate words with any of the four sensory-channels (action, position, object, and color. This paper focuses on cross-situational learning using the co-occurrence between words and information of sensory-channels in complex situations rather than conventional situations of cross-situational learning. We conducted a learning scenario using a simulator and a real humanoid iCub robot. In the scenario, a human tutor provided a sentence that describes an object of visual attention and an accompanying action to the robot. The scenario was set as follows: the number of words per sensory-channel was three or four, and the number of trials for learning was 20 and 40 for the simulator and 25 and 40 for the real robot. The experimental results showed that the proposed method was able to estimate the multiple categorizations and to learn the relationships between multiple sensory-channels and words accurately. In addition, we conducted an action generation task and an action description task based on word meanings learned in the cross-situational learning scenario. The experimental results showed that the robot could successfully use the word meanings learned by using the proposed method.

  10. A Cognitive Skill Classification Based on Multi Objective Optimization Using Learning Vector Quantization for Serious Games

    Directory of Open Access Journals (Sweden)

    Moh. Aries Syufagi

    2013-09-01

    Full Text Available Nowadays, serious games and game technology are poised to transform the way of educating and training students at all levels. However, pedagogical value in games do not help novice students learn, too many memorizing and reduce learning process due to no information of player’s ability. To asses the cognitive level of player ability, we propose a Cognitive Skill Game (CSG. CSG improves this cognitive concept to monitor how players interact with the game. This game employs Learning Vector Quantization (LVQ for optimizing the cognitive skill input classification of the player. CSG is using teacher’s data to obtain the neuron vector of cognitive skill pattern supervise. Three clusters multi objective XE "multi objective"  target will be classified as; trial and error, carefully and, expert cognitive skill. In the game play experiments employ 33 respondent players demonstrates that 61% of players have high trial and error, 21% have high carefully, and 18% have high expert cognitive skill. CSG may provide information to game engine when a player needs help or when wanting a formidable challenge. The game engine will provide the appropriate tasks according to players’ ability. CSG will help balance the emotions of players, so players do not get bored and frustrated. 

  11. Learning Clinical Procedures Through Internet Digital Objects: Experience of Undergraduate Students Across Clinical Faculties

    Science.gov (United States)

    Li, Tse Yan; Wong, Kin; Tse, Christine Shuk Kwan; Chan, Ying Yee

    2015-01-01

    Background Various digital learning objects (DLOs) are available via the World Wide Web, showing the flow of clinical procedures. It is unclear to what extent these freely accessible Internet DLOs facilitate or hamper students’ acquisition of clinical competence. Objective This study aimed to understand the experience of undergraduate students across clinical disciplines—medicine, dentistry, and nursing—in using openly accessible Internet DLOs, and to investigate the role of Internet DLOs in facilitating their clinical learning. Methods Mid-year and final-year groups were selected from each undergraduate clinical degree program of the University of Hong Kong—Bachelor of Medicine and Bachelor of Surgery (MBBS), Bachelor of Dental Surgery (BDS), and Bachelor of Nursing (BNurs). All students were invited to complete a questionnaire on their personal and educational backgrounds, and their experiences and views on using Internet DLOs in learning clinical procedures. The questionnaire design was informed by the findings of six focus groups. Results Among 439 respondents, 97.5% (428/439) learned a variety of clinical procedures through Internet DLOs. Most nursing students (107/122, 87.7%) learned preventive measures through Internet DLOs, with a lower percentage of medical students (99/215, 46.0%) and dental students (43/96, 45%) having learned them this way (both Pstudents accessed DLOs through public search engines, whereas 93.2% (409/439) accessed them by watching YouTube videos. Students often shared DLOs with classmates (277/435, 63.7%), but rarely discussed them with teachers (54/436, 12.4%). The accuracy, usefulness, and importance of Internet DLOs were rated as 6.85 (SD 1.48), 7.27 (SD 1.53), and 7.13 (SD 1.72), respectively, out of a high score of 10. Conclusions Self-exploration of DLOs in the unrestricted Internet environment is extremely common among current e-generation learners and was regarded by students across clinical faculties as an important

  12. A Cognitive Skill Classification Based On Multi Objective Optimization Using Learning Vector Quantization for Serious Games

    Directory of Open Access Journals (Sweden)

