Learning Theory Expertise in the Design of Learning Spaces: Who Needs a Seat at the Table?

Science.gov (United States)

Rook, Michael M.; Choi, Koun; McDonald, Scott P.

2015-01-01

This study highlights the impact of including stakeholders with expertise in learning theory in a learning space design process. We present the decision-making process during the design of the Krause Innovation Studio on the campus of the Pennsylvania State University to draw a distinction between the architect and faculty member's decision-making…

Designing informal learning spaces using student perspectives

Directory of Open Access Journals (Sweden)

Matthew David Riddle

2012-06-01

Full Text Available This article describes the design of informal learning spaces at an Australian university that support students in the generation of knowledge. Recent learning space design projects at La Trobe have been informed by a number of pre-existing projects, including a small research project on student use of technologies, a national project on learning space design, and a significant curriculum renewal process at the university. It demonstrates the ways in which evidence based on student perspectives and principles developed through applied research in teaching and learning can inform real world learning space design projects in a higher education context.

Self and other in digital learning spaces

DEFF Research Database (Denmark)

Schraube, Ernst

expanding human activities, they are also powerful socio-political “forms of life” (Langdon Winner) constituting the relationship between self and the other and transforming fundamentally the practices of teaching and learning and the processes of generating knowledge. This paper explores the meaning......The teaching and learning spaces at universities are in transformation. With the incorporation of electronic technologies like ipads, smart boards and electronic platforms like “moodle” new digital spaces are emerging in educational practices. These technological spaces are not only useful tools...... of digital learning spaces at universities focusing on their implications for the learning processes of students. Usually studies of technology and learning identify teaching with learning and conceptualize research from an external, third-person standpoint. Starting with a discussion of the paradoxes...

Space Operations Learning Center

Science.gov (United States)

Lui, Ben; Milner, Barbara; Binebrink, Dan; Kuok, Heng

2012-01-01

The Space Operations Learning Center (SOLC) is a tool that provides an online learning environment where students can learn science, technology, engineering, and mathematics (STEM) through a series of training modules. SOLC is also an effective media for NASA to showcase its contributions to the general public. SOLC is a Web-based environment with a learning platform for students to understand STEM through interactive modules in various engineering topics. SOLC is unique in its approach to develop learning materials to teach schoolaged students the basic concepts of space operations. SOLC utilizes the latest Web and software technologies to present this educational content in a fun and engaging way for all grade levels. SOLC uses animations, streaming video, cartoon characters, audio narration, interactive games and more to deliver educational concepts. The Web portal organizes all of these training modules in an easily accessible way for visitors worldwide. SOLC provides multiple training modules on various topics. At the time of this reporting, seven modules have been developed: Space Communication, Flight Dynamics, Information Processing, Mission Operations, Kids Zone 1, Kids Zone 2, and Save The Forest. For the first four modules, each contains three components: Flight Training, Flight License, and Fly It! Kids Zone 1 and 2 include a number of educational videos and games designed specifically for grades K-6. Save The Forest is a space operations mission with four simulations and activities to complete, optimized for new touch screen technology. The Kids Zone 1 module has recently been ported to Facebook to attract wider audience.

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

KAUST Repository

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

2017-01-01

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

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

KAUST Repository

Liang, Ru-Ze

2017-01-17

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

Sweeping the State Space

DEFF Research Database (Denmark)

Mailund, Thomas

The thesis describes the sweep-line method, a newly developed reduction method for alleviating the state explosion problem inherent in explicit-state state space exploration. The basic idea underlying the sweep-line method is, when calculating the state space, to recognise and delete states...... that are not reachable from the currently unprocessed states. Intuitively we drag a sweep-line through the state space with the invariant that all states behind the sweep-line have been processed and are unreachable from the states in front of the sweep-line. When calculating the state space of a system we iteratively...

Psychology of Learning Spaces: Impact on Teaching and Learning

Science.gov (United States)

Granito, Vincent J.; Santana, Mary E.

2016-01-01

New research is emerging that focuses on the role the physical classroom space plays in the teaching-learning dynamic. The purpose of this exploratory research is to describe the students' and instructors' perspectives of how the classroom space and environment impact teaching and learning. Focus groups were utilized with data points coming from…

Decision Making in Reinforcement Learning Using a Modified Learning Space Based on the Importance of Sensors

Directory of Open Access Journals (Sweden)

Yasutaka Kishima

2013-01-01

Full Text Available Many studies have been conducted on the application of reinforcement learning (RL to robots. A robot which is made for general purpose has redundant sensors or actuators because it is difficult to assume an environment that the robot will face and a task that the robot must execute. In this case, -space on RL contains redundancy so that the robot must take much time to learn a given task. In this study, we focus on the importance of sensors with regard to a robot’s performance of a particular task. The sensors that are applicable to a task differ according to the task. By using the importance of the sensors, we try to adjust the state number of the sensors and to reduce the size of -space. In this paper, we define the measure of importance of a sensor for a task with the correlation between the value of each sensor and reward. A robot calculates the importance of the sensors and makes the size of -space smaller. We propose the method which reduces learning space and construct the learning system by putting it in RL. In this paper, we confirm the effectiveness of our proposed system with an experimental robot.

Reinforcement Learning State-of-the-Art

CERN Document Server

Wiering, Marco

2012-01-01

Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together the...

Designing informal learning spaces using student perspectives

OpenAIRE

Matthew David Riddle; Kay Souter

2012-01-01

This article describes the design of informal learning spaces at an Australian university that support students in the generation of knowledge. Recent learning space design projects at La Trobe have been informed by a number of pre-existing projects, including a small research project on student use of technologies, a national project on learning space design, and a significant curriculum renewal process at the university. It demonstrates the ways in which evidence based on student perspectiv...

The right time to learn: mechanisms and optimization of spaced learning

Science.gov (United States)

Smolen, Paul; Zhang, Yili; Byrne, John H.

2016-01-01

For many types of learning, spaced training, which involves repeated long inter-trial intervals, leads to more robust memory formation than does massed training, which involves short or no intervals. Several cognitive theories have been proposed to explain this superiority, but only recently have data begun to delineate the underlying cellular and molecular mechanisms of spaced training, and we review these theories and data here. Computational models of the implicated signalling cascades have predicted that spaced training with irregular inter-trial intervals can enhance learning. This strategy of using models to predict optimal spaced training protocols, combined with pharmacotherapy, suggests novel ways to rescue impaired synaptic plasticity and learning. PMID:26806627

LEARNING AND ENVIRONMENTAL DESIGN: Softer Learning Spaces

Directory of Open Access Journals (Sweden)

E. Ümran TOPÇU

2013-07-01

Full Text Available Learning is a central part of everyone’s life that is often associated with school and  classrooms. Today’ classroom looks and functions like the classroom of an earlier century. Desks lined up in neat rows, facing the teacher and a board or screen is the general condition in many educational institutions. Most of us have sat through classes in plain, hard rooms. Although they did not look very pleasant, we all coped with them. If they could be designed slightly more tolerable, would they help in the betterment of education and learning in any measurable way? This paper aims at describing an attempt to design an alternative classroom. Based on several years of experience, it is observed that there is a demand among students for softer, warmer and more intimate instructional spaces. Students of “People and Environment” Course were asked to select a suitable space to redesign as a “Soft Classroom” within Bahçeşehir University Besiktas Campus  premises. This case study presented a potential research project to etter understand,  how student engagement can be increased by changing learning spaces.

Space: the final frontier in the learning of science?

Science.gov (United States)

Milne, Catherine

2014-03-01

In Space, relations, and the learning of science, Wolff-Michael Roth and Pei-Ling Hsu use ethnomethodology to explore high school interns learning shopwork and shoptalk in a research lab that is located in a world class facility for water quality analysis. Using interaction analysis they identify how spaces, like a research laboratory, can be structured as smart spaces to create a workflow (learning flow) so that shoptalk and shopwork can projectively organize the actions of interns even in new and unfamiliar settings. Using these findings they explore implications for the design of curriculum and learning spaces more broadly. The Forum papers of Erica Blatt and Cassie Quigley complement this analysis. Blatt expands the discussion on space as an active component of learning with an examination of teaching settings, beyond laboratory spaces, as active participants of education. Quigley examines smart spaces as authentic learning spaces while acknowledging how internship experiences all empirical elements of authentic learning including open-ended inquiry and empowerment. In this paper I synthesize these ideas and propose that a narrative structure might better support workflow, student agency and democratic decision making.

The International Active Learning Space

DEFF Research Database (Denmark)

Manners, Ian James

2015-01-01

-Danish students receive the basic international and intercultural skills and knowledge they need in current society. The English-language masters’ seminars I teach at the Department of Political Science are international in terms of students and teacher, but they are also Active Learning seminars......-Danish students (and sometimes teachers) rarely speak to each other or learn each other’s names. In the international AL spaces I create, students must work together on joint tasks which require interaction to address tasks and integration in order to benefit from the multinational activity groups. Planning AL...... that complete the seminar soon become vocal advocates of international AL. Ultimately, enriching student learning through immersing Danish and international students in an international AL space is, for me, the best way of ensuring an internationalised learning outcome, rather than just international mobility....

Autonomous Motion Learning for Intra-Vehicular Activity Space Robot

Science.gov (United States)

Watanabe, Yutaka; Yairi, Takehisa; Machida, Kazuo

Space robots will be needed in the future space missions. So far, many types of space robots have been developed, but in particular, Intra-Vehicular Activity (IVA) space robots that support human activities should be developed to reduce human-risks in space. In this paper, we study the motion learning method of an IVA space robot with the multi-link mechanism. The advantage point is that this space robot moves using reaction force of the multi-link mechanism and contact forces from the wall as space walking of an astronaut, not to use a propulsion. The control approach is determined based on a reinforcement learning with the actor-critic algorithm. We demonstrate to clear effectiveness of this approach using a 5-link space robot model by simulation. First, we simulate that a space robot learn the motion control including contact phase in two dimensional case. Next, we simulate that a space robot learn the motion control changing base attitude in three dimensional case.

Learning space preferences of higher education students

NARCIS (Netherlands)

Beckers, R.; van der Voordt, Theo; Dewulf, G

2016-01-01

This paper aims to address higher education students' learning space preferences. The study is based on a survey that involved 697 business management students of a Dutch University of Applied Sciences. The research focuses on preferred learning spaces for individual study activities, which

Learning space preferences of higher education students

NARCIS (Netherlands)

Beckers, Ronald; van der Voordt, Theo; Dewulf, Geert P.M.R.

2016-01-01

This paper aims to address higher education students’ learning space preferences. The study is based on a survey that involved 697 business management students of a Dutch University of Applied Sciences. The research focuses on preferred learning spaces for individual study activities, which require

Learners’ Perceptions of the Effectiveness of Spaced Learning Schedule in L2 Vocabulary Learning

Directory of Open Access Journals (Sweden)

Amir Reza Lotfolahi

2016-05-01

Full Text Available The spacing effect is a ubiquitous phenomenon, whereby memory is enhanced for the information that is learned across different points in time rather than being learned at once. A considerable amount of research has focused on the nature of the spacing effect, and there is general acceptance that spacing learning events out in time promotes learning. However, fewer studies have been conducted in educational settings. The aim of this study is to explore learners’ perceptions of different spacing schedules (massed vs. spaced. To achieve the purpose of the study, we taught 30 children 24 English–Farsi word pairs utilizing different spacing schedules. Later, we administered a questionnaire to explore leaarners’ perceptions of both massed and spaced schedules. The results revealed that the children percieved spaced practice to be more effective than massed practice.

State Space Modeling Using SAS

Directory of Open Access Journals (Sweden)

Rajesh Selukar

2011-05-01

Full Text Available This article provides a brief introduction to the state space modeling capabilities in SAS, a well-known statistical software system. SAS provides state space modeling in a few different settings. SAS/ETS, the econometric and time series analysis module of the SAS system, contains many procedures that use state space models to analyze univariate and multivariate time series data. In addition, SAS/IML, an interactive matrix language in the SAS system, provides Kalman filtering and smoothing routines for stationary and nonstationary state space models. SAS/IML also provides support for linear algebra and nonlinear function optimization, which makes it a convenient environment for general-purpose state space modeling.

Creating a Public Space through Service-Learning

Science.gov (United States)

Brigham, Erin

2012-01-01

In this paper, I suggest that community-based learning can act as a "public space" for the exchange of religious and non-religious identities. By providing a space for the collaboration between religiously-affiliated Universities and non-religiously affiliated community partners, community-based learning offers the opportunity for the negotiation…

Borderland Spaces for Learning Partnership: Opportunities, Benefits and Challenges

Science.gov (United States)

Hill, Jennifer; Thomas, Greg; Diaz, Anita; Simm, David

2016-01-01

This paper uses case studies and secondary literature to critically examine how learning spaces inhabited by geographers might be used productively as borderland spaces for learning partnership. Borderland spaces are novel, challenging, permissive and liminal, destabilizing traditional power hierarchies. In these spaces, students gain confidence…

Overcoming Learning Time And Space Constraints Through Technological Tool

Directory of Open Access Journals (Sweden)

Nafiseh Zarei

2015-08-01

Full Text Available Today the use of technological tools has become an evolution in language learning and language acquisition. Many instructors and lecturers believe that integrating Web-based learning tools into language courses allows pupils to become active learners during learning process. This study investigate how the Learning Management Blog (LMB overcomes the learning time and space constraints that contribute to students’ language learning and language acquisition processes. The participants were 30 ESL students at National University of Malaysia. A qualitative approach comprising an open-ended questionnaire and a semi-structured interview was used to collect data. The results of the study revealed that the students’ language learning and acquisition processes were enhanced. The students did not face any learning time and space limitations while being engaged in the learning process via the LMB. They learned and acquired knowledge using the language learning materials and forum at anytime and anywhere. Keywords: learning time, learning space, learning management blog

A Space-Based Learning Service for Schools Worldwide

Science.gov (United States)

White, Norman A.; Gibson, Alan

2002-01-01

This paper outlines a scheme for international collaboration to enrich the use of space in school education, to improve students' learning about science and related subjects and to enhance the continuity of science-related studies after the age of 16. Guidelines are presented for the design of an on-line learning service to provide schools worldwide with:- interactive curriculum-related learning resources for teaching about space and through - access to a purpose-designed education satellite or satellites; - opportunities for hands-on work by students in out-of-school hours; - news about space developments to attract, widen and deepen initial interest among teachers - support services to enable teachers to make effective use of the learning service. The Learning Service is the product of almost twenty years of experience by a significant number of UK schools in experimenting with, and in using, satellites and space to aid learning; and over four years of study and development by the SpaceLink Learning Foundation - a private-sector, not- for-profit UK registered charity, which is dedicated to help in increasing both the supply of scientists and engineers and the public understanding of science. This initiative provides scope for, and could benefit from, the involvement of relevant/interested organisations drawn from different countries. The Foundation would be ready, from its UK base, to be among such a group of initiating organisations.

Creating Safe Spaces for Music Learning

Science.gov (United States)

Hendricks, Karin S.; Smith, Tawnya D.; Stanuch, Jennifer

2014-01-01

This article offers a practical model for fostering emotionally safe learning environments that instill in music students a positive sense of self-belief, freedom, and purpose. The authors examine the implications for music educators of creating effective learning environments and present recommendations for creating a safe space for learning,…

Aligning physical learning spaces with the curriculum: AMEE Guide No. 107.

Science.gov (United States)

Nordquist, Jonas; Sundberg, Kristina; Laing, Andrew

2016-08-01

This Guide explores emerging issues on the alignment of learning spaces with the changing curriculum in medical education. As technology and new teaching methods have altered the nature of learning in medical education, it is necessary to re-think how physical learning spaces are aligned with the curriculum. The better alignment of learning spaces with the curriculum depends on more directly engaged leadership from faculty and the community of medical education for briefing the requirements for the design of all kinds of learning spaces. However, there is a lack of precedent and well-established processes as to how new kinds of learning spaces should be programmed. Such programmes are essential aspects of optimizing the intended experience of the curriculum. Faculty and the learning community need better tools and instruments to support their leadership role in briefing and programming. A Guide to critical concepts for exploring the alignment of curriculum and learning spaces is provided. The idea of a networked learning landscape is introduced as a way of assessing and evaluating the alignment of physical spaces to the emerging curriculum. The concept is used to explore how technology has widened the range of spaces and places in which learning happens as well as enabling new styles of learning. The networked learning landscaped is explored through four different scales within which learning is accommodated: the classroom, the building, the campus, and the city. High-level guidance on the process of briefing for the networked learning landscape is provided, to take into account the wider scale of learning spaces and the impact of technology. Key to a successful measurement process is argued to be the involvement of relevant academic stakeholders who can identify the strategic direction and purpose for the design of the learning environments in relation to the emerging demands of the curriculum.

Learning from Space Entrepreneurs

Science.gov (United States)

Pomerantz, William

2008-01-01

The early days of rocketry and space exploration in the United States were marked by incredibly rapid progress: a seemingly endless parade of firsts. Not coincidentally, this period also saw more than its fair share of failure, especially in the infamous "kaputnik" days prior to the successful launch of Explorer. Without a standard canon of known quantities to turn to, the early pioneers of rocketry and space flight were forced to dream up new ideas that ranged from the elegant to the bizarre and to accept the fact that the price of radical progress is occasional failure. Nowadays, rapid prototyping and testing have slowed, as we rely more and more on the extensive knowledge pined by our predecessors and on the embarrassment of riches modern engineers get from computational modeling and computer assisted design. In many cases, this leads to much improved or phenomenally more efficient designs. It also, however, fosters a culture so terrified of failure that we over-engineer and overanalyze everything, often tweaking designs for decades before a new system takes flight. (This is not a problem unique to rockets; the same phenomenon seems to have occurred in high-performance jets.) This is one reason why it was possible for President Kennedy to dream of the completion of the Mercury and Gemini missions and a successful landing on the moon in under a decade, while returning to the moon may take nearly twice as long. Lacking access to the tremendous computational resources of the national space program-and, just as importantly, removed from the harsh judgment of public shareholders or congressional appropriations committees-the hungry entrepreneurs who compete for our prizes tend not to display such fear of failure. Instead, most of them follow a rapid "build, test, fly" program. They are willing to throw a handful of concepts against the wall and see what sticks. They often go from drawing on the back of a napkin to firing engines or even flying vehicles in a matter of

Practical Application of Neural Networks in State Space Control

DEFF Research Database (Denmark)

Bendtsen, Jan Dimon

the networks, although some modifications are needed for the method to apply to the multilayer perceptron network. In connection with the multilayer perceptron networks it is also pointed out how instantaneous, sample-by-sample linearized state space models can be extracted from a trained network, thus opening......In the present thesis we address some problems in discrete-time state space control of nonlinear dynamical systems and attempt to solve them using generic nonlinear models based on artificial neural networks. The main aim of the work is to examine how well such control algorithms perform when...... theoretic notions followed by a detailed description of the topology, neuron functions and learning rules of the two types of neural networks treated in the thesis, the multilayer perceptron and the neurofuzzy networks. In both cases, a Least Squares second-order gradient method is used to train...

Consider the category: The effect of spacing depends on individual learning histories.

Science.gov (United States)

Slone, Lauren K; Sandhofer, Catherine M

2017-07-01

The spacing effect refers to increased retention following learning instances that are spaced out in time compared with massed together in time. By one account, the advantages of spaced learning should be independent of task particulars and previous learning experiences given that spacing effects have been demonstrated in a variety of tasks across the lifespan. However, by another account, spaced learning should be affected by previous learning because past learning affects the memory and attention processes that form the crux of the spacing effect. The current study investigated whether individuals' learning histories affect the role of spacing in category learning. We examined the effect of spacing on 24 2- to 3.5-year-old children's learning of categories organized by properties to which children's previous learning experiences have biased them to attend (i.e., shape) and properties to which children are less biased to attend (i.e., texture and color). Spaced presentations led to significantly better learning of shape categories, but not of texture or color categories, compared with massed presentations. In addition, generalized estimating equations analyses revealed positive relations between the size of children's "shape-side" productive vocabularies and their shape category learning and between the size of children's "against-the-system" productive vocabularies and their texture category learning. These results suggest that children's attention to and memory for novel object categories are strongly related to their individual word-learning histories. Moreover, children's learned attentional biases affected the types of categories for which spacing facilitated learning. These findings highlight the importance of considering how learners' previous experiences may influence future learning. Copyright © 2017 Elsevier Inc. All rights reserved.

NASA’s Universe of Learning: Providing a Direct Connection to NASA Science for Learners of all Ages with ViewSpace

Science.gov (United States)

Lawton, Brandon L.; Rhue, Timothy; Smith, Denise A.; Squires, Gordon K.; Biferno, Anya A.; Lestition, Kathleen; Cominsky, Lynn R.; Godfrey, John; Lee, Janice C.; Manning, Colleen

2018-06-01

NASA's Universe of Learning creates and delivers science-driven, audience-driven resources and experiences designed to engage and immerse learners of all ages and backgrounds in exploring the universe for themselves. The project is the result of a unique partnership between the Space Telescope Science Institute, Caltech/IPAC, Jet Propulsion Laboratory, Smithsonian Astrophysical Observatory, and Sonoma State University, and is one of 27 competitively-selected cooperative agreements within the NASA Science Mission Directorate STEM Activation program. The NASA's Universe of Learning team draws upon cutting-edge science and works closely with Subject Matter Experts (scientists and engineers) from across the NASA Astrophysics Physics of the Cosmos, Cosmic Origins, and Exoplanet Exploration themes. As one example, NASA’s Universe of Learning program is uniquely able to provide informal learning venues with a direct connection to the science of NASA astrophysics via the ViewSpace platform. ViewSpace is a modular multimedia exhibit where people explore the latest discoveries in our quest to understand the universe. Hours of awe-inspiring video content connect users’ lives with an understanding of our planet and the wonders of the universe. This experience is rooted in informal learning, astronomy, and earth science. Scientists and educators are intimately involved in the production of ViewSpace material. ViewSpace engages visitors of varying backgrounds and experience at museums, science centers, planetariums, and libraries across the United States. In addition to creating content, the Universe of Learning team is updating the ViewSpace platform to provide for additional functionality, including the introduction of digital interactives to make ViewSpace a multi-modal learning experience. During this presentation we will share the ViewSpace platform, explain how Subject Matter Experts are critical in creating content for ViewSpace, and how we are addressing audience

The Convergent Learning Space:

DEFF Research Database (Denmark)

Kjærgaard, Hanne Wacher; Kjeldsen, Lars Peter; Asmussen, Jørgen Bering

is described as well as the theoretical construct and hypotheses surrounding the emergence of the concept in technology-rich classrooms, where students bring their own devices and involve their personal learning spaces and networks. The need for new ways of approaching concepts like choice, learning resources......This paper describes the concept of “The Convergent Learning Space” as it is being explored in an ongoing action research project carried out at undergraduate level in select bachelor programs at a Danish University College. The background nature, design, and beginning of this work in progress......, trajectories of participation etc. calls for new action and new pedagogies by teachers in order to secure alignment between students’ worlds and expectations and aims and plans of the teacher. Action research methods are being used to define and test the constituents and variables of the convergent learning...

History and Evolution of Active Learning Spaces

Science.gov (United States)

Beichner, Robert J.

2014-01-01

This chapter examines active learning spaces as they have developed over the years. Consistently well-designed classrooms can facilitate active learning even though the details of implementing pedagogies may differ.

Reinforcement Learning in Continuous Action Spaces

NARCIS (Netherlands)

Hasselt, H. van; Wiering, M.A.

2007-01-01

Quite some research has been done on Reinforcement Learning in continuous environments, but the research on problems where the actions can also be chosen from a continuous space is much more limited. We present a new class of algorithms named Continuous Actor Critic Learning Automaton (CACLA)

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

OpenAIRE

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

2017-01-01

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

Spaced learning and innovative teaching: school time, pedagogy of attention and learning awareness

Directory of Open Access Journals (Sweden)

Garzia Maeca

2016-06-01

Full Text Available Currently, the ‘time’ variable has taken on the function of instructional and pedagogical innovation catalyst, after representing-over the years-a symbol of democratisation, learning opportunity and instruction quality, able to incorporate themes such as school dropout, personalisation and vocation into learning. Spaced Learning is a teaching methodology useful to quickly seize information in long-term memory based on a particular arrangement of the lesson time that comprises three input sessions and two intervals. Herein we refer to a teachers’ training initiative on Spaced Learning within the programme ‘DocentiInFormAzione’ in the EDOC@WORK3.0 Project in Apulia region in 2015. The training experience aimed at increasing teachers’ competencies in the Spaced Learning method implemented in a context of collaborative reflection and reciprocal enrichment. The intent of the article is to show how a process of rooting of the same culture of innovation, which opens to the discovery (or rediscovery of effective teaching practices sustained by scientific evidences, can be successfully implemented and to understand how or whether this innovation- based on the particular organisation of instructional time-links learning awareness to learning outcomes.

Designing New Learning Spaces

NARCIS (Netherlands)

Specht, Marcus

2014-01-01

We are moving towards new learning spaces merging the digital and the physical world. Real world objects get augmented by information streams and real world activities are measured with sensor technology to be reviewed afterwards or in real time. A variety of links is currently created to link

Space Transportation and the Computer Industry: Learning from the Past

Science.gov (United States)

Merriam, M. L.; Rasky, D.

2002-01-01

Since the space shuttle began flying in 1981, NASA has made a number of attempts to advance the state of the art in space transportation. In spite of billions of dollars invested, and several concerted attempts, no replacement for the shuttle is expected before 2010. Furthermore, the cost of access to space has dropped very slowly over the last two decades. On the other hand, the same two decades have seen dramatic progress in the computer industry. Computational speeds have increased by about a factor of 1000 and available memory, disk space, and network bandwidth has seen similar increases. At the same time, the cost of computing has dropped by about a factor of 10000. Is the space transportation problem simply harder? Or is there something to be learned from the computer industry? In looking for the answers, this paper reviews the early history of NASA's experience with supercomputers and NASA's visionary course change in supercomputer procurement strategy.

Connecting Learning Spaces Using Mobile Technology

Science.gov (United States)

Chen, Wenli; Seow, Peter; So, Hyo-Jeong; Toh, Yancy; Looi, Chee-Kit

2010-01-01

The use of mobile technology can help extend children's learning spaces and enrich the learning experiences in their everyday lives where they move from one context to another, switching locations, social groups, technologies, and topics. When students have ubiquitous access to mobile devices with full connectivity, the in-situ use of the mobile…

Condensed State Spaces for Symmetrical Coloured Petri Nets

DEFF Research Database (Denmark)

Jensen, Kurt

1996-01-01

equivalence classes of states and equivalence classes of state changes. It is then possible to construct a condensed state space where each node represents an equivalence class of states while each arc represents an equivalence class of state changes. Such a condensed state space is often much smaller than...... the full state space and it is also much faster to construct. Nevertheless, it is possible to use the condensed state space to verify the same kind of behavioural properties as the full state space. Hence, we do not lose analytic power. We define state spaces and condensed state spaces for a language......-nets (or Petri nets in general) - although such knowledge will, of course, be a help. The first four sections of the paper introduce the basic concepts of CP-nets. The next three sections deal with state spaces, condensed state spaces and computer tools for state space analysis. Finally, there is a short...

The Online Classroom: A Thorough Depiction of Distance Learning Spaces

Science.gov (United States)

McKenna, Kelly

2018-01-01

This study investigated the online higher education learning space of a doctoral program offered at a distance. It explored the learning space, the stakeholders, utilization, and creators of the space. Developing a successful online classroom experience that incorporates an engaging environment and dynamic community setting conducive to learning…

My Life with State Space Models

DEFF Research Database (Denmark)

Lundbye-Christensen, Søren

2007-01-01

. The conceptual idea behind the state space model is that the evolution over time in the object we are observing and the measurement process itself are modelled separately. My very first serious analysis of a data set was done using a state space model, and since then I seem to have been "haunted" by state space...

Affinity Spaces and 21st Century Learning

Science.gov (United States)

Gee, James Paul

2017-01-01

This article discusses video games as "attractors" to "affinity spaces." It argues that affinity spaces are key sites today where people teach and learn 21st Century skills. While affinity spaces are proliferating on the Internet as interest-and-passion-driven sites devoted to a common set of endeavors, they are not new, just…

The Critical Importance of Retrieval--and Spacing--for Learning.

Science.gov (United States)

Soderstrom, Nicholas C; Kerr, Tyson K; Bjork, Robert A

2016-02-01

We examined the impact of repeated testing and repeated studying on long-term learning. In Experiment 1, we replicated Karpicke and Roediger's (2008) influential results showing that once information can be recalled, repeated testing on that information enhances learning, whereas restudying that information does not. We then examined whether the apparent ineffectiveness of restudying might be attributable to the spacing differences between items that were inherent in the between-subjects design employed by Karpicke and Roediger. When we controlled for these spacing differences by manipulating the various learning conditions within subjects in Experiment 2, we found that both repeated testing and restudying improved learning, and that learners' awareness of the relative mnemonic benefits of these strategies was enhanced. These findings contribute to understanding how two important factors in learning-test-induced retrieval processes and spacing-can interact, and they illustrate that such interactions can play out differently in between-subjects and within-subjects experimental designs. © The Author(s) 2015.

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

Science.gov (United States)

Phillips, Carolyn L.

2014-09-01

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

Space reactor safety, 1985--1995 lessons learned

International Nuclear Information System (INIS)

Marshall, A.C.

1995-01-01

Space reactor safety activities and decisions have evolved over the last decade. Important safety decisions have been made in the SP-100, Space Exploration Initiative, NEPSTP, SNTP, and Bimodal Space Reactor programs. In addition, international guidance on space reactor safety has been instituted. Space reactor safety decisions and practices have developed in the areas of inadvertent criticality, reentry, radiological release, orbital operation, programmatic, and policy. In general, the lessons learned point out the importance of carefully reviewing previous safety practices for appropriateness to space nuclear programs in general and to the specific mission under consideration

Space reactor safety, 1985--1995 lessons learned

Energy Technology Data Exchange (ETDEWEB)

Marshall, A.C.

1995-12-31

Space reactor safety activities and decisions have evolved over the last decade. Important safety decisions have been made in the SP-100, Space Exploration Initiative, NEPSTP, SNTP, and Bimodal Space Reactor programs. In addition, international guidance on space reactor safety has been instituted. Space reactor safety decisions and practices have developed in the areas of inadvertent criticality, reentry, radiological release, orbital operation, programmatic, and policy. In general, the lessons learned point out the importance of carefully reviewing previous safety practices for appropriateness to space nuclear programs in general and to the specific mission under consideration.

Switching Reinforcement Learning for Continuous Action Space

Science.gov (United States)

Nagayoshi, Masato; Murao, Hajime; Tamaki, Hisashi

Reinforcement Learning (RL) attracts much attention as a technique of realizing computational intelligence such as adaptive and autonomous decentralized systems. In general, however, it is not easy to put RL into practical use. This difficulty includes a problem of designing a suitable action space of an agent, i.e., satisfying two requirements in trade-off: (i) to keep the characteristics (or structure) of an original search space as much as possible in order to seek strategies that lie close to the optimal, and (ii) to reduce the search space as much as possible in order to expedite the learning process. In order to design a suitable action space adaptively, we propose switching RL model to mimic a process of an infant's motor development in which gross motor skills develop before fine motor skills. Then, a method for switching controllers is constructed by introducing and referring to the “entropy”. Further, through computational experiments by using robot navigation problems with one and two-dimensional continuous action space, the validity of the proposed method has been confirmed.

Researching transformative learning spaces through learners' stories

DEFF Research Database (Denmark)

Maslo, Elina

spaces, learning to learn through languages, learners´ stories, qualitative research method Methodology or Methods/Research Instruments or Sources Used A number of semi structured qualitative interviews have been conducted with three learners of Danish as second language. The language learners...... in the paper is on the research process and methodological tools. The goal of this paper is to show, that learners´ stories have a huge potential in researching learning processes. References Benson, P. & D. Nunan (2004). Lerners´ stories. Difference and Diversity in Language Learning. Cambridge University...... to use learners´ stories as a research methodology in the field of learning in general and language learning in particular....

State Space Analysis of Hierarchical Coloured Petri Nets

DEFF Research Database (Denmark)

Christensen, Søren; Kristensen, Lars Michael

2003-01-01

In this paper, we consider state space analysis of Coloured Petri Nets. It is well-known that almost all dynamic properties of the considered system can be verified when the state space is finite. However, state space analysis is more than just formulating a set of formal requirements and invokin...... supporting computation and storage of state spaces which exploi the hierarchical structure of the models....... in which formal verification, partial state spaces, and analysis by means of graphical feedback and simulation are integrated entities. The focus of the paper is twofold: the support for graphical feedback and the way it has been integrated with simulation, and the underlying algorithms and data-structures......In this paper, we consider state space analysis of Coloured Petri Nets. It is well-known that almost all dynamic properties of the considered system can be verified when the state space is finite. However, state space analysis is more than just formulating a set of formal requirements and invoking...

Statistical Software for State Space Methods

Directory of Open Access Journals (Sweden)

Jacques J. F. Commandeur

2011-05-01

Full Text Available In this paper we review the state space approach to time series analysis and establish the notation that is adopted in this special volume of the Journal of Statistical Software. We first provide some background on the history of state space methods for the analysis of time series. This is followed by a concise overview of linear Gaussian state space analysis including the modelling framework and appropriate estimation methods. We discuss the important class of unobserved component models which incorporate a trend, a seasonal, a cycle, and fixed explanatory and intervention variables for the univariate and multivariate analysis of time series. We continue the discussion by presenting methods for the computation of different estimates for the unobserved state vector: filtering, prediction, and smoothing. Estimation approaches for the other parameters in the model are also considered. Next, we discuss how the estimation procedures can be used for constructing confidence intervals, detecting outlier observations and structural breaks, and testing model assumptions of residual independence, homoscedasticity, and normality. We then show how ARIMA and ARIMA components models fit in the state space framework to time series analysis. We also provide a basic introduction for non-Gaussian state space models. Finally, we present an overview of the software tools currently available for the analysis of time series with state space methods as they are discussed in the other contributions to this special volume.

State Space Methods for Timed Petri Nets

DEFF Research Database (Denmark)

Christensen, Søren; Jensen, Kurt; Mailund, Thomas

2001-01-01

it possible to condense the usually infinite state space of a timed Petri net into a finite condensed state space without loosing analysis power. The second method supports on-the-fly verification of certain safety properties of timed systems. We discuss the application of the two methods in a number......We present two recently developed state space methods for timed Petri nets. The two methods reconciles state space methods and time concepts based on the introduction of a global clock and associating time stamps to tokens. The first method is based on an equivalence relation on states which makes...

Learning spaces as representational scaffolds for learning conceptual knowledge of system behaviour

NARCIS (Netherlands)

Bredeweg, B.; Liem, J.; Beek, W.; Salles, P.; Linnebank, F.; Wolpers, M.; Kirschner, P.A.; Scheffel, M.; Lindstaedt, S.; Dimitrova, V.

2010-01-01

Scaffolding is a well-known approach to bridge the gap between novice and expert capabilities in a discovery-oriented learning environment. This paper discusses a set of knowledge representations referred to as Learning Spaces (LSs) that can be used to support learners in acquiring conceptual

Navigation and wayfinding in learning spaces in 3D virtual worlds

OpenAIRE

Minocha, Shailey; Hardy, Christopher

2016-01-01

There is a lack of published research on the design guidelines of learning spaces in virtual worlds. Therefore, when institutions aspire to create learning spaces in Second Life, there are few studies or guidelines to inform them except for individual case studies. The Design of Learning Spaces in 3D Virtual Environments (DELVE) project, funded by the Joint Information Systems Committee in the UK, was one of the first initiatives that identified through empirical investigations the usability ...

