The Effects of Problem Posing on Student Mathematical Learning: A Meta-Analysis

Science.gov (United States)

Rosli, Roslinda; Capraro, Mary Margaret; Capraro, Robert M.

2014-01-01

The purpose of the study was to meta-synthesize research findings on the effectiveness of problem posing and to investigate the factors that might affect the incorporation of problem posing in the teaching and learning of mathematics. The eligibility criteria for inclusion of literature in the meta-analysis was: published between 1989 and 2011,…

Sensing Strategies for Disambiguating among Multiple Objects in Known Poses.

Science.gov (United States)

1985-08-01

ELEMENT. PROIECT. TASK Artificial Inteligence Laboratory AE OKUI UBR 545 Technology Square Cambridge, MA 021.39 11. CONTROLLING OFFICE NAME AND ADDRESS 12...AD-Ali65 912 SENSING STRATEGIES FOR DISAMBIGURTING MONG MULTIPLE 1/1 OBJECTS IN KNOWN POSES(U) MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL ...or Dist Special 1 ’ MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A. I. Memo 855 August, 1985 Sensing Strategies for

Animated pose templates for modeling and detecting human actions.

Science.gov (United States)

Yao, Benjamin Z; Nie, Bruce X; Liu, Zicheng; Zhu, Song-Chun

2014-03-01

This paper presents animated pose templates (APTs) for detecting short-term, long-term, and contextual actions from cluttered scenes in videos. Each pose template consists of two components: 1) a shape template with deformable parts represented in an And-node whose appearances are represented by the Histogram of Oriented Gradient (HOG) features, and 2) a motion template specifying the motion of the parts by the Histogram of Optical-Flows (HOF) features. A shape template may have more than one motion template represented by an Or-node. Therefore, each action is defined as a mixture (Or-node) of pose templates in an And-Or tree structure. While this pose template is suitable for detecting short-term action snippets in two to five frames, we extend it in two ways: 1) For long-term actions, we animate the pose templates by adding temporal constraints in a Hidden Markov Model (HMM), and 2) for contextual actions, we treat contextual objects as additional parts of the pose templates and add constraints that encode spatial correlations between parts. To train the model, we manually annotate part locations on several keyframes of each video and cluster them into pose templates using EM. This leaves the unknown parameters for our learning algorithm in two groups: 1) latent variables for the unannotated frames including pose-IDs and part locations, 2) model parameters shared by all training samples such as weights for HOG and HOF features, canonical part locations of each pose, coefficients penalizing pose-transition and part-deformation. To learn these parameters, we introduce a semi-supervised structural SVM algorithm that iterates between two steps: 1) learning (updating) model parameters using labeled data by solving a structural SVM optimization, and 2) imputing missing variables (i.e., detecting actions on unlabeled frames) with parameters learned from the previous step and progressively accepting high-score frames as newly labeled examples. This algorithm belongs to a

Is Attribute-Based Zero-Shot Learning an Ill-Posed Strategy?

KAUST Repository

Alabdulmohsin, Ibrahim; Cisse, Moustapha; Zhang, Xiangliang

2016-01-01

One transfer learning approach that has gained a wide popularity lately is attribute-based zero-shot learning. Its goal is to learn novel classes that were never seen during the training stage. The classical route towards realizing this goal is to incorporate a prior knowledge, in the form of a semantic embedding of classes, and to learn to predict classes indirectly via their semantic attributes. Despite the amount of research devoted to this subject lately, no known algorithm has yet reported a predictive accuracy that could exceed the accuracy of supervised learning with very few training examples. For instance, the direct attribute prediction (DAP) algorithm, which forms a standard baseline for the task, is known to be as accurate as supervised learning when as few as two examples from each hidden class are used for training on some popular benchmark datasets! In this paper, we argue that this lack of significant results in the literature is not a coincidence; attribute-based zero-shot learning is fundamentally an ill-posed strategy. The key insight is the observation that the mechanical task of predicting an attribute is, in fact, quite different from the epistemological task of learning the “correct meaning” of the attribute itself. This renders attribute-based zero-shot learning fundamentally ill-posed. In more precise mathematical terms, attribute-based zero-shot learning is equivalent to the mirage goal of learning with respect to one distribution of instances, with the hope of being able to predict with respect to any arbitrary distribution. We demonstrate this overlooked fact on some synthetic and real datasets. The data and software related to this paper are available at https://mine. kaust.edu.sa/Pages/zero-shot-learning.aspx. © Springer International Publishing AG 2016.

Is Attribute-Based Zero-Shot Learning an Ill-Posed Strategy?

KAUST Repository

Alabdulmohsin, Ibrahim

2016-09-03

One transfer learning approach that has gained a wide popularity lately is attribute-based zero-shot learning. Its goal is to learn novel classes that were never seen during the training stage. The classical route towards realizing this goal is to incorporate a prior knowledge, in the form of a semantic embedding of classes, and to learn to predict classes indirectly via their semantic attributes. Despite the amount of research devoted to this subject lately, no known algorithm has yet reported a predictive accuracy that could exceed the accuracy of supervised learning with very few training examples. For instance, the direct attribute prediction (DAP) algorithm, which forms a standard baseline for the task, is known to be as accurate as supervised learning when as few as two examples from each hidden class are used for training on some popular benchmark datasets! In this paper, we argue that this lack of significant results in the literature is not a coincidence; attribute-based zero-shot learning is fundamentally an ill-posed strategy. The key insight is the observation that the mechanical task of predicting an attribute is, in fact, quite different from the epistemological task of learning the “correct meaning” of the attribute itself. This renders attribute-based zero-shot learning fundamentally ill-posed. In more precise mathematical terms, attribute-based zero-shot learning is equivalent to the mirage goal of learning with respect to one distribution of instances, with the hope of being able to predict with respect to any arbitrary distribution. We demonstrate this overlooked fact on some synthetic and real datasets. The data and software related to this paper are available at https://mine. kaust.edu.sa/Pages/zero-shot-learning.aspx. © Springer International Publishing AG 2016.

A new benchmark for pose estimation with ground truth from virtual reality

DEFF Research Database (Denmark)

Schlette, Christian; Buch, Anders Glent; Aksoy, Eren Erdal

2014-01-01

The development of programming paradigms for industrial assembly currently gets fresh impetus from approaches in human demonstration and programming-by-demonstration. Major low- and mid-level prerequisites for machine vision and learning in these intelligent robotic applications are pose estimation......, stereo reconstruction and action recognition. As a basis for the machine vision and learning involved, pose estimation is used for deriving object positions and orientations and thus target frames for robot execution. Our contribution introduces and applies a novel benchmark for typical multi...

Development of a Mobile Learning System Based on a Collaborative Problem-Posing Strategy

Science.gov (United States)

Sung, Han-Yu; Hwang, Gwo-Jen; Chang, Ya-Chi

2016-01-01

In this study, a problem-posing strategy is proposed for supporting collaborative mobile learning activities. Accordingly, a mobile learning environment has been developed, and an experiment on a local culture course has been conducted to evaluate the effectiveness of the proposed approach. Three classes of an elementary school in southern Taiwan…

6DoF object pose measurement by a monocular manifold-based pattern recognition technique

International Nuclear Information System (INIS)

Kouskouridas, Rigas; Charalampous, Konstantinos; Gasteratos, Antonios

2012-01-01

In this paper, a novel solution to the compound problem of object recognition and 3D pose estimation is presented. An accurate measurement of the geometrical configuration of a recognized target, relative to a known coordinate system, is of fundamental importance and constitutes a prerequisite for several applications such as robot grasping or obstacle avoidance. The proposed method lays its foundations on the following assumptions: (a) the same object captured under varying viewpoints and perspectives represents data that could be projected onto a well-established and highly distinguishable subspace; (b) totally different objects observed under the same viewpoints and perspectives share identical 3D pose that can be sufficiently modeled to produce a generalized model. Toward this end, we propose an advanced architecture that allows both recognizing patterns and providing efficient solution for 6DoF pose estimation. We employ a manifold modeling architecture that is grounded on a part-based representation of an object, which in turn, is accomplished via an unsupervised clustering of the extracted visual cues. The main contributions of the proposed framework are: (a) the proposed part-based architecture requires minimum supervision, compared to other contemporary solutions, whilst extracting new features encapsulating both appearance and geometrical attributes of the objects; (b) contrary to related projects that extract high-dimensional data, thus, increasing the complexity of the system, the proposed manifold modeling approach makes use of low dimensionality input vectors; (c) the formulation of a novel input–output space mapping that outperforms the existing dimensionality reduction schemes. Experimental results justify our theoretical claims and demonstrate the superiority of our method comparing to other related contemporary projects. (paper)

Robust Pose Estimation using the SwissRanger SR-3000 Camera

DEFF Research Database (Denmark)

Gudmundsson, Sigurjon Arni; Larsen, Rasmus; Ersbøll, Bjarne Kjær

2007-01-01

In this paper a robust method is presented to classify and estimate an objects pose from a real time range image and a low dimensional model. The model is made from a range image training set which is reduced dimensionally by a nonlinear manifold learning method named Local Linear Embedding (LLE)......). New range images are then projected to this model giving the low dimensional coordinates of the object pose in an efficient manner. The range images are acquired by a state of the art SwissRanger SR-3000 camera making the projection process work in real-time....

Automated pose estimation of objects using multiple ID devices for handling and maintenance task in nuclear fusion reactor

International Nuclear Information System (INIS)

Umetani, Tomohiro; Morioka, Jun-ichi; Tamura, Yuichi; Inoue, Kenji; Arai, Tatsuo; Mae, Yasusi

2011-01-01

This paper describes a method for the automated estimation of three-dimensional pose (position and orientation) of objects by autonomous robots, using multiple identification (ID) devices. Our goal is to estimate the object pose for assembly or maintenance tasks in a real nuclear fusion reactor system, with autonomous robots cooperating in a virtual assembly system. The method estimates the three-dimensional pose for autonomous robots. This paper discusses a method of motion generation for ID acquisition using the sensory data acquired by the measurement system attached to the robots and from the environment. Experimental results show the feasibility of the proposed method. (author)

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

Process-based Assignment-Setting Change for Support of Overcoming Bottlenecks in Learning by Problem-Posing in Arithmetic Word Problems

Science.gov (United States)

Supianto, A. A.; Hayashi, Y.; Hirashima, T.

2017-02-01

Problem-posing is well known as an effective activity to learn problem-solving methods. Monsakun is an interactive problem-posing learning environment to facilitate arithmetic word problems learning for one operation of addition and subtraction. The characteristic of Monsakun is problem-posing as sentence-integration that lets learners make a problem of three sentences. Monsakun provides learners with five or six sentences including dummies, which are designed through careful considerations by an expert teacher as a meaningful distraction to the learners in order to learn the structure of arithmetic word problems. The results of the practical use of Monsakun in elementary schools show that many learners have difficulties in arranging the proper answer at the high level of assignments. The analysis of the problem-posing process of such learners found that their misconception of arithmetic word problems causes impasses in their thinking and mislead them to use dummies. This study proposes a method of changing assignments as a support for overcoming bottlenecks of thinking. In Monsakun, the bottlenecks are often detected as a frequently repeated use of a specific dummy. If such dummy can be detected, it is the key factor to support learners to overcome their difficulty. This paper discusses how to detect the bottlenecks and to realize such support in learning by problem-posing.

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.

Exemplar-based human action pose correction.

Science.gov (United States)

Shen, Wei; Deng, Ke; Bai, Xiang; Leyvand, Tommer; Guo, Baining; Tu, Zhuowen

2014-07-01

The launch of Xbox Kinect has built a very successful computer vision product and made a big impact on the gaming industry. This sheds lights onto a wide variety of potential applications related to action recognition. The accurate estimation of human poses from the depth image is universally a critical step. However, existing pose estimation systems exhibit failures when facing severe occlusion. In this paper, we propose an exemplar-based method to learn to correct the initially estimated poses. We learn an inhomogeneous systematic bias by leveraging the exemplar information within a specific human action domain. Furthermore, as an extension, we learn a conditional model by incorporation of pose tags to further increase the accuracy of pose correction. In the experiments, significant improvements on both joint-based skeleton correction and tag prediction are observed over the contemporary approaches, including what is delivered by the current Kinect system. Our experiments for the facial landmark correction also illustrate that our algorithm can improve the accuracy of other detection/estimation systems.

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.

In-the-wild facial expression recognition in extreme poses

Science.gov (United States)

Yang, Fei; Zhang, Qian; Zheng, Chi; Qiu, Guoping

2018-04-01

In the computer research area, facial expression recognition is a hot research problem. Recent years, the research has moved from the lab environment to in-the-wild circumstances. It is challenging, especially under extreme poses. But current expression detection systems are trying to avoid the pose effects and gain the general applicable ability. In this work, we solve the problem in the opposite approach. We consider the head poses and detect the expressions within special head poses. Our work includes two parts: detect the head pose and group it into one pre-defined head pose class; do facial expression recognize within each pose class. Our experiments show that the recognition results with pose class grouping are much better than that of direct recognition without considering poses. We combine the hand-crafted features, SIFT, LBP and geometric feature, with deep learning feature as the representation of the expressions. The handcrafted features are added into the deep learning framework along with the high level deep learning features. As a comparison, we implement SVM and random forest to as the prediction models. To train and test our methodology, we labeled the face dataset with 6 basic expressions.

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...

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

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…

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...

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....

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.

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.

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.

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.

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

Refining Visually Detected Object poses

DEFF Research Database (Denmark)

Holm, Preben; Petersen, Henrik Gordon

2010-01-01

to the particular object and in order to handle the demand for flexibility, there is an increasing demand for avoiding such dedicated mechanical alignment systems. Rather, it would be desirable to automatically locate and grasp randomly placed objects from tables, conveyor belts or even bins with a high accuracy...

The art of problem posing

CERN Document Server

Brown, Stephen I

1990-01-01

Updated and expanded, this second edition satisfies the same philosophical objective as the first -- to show the importance of problem posing. Although interest in mathematical problem solving increased during the past decade, problem posing remained relatively ignored. The Art of Problem Posing draws attention to this equally important act and is the innovator in the field. Special features include: * an exploration ofthe logical relationship between problem posing and problem solving * a special chapter devoted to teaching problem posing as a separate course * sketches, drawings, diagrams, and cartoons that illustrate the schemes proposed * a special section on writing in mathematics.

Person-Independent Head Pose Estimation Using Biased Manifold Embedding

Directory of Open Access Journals (Sweden)

Sethuraman Panchanathan

2008-02-01

Full Text Available Head pose estimation has been an integral problem in the study of face recognition systems and human-computer interfaces, as part of biometric applications. A fine estimate of the head pose angle is necessary and useful for several face analysis applications. To determine the head pose, face images with varying pose angles can be considered to be lying on a smooth low-dimensional manifold in high-dimensional image feature space. However, when there are face images of multiple individuals with varying pose angles, manifold learning techniques often do not give accurate results. In this work, we propose a framework for a supervised form of manifold learning called Biased Manifold Embedding to obtain improved performance in head pose angle estimation. This framework goes beyond pose estimation, and can be applied to all regression applications. This framework, although formulated for a regression scenario, unifies other supervised approaches to manifold learning that have been proposed so far. Detailed studies of the proposed method are carried out on the FacePix database, which contains 181 face images each of 30 individuals with pose angle variations at a granularity of 1∘. Since biometric applications in the real world may not contain this level of granularity in training data, an analysis of the methodology is performed on sparsely sampled data to validate its effectiveness. We obtained up to 2∘ average pose angle estimation error in the results from our experiments, which matched the best results obtained for head pose estimation using related approaches.

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.

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…

Skill Levels of Prospective Physics Teachers on Problem Posing

Science.gov (United States)

Cildir, Sema; Sezen, Nazan

2011-01-01

Problem posing is one of the topics which the educators thoroughly accentuate. Problem posing skill is defined as an introvert activity of a student's learning. In this study, skill levels of prospective physics teachers on problem posing were determined and their views on problem posing were evaluated. To this end, prospective teachers were given…

A Survey of Multi-Objective Sequential Decision-Making

NARCIS (Netherlands)

Roijers, D.M.; Vamplew, P.; Whiteson, S.; Dazeley, R.

2013-01-01

Sequential decision-making problems with multiple objectives arise naturally in practice and pose unique challenges for research in decision-theoretic planning and learning, which has largely focused on single-objective settings. This article surveys algorithms designed for sequential

Spherical blurred shape model for 3-D object and pose recognition: quantitative analysis and HCI applications in smart environments.