    Moh. Aries Syufagi

    2011-12-01

    Full Text Available Nowadays, serious games and game technology are poised to transform the way of educating and training students at all levels. However, pedagogical value in games do not help novice students learn, too many memorizing and reduce learning process due to no information of player’s ability. To asses the cognitive level of player ability, we propose a Cognitive Skill Game (CSG. CSG improves this cognitive concept to monitor how players interact with the game. This game employs Learning Vector Quantization (LVQ for optimizing the cognitive skill input classification of the player. CSG is using teacher’s data to obtain the neuron vector of cognitive skill pattern supervise. Three clusters multi objective target will be classified as; trial and error, carefully and, expert cognitive skill. In the game play experiments using 33 respondent players demonstrates that 61% of players have high trial and error cognitive skill, 21% have high carefully cognitive skill, and 18% have high expert cognitive skill. CSG may provide information to game engine when a player needs help or when wanting a formidable challenge. The game engine will provide the appropriate tasks according to players’ ability. CSG will help balance the emotions of players, so players do not get bored and frustrated. Players have a high interest to finish the game if the player is emotionally stable. Interests in the players strongly support the procedural learning in a serious game.

  13. Model-Agnostic Interpretability of Machine Learning

    OpenAIRE

    Ribeiro, Marco Tulio; Singh, Sameer; Guestrin, Carlos

    2016-01-01

    Understanding why machine learning models behave the way they do empowers both system designers and end-users in many ways: in model selection, feature engineering, in order to trust and act upon the predictions, and in more intuitive user interfaces. Thus, interpretability has become a vital concern in machine learning, and work in the area of interpretable models has found renewed interest. In some applications, such models are as accurate as non-interpretable ones, and thus are preferred f...

  14. MODELING OF CONVECTIVE FLOWS IN PNEUMOBASED OBJECTS. Part 1

    Directory of Open Access Journals (Sweden)

    B. M. Khrustalyov

    2014-01-01

    Full Text Available A computer modeling process of three-dimensional forced convection proceeding from computation of thermodynamic parameters of pneumo basic buildings (pneumo supported structures is presented. The mathematical model of numerical computation method of temperature and velocity fields, pressure profile in the object is developed using the package Solid works and is provided by grid methods on specified software. Special Navier–Stokes, Clapeyron–Mendeleev, continuity and thermal-conductivity equations are used to calculate parameters in the building with four supply and exhaust channels. Differential equations are presented by algebraic equation systems, initial-boundary conditions are changed by differential conditions for mesh functions and their solutions are performed by algebraic operations. In this article the following is demonstrated: in pneumo basic buildings convective and heat flows are identical structures near the surfaces in unlimited space, but in single-multiply shells (envelopescirculation lines take place, geometrical sizes of which depend on thermal-physical characteristics of gas(airin envelopes, radiation reaction with heated surfaces of envelopes with  sphere, earth surface, neighboring buildings. Natural surveys of pneumo-basic buildings of different purposes were carried out in Minsk, in different cities of Belarus and Russia, including temperature fields of external and internal surfaces of air envelopes, relative humidity, thermal (heatflows, radiation characteristics and others.The results of research work are illustrated with diagrams of temperature, velocity, density and pressure dependent on coordinates and time.

  15. "The Spiral Model for the Development of Coordination": A Learning Model Based on Eshkol-Wachman Movement Notation (EWMN)

    Science.gov (United States)

    Al-Dor, Nira

    2006-01-01

    The objective of this study is to present "The Spiral Model for the Development of Coordination" (SMDC), a learning model that reflects the complexity and possibilities embodied in the learning of movement notation Eshkol-Wachman (EWMN), an Israeli invention. This model constituted the infrastructure for a comprehensive study that examined the…

  16. A biologically inspired neural network model to transformation invariant object recognition

    Science.gov (United States)