Problem and Project Based Learning in Hybrid Spaces

DEFF Research Database (Denmark)

Ryberg, Thomas; Davidsen, Jacob; Hodgson, Vivien

2016-01-01

There is a need within networked learning to understand and conceptualise the interplay between digital and physical spaces or what we could term hybrid spaces. Therefore, we discuss a recent study of students from two different programmes who are engaged in long-term, group-based problem...... and project based learning. Based on interviews, workshops and observations of students’ actual group practices in open, shared and flexible spaces in Aalborg University (AAU), we identify and discuss how students incorporate networked and digital technologies into their group work and into the study places...... they create for themselves. We describe how in one of the programmes ‘nomadic’ groups of students used different technologies and spaces for ‘placemaking’. We then show how their experience and approach to collaborative work differs to that of the more static or ‘artisan’ groups of students in the other...

Trial and Error: A new Approach to Space-Bounded Learning

DEFF Research Database (Denmark)

Ameur, F.; Fischer, Paul; Hoeffgen, H.-U.

1996-01-01

A pac-learning algorithm is d-space bounded, if it stores at most d examples from the sample at any time. We characterize the d-space learnable concept classes. For this purpose we introduce the compression parameter of a concept class 𝒞 and design our trial and error learning algorithm. We ...

Self-supervised learning as an enabling technology for future space exploration robots: ISS experiments on monocular distance learning

Science.gov (United States)

van Hecke, Kevin; de Croon, Guido C. H. E.; Hennes, Daniel; Setterfield, Timothy P.; Saenz-Otero, Alvar; Izzo, Dario

2017-11-01

Although machine learning holds an enormous promise for autonomous space robots, it is currently not employed because of the inherent uncertain outcome of learning processes. In this article we investigate a learning mechanism, Self-Supervised Learning (SSL), which is very reliable and hence an important candidate for real-world deployment even on safety-critical systems such as space robots. To demonstrate this reliability, we introduce a novel SSL setup that allows a stereo vision equipped robot to cope with the failure of one of its cameras. The setup learns to estimate average depth using a monocular image, by using the stereo vision depths from the past as trusted ground truth. We present preliminary results from an experiment on the International Space Station (ISS) performed with the MIT/NASA SPHERES VERTIGO satellite. The presented experiments were performed on October 8th, 2015 on board the ISS. The main goals were (1) data gathering, and (2) navigation based on stereo vision. First the astronaut Kimiya Yui moved the satellite around the Japanese Experiment Module to gather stereo vision data for learning. Subsequently, the satellite freely explored the space in the module based on its (trusted) stereo vision system and a pre-programmed exploration behavior, while simultaneously performing the self-supervised learning of monocular depth estimation on board. The two main goals were successfully achieved, representing the first online learning robotic experiments in space. These results lay the groundwork for a follow-up experiment in which the satellite will use the learned single-camera depth estimation for autonomous exploration in the ISS, and are an advancement towards future space robots that continuously improve their navigation capabilities over time, even in harsh and completely unknown space environments.

Representative Model of the Learning Process in Virtual Spaces Supported by ICT

Science.gov (United States)

Capacho, José

2014-01-01

This paper shows the results of research activities for building the representative model of the learning process in virtual spaces (e-Learning). The formal basis of the model are supported in the analysis of models of learning assessment in virtual spaces and specifically in Dembo´s teaching learning model, the systemic approach to evaluating…

Projective loop quantum gravity. I. State space

Science.gov (United States)

Lanéry, Suzanne; Thiemann, Thomas

2016-12-01

Instead of formulating the state space of a quantum field theory over one big Hilbert space, it has been proposed by Kijowski to describe quantum states as projective families of density matrices over a collection of smaller, simpler Hilbert spaces. Beside the physical motivations for this approach, it could help designing a quantum state space holding the states we need. In a latter work by Okolów, the description of a theory of Abelian connections within this framework was developed, an important insight being to use building blocks labeled by combinations of edges and surfaces. The present work generalizes this construction to an arbitrary gauge group G (in particular, G is neither assumed to be Abelian nor compact). This involves refining the definition of the label set, as well as deriving explicit formulas to relate the Hilbert spaces attached to different labels. If the gauge group happens to be compact, we also have at our disposal the well-established Ashtekar-Lewandowski Hilbert space, which is defined as an inductive limit using building blocks labeled by edges only. We then show that the quantum state space presented here can be thought as a natural extension of the space of density matrices over this Hilbert space. In addition, it is manifest from the classical counterparts of both formalisms that the projective approach allows for a more balanced treatment of the holonomy and flux variables, so it might pave the way for the development of more satisfactory coherent states.

The Evolution of Failure Analysis at NASA's Kennedy Space Center and the Lessons Learned

Science.gov (United States)

Long, Victoria S.; Wright, M. Clara; McDanels, Steve

2015-01-01

The United States has had four manned launch programs and three station programs since the era of human space flight began in 1961. The launch programs, Mercury, Gemini, Apollo, and Shuttle, and the station programs, Skylab, Shuttle-Mir, and the International Space Station (ISS), have all been enormously successful, not only in advancing the exploration of space, but also in advancing related technologies. As each subsequent program built upon the successes of previous programs, they similarly learned from their predecessors' failures. While some failures were spectacular and captivated the attention of the world, most only held the attention of the dedicated men and women working to make the missions succeed.

Advanced Learning Space as an Asset for Students with Disabilities

Science.gov (United States)

Císarová, Klára; Lamr, Marián; Vitvarová, Jana

2015-01-01

The paper describes an e-learning system called Advanced Learning Space that was developed at the Technical University of Liberec. The system provides a personalized virtual work space and promotes communication among students and their teachers. The core of the system is a module that can be used to automatically record, store and playback…

Conferences as a Dramaturgical Learning Space

DEFF Research Database (Denmark)

Hansen, Nicoline Jacoby

Arguing that conferences are an important but under-researched and under-developed dimension of continuing education, the paper proposes a notion of conferences as a dramatic learning space. Using the design-based research methodology, a theoretical framework drawing on adult learning theories...... and dramaturgy is developed, consisting of four design principles: rhythm, reflection, involvement and interaction. These are sought implemented in a specific conference program, the case of the ECCI X conference, and the final program is explained and discussed....

State-Space Formulation for Circuit Analysis

Science.gov (United States)

Martinez-Marin, T.

2010-01-01

This paper presents a new state-space approach for temporal analysis of electrical circuits. The method systematically obtains the state-space formulation of nondegenerate linear networks without using concepts of topology. It employs nodal/mesh systematic analysis to reduce the number of undesired variables. This approach helps students to…

Listening to Students: Make Learning Spaces Your Own

Science.gov (United States)

Shouder, Tim; Inglis, Grant; Rossini, Alexander

2014-01-01

Today, collaborative learning and teamwork are largely achieved through remote connections that are increasingly available and powerful. Collaboration of this sort is the highlight of an award-winning film "Your Own," which the authors created in response to the question, "What makes a learning space great?" for Herman…

Lack of spacing effects during piano learning.

Directory of Open Access Journals (Sweden)

Melody Wiseheart

Full Text Available Spacing effects during retention of verbal information are easily obtained, and the effect size is large. Relatively little evidence exists on whether motor skill retention benefits from distributed practice, with even less evidence on complex motor skills. We taught a 17-note musical sequence on a piano to individuals without prior formal training. There were five lags between learning episodes: 0-, 1-, 5-, 10-, and 15-min. After a 5-min retention interval, participants' performance was measured using three criteria: accuracy of note playing, consistency in pressure applied to the keys, and consistency in timing. No spacing effect was found, suggesting that the effect may not always be demonstrable for complex motor skills or non-verbal abilities (timing and motor skills. Additionally, we taught short phrases from five songs, using the same set of lags and retention interval, and did not find any spacing effect for accuracy of song reproduction. Our findings indicate that although the spacing effect is one of the most robust phenomena in the memory literature (as demonstrated by verbal learning studies, the effect may vary when considered in the novel realm of complex motor skills such as piano performance.

Lack of spacing effects during piano learning.

Science.gov (United States)

Wiseheart, Melody; D'Souza, Annalise A; Chae, Jacey

2017-01-01

Spacing effects during retention of verbal information are easily obtained, and the effect size is large. Relatively little evidence exists on whether motor skill retention benefits from distributed practice, with even less evidence on complex motor skills. We taught a 17-note musical sequence on a piano to individuals without prior formal training. There were five lags between learning episodes: 0-, 1-, 5-, 10-, and 15-min. After a 5-min retention interval, participants' performance was measured using three criteria: accuracy of note playing, consistency in pressure applied to the keys, and consistency in timing. No spacing effect was found, suggesting that the effect may not always be demonstrable for complex motor skills or non-verbal abilities (timing and motor skills). Additionally, we taught short phrases from five songs, using the same set of lags and retention interval, and did not find any spacing effect for accuracy of song reproduction. Our findings indicate that although the spacing effect is one of the most robust phenomena in the memory literature (as demonstrated by verbal learning studies), the effect may vary when considered in the novel realm of complex motor skills such as piano performance.

Space Weather in the Machine Learning Era: A Multidisciplinary Approach

Science.gov (United States)

Camporeale, E.; Wing, S.; Johnson, J.; Jackman, C. M.; McGranaghan, R.

2018-01-01

The workshop entitled Space Weather: A Multidisciplinary Approach took place at the Lorentz Center, University of Leiden, Netherlands, on 25-29 September 2017. The aim of this workshop was to bring together members of the Space Weather, Mathematics, Statistics, and Computer Science communities to address the use of advanced techniques such as Machine Learning, Information Theory, and Deep Learning, to better understand the Sun-Earth system and to improve space weather forecasting. Although individual efforts have been made toward this goal, the community consensus is that establishing interdisciplinary collaborations is the most promising strategy for fully utilizing the potential of these advanced techniques in solving Space Weather-related problems.

Student Perceptions of a 21st Century Learning Space

Science.gov (United States)

Adedokun, Omolola A.; Henke, Jacqueline N.; Parker, Loran Carleton; Burgess, Wilella D.

2017-01-01

Higher education institutions are increasingly building or remodeling classrooms to be flexible spaces that support learner-centered instruction. However, little is known about the actual impact of these spaces on student outcomes. Using a mixed method design, this study examined student perceptions of a flexible learning space on student learning…

Successive and discrete spaced conditioning in active avoidance learning in young and aged zebrafish.

Science.gov (United States)

Yang, Peng; Kajiwara, Riki; Tonoki, Ayako; Itoh, Motoyuki

2018-05-01

We designed an automated device to study active avoidance learning abilities of zebrafish. Open source tools were used for the device control, statistical computing, and graphic outputs of data. Using the system, we developed active avoidance tests to examine the effects of trial spacing and aging on learning. Seven-month-old fish showed stronger avoidance behavior as measured by color preference index with discrete spaced training as compared to successive spaced training. Fifteen-month-old fish showed a similar trend, but with reduced cognitive abilities compared with 7-month-old fish. Further, in 7-month-old fish, an increase in learning ability during trials was observed with discrete, but not successive, spaced training. In contrast, 15-month-old fish did not show increase in learning ability during trials. Therefore, these data suggest that discrete spacing is more effective for learning than successive spacing, with the zebrafish active avoidance paradigm, and that the time course analysis of active avoidance using discrete spaced training is useful to detect age-related learning impairment. Copyright © 2017 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.

Organizing for Spaces and Dynamics of Multipolar Learning in Multinational Corporations

DEFF Research Database (Denmark)

Hull Kristensen, Peer; Lotz, Maja

Limited research has been conducted on how MNCs organize conditions and spaces for recursive learning to facilitate the practice of innovation across dispersed units as well as how organizational members at all levels may become involved in innovations through the engagement in ongoing multipolar...... learning dynamics. Based on longitudinal case studies in two MNCs this paper contributes with insights into how spaces and dynamics of multipolar learning are organized and governed across dispersed MNC units at the micro level of everyday work practices. The paper shows that it is possible to organize...... spaces and dynamics that can organize recursiveness and continuity in multipolar learning by way of experimentation with new coordination components and governance architectures. Against the previous literature, however, it becomes evident that these are not the outcome of spontaneous interactions...

Spaced Learning Enhances Subsequent Recognition Memory by Reducing Neural Repetition Suppression

Science.gov (United States)

Xue, Gui; Mei, Leilei; Chen, Chuansheng; Lu, Zhong-Lin; Poldrack, Russell; Dong, Qi

2011-01-01

Spaced learning usually leads to better recognition memory as compared with massed learning, yet the underlying neural mechanisms remain elusive. One open question is whether the spacing effect is achieved by reducing neural repetition suppression. In this fMRI study, participants were scanned while intentionally memorizing 120 novel faces, half…

Studying Space: Improving Space Planning with User Studies

Science.gov (United States)

Pierard, Cindy; Lee, Norice

2011-01-01

How can libraries best assess and improve user space, even if they are not in a position to undertake new construction or a major renovation? Staff at New Mexico State University used a variety of ethnographic methods to learn how our spaces were being used as well as what our users considered to be ideal library space. Our findings helped us make…

Better library and learning space projects, trends, ideas

CERN Document Server

Watson, Les

2014-01-01

What are the most important things a 21st-century library should do with its space? This title includes chapters that address this critical question, capturing the insights and practical ideas of international librarians, educators and designers to offer you a 'creative resource bank' that helps to transform your library and learning spaces.

Human reinforcement learning subdivides structured action spaces by learning effector-specific values.

Science.gov (United States)

Gershman, Samuel J; Pesaran, Bijan; Daw, Nathaniel D

2009-10-28

Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable because of the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning-such as prediction error signals for action valuation associated with dopamine and the striatum-can cope with this "curse of dimensionality." We propose a reinforcement learning framework that allows for learned action valuations to be decomposed into effector-specific components when appropriate to a task, and test it by studying to what extent human behavior and blood oxygen level-dependent (BOLD) activity can exploit such a decomposition in a multieffector choice task. Subjects made simultaneous decisions with their left and right hands and received separate reward feedback for each hand movement. We found that choice behavior was better described by a learning model that decomposed the values of bimanual movements into separate values for each effector, rather than a traditional model that treated the bimanual actions as unitary with a single value. A decomposition of value into effector-specific components was also observed in value-related BOLD signaling, in the form of lateralized biases in striatal correlates of prediction error and anticipatory value correlates in the intraparietal sulcus. These results suggest that the human brain can use decomposed value representations to "divide and conquer" reinforcement learning over high-dimensional action spaces.

Learning Spaces in Academic Libraries--A Review of the Evolving Trends

Science.gov (United States)

Turner, Arlee; Welch, Bernadette; Reynolds, Sue

2013-01-01

This paper presents a review of the professional discourse regarding the evolution of information and learning spaces in academic libraries, particularly in the first decade of the twenty-first century. It investigates the evolution of academic libraries and the development of learning spaces focusing on the use of the terms which have evolved…

Problem and Project Based Learning in Hybrid Spaces:Nomads and Artisans

OpenAIRE

Ryberg, Thomas; Davidsen, Jacob; Hodgson, Vivien

2016-01-01

There is a need within networked learning to understand and conceptualise the interplay between digital and physical spaces or what we could term hybrid spaces. Therefore, we discuss a recent study of students from two different programmes who are engaged in long-term, group-based problem and project based learning. Based on interviews, workshops and observations of students’ actual group practices in open, shared and flexible spaces in Aalborg University (AAU), we identify and discuss how st...

Exploration of joint redundancy but not task space variability facilitates supervised motor learning.

Science.gov (United States)

Singh, Puneet; Jana, Sumitash; Ghosal, Ashitava; Murthy, Aditya

2016-12-13

The number of joints and muscles in a human arm is more than what is required for reaching to a desired point in 3D space. Although previous studies have emphasized how such redundancy and the associated flexibility may play an important role in path planning, control of noise, and optimization of motion, whether and how redundancy might promote motor learning has not been investigated. In this work, we quantify redundancy space and investigate its significance and effect on motor learning. We propose that a larger redundancy space leads to faster learning across subjects. We observed this pattern in subjects learning novel kinematics (visuomotor adaptation) and dynamics (force-field adaptation). Interestingly, we also observed differences in the redundancy space between the dominant hand and nondominant hand that explained differences in the learning of dynamics. Taken together, these results provide support for the hypothesis that redundancy aids in motor learning and that the redundant component of motor variability is not noise.

Portrait of a rural health graduate: exploring alternative learning spaces.

Science.gov (United States)

Ross, Andrew; Pillay, Daisy

2015-05-01

Given that the staffing of rural facilities represents an international challenge, the support, training and development of students of rural origin at institutions of higher learning (IHLs) should be an integral dimension of health care provisioning. International studies have shown these students to be more likely than students of urban origin to return to work in rural areas. However, the crisis in formal school education in some countries, such as South Africa, means that rural students with the capacity to pursue careers in health care are least likely to access the necessary training at an IHL. In addition to challenges of access, throughput is relatively low at IHLs and is determined by a range of learning experiences. Insight into the storied educational experiences of health care professionals (HCPs) of rural origin has the potential to inform the training and development of rural-origin students. Six HCPs of rural origin were purposively selected. Using a narrative inquiry approach, data were generated from long interviews and a range of arts-based methods to create and reconstruct the storied narratives of the six participants. Codes, categories and themes were developed from the reconstructed stories. Reid's four-quadrant model of learning theory was used to focus on the learning experiences of one participant. Alternative learning spaces were identified, which were made available through particular social spaces outwith formal lecture rooms. These offered opportunities for collaboration and for the reconfiguring of the participants' agency to be, think and act differently. Through the practices enacted in particular learning spaces, relationships of caring, sharing, motivating and mentoring were formed, which contributed to personal, social, academic and professional development and success. Learning spaces outwith the formal lecture theatre are critical to the acquisition of good clinical skills and knowledge in the development of socially accountable

Live from Space Station Learning Technologies Project

Science.gov (United States)

2001-01-01

This is the Final Report for the Live From Space Station (LFSS) project under the Learning Technologies Project FY 2001 of the MSFC Education Programs Department. AZ Technology, Inc. (AZTek) has developed and implemented science education software tools to support tasks under the LTP program. Initial audience consisted of 26 TreK in the Classroom schools and thousands of museum visitors to the International Space Station: The Earth Tour exhibit sponsored by Discovery Place museum.

Distributing learning over time: the spacing effect in children's acquisition and generalization of science concepts.

Science.gov (United States)

Vlach, Haley A; Sandhofer, Catherine M

2012-01-01

The spacing effect describes the robust finding that long-term learning is promoted when learning events are spaced out in time rather than presented in immediate succession. Studies of the spacing effect have focused on memory processes rather than for other types of learning, such as the acquisition and generalization of new concepts. In this study, early elementary school children (5- to 7-year-olds; N = 36) were presented with science lessons on 1 of 3 schedules: massed, clumped, and spaced. The results revealed that spacing lessons out in time resulted in higher generalization performance for both simple and complex concepts. Spaced learning schedules promote several types of learning, strengthening the implications of the spacing effect for educational practices and curriculum. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

Yahoo! Answers as a Space for Informal Language Learning

Directory of Open Access Journals (Sweden)

Giuliana Dettori

2014-10-01

Full Text Available Online social spaces, where users can exchange information, opinions and resources, have achieved wide popularity and are gaining attention in many research fields, including education. Their actual potential support to learning, however, still requires investigation, especially because portals can widely differ as concerns purpose and internal structure. This paper aims to contribute in this respect, by concentrating on question answering, a kind of social space not yet widely discussed in education. We analyzed a small corpus of posts from the Languages section of Yahoo! Answers Italy, checking if the questions reveal some inclination to learning or just the desire to obtain a service and if the answers provided by the community members can be considered as reliable sources of knowledge. Our analysis highlights the presence of a variety of question/answer types, from mere information exchange or help for task completion, up to language-related questions prompting valuable short lessons. The quality of answers may widely vary as concerns pertinence, correctness and richness of supporting elements. We found a high number of purely task-oriented questions and answers, but also a higher number of learning-oriented questions and correct, informative answers. This suggests that this kind of social space actually has valuable potential for informal learning.

Aligning Pedagogy with Physical Learning Spaces

Science.gov (United States)

van Merriënboer, Jeroen J. G.; McKenney, Susan; Cullinan, Dominic; Heuer, Jos

2017-01-01

The quality of education suffers when pedagogies are not aligned with physical learning spaces. For example, the architecture of the triple-decker Victorian schools across England fits the information transmission model that was dominant in the industrial age, but makes it more difficult to implement student-centred pedagogies that better fit a…

Understanding Interorganizational Learning Based on Social Spaces and Learning Episodes

Directory of Open Access Journals (Sweden)

Anelise Rebelato Mozzato

2014-07-01

Full Text Available Different organizational settings have been gaining ground in the world economy, resulting in a proliferation of different forms of strategic alliances that translate into a growth in the number of organizations that have started to deal with interorganizational relationships with different actors. These circumstances reinforce Crossan, Lane, White and Djurfeldt (1995 and Crossan, Mauer and White (2011 in exploring what authors refer to as the fourth, interorganizational, level of learning. These authors, amongst others, suggest that the process of interorganizational learning (IOL warrants investigation, as its scope of analysis needs widening and deepening. Therefore, this theoretical essay is an attempt to understand IOL as a dynamic process found in interorganizational cooperative relationships that can take place in different structured and unstructured social spaces and that can generate learning episodes. According to this view, IOL is understood as part of an organizational learning continuum and is analyzed within the framework of practical rationality in an approach that is less cognitive and more social-behavioral.

Machine learning topological states

Science.gov (United States)

Deng, Dong-Ling; Li, Xiaopeng; Das Sarma, S.

2017-11-01

Artificial neural networks and machine learning have now reached a new era after several decades of improvement where applications are to explode in many fields of science, industry, and technology. Here, we use artificial neural networks to study an intriguing phenomenon in quantum physics—the topological phases of matter. We find that certain topological states, either symmetry-protected or with intrinsic topological order, can be represented with classical artificial neural networks. This is demonstrated by using three concrete spin systems, the one-dimensional (1D) symmetry-protected topological cluster state and the 2D and 3D toric code states with intrinsic topological orders. For all three cases, we show rigorously that the topological ground states can be represented by short-range neural networks in an exact and efficient fashion—the required number of hidden neurons is as small as the number of physical spins and the number of parameters scales only linearly with the system size. For the 2D toric-code model, we find that the proposed short-range neural networks can describe the excited states with Abelian anyons and their nontrivial mutual statistics as well. In addition, by using reinforcement learning we show that neural networks are capable of finding the topological ground states of nonintegrable Hamiltonians with strong interactions and studying their topological phase transitions. Our results demonstrate explicitly the exceptional power of neural networks in describing topological quantum states, and at the same time provide valuable guidance to machine learning of topological phases in generic lattice models.

Space strategy and governance of ESA small member states

Science.gov (United States)

Sagath, Daniel; Papadimitriou, Angeliki; Adriaensen, Maarten; Giannopapa, Christina

2018-01-01

The European Space Agency (ESA) has twenty-two Member States with a variety of governance structures and strategic priorities regarding their space activities. The objective of this paper is to provide an up-to date overview and a holistic assessment of the national space governance structures and strategic priorities of the eleven smaller Member States (based on annual ESA contributions). A link is made between the governance structure and the main strategic objectives. The specific needs and interests of small and new Member States in the frame of European Space Integration are addressed. The first part of the paper focuses on the national space governance structures in the eleven smaller ESA Member States. The governance models of these Member States are identified including the responsible ministries and the entities entrusted with the implementation of space strategy/policy and programmes of the country. The second part of this paper focuses on the content and analysis of the national space strategies and indicates the main priorities and trends in the eleven smaller ESA Member States. The priorities are categorised with regards to technology domains, the role of space in the areas of sustainability and the motivators for space investments. In a third and final part, attention is given to the specific needs and interests of the smaller Member States in the frame of European space integration. ESA instruments are tailored to facilitate the needs and interests of the eleven smaller and/or new Member States.

A Sweep-Line Method for State Space Exploration

DEFF Research Database (Denmark)

Christensen, Søren; Kristensen, Lars Michael; Mailund, Thomas

2001-01-01

generation, since these states can never be reached again. This in turn reduces the memory used for state space storage during the task of verification. Examples of progress measures are sequence numbers in communication protocols and time in certain models with time. We illustrate the application...... of the method on a number of Coloured Petri Net models, and give a first evaluation of its practicality by means of an implementation based on the Design/CPN state space tool. Our experiments show significant reductions in both space and time used during state space exploration. The method is not specific...... to Coloured Petri Nets but applicable to a wide range of modelling languages....

Space as a Tool for Analysis: Examining Digital Learning Spaces

Science.gov (United States)

Harrison, Michelle

2018-01-01

Over the past decade we have seen a rise in the adoption and proliferation of social technologies, and along with these a move to build on the capacity to embrace new pedagogies and practices that can open our boundaries for both teaching and learning. How do we determine what we mean by space specifically in online environments and how can we…

Human reinforcement learning subdivides structured action spaces by learning effector-specific values

OpenAIRE

Gershman, Samuel J.; Pesaran, Bijan; Daw, Nathaniel D.

2009-01-01

Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable, due to the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning – such as prediction error signals for action valuation associated with dopamine and the striatum – can cope with this “curse of dimensionality...

Dynamic Influence of Emotional States on Novel Word Learning

Science.gov (United States)

Guo, Jingjing; Zou, Tiantian; Peng, Danling

2018-01-01

Many researchers realize that it's unrealistic to isolate language learning and processing from emotions. However, few studies on language learning have taken emotions into consideration so far, so that the probable influences of emotions on language learning are unclear. The current study thereby aimed to examine the effects of emotional states on novel word learning and their dynamic changes with learning continuing and task varying. Positive, negative or neutral pictures were employed to induce a given emotional state, and then participants learned the novel words through association with line-drawing pictures in four successive learning phases. At the end of each learning phase, participants were instructed to fulfill a semantic category judgment task (in Experiment 1) or a word-picture semantic consistency judgment task (in Experiment 2) to explore the effects of emotional states on different depths of word learning. Converging results demonstrated that negative emotional state led to worse performance compared with neutral condition; however, how positive emotional state affected learning varied with learning task. Specifically, a facilitative role of positive emotional state in semantic category learning was observed but disappeared in word specific meaning learning. Moreover, the emotional modulation on novel word learning was quite dynamic and changeable with learning continuing, and the final attainment of the learned words tended to be similar under different emotional states. The findings suggest that the impact of emotion can be offset when novel words became more and more familiar and a part of existent lexicon. PMID:29695994

Professional Discussion Groups: Informal Learning in a Third Space

Science.gov (United States)

Jordan, Robert A.

2013-01-01

In this ethnographic study, I explored two discussion groups and discovered Third Space elements such as cultural hybridity, counterscript, and sharing of experiences and resources contributed to a safe learning environment existing at the boundaries between participant personal and professional spaces. The groups operated under the auspices of a…

Finite Word-Length Effects in Digital State-Space Filters

Directory of Open Access Journals (Sweden)

B. Psenicka

1999-12-01

Full Text Available The state-space description of digital filters involves except the relationship between input and output signals an additional set of state variables. The state-space structures of digital filters have many positive properties compared with direct canonical structures. The main advantage of digital filter structures developed using state-space technique is a smaller sensitivity to quantization effects by fixed-point implementation. In our presentation, the emphasis is on the analysis of coefficient quantization and on existence of zero-input limit cycles in state-space digital filters. The comparison with direct form II structure is presented.

Space science public outreach at Louisiana State University

Science.gov (United States)

Guzik, T.; Babin, E.; Cooney, W.; Giammanco, J.; Hartman, D.; McNeil, R.; Slovak, M.; Stacy, J.

Over the last seven years the Astronomy / Astrophysics group in the Department of Physics and Astronomy of Louisiana State University has developed an exten- sive Space Science education and public outreach program. This program includes the local park district (the Recreation and Park Commission for the Parish of East Baton Rouge, BREC), the local amateur astronomer group (the Baton Rouge As- tronomical Society, BRAS), the Louisiana Arts and Science Museum (LASM), and Southern University (SU, part of the largest HBCU system in the nation). Our effort has directly led to the development of the Highland Road Park Observatory (HRPO, http://www.bro.lsu.edu/hrpo) that supports student astronomy training at LSU and SU, amateur observations and a public program for adults and children, establishment of a series of teacher professional development workshops in astronomy and physics, and the "Robots for Internet Experiences (ROBIE)" project (http://www.bro.lsu.edu/) where we have several instruments (e.g. HAM radio, radio telescope, optical tele- scopes) that can be controlled over the internet by students and teachers in the class- room along with associated lessons developed by a teacher group. In addition, this year the LASM, will be opening a new planetarium / space theater in downtown Baton Rouge, Louisiana. We are currently working to bring live views of the heavens from the HRPO telescope to audiences attending planetarium shows and will be working closely with planetarium staff to develop shows that highlight LSU astronomy / space science research. During the presentation we will provide some details about our in- dividual projects, the overall structure of our program, establishing community links and some of the lessons we learned along the way. Finally, we would like to acknowl- edge NASA, Louisiana State University, the Louisiana Systemic Initiatives Program and the Louisiana Technology Innovation Fund for their support.

From Commons to Classroom: The Evolution of Learning Spaces in Academic Libraries

Science.gov (United States)

Karasic, Victoria

2016-01-01

Over the past two decades, academic library spaces have evolved to meet the changing teaching and learning needs of diverse campus communities. The Information Commons combines the physical and virtual in an informal library space, whereas the recent Active Learning Classroom creates a more formal setting for collaboration. As scholarship has…

Intentional Process for Intentional Space: Higher Education Classroom Spaces for Learning

Science.gov (United States)

Olsen, Taimi; Guffey, Stanley

2016-01-01

This chapter addresses the confluence of theory and practice in developing and using "flexible" classrooms for student learning. A large classroom building renovation will be described, in terms of how collaboration and co-creation of value led to early success of the renovated space. Co-creation of value for staff and faculty can help…

A Database Approach to Distributed State Space Generation

NARCIS (Netherlands)

Blom, Stefan; Lisser, Bert; van de Pol, Jan Cornelis; Weber, M.

2007-01-01

We study distributed state space generation on a cluster of workstations. It is explained why state space partitioning by a global hash function is problematic when states contain variables from unbounded domains, such as lists or other recursive datatypes. Our solution is to introduce a database

A Database Approach to Distributed State Space Generation

NARCIS (Netherlands)

Blom, Stefan; Lisser, Bert; van de Pol, Jan Cornelis; Weber, M.; Cerna, I.; Haverkort, Boudewijn R.H.M.

2008-01-01

We study distributed state space generation on a cluster of workstations. It is explained why state space partitioning by a global hash function is problematic when states contain variables from unbounded domains, such as lists or other recursive datatypes. Our solution is to introduce a database

Study on state grouping and opportunity evaluation for reinforcement learning methods; Kyoka gakushuho no tame no jotai grouping to opportunity hyoka ni kansuru kenkyu

Energy Technology Data Exchange (ETDEWEB)

Yu, W.; Yokoi, H.; Kakazu, Y. [Hokkaido University, Sapporo (Japan)

1997-08-20

In this paper, we propose the State Grouping scheme for coping with the problem of scaling up the Reinforcement Learning Algorithm to real, large size application. The grouping scheme is based on geographical and trial-error information, and is made up with state generating, state combining, state splitting, state forgetting procedures, with corresponding action selecting module and learning module. Also, we discuss the Labeling Based Evaluation scheme which can evaluate the opportunity of the state-action pair, therefore, use better experience to guide the exploration of the state-space effectively. Incorporating the Labeling Based Evaluation and State Grouping scheme into the Reinforcement Learning Algorithm, we get the approach that can generate organized state space for Reinforcement Learning, and do problem solving as well. We argue that the approach with this kind of ability is necessary for autonomous agent, namely, autonomous agent can not act depending on any pre-defined map, instead, it should search the environment as well as find the optimal problem solution autonomously and simultaneously. By solving the large state-size 3-DOF and 4-link manipulator problem, we show the efficiency of the proposed approach, i.e., the agent can achieve the optimal or sub-optimal path with less memory and less time. 14 refs., 11 figs., 3 tabs.

ASAP: An Extensible Platform for State Space Analysis

DEFF Research Database (Denmark)

Westergaard, Michael; Evangelista, Sami; Kristensen, Lars Michael

2009-01-01

The ASCoVeCo State space Analysis Platform (ASAP) is a tool for performing explicit state space analysis of coloured Petri nets (CPNs) and other formalisms. ASAP supports a wide range of state space reduction techniques and is intended to be easy to extend and to use, making it a suitable tool fo...... for students, researchers, and industrial users that would like to analyze protocols and/or experiment with different algorithms. This paper presents ASAP from these two perspectives....

A Compositional Sweep-Line State Space Exploration Method

DEFF Research Database (Denmark)

Kristensen, Lars Michael; Mailund, Thomas

2002-01-01

State space exploration is a main approach to verification of finite-state systems. The sweep-line method exploits a certain kind of progress present in many systems to reduce peak memory usage during state space exploration. We present a new sweep-line algorithm for a compositional setting where...

Parameter and State Estimator for State Space Models

Directory of Open Access Journals (Sweden)

Ruifeng Ding

2014-01-01

Full Text Available This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.

Towards Ways to Promote Interaction in Digital Learning Spaces

OpenAIRE

Olsson , Hanna ,

2012-01-01

Part 7: Doctoral Student Papers; International audience; Social learning is dependent on social interactions. I am exploring ways to promote interaction in Digital Learning Spaces. As theoretical framework I use the types of interaction between learner, instructor and content. That learners feel isolated and lonely in DLSs is a problem which comes at high cost for social learning. My aim is to promote social interaction by offering the edentity: a system for making participants visible to eac...

Learning Latent Vector Spaces for Product Search

NARCIS (Netherlands)

Van Gysel, C.; de Rijke, M.; Kanoulas, E.

2016-01-01

We introduce a novel latent vector space model that jointly learns the latent representations of words, e-commerce products and a mapping between the two without the need for explicit annotations. The power of the model lies in its ability to directly model the discriminative relation between

The Rhetoric of Multi-Display Learning Spaces: exploratory experiences in visual art disciplines

Directory of Open Access Journals (Sweden)

Brett Bligh

2010-11-01

Full Text Available Multi-Display Learning Spaces (MD-LS comprise technologies to allow the viewing of multiple simultaneous visual materials, modes of learning which encourage critical reflection upon these materials, and spatial configurations which afford interaction between learners and the materials in orchestrated ways. In this paper we provide an argument for the benefits of Multi-Display Learning Spaces in supporting complex, disciplinary reasoning within learning, focussing upon our experiences within postgraduate visual arts education. The importance of considering the affordances of the physical environment within education has been acknowledged by the recent attention given to Learning Spaces, yet within visual art disciplines the perception of visual material within a given space has long been seen as a key methodological consideration with implications for the identity of the discipline itself. We analyse the methodological, technological and spatial affordances of MD-LS to support learning, and discuss comparative viewing as a disciplinary method to structure visual analysis within the space which benefits from the simultaneous display of multiple partitions of visual evidence. We offer an analysis of the role of the teacher in authoring and orchestration and conclude by proposing a more general structure for what we term ‘multiple perspective learning’, in which the presentation of multiple pieces of visual evidence creates the conditions for complex argumentation within Higher Education.