Science.gov (United States)

Lopes, Oscar; Reyes, Miguel; Escalera, Sergio; Gonzàlez, Jordi

2014-12-01

The use of depth maps is of increasing interest after the advent of cheap multisensor devices based on structured light, such as Kinect. In this context, there is a strong need of powerful 3-D shape descriptors able to generate rich object representations. Although several 3-D descriptors have been already proposed in the literature, the research of discriminative and computationally efficient descriptors is still an open issue. In this paper, we propose a novel point cloud descriptor called spherical blurred shape model (SBSM) that successfully encodes the structure density and local variabilities of an object based on shape voxel distances and a neighborhood propagation strategy. The proposed SBSM is proven to be rotation and scale invariant, robust to noise and occlusions, highly discriminative for multiple categories of complex objects like the human hand, and computationally efficient since the SBSM complexity is linear to the number of object voxels. Experimental evaluation in public depth multiclass object data, 3-D facial expressions data, and a novel hand poses data sets show significant performance improvements in relation to state-of-the-art approaches. Moreover, the effectiveness of the proposal is also proved for object spotting in 3-D scenes and for real-time automatic hand pose recognition in human computer interaction scenarios.

Pose Space Surface Manipulation

Directory of Open Access Journals (Sweden)

Yusuke Yoshiyasu

2012-01-01

Full Text Available Example-based mesh deformation techniques produce natural and realistic shapes by learning the space of deformations from examples. However, skeleton-based methods cannot manipulate a global mesh structure naturally, whereas the mesh-based approaches based on a translational control do not allow the user to edit a local mesh structure intuitively. This paper presents an example-driven mesh editing framework that achieves both global and local pose manipulations. The proposed system is built with a surface deformation method based on a two-step linear optimization technique and achieves direct manipulations of a model surface using translational and rotational controls. With the translational control, the user can create a model in natural poses easily. The rotational control can adjust the local pose intuitively by bending and twisting. We encode example deformations with a rotation-invariant mesh representation which handles large rotations in examples. To incorporate example deformations, we infer a pose from the handle translations/rotations and perform pose space interpolation, thereby avoiding involved nonlinear optimization. With the two-step linear approach combined with the proposed multiresolution deformation method, we can edit models at interactive rates without losing important deformation effects such as muscle bulging.

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…

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

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.

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,

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…

Perbedaan Keterampilan Pemecahan Masalah pada Pembelajaran Fisika Menggunakan Metode Problem Posing dan Problem Solving

OpenAIRE

Rahman, Adetya; Hartini, Sri; An'nur, Syubhan

2015-01-01

Teachers should be able to choose the method of learning that can help students in learning physics, namely the method of problem posing and problem solving method. The purposes of this study are : (1) describe the learning physics skills by using problem posing method, (2) describe the learning physics skills by using problem solving method, and (3) know difference between learning physics skills by using problem posing method and problem solving method in class XI of Science SMAN 6 Banjarma...

Transfer between Pose and Illumination Training in Face Recognition

Science.gov (United States)

Liu, Chang Hong; Bhuiyan, Md. Al-Amin; Ward, James; Sui, Jie

2009-01-01

The relationship between pose and illumination learning in face recognition was examined in a yes-no recognition paradigm. The authors assessed whether pose training can transfer to a new illumination or vice versa. Results show that an extensive level of pose training through a face-name association task was able to generalize to a new…

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.

Recovering the 3d Pose and Shape of Vehicles from Stereo Images

Science.gov (United States)

Coenen, M.; Rottensteiner, F.; Heipke, C.

2018-05-01

The precise reconstruction and pose estimation of vehicles plays an important role, e.g. for autonomous driving. We tackle this problem on the basis of street level stereo images obtained from a moving vehicle. Starting from initial vehicle detections, we use a deformable vehicle shape prior learned from CAD vehicle data to fully reconstruct the vehicles in 3D and to recover their 3D pose and shape. To fit a deformable vehicle model to each detection by inferring the optimal parameters for pose and shape, we define an energy function leveraging reconstructed 3D data, image information, the vehicle model and derived scene knowledge. To minimise the energy function, we apply a robust model fitting procedure based on iterative Monte Carlo model particle sampling. We evaluate our approach using the object detection and orientation estimation benchmark of the KITTI dataset (Geiger et al., 2012). Our approach can deal with very coarse pose initialisations and we achieve encouraging results with up to 82 % correct pose estimations. Moreover, we are able to deliver very precise orientation estimation results with an average absolute error smaller than 4°.

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.

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.…

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…

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…

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.

Turkish Primary School Teachers' Opinions about Problem Posing

Science.gov (United States)

Kilic, Cigdem

2013-01-01

Problem posing is one of the most important topics in a mathematics education. Through problem posing, students gain mathematical abilities and concepts and teachers can evaluate their students and arrange adequate learning environments. The aim of the present study is to investigate Turkish primary school teachers' opinions about problem posing…

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

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.

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.

Pose estimation for augmented reality applications using genetic algorithm.

Science.gov (United States)

Yu, Ying Kin; Wong, Kin Hong; Chang, Michael Ming Yuen

2005-12-01

This paper describes a genetic algorithm that tackles the pose-estimation problem in computer vision. Our genetic algorithm can find the rotation and translation of an object accurately when the three-dimensional structure of the object is given. In our implementation, each chromosome encodes both the pose and the indexes to the selected point features of the object. Instead of only searching for the pose as in the existing work, our algorithm, at the same time, searches for a set containing the most reliable feature points in the process. This mismatch filtering strategy successfully makes the algorithm more robust under the presence of point mismatches and outliers in the images. Our algorithm has been tested with both synthetic and real data with good results. The accuracy of the recovered pose is compared to the existing algorithms. Our approach outperformed the Lowe's method and the other two genetic algorithms under the presence of point mismatches and outliers. In addition, it has been used to estimate the pose of a real object. It is shown that the proposed method is applicable to augmented reality applications.

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...

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.

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.

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.

Multi-task pose-invariant face recognition.

Science.gov (United States)

Ding, Changxing; Xu, Chang; Tao, Dacheng

2015-03-01

Face images captured in unconstrained environments usually contain significant pose variation, which dramatically degrades the performance of algorithms designed to recognize frontal faces. This paper proposes a novel face identification framework capable of handling the full range of pose variations within ±90° of yaw. The proposed framework first transforms the original pose-invariant face recognition problem into a partial frontal face recognition problem. A robust patch-based face representation scheme is then developed to represent the synthesized partial frontal faces. For each patch, a transformation dictionary is learnt under the proposed multi-task learning scheme. The transformation dictionary transforms the features of different poses into a discriminative subspace. Finally, face matching is performed at patch level rather than at the holistic level. Extensive and systematic experimentation on FERET, CMU-PIE, and Multi-PIE databases shows that the proposed method consistently outperforms single-task-based baselines as well as state-of-the-art methods for the pose problem. We further extend the proposed algorithm for the unconstrained face verification problem and achieve top-level performance on the challenging LFW data set.

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...

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...

Human action recognition based on estimated weak poses

Science.gov (United States)

Gong, Wenjuan; Gonzàlez, Jordi; Roca, Francesc Xavier

2012-12-01

We present a novel method for human action recognition (HAR) based on estimated poses from image sequences. We use 3D human pose data as additional information and propose a compact human pose representation, called a weak pose, in a low-dimensional space while still keeping the most discriminative information for a given pose. With predicted poses from image features, we map the problem from image feature space to pose space, where a Bag of Poses (BOP) model is learned for the final goal of HAR. The BOP model is a modified version of the classical bag of words pipeline by building the vocabulary based on the most representative weak poses for a given action. Compared with the standard k-means clustering, our vocabulary selection criteria is proven to be more efficient and robust against the inherent challenges of action recognition. Moreover, since for action recognition the ordering of the poses is discriminative, the BOP model incorporates temporal information: in essence, groups of consecutive poses are considered together when computing the vocabulary and assignment. We tested our method on two well-known datasets: HumanEva and IXMAS, to demonstrate that weak poses aid to improve action recognition accuracies. The proposed method is scene-independent and is comparable with the state-of-art method.

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)

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…

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…

Students’ Creativity: Problem Posing in Structured Situation

Science.gov (United States)

Amalina, I. K.; Amirudin, M.; Budiarto, M. T.

2018-01-01

This is a qualitative research concerning on students’ creativity on problem posing task. The study aimed at describing the students’ creative thinking ability to pose the mathematics problem in structured situations with varied condition of given problems. In order to find out the students’ creative thinking ability, an analysis of mathematics problem posing test based on fluency, novelty, and flexibility and interview was applied for categorizing students’ responses on that task. The data analysis used the quality of problem posing and categorized in 4 level of creativity. The results revealed from 29 secondary students grade 8, a student in CTL (Creative Thinking Level) 1 met the fluency. A student in CTL 2 met the novelty, while a student in CTL 3 met both fluency and novelty and no one in CTL 4. These results are affected by students’ mathematical experience. The findings of this study highlight that student’s problem posing creativity are dependent on their experience in mathematics learning and from the point of view of which students start to pose problem.

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,...

Teaching Human Poses Interactively to a Social Robot

Science.gov (United States)

Gonzalez-Pacheco, Victor; Malfaz, Maria; Fernandez, Fernando; Salichs, Miguel A.

2013-01-01

The main activity of social robots is to interact with people. In order to do that, the robot must be able to understand what the user is saying or doing. Typically, this capability consists of pre-programmed behaviors or is acquired through controlled learning processes, which are executed before the social interaction begins. This paper presents a software architecture that enables a robot to learn poses in a similar way as people do. That is, hearing its teacher's explanations and acquiring new knowledge in real time. The architecture leans on two main components: an RGB-D (Red-, Green-, Blue- Depth) -based visual system, which gathers the user examples, and an Automatic Speech Recognition (ASR) system, which processes the speech describing those examples. The robot is able to naturally learn the poses the teacher is showing to it by maintaining a natural interaction with the teacher. We evaluate our system with 24 users who teach the robot a predetermined set of poses. The experimental results show that, with a few training examples, the system reaches high accuracy and robustness. This method shows how to combine data from the visual and auditory systems for the acquisition of new knowledge in a natural manner. Such a natural way of training enables robots to learn from users, even if they are not experts in robotics. PMID:24048336

Teaching Human Poses Interactively to a Social Robot

Directory of Open Access Journals (Sweden)

Miguel A. Salichs

2013-09-01

Full Text Available The main activity of social robots is to interact with people. In order to do that, the robot must be able to understand what the user is saying or doing. Typically, this capability consists of pre-programmed behaviors or is acquired through controlled learning processes, which are executed before the social interaction begins. This paper presents a software architecture that enables a robot to learn poses in a similar way as people do. That is, hearing its teacher’s explanations and acquiring new knowledge in real time. The architecture leans on two main components: an RGB-D (Red-, Green-, Blue- Depth -based visual system, which gathers the user examples, and an Automatic Speech Recognition (ASR system, which processes the speech describing those examples. The robot is able to naturally learn the poses the teacher is showing to it by maintaining a natural interaction with the teacher. We evaluate our system with 24 users who teach the robot a predetermined set of poses. The experimental results show that, with a few training examples, the system reaches high accuracy and robustness. This method shows how to combine data from the visual and auditory systems for the acquisition of new knowledge in a natural manner. Such a natural way of training enables robots to learn from users, even if they are not experts in robotics.

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.

Will learning to solve one-step equations pose a challenge to 8th grade students?

Science.gov (United States)

Ngu, Bing Hiong; Phan, Huy P.

2017-08-01

Assimilating multiple interactive elements simultaneously in working memory to allow understanding to occur, while solving an equation, would impose a high cognitive load. Element interactivity arises from the interaction between elements within and across operational and relational lines. Moreover, operating with special features (e.g. negative pronumeral) poses additional challenge to master equation solving skills. In an experiment, 41 8th grade students (girls = 16, boys = 25) sat for a pre-test, attended a session about equation solving, completed an acquisition phase which constituted the main intervention and were tested again in a post-test. The results showed that at post-test, students performed better on one-step equations tapping low rather than high element interactivity knowledge. In addition, students performed better on those one-step equations that contained no special features. Thus, both the degree of element interactivity and the operation with special features affect the challenge posed to 8th grade students on learning how to solve one-step equations.

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,…

A Survey of Multi-Objective Sequential Decision-Making

OpenAIRE

Roijers, D.M.; Vamplew, P.; Whiteson, S.; Dazeley, R.

2013-01-01

Sequential decision-making problems with multiple objectives arise naturally in practice and pose unique challenges for research in decision-theoretic planning and learning, which has largely focused on single-objective settings. This article surveys algorithms designed for sequential decision-making problems with multiple objectives. Though there is a growing body of literature on this subject, little of it makes explicit under what circumstances special methods are needed to solve multi-obj...

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 ...

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...

Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition

Science.gov (United States)

Yin, Xi; Liu, Xiaoming

2018-02-01

This paper explores multi-task learning (MTL) for face recognition. We answer the questions of how and why MTL can improve the face recognition performance. First, we propose a multi-task Convolutional Neural Network (CNN) for face recognition where identity classification is the main task and pose, illumination, and expression estimations are the side tasks. Second, we develop a dynamic-weighting scheme to automatically assign the loss weight to each side task, which is a crucial problem in MTL. Third, we propose a pose-directed multi-task CNN by grouping different poses to learn pose-specific identity features, simultaneously across all poses. Last but not least, we propose an energy-based weight analysis method to explore how CNN-based MTL works. We observe that the side tasks serve as regularizations to disentangle the variations from the learnt identity features. Extensive experiments on the entire Multi-PIE dataset demonstrate the effectiveness of the proposed approach. To the best of our knowledge, this is the first work using all data in Multi-PIE for face recognition. Our approach is also applicable to in-the-wild datasets for pose-invariant face recognition and achieves comparable or better performance than state of the art on LFW, CFP, and IJB-A datasets.

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.

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.

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…

Generative Learning Objects Instantiated with Random Numbers Based Expressions

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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.

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...

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

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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.

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…

Categorization of questions posed before and after inquiry-based learning

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Sandra Milena García González

2014-07-01

Full Text Available Posing research questions is the central ability of the scientific thought. This article examines the ability of sixth grade children to pose researchable questions before and after a three months’ work on a didactic sequence based on the inquiry school model. According to their purpose, the questions asked by children, after reading a text, were classified into researchable questions -susceptible to be empirically explored-, questions about a cause, and questions on a piece of data. The results show that the amount and the type of questions the students were able to pose during the intervention changed, from most of questions on data or information, to most of researchable questions, subsequently, the importance of designing teaching approaches to foster this ability was proved.

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…

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 ...

Real-Time Head Pose Estimation on Mobile Platforms

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Jianfeng Ren

2010-06-01

Full Text Available Many computer vision applications such as augmented reality require head pose estimation. As far as the real-time implementation of head pose estimation on relatively resource limited mobile platforms is concerned, it is required to satisfy real-time constraints while maintaining reasonable head pose estimation accuracy. The introduced head pose estimation approach in this paper is an attempt to meet this objective. The approach consists of the following components: Viola-Jones face detection, color-based face tracking using an online calibration procedure, and head pose estimation using Hu moment features and Fisher linear discriminant. Experimental results running on an actual mobile device are reported exhibiting both the real- time and accuracy aspects of the developed approach.

Stereovision-based pose and inertia estimation of unknown and uncooperative space objects

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Pesce, Vincenzo; Lavagna, Michèle; Bevilacqua, Riccardo

2017-01-01

Autonomous close proximity operations are an arduous and attractive problem in space mission design. In particular, the estimation of pose, motion and inertia properties of an uncooperative object is a challenging task because of the lack of available a priori information. This paper develops a novel method to estimate the relative position, velocity, angular velocity, attitude and the ratios of the components of the inertia matrix of an uncooperative space object using only stereo-vision measurements. The classical Extended Kalman Filter (EKF) and an Iterated Extended Kalman Filter (IEKF) are used and compared for the estimation procedure. In addition, in order to compute the inertia properties, the ratios of the inertia components are added to the state and a pseudo-measurement equation is considered in the observation model. The relative simplicity of the proposed algorithm could be suitable for an online implementation for real applications. The developed algorithm is validated by numerical simulations in MATLAB using different initial conditions and uncertainty levels. The goal of the simulations is to verify the accuracy and robustness of the proposed estimation algorithm. The obtained results show satisfactory convergence of estimation errors for all the considered quantities. The obtained results, in several simulations, shows some improvements with respect to similar works, which deal with the same problem, present in literature. In addition, a video processing procedure is presented to reconstruct the geometrical properties of a body using cameras. This inertia reconstruction algorithm has been experimentally validated at the ADAMUS (ADvanced Autonomous MUltiple Spacecraft) Lab at the University of Florida. In the future, this different method could be integrated to the inertia ratios estimator to have a complete tool for mass properties recognition.

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…

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!

Elaboration of Statistics Learning Objects for Mobile Devices

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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.

Precise Object Tracking under Deformation

International Nuclear Information System (INIS)

Saad, M.H.