    Iftekharuddin, Khan M.; Li, Yaqin; Siddiqui, Faraz

    2007-09-01

    Transformation invariant image recognition has been an active research area due to its widespread applications in a variety of fields such as military operations, robotics, medical practices, geographic scene analysis, and many others. The primary goal for this research is detection of objects in the presence of image transformations such as changes in resolution, rotation, translation, scale and occlusion. We investigate a biologically-inspired neural network (NN) model for such transformation-invariant object recognition. In a classical training-testing setup for NN, the performance is largely dependent on the range of transformation or orientation involved in training. However, an even more serious dilemma is that there may not be enough training data available for successful learning or even no training data at all. To alleviate this problem, a biologically inspired reinforcement learning (RL) approach is proposed. In this paper, the RL approach is explored for object recognition with different types of transformations such as changes in scale, size, resolution and rotation. The RL is implemented in an adaptive critic design (ACD) framework, which approximates the neuro-dynamic programming of an action network and a critic network, respectively. Two ACD algorithms such as Heuristic Dynamic Programming (HDP) and Dual Heuristic dynamic Programming (DHP) are investigated to obtain transformation invariant object recognition. The two learning algorithms are evaluated statistically using simulated transformations in images as well as with a large-scale UMIST face database with pose variations. In the face database authentication case, the 90° out-of-plane rotation of faces from 20 different subjects in the UMIST database is used. Our simulations show promising results for both designs for transformation-invariant object recognition and authentication of faces. Comparing the two algorithms, DHP outperforms HDP in learning capability, as DHP takes fewer steps to

  17. Reaching Consensus on Essential Biomedical Science Learning Objectives in a Dental Curriculum.

    Science.gov (United States)

    Best, Leandra; Walton, Joanne N; Walker, Judith; von Bergmann, HsingChi

    2016-04-01

    This article describes how the University of British Columbia Faculty of Dentistry reached consensus on essential basic biomedical science objectives for DMD students and applied the information to the renewal of its DMD curriculum. The Delphi Method was used to build consensus among dental faculty members and students regarding the relevance of over 1,500 existing biomedical science objectives. Volunteer panels of at least three faculty members (a basic scientist, a general dentist, and a dental specialist) and a fourth-year dental student were formed for each of 13 biomedical courses in the first two years of the program. Panel members worked independently and anonymously, rating each course objective as "need to know," "nice to know," "irrelevant," or "don't know." Panel members were advised after each round which objectives had not yet achieved a 75% consensus and were asked to reconsider their ratings. After a maximum of three rounds to reach consensus, a second group of faculty experts reviewed and refined the results to establish the biomedical science objectives for the renewed curriculum. There was consensus on 46% of the learning objectives after round one, 80% after round two, and 95% after round three. The second expert group addressed any remaining objectives as part of its review process. Only 47% of previous biomedical science course objectives were judged to be essential or "need to know" for the general dentist. The consensus reached by participants in the Delphi Method panels and a second group of faculty experts led to a streamlined, better integrated DMD curriculum to prepare graduates for future practice.

  18. Automatic video segmentation employing object/camera modeling techniques

    NARCIS (Netherlands)

    Farin, D.S.

    2005-01-01

    Practically established video compression and storage techniques still process video sequences as rectangular images without further semantic structure. However, humans watching a video sequence immediately recognize acting objects as semantic units. This semantic object separation is currently not

  19. The Effect of Inquiry Training Learning Model Based on Just in Time Teaching for Problem Solving Skill

    Science.gov (United States)

    Turnip, Betty; Wahyuni, Ida; Tanjung, Yul Ifda

    2016-01-01

    One of the factors that can support successful learning activity is the use of learning models according to the objectives to be achieved. This study aimed to analyze the differences in problem-solving ability Physics student learning model Inquiry Training based on Just In Time Teaching [JITT] and conventional learning taught by cooperative model…

  20. Object-oriented process dose modeling for glovebox operations

    International Nuclear Information System (INIS)

    Boerigter, S.T.; Fasel, J.H.; Kornreich, D.E.

    1999-01-01

    The Plutonium Facility at Los Alamos National Laboratory supports several defense and nondefense-related missions for the country by performing fabrication, surveillance, and research and development for materials and components that contain plutonium. Most operations occur in rooms with one or more arrays of gloveboxes connected to each other via trolley gloveboxes. Minimizing the effective dose equivalent (EDE) is a growing concern as a result of steadily declining allowable dose limits being imposed and a growing general awareness of safety in the workplace. In general, the authors discriminate three components of a worker's total EDE: the primary EDE, the secondary EDE, and background EDE. A particular background source of interest is the nuclear materials vault. The distinction between sources inside and outside of a particular room is arbitrary with the underlying assumption that building walls and floors provide significant shielding to justify including sources in other rooms in the background category. Los Alamos has developed the Process Modeling System (ProMoS) primarily for performing process analyses of nuclear operations. ProMoS is an object-oriented, discrete-event simulation package that has been used to analyze operations at Los Alamos and proposed facilities such as the new fabrication facilities for the Complex-21 effort. In the past, crude estimates of the process dose (the EDE received when a particular process occurred), room dose (the EDE received when a particular process occurred in a given room), and facility dose (the EDE received when a particular process occurred in the facility) were used to obtain an integrated EDE for a given process. Modifications to the ProMoS package were made to utilize secondary dose information to use dose modeling to enhance the process modeling efforts