Priorities in national space strategies and governance of the member states of the European Space Agency

Science.gov (United States)

Adriaensen, Maarten; Giannopapa, Christina; Sagath, Daniel; Papastefanou, Anastasia

2015-12-01

The European Space Agency (ESA) has twenty Member States with a variety of strategic priorities and governance structures regarding their space activities. A number of countries engage in space activities exclusively though ESA, while others have also their own national space programme. Some consider ESA as their prime space agency and others have additionally their own national agency with respective programmes. The main objective of this paper is to provide an up-to date overview and a holistic assessment of strategic priorities and the national space governance structures in 20 ESA Member States. This analysis and assessment has been conducted by analysing the Member States public documents, information provided at ESA workshop on this topic and though unstructured interviews. The paper is structured to include two main elements: priorities and trends in national space strategies and space governance in ESA Member States. The first part of this paper focuses on the content and analysis of the national space strategies and indicates the main priorities and trends in Member States. The priorities are categorised with regards to technology domains, the role of space in the areas of sustainability and the motivators that boost engagement in space. These vary from one Member State to another and include with different levels of engagement in technology domains amongst others: science and exploration, navigation, Earth observation, human space flight, launchers, telecommunications, and integrated applications. Member States allocate a different role of space as enabling tool adding to the advancement of sustainability areas including: security, resources, environment and climate change, transport and communication, energy, and knowledge and education. The motivators motivating reasoning which enhances or hinders space engagement also differs. The motivators identified are industrial competitiveness, job creation, technology development and transfer, social benefits

Imbalanced Learning for Functional State Assessment

Science.gov (United States)

Li, Feng; McKenzie, Frederick; Li, Jiang; Zhang, Guangfan; Xu, Roger; Richey, Carl; Schnell, Tom

2011-01-01

This paper presents results of several imbalanced learning techniques applied to operator functional state assessment where the data is highly imbalanced, i.e., some function states (majority classes) have much more training samples than other states (minority classes). Conventional machine learning techniques usually tend to classify all data samples into majority classes and perform poorly for minority classes. In this study, we implemented five imbalanced learning techniques, including random undersampling, random over-sampling, synthetic minority over-sampling technique (SMOTE), borderline-SMOTE and adaptive synthetic sampling (ADASYN) to solve this problem. Experimental results on a benchmark driving lest dataset show thai accuracies for minority classes could be improved dramatically with a cost of slight performance degradations for majority classes,

Storytelling in videogames: a cultural space to learn emocional habilities

Directory of Open Access Journals (Sweden)

Graciela Alicia ESNAOLA HORACEK

2017-07-01

Full Text Available We want to analyze the characteristics of nowadays learning and the construction of the social identity through the storytelling of videogames. We recognize these technologies as an “homogeneous culture discourse” that can only be understood searching the keys that move the world beyond the walls of the school. From this perspective we are interested in the new spaces of power and authority that these technologies introduce in the institutions. To understand these processes we organize the analysis around certain aspects that operate in the interaction between children and this object. These reasons will guide us in the analyses. The problem of our investigation is defined by stating that videogames are involved in the construction of the social identity of the users facilitating archetypes of identification models. These discourses, also, design learning modes that generate a microculture of practices and meanings with a particular logic different from the school culture. As educators, we are interested in understanding how students organize their behaviours and identifications once immersed in this technological culture. Furthermore, we aim at comprehending the communicative strategies developed by users when utilizing this technology. We claim that these cultural behaviours bring about consequences in academic learning. This investigation presents basic aspects of the theoretical background, underpinning the construction of the social identity in the context of the global condition and the hybridization of cultures. We point out the characteristics of the cultural scenario linking the students and the Informational Society. It also studies in depth the characteristics of the digitalization of the narrative space and the ludic area, which offer us the possibility to analyze videogames from a complex perspective. To sum up, our main interest is to ascertain the characteristics of learning within the storytelling and game narrative generated

Coherent states in the fermionic Fock space

International Nuclear Information System (INIS)

Oeckl, Robert

2015-01-01

We construct the coherent states in the sense of Gilmore and Perelomov for the fermionic Fock space. Our treatment is from the outset adapted to the infinite-dimensional case. The fermionic Fock space becomes in this way a reproducing kernel Hilbert space of continuous holomorphic functions. (paper)

The Influence of Hierarchy and Layout Geometry in the Design of Learning Spaces

Science.gov (United States)

Smith, Charlie

2017-01-01

For a number of years, higher education has moved away from didactic teaching toward collaborative and self-directed learning. This paper discusses how the configuration and spatial geometry of learning spaces influences engagement and interaction, with a particular focus on hierarchies between people within the space. Layouts, presented as…

Action Research as a Space for Transforming Learning Cultures

Directory of Open Access Journals (Sweden)

Elżbieta Wołodźko

2015-12-01

Full Text Available The article presents a three-year educational action research project on autonomous and reflective learning. Students and teachers, being actively engaged in many learning practices, were both participating in process(es of developing educational and research community. These interrelated processes framed a dynamic space for constructing and reconstructing the participants’ learning cultures. Thanks to linking educational and research aspects of students’ activity and to interpenetration of practice and reflection, action research generates particular conditions for learning cultures’ transformation, from “traditional” toward “new” ones, based on reflectivity, authenticity and empowerment. The dynamism of learning cultures was connected to various and conscious and reflective types of educational participation, which affected autonomy of studying (in its numerous dimensions and types, being in turn a constitutive element of participants’ learning cultures.

Non-monotonic Pre-fixed Points and Learning

Directory of Open Access Journals (Sweden)

Stefano Berardi

2013-08-01

Full Text Available We consider the problem of finding pre-fixed points of interactive realizers over arbitrary knowledge spaces, obtaining a relative recursive procedure. Knowledge spaces and interactive realizers are an abstract setting to represent learning processes, that can interpret non-constructive proofs. Atomic pieces of information of a knowledge space are stratified into levels, and evaluated into truth values depending on knowledge states. Realizers are then used to define operators that extend a given state by adding and possibly removing atoms: in a learning process states of knowledge change nonmonotonically. Existence of a pre-fixed point of a realizer is equivalent to the termination of the learning process with some state of knowledge which is free of patent contradictions and such that there is nothing to add. In this paper we generalize our previous results in the case of level 2 knowledge spaces and deterministic operators to the case of omega-level knowledge spaces and of non-deterministic operators.

An online learning space facilitating supervision pedagogies in ...

African Journals Online (AJOL)

Quality research supervision leading to timely completion and student satisfaction involves explicit pedagogy and effective communication. This article describes the development within an action research cycle of an online learning space designed to achieve these goals. The research 'spirals' involved interventions in the ...

Learning-based adaptive prescribed performance control of postcapture space robot-target combination without inertia identifications

Science.gov (United States)

Wei, Caisheng; Luo, Jianjun; Dai, Honghua; Bian, Zilin; Yuan, Jianping

2018-05-01

In this paper, a novel learning-based adaptive attitude takeover control method is investigated for the postcapture space robot-target combination with guaranteed prescribed performance in the presence of unknown inertial properties and external disturbance. First, a new static prescribed performance controller is developed to guarantee that all the involved attitude tracking errors are uniformly ultimately bounded by quantitatively characterizing the transient and steady-state performance of the combination. Then, a learning-based supplementary adaptive strategy based on adaptive dynamic programming is introduced to improve the tracking performance of static controller in terms of robustness and adaptiveness only utilizing the input/output data of the combination. Compared with the existing works, the prominent advantage is that the unknown inertial properties are not required to identify in the development of learning-based adaptive control law, which dramatically decreases the complexity and difficulty of the relevant controller design. Moreover, the transient and steady-state performance is guaranteed a priori by designer-specialized performance functions without resorting to repeated regulations of the controller parameters. Finally, the three groups of illustrative examples are employed to verify the effectiveness of the proposed control method.

State-space prediction model for chaotic time series

Science.gov (United States)

Alparslan, A. K.; Sayar, M.; Atilgan, A. R.

1998-08-01

A simple method for predicting the continuation of scalar chaotic time series ahead in time is proposed. The false nearest neighbors technique in connection with the time-delayed embedding is employed so as to reconstruct the state space. A local forecasting model based upon the time evolution of the topological neighboring in the reconstructed phase space is suggested. A moving root-mean-square error is utilized in order to monitor the error along the prediction horizon. The model is tested for the convection amplitude of the Lorenz model. The results indicate that for approximately 100 cycles of the training data, the prediction follows the actual continuation very closely about six cycles. The proposed model, like other state-space forecasting models, captures the long-term behavior of the system due to the use of spatial neighbors in the state space.

State Machine Modeling of the Space Launch System Solid Rocket Boosters

Science.gov (United States)

Harris, Joshua A.; Patterson-Hine, Ann

2013-01-01

The Space Launch System is a Shuttle-derived heavy-lift vehicle currently in development to serve as NASA's premiere launch vehicle for space exploration. The Space Launch System is a multistage rocket with two Solid Rocket Boosters and multiple payloads, including the Multi-Purpose Crew Vehicle. Planned Space Launch System destinations include near-Earth asteroids, the Moon, Mars, and Lagrange points. The Space Launch System is a complex system with many subsystems, requiring considerable systems engineering and integration. To this end, state machine analysis offers a method to support engineering and operational e orts, identify and avert undesirable or potentially hazardous system states, and evaluate system requirements. Finite State Machines model a system as a finite number of states, with transitions between states controlled by state-based and event-based logic. State machines are a useful tool for understanding complex system behaviors and evaluating "what-if" scenarios. This work contributes to a state machine model of the Space Launch System developed at NASA Ames Research Center. The Space Launch System Solid Rocket Booster avionics and ignition subsystems are modeled using MATLAB/Stateflow software. This model is integrated into a larger model of Space Launch System avionics used for verification and validation of Space Launch System operating procedures and design requirements. This includes testing both nominal and o -nominal system states and command sequences.

Learning Extended Finite State Machines

Science.gov (United States)

Cassel, Sofia; Howar, Falk; Jonsson, Bengt; Steffen, Bernhard

2014-01-01

We present an active learning algorithm for inferring extended finite state machines (EFSM)s, combining data flow and control behavior. Key to our learning technique is a novel learning model based on so-called tree queries. The learning algorithm uses the tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic. We describe sufficient conditions for the properties that the symbolic constraints provided by a tree query in general must have to be usable in our learning model. We have evaluated our algorithm in a black-box scenario, where tree queries are realized through (black-box) testing. Our case studies include connection establishment in TCP and a priority queue from the Java Class Library.

Reversibility and the structure of the local state space

International Nuclear Information System (INIS)

Al-Safi, Sabri W; Richens, Jonathan

2015-01-01

The richness of quantum theory’s reversible dynamics is one of its unique operational characteristics, with recent results suggesting deep links between the theory’s reversible dynamics, its local state space and the degree of non-locality it permits. We explore the delicate interplay between these features, demonstrating that reversibility places strong constraints on both the local and global state space. Firstly, we show that all reversible dynamics are trivial (composed of local transformations and permutations of subsytems) in maximally non-local theories whose local state spaces satisfy a dichotomy criterion; this applies to a range of operational models that have previously been studied, such as d-dimensional ‘hyperballs’ and almost all regular polytope systems. By separately deriving a similar result for odd-sided polygons, we show that classical systems are the only regular polytope state spaces whose maximally non-local composites allow for non-trivial reversible dynamics. Secondly, we show that non-trivial reversible dynamics do exist in maximally non-local theories whose state spaces are reducible into two or more smaller spaces. We conjecture that this is a necessary condition for the existence of such dynamics, but that reversible entanglement generation remains impossible even in this scenario. (paper)

Habitability and Human Factors: Lessons Learned in Long Duration Space Flight

Science.gov (United States)

Baggerman, Susan D.; Rando, Cynthia M.; Duvall, Laura E.

2006-01-01

This study documents the investigation of qualitative habitability and human factors feedback provided by scientists, engineers, and crewmembers on lessons learned from the ISS Program. A thorough review and understanding of this data is critical in charting NASA's future path in space exploration. NASA has been involved in ensuring that the needs of crewmembers to live and work safely and effectively in space have been met throughout the ISS Program. Human factors and habitability data has been collected from every U.S. crewmember that has resided on the ISS. The knowledge gained from both the developers and inhabitants of the ISS have provided a significant resource of information for NASA and will be used in future space exploration. The recurring issues have been tracked and documented; the top 5 most critical issues have been identified from this data. The top 5 identified problems were: excessive onsrbit stowage; environment; communication; procedures; and inadequate design of systems and equipment. Lessons learned from these issues will be used to aid in future improvements and developments to the space program. Full analysis of the habitability and human factors data has led to the following recommendations. It is critical for human factors to be involved early in the design of space vehicles and hardware. Human factors requirements need to be readdressed and redefined given the knowledge gained during previous ISS and long-duration space flight programs. These requirements must be integrated into vehicle and hardware technical documentation and consistently enforced. Lastly, space vehicles and hardware must be designed with primary focus on the user/operator to successfully complete missions and maintain a safe working environment. Implementation of these lessons learned will significantly improve NASA's likelihood of success in future space endeavors.

Identified state-space prediction model for aero-optical wavefronts

Science.gov (United States)

Faghihi, Azin; Tesch, Jonathan; Gibson, Steve

2013-07-01

A state-space disturbance model and associated prediction filter for aero-optical wavefronts are described. The model is computed by system identification from a sequence of wavefronts measured in an airborne laboratory. Estimates of the statistics and flow velocity of the wavefront data are shown and can be computed from the matrices in the state-space model without returning to the original data. Numerical results compare velocity values and power spectra computed from the identified state-space model with those computed from the aero-optical data.

The Cube and the Poppy Flower: Participatory Approaches for Designing Technology-Enhanced Learning Spaces

Science.gov (United States)

Casanova, Diogo; Mitchell, Paul

2017-01-01

This paper presents an alternative method for learning space design that is driven by user input. An exploratory study was undertaken at an English university with the aim of redesigning technology-enhanced learning spaces. Two provocative concepts were presented through participatory design workshops during which students and teachers reflected…

Distributed Graph-Based State Space Generation

NARCIS (Netherlands)

Blom, Stefan; Kant, Gijs; Rensink, Arend; De Lara, J.; Varro, D.

LTSMIN provides a framework in which state space generation can be distributed easily over many cores on a single compute node, as well as over multiple compute nodes. The tool works on the basis of a vector representation of the states; the individual cores are assigned the task of computing all

Learning characteristics of a space-time neural network as a tether skiprope observer

Science.gov (United States)

Lea, Robert N.; Villarreal, James A.; Jani, Yashvant; Copeland, Charles

1993-01-01

The Software Technology Laboratory at the Johnson Space Center is testing a Space Time Neural Network (STNN) for observing tether oscillations present during retrieval of a tethered satellite. Proper identification of tether oscillations, known as 'skiprope' motion, is vital to safe retrieval of the tethered satellite. Our studies indicate that STNN has certain learning characteristics that must be understood properly to utilize this type of neural network for the tethered satellite problem. We present our findings on the learning characteristics including a learning rate versus momentum performance table.

Experience the city : analysis of space-time behavior and spatial learning

NARCIS (Netherlands)

Moiseeva, A.

2013-01-01

Learning plays an important role by coding information into individual cognitive maps that can be used to make decisions concerning individual behavior in space. Through traveling people learn about the urban environment and update their knowledge. In this regard, the growing concern in the field of

Space groups for solid state scientists

CERN Document Server

Glazer, Michael; Glazer, Alexander N

2014-01-01

This Second Edition provides solid state scientists, who are not necessarily experts in crystallography, with an understandable and comprehensive guide to the new International Tables for Crystallography. The basic ideas of symmetry, lattices, point groups, and space groups are explained in a clear and detailed manner. Notation is introduced in a step-by-step way so that the reader is supplied with the tools necessary to derive and apply space group information. Of particular interest in this second edition are the discussions of space groups application to such timely topics as high-te

Quantization of Space-like States in Lorentz-Violating Theories

Science.gov (United States)

Colladay, Don

2018-01-01

Lorentz violation frequently induces modified dispersion relations that can yield space-like states that impede the standard quantization procedures. In certain cases, an extended Hamiltonian formalism can be used to define observer-covariant normalization factors for field expansions and phase space integrals. These factors extend the theory to include non-concordant frames in which there are negative-energy states. This formalism provides a rigorous way to quantize certain theories containing space-like states and allows for the consistent computation of Cherenkov radiation rates in arbitrary frames and avoids singular expressions.

On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis.

Science.gov (United States)

Yamazaki, Keisuke

2012-07-01

Parametric models for sequential data, such as hidden Markov models, stochastic context-free grammars, and linear dynamical systems, are widely used in time-series analysis and structural data analysis. Computation of the likelihood function is one of primary considerations in many learning methods. Iterative calculation of the likelihood such as the model selection is still time-consuming though there are effective algorithms based on dynamic programming. The present paper studies parameter learning in a simplified feature space to reduce the computational cost. Simplifying data is a common technique seen in feature selection and dimension reduction though an oversimplified space causes adverse learning results. Therefore, we mathematically investigate a condition of the feature map to have an asymptotically equivalent convergence point of estimated parameters, referred to as the vicarious map. As a demonstration to find vicarious maps, we consider the feature space, which limits the length of data, and derive a necessary length for parameter learning in hidden Markov models. Copyright © 2012 Elsevier Ltd. All rights reserved.

Designing new collaborative learning spaces in clinical environments: experiences from a children's hospital in Australia.

Science.gov (United States)

Bines, Julie E; Jamieson, Peter

2013-09-01

Hospitals are complex places that provide a rich learning environment for students, staff, patients and their families, professional groups and the community. The "new" Royal Children's Hospital opened in late 2011. Its mission is focused on improving health and well-being of children and adolescents through leadership in healthcare, research and education. Addressing the need to create "responsive learning environments" aligned with the shift to student-centred pedagogy, two distinct learning environments were developed within the new Royal Children's Hospital; (i) a dedicated education precinct providing a suite of physical environments to promote a more active, collaborative and social learning experience for education and training programs conducted on the Royal Children's Hospital campus and (ii) a suite of learning spaces embedded within clinical areas so that learning becomes an integral part of the daily activities of this busy Hospital environment. The aim of this article is to present the overarching educational principles that lead the design of these learning spaces and describe the opportunities and obstacles encountered in the development of collaborative learning spaces within a large hospital development.

Learning Landscapes: Playing the Way to Learning and Engagement in Public Spaces

Directory of Open Access Journals (Sweden)

Brenna Hassinger-Das

2018-05-01

Full Text Available Children from under-resourced communities regularly enter formal schooling lagging behind their peers. These deficits in areas such as language development, reading readiness, and even in the kind of spatial skills that predict later mathematical knowledge, may persist throughout their lifespan. To address such gaps, policymakers have focused largely on schooling as the great equalizer. Yet, children only spend 20% of their waking hours in school. How can developmental scientists and educators address this “other 80%” for the benefit of children’s development? One answer is the Learning Landscapes initiative, which involves crafting carefully planned play experiences that focus on learning outcomes, particularly for children and families from under-resourced communities. Playful learning, a broad pedagogical approach featuring child-directed play methods, provides a unique way to foster learning and engagement organically within the built environment. Learning Landscapes already incorporates several well-documented projects. The Ultimate Block Party brought over 50,000 people to Central Park to engage in playful learning activities. Supermarkets became hotspots for caregiver-child interaction by simply adding prompts for caregiver-child interaction through signage in everyday “trapped” experiences. Urban Thinkscape transformed a bus stop and adjacent lot into a hub for playful learning while families were waiting for public transportation. Finally, Parkopolis is a life-size human board game that fosters STEM and reasoning skills in public spaces. This paper reflects on data from these projects while reflecting on lessons learned and future directions.

The Present and Future State of Blended Learning in Workplace Learning Settings in the United States

Science.gov (United States)

Bonk, Curtis J.; Kim, Kyong-Jee; Oh, Eun Jung; Teng, Ya-Ting; Son, Su Jin

2007-01-01

This paper reports survey findings related to the present and future state of blended learning in workplace learning settings across the U.S. Surveyed in this study are 118 practitioners in corporate training or elearning in various workplace settings. The findings reveal interesting perceptions by respondents regarding the benefits of and…

Construction and Evaluation of an Integrated Formal/Informal Learning Environment for Foreign Language Learning across Real and Virtual Spaces

Science.gov (United States)

Waragai, Ikumi; Ohta, Tatsuya; Kurabayashi, Shuichi; Kiyoki, Yasushi; Sato, Yukiko; Brückner, Stefan

2017-01-01

This paper presents the prototype of a foreign language learning space, based on the construction of an integrated formal/informal learning environment. Before the background of the continued innovation of information technology that places conventional learning styles and educational methods into new contexts based on new value-standards,…

System resiliency quantification using non-state-space and state-space analytic models

International Nuclear Information System (INIS)

Ghosh, Rahul; Kim, DongSeong; Trivedi, Kishor S.

2013-01-01

Resiliency is becoming an important service attribute for large scale distributed systems and networks. Key problems in resiliency quantification are lack of consensus on the definition of resiliency and systematic approach to quantify system resiliency. In general, resiliency is defined as the ability of (system/person/organization) to recover/defy/resist from any shock, insult, or disturbance [1]. Many researchers interpret resiliency as a synonym for fault-tolerance and reliability/availability. However, effect of failure/repair on systems is already covered by reliability/availability measures and that of on individual jobs is well covered under the umbrella of performability [2] and task completion time analysis [3]. We use Laprie [4] and Simoncini [5]'s definition in which resiliency is the persistence of service delivery that can justifiably be trusted, when facing changes. The changes we are referring to here are beyond the envelope of system configurations already considered during system design, that is, beyond fault tolerance. In this paper, we outline a general approach for system resiliency quantification. Using examples of non-state-space and state-space stochastic models, we analytically–numerically quantify the resiliency of system performance, reliability, availability and performability measures w.r.t. structural and parametric changes

Active learning in the space engineering education at Technical University of Madrid

Science.gov (United States)

Rodríguez, Jacobo; Laverón-Simavilla, Ana; Lapuerta, Victoria; Ezquerro Navarro, Jose Miguel; Cordero-Gracia, Marta

This work describes the innovative activities performed in the field of space education at the Technical University of Madrid (UPM), in collaboration with the center engaged by the European Space Agency (ESA) in Spain to support the operations for scientific experiments on board the International Space Station (E-USOC). These activities have been integrated along the last academic year of the Aerospatiale Engineering degree. A laboratory has been created, where the students have to validate and integrate the subsystems of a microsatellite by using demonstrator satellites. With the acquired skills, the students participate in a training process centered on Project Based Learning, where the students work in groups to perform the conceptual design of a space mission, being each student responsible for the design of a subsystem of the satellite and another one responsible of the mission design. In parallel, the students perform a training using a ground station, installed at the E-USOC building, which allow them to learn how to communicate with satellites, how to download telemetry and how to process the data. This also allows students to learn how the E-USOC works. Two surveys have been conducted to evaluate the impact of these techniques in the student engineering skills and to know the degree of satisfaction of students with respect to the use of these learning methodologies.

Conscious Thought is for facilitating the work places as learning spaces

NARCIS (Netherlands)

van Dellen, Theo

2015-01-01

Conscious Thought is for facilitating the work places as learning spaces Theo van Dellen In the workplace learning and development of work identity can be assumed in at least three ways. First, the processes are managed by the organizational context, which promotes a particular model of workers as

Cultivating social learning spaces at an urban Johannesburg university student residence

OpenAIRE

Agherdien, Najma

2015-01-01

Ph.D. (Education) This case study investigated the conceptualisation and implementation of social learning spaces (SLS) in a University of Johannesburg student residence. The literature base I drew on included ideas, concepts and constructs associated with learning communities [where the terms ‘SLS’ and ‘learning communities’ (LCs) are often used interchangeably], Wenger’s communities of practice, the First Year Experience (FYE), university student residence life and transformation in high...

States in the Hilbert space formulation and in the phase space formulation of quantum mechanics

International Nuclear Information System (INIS)

Tosiek, J.; Brzykcy, P.

2013-01-01

We consider the problem of testing whether a given matrix in the Hilbert space formulation of quantum mechanics or a function considered in the phase space formulation of quantum theory represents a quantum state. We propose several practical criteria for recognising states in these two versions of quantum physics. After minor modifications, they can be applied to check positivity of any operators acting in a Hilbert space or positivity of any functions from an algebra with a ∗-product of Weyl type. -- Highlights: ► Methods of testing whether a given matrix represents a quantum state. ► The Stratonovich–Weyl correspondence on an arbitrary symplectic manifold. ► Criteria for checking whether a function on a symplectic space is a Wigner function

Commentary: Latina Literacies in "Convivencia": Communal Spaces of Teaching and Learning

Science.gov (United States)

Villenas, Sofia A.

2005-01-01

Inspired by Delgado-Gaitan's work with Latina mothers' stories of transformation, this commentary engages scholarship on the communal "mujer-" or womanist-oriented spaces of teaching and learning. The author explores themes of "convivencia" (communalism) centered on faith, spirituality, and humor central to creating compassionate spaces of…

How to upload a physical quantum state into correlation space

International Nuclear Information System (INIS)

Morimae, Tomoyuki

2011-01-01

In the framework of the computational tensor network [Phys. Rev. Lett. 98, 220503 (2007)], the quantum computation is performed in a virtual linear space called the correlation space. It was recently shown [Phys. Rev. Lett. 103, 050503 (2009)] that a state in a correlation space can be downloaded to the real physical space. In this paper, conversely, we study how to upload a state from a real physical space to the correlation space. After showing the impossibility of cloning a state between a real physical space and the correlation space, we propose a simple teleportation-like method of uploading. This method also enables the Gottesman-Chuang gate teleportation trick and entanglement swapping in the virtual-real hybrid setting. Furthermore, compared with the inverse of the downloading method by Cai et al. [Phys. Rev. Lett. 103, 050503 (2009)], which also works to upload, the proposed uploading method has several advantages.

The Role of Space in Learning: Spatio-Educational Experiences of Female Students within Emirati Higher Education

OpenAIRE

Zaidan, Gergana

2015-01-01

This interdisciplinary research examines the intersectional relationship between\\ud the domains of space, gender and education. It aims, first, to understand the\\ud spatio-educational experience of Emirati female learners; and second, to make\\ud it possible to enhance their learning experience by exploring the role of space in\\ud learning in a single gender context. This thesis addresses the lack of literature\\ud on women’s spatiality and space in learning, specifically in relation to Arab\\ud...

State-space approach for evaluating the soil-plant-atmosphere system

International Nuclear Information System (INIS)

Timm, L.C.; Reichardt, K.; Cassaro, F.A.M.; Tominaga, T.T.; Bacchi, O.O.S.; Oliveira, J.C.M.; Dourado-Neto, D.

2004-01-01

Using as examples one sugarcane and one forage oat experiment, both carried out in the State of Sao Paulo, Brazil, this chapter presents recent state-space approaches used to evaluate the relation between soil and plant properties. A contrast is made between classical statistics methodologies that do not take into account the sampling position coordinates, and the more recently used methodologies which include the position coordinates, and allow a better interpretation of the field-sampled data. Classical concepts are first introduced, followed by spatially referenced methodologies like the autocorrelation function, the cross correlation function, and the state-space approach. Two variations of the state-space approach are given: one emphasizes the evolution of the state system while the other based on the bayesian formulation emphasizes the evolution of the estimated observations. It is concluded that these state-space analyses using dynamic regression models improve data analyses and are therefore recommended for analyzing time and space data series related to the performance of a given soil-plant-atmosphere system. (author)

The coherent state on SUq(2) homogeneous space

International Nuclear Information System (INIS)

Aizawa, N; Chakrabarti, R

2009-01-01

The generalized coherent states for quantum groups introduced by Jurco and StovIcek are studied for the simplest example SU q (2) in full detail. It is shown that the normalized SU q (2) coherent states enjoy the property of completeness, and allow a resolution of the unity. This feature is expected to play a key role in the application of these coherent states in physical models. The homogeneous space of SU q (2), i.e. the q-sphere of Podles, is reproduced in complex coordinates by using the coherent states. Differential calculus in the complex form on the homogeneous space is developed. The high spin limit of the SU q (2) coherent states is also discussed.

Facial Expression Recognition of Various Internal States via Manifold Learning

Institute of Scientific and Technical Information of China (English)

Young-Suk Shin

2009-01-01

Emotions are becoming increasingly important in human-centered interaction architectures. Recognition of facial expressions, which are central to human-computer interactions, seems natural and desirable. However, facial expressions include mixed emotions, continuous rather than discrete, which vary from moment to moment. This paper represents a novel method of recognizing facial expressions of various internal states via manifold learning, to achieve the aim of humancentered interaction studies. A critical review of widely used emotion models is described, then, facial expression features of various internal states via the locally linear embedding (LLE) are extracted. The recognition of facial expressions is created with the pleasure-displeasure and arousal-sleep dimensions in a two-dimensional model of emotion. The recognition result of various internal state expressions that mapped to the embedding space via the LLE algorithm can effectively represent the structural nature of the two-dimensional model of emotion. Therefore our research has established that the relationship between facial expressions of various internal states can be elaborated in the two-dimensional model of emotion, via the locally linear embedding algorithm.

Students' Imaginings of Spaces of Learning in Outdoor and Environmental Education

Science.gov (United States)

Preston, Lou

2014-01-01

In this article, I interrogate students' stories about the spaces and places in a tertiary Outdoor and Environmental Education course that support and shape their environmental ethics. Drawing on a longitudinal qualitative study, I explore the ways in which particular sites of learning (outdoor, practical learning) are privileged and how…

The study of selective property of college student’s learning space

Science.gov (United States)

Nagai, Mizuki; Matsumoto, Yuji; Naka, Ryusuke

2018-05-01

These days, college students study not only at places designed for learning such as libraries in colleges, but also cafes in downtown while the number of facilities for learning run by colleges is increasing. Then I have researched facilities in college and those in downtown to find selective properties of college students’ learning space. First, I found by questionnaire survey that students chose “3rd place” such as cafes and fast food shops, second to their houses and libraries in college. Next, I found “psychological factor” were also affected their choice. Furthermore, they studied different subjects at different places. In experiments, I researched how effectively they studied each subject at every place. The results show that I find that places you like and places where learning efficiency is good are different. They learned the least effective at “3d place” regardless of what they learned. The result of how long they kept high-level intellectual activity at each place shows that they could work on the study with more motivation at their favorite place and 3rd place. On the other hand, at the 2nd place, they could study rather effectively, but could not keep concentration and motivation for a long time. In this way, college students have 2 patterns of choosing learning space.

Learning strategies of public health nursing students: conquering operational space.

Science.gov (United States)

Hjälmhult, Esther

2009-11-01

To develop understanding of how public health nursing students learn in clinical practice and explore the main concern for the students and how they acted to resolve this main concern. How professionals perform their work directly affects individuals, but knowledge is lacking in understanding how learning is connected to clinical practice in public health nursing and in other professions. Grounded theory. Grounded theory was used in gathering and analysing data from 55 interviews and 108 weekly reports. The participants were 21 registered nurses who were public health nursing students. The grounded theory of conquering operational space explains how the students work to resolve their main concern. A social process with three identified phases, positioning, involving and integrating, was generated from analysing the data. Their subcategories and dimensions are related to the student role, relations with a supervisor, student activity and the consequences of each phase. Public health nursing students had to work towards gaining independence, often working against 'the system' and managing the tension by taking a risk. Many of them lost, changed and expanded their professional identity during practical placements. Public health nursing students' learning processes in clinical training are complex and dynamic and the theory of 'Conquering operational space' can assist supervisors in further developing their role in relation to guiding students in practice. Relationships are one key to opening or closing access to situations of learning and directly affect the students' achievement of mastering. The findings are pertinent to supervisors and educators as they prepare students for practice. Good relationships are elementary and supervisors can support students in conquering the field by letting students obtain operational space and gain independence. This may create a dialectical process that drives learning forward.

Complexity in Simplicity: Flexible Agent-based State Space Exploration

DEFF Research Database (Denmark)

Rasmussen, Jacob Illum; Larsen, Kim Guldstrand

2007-01-01

In this paper, we describe a new flexible framework for state space exploration based on cooperating agents. The idea is to let various agents with different search patterns explore the state space individually and communicate information about fruitful subpaths of the search tree to each other...

Active and Passive Technology Integration: A Novel Approach for Managing Technology's Influence on Learning Experiences in Context-Aware Learning Spaces

Science.gov (United States)

Laine, Teemu H.; Nygren, Eeva

2016-01-01

Technology integration is the process of overcoming different barriers that hinder efficient utilisation of learning technologies. The authors divide technology integration into two components based on technology's role in the integration process. In active integration, the technology integrates learning resources into a learning space, making it…

Leveraging Faculty Reflective Practice to Understand Active Learning Spaces: Flashbacks and Re-Captures

Science.gov (United States)

Ramsay, Crystal M.; Guo, Xiuyan; Pursel, Barton K.

2017-01-01

Although learning spaces research is not new, research approaches that target the specific teaching and learning experiences of faculty and students who occupy active learning classrooms (ALCs) is nascent. We report on two novels data collection approaches: Flashbacks and Re-Captures. Both leverage faculty reflective practice and provide windows…

Making Faces - State-Space Models Applied to Multi-Modal Signal Processing

DEFF Research Database (Denmark)

Lehn-Schiøler, Tue

2005-01-01

The two main focus areas of this thesis are State-Space Models and multi modal signal processing. The general State-Space Model is investigated and an addition to the class of sequential sampling methods is proposed. This new algorithm is denoted as the Parzen Particle Filter. Furthermore...... optimizer can be applied to speed up convergence. The linear version of the State-Space Model, the Kalman Filter, is applied to multi modal signal processing. It is demonstrated how a State-Space Model can be used to map from speech to lip movements. Besides the State-Space Model and the multi modal...... application an information theoretic vector quantizer is also proposed. Based on interactions between particles, it is shown how a quantizing scheme based on an analytic cost function can be derived....

Developments in the Multilingual and Multicultural Learning Space

DEFF Research Database (Denmark)

Lauridsen, Karen M.; Cozart, Stacey Marie; Kling, Joyce

Uni project (2012-15) recommends that higher education institutions (HEI) provide ‘the necessary professional development and teacher training programmes that will allow HE teachers to appropriately develop (…) their professional and pedagogical knowledge, skills and competences and thereby empower them...... to ensure the quality of their teaching – and their students’ learning – in the multilingual and multicultural learning space’ (www.intluni.eu; Carroll 2015; Leask 2015). For many universities and other HEIs around the world, the multilingual and multicultural classroom is the new – or no longer quite so...... platform with resources targeted at EDs responsible for advancing faculty development in this area. In this session, the presenters will report on the first outcomes of EQUiiP. Participants will then be invited to interact and explore best practices in the multilingual and multicultural learning space...

Uncommons: Transforming Dusty Reading Rooms into Artefactual "Third Space" Library Learning Labs

Science.gov (United States)

Schadl, Suzanne Michele; Nelson, Molly; Valencia, Kristen S.

2015-01-01

This article describes the implementation of two inexpensive social learning library laboratories for advanced students in Latin American and Chicana/o studies. Drawing on philosophical literature from these interdisciplinary areas and ethnic studies, these cases present a "third space" option for library learning called…

IntlUni - The Challenges of the Multilingual and Multicultural Learning Space in the International University

DEFF Research Database (Denmark)

Lauridsen, Karen M.

learning space, and to develop recommendations for how higher education institutions may implement and ensure the sustainability of quality teaching and learning in this space. IntlUni is a three-year Erasmus Academic Network (2012-2015) and has received financial support from the European Commission......IntlUni: The challenges of the multilingual and multicultural learning space in the international university The past decade has witnessed an unprecedented increase in the internationalisation of higher education. This means that more people in higher education than ever before are teaching...... and learning through the medium of a language other than their own first languages. What are the implication of this for lecturers and students? And what are the implications for this for the quality of European higher education programmes? Taking it for granted that the internationalisation of higher...