2010-01-01

The precise object tracking is an essential issue in several serious applications such as; robot vision, automated surveillance (civil and military), inspection, biomedical image analysis, video coding, motion segmentation, human-machine interface, visualization, medical imaging, traffic systems, satellite imaging etc. This framework focuses on the precise object tracking under deformation such as scaling, rotation, noise, blurring and change of illumination. This research is a trail to solve these serious problems in visual object tracking by which the quality of the overall system will be improved. Developing a three dimensional (3D) geometrical model to determine the current pose of an object and predict its future location based on FIR model learned by the OLS. This framework presents a robust ranging technique to track a visual target instead of the traditional expensive ranging sensors. The presented research work is applied to real video stream and achieved high precession results. xiiiThe precise object tracking is an essential issue in several serious applications such as; robot vision, automated surveillance (civil and military), inspection, biomedical image analysis, video coding, motion segmentation, human-machine interface, visualization, medical imaging, traffic systems, satellite imaging etc. This framework focuses on the precise object tracking under deformation such as scaling, rotation, noise, blurring and change of illumination. This research is a trail to solve these serious problems in visual object tracking by which the quality of the overall system will be improved. Developing a three dimensional (3D) geometrical model to determine the current pose of an object and predict its future location based on FIR model learned by the OLS. This framework presents a robust ranging technique to track a visual target instead of the traditional expensive ranging sensors. The presented research work is applied to real video stream and achieved high

EFEKTIVITAS PEMBELAJARAN MATEMATIKA DENGAN METODE PROBLEM POSING BERBASIS PENDIDIKAN KARAKTER

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Eka Lia Susanti

2012-06-01

Full Text Available Abstract Tujuan penelitian ini adalah untuk mengetahui apakah pembelajaran matematika dengan metode Problem Posing berbasis pendidikan karakter di laboratorium TeenZania pada materi garis singgung lingkaran efektif. Populasi dalam penelitian ini adalah peserta didik di SMP N 2 Pati. Sampel dalam penelitian ini diambil dengan teknik cluster random sampling. Variabel dalam penelitian ini yaitu keaktifan sebagai variabel independen dan prestasi belajar sebagai variabel dependen. Cara pengambilan data dengan lembar pengamatan dan tes. Data diolah dengan uji banding t dan uji pengaruh regresi. Hasil penelitian menunjukkan bahwa prestasi belajar kelas eksperimen (82,74 secara statistik melebihi KKM (75. Dengan uji regresi linear sederhana diperoleh persamaan regresi ?=-15,847 + 1,194X dan R^2=0,829. Koefisien X merupakan bilangan positif sehingga keaktifan berpengaruh positif pada prestasi belajar sebesar 82,9%. Rata-rata prestasi belajar kelas eksperimen (82,74 dan rata-rata prestasi belajar kelas kontrol (72,91. Secara uji stastistik prestasi belajar kelas eksperimen lebih baik daripada prestasi belajar kelas kontrol. Berdasarkan hasil analisis disimpulkan (1 pembelajaran mencapai tuntas belajar; (2 adanya pengaruh positif pada keaktifan terhadap prestasi belajar; dan (3 prestasi belajar kelas eksperimen lebih baik daripada prestasi belajar kelas kontrol; sehingga pembelajaran matematika dengan metode problem posing berbasis pendidikan karakter di laboratorium TeenZania merupakan pembelajaran yang efektif. The purpose of this study was to determine whether the learning of mathematics by Problem Posing method in a TeenZania laboratory based character education in circle tangent material effectively. The population in this study were students in SMP N 2 Pati. The sample in this study were drawn by cluster random sampling technique. The variables in this study is the activity as an independent variable and learning achievement as the dependent variable

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

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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.

The Effect of Problem Solving and Problem Posing Models and Innate Ability to Students Achievement

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Ratna Kartika Irawati

2015-04-01

Full Text Available Pengaruh Model Problem Solving dan Problem Posing serta Kemampuan Awal terhadap Hasil Belajar Siswa   Abstract: Chemistry concepts understanding features abstract quality and requires higher order thinking skills. Yet, the learning on chemistry has not boost the higher order thinking skills of the students. The use of the learning model of Problem Solving and Problem Posing in observing the innate ability of the student is expected to resolve the issue. This study aims to determine the learning model which is effective to improve the study of the student with different level of innate ability. This study used the quasi-experimental design. The research data used in this research is the quiz/test of the class which consist of 14 multiple choice questions and 5 essay questions. The data analysis used is ANOVA Two Ways. The results showed that Problem Posing is more effective to improve the student compared to Problem Solving, students with high level of innate ability have better outcomes in learning rather than the students with low level of innate ability after being applied with the Problem solving and Problem posing model, further, Problem Solving and Problem Posing is more suitable to be applied to the students with high level of innate ability. Key Words: problem solving, problem posing, higher order thinking skills, innate ability, learning outcomes   Abstrak: Pemahaman konsep-konsep kimia yang bersifat abstrak membutuhkan keterampilan berpikir tingkat tinggi. Pembelajaran kimia belum mendorong siswa melakukan keterampilan berpikir tingkat tinggi. Penggunaan model pembelajaran Problem Solving dan Problem Posing dengan memperhatikan kemampuan awal siswa diduga dapat mengatasi masalah tersebut. Penelitian ini bertujuan untuk mengetahui model pembelajaran yang efektif dalam meningkatkan hasil belajar dengan kemampuan awal siswa yang berbeda. Penelitian ini menggunakan rancangan eksperimen semu. Data penelitian menggunakan tes hasil belajar

An anti-disturbing real time pose estimation method and system

Science.gov (United States)

Zhou, Jian; Zhang, Xiao-hu

2011-08-01

Pose estimation relating two-dimensional (2D) images to three-dimensional (3D) rigid object need some known features to track. In practice, there are many algorithms which perform this task in high accuracy, but all of these algorithms suffer from features lost. This paper investigated the pose estimation when numbers of known features or even all of them were invisible. Firstly, known features were tracked to calculate pose in the current and the next image. Secondly, some unknown but good features to track were automatically detected in the current and the next image. Thirdly, those unknown features which were on the rigid and could match each other in the two images were retained. Because of the motion characteristic of the rigid object, the 3D information of those unknown features on the rigid could be solved by the rigid object's pose at the two moment and their 2D information in the two images except only two case: the first one was that both camera and object have no relative motion and camera parameter such as focus length, principle point, and etc. have no change at the two moment; the second one was that there was no shared scene or no matched feature in the two image. Finally, because those unknown features at the first time were known now, pose estimation could go on in the followed images in spite of the missing of known features in the beginning by repeating the process mentioned above. The robustness of pose estimation by different features detection algorithms such as Kanade-Lucas-Tomasi (KLT) feature, Scale Invariant Feature Transform (SIFT) and Speed Up Robust Feature (SURF) were compared and the compact of the different relative motion between camera and the rigid object were discussed in this paper. Graphic Processing Unit (GPU) parallel computing was also used to extract and to match hundreds of features for real time pose estimation which was hard to work on Central Processing Unit (CPU). Compared with other pose estimation methods, this new

An Investigation of Eighth Grade Students' Problem Posing Skills (Turkey Sample)

Science.gov (United States)

Arikan, Elif Esra; Ünal, Hasan

2015-01-01

To pose a problem refers to the creative activity for mathematics education. The purpose of the study was to explore the eighth grade students' problem posing ability. Three learning domains such as requiring four operations, fractions and geometry were chosen for this reason. There were two classes which were coded as class A and class B. Class A…

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.

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…

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.

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...

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.

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.

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.

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…

Problem-Posing in Education: Transformation of the Practice of the Health Professional.

Science.gov (United States)

Casagrande, L. D. R.; Caron-Ruffino, M.; Rodrigues, R. A. P.; Vendrusculo, D. M. S.; Takayanagui, A. M. M.; Zago, M. M. F.; Mendes, M. D.

1998-01-01

Studied the use of a problem-posing model in health education. The model based on the ideas of Paulo Freire is presented. Four innovative experiences of teaching-learning in environmental and occupational health and patient education are reported. Notes that the problem-posing model has the capability to transform health-education practice.…

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.

Learning Grasp Affordance Densities

DEFF Research Database (Denmark)

Detry, Renaud; Kraft, Dirk; Kroemer, Oliver

2011-01-01

and relies on kernel density estimation to provide a continuous model. Grasp densities are learned and refined from exploration, by letting a robot “play” with an object in a sequence of graspand-drop actions: The robot uses visual cues to generate a set of grasp hypotheses; it then executes......We address the issue of learning and representing object grasp affordance models. We model grasp affordances with continuous probability density functions (grasp densities) which link object-relative grasp poses to their success probability. The underlying function representation is nonparametric...... these and records their outcomes. When a satisfactory number of grasp data is available, an importance-sampling algorithm turns these into a grasp density. We evaluate our method in a largely autonomous learning experiment run on three objects of distinct shapes. The experiment shows how learning increases success...

Integrating Worked Examples into Problem Posing in a Web-Based Learning Environment

Science.gov (United States)

Hsiao, Ju-Yuan; Hung, Chun-Ling; Lan, Yu-Feng; Jeng, Yoau-Chau

2013-01-01

Most students always lack of experience and perceive difficult regarding problem posing. The study hypothesized that worked examples may have benefits for supporting students' problem posing activities. A quasi-experiment was conducted in the context of a business mathematics course for examining the effects of integrating worked examples into…

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.

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).

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.

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.

A multi-camera system for real-time pose estimation

Science.gov (United States)

Savakis, Andreas; Erhard, Matthew; Schimmel, James; Hnatow, Justin

2007-04-01

This paper presents a multi-camera system that performs face detection and pose estimation in real-time and may be used for intelligent computing within a visual sensor network for surveillance or human-computer interaction. The system consists of a Scene View Camera (SVC), which operates at a fixed zoom level, and an Object View Camera (OVC), which continuously adjusts its zoom level to match objects of interest. The SVC is set to survey the whole filed of view. Once a region has been identified by the SVC as a potential object of interest, e.g. a face, the OVC zooms in to locate specific features. In this system, face candidate regions are selected based on skin color and face detection is accomplished using a Support Vector Machine classifier. The locations of the eyes and mouth are detected inside the face region using neural network feature detectors. Pose estimation is performed based on a geometrical model, where the head is modeled as a spherical object that rotates upon the vertical axis. The triangle formed by the mouth and eyes defines a vertical plane that intersects the head sphere. By projecting the eyes-mouth triangle onto a two dimensional viewing plane, equations were obtained that describe the change in its angles as the yaw pose angle increases. These equations are then combined and used for efficient pose estimation. The system achieves real-time performance for live video input. Testing results assessing system performance are presented for both still images and video.

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.

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

Comparison On Matching Methods Used In Pose Tracking For 3D Shape Representation

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Khin Kyu Kyu Win

2017-01-01

Full Text Available In this work three different algorithms such as Brute Force Delaunay Triangulation and k-d Tree are analyzed on matching comparison for 3D shape representation. It is intended for developing the pose tracking of moving objects in video surveillance. To determine 3D pose of moving objects some tracking system may require full 3D pose estimation of arbitrarily shaped objects in real time. In order to perform 3D pose estimation in real time each step in the tracking algorithm must be computationally efficient. This paper presents method comparison for the computationally efficient registration of 3D shapes including free-form surfaces. Matching of free-form surfaces are carried out by using geometric point matching algorithm ICP. Several aspects of the ICP algorithm are investigated and analyzed by using specified surface setup. The surface setup processed in this system is represented by simple geometric primitive dealing with objects of free-from shape. Considered representations are a cloud of points.

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.

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...

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Science.gov (United States)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Directory of Open Access Journals (Sweden)

Aichun Zhu

2018-03-01

Full Text Available This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN. Firstly, a Relative Mixture Deformable Model (RMDM is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Learning Ontology from Object-Relational Database

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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.

Novelty Detection for Interactive Pose Recognition by a Social Robot

Directory of Open Access Journals (Sweden)

Victor Gonzalez-Pacheco

2015-04-01

Full Text Available Active robot learners take an active role in their own learning by making queries to their human teachers when they receive new data. However, not every received input is useful for the robot, and asking for non-informative inputs or asking too many questions might worsen the user's perception of the robot. We present a novelty detection system that enables a robot to ask labels for new stimuli only when they seem both novel and interesting. Our system separates the decision process into two steps: first, it discriminates novel from known stimuli, and second, it estimates if these stimuli are likely to happen again. Our approach uses the notion of curiosity, which controls the eagerness with which the robot asks questions to the user. We evaluate our approach in the domain of pose learning by training our robot with a set of pointing poses able to detect up to 84%, 79%, and 78% of the observed novelties in three different experiments. Our approach enables robots to keep learning continuously, even after training is finished. The introduction of the curiosity parameter allows tuning, for the conditions in which the robot should want to learn more.

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…

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.

Meanings Given to Algebraic Symbolism in Problem-Posing

Science.gov (United States)

Cañadas, María C.; Molina, Marta; del Río, Aurora

2018-01-01

Some errors in the learning of algebra suggest that students might have difficulties giving meaning to algebraic symbolism. In this paper, we use problem posing to analyze the students' capacity to assign meaning to algebraic symbolism and the difficulties that students encounter in this process, depending on the characteristics of the algebraic…

A Convergent Participation Model for Evaluation of Learning Objects

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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.

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,…

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…

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

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.

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

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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.

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.

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.)

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.

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.

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

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.

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...

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.

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

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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.

Problem Posing

OpenAIRE

Šilhavá, Marie

2009-01-01

This diploma thesis concentrates on problem posing from the students' point of view. Problem posing can be either seen as a teaching method which can be used in the class, or it can be used as a tool for researchers or teachers to assess the level of students' understanding of the topic. In my research, I compare three classes, one mathematics specialist class and two generalist classes, in their ability of problem posing. As an assessment tool it seemed that mathemathics specialists were abl...

Locating binding poses in protein-ligand systems using reconnaissance metadynamics

Science.gov (United States)

Söderhjelm, Pär; Tribello, Gareth A.; Parrinello, Michele

2012-01-01

A molecular dynamics-based protocol is proposed for finding and scoring protein-ligand binding poses. This protocol uses the recently developed reconnaissance metadynamics method, which employs a self-learning algorithm to construct a bias that pushes the system away from the kinetic traps where it would otherwise remain. The exploration of phase space with this algorithm is shown to be roughly six to eight times faster than unbiased molecular dynamics and is only limited by the time taken to diffuse about the surface of the protein. We apply this method to the well-studied trypsin–benzamidine system and show that we are able to refind all the poses obtained from a reference EADock blind docking calculation. These poses can be scored based on the length of time the system remains trapped in the pose. Alternatively, one can perform dimensionality reduction on the output trajectory and obtain a map of phase space that can be used in more expensive free-energy calculations. PMID:22440749

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.

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…

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.

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

Precise object tracking under deformation

International Nuclear Information System (INIS)

Saad, M.H

2010-01-01

The precise object tracking is an essential issue in several serious applications such as; robot vision, automated surveillance (civil and military), inspection, biomedical image analysis, video coding, motion segmentation, human-machine interface, visualization, medical imaging, traffic systems, satellite imaging etc. This frame-work focuses on the precise object tracking under deformation such as scaling , rotation, noise, blurring and change of illumination. This research is a trail to solve these serious problems in visual object tracking by which the quality of the overall system will be improved. Developing a three dimensional (3D) geometrical model to determine the current pose of an object and predict its future location based on FIR model learned by the OLS. This framework presents a robust ranging technique to track a visual target instead of the traditional expensive ranging sensors. The presented research work is applied to real video stream and achieved high precession results.

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,…

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

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.

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…

[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.

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...

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

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…

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.

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…

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…

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.…

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

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.

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…

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…

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…

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.

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.

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.

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,…

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

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

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.

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

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

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.

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.

Yoga Poses Increase Subjective Energy and State Self-Esteem in Comparison to 'Power Poses'.

Science.gov (United States)

Golec de Zavala, Agnieszka; Lantos, Dorottya; Bowden, Deborah

2017-01-01

Research on beneficial consequences of yoga focuses on the effects of yogic breathing and meditation. Less is known about the psychological effects of performing yoga postures. The present study investigated the effects of yoga poses on subjective sense of energy and self-esteem. The effects of yoga postures were compared to the effects of 'power poses,' which arguably increase the sense of power and self-confidence due to their association with interpersonal dominance (Carney et al., 2010). The study tested the novel prediction that yoga poses, which are not associated with interpersonal dominance but increase bodily energy, would increase the subjective feeling of energy and therefore increase self-esteem compared to 'high power' and 'low power' poses. A two factorial, between participants design was employed. Participants performed either two standing yoga poses with open front of the body ( n = 19), two standing yoga poses with covered front of the body ( n = 22), two expansive, high power poses ( n = 21), or two constrictive, low power poses ( n = 20) for 1-min each. The results showed that yoga poses in comparison to 'power poses' increased self-esteem. This effect was mediated by an increased subjective sense of energy and was observed when baseline trait self-esteem was controlled for. These results suggest that the effects of performing open, expansive body postures may be driven by processes other than the poses' association with interpersonal power and dominance. This study demonstrates that positive effects of yoga practice can occur after performing yoga poses for only 2 min.

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.

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.

Enhancing students’ mathematical problem posing skill through writing in performance tasks strategy

Science.gov (United States)

Kadir; Adelina, R.; Fatma, M.