  1. Multi-Objective Nonlinear Model Predictive Control: Lexicographic Method

    OpenAIRE

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

    2010-01-01

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

  2. Object-oriented classification of drumlins from digital elevation models

    Science.gov (United States)

    Saha, Kakoli

    Drumlins are common elements of glaciated landscapes which are easily identified by their distinct morphometric characteristics including shape, length/width ratio, elongation ratio, and uniform direction. To date, most researchers have mapped drumlins by tracing contours on maps, or through on-screen digitization directly on top of hillshaded digital elevation models (DEMs). This paper seeks to utilize the unique morphometric characteristics of drumlins and investigates automated extraction of the landforms as objects from DEMs by Definiens Developer software (V.7), using the 30 m United States Geological Survey National Elevation Dataset DEM as input. The Chautauqua drumlin field in Pennsylvania and upstate New York, USA was chosen as a study area. As the study area is huge (approximately covers 2500 sq.km. of area), small test areas were selected for initial testing of the method. Individual polygons representing the drumlins were extracted from the elevation data set by automated recognition, using Definiens' Multiresolution Segmentation tool, followed by rule-based classification. Subsequently parameters such as length, width and length-width ratio, perimeter and area were measured automatically. To test the accuracy of the method, a second base map was produced by manual on-screen digitization of drumlins from topographic maps and the same morphometric parameters were extracted from the mapped landforms using Definiens Developer. Statistical comparison showed a high agreement between the two methods confirming that object-oriented classification for extraction of drumlins can be used for mapping these landforms. The proposed method represents an attempt to solve the problem by providing a generalized rule-set for mass extraction of drumlins. To check that the automated extraction process was next applied to a larger area. Results showed that the proposed method is as successful for the bigger area as it was for the smaller test areas.

  3. Learning About Climate and Atmospheric Models Through Machine Learning

    Science.gov (United States)

    Lucas, D. D.

    2017-12-01

    From the analysis of ensemble variability to improving simulation performance, machine learning algorithms can play a powerful role in understanding the behavior of atmospheric and climate models. To learn about model behavior, we create training and testing data sets through ensemble techniques that sample different model configurations and values of input parameters, and then use supervised machine learning to map the relationships between the inputs and outputs. Following this procedure, we have used support vector machines, random forests, gradient boosting and other methods to investigate a variety of atmospheric and climate model phenomena. We have used machine learning to predict simulation crashes, estimate the probability density function of climate sensitivity, optimize simulations of the Madden Julian oscillation, assess the impacts of weather and emissions uncertainty on atmospheric dispersion, and quantify the effects of model resolution changes on precipitation. This presentation highlights recent examples of our applications of machine learning to improve the understanding of climate and atmospheric models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  4. Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

    Science.gov (United States)

    Ferreria, Paulo Victor R.; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy M.; Bilen, Sven G.; Reinhart, Richard C.; Mortensen, Dale J.

    2017-01-01

    Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

  5. A control model for object virtualization in supply chain management

    NARCIS (Netherlands)

    Verdouw, C.N.; Beulens, A.J.M.; Reijers, H.A.; van der Vorst, J.G.A.J.

    2015-01-01

    Due to the emergence of the Internet of Things, supply chain control can increasingly be based on virtual objects instead of on the direct observation of physical objects. Object virtualization allows the decoupling of control activities from the handling and observing of physical products and

  6. Auditory object perception: A neurobiological model and prospective review.

    Science.gov (United States)