Volumes of conditioned bipartite state spaces

International Nuclear Information System (INIS)

Milz, Simon; Strunz, Walter T

2015-01-01

We analyze the metric properties of conditioned quantum state spaces M η (n×m) . These spaces are the convex sets of nm×nm density matrices that, when partially traced over m degrees of freedom, respectively yield the given n × n density matrix η. For the case n = 2, the volume of M η (2×m) equipped with the Hilbert–Schmidt measure can be conjectured to be a simple polynomial of the radius of η in the Bloch-ball. Remarkably, for m=2,3 we find numerically that the probability p sep (2×m) (η) to find a separable state in M η (2×m) is independent of η (except for η pure). For m>3, the same holds for p PosPart (2×m) (η), the probability to find a state with a positive partial transpose in M η (2×m) . These results are proven analytically for the case of the family of 4 × 4 X-states, and thoroughly numerically investigated for the general case. The important implications of these findings for the clarification of open problems in quantum theory are pointed out and discussed. (paper)

Prototypes and matrix relevance learning in complex fourier space

NARCIS (Netherlands)

Straat, M.; Kaden, M.; Gay, M.; Villmann, T.; Lampe, Alexander; Seiffert, U.; Biehl, M.; Melchert, F.

2017-01-01

In this contribution, we consider the classification of time-series and similar functional data which can be represented in complex Fourier coefficient space. We apply versions of Learning Vector Quantization (LVQ) which are suitable for complex-valued data, based on the so-called Wirtinger

Public policies for managing urban growth and protecting open space: policy instruments and lessons learned in the United States

Science.gov (United States)

David N. Bengston; Jennifer O. Fletcher

2003-01-01

The public sector in the United States has responded to growing concern about the social and environmental costs of sprawling development patterns by creating a wide range of policy instruments designed to manage urban growth and protect open space. These techniques have been implemented at the local, regional, state and, to a limited extent, national levels. This...

Projective limits of state spaces II. Quantum formalism

Science.gov (United States)

Lanéry, Suzanne; Thiemann, Thomas

2017-06-01

In this series of papers, we investigate the projective framework initiated by Kijowski (1977) and Okołów (2009, 2014, 2013), which describes the states of a quantum theory as projective families of density matrices. A short reading guide to the series can be found in Lanéry (2016). After discussing the formalism at the classical level in a first paper (Lanéry, 2017), the present second paper is devoted to the quantum theory. In particular, we inspect in detail how such quantum projective state spaces relate to inductive limit Hilbert spaces and to infinite tensor product constructions (Lanéry, 2016, subsection 3.1) [1]. Regarding the quantization of classical projective structures into quantum ones, we extend the results by Okołów (2013), that were set up in the context of linear configuration spaces, to configuration spaces given by simply-connected Lie groups, and to holomorphic quantization of complex phase spaces (Lanéry, 2016, subsection 2.2) [1].

Transforming Conceptual Space into a Creative Learning Place: Crossing a Threshold

Science.gov (United States)

Moffat, Kirstine; McKim, Anne

2016-01-01

This article describes, discusses and reflects on a teaching and learning experiment in a first year BA course. Students were led out of the lecture room to a different space, the New Place Theatre. While this move out of the usual teaching space was appropriate for the text being studied, William Shakespeare's "The Tempest", the…

Projective limits of state spaces IV. Fractal label sets

Science.gov (United States)

Lanéry, Suzanne; Thiemann, Thomas

2018-01-01

Instead of formulating the state space of a quantum field theory over one big Hilbert space, it has been proposed by Kijowski (1977) to represent quantum states as projective families of density matrices over a collection of smaller, simpler Hilbert spaces (see Lanéry (2016) [1] for a concise introduction to this formalism). One can thus bypass the need to select a vacuum state for the theory, and still be provided with an explicit and constructive description of the quantum state space, at least as long as the label set indexing the projective structure is countable. Because uncountable label sets are much less practical in this context, we develop in the present article a general procedure to trim an originally uncountable label set down to countable cardinality. In particular, we investigate how to perform this tightening of the label set in a way that preserves both the physical content of the algebra of observables and its symmetries. This work is notably motivated by applications to the holonomy-flux algebra underlying Loop Quantum Gravity. Building on earlier work by Okołów (2013), a projective state space was introduced for this algebra in Lanéry and Thiemann (2016). However, the non-trivial structure of the holonomy-flux algebra prevents the construction of satisfactory semi-classical states (Lanéry and Thiemann, 2017). Implementing the general procedure just mentioned in the case of a one-dimensional version of this algebra, we show how a discrete subalgebra can be extracted without destroying universality nor diffeomorphism invariance. On this subalgebra, quantum states can then be constructed which are more regular than was possible on the original algebra. In particular, this allows the design of semi-classical states whose semi-classicality is enforced step by step, starting from collective, macroscopic degrees of freedom and going down progressively toward smaller and smaller scales.

Transformative learning spaces

DEFF Research Database (Denmark)

Maslo, Elina

Despite rapid development of learning theory in general and language learning theory in particular in the last years, we still cannot provide an unequivocal answer on the question “why do individuals who presumably possess similar cognitive capacities for second language learning achieve such var......, Leo (2010). The ecology of language learning: Practice to theory, theory to practice. Procedia – Social and Behavioral Sciences. Elsevier......., social, personal, cultural, and historical world they live in (van Lier, 2000). People can learn when they discover possibilities for learning, which appear in this complex world – so called affordances (Gibson, 1979). This happens in the interaction between people and their environment on the basis...... to the different ways of interaction of cognitive, affective and social factors by different individuals. Learning stories, where multilingual individuals are telling about their subjective experiences in language learning in particular and learning in general, are constructed by using a special developed...

State-Space Modelling in Marine Science

DEFF Research Database (Denmark)

Albertsen, Christoffer Moesgaard

State-space models provide a natural framework for analysing time series that cannot be observed without error. This is the case for fisheries stock assessments and movement data from marine animals. In fisheries stock assessments, the aim is to estimate the stock size; however, the only data...... available is the number of fish removed from the population and samples on a small fraction of the population. In marine animal movement, accurate position systems such as GPS cannot be used. Instead, inaccurate alternative must be used yielding observations with large errors. Both assessment and individual...... animal movement models are important for management and conservation of marine animals. Consequently, models should be developed to be operational in a management context while adequately evaluating uncertainties in the models. This thesis develops state-space models using the Laplace approximation...

The unitary space of particle internal states

International Nuclear Information System (INIS)

Perjes, Z.

1978-09-01

A relativistic theory of particle internal properties has been developed. Suppressing space-time information, internal wave functions and -observables are constructed in a 3-complex-dimensional space. The quantum numbers of a spinning point particle in this unitary space correspond with those of a low-mass hadron. Unitary space physics is linked with space-time notions via the Penrose theory of twistors, where new flavors may be represented by many-twistor systems. It is shown here that a four-twistor particle fits into the unitary space picture as a system of two points with equal masses and oppositely pointing unitary spins. Quantum states fall into the ISU(3) irreducible representations discovered by Sparling and the author. Full details of the computation involving SU(3) recoupling techniques are given. (author)

Investigating the Impact of Schools' Open Space on Learning and Educational Achievement of Elementary Students

Directory of Open Access Journals (Sweden)

Abdolreza Gilavand

2016-04-01

Full Text Available Background It is obvious that most of informal learnings of social skills and constructive plays occur in school yards and play-fields where children spend much of their non-official time of teaching. This study aimed to investigate the impact of schools' open space on learning and educational achievement of elementary students in Ahvaz, Southwest of Iran. Materials and Methods At a cross-sectional study, 210 students were selected randomly as sample of study. Data collection tools included Hermance’s achievement motivation questionnaire and researcher-constructed questionnaire (observation checklist to examine the physical parameters of learning schools' open space and interviews with students. Data of study were analyzed in SPSS- 21 software. Results Results of this study showed that schools' open space has a significant impact on learning and academic achievement of elementary school students in Ahvaz- Iran (P

Lack of spacing effects during piano learning

OpenAIRE

Wiseheart, Melody; D?Souza, Annalise A.; Chae, Jacey

2017-01-01

Spacing effects during retention of verbal information are easily obtained, and the effect size is large. Relatively little evidence exists on whether motor skill retention benefits from distributed practice, with even less evidence on complex motor skills. We taught a 17-note musical sequence on a piano to individuals without prior formal training. There were five lags between learning episodes: 0-, 1-, 5-, 10-, and 15-min. After a 5-min retention interval, participants' performance was meas...

Warping similarity space in category learning by human subjects: the role of task difficulty

OpenAIRE

Pevtzow, Rachel; Harnad, Stevan

1997-01-01

In innate Categorical Perception (CP) (e.g., colour perception), similarity space is "warped," with regions of increased within-category similarity (compression) and regions of reduced between-category similarity (separation) enh ancing the category boundaries and making categorisation reliable and all-or-none rather than graded. We show that category learning can likewise warp similarity space, resolving uncertainty near category boundaries. Two Hard and two Easy texture learning tasks were ...

Innovative Learning Environments and New Materialism: A Conjunctural Analysis of Pedagogic Spaces

Science.gov (United States)

Charteris, Jennifer; Smardon, Dianne; Nelson, Emily

2017-01-01

An Organisation for Economic Cooperation and Development research priority, innovative learning environments (ILEs) have been translated into policy and practice in 25 countries around the world. In Aotearoa/New Zealand, learning spaces are being reconceptualised in relation to this policy work by school leaders who are confronted by an impetus to…

State space in BRST-quantization and Kugo-Ojima quartets

International Nuclear Information System (INIS)

Rybkin, G.N.

1989-01-01

The structure of the state space in the BRST-quantization is considered and the connection between different approaches to the proof of the positive definiteness of the metric on the physical state space is established. The correspondence between different expressions for the BRST-charge, quadratic in fields, is obtained. The relation between different representations of the BRST-algebra is found. 22 refs

Multivariate time series with linear state space structure

CERN Document Server

Gómez, Víctor

2016-01-01

This book presents a comprehensive study of multivariate time series with linear state space structure. The emphasis is put on both the clarity of the theoretical concepts and on efficient algorithms for implementing the theory. In particular, it investigates the relationship between VARMA and state space models, including canonical forms. It also highlights the relationship between Wiener-Kolmogorov and Kalman filtering both with an infinite and a finite sample. The strength of the book also lies in the numerous algorithms included for state space models that take advantage of the recursive nature of the models. Many of these algorithms can be made robust, fast, reliable and efficient. The book is accompanied by a MATLAB package called SSMMATLAB and a webpage presenting implemented algorithms with many examples and case studies. Though it lays a solid theoretical foundation, the book also focuses on practical application, and includes exercises in each chapter. It is intended for researchers and students wor...

State-Space Realization of the Wave-Radiation Force within FAST: Preprint

Energy Technology Data Exchange (ETDEWEB)

Duarte, T.; Sarmento, A.; Alves, M.; Jonkman, J.

2013-06-01

Several methods have been proposed in the literature to find a state-space model for the wave-radiation forces. In this paper, four methods were compared, two in the frequency domain and two in the time domain. The frequency-response function and the impulse response of the resulting state-space models were compared against the ones derived by the numerical code WAMIT. The implementation of the state-space module within the FAST offshore wind turbine computer-aided engineering (CAE) tool was verified, comparing the results against the previously implemented numerical convolution method. The results agreed between the two methods, with a significant reduction in required computational time when using the state-space module.

Approximate Bayesian Computation by Subset Simulation using hierarchical state-space models

Science.gov (United States)

Vakilzadeh, Majid K.; Huang, Yong; Beck, James L.; Abrahamsson, Thomas

2017-02-01

A new multi-level Markov Chain Monte Carlo algorithm for Approximate Bayesian Computation, ABC-SubSim, has recently appeared that exploits the Subset Simulation method for efficient rare-event simulation. ABC-SubSim adaptively creates a nested decreasing sequence of data-approximating regions in the output space that correspond to increasingly closer approximations of the observed output vector in this output space. At each level, multiple samples of the model parameter vector are generated by a component-wise Metropolis algorithm so that the predicted output corresponding to each parameter value falls in the current data-approximating region. Theoretically, if continued to the limit, the sequence of data-approximating regions would converge on to the observed output vector and the approximate posterior distributions, which are conditional on the data-approximation region, would become exact, but this is not practically feasible. In this paper we study the performance of the ABC-SubSim algorithm for Bayesian updating of the parameters of dynamical systems using a general hierarchical state-space model. We note that the ABC methodology gives an approximate posterior distribution that actually corresponds to an exact posterior where a uniformly distributed combined measurement and modeling error is added. We also note that ABC algorithms have a problem with learning the uncertain error variances in a stochastic state-space model and so we treat them as nuisance parameters and analytically integrate them out of the posterior distribution. In addition, the statistical efficiency of the original ABC-SubSim algorithm is improved by developing a novel strategy to regulate the proposal variance for the component-wise Metropolis algorithm at each level. We demonstrate that Self-regulated ABC-SubSim is well suited for Bayesian system identification by first applying it successfully to model updating of a two degree-of-freedom linear structure for three cases: globally

Online Distributed Learning Over Networks in RKH Spaces Using Random Fourier Features

Science.gov (United States)

Bouboulis, Pantelis; Chouvardas, Symeon; Theodoridis, Sergios

2018-04-01

We present a novel diffusion scheme for online kernel-based learning over networks. So far, a major drawback of any online learning algorithm, operating in a reproducing kernel Hilbert space (RKHS), is the need for updating a growing number of parameters as time iterations evolve. Besides complexity, this leads to an increased need of communication resources, in a distributed setting. In contrast, the proposed method approximates the solution as a fixed-size vector (of larger dimension than the input space) using Random Fourier Features. This paves the way to use standard linear combine-then-adapt techniques. To the best of our knowledge, this is the first time that a complete protocol for distributed online learning in RKHS is presented. Conditions for asymptotic convergence and boundness of the networkwise regret are also provided. The simulated tests illustrate the performance of the proposed scheme.

Advanced Solid State Lighting for AES Deep Space Hab

Data.gov (United States)

National Aeronautics and Space Administration — The advanced Solid State Lighting (SSL) assemblies augmented 2nd generation modules under development for the Advanced Exploration Systems Deep Space Habitat in...

Learning in Discussion Forums: An Analysis of Knowledge Construction in a Gaming Affinity Space

Science.gov (United States)

Davis, Don; Marone, Vittorio

2016-01-01

In the learning sciences and game studies communities, there has been an increasing interest in the potential of game-related "paratexts" and "surrounds" in supporting learning, such as online discussion forums and gaming affinity spaces. While there have been studies identifying how learning occurs in such communities, little…

Designing learning spaces for interprofessional education in the anatomical sciences.

Science.gov (United States)

Cleveland, Benjamin; Kvan, Thomas

2015-01-01

This article explores connections between interprofessional education (IPE) models and the design of learning spaces for undergraduate and graduate education in the anatomical sciences and other professional preparation. The authors argue that for IPE models to be successful and sustained they must be embodied in the environment in which interprofessional learning occurs. To elaborate these arguments, two exemplar tertiary education facilities are discussed: the Charles Perkins Centre at the University of Sydney for science education and research, and Victoria University's Interprofessional Clinic in Wyndham for undergraduate IPE in health care. Backed by well-conceived curriculum and pedagogical models, the architectures of these facilities embody the educational visions, methods, and practices they were designed to support. Subsequently, the article discusses the spatial implications of curriculum and pedagogical change in the teaching of the anatomical sciences and explores how architecture might further the development of IPE models in the field. In conclusion, it is argued that learning spaces should be designed and developed (socially) with the expressed intention of supporting collaborative IPE models in health education settings, including those in the anatomical sciences. © 2015 American Association of Anatomists.

A dynamical topology for the space of states

International Nuclear Information System (INIS)

Dittrich, J.

1979-01-01

A new topology is introduced for the space of states of a physical system. This topology is given by dynamics, every state has a neighbourhood consisting of states connected by the time evolution only. With respect to the new topology, all conservation laws can be treated as topological laws. (author)

VirtualSpace: A vision of a machine-learned virtual space environment

Science.gov (United States)

Bortnik, J.; Sarno-Smith, L. K.; Chu, X.; Li, W.; Ma, Q.; Angelopoulos, V.; Thorne, R. M.

2017-12-01

Space borne instrumentation tends to come and go. A typical instrument will go through a phase of design and construction, be deployed on a spacecraft for several years while it collects data, and then be decommissioned and fade into obscurity. The data collected from that instrument will typically receive much attention while it is being collected, perhaps in the form of event studies, conjunctions with other instruments, or a few statistical surveys, but once the instrument or spacecraft is decommissioned, the data will be archived and receive progressively less attention with every passing year. This is the fate of all historical data, and will be the fate of data being collected by instruments even at the present time. But what if those instruments could come alive, and all be simultaneously present at any and every point in time and space? Imagine the scientific insights, and societal gains that could be achieved with a grand (virtual) heliophysical observatory that consists of every current and historical mission ever deployed? We propose that this is not just fantasy but is imminently doable with the data currently available, with the present computational resources, and with currently available algorithms. This project revitalizes existing data resources and lays the groundwork for incorporating data from every future mission to expand the scope and refine the resolution of the virtual observatory. We call this project VirtualSpace: a machine-learned virtual space environment.

Quantum learning of coherent states

Energy Technology Data Exchange (ETDEWEB)

Sentis, Gael [Universitat Autonoma de Barcelona, Fisica Teorica: Informacio i Fenomens Quantics, Barcelona (Spain); Guta, Madalin; Adesso, Gerardo [University of Nottingham, School of Mathematical Sciences, Nottingham (United Kingdom)

2015-12-15

We develop a quantum learning scheme for binary discrimination of coherent states of light. This is a problem of technological relevance for the reading of information stored in a digital memory. In our setting, a coherent light source is used to illuminate a memory cell and retrieve its encoded bit by determining the quantum state of the reflected signal. We consider a situation where the amplitude of the states produced by the source is not fully known, but instead this information is encoded in a large training set comprising many copies of the same coherent state. We show that an optimal global measurement, performed jointly over the signal and the training set, provides higher successful identification rates than any learning strategy based on first estimating the unknown amplitude by means of Gaussian measurements on the training set, followed by an adaptive discrimination procedure on the signal. By considering a simplified variant of the problem, we argue that this is the case even for non-Gaussian estimation measurements. Our results show that, even in absence of entanglement, collective quantum measurements yield an enhancement in the readout of classical information, which is particularly relevant in the operating regime of low-energy signals. (orig.)

Quantum learning of coherent states

International Nuclear Information System (INIS)

Sentis, Gael; Guta, Madalin; Adesso, Gerardo

2015-01-01

We develop a quantum learning scheme for binary discrimination of coherent states of light. This is a problem of technological relevance for the reading of information stored in a digital memory. In our setting, a coherent light source is used to illuminate a memory cell and retrieve its encoded bit by determining the quantum state of the reflected signal. We consider a situation where the amplitude of the states produced by the source is not fully known, but instead this information is encoded in a large training set comprising many copies of the same coherent state. We show that an optimal global measurement, performed jointly over the signal and the training set, provides higher successful identification rates than any learning strategy based on first estimating the unknown amplitude by means of Gaussian measurements on the training set, followed by an adaptive discrimination procedure on the signal. By considering a simplified variant of the problem, we argue that this is the case even for non-Gaussian estimation measurements. Our results show that, even in absence of entanglement, collective quantum measurements yield an enhancement in the readout of classical information, which is particularly relevant in the operating regime of low-energy signals. (orig.)

Space Sciences Education and Outreach Project of Moscow State University

Science.gov (United States)

Krasotkin, S.

2006-11-01

sergekras@mail.ru The space sciences education and outreach project was initiated at Moscow State University in order to incorporate modern space research into the curriculum popularize the basics of space physics, and enhance public interest in space exploration. On 20 January 2005 the first Russian University Satellite “Universitetskiy-Tatyana” was launched into circular polar orbit (inclination 83 deg., altitude 940-980 km). The onboard scientific complex “Tatyana“, as well as the mission control and information receiving centre, was designed and developed at Moscow State University. The scientific programme of the mission includes measurements of space radiation in different energy channels and Earth UV luminosity and lightning. The current education programme consists of basic multimedia lectures “Life of the Earth in the Solar Atmosphere” and computerized practice exercises “Space Practice” (based on the quasi-real-time data obtained from “Universitetskiy-Tatyana” satellite and other Internet resources). A multimedia lectures LIFE OF EARTH IN THE SOLAR ATMOSPHERE containing the basic information and demonstrations of heliophysics (including Sun structure and solar activity, heliosphere and geophysics, solar-terrestrial connections and solar influence on the Earth’s life) was created for upper high-school and junior university students. For the upper-university students there a dozen special computerized hands-on exercises were created based on the experimental quasi-real-time data obtained from our satellites. Students specializing in space physics from a few Russian universities are involved in scientific work. Educational materials focus on upper high school, middle university and special level for space physics students. Moscow State University is now extending its space science education programme by creating multimedia lectures on remote sensing, space factors and materials study, satellite design and development, etc. The space

State space modeling of Memristor-based Wien oscillator

KAUST Repository

Talukdar, Abdul Hafiz Ibne; Radwan, Ahmed G.; Salama, Khaled N.

2011-01-01

State space modeling of Memristor based Wien 'A' oscillator has been demonstrated for the first time considering nonlinear ion drift in Memristor. Time dependant oscillating resistance of Memristor is reported in both state space solution and SPICE simulation which plausibly provide the basis of realizing parametric oscillation by Memristor based Wien oscillator. In addition to this part Memristor is shown to stabilize the final oscillation amplitude by means of its nonlinear dynamic resistance which hints for eliminating diode in the feedback network of conventional Wien oscillator. © 2011 IEEE.

State space modeling of Memristor-based Wien oscillator

KAUST Repository

Talukdar, Abdul Hafiz Ibne

2011-12-01

State space modeling of Memristor based Wien \\'A\\' oscillator has been demonstrated for the first time considering nonlinear ion drift in Memristor. Time dependant oscillating resistance of Memristor is reported in both state space solution and SPICE simulation which plausibly provide the basis of realizing parametric oscillation by Memristor based Wien oscillator. In addition to this part Memristor is shown to stabilize the final oscillation amplitude by means of its nonlinear dynamic resistance which hints for eliminating diode in the feedback network of conventional Wien oscillator. © 2011 IEEE.

Coherent and squeezed states in phase space

International Nuclear Information System (INIS)

Jannussis, A.; Bartzis, V.; Vlahos, E.

1990-01-01

In the present paper, the coherent and the squeezed states in phase space have been studied. From the wave functions of the coherent and the squeezed state, their corresponding Wigner distribution functions are calculated. Especially the calculation of the corresponding Wigner functions for the above states permits the determination of the mean values of position and momentum and thus the Heisenberg uncertainty relation. In fact, from the related results, it is concluded that the uncertainty relation of the coherent and associated squeezed states is the same

Machinery running state identification based on discriminant semi-supervised local tangent space alignment for feature fusion and extraction

International Nuclear Information System (INIS)

Su, Zuqiang; Xiao, Hong; Zhang, Yi; Tang, Baoping; Jiang, Yonghua

2017-01-01

Extraction of sensitive features is a challenging but key task in data-driven machinery running state identification. Aimed at solving this problem, a method for machinery running state identification that applies discriminant semi-supervised local tangent space alignment (DSS-LTSA) for feature fusion and extraction is proposed. Firstly, in order to extract more distinct features, the vibration signals are decomposed by wavelet packet decomposition WPD, and a mixed-domain feature set consisted of statistical features, autoregressive (AR) model coefficients, instantaneous amplitude Shannon entropy and WPD energy spectrum is extracted to comprehensively characterize the properties of machinery running state(s). Then, the mixed-dimension feature set is inputted into DSS-LTSA for feature fusion and extraction to eliminate redundant information and interference noise. The proposed DSS-LTSA can extract intrinsic structure information of both labeled and unlabeled state samples, and as a result the over-fitting problem of supervised manifold learning and blindness problem of unsupervised manifold learning are overcome. Simultaneously, class discrimination information is integrated within the dimension reduction process in a semi-supervised manner to improve sensitivity of the extracted fusion features. Lastly, the extracted fusion features are inputted into a pattern recognition algorithm to achieve the running state identification. The effectiveness of the proposed method is verified by a running state identification case in a gearbox, and the results confirm the improved accuracy of the running state identification. (paper)

United States Changing Demographics - English/Spanish Space Education

Science.gov (United States)

Leon, R.

2002-01-01

Accordingly the United States Census Bureau, the ethnic group adding the largest number of people to the national population is the Hispanic exceeding 12 percent of the population and growing by almost 60 percent between 1990 and 2000. The status of the nation's educational system with respect to Hispanic students is perhaps one of the most influential issues facing the largest economy of the world. The low income, lack of language skills, highest drop-out rate in the nation, are some of the reasons why Hispanics are less likely to receive a university degree than any other ethical group. In short, the government requires to implement compensatory programs and bilingual education to ensure global leadership. Because of ongoing immigration, Spanish persists longer among Hispanics than it did among other immigrant groups. Spanish is the fourth most spoken language in the world after Mandarin, Hindustani and English. Although not all U.S. Hispanics speak Spanish, almost all U.S. Spanish speakers are Hispanics. This paper is intended to outline the challenging implementation of a bilingual education project affiliated to NASA Johnson Space Center encouraging greater academic success of Hispanics in engineering, math and science. The prospective project covers the overall role of space activities in the development of science and technology, socioeconomic issues and international cooperation. An existent JSC project is the starting stage to keep on developing an interactive video teleconference and web-media technology and produce stimulating learning products in English and Spanish for students and teachers across the nation and around the world.

Steering the dynamics within reduced space through quantum learning control

International Nuclear Information System (INIS)

Kim, Young Sik

2003-01-01

In quantum dynamics of many-body systems, to identify the Hamiltonian becomes more difficult very rapidly as the number of degrees of freedom increases. In order to simplify the dynamics and to deduce dynamically relevant Hamiltonian information, it is desirable to control the dynamics to lie within a reduced space. With a judicious choice for the cost functional, the closed loop optimal control experiments can be manipulated efficiently to steer the dynamics to lie within a subspace of the system eigenstates without requiring any prior detailed knowledge about the system Hamiltonian. The procedure is simulated for optimally controlled population transfer experiments in the system of two degrees of freedom. To show the feasibility of steering the dynamics to lie in a specified subspace, the learning algorithms guiding the dynamics are presented along with frequency filtering. The results demonstrate that the optimal control fields derive the system to the desired target state through the desired subspace

Developments in the Multilingual and Multicultural Learning Space

DEFF Research Database (Denmark)

Lauridsen, Karen M.; Cozart, Stacey Marie; Kling, Joyce

Uni project (2012-15) recommends that higher education institutions (HEI) provide ‘the necessary professional development and teacher training programmes that will allow HE teachers to appropriately develop (…) their professional and pedagogical knowledge, skills and competences and thereby empower them...... platform with resources targeted at EDs responsible for advancing faculty development in this area. In this session, the presenters will report on the first outcomes of EQUiiP. Participants will then be invited to interact and explore best practices in the multilingual and multicultural learning space......Internationalization of higher education, and the often accompanying shift from what previously were relatively homogenous national student populations, to more blended, culturally and linguistically heterogeneous group of students, impacts teaching and learning in a number of ways. The Intl...

Formulating state space models in R with focus on longitudinal regression models

DEFF Research Database (Denmark)

Dethlefsen, Claus; Lundbye-Christensen, Søren

  We provide a language for formulating a range of state space models. The described methodology is implemented in the R -package sspir available from cran.r-project.org . A state space model is specified similarly to a generalized linear model in R , by marking the time-varying terms in the form......  We provide a language for formulating a range of state space models. The described methodology is implemented in the R -package sspir available from cran.r-project.org . A state space model is specified similarly to a generalized linear model in R , by marking the time-varying terms...

Manifold learning to interpret JET high-dimensional operational space

International Nuclear Information System (INIS)

Cannas, B; Fanni, A; Pau, A; Sias, G; Murari, A

2013-01-01

In this paper, the problem of visualization and exploration of JET high-dimensional operational space is considered. The data come from plasma discharges selected from JET campaigns from C15 (year 2005) up to C27 (year 2009). The aim is to learn the possible manifold structure embedded in the data and to create some representations of the plasma parameters on low-dimensional maps, which are understandable and which preserve the essential properties owned by the original data. A crucial issue for the design of such mappings is the quality of the dataset. This paper reports the details of the criteria used to properly select suitable signals downloaded from JET databases in order to obtain a dataset of reliable observations. Moreover, a statistical analysis is performed to recognize the presence of outliers. Finally data reduction, based on clustering methods, is performed to select a limited and representative number of samples for the operational space mapping. The high-dimensional operational space of JET is mapped using a widely used manifold learning method, the self-organizing maps. The results are compared with other data visualization methods. The obtained maps can be used to identify characteristic regions of the plasma scenario, allowing to discriminate between regions with high risk of disruption and those with low risk of disruption. (paper)

Modeling volatility using state space models.

Science.gov (United States)

Timmer, J; Weigend, A S

1997-08-01

In time series problems, noise can be divided into two categories: dynamic noise which drives the process, and observational noise which is added in the measurement process, but does not influence future values of the system. In this framework, we show that empirical volatilities (the squared relative returns of prices) exhibit a significant amount of observational noise. To model and predict their time evolution adequately, we estimate state space models that explicitly include observational noise. We obtain relaxation times for shocks in the logarithm of volatility ranging from three weeks (for foreign exchange) to three to five months (for stock indices). In most cases, a two-dimensional hidden state is required to yield residuals that are consistent with white noise. We compare these results with ordinary autoregressive models (without a hidden state) and find that autoregressive models underestimate the relaxation times by about two orders of magnitude since they do not distinguish between observational and dynamic noise. This new interpretation of the dynamics of volatility in terms of relaxators in a state space model carries over to stochastic volatility models and to GARCH models, and is useful for several problems in finance, including risk management and the pricing of derivative securities. Data sets used: Olsen & Associates high frequency DEM/USD foreign exchange rates (8 years). Nikkei 225 index (40 years). Dow Jones Industrial Average (25 years).

State Space Reduction for Model Checking Agent Programs

NARCIS (Netherlands)

S.-S.T.Q. Jongmans (Sung-Shik); K.V. Hindriks; M.B. van Riemsdijk; L. Dennis; O. Boissier; R.H. Bordini (Rafael)

2012-01-01

htmlabstractState space reduction techniques have been developed to increase the efficiency of model checking in the context of imperative programming languages. Unfortunately, these techniques cannot straightforwardly be applied to agents: the nature of states in the two programming paradigms

University-Preschool Partnership and Workplace-Based Learning: A Collaborative "Third Space" or No Space at All?

Science.gov (United States)

Jónsdóttir, Arna H.

2015-01-01

The article examines the aims of the workplace-based learning of prospective preschool teachers in Iceland and associated cooperative practices between the University of Iceland and preschools. A "third space" of collaboration between these two sites is considered necessary if the education of preschool student teachers is to be…

A History of Space Toxicology Mishaps: Lessons Learned and Risk Management

Science.gov (United States)

James, John T.

2009-01-01

After several decades of human spaceflight, the community of space-faring nations has accumulated a diverse and sometimes harrowing history of toxicological events that have plagued human space endeavors almost from the very beginning. Lessons have been learned in ground-based test beds and others were discovered the hard way - when human lives were at stake in space. From such lessons one can build a risk-management framework for toxicological events to minimize the probability of a harmful exposure, while recognizing that we cannot foresee all events. Space toxicologists have learned that relatively harmless compounds can be converted by air revitalization systems into compounds that cause serious harm to the crew. Our toxic risk management strategy now includes an assessment of the fate of any compound that might be released into the atmosphere. Propellants are highly toxic compounds, yet we have not always been able to thoroughly isolate the crew from exposure to these toxicants. Leakage of fluids from systems has resulted in hazardous conditions at times, and the behavior of such compounds inside a spacecraft has taught us how to manage potentially harmful escapes should they occur. Potential combustion events are an ever-present threat to the wellbeing of the crew. Such events have been sufficiently common that we have learned that one cannot judge the health threat of a given fire by the magnitude of the event. Management of such risks demands monitoring of combustion products. In the category of unpredictable toxic events, if one assumes that fires are predictable, we can place experience with toxic microbial metabolites, upsets during repair operations, and discharges from filters that have accumulated a substantial load of pollutants in their absorption beds. Management of such events requires a broad-spectrum, real-time analytical capability to discern the identity and concentrations of pollutants if they enter the atmosphere. Adverse events are an

Automatic Design of a Maglev Controller in State Space

Science.gov (United States)

1991-12-01

Design of a Maglev Controller in State Space Feng Zhao Richard Thornton Abstract We describe the automatic synthesis of a global nonlinear controller for...the global switching points of the controller is presented. The synthesized control system can stabilize the maglev vehicle with large initial displace...NUMBERS Automation Desing of a Maglev Controller in State Space N00014-89-J-3202 MIP-9001651 6. AUTHOR(S) Feng Zhao and Richard Thornton 7. PERFORMING

Transformation of Socioeconomic Space: The Role of the State

Directory of Open Access Journals (Sweden)

Alexander Nikolaevich Shvetsov

2015-03-01

Full Text Available Modern Russia is traditionally characterized by a special and strong public participation in solving problems of spatial development. Thus, the state has following diverse roles: 1 the creator of the modern space configuration; 2 the mastermind and main driving force of modern spatial transformations; 3 the regulator and investor of these processes; 4 the main sponsor and beneficiary of space transformation; and, finally, the hostage of its own dominance in the processes of spatial transformation. However, stereotypes are being gradually overcome and public policy in the area of spatial transformations focuses not only on «public projects» but also on self-development of regions, combined with the interests of big business which plays an increasing role in the transformation of socioeconomic space. The article reveals the meaning and content of the problem of systemic interaction between the state and space concerning the modernization of the country. The author explores the range of fundamental research and applied issues resulting from the contradictory combination of traditional (historical stereotypes and the latest Russian circumstances. These issues determine the background, nature and consequences of state impacts on socio-economic space, as well as the composition, content and validity of the used instruments

Information Theoretic Characterization of Physical Theories with Projective State Space

Science.gov (United States)

Zaopo, Marco

2015-08-01

Probabilistic theories are a natural framework to investigate the foundations of quantum theory and possible alternative or deeper theories. In a generic probabilistic theory, states of a physical system are represented as vectors of outcomes probabilities and state spaces are convex cones. In this picture the physics of a given theory is related to the geometric shape of the cone of states. In quantum theory, for instance, the shape of the cone of states corresponds to a projective space over complex numbers. In this paper we investigate geometric constraints on the state space of a generic theory imposed by the following information theoretic requirements: every non completely mixed state of a system is perfectly distinguishable from some other state in a single shot measurement; information capacity of physical systems is conserved under making mixtures of states. These assumptions guarantee that a generic physical system satisfies a natural principle asserting that the more a state of the system is mixed the less information can be stored in the system using that state as logical value. We show that all theories satisfying the above assumptions are such that the shape of their cones of states is that of a projective space over a generic field of numbers. Remarkably, these theories constitute generalizations of quantum theory where superposition principle holds with coefficients pertaining to a generic field of numbers in place of complex numbers. If the field of numbers is trivial and contains only one element we obtain classical theory. This result tells that superposition principle is quite common among probabilistic theories while its absence gives evidence of either classical theory or an implausible theory.

Construction of spaces of kinematic quantum states for field theories via projective techniques

International Nuclear Information System (INIS)

Okołów, Andrzej

2013-01-01

We present a method of constructing a space of quantum states for a field theory: given phase space of a theory, we define a family of physical systems each possessing a finite number of degrees of freedom, next we define a space of quantum states for each finite system, finally using projective techniques we organize all these spaces into a space of quantum states which corresponds to the original phase space. This construction is kinematic in this sense that it bases merely on the structure of the phase space of a theory and does not take into account possible constraints on the space. The construction is a generalization of a construction by Kijowski—the latter one is limited to theories of linear phase spaces, while the former one is free of this limitation. The method presented in this paper enables to construct a space of quantum states for the teleparallel equivalent of general relativity. (paper)

What Drives Student Engagement: Is It Learning Space, Instructor Behavior, or Teaching Philosophy?