2018-01-01

Many researchers have studied the Writing in Performance Task (WiPT) strategy in learning, but only a few paid attention on its relation to the problem-posing skill in mathematics. The problem-posing skill in mathematics covers problem reformulation, reconstruction, and imitation. The purpose of the present study was to examine the effect of WiPT strategy on students’ mathematical problem-posing skill. The research was conducted at a Public Junior Secondary School in Tangerang Selatan. It used a quasi-experimental method with randomized control group post-test. The samples were 64 students consists of 32 students of the experiment group and 32 students of the control. A cluster random sampling technique was used for sampling. The research data were obtained by testing. The research shows that the problem-posing skill of students taught by WiPT strategy is higher than students taught by a conventional strategy. The research concludes that the WiPT strategy is more effective in enhancing the students’ mathematical problem-posing skill compared to the conventional strategy.

PENGARUH DARI PROBLEM POSING METHOD TERHADAP KREATIVITAS VERBAL SISWA SMP KELAS VII

Directory of Open Access Journals (Sweden)

Bagus Priambodo

2013-10-01

Full Text Available Verbal creativity is the ability to think fluent, flexible, and original that manifested through the words. Psychological freedom is one factor that can develop creativity. One alternative teaching methods that provide freedom in an atmosphere of learning is the Problem Posing Method (PPM which is triggered by Paulo Freire. This research aims to determine the presence or absence of the influence of PPM on verbal creativity. Characteristic of the subjects was junior high school students in grade 7th, received conventional learning materials, and have never had learning by using PPM. This study used a non-randomized pretest-posttest control group design. Subjects in the study were divided into two, experimental group (N = 33 and control group (N= 35. The data was collected using the Verbal Creativity Test. The results of hypothesis testing used Independent Sample T Test techniques showed the differences of mean = 3.294, α = 0.014 with (p<0.05. Keywords: Verbal creativity, problem posing method, a test of verbal creativity, junior high school students

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

The effect of problem posing and problem solving with realistic mathematics education approach to the conceptual understanding and adaptive reasoning

Science.gov (United States)

Mahendra, Rengga; Slamet, Isnandar; Budiyono

2017-12-01

One of the difficulties of students in learning mathematics is on the subject of geometry that requires students to understand abstract things. The aim of this research is to determine the effect of learning model Problem Posing and Problem Solving with Realistic Mathematics Education Approach to conceptual understanding and students' adaptive reasoning in learning mathematics. This research uses a kind of quasi experimental research. The population of this research is all seventh grade students of Junior High School 1 Jaten, Indonesia. The sample was taken using stratified cluster random sampling technique. The test of the research hypothesis was analyzed by using t-test. The results of this study indicate that the model of Problem Posing learning with Realistic Mathematics Education Approach can improve students' conceptual understanding significantly in mathematics learning. In addition tu, the results also showed that the model of Problem Solving learning with Realistic Mathematics Education Approach can improve students' adaptive reasoning significantly in learning mathematics. Therefore, the model of Problem Posing and Problem Solving learning with Realistic Mathematics Education Approach is appropriately applied in mathematics learning especially on the subject of geometry so as to improve conceptual understanding and students' adaptive reasoning. Furthermore, the impact can improve student achievement.

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...

Boneless Pose Editing and Animation

DEFF Research Database (Denmark)

Bærentzen, Jakob Andreas; Hansen, Kristian Evers; Erleben, Kenny

2007-01-01

In this paper, we propose a pose editing and animation method for triangulated surfaces based on a user controlled partitioning of the model into deformable parts and rigid parts which are denoted handles. In our pose editing system, the user can sculpt a set of poses simply by transforming...... the handles for each pose. Using Laplacian editing, the deformable parts are deformed to match the handles. In our animation system the user can constrain one or several handles in order to define a new pose. New poses are interpolated from the examples poses, by solving a small non-linear optimization...... problem in order to obtain the interpolation weights. While the system can be used simply for building poses, it is also an animation system. The user can specify a path for a given constraint and the model is animated correspondingly....

Penerapan Pendekatan Contextual Teaching and Learning (Ctl) Dengan Model Problem Posing Untuk Meningkatkan Kualitas Pembelajaran Biologi Siswa Kelas X.2 SMA Negeri 2 Karanganyar Tahun Pelajaran 2011/2012

OpenAIRE

Suparmi, Suparmi; Suciati, Suciati; Harlita, Harlita

2013-01-01

– This research aims to improve low quality of biology in class X.2 SMA Negeri 2 Karanganyar in academic year 2011/2012. Learning considered by teacher's performance, utility of facilities in the classroom, classroom climate, student's scientific attitude, and student motivation of achievement applying for approach Contextual Teaching and Learning with Problem Posing model. This research was a classroom action research which and performed in three cycles. Each cycle consisted of 4 ...

Regularization theory for ill-posed problems selected topics

CERN Document Server

Lu, Shuai

2013-01-01

Thismonograph is a valuable contribution to thehighly topical and extremly productive field ofregularisationmethods for inverse and ill-posed problems. The author is an internationally outstanding and acceptedmathematicianin this field. In his book he offers a well-balanced mixtureof basic and innovative aspects.He demonstrates new,differentiatedviewpoints, and important examples for applications. The bookdemontrates thecurrent developments inthe field of regularization theory,such as multiparameter regularization and regularization in learning theory. The book is written for graduate and PhDs

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...

A Grasp-Pose Generation Method Based on Gaussian Mixture Models

Directory of Open Access Journals (Sweden)

Wenjia Wu

2015-11-01

Full Text Available A Gaussian Mixture Model (GMM-based grasp-pose generation method is proposed in this paper. Through offline training, the GMM is set up and used to depict the distribution of the robot's reachable orientations. By dividing the robot's workspace into small 3D voxels and training the GMM for each voxel, a look-up table covering all the workspace is built with the x, y and z positions as the index and the GMM as the entry. Through the definition of Task Space Regions (TSR, an object's feasible grasp poses are expressed as a continuous region. With the GMM, grasp poses can be preferentially sampled from regions with high reachability probabilities in the online grasp-planning stage. The GMM can also be used as a preliminary judgement of a grasp pose's reachability. Experiments on both a simulated and a real robot show the superiority of our method over the existing method.

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.

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.

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…

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...

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, �

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

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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,…

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.

Investigasi Kemampuan Problem Solving dan Problem Posing Matematis Mahasiswa Via Pendekatan Realistic

OpenAIRE

Afriansyah, Ekasatya Aldila

2016-01-01

Mathematical problem solving and problem posing skill are the mathematical skills that need to be owned by students. By having this skill, students can be more creative in expressing ideas by connecting the knowledge that they held previously. But in reality, there are some students who are lack of problem solving skill; therefore it is really important to improve learning through appropriate approach. Realistic approach had been chosen as the learning theory to be applied in the class. This ...

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.

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.

Camera pose estimation for augmented reality in a small indoor dynamic scene

Science.gov (United States)

Frikha, Rawia; Ejbali, Ridha; Zaied, Mourad

2017-09-01

Camera pose estimation remains a challenging task for augmented reality (AR) applications. Simultaneous localization and mapping (SLAM)-based methods are able to estimate the six degrees of freedom camera motion while constructing a map of an unknown environment. However, these methods do not provide any reference for where to insert virtual objects since they do not have any information about scene structure and may fail in cases of occlusion of three-dimensional (3-D) map points or dynamic objects. This paper presents a real-time monocular piece wise planar SLAM method using the planar scene assumption. Using planar structures in the mapping process allows rendering virtual objects in a meaningful way on the one hand and improving the precision of the camera pose and the quality of 3-D reconstruction of the environment by adding constraints on 3-D points and poses in the optimization process on the other hand. We proposed to benefit from the 3-D planes rigidity motion in the tracking process to enhance the system robustness in the case of dynamic scenes. Experimental results show that using a constrained planar scene improves our system accuracy and robustness compared with the classical SLAM systems.

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).

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

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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.

Learning Visual Representations for Perception-Action Systems

DEFF Research Database (Denmark)

Piater, Justus; Jodogne, Sebastien; Detry, Renaud

2011-01-01

and RLJC, our second method learns structural object models for robust object detection and pose estimation by probabilistic inference. To these models, the method associates grasp experiences autonomously learned by trial and error. These experiences form a nonparametric representation of grasp success......We discuss vision as a sensory modality for systems that effect actions in response to perceptions. While the internal representations informed by vision may be arbitrarily complex, we argue that in many cases it is advantageous to link them rather directly to action via learned mappings....... These arguments are illustrated by two examples of our own work. First, our RLVC algorithm performs reinforcement learning directly on the visual input space. To make this very large space manageable, RLVC interleaves the reinforcement learner with a supervised classification algorithm that seeks to split...

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.

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...

Probabilistic Mapping of Human Visual Attention from Head Pose Estimation

Directory of Open Access Journals (Sweden)

Andrea Veronese

2017-10-01

Full Text Available Effective interaction between a human and a robot requires the bidirectional perception and interpretation of actions and behavior. While actions can be identified as a directly observable activity, this might not be sufficient to deduce actions in a scene. For example, orienting our face toward a book might suggest the action toward “reading.” For a human observer, this deduction requires the direction of gaze, the object identified as a book and the intersection between gaze and book. With this in mind, we aim to estimate and map human visual attention as directed to a scene, and assess how this relates to the detection of objects and their related actions. In particular, we consider human head pose as measurement to infer the attention of a human engaged in a task and study which prior knowledge should be included in such a detection system. In a user study, we show the successful detection of attention to objects in a typical office task scenario (i.e., reading, working with a computer, studying an object. Our system requires a single external RGB camera for head pose measurements and a pre-recorded 3D point cloud of the environment.

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.

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.

Using Online Modelled Spatial Constraints for Pose Estimation in an Industrial Setting

DEFF Research Database (Denmark)

Meyer, Kenneth Korsgaard; Wolniakowski, Adam; Hagelskjær, Frederik

2017-01-01

We introduce a vision system that is able to on-line learn spatial constraints to improve pose estimation in terms of correct recognition as well as computational speed. By making use of a simulated industrial robot system performing various pick and place tasks, we show the effect of model...

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.

The relative pose estimation of aircraft based on contour model

Science.gov (United States)

Fu, Tai; Sun, Xiangyi

2017-02-01

This paper proposes a relative pose estimation approach based on object contour model. The first step is to obtain a two-dimensional (2D) projection of three-dimensional (3D)-model-based target, which will be divided into 40 forms by clustering and LDA analysis. Then we proceed by extracting the target contour in each image and computing their Pseudo-Zernike Moments (PZM), thus a model library is constructed in an offline mode. Next, we spot a projection contour that resembles the target silhouette most in the present image from the model library with reference of PZM; then similarity transformation parameters are generated as the shape context is applied to match the silhouette sampling location, from which the identification parameters of target can be further derived. Identification parameters are converted to relative pose parameters, in the premise that these values are the initial result calculated via iterative refinement algorithm, as the relative pose parameter is in the neighborhood of actual ones. At last, Distance Image Iterative Least Squares (DI-ILS) is employed to acquire the ultimate relative pose parameters.

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.

A review of cooperative and uncooperative spacecraft pose determination techniques for close-proximity operations

Science.gov (United States)

Opromolla, Roberto; Fasano, Giancarmine; Rufino, Giancarlo; Grassi, Michele

2017-08-01

The capability of an active spacecraft to accurately estimate its relative position and attitude (pose) with respect to an active/inactive, artificial/natural space object (target) orbiting in close-proximity is required to carry out various activities like formation flying, on-orbit servicing, active debris removal, and space exploration. According to the specific mission scenario, the pose determination task involves both theoretical and technological challenges related to the search for the most suitable algorithmic solution and sensor architecture, respectively. As regards the latter aspect, electro-optical sensors represent the best option as their use is compatible with mass and power limitation of micro and small satellites, and their measurements can be processed to estimate all the pose parameters. Overall, the degree of complexity of the challenges related to pose determination largely varies depending on the nature of the targets, which may be actively/passively cooperative, uncooperative but known, or uncooperative and unknown space objects. In this respect, while cooperative pose determination has been successfully demonstrated in orbit, the uncooperative case is still under study by universities, research centers, space agencies and private companies. However, in both the cases, the demand for space applications involving relative navigation maneuvers, also in close-proximity, for which pose determination capabilities are mandatory, is significantly increasing. In this framework, a review of state-of-the-art techniques and algorithms developed in the last decades for cooperative and uncooperative pose determination by processing data provided by electro-optical sensors is herein presented. Specifically, their main advantages and drawbacks in terms of achieved performance, computational complexity, and sensitivity to variability of pose and target geometry, are highlighted.

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

Pose Estimation using a Hierarchical 3D Representation of Contours and Surfaces

DEFF Research Database (Denmark)

Buch, Anders Glent; Kraft, Dirk; Kämäräinen, Joni-Kristian

2013-01-01

We present a system for detecting the pose of rigid objects using texture and contour information. From a stereo image view of a scene, a sparse hierarchical scene representation is reconstructed using an early cognitive vision system. We define an object model in terms of a simple context...

An Improved Method of Pose Estimation for Lighthouse Base Station Extension.

Science.gov (United States)

Yang, Yi; Weng, Dongdong; Li, Dong; Xun, Hang

2017-10-22

In 2015, HTC and Valve launched a virtual reality headset empowered with Lighthouse, the cutting-edge space positioning technology. Although Lighthouse is superior in terms of accuracy, latency and refresh rate, its algorithms do not support base station expansion, and is flawed concerning occlusion in moving targets, that is, it is unable to calculate their poses with a small set of sensors, resulting in the loss of optical tracking data. In view of these problems, this paper proposes an improved pose estimation algorithm for cases where occlusion is involved. Our algorithm calculates the pose of a given object with a unified dataset comprising of inputs from sensors recognized by all base stations, as long as three or more sensors detect a signal in total, no matter from which base station. To verify our algorithm, HTC official base stations and autonomous developed receivers are used for prototyping. The experiment result shows that our pose calculation algorithm can achieve precise positioning when a few sensors detect the signal.

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.

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…

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...

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.

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

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.

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…

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.

EDUCATIONAL PERSPECTIVES ON SIMULATED LEARNING IN WOUND MANAGEMENT

DEFF Research Database (Denmark)

Christiansen, Sytter; Rethmeier, Anita

authenticity of the simulated learning. The objectives of the course are that students can identify different kinds of chronic wounds and risk factors contributing to decreased wound healing. This demands knowledge related to skin and wound types. We used five medium fidelity mannequins equipped......Aim: The aim was to explore whether simulated learning is useful in relation to wound management among undergraduate student nurses. Methods: A key element in simulated learning is to create an authentic environment. The pur-pose of establishing collaboration with a private company was to keep...

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.

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....

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.

Statistical Model-Based Face Pose Estimation

Institute of Scientific and Technical Information of China (English)

GE Xinliang; YANG Jie; LI Feng; WANG Huahua

2007-01-01

A robust face pose estimation approach is proposed by using face shape statistical model approach and pose parameters are represented by trigonometric functions. The face shape statistical model is firstly built by analyzing the face shapes from different people under varying poses. The shape alignment is vital in the process of building the statistical model. Then, six trigonometric functions are employed to represent the face pose parameters. Lastly, the mapping function is constructed between face image and face pose by linearly relating different parameters. The proposed approach is able to estimate different face poses using a few face training samples. Experimental results are provided to demonstrate its efficiency and accuracy.

The investigation and implementation of real-time face pose and direction estimation on mobile computing devices

Science.gov (United States)

Fu, Deqian; Gao, Lisheng; Jhang, Seong Tae

2012-04-01

The mobile computing device has many limitations, such as relative small user interface and slow computing speed. Usually, augmented reality requires face pose estimation can be used as a HCI and entertainment tool. As far as the realtime implementation of head pose estimation on relatively resource limited mobile platforms is concerned, it is required to face different constraints while leaving enough face pose estimation accuracy. The proposed face pose estimation method met this objective. Experimental results running on a testing Android mobile device delivered satisfactory performing results in the real-time and accurately.

Fraction Multiplication and Division Word Problems Posed by Different Years of Pre-Service Elementary Mathematics Teachers

Directory of Open Access Journals (Sweden)

Tuba Aydogdu Iskenderoglu

2018-04-01

Full Text Available It is important for pre-service teachers to know the conceptual difficulties they have experienced regarding the concepts of multiplication and division in fractions and problem posing is a way to learn these conceptual difficulties. Problem posing is a synthetic activity that fundamentally has multiple answers. The purpose of this study is to analyze the multiplication and division of fractions problems posed by pre-service elementary mathematics teachers and to investigate how the problems posed change according to the year of study the pre-service teachers are in. The study employed developmental research methods. A total of 213 pre-service teachers enrolled in different years of the Elementary Mathematics Teaching program at a state university in Turkey took part in the study. The “Problem Posing Test” was used as the data collecting tool. In this test, there are 3 multiplication and 3 division operations. The data were analyzed using qualitative descriptive analysis. The findings suggest that, regardless of the year, pre-service teachers had more conceptual difficulties in problem posing about the division of fractions than in problem posing about the multiplication of fractions.

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.

[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.

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.

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.

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…

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).

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.

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

Transforming clinical imaging and 3D data for virtual reality learning objects: HTML5 and mobile devices implementation.