    Brefczynski-Lewis, Julie A; Lewis, James W

    2017-10-01

    Interaction with the world is a multisensory experience, but most of what is known about the neural correlates of perception comes from studying vision. Auditory inputs enter cortex with its own set of unique qualities, and leads to use in oral communication, speech, music, and the understanding of emotional and intentional states of others, all of which are central to the human experience. To better understand how the auditory system develops, recovers after injury, and how it may have transitioned in its functions over the course of hominin evolution, advances are needed in models of how the human brain is organized to process real-world natural sounds and "auditory objects". This review presents a simple fundamental neurobiological model of hearing perception at a category level that incorporates principles of bottom-up signal processing together with top-down constraints of grounded cognition theories of knowledge representation. Though mostly derived from human neuroimaging literature, this theoretical framework highlights rudimentary principles of real-world sound processing that may apply to most if not all mammalian species with hearing and acoustic communication abilities. The model encompasses three basic categories of sound-source: (1) action sounds (non-vocalizations) produced by 'living things', with human (conspecific) and non-human animal sources representing two subcategories; (2) action sounds produced by 'non-living things', including environmental sources and human-made machinery; and (3) vocalizations ('living things'), with human versus non-human animals as two subcategories therein. The model is presented in the context of cognitive architectures relating to multisensory, sensory-motor, and spoken language organizations. The models' predictive values are further discussed in the context of anthropological theories of oral communication evolution and the neurodevelopment of spoken language proto-networks in infants/toddlers. These phylogenetic

  7. Enhanced democratic learning within the Aalborg Model

    DEFF Research Database (Denmark)

    Qvist, Palle

    2010-01-01

    The Aalborg PBL Model [Kjersdam & Enemark, 1997; Kolmos et al., 2004] is an example of a democratic learning system [Qvist, 2008]. Writing one project each semester in teams is an important element in the model. Medicine with Industrial Specialisation - a study at the Faculties of Engineering......, Science and Medicine at Aalborg University - has combined the Aalborg Model with solving cases as used by other models. A questionnaire survey related to democratic learning indicates that the democratic learning has been enhanced. This paper presents the results....

  8. Practicing doctors' perceptions on new learning objectives for Vietnamese medical schools

    Directory of Open Access Journals (Sweden)

    Dung Do Van

    2007-06-01

    Full Text Available Abstract Background As part of the process to develop more community-oriented medical teaching in Vietnam, eight medical schools prepared a set of standard learning objectives with attention to the needs of a doctor working with the community. Because they were prepared based on government documents and the opinions of the teachers, it was necessary to check them with doctors who had already graduated and were working at different sites in the community. Methods Each of the eight medical faculties asked 100 practising recent graduates to complete a questionnaire to check the relevance of the skills that the teachers considered most important. We used mean and standard deviation to summarize the scores rated by the respondents for each skill and percentile at four points: p50, p25, p10 and p5 to describe the variation of scores among the respondents. Correlation coefficient was used to measure the relationship between skill levels set by the teachers and the perception of practicing doctors regarding frequency of using skills and priority for each skill. Additional information was taken from the records of focus group discussions to clarify, explain or expand on the results from the quantitative data. Results In many cases the skills considered important by teachers were also rated as highly necessary and/or frequently used by the respondents. There were, however, discrepancies: some skills important to teachers were seldom used and not considered important by the doctors. In focus group discussions the doctors also identified skills that are not taught at all in the medical schools but would be needed by practising doctors. Conclusion Although most of the skills and skill levels included in the learning objectives by the teachers were consistent with the opinions of their graduates, the match was not perfect. The experience of the graduates and their additional comments should be included as inputs to the definition of learning objectives for

  9. Online Learning of Industrial Manipulators' Dynamics Models

    DEFF Research Database (Denmark)

    Polydoros, Athanasios

    2017-01-01

    , it was compared with multiple other state-of-the-art machine learning algorithms. Moreover, the thesis presents the application of the proposed learning method on robot control for achieving trajectory execution while learning the inverse dynamics models  on-the-fly . Also it is presented the application...... of the dynamics models. Those mainly derive from physics-based methods and thus they are based on physical properties which are hard to be calculated.  In this thesis, is presented, a novel online machine learning approach  which is able to model both inverse and forward dynamics models of industrial manipulators....... The proposed method belongs to the class of deep learning and exploits the concepts of self-organization, recurrent neural networks and iterative multivariate Bayesian regression. It has been evaluated on multiple datasets captured from industrial robots while they were performing various tasks. Also...

  10. Learning Markov models for stationary system behaviors

    DEFF Research Database (Denmark)

    Chen, Yingke; Mao, Hua; Jaeger, Manfred

    2012-01-01

    to a single long observation sequence, and in these situations existing automatic learning methods cannot be applied. In this paper, we adapt algorithms for learning variable order Markov chains from a single observation sequence of a target system, so that stationary system properties can be verified using......Establishing an accurate model for formal verification of an existing hardware or software system is often a manual process that is both time consuming and resource demanding. In order to ease the model construction phase, methods have recently been proposed for automatically learning accurate...... the learned model. Experiments demonstrate that system properties (formulated as stationary probabilities of LTL formulas) can be reliably identified using the learned model....