Science.gov (United States)

Sawers, Kimberly M.; Wicks, David; Mvududu, Nyaradzo; Seeley, Lane; Copeland, Raedene

2016-01-01

This study investigates how instructor teaching philosophy (traditional vs. constructivist) and type of learning space (traditional vs. active) influence instructor perceptions of student engagement. In a quasi-experimental study, we found that instructors perceived that students were more engaged in the active learning classroom (ALC) than in the…

Problem of short-term forecasting of near-earth space state

International Nuclear Information System (INIS)

Eselevich, V.G.; Ashmanets, V.I.; Startsev, S.A.

1996-01-01

The paper deals with actual and practically important problem of investigation and forecasting of state condition during magnetic storms. The available methods of forecasting of near-earth space state are analyzed. Forecasting of magnetic storms was conducted for control of space vehicles. Quasi-determinate method of magnetic storm forecasting is suggested. 13 refs., 3 figs

Learning Without Boundaries: A NASA - National Guard Bureau Distance Learning Partnership

Science.gov (United States)

Anderson, Susan H.; Chilelli, Christopher J.; Picard, Stephan

2003-01-01

With a variety of high-quality live interactive educational programs originating at the Johnson Space Center in Houston, Texas and other space and research centers, the US space agency NASA (National Aeronautics and Space Administration) has a proud track record of connecting with students throughout the world and stimulating their creativity and collaborative skills by teaching them underlying scientific and technological underpinnings of space exploration. However, NASA desires to expand its outreach capability for this type of interactive instruction. In early 2002, NASA and the National Guard Bureau -- using the Guard's nationwide system of state-ofthe-art classrooms and high bandwidth network -- began a collaboration to extend the reach of NASA content and educational programs to more of America's young people. Already, hundreds of elementary, middle, and high school students have visited Guard e-Learning facilities and participated in interactive NASA learning events. Topics have included experimental flight, satellite imagery-interpretation, and Mars exploration. Through this partnership, NASA and the National Guard are enabling local school systems throughout the United States (and, increasingly, the world) to use the excitement of space flight to encourage their students to become passionate about the possibility of one day serving as scientists, mathematicians, technologists, and engineers. At the 54th International Astronautical Conference MAJ Stephan Picard, the guiding visionary behind the Guard's partnership with NASA, and Chris Chilelli, an educator and senior instructional designer at NASA, will share with attendees background on NASA's educational products and the National Guard's distributed learning network; will discuss the unique opportunity this partnership already has provided students and teachers throughout the United States; will offer insights into the formation by government entities of e-Learning partnerships with one another; and will

Repurposing With Purpose: Creating a Collaborative Learning Space to Support Institutional Interprofessional Initiatives.

Science.gov (United States)

Young, Lauren M; Machado, Connie K; Clark, Susan B

2015-01-01

When the University of Mississippi Medical Center embraced a didactic shift to patient-centered, interprofessional education of its medical, dental, nursing, pharmacy, and allied health students, the Rowland Medical Library repurposed space to support the cause and created a collaborative learning space designated for campus-wide utility.

Deformed two-photon squeezed states in noncommutative space

International Nuclear Information System (INIS)

Zhang Jianzu

2004-01-01

Recent studies on nonperturbation aspects of noncommutative quantum mechanics explored a new type of boson commutation relations at the deformed level, described by deformed annihilation-creation operators in noncommutative space. This correlated boson commutator correlates different degrees of freedom, and shows an essential influence on dynamics. This Letter devotes to the development of formalism of deformed two-photon squeezed states in noncommutative space. General representations of deformed annihilation-creation operators and the consistency condition for the electromagnetic wave with a single mode of frequency in noncommunicative space are obtained. Two-photon squeezed states are studied. One finds that variances of the dimensionless Hermitian quadratures of the annihilation operator in one degree of freedom include variances in the other degree of freedom. Such correlations show the new feature of spatial noncommutativity and allow a deeper understanding of the correlated boson commutator

Previous experience in manned space flight: A survey of human factors lessons learned

Science.gov (United States)

Chandlee, George O.; Woolford, Barbara

1993-01-01

Previous experience in manned space flight programs can be used to compile a data base of human factors lessons learned for the purpose of developing aids in the future design of inhabited spacecraft. The objectives are to gather information available from relevant sources, to develop a taxonomy of human factors data, and to produce a data base that can be used in the future for those people involved in the design of manned spacecraft operations. A study is currently underway at the Johnson Space Center with the objective of compiling, classifying, and summarizing relevant human factors data bearing on the lessons learned from previous manned space flights. The research reported defines sources of data, methods for collection, and proposes a classification for human factors data that may be a model for other human factors disciplines.

Space Mechanisms Lessons Learned and Accelerated Testing Studies

Science.gov (United States)

Fusaro, Robert L.

1997-01-01

A number of mechanism (mechanical moving component) failures and anomalies have recently occurred on satellites. In addition, more demanding operating and life requirements have caused mechanism failures or anomalies to occur even before some satellites were launched (e.g., during the qualification testing of GOES-NEXT, CERES, and the Space Station Freedom Beta Joint Gimbal). For these reasons, it is imperative to determine which mechanisms worked in the past and which have failed so that the best selection of mechanically moving components can be made for future satellites. It is also important to know where the problem areas are so that timely decisions can be made on the initiation of research to develop future needed technology. To chronicle the life and performance characteristics of mechanisms operating in a space environment, a Space Mechanisms Lessons Learned Study was conducted. The work was conducted by the NASA Lewis Research Center and by Mechanical Technologies Inc. (MTI) under contract NAS3-27086. The expectation of the study was to capture and retrieve information relating to the life and performance of mechanisms operating in the space environment to determine what components had operated successfully and what components had produced anomalies.

Investigating the Impact of Lighting Educational Spaces on Learning and Academic Achievement of Elementary Students

Directory of Open Access Journals (Sweden)

Abdolreza Gilavand

2016-05-01

Full Text Available Background In modern education, physical space is considered as a dynamic factor in students' educational activities. This study was conducted to investigating the impact of lighting educational spaces on learning and academic achievement of elementary students. Materials and Methods At a cross-sectional study (2015-2016, a total of 210 students were selected randomly as sample of study. Cluster sampling was done by appropriate allocation and questionnaires were randomly divided among students. Data collection tools included Hermance’s achievement motivation questionnaire and researcher-constructed questionnaire (observation checklist to examine the physical parameters of learning environment lighting and interviews with students. Data of study were analyzed using SPSS- 21 software. Results Results of this study showed that lighting educational spaces has a significant impact on learning and academic achievement of elementary school students in Ahvaz, Iran (P

A Sweep-Line Method for State Space Exploration

DEFF Research Database (Denmark)

Christensen, Søren; Kristensen, Lars Michael; Mailund, Thomas

2001-01-01

generation, since these states can never be reached again. This in turn reduces the memory used for state space storage during the task of verification. Examples of progress measures are sequence numbers in communication protocols and time in certain models with time. We illustrate the application...

Uncanny spaces for higher education: teaching and learning in virtual worlds

Directory of Open Access Journals (Sweden)

Siân Bayne

2008-12-01

Full Text Available This paper brings together the theory of the uncanny as it emerges in cultural theory, with an understanding of the uncanniness and troublesomeness seen to be inherent in certain understandings of teaching and learning in higher education. Drawing on research into students' experiences of learning in virtual worlds, it explores the sense in which teaching in such spaces materialises and extends the positive aspects of uncertainty, strangeness, disquietude and troublesomeness in online higher education.

A Danish Perspective on Problem Based Learning in Space Education

DEFF Research Database (Denmark)

Bhanderi, Dan D. V.; Bisgaard, Morten; Alminde, Lars

2006-01-01

This paper describes the goals of the Student Satellite Program at Aalborg University (AAU), and the means for implementing it, namely a concept called Problem Based Learning, which is the cornerstone in the education at AAU. AAU has within the last decade chosen to focus strongly on education...... in space technology, not because the country lacks aerospace engineers, but because space projects require the students to think about systems rather than individual modules, while providing problems that are technically challenging for the students to solve. This combination makes the graduates very...

Parallel symbolic state-space exploration is difficult, but what is the alternative?

Directory of Open Access Journals (Sweden)

Gianfranco Ciardo

2009-12-01

Full Text Available State-space exploration is an essential step in many modeling and analysis problems. Its goal is to find the states reachable from the initial state of a discrete-state model described. The state space can used to answer important questions, e.g., "Is there a dead state?" and "Can N become negative?", or as a starting point for sophisticated investigations expressed in temporal logic. Unfortunately, the state space is often so large that ordinary explicit data structures and sequential algorithms cannot cope, prompting the exploration of (1 parallel approaches using multiple processors, from simple workstation networks to shared-memory supercomputers, to satisfy large memory and runtime requirements and (2 symbolic approaches using decision diagrams to encode the large structured sets and relations manipulated during state-space generation. Both approaches have merits and limitations. Parallel explicit state-space generation is challenging, but almost linear speedup can be achieved; however, the analysis is ultimately limited by the memory and processors available. Symbolic methods are a heuristic that can efficiently encode many, but not all, functions over a structured and exponentially large domain; here the pitfalls are subtler: their performance varies widely depending on the class of decision diagram chosen, the state variable order, and obscure algorithmic parameters. As symbolic approaches are often much more efficient than explicit ones for many practical models, we argue for the need to parallelize symbolic state-space generation algorithms, so that we can realize the advantage of both approaches. This is a challenging endeavor, as the most efficient symbolic algorithm, Saturation, is inherently sequential. We conclude by discussing challenges, efforts, and promising directions toward this goal.

An Integrated Approach to Parameter Learning in Infinite-Dimensional Space

Energy Technology Data Exchange (ETDEWEB)

Boyd, Zachary M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Wendelberger, Joanne Roth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-09-14

The availability of sophisticated modern physics codes has greatly extended the ability of domain scientists to understand the processes underlying their observations of complicated processes, but it has also introduced the curse of dimensionality via the many user-set parameters available to tune. Many of these parameters are naturally expressed as functional data, such as initial temperature distributions, equations of state, and controls. Thus, when attempting to find parameters that match observed data, being able to navigate parameter-space becomes highly non-trivial, especially considering that accurate simulations can be expensive both in terms of time and money. Existing solutions include batch-parallel simulations, high-dimensional, derivative-free optimization, and expert guessing, all of which make some contribution to solving the problem but do not completely resolve the issue. In this work, we explore the possibility of coupling together all three of the techniques just described by designing user-guided, batch-parallel optimization schemes. Our motivating example is a neutron diffusion partial differential equation where the time-varying multiplication factor serves as the unknown control parameter to be learned. We find that a simple, batch-parallelizable, random-walk scheme is able to make some progress on the problem but does not by itself produce satisfactory results. After reducing the dimensionality of the problem using functional principal component analysis (fPCA), we are able to track the progress of the solver in a visually simple way as well as viewing the associated principle components. This allows a human to make reasonable guesses about which points in the state space the random walker should try next. Thus, by combining the random walker's ability to find descent directions with the human's understanding of the underlying physics, it is possible to use expensive simulations more efficiently and more quickly arrive at the

Adaptive importance sampling of random walks on continuous state spaces

International Nuclear Information System (INIS)

Baggerly, K.; Cox, D.; Picard, R.

1998-01-01

The authors consider adaptive importance sampling for a random walk with scoring in a general state space. Conditions under which exponential convergence occurs to the zero-variance solution are reviewed. These results generalize previous work for finite, discrete state spaces in Kollman (1993) and in Kollman, Baggerly, Cox, and Picard (1996). This paper is intended for nonstatisticians and includes considerable explanatory material

Learning to Estimate Dynamical State with Probabilistic Population Codes.

Directory of Open Access Journals (Sweden)

Joseph G Makin

2015-11-01

Full Text Available Tracking moving objects, including one's own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is known that this process of state estimation can be learned purely from the statistics of noisy observations. When the dynamics are simply linear with additive Gaussian noise, the optimal solution is the well known Kalman filter (KF, the parameters of which can be learned via latent-variable density estimation (the EM algorithm. The brain does not, however, directly manipulate matrices and vectors, but instead appears to represent probability distributions with the firing rates of population of neurons, "probabilistic population codes." We show that a recurrent neural network-a modified form of an exponential family harmonium (EFH-that takes a linear probabilistic population code as input can learn, without supervision, to estimate the state of a linear dynamical system. After observing a series of population responses (spike counts to the position of a moving object, the network learns to represent the velocity of the object and forms nearly optimal predictions about the position at the next time-step. This result builds on our previous work showing that a similar network can learn to perform multisensory integration and coordinate transformations for static stimuli. The receptive fields of the trained network also make qualitative predictions about the developing and learning brain: tuning gradually emerges for higher-order dynamical states not explicitly present in the inputs, appearing as delayed tuning for the lower-order states.

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

Science.gov (United States)

Ferreria, Paulo Victor R.; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy M.; Bilen, Sven G.; Reinhart, Richard C.; Mortensen, Dale J.

2017-01-01

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

Relativistic resonances as non-orthogonal states in Hilbert space

CERN Document Server

Blum, W

2003-01-01

We analyze the energy-momentum properties of relativistic short-lived particles with the result that they are characterized by two 4-vectors: in addition to the familiar energy-momentum vector (timelike) there is an energy-momentum 'spread vector' (spacelike). The wave functions in space and time for unstable particles are constructed. For the relativistic properties of unstable states we refer to Wigner's method of Poincare group representations that are induced by representations of the space-time translation and rotation groups. If stable particles, unstable particles and resonances are treated as elementary objects that are not fundamentally different one has to take into account that they will not generally be orthogonal to each other in their state space. The scalar product between a stable and an unstable state with otherwise identical properties is calculated in a particular Lorentz frame. The spin of an unstable particle is not infinitely sharp but has a 'spin spread' giving rise to 'spin neighbors'....

On the state space of the dipole ghost

International Nuclear Information System (INIS)

Binegar, B.

1984-01-01

A particular representation of SO(4, 2) is identified with the state space of the free dipole ghost. This representation is then given an explicit realization as the solution space of a 4th-order wave equation on a spacetime locally isomorphic to Minkowski space. A discrete basis for this solution space is given, as well as an explicit expression for its SO(4, 2) invariant inner product. The connection between the modes of dipole field and those of the massless scalar field is clarified, and a recent conjecture concerning the restriction of the dipole representation to the Poincare subgroup is confirmed. A particular coordinate transformation then reveals the theory of the dipole ghost in Minkowski space. Finally, it is shown that the solution space of the dipole equation is not unitarizable in a Poincare invariant manner. (orig.)

E-Learning, State and Educational System in Middle East Countries

Science.gov (United States)

Rashidi, Hamid; Arani, Abbas Madandar; Kakia, Lida

2012-01-01

E-learning has provided men with new opportunities in teaching-learning procedures. A historical review of educational systems literature reveals that e-learning has spread out among people much faster than any other learning methods. E-learning as a state-of-the-art technology, has caused great innovations in materials development in those…

Process Improvement for Next Generation Space Flight Vehicles: MSFC Lessons Learned

Science.gov (United States)

Housch, Helen

2008-01-01

This viewgraph presentation reviews the lessons learned from process improvement for Next Generation Space Flight Vehicles. The contents include: 1) Organizational profile; 2) Process Improvement History; 3) Appraisal Preparation; 4) The Appraisal Experience; 5) Useful Tools; and 6) Is CMMI working?

Entering the Interaction Age: Implementing a Future Vision for Campus Learning Spaces...Today

Science.gov (United States)

Milne, Andrew J.

2007-01-01

Learning space design for higher education has become a popular topic of discussion as institutions attempt to chart a course for the future of their campuses. Several authors in EDUCAUSE publications have forecast the future for such spaces, a future infused with new and sometimes exotic-sounding technologies. Indeed, some discussions in the…

Teaching students in place: the languages of third space learning

Science.gov (United States)

Morawski, Cynthia M.

2017-09-01

With a perceptive eye cast on geoscience pedagogy for students labeled as disabled, Martinez-Álvarez makes important contributions to the existing conversation on placed-based learning. It is in our local backyards, from the corner basketball court, to the mud bank of a city lake, to the adjacent field where rocky outcrops spill down to a forgotten farmer's field, that we find rich working material for connecting self and community, moving students' out-of-school experiences that feature their cultural and linguistic knowledge, from misconceptions to "alternative conceptions." Informed by her insights regarding the learning of students whose literacy does not match conventional classroom practice, geoscience learning in the place of third space can act as a model of meaning making across the entire curriculum. In the pages that follow, I transact, both aesthetically and efferently, with Martinez-Álvarez's text as she presents her research on special ways of learning in placed-based geoscience explorations with bilingual children experiencing disabilities.

Learning to reach by reinforcement learning using a receptive field based function approximation approach with continuous actions.

Science.gov (United States)

Tamosiunaite, Minija; Asfour, Tamim; Wörgötter, Florentin

2009-03-01

Reinforcement learning methods can be used in robotics applications especially for specific target-oriented problems, for example the reward-based recalibration of goal directed actions. To this end still relatively large and continuous state-action spaces need to be efficiently handled. The goal of this paper is, thus, to develop a novel, rather simple method which uses reinforcement learning with function approximation in conjunction with different reward-strategies for solving such problems. For the testing of our method, we use a four degree-of-freedom reaching problem in 3D-space simulated by a two-joint robot arm system with two DOF each. Function approximation is based on 4D, overlapping kernels (receptive fields) and the state-action space contains about 10,000 of these. Different types of reward structures are being compared, for example, reward-on- touching-only against reward-on-approach. Furthermore, forbidden joint configurations are punished. A continuous action space is used. In spite of a rather large number of states and the continuous action space these reward/punishment strategies allow the system to find a good solution usually within about 20 trials. The efficiency of our method demonstrated in this test scenario suggests that it might be possible to use it on a real robot for problems where mixed rewards can be defined in situations where other types of learning might be difficult.

E-LEARNING: CURRENT STATE, TRENDS AND FUTURE PROSPECTS

Directory of Open Access Journals (Sweden)

Г А Краснова

2017-12-01

Full Text Available The article is devoted to the main trends of development of e-learning in formal and non-formal education in different countries. The article discusses the main quantitative and qualitative characteristics of the market of e-learning education. The authors define main reasons the development of e-learning education in higher education. The authors note that the demand for e-learning by various groups of users will push the education authorities and educational institutions to develop different forms of e-learning and implement new business models of universities. In most universities in Europe and the United States adopted or will be adopted for the institutional strategy of development of e-learning.

Learning physical space

DEFF Research Database (Denmark)

Hasse, Cathrine

2002-01-01

The article argues that cultural learning is a useful concept in analysing how neophytes learn from reactions and other forms of social designation. Through the newcomers learning process a concrete physical place takes on new cultural meaning. The specific example deals with first year students...... who have to learn that certain physical places, acts and objects are imbued with a cultural significance as the act of sitting on a chair or wearing a short dress takes on a new symbolic meaning in a cultural context where inclusion and exclusion are a constant concern. By following and analysing what...... is involved in the process of becoming ? in this case the becoming of physicist students ? the moral cultural logic behind in- and exclusion from physical places are established....

A safe place with space for learning: Experiences from an interprofessional training ward.

Science.gov (United States)

Hallin, Karin; Kiessling, Anna

2016-01-01

Interprofessional learning in a real ward context effectively increases collaborative and professional competence among students. However, less is known on the processes behind this. The aim of this study was to explore medical, nurse, physiotherapy, and occupational therapy students' perspectives on the process of their own learning at an interprofessional training ward (IPTW). We performed a qualitative content analysis on free-text answers of 333 student questionnaires from the years 2004 to 2011. Two main themes emerged: first, students found that the IPTW provided an enriching learning environment--a safe place with space. It included authentic and relevant patients, well-composed and functioning student teams, competent and supportive supervisors, and adjusted ward structures to support learning. Second, they developed an awareness of their own development with faith in the future--from chaos to clarity. It included personal, professional, and interprofessional development towards a comprehensive view of practice and a faith in their ability to work as professionals in the future. Our findings are discussed with a social constructivist perspective. This study suggests that when an IPTW provides a supportive and permissive learning environment with possibilities to interact with one another--a safe place with space--it enables students to move from insecurity to faith in their abilities--from chaos to clarity. However, if the learning environment is impaired, the students' development could be halted.

Space space space

CERN Document Server

Trembach, Vera

2014-01-01

Space is an introduction to the mysteries of the Universe. Included are Task Cards for independent learning, Journal Word Cards for creative writing, and Hands-On Activities for reinforcing skills in Math and Language Arts. Space is a perfect introduction to further research of the Solar System.

Estimation methods for nonlinear state-space models in ecology

DEFF Research Database (Denmark)

Pedersen, Martin Wæver; Berg, Casper Willestofte; Thygesen, Uffe Høgsbro

2011-01-01

The use of nonlinear state-space models for analyzing ecological systems is increasing. A wide range of estimation methods for such models are available to ecologists, however it is not always clear, which is the appropriate method to choose. To this end, three approaches to estimation in the theta...... logistic model for population dynamics were benchmarked by Wang (2007). Similarly, we examine and compare the estimation performance of three alternative methods using simulated data. The first approach is to partition the state-space into a finite number of states and formulate the problem as a hidden...... Markov model (HMM). The second method uses the mixed effects modeling and fast numerical integration framework of the AD Model Builder (ADMB) open-source software. The third alternative is to use the popular Bayesian framework of BUGS. The study showed that state and parameter estimation performance...

Multimedia Mapping using Continuous State Space Models

DEFF Research Database (Denmark)

Lehn-Schiøler, Tue

2004-01-01

In this paper a system that transforms speech waveforms to animated faces are proposed. The system relies on continuous state space models to perform the mapping, this makes it possible to ensure video with no sudden jumps and allows continuous control of the parameters in 'face space'. Simulations...... are performed on recordings of 3-5 sec. video sequences with sentences from the Timit database. The model is able to construct an image sequence from an unknown noisy speech sequence fairly well even though the number of training examples are limited....

Tips for a Healthy Long-Life Learned from Space Medicine

Science.gov (United States)

Ohshima, Hiroshi; Yamada, Shin; Matsuo, Tomoaki; Yamamoto, Masafumi; Mukai, Chiaki

2013-02-01

The field of space medicine is responsible for maintaining astronauts’ health and optimizing their performance. A prolonged stay in space with little gravity results in weakening of the bones and muscles that otherwise support body weight, which is precisely the problem faced by elderly people on Earth. Space medicine provides the means of alleviating such problems. Bone loss, muscle atrophy, and disturbed circadian rhythms are common issues for both astronauts and the elderly alike and can be prevented, if the risks are addressed correctly. To have a healthy long-life, it is important to practice effective health improvement techniques and take preventive measures. The space medicine technologies a for astronauts will provide helpful information to people living in a super aging society. and Japanese medical societies for health promotion. With the aids of the Japanese Society of Physical Fitness and Sports Medicine, the Japanese Orthopaedic Association, and the Japanese Association of Rehabilitation Medicine, JAXA has made a leaflet titled for general citizen to show the tips for a healthy long-life learned from space medicine from the viewpoints of their respective expertise.

Does emotion modulate the efficacy of spaced learning in recognition memory?

Directory of Open Access Journals (Sweden)

Nicola Mammarella

2014-12-01

Full Text Available Memory for repeated items improves when presentations are spaced during study. Here, two experiments assessed the so-called spacing effect on a yes–no recognition memory task using affective and neutral words. In Experiment 1, a group of participants was asked to orient their attention to semantic features of target words (deep semantic analysis that were consecutively repeated or spaced, while another group was engaged in a graphemic shallow analysis of words (Experiment 2. The depth of word processing approach was meant to highlight the role of repetition priming mechanisms in the generation of spacing effects. We found that spacing effects occurred for both affective and neutral words (Experiment 1. However, following shallow analysis of words, the spacing effect was reduced for both affective and neutral words (Experiment 2. No differences were detected in terms of positive versus negative words. These results suggest that spaced learning operates when the to-be-remembered material is also affectively charged and that, under certain circumstances, it may enhance recognition memory as affective connotation does.

Self-learning estimation of quantum states

International Nuclear Information System (INIS)

Hannemann, Th.; Reiss, D.; Balzer, Ch.; Neuhauser, W.; Toschek, P.E.; Wunderlich, Ch.

2002-01-01

We report the experimental estimation of arbitrary qubit states using a succession of N measurements on individual qubits, where the measurement basis is changed during the estimation procedure conditioned on the outcome of previous measurements (self-learning estimation). Two hyperfine states of a single trapped 171 Yb + ion serve as a qubit. It is demonstrated that the difference in fidelity between this adaptive strategy and passive strategies increases in the presence of decoherence

Workplace learning from a socio-cultural perspective: creating developmental space during the general practice clerkship.

Science.gov (United States)

van der Zwet, J; Zwietering, P J; Teunissen, P W; van der Vleuten, C P M; Scherpbier, A J J A

2011-08-01

Workplace learning in undergraduate medical education has predominantly been studied from a cognitive perspective, despite its complex contextual characteristics, which influence medical students' learning experiences in such a way that explanation in terms of knowledge, skills, attitudes and single determinants of instructiveness is unlikely to suffice. There is also a paucity of research which, from a perspective other than the cognitive or descriptive one, investigates student learning in general practice settings, which are often characterised as powerful learning environments. In this study we took a socio-cultural perspective to clarify how students learn during a general practice clerkship and to construct a conceptual framework that captures this type of learning. Our analysis of group interviews with 44 fifth-year undergraduate medical students about their learning experiences in general practice showed that students needed developmental space to be able to learn and develop their professional identity. This space results from the intertwinement of workplace context, personal and professional interactions and emotions such as feeling respected and self-confident. These forces framed students' participation in patient consultations, conversations with supervisors about consultations and students' observation of supervisors, thereby determining the opportunities afforded to students to mind their learning. These findings resonate with other conceptual frameworks and learning theories. In order to refine our interpretation, we recommend that further research from a socio-cultural perspective should also explore other aspects of workplace learning in medical education.

State Digital Learning Exemplars: Highlights from States Leading Change through Policies and Funding

Science.gov (United States)

Acree, Lauren; Fox, Christine

2015-01-01

States are striving to support the expansion of technology tools and resources in K-12 education through state policies, programs, and funding in order to provide digital learning opportunities for all students. This paper highlights examples of states with policies in support of five key areas: (1) innovative funding streams and policy; (2)…

Differential effects of massed and spaced training on place and response learning: A memory systems perspective.

Science.gov (United States)

Wingard, Jeffrey C; Goodman, Jarid; Leong, Kah-Chung; Packard, Mark G

2015-09-01

Studies employing brain lesion or intracerebral drug infusions in rats have demonstrated a double dissociation between the roles of the hippocampus and dorsolateral striatum in place and response learning. The hippocampus mediates a rapid cognitive learning process underlying place learning, whereas the dorsolateral striatum mediates a relatively slower learning process in which stimulus-response habits underlying response learning are acquired in an incremental fashion. One potential implication of these findings is that hippocampus-dependent learning may benefit from a relative massing of training trials, whereas dorsal striatum-dependent learning may benefit from a relative distribution of training trials. In order to examine this hypothesis, the present study compared the effects of massed (30s inter-trial interval; ITI) or spaced (30min ITI) training on acquisition of a hippocampus-dependent place learning task, and a dorsolateral striatum-dependent response task in a plus-maze. In the place task rats swam from varying start points (N or S) to a hidden escape platform located in a consistent spatial location (W). In the response task rats swam from varying start points (N or S) to a hidden escape platform located in the maze arm consistent with a body-turn response (left). In the place task, rats trained with the massed trial schedule acquired the task quicker than rats trained with the spaced trial schedule. In the response task, rats trained with the spaced trial schedule acquired the task quicker than rats trained with the massed trial schedule. The double dissociation observed suggests that the reinforcement parameters most conducive to effective learning in hippocampus-dependent and dorsolateral striatum-dependent learning may have differential temporal characteristics. Copyright © 2015 Elsevier B.V. All rights reserved.

Developing Learning Analytics Design Knowledge in the "Middle Space": The Student Tuning Model and Align Design Framework for Learning Analytics Use

Science.gov (United States)

Wise, Alyssa Friend; Vytasek, Jovita Maria; Hausknecht, Simone; Zhao, Yuting

2016-01-01

This paper addresses a relatively unexplored area in the field of learning analytics: how analytics are taken up and used as part of teaching and learning processes. Initial steps are taken towards developing design knowledge for this "middle space," with a focus on students as analytics users. First, a core set of challenges for…

Flexible Heuristic Dynamic Programming for Reinforcement Learning in Quadrotors

NARCIS (Netherlands)

Helmer, Alexander; de Visser, C.C.; van Kampen, E.

2018-01-01

Reinforcement learning is a paradigm for learning decision-making tasks from interaction with the environment. Function approximators solve a part of the curse of dimensionality when learning in high-dimensional state and/or action spaces. It can be a time-consuming process to learn a good policy in

Pure state consciousness and its local reduction to neuronal space

Science.gov (United States)

Duggins, A. J.

2013-01-01

The single neuronal state can be represented as a vector in a complex space, spanned by an orthonormal basis of integer spike counts. In this model a scalar element of experience is associated with the instantaneous firing rate of a single sensory neuron over repeated stimulus presentations. Here the model is extended to composite neural systems that are tensor products of single neuronal vector spaces. Depiction of the mental state as a vector on this tensor product space is intended to capture the unity of consciousness. The density operator is introduced as its local reduction to the single neuron level, from which the firing rate can again be derived as the objective correlate of a subjective element. However, the relational structure of perceptual experience only emerges when the non-local mental state is considered. A metric of phenomenal proximity between neuronal elements of experience is proposed, based on the cross-correlation function of neurophysiology, but constrained by the association of theoretical extremes of correlation/anticorrelation in inseparable 2-neuron states with identical and opponent elements respectively.

State-space Manifold and Rotating Black Holes

CERN Document Server

Bellucci, Stefano

2010-01-01

We study a class of fluctuating higher dimensional black hole configurations obtained in string theory/ $M$-theory compactifications. We explore the intrinsic Riemannian geometric nature of Gaussian fluctuations arising from the Hessian of the coarse graining entropy, defined over an ensemble of brane microstates. It has been shown that the state-space geometry spanned by the set of invariant parameters is non-degenerate, regular and has a negative scalar curvature for the rotating Myers-Perry black holes, Kaluza-Klein black holes, supersymmetric $AdS_5$ black holes, $D_1$-$D_5$ configurations and the associated BMPV black holes. Interestingly, these solutions demonstrate that the principal components of the state-space metric tensor admit a positive definite form, while the off diagonal components do not. Furthermore, the ratio of diagonal components weakens relatively faster than the off diagonal components, and thus they swiftly come into an equilibrium statistical configuration. Novel aspects of the scali...

Learning Agents for Autonomous Space Asset Management (LAASAM)

Science.gov (United States)

Scally, L.; Bonato, M.; Crowder, J.

2011-09-01

Current and future space systems will continue to grow in complexity and capabilities, creating a formidable challenge to monitor, maintain, and utilize these systems and manage their growing network of space and related ground-based assets. Integrated System Health Management (ISHM), and in particular, Condition-Based System Health Management (CBHM), is the ability to manage and maintain a system using dynamic real-time data to prioritize, optimize, maintain, and allocate resources. CBHM entails the maintenance of systems and equipment based on an assessment of current and projected conditions (situational and health related conditions). A complete, modern CBHM system comprises a number of functional capabilities: sensing and data acquisition; signal processing; conditioning and health assessment; diagnostics and prognostics; and decision reasoning. In addition, an intelligent Human System Interface (HSI) is required to provide the user/analyst with relevant context-sensitive information, the system condition, and its effect on overall situational awareness of space (and related) assets. Colorado Engineering, Inc. (CEI) and Raytheon are investigating and designing an Intelligent Information Agent Architecture that will provide a complete range of CBHM and HSI functionality from data collection through recommendations for specific actions. The research leverages CEI’s expertise with provisioning management network architectures and Raytheon’s extensive experience with learning agents to define a system to autonomously manage a complex network of current and future space-based assets to optimize their utilization.

Identification of a class of nonlinear state-space models using RPE techniques

DEFF Research Database (Denmark)

Zhou, W. W.; Blanke, Mogens

1986-01-01

The recursive prediction error methods in state-space form have been efficiently used as parameter identifiers for linear systems, and especially Ljung's innovations filter using a Newton search direction has proved to be quite ideal. In this paper, the RPE method in state-space form is developed...... a quite convincing performance of the filter as combined parameter and state estimator....

Coherent states on horospheric three-dimensional Lobachevsky space

Energy Technology Data Exchange (ETDEWEB)

Kurochkin, Yu., E-mail: y.kurochkin@ifanbel.bas-net.by; Shoukavy, Dz., E-mail: shoukavy@ifanbel.bas-net.by [Institute of Physics, National Academy of Sciences of Belarus, 68 Nezalezhnasci Ave., Minsk 220072 (Belarus); Rybak, I., E-mail: Ivan.Rybak@astro.up.pt [Institute of Physics, National Academy of Sciences of Belarus, 68 Nezalezhnasci Ave., Minsk 220072 (Belarus); Instituto de Astrofísica e Ciências do Espaço, CAUP, Rua das Estrelas, 4150-762 Porto (Portugal); Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto (Portugal)

2016-08-15

In the paper it is shown that due to separation of variables in the Laplace-Beltrami operator (Hamiltonian of a free quantum particle) in horospheric and quasi-Cartesian coordinates of three dimensional Lobachevsky space, it is possible to introduce standard (“conventional” according to Perelomov [Generalized Coherent States and Their Applications (Springer-Verlag, 1986), p. 320]) coherent states. Some problems (oscillator on horosphere, charged particle in analogy of constant uniform magnetic field) where coherent states are suitable for treating were considered.

Dynamic State Space Partitioning for External Memory Model Checking

DEFF Research Database (Denmark)

Evangelista, Sami; Kristensen, Lars Michael

2009-01-01

We describe a dynamic partitioning scheme usable by model checking techniques that divide the state space into partitions, such as most external memory and distributed model checking algorithms. The goal of the scheme is to reduce the number of transitions that link states belonging to different...

Motor imagery learning modulates functional connectivity of multiple brain systems in resting state.

Science.gov (United States)

Zhang, Hang; Long, Zhiying; Ge, Ruiyang; Xu, Lele; Jin, Zhen; Yao, Li; Liu, Yijun

2014-01-01

Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning. We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN. These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning.

Video Demo: Deep Reinforcement Learning for Coordination in Traffic Light Control

NARCIS (Netherlands)

van der Pol, E.; Oliehoek, F.A.; Bosse, T.; Bredeweg, B.

2016-01-01

This video demonstration contrasts two approaches to coordination in traffic light control using reinforcement learning: earlier work, based on a deconstruction of the state space into a linear combination of vehicle states, and our own approach based on the Deep Q-learning algorithm.

Limits on nonlocal correlations from the structure of the local state space

International Nuclear Information System (INIS)

Janotta, Peter; Gogolin, Christian; Barrett, Jonathan; Brunner, Nicolas

2011-01-01

The outcomes of measurements on entangled quantum systems can be nonlocally correlated. However, while it is easy to write down toy theories allowing arbitrary nonlocal correlations, those allowed in quantum mechanics are limited. Quantum correlations cannot, for example, violate a principle known as macroscopic locality, which implies that they cannot violate Tsirelson's bound. This paper shows that there is a connection between the strength of nonlocal correlations in a physical theory and the structure of the state spaces of individual systems. This is illustrated by a family of models in which local state spaces are regular polygons, where a natural analogue of a maximally entangled state of two systems exists. We characterize the nonlocal correlations obtainable from such states. The family allows us to study the transition between classical, quantum and super-quantum correlations by varying only the local state space. We show that the strength of nonlocal correlations - in particular whether the maximally entangled state violates Tsirelson's bound or not-depends crucially on a simple geometric property of the local state space, known as strong self-duality. This result is seen to be a special case of a general theorem, which states that a broad class of entangled states in probabilistic theories-including, by extension, all bipartite classical and quantum states-cannot violate macroscopic locality. Finally, our results show that models exist that are locally almost indistinguishable from quantum mechanics, but can nevertheless generate maximally nonlocal correlations.