Science.gov (United States)

Trelease, Robert B; Nieder, Gary L

2013-01-01

Web deployable anatomical simulations or "virtual reality learning objects" can easily be produced with QuickTime VR software, but their use for online and mobile learning is being limited by the declining support for web browser plug-ins for personal computers and unavailability on popular mobile devices like Apple iPad and Android tablets. This article describes complementary methods for creating comparable, multiplatform VR learning objects in the new HTML5 standard format, circumventing platform-specific limitations imposed by the QuickTime VR multimedia file format. Multiple types or "dimensions" of anatomical information can be embedded in such learning objects, supporting different kinds of online learning applications, including interactive atlases, examination questions, and complex, multi-structure presentations. Such HTML5 VR learning objects are usable on new mobile devices that do not support QuickTime VR, as well as on personal computers. Furthermore, HTML5 VR learning objects can be embedded in "ebook" document files, supporting the development of new types of electronic textbooks on mobile devices that are increasingly popular and self-adopted for mobile learning. © 2012 American Association of Anatomists.

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.

Pengenalan Pose Tangan Menggunakan HuMoment

Directory of Open Access Journals (Sweden)

Dina Budhi Utami

2017-02-01

Full Text Available Computer vision yang didasarkan pada pengenalan bentuk memiliki banyak potensi dalam interaksi manusia dan komputer. Pose tangan dapat dijadikan simbol interaksi manusia dengan komputer seperti halnya pada penggunaan berbagai pose tangan pada bahasa isyarat. Berbagai pose tangan dapat digunakan untuk menggantikan fungsi mouse, untuk mengendalikan robot, dan sebagainya. Penelitian ini difokuskan pada pembangunan sistem pengenalan pose tangan menggunakan HuMoment. Proses pengenalan pose tangan dimulai dengan melakukan segmentasi citra masukan untuk menghasilkan citra ROI (Region of Interest yaitu area telapak tangan. Selanjutnya dilakukan proses deteksi tepi. Kemudian dilakukan ekstraksi nilai HuMoment. Nilai HuMoment dikuantisasikan ke dalam bukukode yang dihasilkan dari proses pelatihan menggunakan K-Means. Proses kuantisasi dilakukan dengan menghitung nilai Euclidean Distance terkecil antara nilai HuMomment citra masukan dan bukukode. Berdasarkan hasil penelitian, nilai akurasi sistem dalam mengenali pose tangan adalah 88.57%.

Pose measurement method with six parameters for microassembly based on an optical micrometer

Science.gov (United States)

Ye, Xin; Wang, Qiang; Zhang, Zhi-jing; Sun, Yuan; Zhang, Xiao-feng

2009-07-01

This paper presents a new pose measurement method of microminiature parts that is capable of transforming one dimension (1D) contour size obtained by optical micrometer to three dimension (3D) data with six parameters for microassembly. Pose measurement is one of the most important processes for microminiature parts' alignment and insertion in microassembly. During the past few years, researchers have developed their microassembly systems focusing on visual identification to obtain two or three dimension data with no more than three parameters. Scanning electronic microscope (SEM), optical microscope, and stereomicroscope are applied in their systems. However, as structures of microminiature parts become increasingly complex, six parameters to represent their position and orientation are specifically needed. Firstly, The pose measurement model is established based on the introduction of measuring objects and measuring principle of optical micrometer. The measuring objects are microminiature parts with complex 3D structure. Two groups of two dimension (2D) data are gathered at two different measurement positions. Then part pose with 6 parameters is calculated, including 3 position parameters of feature point of the part and 3 orientation parameters of the part axis. Secondly, pose measurement process for a small shaft, vertical orientation determination, and position parameters obtaining are presented. 2D data is gathered by scanning the generatrix of the part, and valid data is extracted and saved in arrays. A vertical orientation criterion is proposed to determine whether the part is parallel to the Z-axis of the coordinate. If not, 2D data will be fixed into a linear equation using least square algorithm. Then orientation parameters are calculated. Center of Part End (CPE) is selected as feature point of the part, and its position parameters are extracted form two group of 2D data. Finally, a fast pose measurement device is developed and representative

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...

Optical neural network system for pose determination of spinning satellites

Science.gov (United States)

Lee, Andrew; Casasent, David

1990-01-01

An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

ONKALO POSE experiment. Phase 3: execution and monitoring

International Nuclear Information System (INIS)

Valli, J.; Hakala, M.; Wanne, T.; Kantia, P.; Siren, T.

2014-01-01

In-depth knowledge of the in situ stress state at the Olkiluoto site is critical for stability assessment both prior to and after deposition of spent nuclear fuel in order to understand and avoid potential damage to the rock at the site. Posiva's Olkiluoto Spalling Experiment (POSE) was designed specifically for this purpose with three primary goals: establish the in situ spalling/damage strength of Olkiluoto migmatitic gneiss, establish the state of in situ stress at the -345 m depth level and act as a Prediction-Outcome (P-O) exercise. Phases 1 and 2 of POSE are outlined in WR 2012-60. The objectives of the third phase of the POSE experiment are the same as the original objectives outlined above. This report outlines the execution and results of the third phase of the POSE experiment. The third phase of the experiment involved internally heating the third experimental hole (ONK-EH3) of the POSE niche in order to cause a symmetrical thermal stress increase around the hole due to the thermal expansion of rock. This thermomechanically induced stress increase, coupled with the estimated existing in situ stress state, should cause the maximum principal stress around the hole to exceed the predicted spalling strength of the rock around the hole. ONK-EH3 is located almost completely in pegmatitic granite. Four fractures near the top of the hole were mapped after boring ONK-EH3, and a tensile failure located at the contact between mica-rich gneiss and pegmatitic granite was observed 18 months after boring, prior to the experiment. Based on predictive calculations and the estimated in situ state of stress, the maximum principal stress magnitude should reach ca. 100 MPa when the temperature was just below 100 deg C after 12 weeks of heating. There were problems with the heater control unit at the beginning of the experiment, after which heating proceeded according to plan. The crack damage threshold of pegmatitic granite has been determined to be 85 ±17 MPa at Olkiluoto

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.

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...

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...

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…

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…

Perturbation-Based Regularization for Signal Estimation in Linear Discrete Ill-posed Problems

KAUST Repository

Suliman, Mohamed Abdalla Elhag; Ballal, Tarig; Al-Naffouri, Tareq Y.

2016-01-01

Estimating the values of unknown parameters from corrupted measured data faces a lot of challenges in ill-posed problems. In such problems, many fundamental estimation methods fail to provide a meaningful stabilized solution. In this work, we propose a new regularization approach and a new regularization parameter selection approach for linear least-squares discrete ill-posed problems. The proposed approach is based on enhancing the singular-value structure of the ill-posed model matrix to acquire a better solution. Unlike many other regularization algorithms that seek to minimize the estimated data error, the proposed approach is developed to minimize the mean-squared error of the estimator which is the objective in many typical estimation scenarios. The performance of the proposed approach is demonstrated by applying it to a large set of real-world discrete ill-posed problems. Simulation results demonstrate that the proposed approach outperforms a set of benchmark regularization methods in most cases. In addition, the approach also enjoys the lowest runtime and offers the highest level of robustness amongst all the tested benchmark regularization methods.

Perturbation-Based Regularization for Signal Estimation in Linear Discrete Ill-posed Problems

KAUST Repository

Suliman, Mohamed Abdalla Elhag

2016-11-29

Estimating the values of unknown parameters from corrupted measured data faces a lot of challenges in ill-posed problems. In such problems, many fundamental estimation methods fail to provide a meaningful stabilized solution. In this work, we propose a new regularization approach and a new regularization parameter selection approach for linear least-squares discrete ill-posed problems. The proposed approach is based on enhancing the singular-value structure of the ill-posed model matrix to acquire a better solution. Unlike many other regularization algorithms that seek to minimize the estimated data error, the proposed approach is developed to minimize the mean-squared error of the estimator which is the objective in many typical estimation scenarios. The performance of the proposed approach is demonstrated by applying it to a large set of real-world discrete ill-posed problems. Simulation results demonstrate that the proposed approach outperforms a set of benchmark regularization methods in most cases. In addition, the approach also enjoys the lowest runtime and offers the highest level of robustness amongst all the tested benchmark regularization methods.

Pose tracking for augmented reality applications in outdoor archaeological sites

Science.gov (United States)

Younes, Georges; Asmar, Daniel; Elhajj, Imad; Al-Harithy, Howayda

2017-01-01

In recent years, agencies around the world have invested huge amounts of effort toward digitizing many aspects of the world's cultural heritage. Of particular importance is the digitization of outdoor archaeological sites. In the spirit of valorization of this digital information, many groups have developed virtual or augmented reality (AR) computer applications themed around a particular archaeological object. The problem of pose tracking in outdoor AR applications is addressed. Different positional systems are analyzed, resulting in the selection of a monocular camera-based user tracker. The limitations that challenge this technique from map generation, scale, anchoring, to lighting conditions are analyzed and systematically addressed. Finally, as a case study, our pose tracking system is implemented within an AR experience in the Byblos Roman theater in Lebanon.

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…

Monocular-Based 6-Degree of Freedom Pose Estimation Technology for Robotic Intelligent Grasping Systems

Directory of Open Access Journals (Sweden)

Tao Liu

2017-02-01

Full Text Available Industrial robots are expected to undertake ever more advanced tasks in the modern manufacturing industry, such as intelligent grasping, in which robots should be capable of recognizing the position and orientation of a part before grasping it. In this paper, a monocular-based 6-degree of freedom (DOF pose estimation technology to enable robots to grasp large-size parts at informal poses is proposed. A camera was mounted on the robot end-flange and oriented to measure several featured points on the part before the robot moved to grasp it. In order to estimate the part pose, a nonlinear optimization model based on the camera object space collinearity error in different poses is established, and the initial iteration value is estimated with the differential transformation. Measuring poses of the camera are optimized based on uncertainty analysis. Also, the principle of the robotic intelligent grasping system was developed, with which the robot could adjust its pose to grasp the part. In experimental tests, the part poses estimated with the method described in this paper were compared with those produced by a laser tracker, and results show the RMS angle and position error are about 0.0228° and 0.4603 mm. Robotic intelligent grasping tests were also successfully performed in the experiments.

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...

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.

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.

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…

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.

RuleML-Based Learning Object Interoperability on the Semantic Web

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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…

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)

Tooth display and lip position during spontaneous and posed smiling in adults.

NARCIS (Netherlands)

Geld, P.A.A.M. van der; Oosterveld, P.; Berge, S.J.; Kuijpers-Jagtman, A.M.

2008-01-01

OBJECTIVE: To analyze differences in tooth display, lip-line height, and smile width between the posed smiling record, traditionally produced for orthodontic diagnosis, and the spontaneous (Duchenne) smile of joy. MATERIAL AND METHODS: The faces of 122 male participants were each filmed during

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

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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

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.

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.

Communication in Health Professions: A European consensus on inter- and multi-professional learning objectives in German.

Science.gov (United States)

Bachmann, Cadja; Kiessling, Claudia; Härtl, Anja; Haak, Rainer

2016-01-01

Communication is object of increasing attention in the health professions. Teaching communication competencies should already begin in undergraduate education or pre-registration training. The aim of this project was to translate the Health Professions Core Communication Curriculum (HPCCC), an English catalogue of learning objectives, into German to make its content widely accessible in the German-speaking countries. This catalogue lists 61 educational objectives and was agreed on by 121 international communication experts. A European reference framework for inter- and multi-professional curriculum development for communication in the health professions in German-speaking countries should be provided. The German version of the HPCCC was drafted by six academics and went through multiple revisions until consensus was reached. The learning objectives were paired with appropriate teaching and assessment tools drawn from the database of the teaching Committee of the European Association for Communication Health Care (tEACH). The HPCCC learning objectives are now available in German and can be applied for curriculum planning and development in the different German-speaking health professions, the educational objectives can also be used for inter-professional purposes. Examples for teaching methods and assessment tools are given for using and implementing the objectives. The German version of the HPCCC with learning objectives for communication in health professions can contribute significantly to inter- and multi-professional curriculum development in the health care professions in the German-speaking countries. Examples for teaching methods and assessment tools from the materials compiled by tEACH supplement the curricular content and provide suggestions for practical implementation of the learning objectives in teaching and assessment. The relevance of the German HPCCC to the processes of curriculum development for the various health professions and inter

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,…

Problem posing reflections and applications

CERN Document Server

Brown, Stephen I

2014-01-01

As a result of the editors' collaborative teaching at Harvard in the late 1960s, they produced a ground-breaking work -- The Art Of Problem Posing -- which related problem posing strategies to the already popular activity of problem solving. It took the concept of problem posing and created strategies for engaging in that activity as a central theme in mathematics education. Based in part upon that work and also upon a number of articles by its authors, other members of the mathematics education community began to apply and expand upon their ideas. This collection of thirty readings is a tes

Self-Organizing Neural Integration of Pose-Motion Features for Human Action Recognition

Directory of Open Access Journals (Sweden)

German Ignacio Parisi

2015-06-01

Full Text Available The visual recognition of complex, articulated human movements is fundamental for a wide range of artificial systems oriented towards human-robot communication, action classification, and action-driven perception. These challenging tasks may generally involve the processing of a huge amount of visual information and learning-based mechanisms for generalizing a set of training actions and classifying new samples. To operate in natural environments, a crucial property is the efficient and robust recognition of actions, also under noisy conditions caused by, for instance, systematic sensor errors and temporarily occluded persons. Studies of the mammalian visual system and its outperforming ability to process biological motion information suggest separate neural pathways for the distinct processing of pose and motion features at multiple levels and the subsequent integration of these visual cues for action perception. We present a neurobiologically-motivated approach to achieve noise-tolerant action recognition in real time. Our model consists of self-organizing Growing When Required (GWR networks that obtain progressively generalized representations of sensory inputs and learn inherent spatiotemporal dependencies. During the training, the GWR networks dynamically change their topological structure to better match the input space. We first extract pose and motion features from video sequences and then cluster actions in terms of prototypical pose-motion trajectories. Multi-cue trajectories from matching action frames are subsequently combined to provide action dynamics in the joint feature space. Reported experiments show that our approach outperforms previous results on a dataset of full-body actions captured with a depth sensor, and ranks among the best 21 results for a public benchmark of domestic daily actions.

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

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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…

6-DOF Pose Estimation of a Robotic Navigation Aid by Tracking Visual and Geometric Features.

Science.gov (United States)

Ye, Cang; Hong, Soonhac; Tamjidi, Amirhossein

2015-10-01

This paper presents a 6-DOF Pose Estimation (PE) method for a Robotic Navigation Aid (RNA) for the visually impaired. The RNA uses a single 3D camera for PE and object detection. The proposed method processes the camera's intensity and range data to estimates the camera's egomotion that is then used by an Extended Kalman Filter (EKF) as the motion model to track a set of visual features for PE. A RANSAC process is employed in the EKF to identify inliers from the visual feature correspondences between two image frames. Only the inliers are used to update the EKF's state. The EKF integrates the egomotion into the camera's pose in the world coordinate system. To retain the EKF's consistency, the distance between the camera and the floor plane (extracted from the range data) is used by the EKF as the observation of the camera's z coordinate. Experimental results demonstrate that the proposed method results in accurate pose estimates for positioning the RNA in indoor environments. Based on the PE method, a wayfinding system is developed for localization of the RNA in a home environment. The system uses the estimated pose and the floorplan to locate the RNA user in the home environment and announces the points of interest and navigational commands to the user through a speech interface. This work was motivated by the limitations of the existing navigation technology for the visually impaired. Most of the existing methods use a point/line measurement sensor for indoor object detection. Therefore, they lack capability in detecting 3D objects and positioning a blind traveler. Stereovision has been used in recent research. However, it cannot provide reliable depth data for object detection. Also, it tends to produce a lower localization accuracy because its depth measurement error quadratically increases with the true distance. This paper suggests a new approach for navigating a blind traveler. The method uses a single 3D time-of-flight camera for both 6-DOF PE and 3D object

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

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

Improving head and body pose estimation through semi-supervised manifold alignment

KAUST Repository

Heili, Alexandre

2014-10-27

In this paper, we explore the use of a semi-supervised manifold alignment method for domain adaptation in the context of human body and head pose estimation in videos. We build upon an existing state-of-the-art system that leverages on external labelled datasets for the body and head features, and on the unlabelled test data with weak velocity labels to do a coupled estimation of the body and head pose. While this previous approach showed promising results, the learning of the underlying manifold structure of the features in the train and target data and the need to align them were not explored despite the fact that the pose features between two datasets may vary according to the scene, e.g. due to different camera point of view or perspective. In this paper, we propose to use a semi-supervised manifold alignment method to bring the train and target samples closer within the resulting embedded space. To this end, we consider an adaptation set from the target data and rely on (weak) labels, given for example by the velocity direction whenever they are reliable. These labels, along with the training labels are used to bias the manifold distance within each manifold and to establish correspondences for alignment.

Evaluating the Use of Learning Objects for Improving Calculus Readiness

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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…

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

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.

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.

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)…

#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…

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

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.

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…

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

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....