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

    Science.gov (United States)

    Zachrisson, Anders

    2013-01-01

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

  12. Learning Objects and the FATIH Project: Proposal of a Model

    Science.gov (United States)

    Eryilmaz, Selami

    2014-01-01

    Globalization together with new information and communication technologies (ICTs) and accelerated changes in society affect the economic and social life to a great extent. In order to achieve the goals mentioned in the strategy document, the necessary arrangements were made and FATIH (Increasing the opportunities and Technology Improvement…

  13. The Implementation of Medical Informatics in the National Competence Based Catalogue of Learning Objectives for Undergraduate Medical Education (NKLM).

    Science.gov (United States)

    Behrends, Marianne; Steffens, Sandra; Marschollek, Michael

    2017-01-01

    The National Competence Based Catalogue of Learning Objectives for Undergraduate Medical Education (NKLM) describes medical skills and attitudes without being ordered by subjects or organs. Thus, the NKLM enables systematic curriculum mapping and supports curricular transparency. In this paper we describe where learning objectives related to Medical Informatics (MI) in Hannover coincide with other subjects and where they are taught exclusively in MI. An instance of the web-based MERLIN-database was used for the mapping process. In total 52 learning objectives overlapping with 38 other subjects could be allocated to MI. No overlap exists for six learning objectives describing explicitly topics of information technology or data management for scientific research. Most of the overlap was found for learning objectives relating to documentation and aspects of data privacy. The identification of numerous shared learning objectives with other subjects does not mean that other subjects teach the same content as MI. Identifying common learning objectives rather opens up the possibility for teaching cooperations which could lead to an important exchange and hopefully an improvement in medical education. Mapping of a whole medical curriculum offers the opportunity to identify common ground between MI and other medical subjects. Furthermore, in regard to MI, the interaction with other medical subjects can strengthen its role in medical education.

  14. A Hybrid Teaching and Learning Model

    Science.gov (United States)

    Juhary, Jowati Binti

    This paper aims at analysing the needs for a specific teaching and learning model for the National Defence University of Malaysia (NDUM). The main argument is that whether there are differences between teaching and learning for academic component versus military component at the university. It is further argued that in order to achieve excellence, there should be one teaching and learning culture. Data were collected through interviews with military cadets. It is found that there are variations of teaching and learning strategies for academic courses, in comparison to a dominant teaching and learning style for military courses. Thus, in the interest of delivering quality education and training for students at the university, the paper argues that possibly a hybrid model for teaching and learning is fundamental in order to generate a one culture of academic and military excellence for the NDUM.

  15. Study on modeling of operator's learning mechanism

    International Nuclear Information System (INIS)

    Yoshimura, Seichi; Hasegawa, Naoko

    1998-01-01

    One effective method to analyze the causes of human errors is to model the behavior of human and to simulate it. The Central Research Institute of Electric Power Industry (CRIEPI) has developed an operator team behavior simulation system called SYBORG (Simulation System for the Behavior of an Operating Group) to analyze the human errors and to establish the countermeasures for them. As an operator behavior model which composes SYBORG has no learning mechanism and the knowledge of a plant is fixed, it cannot take suitable actions when unknown situations occur nor learn anything from the experience. However, considering actual operators, learning is an essential human factor to enhance their abilities to diagnose plant anomalies. In this paper, Q learning with 1/f fluctuation was proposed as a learning mechanism of an operator and simulation using the mechanism was conducted. The results showed the effectiveness of the learning mechanism. (author)

  16. Teaching tools in Evidence Based Practice: evaluation of reusable learning objects (RLOs for learning about Meta-analysis

    Directory of Open Access Journals (Sweden)