Flexible State-Merging for learning (P)DFAs in Python

OpenAIRE

Hammerschmidt, Christian; Loos, Benjamin Laurent; Verwer, Sicco; State, Radu

2016-01-01

We present a Python package for learning (non-)probabilistic deterministic finite state automata and provide heuristics in the red-blue framework. As our package is built along the API of the popular \\texttt{scikit-learn} package, it is easy to use and new learning methods are easy to add. It provides PDFA learning as an additional tool for sequence prediction or classification to data scientists, without the need to understand the algorithm itself but rather the limitations of PDFA as a mode...

State-Space Modelling of Loudspeakers using Fractional Derivatives

DEFF Research Database (Denmark)

King, Alexander Weider; Agerkvist, Finn T.

2015-01-01

This work investigates the use of fractional order derivatives in modeling moving-coil loudspeakers. A fractional order state-space solution is developed, leading the way towards incorporating nonlinearities into a fractional order system. The method is used to calculate the response of a fractio......This work investigates the use of fractional order derivatives in modeling moving-coil loudspeakers. A fractional order state-space solution is developed, leading the way towards incorporating nonlinearities into a fractional order system. The method is used to calculate the response...... of a fractional harmonic oscillator, representing the mechanical part of a loudspeaker, showing the effect of the fractional derivative and its relationship to viscoelasticity. Finally, a loudspeaker model with a fractional order viscoelastic suspension and fractional order voice coil is fit to measurement data...

State Space Models and the Kalman-Filter in Stochastic Claims Reserving: Forecasting, Filtering and Smoothing

Directory of Open Access Journals (Sweden)

Nataliya Chukhrova

2017-05-01

Full Text Available This paper gives a detailed overview of the current state of research in relation to the use of state space models and the Kalman-filter in the field of stochastic claims reserving. Most of these state space representations are matrix-based, which complicates their applications. Therefore, to facilitate the implementation of state space models in practice, we present a scalar state space model for cumulative payments, which is an extension of the well-known chain ladder (CL method. The presented model is distribution-free, forms a basis for determining the entire unobservable lower and upper run-off triangles and can easily be applied in practice using the Kalman-filter for prediction, filtering and smoothing of cumulative payments. In addition, the model provides an easy way to find outliers in the data and to determine outlier effects. Finally, an empirical comparison of the scalar state space model, promising prior state space models and some popular stochastic claims reserving methods is performed.

The State of Educators' Professional Learning in Canada. Executive Summary

Science.gov (United States)

Campbell, Carol; Osmond-Johnson, Pamela; Faubert, Brenton; Zeichner, Kenneth; Hobbs-Johnson, Audrey

2016-01-01

Coinciding with the 2016 Annual Conference in Vancouver, British Columbia, Learning Forward commissioned and supported a study of professional learning across the nation of Canada. "The State of Educators' Professional Learning in Canada" was researched by a team led by Carol Campbell, Associate Professor of Leadership and Educational…

States of curiosity modulate hippocampus-dependent learning via the dopaminergic circuit

Science.gov (United States)

Gruber, Matthias J.; Gelman, Bernard D.; Ranganath, Charan

2014-01-01

Summary People find it easier to learn about topics that interest them, but little is known about the mechanisms by which intrinsic motivational states affect learning. We used functional magnetic resonance imaging to investigate how curiosity (intrinsic motivation to learn) influences memory. In both immediate and one-day delayed memory tests, participants showed improved memory for information that they were curious about, and also for incidental material learned during states of high curiosity. FMRI results revealed that activity in the midbrain and the nucleus accumbens was enhanced during states of high curiosity. Importantly, individual variability in curiosity-driven memory benefits for incidental material was supported by anticipatory activity in the midbrain and hippocampus and by functional connectivity between these regions. These findings suggest a link between the mechanisms supporting extrinsic reward motivation and intrinsic curiosity and highlight the importance of stimulating curiosity in order to create more effective learning experiences. PMID:25284006

States of curiosity modulate hippocampus-dependent learning via the dopaminergic circuit.

Science.gov (United States)

Gruber, Matthias J; Gelman, Bernard D; Ranganath, Charan

2014-10-22

People find it easier to learn about topics that interest them, but little is known about the mechanisms by which intrinsic motivational states affect learning. We used functional magnetic resonance imaging to investigate how curiosity (intrinsic motivation to learn) influences memory. In both immediate and one-day-delayed memory tests, participants showed improved memory for information that they were curious about and for incidental material learned during states of high curiosity. Functional magnetic resonance imaging results revealed that activity in the midbrain and the nucleus accumbens was enhanced during states of high curiosity. Importantly, individual variability in curiosity-driven memory benefits for incidental material was supported by anticipatory activity in the midbrain and hippocampus and by functional connectivity between these regions. These findings suggest a link between the mechanisms supporting extrinsic reward motivation and intrinsic curiosity and highlight the importance of stimulating curiosity to create more effective learning experiences. Copyright © 2014 Elsevier Inc. All rights reserved.

CSU Digital Ambassadors: An Empowering and Impactful Faculty Learning Community

Science.gov (United States)

Soodjinda, Daniel; Parker, Jessica K.; Ross, Donna L.; Meyer, Elizabeth J.

2014-01-01

This article chronicles the work of the California State University Digital Ambassador Program (DA), a Faculty Learning Community (FLC), which brought together 13 faculty members across the state to create ongoing, targeted spaces of support for colleagues and educational partners to learn about innovative technological and pedagogical practices…

Rosette of rosettes of Hilbert spaces in the indefinite metric state space of the quantized Maxwell field

International Nuclear Information System (INIS)

Gessner, W.; Ernst, V.

1980-01-01

The indefinite metric space O/sub M/ of the covariant form of the quantized Maxwell field M is analyzed in some detail. S/sub M/ contains not only the pre-Hilbert space X 0 of states of transverse photons which occurs in the Gupta--Bleuler formalism of the free M, but a whole rosette of continuously many, isomorphic, complete, pre-Hilbert spaces L/sup q/ disjunct up to the zero element o of S/sub M/. The L/sup q/ are the maximal subspaces of S/sub M/ which allow the usual statistical interpretation. Each L/sup q/ corresponds uniquely to one square integrable, spatial distribution j/sup o/(x) of the total charge Q=0. If M is in any state from L/sup q/, the bare charge j 0 (x) appears to be inseparably dressed by the quantum equivalent of its proper, classical Coulomb field E(x). The vacuum occurs only in the state space L 0 of the free Maxwell field. Each L/sup q/ contains a secondary rosette of continuously many, up to o disjunct, isomorphic Hilbert spaces H/sub g//sup q/ related to different electromagnetic gauges. The space H/sub o//sup q/, which corresponds to the Coulomb gauge within the Lorentz gauge, plays a physically distinguished role in that only it leads to the usual concept of energy. If M is in any state from H/sub g//sup q/, the bare 4-current j 0 (x), j(x), where j(x) is any square integrable, transverse current density in space, is endowed with its proper 4-potential which depends on the chosen gauge, and with its proper, gauge independent, Coulomb--Oersted field E(x), B(x). However, these fields exist only in the sense of quantum mechanical expectation values equipped with the corresponding field fluctuations. So they are basically different from classical electromagnetic fields

Statistical learning modeling method for space debris photometric measurement

Science.gov (United States)

Sun, Wenjing; Sun, Jinqiu; Zhang, Yanning; Li, Haisen

2016-03-01

Photometric measurement is an important way to identify the space debris, but the present methods of photometric measurement have many constraints on star image and need complex image processing. Aiming at the problems, a statistical learning modeling method for space debris photometric measurement is proposed based on the global consistency of the star image, and the statistical information of star images is used to eliminate the measurement noises. First, the known stars on the star image are divided into training stars and testing stars. Then, the training stars are selected as the least squares fitting parameters to construct the photometric measurement model, and the testing stars are used to calculate the measurement accuracy of the photometric measurement model. Experimental results show that, the accuracy of the proposed photometric measurement model is about 0.1 magnitudes.

Formulating state space models in R with focus on longitudinal regression models

DEFF Research Database (Denmark)

Dethlefsen, Claus; Lundbye-Christensen, Søren

2006-01-01

We provide a language for formulating a range of state space models with response densities within the exponential family. The described methodology is implemented in the R-package sspir. A state space model is specified similarly to a generalized linear model in R, and then the time-varying terms...

An application of gain-scheduled control using state-space interpolation to hydroactive gas bearings

DEFF Research Database (Denmark)

Theisen, Lukas Roy Svane; Camino, Juan F.; Niemann, Hans Henrik

2016-01-01

with a gain-scheduling strategy using state-space interpolation, which avoids both the performance loss and the increase of controller order associated to the Youla parametrisation. The proposed state-space interpolation for gain-scheduling is applied for mass imbalance rejection for a controllable gas...... bearing scheduled in two parameters. Comparisons against the Youla-based scheduling demonstrate the superiority of the state-space interpolation....

Applied Drama and the Higher Education Learning Spaces: A Reflective Analysis

Science.gov (United States)

Moyo, Cletus

2015-01-01

This paper explores Applied Drama as a teaching approach in Higher Education learning spaces. The exploration takes a reflective analysis approach by first examining the impact that Applied Drama has had on my career as a Lecturer/Educator/Teacher working in Higher Education environments. My engagement with Applied Drama practice and theory is…

"Space on Earth:" A Learning Community Integrating English, Math, and Science

Science.gov (United States)

Fortna, Joanna; Sullivan, Jim

2010-01-01

Imagine a mathematics instructor and English instructor sharing an office; scribbled equations litter one desk, snatches of poetry the other. Our learning community, "Space on Earth," grew from conversations in just such an office where we bridged our own disciplinary gap and discovered a shared passion for helping students apply the concepts and…

Space-time complexity in solid state models

International Nuclear Information System (INIS)

Bishop, A.R.

1985-01-01

In this Workshop on symmetry-breaking it is appropriate to include the evolving fields of nonlinear-nonequilibrium systems in which transitions to and between various degrees of ''complexity'' (including ''chaos'') occur in time or space or both. These notions naturally bring together phenomena of pattern formation and chaos and therefore have ramifications for a huge array of natural sciences - astrophysics, plasmas and lasers, hydrodynamics, field theory, materials and solid state theory, optics and electronics, biology, pattern recognition and evolution, etc. Our particular concerns here are with examples from solid state and condensed matter

Abelian faces of state spaces of C*-algebras

International Nuclear Information System (INIS)

Batty, C.J.K.

1980-01-01

Let F be a closed face of the weak* compact convex state space of a unital C*-algebra A. The class of F-abelian states, introduced earlier by the author, is studied further. It is shown (without any restriction on A or F) that F is a Choquet simplex if and only if every state in F is F-abelian, and that it is sufficient for this that every pure state in F is F-abelian. As a corollary, it is deduced that an arbitrary C*-dynamical system (A,G,α) is G-abelian if and only if every ergodic state is weakly clustering. Nevertheless the set of all F-abelian (or even G-abelian) states is not necessarily weak* compact. (orig.)

Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State

Science.gov (United States)

Zhang, Hang; Long, Zhiying; Ge, Ruiyang; Xu, Lele; Jin, Zhen; Yao, Li; Liu, Yijun

2014-01-01

Background Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning. Methodology/Principal Findings We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN. Conclusions/Significance These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning. PMID:24465577

Safe robot execution in model-based reinforcement learning

OpenAIRE

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

2015-01-01

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

Project Based Learning experiences in the space engineering education at Technical University of Madrid

Science.gov (United States)

Rodríguez, Jacobo; Laverón-Simavilla, Ana; del Cura, Juan M.; Ezquerro, José M.; Lapuerta, Victoria; Cordero-Gracia, Marta

2015-10-01

This work describes the innovation activities performed in the field of space education since the academic year 2009/10 at the Technical University of Madrid (UPM), in collaboration with the Spanish User Support and Operations Center (E-USOC), the center assigned by the European Space Agency (ESA) in Spain to support the operations of scientific experiments on board the International Space Station. These activities have been integrated within the last year of the UPM Aerospace Engineering degree. A laboratory has been created, where students have to validate and integrate the subsystems of a microsatellite using demonstrator satellites. In parallel, the students participate in a Project Based Learning (PBL) training process in which they work in groups to develop the conceptual design of a space mission. One student in each group takes the role of project manager, another one is responsible for the mission design and the rest are each responsible for the design of one of the satellite subsystems. A ground station has also been set up with the help of students developing their final thesis, which will allow future students to perform training sessions and learn how to communicate with satellites, how to receive telemetry and how to process the data. Several surveys have been conducted along two academic years to evaluate the impact of these techniques in engineering learning. The surveys evaluate the acquisition of specific and generic competences, as well as the students' degree of satisfaction with respect to the use of these learning methodologies. The results of the surveys and the perception of the lecturers show that PBL encourages students' motivation and improves their results. They not only acquire better technical training, but also improve their transversal skills. It is also pointed out that this methodology requires more dedication from lecturers than traditional methods.

Sustainable development and social learning: Re-contextualising the space of orientation

Science.gov (United States)

Seddon, Terri

2016-10-01

In the lead-up to the 2007 Australian federal election, Labor candidate Kevin Rudd described climate change as the "great moral challenge of our generation". In the years since then, the heat in Australia has been rising - in terms of both temperature and climate politics -, but government action has slowed down. Endorsement of economic growth is prioritised, with only intermittent recognition of environmental costs. At grassroots level, citizens' attitudes are influenced by social norms. This kind of social learning is a major constraint on sustainability. Therefore, it seems useful to consider how educators might help build sustainable futures. To understand how historical context entangles social learning in ways that complicate policies associated with Education for Sustainable Development (ESD) and practices of Education for Sustainability (EfS), the author of this paper draws on the concept of "space of orientation". Focusing on adult education, she traces the contradiction between "globalisation" and "sustainability" through policy logics, relational practices in Australian adult education and the "necessary utopia" which provides a point of reference for making futures. She argues that spaces of orientation are a critical resource in this era of intensifying conflicts of interest between economic priorities of globalisation and environmental priorities intended to slow global warming, because they mediate context and orient learning in ways that clear a path towards sustainability through the entangled histories of this present.

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

Science.gov (United States)

Gallos, Ioannis; Siettos, Constantinos

2017-11-01

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

Learning by random walks in the weight space of the Ising perceptron

International Nuclear Information System (INIS)

Huang, Haiping; Zhou, Haijun

2010-01-01

Several variants of a stochastic local search process for constructing the synaptic weights of an Ising perceptron are studied. In this process, binary patterns are sequentially presented to the Ising perceptron and are then learned as the synaptic weight configuration is modified through a chain of single- or double-weight flips within the compatible weight configuration space of the earlier learned patterns. This process is able to reach a storage capacity of α≈0.63 for pattern length N = 101 and α≈0.41 for N = 1001. If in addition a relearning process is exploited, the learning performance is further improved to a storage capacity of α≈0.80 for N = 101 and α≈0.42 for N = 1001. We found that, for a given learning task, the solutions constructed by the random walk learning process are separated by a typical Hamming distance, which decreases with the constraint density α of the learning task; at a fixed value of α, the width of the Hamming distance distribution decreases with N

Using an Outdoor Learning Space to Teach Sustainability and Material Processes in HE Product Design

Science.gov (United States)

Firth, Richard; Stoltenberg, Einar; Jennings, Trent

2016-01-01

This "case study" of two jewellery workshops, used outdoor learning spaces to explore both its impact on learning outcomes and to introduce some key principles of sustainable working methodologies and practices. Using the beach as the classroom, academics and students from a Norwegian and Scottish (HE) product design exchange programme…

Why Do They Study There? Diary Research into Students' Learning Space Choices in Higher Education

Science.gov (United States)

Beckers, Ronald; van der Voordt, Theo; Dewulf, Geert

2016-01-01

Higher education learning and teaching methods have changed while most educational buildings are still rather traditional. Yet, there is an increasing interest in whether we can educate today's higher education students in yesterday's buildings. This paper aims to contribute to this debate by studying the learning space choices of higher education…

Effect of urban noise to the acoustical performance of the secondary school’s learning spaces - A case study in Batu Pahat.

Science.gov (United States)

Tong, Y. G.; Abu Bakar, H.; Mohd. Sari, K. A.; Ewon, U.; Labeni, M. N.; Fauzan, N. F. A.

2017-11-01

Classrooms and laboratories are important spaces that use for teaching and learning process in the school. Therefore, good acoustical performances of these spaces are essential to ensure the speech or message from the teacher can be delivered to the students effectively and clearly. The aims of this study is to determine the acoustical performance of the teaching and learning spaces in public school that situated near to the traffic roads. The acoustical performance of the classrooms and laboratories at Sekolah Menengah Kebangsaan Convent Batu Pahat was evaluated in this study. The reverberation time and ambient noise of these learning spaces which are the main parameters for classroom design criteria were evaluated. Field measurements were carried out inside six classrooms and four laboratories unoccupied furnished according to the international standards. The acoustical performances of the tested learning spaces were poor where the noise criteria and reverberation times inside the measured classrooms and laboratories were higher than recommended values.

"From Bricks to Clicks": Hybrid Commercial Spaces in the Landscape of Early Literacy and Learning

Science.gov (United States)

Nixon, Helen

2011-01-01

In their quest for resources to support children's early literacy learning and development, parents encounter and traverse different spaces in which discourses and artifacts are produced and circulated. This paper uses conceptual tools from the field of geosemiotics to examine some commercial spaces designed for parents and children that…

Learning to Act: Qualitative Learning of Deterministic Action Models

DEFF Research Database (Denmark)

Bolander, Thomas; Gierasimczuk, Nina

2017-01-01

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

Coherent states for FLRW space-times in loop quantum gravity

International Nuclear Information System (INIS)

Magliaro, Elena; Perini, Claudio; Marciano, Antonino

2011-01-01

We construct a class of coherent spin-network states that capture properties of curved space-times of the Friedmann-Lamaitre-Robertson-Walker type on which they are peaked. The data coded by a coherent state are associated to a cellular decomposition of a spatial (t=const) section with a dual graph given by the complete five-vertex graph, though the construction can be easily generalized to other graphs. The labels of coherent states are complex SL(2,C) variables, one for each link of the graph, and are computed through a smearing process starting from a continuum extrinsic and intrinsic geometry of the canonical surface. The construction covers both Euclidean and Lorentzian signatures; in the Euclidean case and in the limit of flat space we reproduce the simplicial 4-simplex semiclassical states used in spin foams.

Lessons learned by southern states in designating alternative routes

International Nuclear Information System (INIS)

1989-08-01

The purpose of this report is to discuss the ''lessons learned'' by the five states within the southem region that have designated alternative or preferred routes under the regulations of the Department of Transportation (DOT) established for the transportation of radioactive materials. The document was prepared by reviewing applicable federal laws and regulations, examining state reports and documents and contacting state officials and routing agencies involved in making routing decisions. In undertaking this project, the Southern States Energy Board hopes to reveal the process used by states that have designated alternative routes and thereby share their experiences (i.e., lessons learned) with other southern states that have yet to make designations. Under DOT regulations (49 CFR 177.826), carriers of highway route controlled quantities of radioactive materials (which include spent nuclear fuel and high-level waste) must use preferred routes selected to reduce time in transit. Such preferred routes consist of (1) an interstate system highway with use of an interstate system bypass or beltway around cities when available, and (2) alternate routes selected by a ''state routing agency.''

Animals in Space From Research Rockets to the Space Shuttle

CERN Document Server

Burgess, Colin

2007-01-01

Many readers will doubtless be astonished to learn that animals were being fired aloft in U.S. and Soviet research rockets in the late 1940s. In fact most people not only believe that the Russian space dog Laika was the first canine to be launched into space, but also that the high-profile, precursory Mercury flights of chimps Ham and Enos were the only primate flights conducted by the United States. In fact, both countries had sent literally dozens of animals aloft for many years prior to these events and continued to do so for many years after. Other latter-day space nations, such as France and China, would also begin to use animals in their own space research. Animals in Space will explain why dogs, primates, mice and other rodents were chosen and tested, at a time when dedicated scientists from both space nations were determined to establish the survivability of human subjects on both ballistic and orbital space flights. It will also recount the way this happened; the secrecy involved and the methods empl...

Learning in third spaces: community art studio as storefront university classroom.

Science.gov (United States)

Timm-Bottos, Janis; Reilly, Rosemary C

2015-03-01

Third spaces are in-between places where teacher-student scripts intersect, creating the potential for authentic interaction and a shift in what counts as knowledge. This paper describes a unique community-university initiative: a third space storefront classroom for postsecondary students in professional education programs, which also functions as a community art studio for the surrounding neighborhood. This approach to professional education requires an innovative combination of theory, methods, and materials as enacted by the professionals involved and performed by the students. This storefront classroom utilizes collaborative and inclusive instructional practices that promote human and community development. It facilitates the use of innovative instructional strategies including art making and participatory dialogue to create a liminal learning space that reconfigures professional education. In researching the effectiveness of this storefront classroom, we share the voices of students who have participated in this third space as part of their coursework to underscore these principles and practices.

The quantum state vector in phase space and Gabor's windowed Fourier transform

International Nuclear Information System (INIS)

Bracken, A J; Watson, P

2010-01-01

Representations of quantum state vectors by complex phase space amplitudes, complementing the description of the density operator by the Wigner function, have been defined by applying the Weyl-Wigner transform to dyadic operators, linear in the state vector and anti-linear in a fixed 'window state vector'. Here aspects of this construction are explored, and a connection is established with Gabor's 'windowed Fourier transform'. The amplitudes that arise for simple quantum states from various choices of windows are presented as illustrations. Generalized Bargmann representations of the state vector appear as special cases, associated with Gaussian windows. For every choice of window, amplitudes lie in a corresponding linear subspace of square-integrable functions on phase space. A generalized Born interpretation of amplitudes is described, with both the Wigner function and a generalized Husimi function appearing as quantities linear in an amplitude and anti-linear in its complex conjugate. Schroedinger's time-dependent and time-independent equations are represented on phase space amplitudes, and their solutions described in simple cases.

Filtering and smoothing of stae vector for diffuse state space models

NARCIS (Netherlands)

Koopman, S.J.; Durbin, J.

2003-01-01

This paper presents exact recursions for calculating the mean and mean square error matrix of the state vector given the observations for the multi-variate linear Gaussian state-space model in the case where the initial state vector is (partially) diffuse.

Investigation of unstable periodic space-time states in distributed active system with supercritical current

International Nuclear Information System (INIS)

Koronovskij, A.A.; Rempen, I.S.; Khramov, A.E.

2003-01-01

The set of the unstable periodic space-time states, characterizing the chaotic space-time dynamics of the electron beam with the supercritical current in the Pierce diode is discussed. The Lyapunov indicators of the revealed instable space-time states of the chaotic dynamics of the distributed self-excited system are calculated. It is shown that change in the set of the unstable periodic states in dependence on the Pierce parameter is determined by change in the various orbits stability, which is demonstrated by the values of senior Lyapunov unstable state index [ru

An Online Causal Inference Framework for Modeling and Designing Systems Involving User Preferences: A State-Space Approach

Directory of Open Access Journals (Sweden)

Ibrahim Delibalta

2017-01-01

Full Text Available We provide a causal inference framework to model the effects of machine learning algorithms on user preferences. We then use this mathematical model to prove that the overall system can be tuned to alter those preferences in a desired manner. A user can be an online shopper or a social media user, exposed to digital interventions produced by machine learning algorithms. A user preference can be anything from inclination towards a product to a political party affiliation. Our framework uses a state-space model to represent user preferences as latent system parameters which can only be observed indirectly via online user actions such as a purchase activity or social media status updates, shares, blogs, or tweets. Based on these observations, machine learning algorithms produce digital interventions such as targeted advertisements or tweets. We model the effects of these interventions through a causal feedback loop, which alters the corresponding preferences of the user. We then introduce algorithms in order to estimate and later tune the user preferences to a particular desired form. We demonstrate the effectiveness of our algorithms through experiments in different scenarios.

Blending Learning: The Evolution of Online and Face-to-Face Education from 2008-2015. Promising Practices in Blended and Online Learning Series

Science.gov (United States)

Powell, Allison; Watson, John; Staley, Patrick; Patrick, Susan; Horn, Michael; Fetzer, Leslie; Hibbard, Laura; Oglesby, Jonathan; Verma, Sue

2015-01-01

In 2008, the International Association for K-12 Online Learning (iNACOL) produced a series of papers documenting promising practices identified throughout the field of K-12 online learning. Since then, we have witnessed a tremendous acceleration of transformative policy and practice driving personalized learning in the K-12 education space. State,…

Less is more: Sampling chemical space with active learning

Science.gov (United States)

Smith, Justin S.; Nebgen, Ben; Lubbers, Nicholas; Isayev, Olexandr; Roitberg, Adrian E.

2018-06-01

The development of accurate and transferable machine learning (ML) potentials for predicting molecular energetics is a challenging task. The process of data generation to train such ML potentials is a task neither well understood nor researched in detail. In this work, we present a fully automated approach for the generation of datasets with the intent of training universal ML potentials. It is based on the concept of active learning (AL) via Query by Committee (QBC), which uses the disagreement between an ensemble of ML potentials to infer the reliability of the ensemble's prediction. QBC allows the presented AL algorithm to automatically sample regions of chemical space where the ML potential fails to accurately predict the potential energy. AL improves the overall fitness of ANAKIN-ME (ANI) deep learning potentials in rigorous test cases by mitigating human biases in deciding what new training data to use. AL also reduces the training set size to a fraction of the data required when using naive random sampling techniques. To provide validation of our AL approach, we develop the COmprehensive Machine-learning Potential (COMP6) benchmark (publicly available on GitHub) which contains a diverse set of organic molecules. Active learning-based ANI potentials outperform the original random sampled ANI-1 potential with only 10% of the data, while the final active learning-based model vastly outperforms ANI-1 on the COMP6 benchmark after training to only 25% of the data. Finally, we show that our proposed AL technique develops a universal ANI potential (ANI-1x) that provides accurate energy and force predictions on the entire COMP6 benchmark. This universal ML potential achieves a level of accuracy on par with the best ML potentials for single molecules or materials, while remaining applicable to the general class of organic molecules composed of the elements CHNO.

Secondary structure classification of amino-acid sequences using state-space modeling

OpenAIRE

Brunnert, Marcus; Krahnke, Tillmann; Urfer, Wolfgang

2001-01-01

The secondary structure classification of amino acid sequences can be carried out by a statistical analysis of sequence and structure data using state-space models. Aiming at this classification, a modified filter algorithm programmed in S is applied to data of three proteins. The application leads to correct classifications of two proteins even when using relatively simple estimation methods for the parameters of the state-space models. Furthermore, it has been shown that the assumed initial...

A Learning Patterns Perspective on Student Learning in Higher Education: State of the Art and Moving Forward

Science.gov (United States)

Vermunt, Jan D.; Donche, Vincent

2017-01-01

The aim of this article is to review the state of the art of research and theory development on student learning patterns in higher education and beyond. First, the learning patterns perspective and the theoretical framework are introduced. Second, research published since 2004 on student learning patterns is systematically identified and…

State-Space Geometry, Statistical Fluctuations, and Black Holes in String Theory

Directory of Open Access Journals (Sweden)

Stefano Bellucci

2014-01-01

Full Text Available We study the state-space geometry of various extremal and nonextremal black holes in string theory. From the notion of the intrinsic geometry, we offer a state-space perspective to the black hole vacuum fluctuations. For a given black hole entropy, we explicate the intrinsic geometric meaning of the statistical fluctuations, local and global stability conditions, and long range statistical correlations. We provide a set of physical motivations pertaining to the extremal and nonextremal black holes, namely, the meaning of the chemical geometry and physics of correlation. We illustrate the state-space configurations for general charge extremal black holes. In sequel, we extend our analysis for various possible charge and anticharge nonextremal black holes. From the perspective of statistical fluctuation theory, we offer general remarks, future directions, and open issues towards the intrinsic geometric understanding of the vacuum fluctuations and black holes in string theory.

A Markovian state-space framework for integrating flexibility into space system design decisions

Science.gov (United States)

Lafleur, Jarret M.

The past decades have seen the state of the art in aerospace system design progress from a scope of simple optimization to one including robustness, with the objective of permitting a single system to perform well even in off-nominal future environments. Integrating flexibility, or the capability to easily modify a system after it has been fielded in response to changing environments, into system design represents a further step forward. One challenge in accomplishing this rests in that the decision-maker must consider not only the present system design decision, but also sequential future design and operation decisions. Despite extensive interest in the topic, the state of the art in designing flexibility into aerospace systems, and particularly space systems, tends to be limited to analyses that are qualitative, deterministic, single-objective, and/or limited to consider a single future time period. To address these gaps, this thesis develops a stochastic, multi-objective, and multi-period framework for integrating flexibility into space system design decisions. Central to the framework are five steps. First, system configuration options are identified and costs of switching from one configuration to another are compiled into a cost transition matrix. Second, probabilities that demand on the system will transition from one mission to another are compiled into a mission demand Markov chain. Third, one performance matrix for each design objective is populated to describe how well the identified system configurations perform in each of the identified mission demand environments. The fourth step employs multi-period decision analysis techniques, including Markov decision processes from the field of operations research, to find efficient paths and policies a decision-maker may follow. The final step examines the implications of these paths and policies for the primary goal of informing initial system selection. Overall, this thesis unifies state-centric concepts of

Augmented Reality and Mobile Learning: The State of the Art

Science.gov (United States)

FitzGerald, Elizabeth; Ferguson, Rebecca; Adams, Anne; Gaved, Mark; Mor, Yishay; Thomas, Rhodri

2013-01-01

In this paper, the authors examine the state of the art in augmented reality (AR) for mobile learning. Previous work in the field of mobile learning has included AR as a component of a wider toolkit but little has been done to discuss the phenomenon in detail or to examine in a balanced fashion its potential for learning, identifying both positive…

A state space algorithm for the spectral factorization

NARCIS (Netherlands)

Kraffer, F.; Kraffer, F.; Kwakernaak, H.

1997-01-01

This paper presents an algorithm for the spectral factorization of a para-Hermitian polynomial matrix. The algorithm is based on polynomial matrix to state space and vice versa conversions, and avoids elementary polynomial operations in computations; It relies on well-proven methods of numerical

Embedding a State Space Model Into a Markov Decision Process

DEFF Research Database (Denmark)

Nielsen, Lars Relund; Jørgensen, Erik; Højsgaard, Søren

2011-01-01

In agriculture Markov decision processes (MDPs) with finite state and action space are often used to model sequential decision making over time. For instance, states in the process represent possible levels of traits of the animal and transition probabilities are based on biological models...

Bayesian state space models for dynamic genetic network construction across multiple tissues.

Science.gov (United States)

Liang, Yulan; Kelemen, Arpad

2016-08-01

Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes.

Adaptive Learning in Cartesian Product of Reproducing Kernel Hilbert Spaces

OpenAIRE

Yukawa, Masahiro

2014-01-01

We propose a novel adaptive learning algorithm based on iterative orthogonal projections in the Cartesian product of multiple reproducing kernel Hilbert spaces (RKHSs). The task is estimating/tracking nonlinear functions which are supposed to contain multiple components such as (i) linear and nonlinear components, (ii) high- and low- frequency components etc. In this case, the use of multiple RKHSs permits a compact representation of multicomponent functions. The proposed algorithm is where t...

The State of Educators' Professional Learning in British Columbia: Executive Summary

Science.gov (United States)

Brown, Sherri; Hales, Anne; Kuehn, Larry; Steffensen, Karen

2016-01-01

Coinciding with the 2016 Annual Conference in Vancouver, British Columbia, Learning Forward commissioned and supported a study of professional learning across the nation of Canada entitled "The State of Educators' Professional Learning in Canada." A research team led by Carol Campbell, Associate Professor of Leadership and Educational…

State-space dimensionality in short-memory hidden-variable theories

International Nuclear Information System (INIS)

Montina, Alberto

2011-01-01

Recently we have presented a hidden-variable model of measurements for a qubit where the hidden-variable state-space dimension is one-half the quantum-state manifold dimension. The absence of a short memory (Markov) dynamics is the price paid for this dimensional reduction. The conflict between having the Markov property and achieving the dimensional reduction was proved by Montina [A. Montina, Phys. Rev. A 77, 022104 (2008)] using an additional hypothesis of trajectory relaxation. Here we analyze in more detail this hypothesis introducing the concept of invertible process and report a proof that makes clearer the role played by the topology of the hidden-variable space. This is accomplished by requiring suitable properties of regularity of the conditional probability governing the dynamics. In the case of minimal dimension the set of continuous hidden variables is identified with an object living an N-dimensional Hilbert space whose dynamics is described by the Schroedinger equation. A method for generating the economical non-Markovian model for the qubit is also presented.

Contesting a linguistic space: A case in the teaching and learning of ...

African Journals Online (AJOL)

The paper aims to highlight a contesting linguistic space, investigating the impact and the significance of code-switching in the teaching and learning of African languages in private schools. This research was undertaken in three private schools in the Limpopo Province in South Africa. In these schools English is prescribed ...

Perceptions of Online Learning Spaces and Their Incorporation in Mathematics Teacher Education

Science.gov (United States)

Moore-Russo, Deborah; Wilsey, Jillian; Grabowski, Jeremiah; Bampton, Tina M.

2015-01-01

While digital environments can offer convenient, viable options for preservice and inservice teachers to engage in or continue their studies, little is known about teachers' experiences with and perceptions of various existing online learning spaces. This paper describes an initial investigation using data from a group of preservice and in-service…

Mixture estimation with state-space components and Markov model of switching

Czech Academy of Sciences Publication Activity Database

Nagy, Ivan; Suzdaleva, Evgenia

2013-01-01

Roč. 37, č. 24 (2013), s. 9970-9984 ISSN 0307-904X R&D Projects: GA TA ČR TA01030123 Institutional support: RVO:67985556 Keywords : probabilistic dynamic mixtures, * probability density function * state-space models * recursive mixture estimation * Bayesian dynamic decision making under uncertainty * Kerridge inaccuracy Subject RIV: BC - Control Systems Theory Impact factor: 2.158, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/nagy-mixture estimation with state-space components and markov model of switching.pdf

A Connected Space for Early Experiential Learning in Teacher Education

Directory of Open Access Journals (Sweden)

Yong Yu

2016-11-01

Full Text Available Carefully constructed field-based experiences in teacher education programs have been recognized as one of the essential conditions for effective teacher learning. Most college/university-based teacher education programs, however, are still dominated by the epistemology that academic knowledge is the authoritative source of knowledge about teaching, while spaces outside the college classroom remain the “practice fields.” This study examined Project CONNECT (PC, an after-school program designed to create early experiential learning opportunities for pre-service teachers (PSTs by bringing together different aspects of expertise from the schools, communities, and universities. Pre-service teachers in this study worked with children one afternoon a week in school-based sites during their sophomore and junior years. Case study was adopted to assess the impact of the experience on teacher learning and the factors contributing to the effect. Multiple data sources, including weekly reflection journals, field observation notes, and an exit survey were collected and analyzed. Results revealed participants’ transformation of professional identity, and development of professional skills and dispositions. Several factors emerged as important to PSTs’ learning throughout the experience, including connections between the course and the program, quality of faculty supervision, and systematic reflection. Implications for teacher education were discussed.