Mendalami Dasar-Dasar dalam Pengambilan Pose pada Pemotretan Model

Directory of Open Access Journals (Sweden)

Agnes Paulina Gunawan

2013-04-01

Full Text Available There are many activities and numerous objects in this universe, which make them interesting for photographers to explore as their masterpiece. One of the things that has been enjoyed and is always developing over time is the use of human as an object, whether as a candid photography or as a posing model in accordance to photographer's concept and theme. Using human being as an object is always popular among beginners and professional photographers. Even nowadays people often hold photo shoot as a media in many social network sites. And so if they understand the simple theories in basic knowledge of using human object, the results will be maximized, and of course, much more interesting. The more a photographer does his job, the better his experience is, and his work will develop. Thus, it makes him more alert to the situation and character of a model, which will then become more observant in predicting their outcome in photography.   

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.

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.

Associative vocabulary learning: development and testing of two paradigms for the (re-) acquisition of action- and object-related words.

Science.gov (United States)

Freundlieb, Nils; Ridder, Volker; Dobel, Christian; Enriquez-Geppert, Stefanie; Baumgaertner, Annette; Zwitserlood, Pienie; Gerloff, Christian; Hummel, Friedhelm C; Liuzzi, Gianpiero

2012-01-01

Despite a growing number of studies, the neurophysiology of adult vocabulary acquisition is still poorly understood. One reason is that paradigms that can easily be combined with neuroscientfic methods are rare. Here, we tested the efficiency of two paradigms for vocabulary (re-) acquisition, and compared the learning of novel words for actions and objects. Cortical networks involved in adult native-language word processing are widespread, with differences postulated between words for objects and actions. Words and what they stand for are supposed to be grounded in perceptual and sensorimotor brain circuits depending on their meaning. If there are specific brain representations for different word categories, we hypothesized behavioural differences in the learning of action-related and object-related words. Paradigm A, with the learning of novel words for body-related actions spread out over a number of days, revealed fast learning of these new action words, and stable retention up to 4 weeks after training. The single-session Paradigm B employed objects and actions. Performance during acquisition did not differ between action-related and object-related words (time*word category: p = 0.01), but the translation rate was clearly better for object-related (79%) than for action-related words (53%, p = 0.002). Both paradigms yielded robust associative learning of novel action-related words, as previously demonstrated for object-related words. Translation success differed for action- and object-related words, which may indicate different neural mechanisms. The paradigms tested here are well suited to investigate such differences with neuroscientific means. Given the stable retention and minimal requirements for conscious effort, these learning paradigms are promising for vocabulary re-learning in brain-lesioned people. In combination with neuroimaging, neuro-stimulation or pharmacological intervention, they may well advance the understanding of language learning

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

MODEL PEMBELAJARAN PROBLEM POSING DENGAN PENDEKATAN SAINTIFIK UNTUK MENINGKATKAN KEMAMPUAN PEMECAHAN MASALAH

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Adi Purnomo

2015-08-01

lesson plan is effective: (1 completeness clasical is over 75%, class average is over KKM; (2 the ability of students’ problem solving that the learning use problem posing with secientific approach better than students in conventional learning; (3 scientific skill hardwork and character independencet positively to the ability of problem solving; (4 there is improvement ability of students’ problem solving and improvement in problem solving skills based on those solo taxonomy.

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

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…

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…

Curriculum development for a national cardiotocography education program: a Delphi survey to obtain consensus on learning objectives.

Science.gov (United States)

Thellesen, Line; Hedegaard, Morten; Bergholt, Thomas; Colov, Nina P; Hoegh, Stinne; Sorensen, Jette L

2015-08-01

To define learning objectives for a national cardiotocography (CTG) education program based on expert consensus. A three-round Delphi survey. One midwife and one obstetrician from each maternity unit in Denmark were appointed based on CTG teaching experience and clinical obstetric experience. Following national and international guidelines, the research group determined six topics as important when using CTG: fetal physiology, equipment, indication, interpretation, clinical management, and communication/responsibility. In the first Delphi round, participants listed one to five learning objectives within the predefined topics. Responses were analyzed by a directed approach to content analysis. Phrasing was modified in accordance with Bloom's taxonomy. In the second and third Delphi rounds, participants rated each objective on a five-point relevance scale. Consensus was predefined as objectives with a mean rating value of ≥ 3. A prioritized list of CTG learning objectives. A total of 42 midwives and obstetricians from 21 maternity units were invited to participate, of whom 26 completed all three Delphi rounds, representing 18 maternity units. The final prioritized list included 40 objectives. The highest ranked objectives emphasized CTG interpretation and clinical management. The lowest ranked objectives emphasized fetal physiology. Mean ratings of relevance ranged from 3.15 to 5.00. National consensus on CTG learning objectives was achieved using the Delphi methodology. This was an initial step in developing a valid CTG education program. A prioritized list of objectives will clarify which topics to emphasize in a CTG education program. © 2015 Nordic Federation of Societies of Obstetrics and Gynecology.

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.

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

Deep Learning for Computer Vision: A Brief Review

Science.gov (United States)

Doulamis, Nikolaos; Doulamis, Anastasios; Protopapadakis, Eftychios

2018-01-01

Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein. PMID:29487619

Deep Learning for Computer Vision: A Brief Review

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Athanasios Voulodimos

2018-01-01

Full Text Available Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein.

Deep Learning for Computer Vision: A Brief Review.

Science.gov (United States)

Voulodimos, Athanasios; Doulamis, Nikolaos; Doulamis, Anastasios; Protopapadakis, Eftychios

2018-01-01

Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein.

Adventure Learning: Theory and Implementation of Hybrid Learning

Science.gov (United States)

Doering, A.

2008-12-01

Adventure Learning (AL), a hybrid distance education approach, provides students and teachers with the opportunity to learn about authentic curricular content areas while interacting with adventurers, students, and content experts at various locations throughout the world within an online learning environment (Doering, 2006). An AL curriculum and online environment provides collaborative community spaces where traditional hierarchical classroom roles are blurred and learning is transformed. AL has most recently become popular in K-12 classrooms nationally and internationally with millions of students participating online. However, in the literature, the term "adventure learning" many times gets confused with phrases such as "virtual fieldtrip" and activities where someone "exploring" is posting photos and text. This type of "adventure learning" is not "Adventure Learning" (AL), but merely a slideshow of their activities. The learning environment may not have any curricular and/or social goals, and if it does, the environment design many times does not support these objectives. AL, on the other hand, is designed so that both teachers and students understand that their online and curriculum activities are in synch and supportive of the curricular goals. In AL environments, there are no disparate activities as the design considers the educational, social, and technological affordances (Kirschner, Strijbos, Kreijns, & Beers, 2004); in other words, the artifacts of the learning environment encourage and support the instructional goals, social interactions, collaborative efforts, and ultimately learning. AL is grounded in two major theoretical approaches to learning - experiential and inquiry-based learning. As Kolb (1984) noted, in experiential learning, a learner creates meaning from direct experiences and reflections. Such is the goal of AL within the classroom. Additionally, AL affords learners a real-time authentic online learning experience concurrently as they

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

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

Compensating Pose Uncertainties through Appropriate Gripper Finger Cutouts

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Wolniakowski Adam

2018-03-01

Full Text Available The gripper finger design is a recurring problem in many robotic grasping platforms used in industry. The task of switching the gripper configuration to accommodate for a new batch of objects typically requires engineering expertise, and is a lengthy and costly iterative trial-and-error process. One of the open challenges is the need for the gripper to compensate for uncertainties inherent to the workcell, e.g. due to errors in calibration, inaccurate pose estimation from the vision system, or object deformation. In this paper, we present an analysis of gripper uncertainty compensating capabilities in a sample industrial object grasping scenario for a finger that was designed using an automated simulation-based geometry optimization method (Wolniakowski et al., 2013, 2015. We test the developed gripper with a set of grasps subjected to structured perturbation in a simulation environment and in the real-world setting. We provide a comparison of the data obtained by using both of these approaches. We argue that the strong correspondence observed in results validates the use of dynamic simulation for the gripper finger design and optimization.

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.

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.

3D pose estimation and motion analysis of the articulated human hand-forearm limb in an industrial production environment

Science.gov (United States)

Hahn, Markus; Barrois, Björn; Krüger, Lars; Wöhler, Christian; Sagerer, Gerhard; Kummert, Franz

2010-09-01

This study introduces an approach to model-based 3D pose estimation and instantaneous motion analysis of the human hand-forearm limb in the application context of safe human-robot interaction. 3D pose estimation is performed using two approaches: The Multiocular Contracting Curve Density (MOCCD) algorithm is a top-down technique based on pixel statistics around a contour model projected into the images from several cameras. The Iterative Closest Point (ICP) algorithm is a bottom-up approach which uses a motion-attributed 3D point cloud to estimate the object pose. Due to their orthogonal properties, a fusion of these algorithms is shown to be favorable. The fusion is performed by a weighted combination of the extracted pose parameters in an iterative manner. The analysis of object motion is based on the pose estimation result and the motion-attributed 3D points belonging to the hand-forearm limb using an extended constraint-line approach which does not rely on any temporal filtering. A further refinement is obtained using the Shape Flow algorithm, a temporal extension of the MOCCD approach, which estimates the temporal pose derivative based on the current and the two preceding images, corresponding to temporal filtering with a short response time of two or at most three frames. Combining the results of the two motion estimation stages provides information about the instantaneous motion properties of the object. Experimental investigations are performed on real-world image sequences displaying several test persons performing different working actions typically occurring in an industrial production scenario. In all example scenes, the background is cluttered, and the test persons wear various kinds of clothes. For evaluation, independently obtained ground truth data are used. [Figure not available: see fulltext.

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.

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...

Credit assignment between body and object probed by an object transportation task.

Science.gov (United States)

Kong, Gaiqing; Zhou, Zhihao; Wang, Qining; Kording, Konrad; Wei, Kunlin

2017-10-17

It has been proposed that learning from movement errors involves a credit assignment problem: did I misestimate properties of the object or those of my body? For example, an overestimate of arm strength and an underestimate of the weight of a coffee cup can both lead to coffee spills. Though previous studies have found signs of simultaneous learning of the object and of the body during object manipulation, there is little behavioral evidence about their quantitative relation. Here we employed a novel weight-transportation task, in which participants lift the first cup filled with liquid while assessing their learning from errors. Specifically, we examined their transfer of learning when switching to a contralateral hand, the second identical cup, or switching both hands and cups. By comparing these transfer behaviors, we found that 25% of the learning was attributed to the object (simply because of the use of the same cup) and 58% of the learning was attributed to the body (simply because of the use of the same hand). The nervous system thus seems to partition the learning of object manipulation between the object and the body.

Libraries in Second Life: New Approaches to Education, Information Sharing, Learning Object Implementation, User Interactions and Collaborations

Directory of Open Access Journals (Sweden)

Susan Smith Nash

2009-10-01

Full Text Available Three-dimensional virtual worlds such as Second Life continue to expand the way they provide information, learning activities, and educational applications. This paper explores the types of learning activities that take place in Second Life and discusses how learning takes place, with a view toward developing effective instructional strategies. As learning objects are being launched in Second Life, new approaches to collaboration, interactivity, and cognition are being developed. Many learning-centered islands appeal to individuals who benefit from interaction with peers and instructors, and who can access learning objects such as information repositories, simulations, and interactive animations. The key advantages that Second Life offers include engaging and meaningful interaction with fellow learners, media-rich learning environments with embedded video, graphics, and interactive quizzes and assessments, an engaging environment for simulations such as virtual labs, and culturally inclusive immersive environments. However, because of the steep learning curve, technical difficulties, and cultural diversity, learners may become frustrated in Second Life. Since Second Life is social learning environment that emphasizes the creation of a self, effective learning requires step-by-step empowerment of that new, constructed self.

Construction and validation of a virtual learning object on intestinal elimination stoma

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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.

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.

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…

Pose Planning for the Feed Support System of FAST

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Rui Yao

2014-01-01

Full Text Available A six-cable driven parallel manipulator and an A-B rotator in the feed support system of the Five-hundred-meter Aperture Spherical radio Telescope (FAST are adopted for realizing the position and pose of nine feeds. The six-cable driven parallel manipulator is a flexible mechanism, which may not be stably controlled due to a small cable tension. The A-B rotator is a rigid mechanism, and its stability and accuracy can be improved by small pose angle. Based on the different characteristics, a pose planning function is presented. The optimization target of the pose planning function is to get the smallest pose angle of the A-B rotator, and the constraint condition can reflect the controllability of the six-cable driven parallel manipulator. Then, the pose planning realization process of the feed support system is proposed. Based on the pose planning method, optimized pose angles of the feed support system for the nine feeds are obtained, which suggests that the pose angle of the six-cable driven parallel manipulator changes from 0° to 14° and the pose angle of the A-B rotator changes from 0° to 26.4°.

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

2D Methods for pose invariant face recognition

CSIR Research Space (South Africa)

Mokoena, Ntabiseng

2016-12-01

Full Text Available The ability to recognise face images under random pose is a task that is done effortlessly by human beings. However, for a computer system, recognising face images under varying poses still remains an open research area. Face recognition across pose...

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

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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.

Design and Test of Object Aligning Grippers for Industrial Applications

DEFF Research Database (Denmark)

Ellekilde, Lars-Peter; Petersen, Henrik Gordon

2006-01-01

In this paper we will present a new concept for gripping objects in industrial applications. We assume that a priori, the object pose is only known with a relative low accuracy. Despite this, our method can lead to high accuracy gripping suitable for e.g. industrial assembly. Our concept...... is to augment a simple parallel gripper by mounting a set of object speci?c jaws. Given the right shapes these jaws enable the gripper to automatically align the object, and thereby compensate for errors in the original object pose estimation. We will introduce a couple of automatic and semi-automatic design...

The nucleolus is well-posed

Science.gov (United States)

Fragnelli, Vito; Patrone, Fioravante; Torre, Anna

2006-02-01

The lexicographic order is not representable by a real-valued function, contrary to many other orders or preorders. So, standard tools and results for well-posed minimum problems cannot be used. We prove that under suitable hypotheses it is however possible to guarantee the well-posedness of a lexicographic minimum over a compact or convex set. This result allows us to prove that some game theoretical solution concepts, based on lexicographic order are well-posed: in particular, this is true for the nucleolus.

Sub-OBB based object recognition and localization algorithm using range images

International Nuclear Information System (INIS)

Hoang, Dinh-Cuong; Chen, Liang-Chia; Nguyen, Thanh-Hung

2017-01-01

This paper presents a novel approach to recognize and estimate pose of the 3D objects in cluttered range images. The key technical breakthrough of the developed approach can enable robust object recognition and localization under undesirable condition such as environmental illumination variation as well as optical occlusion to viewing the object partially. First, the acquired point clouds are segmented into individual object point clouds based on the developed 3D object segmentation for randomly stacked objects. Second, an efficient shape-matching algorithm called Sub-OBB based object recognition by using the proposed oriented bounding box (OBB) regional area-based descriptor is performed to reliably recognize the object. Then, the 3D position and orientation of the object can be roughly estimated by aligning the OBB of segmented object point cloud with OBB of matched point cloud in a database generated from CAD model and 3D virtual camera. To detect accurate pose of the object, the iterative closest point (ICP) algorithm is used to match the object model with the segmented point clouds. From the feasibility test of several scenarios, the developed approach is verified to be feasible for object pose recognition and localization. (paper)

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…

Constraints on Perceptual Learning: Objects and Dimensions.

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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)

Face pose tracking using the four-point algorithm

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Fung, Ho Yin; Wong, Kin Hong; Yu, Ying Kin; Tsui, Kwan Pang; Kam, Ho Chuen

2017-06-01

In this paper, we have developed an algorithm to track the pose of a human face robustly and efficiently. Face pose estimation is very useful in many applications such as building virtual reality systems and creating an alternative input method for the disabled. Firstly, we have modified a face detection toolbox called DLib for the detection of a face in front of a camera. The detected face features are passed to a pose estimation method, known as the four-point algorithm, for pose computation. The theory applied and the technical problems encountered during system development are discussed in the paper. It is demonstrated that the system is able to track the pose of a face in real time using a consumer grade laptop computer.

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

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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.

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.

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

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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…

Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

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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.

Gaussian particle filter based pose and motion estimation

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

Determination of relative three-dimensional (3D) position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry.A solution to pose and motion estimation problem that uses two-dimensional (2D) intensity images from a single camera is desirable for real-time applications. The difficulty in performing this measurement is that the process of projecting 3D object features to 2D images is a nonlinear transformation. In this paper, the 3D transformation is modeled as a nonlinear stochastic system with the state estimation providing six degrees-of-freedom motion and position values, using line features in image plane as measuring inputs and dual quaternion to represent both rotation and translation in a unified notation. A filtering method called the Gaussian particle filter (GPF) based on the particle filtering concept is presented for 3D pose and motion estimation of a moving target from monocular image sequences. The method has been implemented with simulated data, and simulation results are provided along with comparisons to the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) to show the relative advantages of the GPF. Simulation results showed that GPF is a superior alternative to EKF and UKF.