    Wharrad Heather

    2011-05-01

    Full Text Available Abstract Background All healthcare students are taught the principles of evidence based practice on their courses. The ability to understand the procedures used in systematically reviewing evidence reported in studies, such as meta-analysis, are an important element of evidence based practice. Meta-analysis is a difficult statistical concept for healthcare students to understand yet it is an important technique used in systematic reviews to pool data from studies to look at combined effectiveness of treatments. In other areas of the healthcare curricula, by supplementing lectures, workbooks and workshops with pedagogically designed, multimedia learning objects (known as reusable learning objects or RLOs we have shown an improvement in students' perceived understanding in subjects they found difficult. In this study we describe the development and evaluation of two RLOs on meta-analysis. The RLOs supplement associated lectures and aim to improve students' understanding of meta-analysis in healthcare students. Methods Following a quality controlled design process two RLOs were developed and delivered to two cohorts of students, a Master in Public Health course and Postgraduate diploma in nursing course. Students' understanding of five key concepts of Meta-analysis were measured before and after a lecture and again after RLO use. RLOs were also evaluated for their educational value, learning support, media attributes and usability using closed and open questions. Results Students rated their understanding of meta-analysis as improved after a lecture and further improved after completing the RLOs (Wilcoxon paired test, p Conclusions Meta-analysis RLOs that are openly accessible and unrestricted by usernames and passwords provide flexible support for students who find the process of meta-analysis difficult.

  17. The Effect of Cooperative Learning Model and Kolb Learning Styles on Learning Result of the Basics of Politics

    Science.gov (United States)

    Sugiharto

    2015-01-01

    The aims of this research were to determine the effect of cooperative learning model and learning styles on learning result. This quasi-experimental study employed a 2x2 treatment by level, involved independent variables, i.e. cooperative learning model and learning styles, and learning result as the dependent variable. Findings signify that: (1)…

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-09-13

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

  19. Handling Emergency Management in [an] Object Oriented Modeling Environment

    Science.gov (United States)

    Tokgoz, Berna Eren; Cakir, Volkan; Gheorghe, Adrian V.

    2010-01-01

    It has been understood that protection of a nation from extreme disasters is a challenging task. Impacts of extreme disasters on a nation's critical infrastructures, economy and society could be devastating. A protection plan itself would not be sufficient when a disaster strikes. Hence, there is a need for a holistic approach to establish more resilient infrastructures to withstand extreme disasters. A resilient infrastructure can be defined as a system or facility that is able to withstand damage, but if affected, can be readily and cost-effectively restored. The key issue to establish resilient infrastructures is to incorporate existing protection plans with comprehensive preparedness actions to respond, recover and restore as quickly as possible, and to minimize extreme disaster impacts. Although national organizations will respond to a disaster, extreme disasters need to be handled mostly by local emergency management departments. Since emergency management departments have to deal with complex systems, they have to have a manageable plan and efficient organizational structures to coordinate all these systems. A strong organizational structure is the key in responding fast before and during disasters, and recovering quickly after disasters. In this study, the entire emergency management is viewed as an enterprise and modelled through enterprise management approach. Managing an enterprise or a large complex system is a very challenging task. It is critical for an enterprise to respond to challenges in a timely manner with quick decision making. This study addresses the problem of handling emergency management at regional level in an object oriented modelling environment developed by use of TopEase software. Emergency Operation Plan of the City of Hampton, Virginia, has been incorporated into TopEase for analysis. The methodology used in this study has been supported by a case study on critical infrastructure resiliency in Hampton Roads.

  20. Trajectory control sensor engineering model detailed test objective

    Science.gov (United States)

    Dekome, Kent; Barr, Joseph Martin

    1991-01-01

    The concept employed in an existing Trajectory Control Sensor (TCS) breadboard is being developed into an engineering model to be considered for flight on the Shuttle as a Detailed Test Objective (DTO). The sensor design addresses the needs of Shuttle/SSF docking/berthing by providing relative range and range rate to 1500 meters as well as the perceived needs of AR&C by relative attitude measurement over the last 100 meters. Range measurement is determined using a four-tone ranging technique. The Doppler shift on the highest frequency tone will be used to provide direct measurement of range rate. Bearing rate and attitude rates will be determined through back differencing of bearing and attitude, respectively. The target consists of an isosceles triangle configuration of three optical retroreflectors, roughly one meter and one-half meter in size. After target acquisition, the sensor continually updates the positions of the three retros at a rate of about one hertz. The engineering model is expected to weigh about 25 pounds, consume 25-30 watts, and have an envelope of about 1.25 cubic feet. The following concerns were addressed during the presentation: are there any concerns with differentiating attitude and bearing to get attitude and bearing rates? Since the docking scenario has low data bandwidth, back differencing is a sufficient approximation of a perfect differentiator for this application. Could range data be obtained if there were no retroreflectors on the target vehicle? Possibly, but only at close range. It would be dependent on target characteristics.