Quantum learning: asymptotically optimal classification of qubit states

International Nuclear Information System (INIS)

Guta, Madalin; Kotlowski, Wojciech

2010-01-01

Pattern recognition is a central topic in learning theory, with numerous applications such as voice and text recognition, image analysis and computer diagnosis. The statistical setup in classification is the following: we are given an i.i.d. training set (X 1 , Y 1 ), ... , (X n , Y n ), where X i represents a feature and Y i in{0, 1} is a label attached to that feature. The underlying joint distribution of (X, Y) is unknown, but we can learn about it from the training set, and we aim at devising low error classifiers f: X→Y used to predict the label of new incoming features. In this paper, we solve a quantum analogue of this problem, namely the classification of two arbitrary unknown mixed qubit states. Given a number of 'training' copies from each of the states, we would like to 'learn' about them by performing a measurement on the training set. The outcome is then used to design measurements for the classification of future systems with unknown labels. We found the asymptotically optimal classification strategy and show that typically it performs strictly better than a plug-in strategy, which consists of estimating the states separately and then discriminating between them using the Helstrom measurement. The figure of merit is given by the excess risk equal to the difference between the probability of error and the probability of error of the optimal measurement for known states. We show that the excess risk scales as n -1 and compute the exact constant of the rate.

Spaces of homotopy self-equivalences a survey

CERN Document Server

Rutter, John W

1997-01-01

This survey covers groups of homotopy self-equivalence classes of topological spaces, and the homotopy type of spaces of homotopy self-equivalences. For manifolds, the full group of equivalences and the mapping class group are compared, as are the corresponding spaces. Included are methods of calculation, numerous calculations, finite generation results, Whitehead torsion and other areas. Some 330 references are given. The book assumes familiarity with cell complexes, homology and homotopy. Graduate students and established researchers can use it for learning, for reference, and to determine the current state of knowledge.

An Embeddable Virtual Machine for State Space Generation

NARCIS (Netherlands)

Weber, M.; Bosnacki, D.; Edelkamp, S.

2007-01-01

The semantics of modelling languages are not always specified in a precise and formal way, and their rather complex underlying models make it a non-trivial exercise to reuse them in newly developed tools. We report on experiments with a virtual machine-based approach for state space generation. The

Which Way is Up? Lessons Learned from Space Shuttle Sensorimotor Research

Science.gov (United States)

Wood, S. J.; Reschke, M. F.; Harm, D. L.; Paloski, W. H.; Bloomberg, J. J.

2011-01-01

.g., sensory aids) will have both space and Earth-based applications. Early postflight field tests are recommended to provide the evidence base for best practices for future commercial flight programs. Learning Objective: Overview of the Space Shuttle Program regarding adaptive changes in sensorimotor function, including what was learned from research, what was implemented for medical operations, and what is recommended for commercial flights.

Action Research to Improve the Learning Space for Diagnostic Techniques

Directory of Open Access Journals (Sweden)

Ellen Ariel

2015-08-01

Full Text Available The module described and evaluated here was created in response to perceived learning difficulties in diagnostic test design and interpretation for students in third-year Clinical Microbiology. Previously, the activities in lectures and laboratory classes in the module fell into the lower cognitive operations of “knowledge” and “understanding.” The new approach was to exchange part of the traditional activities with elements of interactive learning, where students had the opportunity to engage in deep learning using a variety of learning styles. The effectiveness of the new curriculum was assessed by means of on-course student assessment throughout the module, a final exam, an anonymous questionnaire on student evaluation of the different activities and a focus group of volunteers. Although the new curriculum enabled a major part of the student cohort to achieve higher pass grades (p < 0.001, it did not meet the requirements of the weaker students, and the proportion of the students failing the module remained at 34%. The action research applied here provided a number of valuable suggestions from students on how to improve future curricula from their perspective. Most importantly, an interactive online program that facilitated flexibility in the learning space for the different reagents and their interaction in diagnostic tests was proposed. The methods applied to improve and assess a curriculum refresh by involving students as partners in the process, as well as the outcomes, are discussed.

Action Research to Improve the Learning Space for Diagnostic Techniques.

Science.gov (United States)

Ariel, Ellen; Owens, Leigh

2015-12-01

The module described and evaluated here was created in response to perceived learning difficulties in diagnostic test design and interpretation for students in third-year Clinical Microbiology. Previously, the activities in lectures and laboratory classes in the module fell into the lower cognitive operations of "knowledge" and "understanding." The new approach was to exchange part of the traditional activities with elements of interactive learning, where students had the opportunity to engage in deep learning using a variety of learning styles. The effectiveness of the new curriculum was assessed by means of on-course student assessment throughout the module, a final exam, an anonymous questionnaire on student evaluation of the different activities and a focus group of volunteers. Although the new curriculum enabled a major part of the student cohort to achieve higher pass grades (p < 0.001), it did not meet the requirements of the weaker students, and the proportion of the students failing the module remained at 34%. The action research applied here provided a number of valuable suggestions from students on how to improve future curricula from their perspective. Most importantly, an interactive online program that facilitated flexibility in the learning space for the different reagents and their interaction in diagnostic tests was proposed. The methods applied to improve and assess a curriculum refresh by involving students as partners in the process, as well as the outcomes, are discussed. Journal of Microbiology & Biology Education.

On classical state space realizability of bilinear inout-output differential equations

OpenAIRE

Kotta, U.; Mullari, T.; Kotta, P.; Zinober, A.S.I.

2006-01-01

This paper studies the realizability property of continuous-time bilinear i/o equations in the classical state space form. Constraints on the parameters of the bilinear i/o model are suggested that lead to realizable models. The paper proves that the 2nd order bilinear i/o differential equation, unlike the discrete-time case, is always realizable in the classical state space form. The complete list of 3rd and 4th order realizable i/o bilinear models is given and two subclasses of realizable i...

Impact of Spacing of Practice on Learning Brand Name and Generic Drugs.

Science.gov (United States)

Terenyi, James; Anksorus, Heidi; Persky, Adam M

2018-02-01

Objective. To test the impact of schedules of retrieval practice on learning brand and generic name drug information in a self-paced course. Methods. Students completed weekly quizzes on brand and generic name conversions for 100 commonly prescribed drugs. Each student completed part of the drug list on a schedule of equal, expanding, or contracting spacing, one practice (massed) or study only in a partial block design. Results. On measures of long-term retention, the contracting spacing schedule led to superior retention (67%) compared to the massed practice (50%) and study-only condition (46%); contracting practice also was significantly higher than expanding practice (58%,) or equal practice (59%). Overall performance decreased by almost 50% (final exam 95%, long-term retention 55%) over a 6-week period. Conclusion. A contracting spacing schedule was the most effective schedule of practice, and all spacing schedules were superior to massed practice or study-only conditions.

Solid State Pathways towards Molecular Complexity in Space

Science.gov (United States)

Linnartz, Harold; Bossa, Jean-Baptiste; Bouwman, Jordy; Cuppen, Herma M.; Cuylle, Steven H.; van Dishoeck, Ewine F.; Fayolle, Edith C.; Fedoseev, Gleb; Fuchs, Guido W.; Ioppolo, Sergio; Isokoski, Karoliina; Lamberts, Thanja; Öberg, Karin I.; Romanzin, Claire; Tenenbaum, Emily; Zhen, Junfeng

2011-12-01

It has been a long standing problem in astrochemistry to explain how molecules can form in a highly dilute environment such as the interstellar medium. In the last decennium more and more evidence has been found that the observed mix of small and complex, stable and highly transient species in space is the cumulative result of gas phase and solid state reactions as well as gas-grain interactions. Solid state reactions on icy dust grains are specifically found to play an important role in the formation of the more complex ``organic'' compounds. In order to investigate the underlying physical and chemical processes detailed laboratory based experiments are needed that simulate surface reactions triggered by processes as different as thermal heating, photon (UV) irradiation and particle (atom, cosmic ray, electron) bombardment of interstellar ice analogues. Here, some of the latest research performed in the Sackler Laboratory for Astrophysics in Leiden, the Netherlands is reviewed. The focus is on hydrogenation, i.e., H-atom addition reactions and vacuum ultraviolet irradiation of interstellar ice analogues at astronomically relevant temperatures. It is shown that solid state processes are crucial in the chemical evolution of the interstellar medium, providing pathways towards molecular complexity in space.

Feel the Fear: Learning Graphic Design in Affective Places and Online Spaces

Science.gov (United States)

Nottingham, Anitra

2017-01-01

This article explores the idea of pedagogic affect in both onsite and online graphic design learning spaces, and speculates on the role that this affect plays in the formation of the design student. I argue that embodied design knowledge is built by interactions with design professionals, activities that mimic the daily work of designers, and…

THE STATE OF GREEN SPACES IN KUMASI CITY (GHANA: LESSONS FOR OTHER AFRICAN CITIES

Directory of Open Access Journals (Sweden)

Collins ADJEI MENSAH

2016-12-01

Full Text Available Integrating green spaces such as parks and gardens into the physical landscape of cities has been identified to enhance the health and wellbeing of urban dwellers. This paper assesses the state of green spaces in Kumasi city (Ghana, once known as the garden city of West Africa. Using a case study approach, a mixture of qualitative research techniques were employed whilst a set of eight themes were put together to guide the assessment. In all, green spaces were found to be in poor state. With the exception of conservation and heritage theme, the remaining seven themes that were used for the assessment all found the green spaces to be in poor state. It is therefore recommended that there should be an attitudinal change towards the maintenance of green spaces, the application of a collaborative governance approach, and priority giving to green spaces in all development agendas by city authorities.

Learning organisations: the challenge of finding a safe space in a climate of accountability.

Science.gov (United States)

McKee, Anne

2017-03-01

The effects of health policy reforms over a twenty-five year period have changed the NHS as a place in which to work and learn. Some of these changes have had unintentional consequences for learning in the workplace. A recent King's Fund contribution to quality improvement debates included an extensive review of NHS policies encouraging change 'from within' the NHS and renewed calls to develop learning organisations there. I draw upon an action research project designed to develop learning organisations in primary care to locate quality improvement debates amid the realities of practice. The project identified key challenges primary care practices encountered to protect time and space for this form of work based learning, even when they recognised the need for it and wanted to engage in it. Implications for policy makers, primary care practices and health professional educationalists are identified.

Continuous residual reinforcement learning for traffic signal control optimization

NARCIS (Netherlands)

Aslani, Mohammad; Seipel, Stefan; Wiering, Marco

2018-01-01

Traffic signal control can be naturally regarded as a reinforcement learning problem. Unfortunately, it is one of the most difficult classes of reinforcement learning problems owing to its large state space. A straightforward approach to address this challenge is to control traffic signals based on

Machine Learning Applications to Resting-State Functional MR Imaging Analysis.

Science.gov (United States)

Billings, John M; Eder, Maxwell; Flood, William C; Dhami, Devendra Singh; Natarajan, Sriraam; Whitlow, Christopher T

2017-11-01

Machine learning is one of the most exciting and rapidly expanding fields within computer science. Academic and commercial research entities are investing in machine learning methods, especially in personalized medicine via patient-level classification. There is great promise that machine learning methods combined with resting state functional MR imaging will aid in diagnosis of disease and guide potential treatment for conditions thought to be impossible to identify based on imaging alone, such as psychiatric disorders. We discuss machine learning methods and explore recent advances. Copyright © 2017 Elsevier Inc. All rights reserved.

Mobile Robot Navigation Based on Q-Learning Technique

Directory of Open Access Journals (Sweden)

Lazhar Khriji

2011-03-01

Full Text Available This paper shows how Q-learning approach can be used in a successful way to deal with the problem of mobile robot navigation. In real situations where a large number of obstacles are involved, normal Q-learning approach would encounter two major problems due to excessively large state space. First, learning the Q-values in tabular form may be infeasible because of the excessive amount of memory needed to store the table. Second, rewards in the state space may be so sparse that with random exploration they will only be discovered extremely slowly. In this paper, we propose a navigation approach for mobile robot, in which the prior knowledge is used within Q-learning. We address the issue of individual behavior design using fuzzy logic. The strategy of behaviors based navigation reduces the complexity of the navigation problem by dividing them in small actions easier for design and implementation. The Q-Learning algorithm is applied to coordinate between these behaviors, which make a great reduction in learning convergence times. Simulation and experimental results confirm the convergence to the desired results in terms of saved time and computational resources.

An Exploration of Secondary Students' Mental States When Learning about Acids and Bases

Science.gov (United States)

Liu, Chia-Ju; Hou, I-Lin; Chiu, Houn-Lin; Treagust, David F.

2014-01-01

This study explored factors of students' mental states, including emotion, intention, internal mental representation, and external mental representation, which can affect their learning performance. In evaluating students' mental states during the science learning process and the relationship between mental states and learning…

IntlUni - The Challenges of the Multilingual and Multicultural Learning Space in the International University

DEFF Research Database (Denmark)

Lauridsen, Karen M.

IntlUni: The challenges of the multilingual and multicultural learning space in the international university The past decade has witnessed an unprecedented increase in the internationalisation of higher education. This means that more people in higher education than ever before are teaching...... education adds value – or has the potential to add value – to the programmes offered and the learning outcomes achieved by students, the overarching aim of IntlUni is to identify the quality criteria that characterize or should characterize teaching and learning in the multilingual and multicultural...

Engagement states and learning from educational games.

Science.gov (United States)

Deater-Deckard, Kirby; Chang, Mido; Evans, Michael E

2013-01-01

Children's and adolescents' cognitive, affective, and behavioral states of engagement enhance or impede enjoyment of, and performance with, educational games. We propose a comprehensive model of engagement states and apply it to research on educational game development and research on the role of various aspects of engagement on game play and learning. Emphasis is placed on individual differences in attention, memory, motor speed and control, persistence, and positive and negative affect (approach/avoidance), and how these pertain to social cognitions regarding mathematics achievement. Our challenge is to develop educational games that are effective for a wide variety of student engagement states. Copyright © 2013 Wiley Periodicals, Inc., A Wiley Company.

Unpacking Virtual and Intercultural Spaces: A Presentation of a Conceptual Framework to Investigate the Connection between Technology and Intercultural Learning

DEFF Research Database (Denmark)

Pedersen, Rikke; Jørgensen, Mette; Harrison, Roger

This paper presents a framework for the development of research within the emerging areas of internationalisation and technology that connect to build potential learning spaces within intercultural and global settings.......This paper presents a framework for the development of research within the emerging areas of internationalisation and technology that connect to build potential learning spaces within intercultural and global settings....

State space model extraction of thermohydraulic systems – Part I: A linear graph approach

International Nuclear Information System (INIS)

Uren, K.R.; Schoor, G. van

2013-01-01

Thermohydraulic simulation codes are increasingly making use of graphical design interfaces. The user can quickly and easily design a thermohydraulic system by placing symbols on the screen resembling system components. These components can then be connected to form a system representation. Such system models may then be used to obtain detailed simulations of the physical system. Usually this kind of simulation models are too complex and not ideal for control system design. Therefore, a need exists for automated techniques to extract lumped parameter models useful for control system design. The goal of this first paper, in a two part series, is to propose a method that utilises a graphical representation of a thermohydraulic system, and a lumped parameter modelling approach, to extract state space models. In this methodology each physical domain of the thermohydraulic system is represented by a linear graph. These linear graphs capture the interaction between all components within and across energy domains – hydraulic, thermal and mechanical. These linear graphs are analysed using a graph-theoretic approach to derive reduced order state space models. These models capture the dominant dynamics of the thermohydraulic system and are ideal for control system design purposes. The proposed state space model extraction method is demonstrated by considering a U-tube system. A non-linear state space model is extracted representing both the hydraulic and thermal domain dynamics of the system. The simulated state space model is compared with a Flownex ® model of the U-tube. Flownex ® is a validated systems thermal-fluid simulation software package. - Highlights: • A state space model extraction methodology based on graph-theoretic concepts. • An energy-based approach to consider multi-domain systems in a common framework. • Allow extraction of transparent (white-box) state space models automatically. • Reduced order models containing only independent state

Designing flexible instructional space for teaching introductory physics with emphasis on inquiry and collaborative active learning

Science.gov (United States)

Bykov, Tikhon

2010-03-01

In recent years McMurry University's introductory physics curriculum has gone through a series of significant changes to achieve better integration of traditional course components (lecture/lab/discussion) by means of instructional design and technology. A system of flexible curriculum modules with emphasis on inquiry-based teaching and collaborative active learning has been introduced. To unify module elements, a technology suite has been used that consists of Tablet PC's and software applications including Physlets, tablet-adapted personal response system, PASCO data acquisition systems, and MS One-note collaborative writing software. Adoption of the new teaching model resulted in reevaluation of existing instructional spaces. The new teaching space will be created during the renovation of the McMurry Science Building. This space will allow for easy transitions between lecture and laboratory modes. Movable partitions will be used to accommodate student groups of different sizes. The space will be supportive of small peer-group activities with easy-to-reconfigure furniture, multiple white and black board surfaces and multiple projection screens. The new space will be highly flexible to account for different teaching functions, different teaching modes and learning styles.

Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions.

Science.gov (United States)

Akkus, Zeynettin; Galimzianova, Alfiia; Hoogi, Assaf; Rubin, Daniel L; Erickson, Bradley J

2017-08-01

Quantitative analysis of brain MRI is routine for many neurological diseases and conditions and relies on accurate segmentation of structures of interest. Deep learning-based segmentation approaches for brain MRI are gaining interest due to their self-learning and generalization ability over large amounts of data. As the deep learning architectures are becoming more mature, they gradually outperform previous state-of-the-art classical machine learning algorithms. This review aims to provide an overview of current deep learning-based segmentation approaches for quantitative brain MRI. First we review the current deep learning architectures used for segmentation of anatomical brain structures and brain lesions. Next, the performance, speed, and properties of deep learning approaches are summarized and discussed. Finally, we provide a critical assessment of the current state and identify likely future developments and trends.

Manifold Regularized Reinforcement Learning.

Science.gov (United States)

Li, Hongliang; Liu, Derong; Wang, Ding

2018-04-01

This paper introduces a novel manifold regularized reinforcement learning scheme for continuous Markov decision processes. Smooth feature representations for value function approximation can be automatically learned using the unsupervised manifold regularization method. The learned features are data-driven, and can be adapted to the geometry of the state space. Furthermore, the scheme provides a direct basis representation extension for novel samples during policy learning and control. The performance of the proposed scheme is evaluated on two benchmark control tasks, i.e., the inverted pendulum and the energy storage problem. Simulation results illustrate the concepts of the proposed scheme and show that it can obtain excellent performance.

Study on Space Audit Assessment Criteria for Public Higher Education Institution in Malaysia: Space Capacity Assessment

Directory of Open Access Journals (Sweden)

Wan Hamdan Wan Samsul Zamani

2016-01-01

Full Text Available The aim of this study is to measure the capacity rate of learning space based on the as-built drawing provided by the institutions or if the as-built drawing is missing, the researcher have to prepare measured drawing as per actual on site. The learning space Capacity Index is developed by analyzing the space design in as-built drawing or measured drawing and the list of learning spaces available at the institution. The Capacity Index is classified according to the level of Usable Floor Area (UFA and Occupancy Load (OL according to learning space design capacity. The classification of Capacity Index is demonstrated through linguistic value and the color-coded key. From the said index, the institution can easily identify whether the existing learning space is currently best used or vice versa and standard space planning compliance in Malaysia Public Higher Education Institutions. The data will assist the management to clarify whether to maximize the use of existing space or to request for new learning space.

Evaluating abundance and trends in a Hawaiian avian community using state-space analysis

Science.gov (United States)

Camp, Richard J.; Brinck, Kevin W.; Gorresen, P.M.; Paxton, Eben H.

2016-01-01

Estimating population abundances and patterns of change over time are important in both ecology and conservation. Trend assessment typically entails fitting a regression to a time series of abundances to estimate population trajectory. However, changes in abundance estimates from year-to-year across time are due to both true variation in population size (process variation) and variation due to imperfect sampling and model fit. State-space models are a relatively new method that can be used to partition the error components and quantify trends based only on process variation. We compare a state-space modelling approach with a more traditional linear regression approach to assess trends in uncorrected raw counts and detection-corrected abundance estimates of forest birds at Hakalau Forest National Wildlife Refuge, Hawai‘i. Most species demonstrated similar trends using either method. In general, evidence for trends using state-space models was less strong than for linear regression, as measured by estimates of precision. However, while the state-space models may sacrifice precision, the expectation is that these estimates provide a better representation of the real world biological processes of interest because they are partitioning process variation (environmental and demographic variation) and observation variation (sampling and model variation). The state-space approach also provides annual estimates of abundance which can be used by managers to set conservation strategies, and can be linked to factors that vary by year, such as climate, to better understand processes that drive population trends.

The Learning Disabilities Unit at the State College of Optometry/SUNY.

Science.gov (United States)

Solan, Harold A.; Springer, Florence E.

1986-01-01

The Learning Disabilities Unit of New York's State College of Optometry, providing testing and research for learning disabled adults and children and professional instruction and clinical experience for students of optometry and related fields, is described. (MSE)

Which Space? Whose Space? An Experience in Involving Students and Teachers in Space Design

Science.gov (United States)

Casanova, Diogo; Di Napoli, Roberto; Leijon, Marie

2018-01-01

To date, learning spaces in higher education have been designed with little engagement on the part of their most important users: students and teachers. In this paper, we present the results of research carried out in a UK university. The research aimed to understand how students and teachers conceptualise learning spaces when they are given the…

An evaluation of behavior inferences from Bayesian state-space models: A case study with the Pacific walrus

Science.gov (United States)

Beatty, William; Jay, Chadwick V.; Fischbach, Anthony S.

2016-01-01

State-space models offer researchers an objective approach to modeling complex animal location data sets, and state-space model behavior classifications are often assumed to have a link to animal behavior. In this study, we evaluated the behavioral classification accuracy of a Bayesian state-space model in Pacific walruses using Argos satellite tags with sensors to detect animal behavior in real time. We fit a two-state discrete-time continuous-space Bayesian state-space model to data from 306 Pacific walruses tagged in the Chukchi Sea. We matched predicted locations and behaviors from the state-space model (resident, transient behavior) to true animal behavior (foraging, swimming, hauled out) and evaluated classification accuracy with kappa statistics (κ) and root mean square error (RMSE). In addition, we compared biased random bridge utilization distributions generated with resident behavior locations to true foraging behavior locations to evaluate differences in space use patterns. Results indicated that the two-state model fairly classified true animal behavior (0.06 ≤ κ ≤ 0.26, 0.49 ≤ RMSE ≤ 0.59). Kernel overlap metrics indicated utilization distributions generated with resident behavior locations were generally smaller than utilization distributions generated with true foraging behavior locations. Consequently, we encourage researchers to carefully examine parameters and priors associated with behaviors in state-space models, and reconcile these parameters with the study species and its expected behaviors.

Learning about Student Research Practices through an Ethnographic Investigation: Insights into Contact with Librarians and Use of Library Space

Directory of Open Access Journals (Sweden)

Eamon Tewell

2017-12-01

Full Text Available Abstract Objective – Student research habits and expectations continue to change, complicating the design of library spaces and the provision of research support. This study’s intent was to explore undergraduate and graduate student research and study needs at a mid-sized university’s two campuses in the Northeastern United States, and to improve librarians’ understandings of these practices so that more appropriate services and spaces may be developed to support student learning. Methods – The research project utilized a primarily qualitative design for data collection that spanned from fall 2012 to summer 2013, consisting of an online questionnaire, unobtrusive observations, and in-depth semi-structured interviews. Data collection commenced with a questionnaire consisting of 51 items, distributed through campus email to all students and receiving 1182 responses. Second, 32 hours of unobtrusive observations were carried out by librarians, who took ethnographic “field notes” in a variety of Library locations during different times and days of the week. The final method was in-depth interviews conducted with 30 undergraduate and graduate students. The qualitative data were analyzed through the application of a codebook consisting of 459 codes, developed by a data analysis team of 4 librarians. Results – The results address topical areas of student interactions with librarians, contact preferences, and use of library space. Of the interviewees, 60% contacted a librarian at least once, with texting being the most popular method of contact (27%. In being contacted by the library, students preferred a range of methods and generally indicated interest in learning about library news and events through posters and signage. Participants were less interested in receiving library contact via social media, such as Facebook or Twitter. Regarding student use of and preference for library space, prominent themes were students creating their own

Machine learning techniques in optical communication

DEFF Research Database (Denmark)

Zibar, Darko; Piels, Molly; Jones, Rasmus Thomas

2015-01-01

Techniques from the machine learning community are reviewed and employed for laser characterization, signal detection in the presence of nonlinear phase noise, and nonlinearity mitigation. Bayesian filtering and expectation maximization are employed within nonlinear state-space framework...

Early Childhood Studies--Students' Participation in the Development of a Learning Space in a Higher Education Institution

Science.gov (United States)

Kanyal, Mallika

2014-01-01

The article argues for the participation and involvement of students in developing learning spaces within higher education. In early childhood education there is a strong emphasis upon rights, democracy and planning learning through listening to young children. Taking inspiration from this, the study explores the use of participatory approaches in…

Limitations Of The Current State Space Modelling Approach In Multistage Machining Processes Due To Operation Variations

Science.gov (United States)

Abellán-Nebot, J. V.; Liu, J.; Romero, F.

2009-11-01

The State Space modelling approach has been recently proposed as an engineering-driven technique for part quality prediction in Multistage Machining Processes (MMP). Current State Space models incorporate fixture and datum variations in the multi-stage variation propagation, without explicitly considering common operation variations such as machine-tool thermal distortions, cutting-tool wear, cutting-tool deflections, etc. This paper shows the limitations of the current State Space model through an experimental case study where the effect of the spindle thermal expansion, cutting-tool flank wear and locator errors are introduced. The paper also discusses the extension of the current State Space model to include operation variations and its potential benefits.

A reward optimization method based on action subrewards in hierarchical reinforcement learning.

Science.gov (United States)

Fu, Yuchen; Liu, Quan; Ling, Xionghong; Cui, Zhiming

2014-01-01

Reinforcement learning (RL) is one kind of interactive learning methods. Its main characteristics are "trial and error" and "related reward." A hierarchical reinforcement learning method based on action subrewards is proposed to solve the problem of "curse of dimensionality," which means that the states space will grow exponentially in the number of features and low convergence speed. The method can reduce state spaces greatly and choose actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed. Apply it to the online learning in Tetris game, and the experiment result shows that the convergence speed of this algorithm can be enhanced evidently based on the new method which combines hierarchical reinforcement learning algorithm and action subrewards. The "curse of dimensionality" problem is also solved to a certain extent with hierarchical method. All the performance with different parameters is compared and analyzed as well.

Balancing through episodic learning

DEFF Research Database (Denmark)

Scheuer, John Damm

2013-01-01

Peter Jarvis’s theory about learning suggests that human beings learn and change as a result of hearing, seeing, smelling, tasting, touching, and feeling. They change and learn by interacting with other humans, things, and events in certain time-space contexts and by reflecting upon these, as well...... as upon wished-for future states or past experiences, knowledge, and history, and upon what these experiences mean to one’s own self and identity. This chapter explores how female top managers have to reflect and find a balance in their work-family lives on the basis of interaction with, and inputs from...

Functional Contour-following via Haptic Perception and Reinforcement Learning.

Science.gov (United States)

Hellman, Randall B; Tekin, Cem; van der Schaar, Mihaela; Santos, Veronica J

2018-01-01

Many tasks involve the fine manipulation of objects despite limited visual feedback. In such scenarios, tactile and proprioceptive feedback can be leveraged for task completion. We present an approach for real-time haptic perception and decision-making for a haptics-driven, functional contour-following task: the closure of a ziplock bag. This task is challenging for robots because the bag is deformable, transparent, and visually occluded by artificial fingertip sensors that are also compliant. A deep neural net classifier was trained to estimate the state of a zipper within a robot's pinch grasp. A Contextual Multi-Armed Bandit (C-MAB) reinforcement learning algorithm was implemented to maximize cumulative rewards by balancing exploration versus exploitation of the state-action space. The C-MAB learner outperformed a benchmark Q-learner by more efficiently exploring the state-action space while learning a hard-to-code task. The learned C-MAB policy was tested with novel ziplock bag scenarios and contours (wire, rope). Importantly, this work contributes to the development of reinforcement learning approaches that account for limited resources such as hardware life and researcher time. As robots are used to perform complex, physically interactive tasks in unstructured or unmodeled environments, it becomes important to develop methods that enable efficient and effective learning with physical testbeds.

Machine learning techniques in optical communication

DEFF Research Database (Denmark)

Zibar, Darko; Piels, Molly; Jones, Rasmus Thomas

2016-01-01

Machine learning techniques relevant for nonlinearity mitigation, carrier recovery, and nanoscale device characterization are reviewed and employed. Markov Chain Monte Carlo in combination with Bayesian filtering is employed within the nonlinear state-space framework and demonstrated for parameter...

Resting-state low-frequency fluctuations reflect individual differences in spoken language learning.

Science.gov (United States)

Deng, Zhizhou; Chandrasekaran, Bharath; Wang, Suiping; Wong, Patrick C M

2016-03-01

A major challenge in language learning studies is to identify objective, pre-training predictors of success. Variation in the low-frequency fluctuations (LFFs) of spontaneous brain activity measured by resting-state functional magnetic resonance imaging (RS-fMRI) has been found to reflect individual differences in cognitive measures. In the present study, we aimed to investigate the extent to which initial spontaneous brain activity is related to individual differences in spoken language learning. We acquired RS-fMRI data and subsequently trained participants on a sound-to-word learning paradigm in which they learned to use foreign pitch patterns (from Mandarin Chinese) to signal word meaning. We performed amplitude of spontaneous low-frequency fluctuation (ALFF) analysis, graph theory-based analysis, and independent component analysis (ICA) to identify functional components of the LFFs in the resting-state. First, we examined the ALFF as a regional measure and showed that regional ALFFs in the left superior temporal gyrus were positively correlated with learning performance, whereas ALFFs in the default mode network (DMN) regions were negatively correlated with learning performance. Furthermore, the graph theory-based analysis indicated that the degree and local efficiency of the left superior temporal gyrus were positively correlated with learning performance. Finally, the default mode network and several task-positive resting-state networks (RSNs) were identified via the ICA. The "competition" (i.e., negative correlation) between the DMN and the dorsal attention network was negatively correlated with learning performance. Our results demonstrate that a) spontaneous brain activity can predict future language learning outcome without prior hypotheses (e.g., selection of regions of interest--ROIs) and b) both regional dynamics and network-level interactions in the resting brain can account for individual differences in future spoken language learning success

Resting-state low-frequency fluctuations reflect individual differences in spoken language learning

Science.gov (United States)

Deng, Zhizhou; Chandrasekaran, Bharath; Wang, Suiping; Wong, Patrick C.M.

2016-01-01

A major challenge in language learning studies is to identify objective, pre-training predictors of success. Variation in the low-frequency fluctuations (LFFs) of spontaneous brain activity measured by resting-state functional magnetic resonance imaging (RS-fMRI) has been found to reflect individual differences in cognitive measures. In the present study, we aimed to investigate the extent to which initial spontaneous brain activity is related to individual differences in spoken language learning. We acquired RS-fMRI data and subsequently trained participants on a sound-to-word learning paradigm in which they learned to use foreign pitch patterns (from Mandarin Chinese) to signal word meaning. We performed amplitude of spontaneous low-frequency fluctuation (ALFF) analysis, graph theory-based analysis, and independent component analysis (ICA) to identify functional components of the LFFs in the resting-state. First, we examined the ALFF as a regional measure and showed that regional ALFFs in the left superior temporal gyrus were positively correlated with learning performance, whereas ALFFs in the default mode network (DMN) regions were negatively correlated with learning performance. Furthermore, the graph theory-based analysis indicated that the degree and local efficiency of the left superior temporal gyrus were positively correlated with learning performance. Finally, the default mode network and several task-positive resting-state networks (RSNs) were identified via the ICA. The “competition” (i.e., negative correlation) between the DMN and the dorsal attention network was negatively correlated with learning performance. Our results demonstrate that a) spontaneous brain activity can predict future language learning outcome without prior hypotheses (e.g., selection of regions of interest – ROIs) and b) both regional dynamics and network-level interactions in the resting brain can account for individual differences in future spoken language learning success

Solid-State Lighting. Early Lessons Learned on the Way to Market

Energy Technology Data Exchange (ETDEWEB)

Sandahl, L. J.; Cort, K. A.; Gordon, K. L.

2014-01-01

Analysis of issues and lessons learned during the early stages of solid-state lighting market introduction in the U.S., which also summarizes early actions taken to avoid potential problems anticipated based on lessons learned from the market introduction of compact fluorescent lamps.

Reinforcement learning on slow features of high-dimensional input streams.

Directory of Open Access Journals (Sweden)

Robert Legenstein

Full Text Available Humans and animals are able to learn complex behaviors based on a massive stream of sensory information from different modalities. Early animal studies have identified learning mechanisms that are based on reward and punishment such that animals tend to avoid actions that lead to punishment whereas rewarded actions are reinforced. However, most algorithms for reward-based learning are only applicable if the dimensionality of the state-space is sufficiently small or its structure is sufficiently simple. Therefore, the question arises how the problem of learning on high-dimensional data is solved in the brain. In this article, we propose a biologically plausible generic two-stage learning system that can directly be applied to raw high-dimensional input streams. The system is composed of a hierarchical slow feature analysis (SFA network for preprocessing and a simple neural network on top that is trained based on rewards. We demonstrate by computer simulations that this generic architecture is able to learn quite demanding reinforcement learning tasks on high-dimensional visual input streams in a time that is comparable to the time needed when an explicit highly informative low-dimensional state-space representation is given instead of the high-dimensional visual input. The learning speed of the proposed architecture in a task similar to the Morris water maze task is comparable to that found in experimental studies with rats. This study thus supports the hypothesis that slowness learning is one important unsupervised learning principle utilized in the brain to form efficient state representations for behavioral learning.

Lessons learned from the design of chemical space networks and opportunities for new applications

Science.gov (United States)

Vogt, Martin; Stumpfe, Dagmar; Maggiora, Gerald M.; Bajorath, Jürgen

2016-03-01

The concept of chemical space is of fundamental relevance in chemical informatics and computer-aided drug discovery. In a series of articles published in the Journal of Computer- Aided Molecular Design, principles of chemical space design were evaluated, molecular networks proposed as an alternative to conventional coordinate-based chemical reference spaces, and different types of chemical space networks (CSNs) constructed and analyzed. Central to the generation of CSNs was the way in which molecular similarity relationships were assessed and a primary focal point was the network-based representation of biologically relevant chemical space. The design and comparison of CSNs based upon alternative similarity measures can be viewed as an evolutionary path with interesting lessons learned along the way. CSN design has matured to the point that such chemical space representations can be used in practice. In this contribution, highlights from the sequence of CSN design efforts are discussed in context, providing a perspective for future practical applications.

Lessons learned from the design of chemical space networks and opportunities for new applications.

Science.gov (United States)

Vogt, Martin; Stumpfe, Dagmar; Maggiora, Gerald M; Bajorath, Jürgen

2016-03-01

The concept of chemical space is of fundamental relevance in chemical informatics and computer-aided drug discovery. In a series of articles published in the Journal of Computer-Aided Molecular Design, principles of chemical space design were evaluated, molecular networks proposed as an alternative to conventional coordinate-based chemical reference spaces, and different types of chemical space networks (CSNs) constructed and analyzed. Central to the generation of CSNs was the way in which molecular similarity relationships were assessed and a primary focal point was the network-based representation of biologically relevant chemical space. The design and comparison of CSNs based upon alternative similarity measures can be viewed as an evolutionary path with interesting lessons learned along the way. CSN design has matured to the point that such chemical space representations can be used in practice. In this contribution, highlights from the sequence of CSN design efforts are discussed in context, providing a perspective for future practical applications.