Exploring the impact of learning objects in middle school mathematics and science classrooms: A formative analysis

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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

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

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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.

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

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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…

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

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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…

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

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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.

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

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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.

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

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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

To Strike a Pose: No Stereotype Backlash for Power Posing Women

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Miriam Rennung

2016-09-01

Full Text Available Power posing, the adoption of open and powerful postures, has effects that parallel those of actual social power. This study explored the social evaluation of adopting powerful versus powerless body postures in men and women regarding perceived warmth, competence, and the likelihood of eliciting admiration, envy, pity, and contempt. Previous findings suggest that the display of power by women may have side effects due to gender stereotyping, namely reduced warmth ratings and negative emotional reactions. An experiment (N = 2,473 asked participants to rate pictures of men and women who adopted high-power or low-power body postures. High-power posers were rated higher on competence, admiration, envy, and contempt compared to low-power posers, whereas the opposite was true for pity. There was no impact of power posing on perceived warmth. Contrary to expectations, the poser’s gender did not moderate any of the effects. These findings suggest that nonverbal displays of power do influence fundamental dimensions of social perception and their accompanying emotional reactions but result in comparably positive and negative evaluations for both genders.

A biologically inspired neural network model to transformation invariant object recognition

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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

The ambiguous and bewitching power of knowledge, skills and attitudes leads to confusing statements of learning objectives.

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Guilbert, J-J

2002-01-01

The words "knowledge", "skills" and "attitudes" are given different meanings by health personnel when discussing educational issues. Ambiguity is known as a handicap to efficient communication. In the design of a curriculum the quality of the definition of learning objectives plays a fundamental role. If learning objectives lack clarity, learners and teachers will face operational difficulties. As Robert Mager said, "If you are not certain of where you are going you may very well end up somewhere else and not even know it". Knowledge is not only memory of facts but what you do with it. The complexity of human behaviour should not be underestimated. This is why educational objectives need active non-ambiguous verbs in order to achieve better communication between teachers and learners and to assess that complexity. This is why I suggest using the expression intellectual skill (or competence) as meaning "a rational decision or act". Sensomotor skill (or competence) would replace "skills" as presently used and cover only "acts which require a neuromuscular coordination". Interpersonal communication skill (or competence) would replace "attitude(s)" and be limited to "verbal and non-verbal relation between persons". As the level of validity of assessment of learners' competencies is linked to the clarity of learning objectives, it is hoped that the above suggestions will raise the overall level of validity of the evaluation system. This is why it is important that everybody understands, in the same manner, the meaning of a learning objective. It will help learners to focus their learning efforts on the right target. It will help teachers to ensure the relevance to health needs of their teaching and the validity of assessment instruments. In both cases it will be beneficial to the health of the population.

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

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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…

Science Integrating Learning Objectives: A Cooperative Learning Group Process

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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…

University Students' Problem Posing Abilities and Attitudes towards Mathematics.

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Grundmeier, Todd A.

2002-01-01

Explores the problem posing abilities and attitudes towards mathematics of students in a university pre-calculus class and a university mathematical proof class. Reports a significant difference in numeric posing versus non-numeric posing ability in both classes. (Author/MM)

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

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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…

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

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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…

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

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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.

Remote-controlled flexible pose measurement system and method for a moving target in wind tunnel

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Wei LIU

2018-01-01

Full Text Available The measurement of position and attitude parameters for the isolated target from a high-speed aircraft is a great challenge in the field of wind tunnel simulation technology. This paper proposes a remote-controlled flexible pose measurement system in wind tunnel conditions for the separation of a target from an aircraft. The position and attitude parameters of a moving object are obtained by utilizing a single camera with a focal length and camera orientation that can be changed based on different measurement conditions. Using this proposed system and method, both the flexibility and efficiency of the pose measurement system can be enhanced in wind tunnel conditions to meet the measurement requirements of different objects and experiments, which is also useful for the development of an intelligent position and attitude measurement system. The position and the focal length of the camera also can be controlled remotely during measurements to enlarge both the vertical and horizontal measurement range of this system. Experiments are conducted in the laboratory to measure the position and attitude of moving objects with high flexibility and efficiency, and the measurement precision of the measurement system is also verified through experiments.

The effects of short-term and long-term learning on the responses of lateral intraparietal neurons to visually presented objects.

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Sigurdardottir, Heida M; Sheinberg, David L

2015-07-01

The lateral intraparietal area (LIP) is thought to play an important role in the guidance of where to look and pay attention. LIP can also respond selectively to differently shaped objects. We sought to understand to what extent short-term and long-term experience with visual orienting determines the responses of LIP to objects of different shapes. We taught monkeys to arbitrarily associate centrally presented objects of various shapes with orienting either toward or away from a preferred spatial location of a neuron. The training could last for less than a single day or for several months. We found that neural responses to objects are affected by such experience, but that the length of the learning period determines how this neural plasticity manifests. Short-term learning affects neural responses to objects, but these effects are only seen relatively late after visual onset; at this time, the responses to newly learned objects resemble those of familiar objects that share their meaning or arbitrary association. Long-term learning affects the earliest bottom-up responses to visual objects. These responses tend to be greater for objects that have been associated with looking toward, rather than away from, LIP neurons' preferred spatial locations. Responses to objects can nonetheless be distinct, although they have been similarly acted on in the past and will lead to the same orienting behavior in the future. Our results therefore indicate that a complete experience-driven override of LIP object responses may be difficult or impossible. We relate these results to behavioral work on visual attention.

Learning from Failed Decisions

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Nutt, Paul C.

2010-01-01

The consequences and dilemmas posed by learning issues for decision making are discussed. Learning requires both awareness of barriers and a coping strategy. The motives to hold back information essential for learning stem from perverse incentives, obscure outcomes, and the hindsight bias. There is little awareness of perverse incentives that…

Manifolds for pose tracking from monocular video

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Basu, Saurav; Poulin, Joshua; Acton, Scott T.

2015-03-01

We formulate a simple human-pose tracking theory from monocular video based on the fundamental relationship between changes in pose and image motion vectors. We investigate the natural embedding of the low-dimensional body pose space into a high-dimensional space of body configurations that behaves locally in a linear manner. The embedded manifold facilitates the decomposition of the image motion vectors into basis motion vector fields of the tangent space to the manifold. This approach benefits from the style invariance of image motion flow vectors, and experiments to validate the fundamental theory show reasonable accuracy (within 4.9 deg of the ground truth).

Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2

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da Silva Figueiredo Celestino Gomes, Priscila; Da Silva, Franck; Bret, Guillaume; Rognan, Didier

2018-01-01

A novel docking challenge has been set by the Drug Design Data Resource (D3R) in order to predict the pose and affinity ranking of a set of Farnesoid X receptor (FXR) agonists, prior to the public release of their bound X-ray structures and potencies. In a first phase, 36 agonists were docked to 26 Protein Data Bank (PDB) structures of the FXR receptor, and next rescored using the in-house developed GRIM method. GRIM aligns protein-ligand interaction patterns of docked poses to those of available PDB templates for the target protein, and rescore poses by a graph matching method. In agreement with results obtained during the previous 2015 docking challenge, we clearly show that GRIM rescoring improves the overall quality of top-ranked poses by prioritizing interaction patterns already visited in the PDB. Importantly, this challenge enables us to refine the applicability domain of the method by better defining the conditions of its success. We notably show that rescoring apolar ligands in hydrophobic pockets leads to frequent GRIM failures. In the second phase, 102 FXR agonists were ranked by decreasing affinity according to the Gibbs free energy of the corresponding GRIM-selected poses, computed by the HYDE scoring function. Interestingly, this fast and simple rescoring scheme provided the third most accurate ranking method among 57 contributions. Although the obtained ranking is still unsuitable for hit to lead optimization, the GRIM-HYDE scoring scheme is accurate and fast enough to post-process virtual screening data.

Learning Grasp Strategies Composed of Contact Relative Motions

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Platt, Robert, Jr.

2007-01-01

Of central importance to grasp synthesis algorithms are the assumptions made about the object to be grasped and the sensory information that is available. Many approaches avoid the issue of sensing entirely by assuming that complete information is available. In contrast, this paper proposes an approach to grasp synthesis expressed in terms of units of control that simultaneously change the contact configuration and sense information about the object and the relative manipulator-object pose. These units of control, known as contact relative motions (CRMs), allow the grasp synthesis problem to be recast as an optimal control problem where the goal is to find a strategy for executing CRMs that leads to a grasp in the shortest number of steps. An experiment is described that uses Robonaut, the NASA-JSC space humanoid, to show that CRMs are a viable means of synthesizing grasps. However, because of the limited amount of information that a single CRM can sense, the optimal control problem may be partially observable. This paper proposes expressing the problem as a k-order Markov Decision Process (MDP) and solving it using Reinforcement Learning. This approach is tested in a simulation of a two-contact manipulator that learns to grasp an object. Grasp strategies learned in simulation are tested on the physical Robonaut platform and found to lead to grasp configurations consistently.

The lighter side of advertising: investigating posing and lighting biases.

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Thomas, Nicole A; Burkitt, Jennifer A; Patrick, Regan E; Elias, Lorin J

2008-11-01

People tend to display the left cheek when posing for a portrait; however, this effect does not appear to generalise to advertising. The amount of body visible in the image and the sex of the poser might also contribute to the posing bias. Portraits also exhibit lateral lighting biases, with most images being lit from the left. This effect might also be present in advertisements. A total of 2801 full-page advertisements were sampled and coded for posing direction, lighting direction, sex of model, and amount of body showing. Images of females showed an overall leftward posing bias, but the biases in males depended on the amount of body visible. Males demonstrated rightward posing biases for head-only images. Overall, images tended to be lit from the top left corner. The two factors of posing and lighting biases appear to influence one another. Leftward-lit images had more leftward poses than rightward, while the opposite occurred for rightward-lit images. Collectively, these results demonstrate that the posing biases in advertisements are dependent on the amount of body showing in the image, and that biases in lighting direction interact with these posing biases.

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.

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...

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…

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

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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…

Coupled bias-variance tradeoff for cross-pose face recognition.

Science.gov (United States)

Li, Annan; Shan, Shiguang; Gao, Wen

2012-01-01

Subspace-based face representation can be looked as a regression problem. From this viewpoint, we first revisited the problem of recognizing faces across pose differences, which is a bottleneck in face recognition. Then, we propose a new approach for cross-pose face recognition using a regressor with a coupled bias-variance tradeoff. We found that striking a coupled balance between bias and variance in regression for different poses could improve the regressor-based cross-pose face representation, i.e., the regressor can be more stable against a pose difference. With the basic idea, ridge regression and lasso regression are explored. Experimental results on CMU PIE, the FERET, and the Multi-PIE face databases show that the proposed bias-variance tradeoff can achieve considerable reinforcement in recognition performance.

Objects of Desire.

Science.gov (United States)

Zielinski, Dave

2000-01-01

Describes learning objects, also known as granules, chunks, or information nuggets, and likens them to help screens. Discusses concerns about how they can go wrong: (1) faulty pretest questions; (2) missing links in the learning object chain; (3) poor frames of reference; and (4) lack of customization. (JOW)

Formulas in inverse and ill-posed problems

CERN Document Server

Anikonov, Yu E

1997-01-01

The Inverse and Ill-Posed Problems Series is a series of monographs publishing postgraduate level information on inverse and ill-posed problems for an international readership of professional scientists and researchers. The series aims to publish works which involve both theory and applications in, e.g., physics, medicine, geophysics, acoustics, electrodynamics, tomography, and ecology.

The STS-93 crew pose in front of Columbia

Science.gov (United States)

1999-01-01

The STS-93 crew pose in front of the Space Shuttle orbiter Columbia following their landing on runway 33 at the Shuttle Landing Facility. Main gear touchdown occurred at 11:20:35 p.m. EDT on July 27. From left to right, they are Mission Specialists Catherine G. Coleman (Ph.D.) and Stephen A. Hawley (Ph.D.), Pilot Jeffrey S. Ashby, Commander Eileen Collins, and Mission Specialist Michel Tognini of France, with the Centre National d'Etudes Spatiales (CNES). The mission's primary objective was to deploy the Chandra X-ray Observatory, which will allow scientists from around the world to study some of the most distant, powerful and dynamic objects in the universe. This was the 95th flight in the Space Shuttle program and the 26th for Columbia. The landing was the 19th consecutive Shuttle landing in Florida and the 12th night landing in Shuttle program history. On this mission, Collins became the first woman to serve as a Shuttle commander.

STS-93 Commander Collins poses in front of Columbia

Science.gov (United States)

1999-01-01

STS-93 Commander Eileen Collins poses in front of the Space Shuttle orbiter Columbia following her textbook landing on runway 33 at the Shuttle Landing Facility. Main gear touchdown occurred at 11:20:35 p.m. EDT on July 27. On this mission, Collins became the first woman to serve as a Shuttle commander. Also on board were her fellow STS-93 crew members: Pilot Jeffrey S. Ashby and Mission Specialists Stephen A. Hawley (Ph.D.), Catherine G. Coleman (Ph.D.) and Michel Tognini of France, with the Centre National d'Etudes Spatiales (CNES). The mission's primary objective was to deploy the Chandra X-ray Observatory, which will allow scientists from around the world to study some of the most distant, powerful and dynamic objects in the universe. This was the 95th flight in the Space Shuttle program and the 26th for Columbia. The landing was the 19th consecutive Shuttle landing in Florida and the 12th night landing in Shuttle program history.

Pre-Service and In-Service Teachers' Experiences of Learning to Program in an Object-Oriented Language

Science.gov (United States)

Govender, I.; Grayson, D. J.

2008-01-01

This paper presents the results of an investigation into the various ways in which pre-service and in-service teachers experience learning to program in an object-oriented language. Both groups of teachers were enrolled in university courses. In most cases, the pre-service teachers were learning to program for the first time, while the in-service…

Pedagogical entrepreneurship in learning tasks

Directory of Open Access Journals (Sweden)

Marit Engum Hansen

2016-11-01

Full Text Available Background: The action plan "Entrepreneurship in Education – from primary to higher education "(2009-2014, proposed to establish a site for digital learning materials within entrepreneurship in basic education. PedEnt (Pedagogical Entrepreneurship was launched in autumn of 2014, and both the authors have contributed to the professional development of the site. Two of the learning assignments published on PedEnt constitute the research objects of this study. Methods: Based on pedagogical entrepreneurship we present a case study of learning work carried out by students at lower and upper secondary level. Using an analysis of assignment texts and as well as with video recordings we have identified the characteristics of entrepreneurial learning methods as they were expressed through each case. Results: The analysis showed that learning assignments can be characterized as entrepreneurial because they promoted the actor role and creativity of the students. We found that the relationship between the relevance of the assignments and the context in which they are given pose an important prerequisite for the students in order to experience the learning work as meaningful. Conclusions: Entrepreneurial learning methods challenge the traditional view that theory tends to take primacy over practice. To orient learning assignments within relevant contexts gives students opportunities to experience by themselves the need for increased knowledge.

Fast human pose estimation using 3D Zernike descriptors

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Berjón, Daniel; Morán, Francisco

2012-03-01

Markerless video-based human pose estimation algorithms face a high-dimensional problem that is frequently broken down into several lower-dimensional ones by estimating the pose of each limb separately. However, in order to do so they need to reliably locate the torso, for which they typically rely on time coherence and tracking algorithms. Their losing track usually results in catastrophic failure of the process, requiring human intervention and thus precluding their usage in real-time applications. We propose a very fast rough pose estimation scheme based on global shape descriptors built on 3D Zernike moments. Using an articulated model that we configure in many poses, a large database of descriptor/pose pairs can be computed off-line. Thus, the only steps that must be done on-line are the extraction of the descriptors for each input volume and a search against the database to get the most likely poses. While the result of such process is not a fine pose estimation, it can be useful to help more sophisticated algorithms to regain track or make more educated guesses when creating new particles in particle-filter-based tracking schemes. We have achieved a performance of about ten fps on a single computer using a database of about one million entries.

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

OBJECTIVE STRUCTURED PRACTICAL EXAMINATION AS A LEARNING AND EVALUATION TOOL FOR BIOCHEMISTRY- FIRST EXPERIENCE

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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.

Thoughts on Improvable Objects, Contradiction and Object/Tool Reciprocity in a Study of Zoo Educator Professional Development

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Ash, Doris B.; Kelly, Lisa-Anne DeGregoria

2013-01-01

In this forum we discuss three aspects designed to clarify and extend Kelly and Kassing's paper. These are the roles of improvable objects, contradiction and object/tool reciprocity. In each case we cite relevant literature and pose questions to the field. Our goal is to seed ideas for future discussions concerning the role of activity theory…

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.

Successful online learning the five Ps

OpenAIRE

Jim FLOOD

2004-01-01

Successful online learning the five Ps Jim FLOOD E-learning Consultant-UK Key learning points An important aspect of design for online learning is visual ergonomics. Learning theories offer poor predictive power in terms of how learners work and learn. Success at learning is closely related to emotional engagementand learning designers tend to ignore this aspect. Online learning poses a challenging experience for learnersand they need support t...

The Computer Book of the Internal Medicine Resident: competence acquisition and achievement of learning objectives.

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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.

Chapter Five: Language Learning and Discursive Practice

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Young, Richard F.

2008-01-01

This chapter is framed by the three questions related to learning in Practice Theory posed by Johannes Wagner (2008): (1) What is learned?; (2) Who is learning?; and (3) Who is participating in the learning? These questions are addressed in two learning theories: Language Socialization and Situated Learning theory. In Language Socialization, the…

Learning User Preferences for Sets of Objects

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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.

Segmentation, classification, and pose estimation of military vehicles in low resolution laser radar images

Science.gov (United States)

Neulist, Joerg; Armbruster, Walter

2005-05-01

Model-based object recognition in range imagery typically involves matching the image data to the expected model data for each feasible model and pose hypothesis. Since the matching procedure is computationally expensive, the key to efficient object recognition is the reduction of the set of feasible hypotheses. This is particularly important for military vehicles, which may consist of several large moving parts such as the hull, turret, and gun of a tank, and hence require an eight or higher dimensional pose space to be searched. The presented paper outlines techniques for reducing the set of feasible hypotheses based on an estimation of target dimensions and orientation. Furthermore, the presence of a turret and a main gun and their orientations are determined. The vehicle parts dimensions as well as their error estimates restrict the number of model hypotheses whereas the position and orientation estimates and their error bounds reduce the number of pose hypotheses needing to be verified. The techniques are applied to several hundred laser radar images of eight different military vehicles with various part classifications and orientations. On-target resolution in azimuth, elevation and range is about 30 cm. The range images contain up to 20% dropouts due to atmospheric absorption. Additionally some target retro-reflectors produce outliers due to signal crosstalk. The presented algorithms are extremely robust with respect to these and other error sources. The hypothesis space for hull orientation is reduced to about 5 degrees as is the error for turret rotation and gun elevation, provided the main gun is visible.

An improved silhouette for human pose estimation

Science.gov (United States)

Hawes, Anthony H.; Iftekharuddin, Khan M.

2017-08-01

We propose a novel method for analyzing images that exploits the natural lines of a human poses to find areas where self-occlusion could be present. Errors caused by self-occlusion cause several modern human pose estimation methods to mis-identify body parts, which reduces the performance of most action recognition algorithms. Our method is motivated by the observation that, in several cases, occlusion can be reasoned using only boundary lines of limbs. An intelligent edge detection algorithm based on the above principle could be used to augment the silhouette with information useful for pose estimation algorithms and push forward progress on occlusion handling for human action recognition. The algorithm described is applicable to computer vision scenarios involving 2D images and (appropriated flattened) 3D images.

A multi-objective improved teaching-learning based optimization algorithm for unconstrained and constrained optimization problems

Directory of Open Access Journals (Sweden)

R. Venkata Rao

2014-01-01

Full Text Available The present work proposes a multi-objective improved teaching-learning based optimization (MO-ITLBO algorithm for unconstrained and constrained multi-objective function optimization. The MO-ITLBO algorithm is the improved version of basic teaching-learning based optimization (TLBO algorithm adapted for multi-objective problems. The basic TLBO algorithm is improved to enhance its exploration and exploitation capacities by introducing the concept of number of teachers, adaptive teaching factor, tutorial training and self-motivated learning. The MO-ITLBO algorithm uses a grid-based approach to adaptively assess the non-dominated solutions (i.e. Pareto front maintained in an external archive. The performance of the MO-ITLBO algorithm is assessed by implementing it on unconstrained and constrained test problems proposed for the Congress on Evolutionary Computation 2009 (CEC 2009 competition. The performance assessment is done by using the inverted generational distance (IGD measure. The IGD measures obtained by using the MO-ITLBO algorithm are compared with the IGD measures of the other state-of-the-art algorithms available in the literature. Finally, Lexicographic ordering is used to assess the overall performance of competitive algorithms. Results have shown that the proposed MO-ITLBO algorithm has obtained the 1st rank in the optimization of unconstrained test functions and the 3rd rank in the optimization of constrained test functions.

Pose estimation for mobile robots working on turbine blade

Energy Technology Data Exchange (ETDEWEB)

Ma, X.D.; Chen, Q.; Liu, J.J.; Sun, Z.G.; Zhang, W.Z. [Tsinghua Univ., Beijing (China). Key Laboratory for Advanced Materials Processing Technology, Ministry of Education, Dept. of Mechanical Engineering

2009-03-11

This paper discussed a features point detection and matching task technique for mobile robots used in wind turbine blade applications. The vision-based scheme used visual information from the robot's surrounding environment to match successive image frames. An improved pose estimation algorithm based on a scale invariant feature transform (SIFT) was developed to consider the characteristics of local images of turbine blades, pose estimation problems, and conditions. The method included a pre-subsampling technique for reducing computation and bidirectional matching for improving precision. A random sample consensus (RANSAC) method was used to estimate the robot's pose. Pose estimation conditions included a wide pose range; the distance between neighbouring blades; and mechanical, electromagnetic, and optical disturbances. An experimental platform was used to demonstrate the validity of the proposed algorithm. 20 refs., 6 figs.

Temporal subtraction of chest radiographs compensating pose differences

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von Berg, Jens; Dworzak, Jalda; Klinder, Tobias; Manke, Dirk; Kreth, Adrian; Lamecker, Hans; Zachow, Stefan; Lorenz, Cristian

2011-03-01

Temporal subtraction techniques using 2D image registration improve the detectability of interval changes from chest radiographs. Although such methods are well known for some time they are not widely used in radiologic practice. The reason is the occurrence of strong pose differences between two acquisitions with a time interval of months to years in between. Such strong perspective differences occur in a reasonable number of cases. They cannot be compensated by available image registration methods and thus mask interval changes to be undetectable. In this paper a method is proposed to estimate a 3D pose difference by the adaptation of a 3D rib cage model to both projections. The difference between both is then compensated for, thus producing a subtraction image with virtually no change in pose. The method generally assumes that no 3D image data is available from the patient. The accuracy of pose estimation is validated with chest phantom images acquired under controlled geometric conditions. A subtle interval change simulated by a piece of plastic foam attached to the phantom becomes visible in subtraction images generated with this technique even at strong angular pose differences like an anterior-posterior inclination of 13 degrees.

Non-standard and improperly posed problems

CERN Document Server

Straughan, Brian; Ames, William F

1997-01-01

Written by two international experts in the field, this book is the first unified survey of the advances made in the last 15 years on key non-standard and improperly posed problems for partial differential equations.This reference for mathematicians, scientists, and engineers provides an overview of the methodology typically used to study improperly posed problems. It focuses on structural stability--the continuous dependence of solutions on the initial conditions and the modeling equations--and on problems for which data are only prescribed on part of the boundary.The book addresses continuou

Assessing the risk posed by high-turbidity water to water supplies.

Science.gov (United States)

Chang, Chia-Ling; Liao, Chung-Sheng

2012-05-01

The objective of this study is to assess the risk of insufficient water supply posed by high-turbidity water. Several phenomena can pose risks to the sufficiency of a water supply; this study concerns risks to water treatment plants from particular properties of rainfall and raw water turbidity. High-turbidity water can impede water treatment plant operations; rainfall properties can influence the degree of soil erosion. Thus, water turbidity relates to rainfall characteristics. Exceedance probabilities are presented for different rainfall intensities and turbidities of water. When the turbidity of raw water is higher than 5,000 NTU, it can cause operational problems for a water treatment plant. Calculations show that the turbidity of raw water at the Ban-Sin water treatment plant will be higher than 5,000 NTU if the rainfall intensity is larger than 165 mm/day. The exceedance probability of high turbidity (turbidity >5,000 NTU) in the Ban-Sin water treatment plant is larger than 10%. When any water treatment plant cannot work regularly, its ability to supply water to its customers is at risk.

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

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Shin, Shin-Shing

2016-01-01

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

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.

Discriminative kernel feature extraction and learning for object recognition and detection

DEFF Research Database (Denmark)

Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

2015-01-01

Feature extraction and learning is critical for object recognition and detection. By embedding context cue of image attributes into the kernel descriptors, we propose a set of novel kernel descriptors called context kernel descriptors (CKD). The motivation of CKD is to use the spatial consistency...... even in high-dimensional space. In addition, the latent connection between Rényi quadratic entropy and the mapping data in kernel feature space further facilitates us to capture the geometric structure as well as the information about the underlying labels of the CKD using CSQMI. Thus the resulting...... codebook and reduced CKD are discriminative. We report superior performance of our algorithm for object recognition on benchmark datasets like Caltech-101 and CIFAR-10, as well as for detection on a challenging chicken feet dataset....

Facilitating peer based learning through summative assessment - An adaptation of the Objective Structured Clinical Assessment tool for the blended learning environment.

Science.gov (United States)

Wikander, Lolita; Bouchoucha, Stéphane L

2018-01-01

Adapting a course from face to face to blended delivery necessitates that assessments are modified accordingly. In Australia the Objective Structured Clinical Assessment tool, as a derivative from the Objective Structured Clinical Examination, has been used in the face-to-face delivery mode as a formative or summative assessment tool in medicine and nursing since 1990. The Objective Structured Clinical Assessment has been used at Charles Darwin University to assess nursing students' simulated clinical skills prior to the commencement of their clinical placements since 2008. Although the majority of the course is delivered online, students attend a one-week intensive clinical simulation block yearly, prior to attending clinical placements. Initially, the Objective Structured Clinical Assessment was introduced as a lecturer assessed summative assessment, over time it was adapted to better suit the blended learning environment. The modification of the tool from an academic to peer assessed assessment tool, was based on the empirical literature, student feedback and a cross-sectional, qualitative study exploring academics' perceptions of the Objective Structured Clinical Assessment (Bouchoucha et al., 2013a, b). This paper presents an overview of the process leading to the successful adaptation of the Objective Structured Clinical Assessment to suit the requirements of a preregistration nursing course delivered through blended learning. This is significant as many universities are moving their curriculum to fully online or blended delivery, yet little attention has been paid to adapting the assessment of simulated clinical skills. The aim is to identify the benefits and drawbacks of using the peer assessed Objective Structured Clinical Assessment and share recommendations for successful implementation. Copyright © 2017 Elsevier Ltd. All rights reserved.

The scholar role in the National Competence Based Catalogues of Learning Objectives for Undergraduate Medical Education (NKLM) compared to other international frameworks.

Science.gov (United States)

Hautz, Stefanie C; Hautz, Wolf E; Keller, Niklas; Feufel, Markus A; Spies, Claudia

2015-01-01

In Germany, a national competence based catalogue of learning objectives in medicine (NKLM) was developed by the Society for Medical Education and the Council of Medical Faculties. As many of its international counterparts the NKLM describes the qualifications of medical school graduates. The definition of such outcome frameworks indents to make medical education transparent to students, teachers and society. The NKLM aims to amend existing lists of medical topics for assessment with learnable competencies. All outcome frameworks are structured into chapters, domains or physician roles. The definition of the scholar-role poses a number of questions such as: What distinguishes necessary qualifications of a scientifically qualified physician from those of a medical scientist? 13 outcome frameworks were identified through a systematic three-step literature review and their content compared to the scholar role in the NKLM by means of a qualitative text analysis. The three steps consist of (1) search for outcome frameworks, (2) in- and exclusion, and (3) data extraction, categorization, and validation. The results were afterwards matched with the scholar role of the NKLM. Extracted contents of all frameworks may be summarized into the components Common Basics, Clinical Application, Research, Teaching and Education, and Lifelong Learning. Compared to the included frameworks the NKLM emphasises competencies necessary for research and teaching while clinical application is less prominently mentioned. The scholar role of the NKLM differs from other international outcome frameworks. Discussing these results shall increase propagation and understanding of the NKLM and thus contribute to the qualification of future medical graduates in Germany.

The Effects of Discipline on the Application of Learning Object Metadata in UK Higher Education: The Case of the Jorum Repository

Science.gov (United States)

Balatsoukas, Panos; O'Brien, Ann; Morris, Anne

2011-01-01

Introduction: This paper reports on the findings of a study investigating the potential effects of discipline (sciences and engineering versus humanities and social sciences) on the application of the Institute of Electrical and Electronic Engineers learning object metadata elements for the description of learning objects in the Jorum learning…

Method of orthogonally splitting imaging pose measurement

Science.gov (United States)

Zhao, Na; Sun, Changku; Wang, Peng; Yang, Qian; Liu, Xintong

2018-01-01

In order to meet the aviation's and machinery manufacturing's pose measurement need of high precision, fast speed and wide measurement range, and to resolve the contradiction between measurement range and resolution of vision sensor, this paper proposes an orthogonally splitting imaging pose measurement method. This paper designs and realizes an orthogonally splitting imaging vision sensor and establishes a pose measurement system. The vision sensor consists of one imaging lens, a beam splitter prism, cylindrical lenses and dual linear CCD. Dual linear CCD respectively acquire one dimensional image coordinate data of the target point, and two data can restore the two dimensional image coordinates of the target point. According to the characteristics of imaging system, this paper establishes the nonlinear distortion model to correct distortion. Based on cross ratio invariability, polynomial equation is established and solved by the least square fitting method. After completing distortion correction, this paper establishes the measurement mathematical model of vision sensor, and determines intrinsic parameters to calibrate. An array of feature points for calibration is built by placing a planar target in any different positions for a few times. An terative optimization method is presented to solve the parameters of model. The experimental results show that the field angle is 52 °, the focus distance is 27.40 mm, image resolution is 5185×5117 pixels, displacement measurement error is less than 0.1mm, and rotation angle measurement error is less than 0.15°. The method of orthogonally splitting imaging pose measurement can satisfy the pose measurement requirement of high precision, fast speed and wide measurement range.

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…

Characterization of medical students recall of factual knowledge using learning objects and repeated testing in a novel e-learning system.

Science.gov (United States)

Taveira-Gomes, Tiago; Prado-Costa, Rui; Severo, Milton; Ferreira, Maria Amélia

2015-01-24

Spaced-repetition and test-enhanced learning are two methodologies that boost knowledge retention. ALERT STUDENT is a platform that allows creation and distribution of Learning Objects named flashcards, and provides insight into student judgments-of-learning through a metric called 'recall accuracy'. This study aims to understand how the spaced-repetition and test-enhanced learning features provided by the platform affect recall accuracy, and to characterize the effect that students, flashcards and repetitions exert on this measurement. Three spaced laboratory sessions (s0, s1 and s2), were conducted with n=96 medical students. The intervention employed a study task, and a quiz task that consisted in mentally answering open-ended questions about each flashcard and grading recall accuracy. Students were randomized into study-quiz and quiz groups. On s0 both groups performed the quiz task. On s1 and s2, the study-quiz group performed the study task followed by the quiz task, whereas the quiz group only performed the quiz task. We measured differences in recall accuracy between groups/sessions, its variance components, and the G-coefficients for the flashcard component. At s0 there were no differences in recall accuracy between groups. The experiment group achieved a significant increase in recall accuracy that was superior to the quiz group in s1 and s2. In the study-quiz group, increases in recall accuracy were mainly due to the session, followed by flashcard factors and student factors. In the quiz group, increases in recall accuracy were mainly accounted by flashcard factors, followed by student and session factors. The flashcard G-coefficient indicated an agreement on recall accuracy of 91% in the quiz group, and of 47% in the study-quiz group. Recall accuracy is an easily collectible measurement that increases the educational value of Learning Objects and open-ended questions. This metric seems to vary in a way consistent with knowledge retention, but further

The Dynamic Features of Lip Corners in Genuine and Posed Smiles

Directory of Open Access Journals (Sweden)

Hui Guo

2018-02-01

Full Text Available The smile is a frequently expressed facial expression that typically conveys a positive emotional state and friendly intent. However, human beings have also learned how to fake smiles, typically by controlling the mouth to provide a genuine-looking expression. This is often accompanied by inaccuracies that can allow others to determine that the smile is false. Mouth movement is one of the most striking features of the smile, yet our understanding of its dynamic elements is still limited. The present study analyzes the dynamic features of lip corners, and considers how they differ between genuine and posed smiles. Employing computer vision techniques, we investigated elements such as the duration, intensity, speed, symmetry of the lip corners, and certain irregularities in genuine and posed smiles obtained from the UvA-NEMO Smile Database. After utilizing the facial analysis tool OpenFace, we further propose a new approach to segmenting the onset, apex, and offset phases of smiles, as well as a means of measuring irregularities and symmetry in facial expressions. We extracted these features according to 2D and 3D coordinates, and conducted an analysis. The results reveal that genuine smiles have higher values for onset, offset, apex, and total durations, as well as offset displacement, and a variable we termed Irregularity-b (the SD of the apex phase than do posed smiles. Conversely, values tended to be lower for onset and offset Speeds, and Irregularity-a (the rate of peaks, Symmetry-a (the correlation between left and right facial movements, and Symmetry-d (differences in onset frame numbers between the left and right faces. The findings from the present study have been compared to those of previous research, and certain speculations are made.

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