Defining Learning Space in a Serious Game in Terms of Operative and Resultant Actions

Science.gov (United States)

Martin, Michael W.; Shen, Yuzhong

2012-01-01

This paper explores the distinction between operative and resultant actions in games, and proposes that the learning space created by a serious game is a function of these actions. Further, it suggests a possible relationship between these actions and the forms of cognitive load imposed upon the game player. Association of specific types of cognitive load with respective forms of actions in game mechanics also presents some heuristics for integrating learning content into serious games. Research indicates that different balances of these types of actions are more suitable for novice or experienced learners. By examining these relationships, we can develop a few basic principles of game design which have an increased potential to promote positive learning outcomes.

Role of state-dependent learning in the cognitive effects of caffeine in mice.

Science.gov (United States)

Sanday, Leandro; Zanin, Karina A; Patti, Camilla L; Fernandes-Santos, Luciano; Oliveira, Larissa C; Longo, Beatriz M; Andersen, Monica L; Tufik, Sergio; Frussa-Filho, Roberto

2013-08-01

Caffeine is the most widely used psychoactive substance in the world and it is generally believed that it promotes beneficial effects on cognitive performance. However, there is also evidence suggesting that caffeine has inhibitory effects on learning and memory. Considering that caffeine may have anxiogenic effects, thus changing the emotional state of the subjects, state-dependent learning may play a role in caffeine-induced cognitive alterations. Mice were administered 20 mg/kg caffeine before training and/or before testing both in the plus-maze discriminative avoidance task (an animal model that concomitantly evaluates learning, memory, anxiety-like behaviour and general activity) and in the inhibitory avoidance task, a classic paradigm for evaluating memory in rodents. Pre-training caffeine administration did not modify learning, but produced an anxiogenic effect and impaired memory retention. While pre-test administration of caffeine did not modify retrieval on its own, the pre-test administration counteracted the memory deficit induced by the pre-training caffeine injection in both the plus-maze discriminative and inhibitory avoidance tasks. Our data demonstrate that caffeine-induced memory deficits are critically related to state-dependent learning, reinforcing the importance of considering the participation of state-dependency on the interpretation of the cognitive effects of caffeine. The possible participation of caffeine-induced anxiety alterations in state-dependent memory deficits is discussed.

Crossing Boundaries in Facebook: Students' Framing of Language Learning Activities as Extended Spaces

Science.gov (United States)

Lantz-Andersson, Annika; Vigmo, Sylvi; Bowen, Rhonwen

2013-01-01

Young people's interaction online is rapidly increasing, which enables new spaces for communication; the impact on learning, however, is not yet acknowledged in education. The aim of this exploratory case study is to scrutinize how students frame their interaction in social networking sites (SNS) in school practices and what that implies for…

Lessons Learned for Space Safety from the Fukushima Nuclear Power Plant Accident

Science.gov (United States)

Nogami, Manami; Miki, Masami; Mitsui, Masami; Kawada, Ysuhiro; Takeuchi, Nobuo

2013-09-01

On March 11 2011, Tohoku Region Pacific Coast Earthquake hit Japan and caused the devastating damage. The Fukushima Nuclear Power Station (NPS) was also severely damaged.The Japanese NPSs are designed based on the detailed safety requirements and have multiple-folds of hazard controls to the catastrophic hazards as in space system. However, according to the initial information from the Tokyo Electric Power Company (TEPCO) and the Japanese government, the larger-than-expected tsunami and subsequent events lost the all hazard controls to the release of radioactive materials.At the 5th IAASS, Lessons Learned from this disaster was reported [1] mainly based on the "Report of the Japanese Government to the IAEA Ministerial Conference on Nuclear Safety" [2] published by Nuclear Emergency Response Headquarters in June 2011, three months after the earthquake.Up to 2012 summer, the major investigation boards, including the Japanese Diet, the Japanese Cabinet and TEPCO, published their final reports, in which detailed causes of this accident and several recommendations are assessed from each perspective.In this paper, the authors examine to introduce the lessons learned to be applied to the space safety as findings from these reports.

EEG Eye State Identification Using Incremental Attribute Learning with Time-Series Classification

Directory of Open Access Journals (Sweden)

Ting Wang

2014-01-01

Full Text Available Eye state identification is a kind of common time-series classification problem which is also a hot spot in recent research. Electroencephalography (EEG is widely used in eye state classification to detect human's cognition state. Previous research has validated the feasibility of machine learning and statistical approaches for EEG eye state classification. This paper aims to propose a novel approach for EEG eye state identification using incremental attribute learning (IAL based on neural networks. IAL is a novel machine learning strategy which gradually imports and trains features one by one. Previous studies have verified that such an approach is applicable for solving a number of pattern recognition problems. However, in these previous works, little research on IAL focused on its application to time-series problems. Therefore, it is still unknown whether IAL can be employed to cope with time-series problems like EEG eye state classification. Experimental results in this study demonstrates that, with proper feature extraction and feature ordering, IAL can not only efficiently cope with time-series classification problems, but also exhibit better classification performance in terms of classification error rates in comparison with conventional and some other approaches.

Quantum states and the Hadamard form. III. Constraints in cosmological space-times

International Nuclear Information System (INIS)

Najmi, A.; Ottewill, A.C.

1985-01-01

We examine the constraints on the construction of Fock spaces for scalar fields in spatially flat Robertson-Walker space-times imposed by requiring that the vacuum state of the theory have a two-point function possessing the Hadamard singularity structure required by standard renormalization theory. It is shown that any such vacuum state must be a second-order adiabatic vacuum. We discuss the global requirements on the two-point function for it to possess the Hadamard form at all times if it possesses it at one time

Sensorless State-Space Control of Elastic Two-Inertia Drive System Using a Minimum State Order Observer

Directory of Open Access Journals (Sweden)

V. Comnac

2009-12-01

Full Text Available The paper presents sensorless state-space control of two-inertia drive system with resilient coupling. The control structure contains an I+PI controller for load speed regulation and a state feedback controller for effective vibration suppression of the elastic coupling. Mechanical state variable of two-inertia drive are obtained by using a linear minimum-order (Gopinath state observer. The design of the combined (I+PI and state feedback controller is achieved with the extended version of the modulus criterion [5]. The dynamic behavior of presented control structure has been examined, for different conditions, using MATLAB/SIMULINK simulation.

The Learning Exchange: A Shared Space for the University of British Columbia and Vancouver's Downtown Eastside Communities

Science.gov (United States)

Towle, Angela; Leahy, Kathleen

2016-01-01

The Learning Exchange was established by the University of British Columbia (UBC) in 1999 in Vancouver's Downtown Eastside (DTES). The challenge has been to create a shared space for learning exchanges between two very different communities: a research-intensive university and an inner city area most commonly depicted as a place of hopelessness.…

Dwelling and Creative Imagination in Gaston Bachelard's Phenomenology: Returning to the Poetic Space of Education and Learning

Science.gov (United States)

Magrini, James M.

2017-01-01

In response to the so-called crisis in contemporary education in the institutions of higher learning (USA)--the encroachment of corporatism and pervasion of standardization--there is a move to offset this dominance by reconceiving the university in terms of an intimate space of dwelling in learning and education. In light of this moribund…

Deep-Inelastic Final States in a Space-Time Description of Shower Development and Hadronization

OpenAIRE

Ellis, John; Geiger, Klaus; Kowalski, Henryk

1996-01-01

We extend a quantum kinetic approach to the description of hadronic showers in space, time and momentum space to deep-inelastic $ep$ collisions, with particular reference to experiments at HERA. We follow the history of hard scattering events back to the initial hadronic state and forward to the formation of colour-singlet pre-hadronic clusters and their decays into hadrons. The time evolution of the space-like initial-state shower and the time-like secondary partons are treated similarly, an...

State-space approaches for modelling and control in financial engineering systems theory and machine learning methods

CERN Document Server

Rigatos, Gerasimos G

2017-01-01

The book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in financial systems when these are described in the form of nonlinear ordinary differential equations. It then addresses problems associated with the control and estimation of financial systems governed by partial differential equations (e.g. the Black–Scholes partial differential equation (PDE) and its variants). Lastly it an offers optimal solution to the problem of statistical validation of computational models and tools used to support financial engineers in decision making. The application of state-space models in financial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for finance can be eliminated. It also allows methods of fault-free performance and optimality in the management of assets and capitals and methods assuring stability in the functioning of financial systems to be established. Covering the following key are...

Application of space technologies for the purpose of education at the Belarusian state university

Science.gov (United States)

Liashkevich, Siarhey

Application of space technologies for the purpose of education at the Aerospace Educational Center of Belarusian state university is discussed. The aim of the work is to prepare launch of small satellite. Students are expected to participate in the design of control station, systems of communication, earth observation, navigation, and positioning. Benefit of such project-based learning from economical perspective is discussed. At present our training system at the base of EyasSat classroom satellite is used for management of satellite orientation and stabilization system. Principles of video processing, communication technologies and informational security for small spacecraft are developed at the base of Wi9M-2443 developer kit. More recent equipment allows obtaining the skills in digital signal processing at the base of FPGA. Development of ground station includes setup of 2.6 meter diameter dish for L-band, and spiral rotational antennas for UHF and VHF bands. Receiver equipment from National Instruments is used for digital signal processing and signal management.

Differentiating qualitative representations into learning spaces

NARCIS (Netherlands)

Liem, J.; Beek, W.; Bredeweg, B.; de Kleer, J.; Forbus, K.D.

2010-01-01

The DynaLearn interactive learning environment allows learners to construct their conceptual ideas and investigate the logical consequences of those ideas. By building and simulating causal models, students develop an understanding of how systems work. The DynaLearn interactive learning environment

State-space models for bio-loggers: A methodological road map

DEFF Research Database (Denmark)

Jonsen, I.D.; Basson, M.; Bestley, S.

2012-01-01

Ecologists have an unprecedented array of bio-logging technologies available to conduct in situ studies of horizontal and vertical movement patterns of marine animals. These tracking data provide key information about foraging, migratory, and other behaviours that can be linked with bio-physical...... development of state-space modelling approaches for animal movement data provides statistical rigor for inferring hidden behavioural states, relating these states to bio-physical data, and ultimately for predicting the potential impacts of climate change. Despite the widespread utility, and current popularity...

State space approach to mixed boundary value problems.

Science.gov (United States)

Chen, C. F.; Chen, M. M.

1973-01-01

A state-space procedure for the formulation and solution of mixed boundary value problems is established. This procedure is a natural extension of the method used in initial value problems; however, certain special theorems and rules must be developed. The scope of the applications of the approach includes beam, arch, and axisymmetric shell problems in structural analysis, boundary layer problems in fluid mechanics, and eigenvalue problems for deformable bodies. Many classical methods in these fields developed by Holzer, Prohl, Myklestad, Thomson, Love-Meissner, and others can be either simplified or unified under new light shed by the state-variable approach. A beam problem is included as an illustration.

Transient Response Analysis of Metropolis Learning in Games

KAUST Repository

Jaleel, Hassan

2017-10-19

The objective of this work is to provide a qualitative description of the transient properties of stochastic learning dynamics like adaptive play, log-linear learning, and Metropolis learning. The solution concept used in these learning dynamics for potential games is that of stochastic stability, which is based on the stationary distribution of the reversible Markov chain representing the learning process. However, time to converge to a stochastically stable state is exponential in the inverse of noise, which limits the use of stochastic stability as an effective solution concept for these dynamics. We propose a complete solution concept that qualitatively describes the state of the system at all times. The proposed concept is prevalent in control systems literature where a solution to a linear or a non-linear system has two parts, transient response and steady state response. Stochastic stability provides the steady state response of stochastic learning rules. In this work, we study its transient properties. Starting from an initial condition, we identify the subsets of the state space called cycles that have small hitting times and long exit times. Over the long time scales, we provide a description of how the distributions over joint action profiles transition from one cycle to another till it reaches the globally optimal state.

Transient Response Analysis of Metropolis Learning in Games

KAUST Repository

Jaleel, Hassan; Shamma, Jeff S.

2017-01-01

The objective of this work is to provide a qualitative description of the transient properties of stochastic learning dynamics like adaptive play, log-linear learning, and Metropolis learning. The solution concept used in these learning dynamics for potential games is that of stochastic stability, which is based on the stationary distribution of the reversible Markov chain representing the learning process. However, time to converge to a stochastically stable state is exponential in the inverse of noise, which limits the use of stochastic stability as an effective solution concept for these dynamics. We propose a complete solution concept that qualitatively describes the state of the system at all times. The proposed concept is prevalent in control systems literature where a solution to a linear or a non-linear system has two parts, transient response and steady state response. Stochastic stability provides the steady state response of stochastic learning rules. In this work, we study its transient properties. Starting from an initial condition, we identify the subsets of the state space called cycles that have small hitting times and long exit times. Over the long time scales, we provide a description of how the distributions over joint action profiles transition from one cycle to another till it reaches the globally optimal state.

Evaluating Russian space nuclear reactor technology for United States applications

International Nuclear Information System (INIS)

Polansky, G.F.; Schmidt, G.L.; Voss, S.S.; Reynolds, E.L.

1994-01-01

Space nuclear power and nuclear electric propulsion are considered important technologies for planetary exploration, as well as selected earth orbit applications. The Nuclear Electric Propulsion Space Test Program (NEPSTP) was intended to provide an early flight demonstration of these technologies at relatively low cost through extensive use of existing Russian technology. The key element of Russian technology employed in the program was the Topaz II reactor. Refocusing of the activities of the Ballistic Missile Defense Organization (BMDO), combined with budgetary pressures, forced the cancellation of the NEPSTP at the end of the 1993 fiscal year. The NEPSTP was faced with many unique flight qualification issues. In general, the launch of a spacecraft employing a nuclear reactor power system complicates many spacecraft qualification activities. However, the NEPSTP activities were further complicated because the reactor power system was a Russian design. Therefore, this program considered not only the unique flight qualification issues associated with space nuclear power, but also with differences between Russian and United States flight qualification procedures. This paper presents an overview of the NEPSTP. The program goals, the proposed mission, the spacecraft, and the Topaz II space nuclear power system are described. The subject of flight qualification is examined and the inherent difficulties of qualifying a space reactor are described. The differences between United States and Russian flight qualification procedures are explored. A plan is then described that was developed to determine an appropriate flight qualification program for the Topaz II reactor to support a possible NEPSTP launch

34 CFR 692.30 - How does a State administer its community service-learning job program?

Science.gov (United States)

2010-07-01

...-learning job program? 692.30 Section 692.30 Education Regulations of the Offices of the Department of... Administer Its Community Service-Learning Job Program? § 692.30 How does a State administer its community service-learning job program? (a)(1) Each year, a State may use up to 20 percent of its allotment for a...

Space Science in Action: Space Exploration [Videotape].

Science.gov (United States)

1999

In this videotape recording, students learn about the human quest to discover what is out in space. Students see the challenges and benefits of space exploration including the development of rocket science, a look back at the space race, and a history of manned space travel. A special section on the Saturn V rocket gives students insight into the…

Cognitive Bias for Learning Speech Sounds From a Continuous Signal Space Seems Nonlinguistic

Directory of Open Access Journals (Sweden)

Sabine van der Ham

2015-10-01

Full Text Available When learning language, humans have a tendency to produce more extreme distributions of speech sounds than those observed most frequently: In rapid, casual speech, vowel sounds are centralized, yet cross-linguistically, peripheral vowels occur almost universally. We investigate whether adults’ generalization behavior reveals selective pressure for communication when they learn skewed distributions of speech-like sounds from a continuous signal space. The domain-specific hypothesis predicts that the emergence of sound categories is driven by a cognitive bias to make these categories maximally distinct, resulting in more skewed distributions in participants’ reproductions. However, our participants showed more centered distributions, which goes against this hypothesis, indicating that there are no strong innate linguistic biases that affect learning these speech-like sounds. The centralization behavior can be explained by a lack of communicative pressure to maintain categories.

Inspiring the Next Generation in Space Life Sciences

Science.gov (United States)

Hayes, Judith

2010-01-01

Competitive summer internships in space life sciences at NASA are awarded to college students every summer. Each student is aligned with a NASA mentor and project that match his or her skills and interests, working on individual projects in ongoing research activities. The interns consist of undergraduate, graduate, and medical students in various majors and disciplines from across the United States. To augment their internship experience, students participate in the Space Life Sciences Summer Institute (SLSSI). The purpose of the Institute is to offer a unique learning environment that focuses on the current biomedical issues associated with human spaceflight; providing an introduction of the paradigms, problems, and technologies of modern spaceflight cast within the framework of life sciences. The Institute faculty includes NASA scientists, physicians, flight controllers, engineers, managers, and astronauts; and fosters a multi-disciplinary science approach to learning with a particular emphasis on stimulating experimental creativity and innovation within an operational environment. This program brings together scientists and students to discuss cutting-edge solutions to problems in space physiology, environmental health, and medicine; and provides a familiarization of the various aspects of space physiology and environments. In addition to the lecture series, behind-the-scenes tours are offered that include the Neutral Buoyancy Laboratory, Mission Control Center, space vehicle training mockups, and a hands-on demonstration of the Space Shuttle Advanced Crew Escape Suit. While the SLSSI is managed and operated at the Johnson Space Center in Texas, student interns from the other NASA centers (Glenn and Ames Research Centers, in Ohio and California) also participate through webcast distance learning capabilities.

State space orderings for Gauss-Seidel in Markov chains revisited

Energy Technology Data Exchange (ETDEWEB)

Dayar, T. [Bilkent Univ., Ankara (Turkey)

1996-12-31

Symmetric state space orderings of a Markov chain may be used to reduce the magnitude of the subdominant eigenvalue of the (Gauss-Seidel) iteration matrix. Orderings that maximize the elemental mass or the number of nonzero elements in the dominant term of the Gauss-Seidel splitting (that is, the term approximating the coefficient matrix) do not necessarily converge faster. An ordering of a Markov chain that satisfies Property-R is semi-convergent. On the other hand, there are semi-convergent symmetric state space orderings that do not satisfy Property-R. For a given ordering, a simple approach for checking Property-R is shown. An algorithm that orders the states of a Markov chain so as to increase the likelihood of satisfying Property-R is presented. The computational complexity of the ordering algorithm is less than that of a single Gauss-Seidel iteration (for sparse matrices). In doing all this, the aim is to gain an insight for faster converging orderings. Results from a variety of applications improve the confidence in the algorithm.

Creating a Space for Creativity

DEFF Research Database (Denmark)

Bøjer, Bodil

2017-01-01

Space shapes us but is also shaped by the way we interact with and act within the space. In recent years many schools are being built or rebuilt based on student-centred learning with smaller classrooms and large innovative learning environments (ILEs), expected to foster collaboration and creati......Space shapes us but is also shaped by the way we interact with and act within the space. In recent years many schools are being built or rebuilt based on student-centred learning with smaller classrooms and large innovative learning environments (ILEs), expected to foster collaboration...... teacher), space (the designer) and organisation (management). With my research, I would like to contribute to the understanding of the relationship between the physical learning environment and creative learning processes and the potential of the space as a tool to stimulate creativity. In my poster...... presentation at ‘Educational Architecture’ I will present a case study from my PhD-project where I developed a new ILE at a Danish municipal school in collaboration with the design agency Rune Fjord Studio. A starting point for the project was to examine if and how involving teachers and management...

Resting-state Functional Connectivity is an Age-dependent Predictor of Motor Learning Abilities.

Science.gov (United States)

Mary, Alison; Wens, Vincent; Op de Beeck, Marc; Leproult, Rachel; De Tiège, Xavier; Peigneux, Philippe

2017-10-01

This magnetoencephalography study investigates how ageing modulates the relationship between pre-learning resting-state functional connectivity (rsFC) and subsequent learning. Neuromagnetic resting-state activity was recorded 5 min before motor sequence learning in 14 young (19-30 years) and 14 old (66-70 years) participants. We used a seed-based beta-band power envelope correlation approach to estimate rsFC maps, with the seed located in the right primary sensorimotor cortex. In each age group, the relation between individual rsFC and learning performance was investigated using Pearson's correlation analyses. Our results show that rsFC is predictive of subsequent motor sequence learning but involves different cross-network interactions in the two age groups. In young adults, decreased coupling between the sensorimotor network and the cortico-striato-cerebellar network is associated with better motor learning, whereas a similar relation is found in old adults between the sensorimotor, the dorsal-attentional and the DMNs. Additionally, age-related correlational differences were found in the dorsolateral prefrontal cortex, known to subtend attentional and controlled processes. These findings suggest that motor skill learning depends-in an age-dependent manner-on subtle interactions between resting-state networks subtending motor activity on the one hand, and controlled and attentional processes on the other hand. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Virtual Spaces: Employing a Synchronous Online Classroom to Facilitate Student Engagement in Online Learning

Directory of Open Access Journals (Sweden)

J. Lynn McBrien

2009-06-01

Full Text Available This research study is a collaborative project between faculty in social foundations, special education, and instructional technology in which we analyze student data from six undergraduate and graduate courses related to the use of a virtual classroom space. Transactional distance theory (Moore & Kearsley, 1996 operates as our theoretical framework as we explore the role of a virtual classroom in distance education and analyze the ways in which a synchronous learning environment affects students’ learning experiences. Elluminate Live! was the software employed in the virtual classroom. In this analysis, particular themes emerged related to dialogue, structure, and learner autonomy. In addition, students rated convenience, technical issues, and pedagogical preferences as important elements in their learning experiences. The article discusses these themes as a contribution to reducing the “distance” that students experience in online learning and to developing quality distance education experiences for students in higher education.

Boundary Interaction: Towards Developing a Mobile Technology-Enabled Science Curriculum to Integrate Learning in the Informal Spaces

Science.gov (United States)

Sun, Daner; Looi, Chee-Kit

2018-01-01

This paper explores the crossover between formal learning and learning in informal spaces supported by mobile technology, and proposes design principles for educators to carry out a science curriculum, namely Boundary Activity-based Science Curriculum (BAbSC). The conceptualization of the boundary object, and the principles of boundary activity as…

News Teaching: The epiSTEMe project: KS3 maths and science improvement Field trip: Pupils learn physics in a stately home Conference: ShowPhysics welcomes fun in Europe Student numbers: Physics numbers increase in UK Tournament: Physics tournament travels to Singapore Particle physics: Hadron Collider sets new record Astronomy: Take your classroom into space Forthcoming Events

Science.gov (United States)

2010-05-01

Teaching: The epiSTEMe project: KS3 maths and science improvement Field trip: Pupils learn physics in a stately home Conference: ShowPhysics welcomes fun in Europe Student numbers: Physics numbers increase in UK Tournament: Physics tournament travels to Singapore Particle physics: Hadron Collider sets new record Astronomy: Take your classroom into space Forthcoming Events

Dynamic Sensor Tasking for Space Situational Awareness via Reinforcement Learning

Science.gov (United States)

Linares, R.; Furfaro, R.

2016-09-01

This paper studies the Sensor Management (SM) problem for optical Space Object (SO) tracking. The tasking problem is formulated as a Markov Decision Process (MDP) and solved using Reinforcement Learning (RL). The RL problem is solved using the actor-critic policy gradient approach. The actor provides a policy which is random over actions and given by a parametric probability density function (pdf). The critic evaluates the policy by calculating the estimated total reward or the value function for the problem. The parameters of the policy action pdf are optimized using gradients with respect to the reward function. Both the critic and the actor are modeled using deep neural networks (multi-layer neural networks). The policy neural network takes the current state as input and outputs probabilities for each possible action. This policy is random, and can be evaluated by sampling random actions using the probabilities determined by the policy neural network's outputs. The critic approximates the total reward using a neural network. The estimated total reward is used to approximate the gradient of the policy network with respect to the network parameters. This approach is used to find the non-myopic optimal policy for tasking optical sensors to estimate SO orbits. The reward function is based on reducing the uncertainty for the overall catalog to below a user specified uncertainty threshold. This work uses a 30 km total position error for the uncertainty threshold. This work provides the RL method with a negative reward as long as any SO has a total position error above the uncertainty threshold. This penalizes policies that take longer to achieve the desired accuracy. A positive reward is provided when all SOs are below the catalog uncertainty threshold. An optimal policy is sought that takes actions to achieve the desired catalog uncertainty in minimum time. This work trains the policy in simulation by letting it task a single sensor to "learn" from its performance

E-Learning for Geography's Teaching and Learning Spaces

Science.gov (United States)

Lynch, Kenneth; Bednarz, Bob; Boxall, James; Chalmers, Lex; France, Derek; Kesby, Julie

2008-01-01

The authors embed their advocacy of educational technology in a consideration of contemporary pedagogy in geography. They provide examples of e-learning from a wide range of teaching and learning contexts. They promote the idea that considering best practice with reference to educational technology will increase the versatility of teaching…

Grey-box state-space identification of nonlinear mechanical vibrations

Science.gov (United States)

Noël, J. P.; Schoukens, J.

2018-05-01

The present paper deals with the identification of nonlinear mechanical vibrations. A grey-box, or semi-physical, nonlinear state-space representation is introduced, expressing the nonlinear basis functions using a limited number of measured output variables. This representation assumes that the observed nonlinearities are localised in physical space, which is a generic case in mechanics. A two-step identification procedure is derived for the grey-box model parameters, integrating nonlinear subspace initialisation and weighted least-squares optimisation. The complete procedure is applied to an electrical circuit mimicking the behaviour of a single-input, single-output (SISO) nonlinear mechanical system and to a single-input, multiple-output (SIMO) geometrically nonlinear beam structure.

Loss of Signal, Aeromedical Lessons Learned for the STS-I07 Columbia Space Shuttle Mishap

Science.gov (United States)

Patlach, Robert; Stepaniak, Philip C.; Lane, Helen W.

2014-01-01

Loss of Signal, a NASA publication to be available in May 2014, presents the aeromedical lessons learned from the Columbia accident that will enhance crew safety and survival on human space flight missions. These lessons were presented to limited audiences at three separate Aerospace Medical Association (AsMA) conferences: in 2004 in Anchorage, Alaska, on the causes of the accident; in 2005 in Kansas City, Missouri, on the response, recovery, and identification aspects of the investigation; and in 2011, again in Anchorage, Alaska, on future implications for human space flight. As we embark on the development of new spacefaring vehicles through both government and commercial efforts, the NASA Johnson Space Center Human Health and Performance Directorate is continuing to make this information available to a wider audience engaged in the design and development of future space vehicles. Loss of Signal summarizes and consolidates the aeromedical impacts of the Columbia mishap process-the response, recovery, identification, investigative studies, medical and legal forensic analysis, and future preparation that are needed to respond to spacecraft mishaps. The goals of this book are to provide an account of the aeromedical aspects of the Columbia accident and the investigation that followed, and to encourage aerospace medical specialists to continue to capture information, learn from it, and improve procedures and spacecraft designs for the safety of future crews.

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.

Does Digitized Virtual Space Allow for Effective Learning in Creating Environments for Theatrical Productions?

Science.gov (United States)

Magruder, Lewis

2016-01-01

Learning how to transform an empty space into one alive with dramatic possibilities is one of the challenges facing students in several disciplines--for example, graphic design, filmmaking, gaming, architecture, interior design, visual arts, and designing and directing for the theatre. The author, a professor of directing for the theatre,…

Creating a Space for Creativity

DEFF Research Database (Denmark)

Bøjer, Bodil

2017-01-01

and creativity. But the relational dependence between the physical space, pedagogics and organisation is widely overlooked when designing these new learning environments as a new spatial design in itself is expected to change the way we teach and learn. Simply changing the space is not enough (Imms & Byers, 2017......) and the intentions of the space can only be fully realised if the inhabitants of the schools completely understand and support the pedagogical principles informing the provision of these spaces (Burke, 2016). This is why three things should be aligned in order for an ILE to work intendedly: creative teaching (the...... teacher), space (the designer) and organisation (management). With my research, I would like to contribute to the understanding of the relationship between the physical learning environment and creative learning processes and the potential of the space as a tool to stimulate creativity. In my poster...

Multivariable Wind Modeling in State Space

DEFF Research Database (Denmark)

Sichani, Mahdi Teimouri; Pedersen, B. J.

2011-01-01

Turbulence of the incoming wind field is of paramount importance to the dynamic response of wind turbines. Hence reliable stochastic models of the turbulence should be available from which time series can be generated for dynamic response and structural safety analysis. In the paper an empirical...... for the vector turbulence process incorporating its phase spectrum in one stage, and its results are compared with a conventional ARMA modeling method....... the succeeding state space and ARMA modeling of the turbulence rely on the positive definiteness of the cross-spectral density matrix, the problem with the non-positive definiteness of such matrices is at first addressed and suitable treatments regarding it are proposed. From the adjusted positive definite cross...

State-Space Estimation of Soil Organic Carbon Stock

Science.gov (United States)

Ogunwole, Joshua O.; Timm, Luis C.; Obidike-Ugwu, Evelyn O.; Gabriels, Donald M.

2014-04-01

Understanding soil spatial variability and identifying soil parameters most determinant to soil organic carbon stock is pivotal to precision in ecological modelling, prediction, estimation and management of soil within a landscape. This study investigates and describes field soil variability and its structural pattern for agricultural management decisions. The main aim was to relate variation in soil organic carbon stock to soil properties and to estimate soil organic carbon stock from the soil properties. A transect sampling of 100 points at 3 m intervals was carried out. Soils were sampled and analyzed for soil organic carbon and other selected soil properties along with determination of dry aggregate and water-stable aggregate fractions. Principal component analysis, geostatistics, and state-space analysis were conducted on the analyzed soil properties. The first three principal components explained 53.2% of the total variation; Principal Component 1 was dominated by soil exchange complex and dry sieved macroaggregates clusters. Exponential semivariogram model described the structure of soil organic carbon stock with a strong dependence indicating that soil organic carbon values were correlated up to 10.8m.Neighbouring values of soil organic carbon stock, all waterstable aggregate fractions, and dithionite and pyrophosphate iron gave reliable estimate of soil organic carbon stock by state-space.

A state-space Bayesian framework for estimating biogeochemical transformations using time-lapse geophysical data

Energy Technology Data Exchange (ETDEWEB)

Chen, J.; Hubbard, S.; Williams, K.; Pride, S.; Li, L.; Steefel, C.; Slater, L.

2009-04-15

We develop a state-space Bayesian framework to combine time-lapse geophysical data with other types of information for quantitative estimation of biogeochemical parameters during bioremediation. We consider characteristics of end-products of biogeochemical transformations as state vectors, which evolve under constraints of local environments through evolution equations, and consider time-lapse geophysical data as available observations, which could be linked to the state vectors through petrophysical models. We estimate the state vectors and their associated unknown parameters over time using Markov chain Monte Carlo sampling methods. To demonstrate the use of the state-space approach, we apply it to complex resistivity data collected during laboratory column biostimulation experiments that were poised to precipitate iron and zinc sulfides during sulfate reduction. We develop a petrophysical model based on sphere-shaped cells to link the sulfide precipitate properties to the time-lapse geophysical attributes and estimate volume fraction of the sulfide precipitates, fraction of the dispersed, sulfide-encrusted cells, mean radius of the aggregated clusters, and permeability over the course of the experiments. Results of the case study suggest that the developed state-space approach permits the use of geophysical datasets for providing quantitative estimates of end-product characteristics and hydrological feedbacks associated with biogeochemical transformations. Although tested here on laboratory column experiment datasets, the developed framework provides the foundation needed for quantitative field-scale estimation of biogeochemical parameters over space and time using direct, but often sparse wellbore data with indirect, but more spatially extensive geophysical datasets.

Social Justice and Out-of-School Science Learning: Exploring Equity in Science Television, Science Clubs and Maker Spaces

Science.gov (United States)

Dawson, Emily

2017-01-01

This article outlines how social justice theories, in combination with the concepts of infrastructure access, literacies and community acceptance, can be used to think about equity in out-of-school science learning. The author applies these ideas to out-of-school learning via television, science clubs, and maker spaces, looking at research as well…

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction

KAUST Repository

Cui, Xuefeng

2016-06-15

Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. Method: We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence–structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. Results: We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM–HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods.

Cocaine induces state-dependent learning of sexual conditioning in male Japanese quail.

Science.gov (United States)

Gill, Karin E; Rice, Beth Ann; Akins, Chana K

2015-01-01

State dependent learning effects have been widely studied in a variety of drugs of abuse. However, they have yet to be studied in relation to sexual motivation. The current study investigated state-dependent learning effects of cocaine in male Japanese quail (Coturnix japonica) using a sexual conditioning paradigm. Cocaine-induced state-dependent learning effects were investigated using a 2×2 factorial design with training state as one factor and test state as the other factor. During a 14-day training phase, male quail were injected once daily with 10mg/kg cocaine or saline and then placed in a test chamber after 15min. In the test chamber, sexual conditioning trials consisted of presentation of a light conditioned stimulus (CS) followed by sexual reinforcement. During the state dependent test, half of the birds received a shift in drug state from training to testing (Coc→Sal or Sal→Coc) while the other half remained in the same drug state (Coc→Coc or Sal→Sal). Results showed that male quail that were trained and tested in the same state (Coc→Coc or Sal→Sal) showed greater sexual conditioning than male quail that were trained and tested in different states (Sal→Coc) except when cocaine was administered chronically prior to the test (Coc→Sal). For the latter condition, sexual conditioning persisted from cocaine training to the saline test. The findings suggest that state dependent effects may alter sexual motivation and that repeated exposure to cocaine during sexual activity may increase sexual motivation which, in turn, may lead to high risk sexual activities. An alternative explanation for the findings is also discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

Solar Pumped Solid State Lasers for Space Solar Power: Experimental Path

Science.gov (United States)

Fork, Richard L.; Carrington, Connie K.; Walker, Wesley W.; Cole, Spencer T.; Green, Jason J. A.; Laycock, Rustin L.

2003-01-01

We outline an experimentally based strategy designed to lead to solar pumped solid state laser oscillators useful for space solar power. Our method involves solar pumping a novel solid state gain element specifically designed to provide efficient conversion of sunlight in space to coherent laser light. Kilowatt and higher average power is sought from each gain element. Multiple such modular gain elements can be used to accumulate total average power of interest for power beaming in space, e.g., 100 kilowatts and more. Where desirable the high average power can also be produced as a train of pulses having high peak power (e.g., greater than 10(exp 10 watts). The modular nature of the basic gain element supports an experimental strategy in which the core technology can be validated by experiments on a single gain element. We propose to do this experimental validation both in terrestrial locations and also on a smaller scale in space. We describe a terrestrial experiment that includes diagnostics and the option of locating the laser beam path in vacuum environment. We describe a space based experiment designed to be compatible with the Japanese Experimental Module (JEM) on the International Space Station (ISS). We anticipate the gain elements will be based on low temperature (approx. 100 degrees Kelvin) operation of high thermal conductivity (k approx. 100 W/cm-K) diamond and sapphire (k approx. 4 W/cm-K). The basic gain element will be formed by sequences of thin alternating layers of diamond and Ti:sapphire with special attention given to the material interfaces. We anticipate this strategy will lead to a particularly simple, robust, and easily maintained low mass modelocked multi-element laser oscillator useful for space solar power.

Entertainment, Engagement and Education: Foundations and Developments in Digital and Physical Spaces to Support Learning through Making

DEFF Research Database (Denmark)

Giannakos, Michail N.; Divitini, Monica; Iversen, Ole Sejer

2017-01-01

like problem solving, design thinking, collaboration, and innovation, to mention few. Contemporary technical and infrastructural developments, like Hackerspaces, Makerspaces, TechShops, FabLabs and the appearance of tools such as wearable computing, robotics, 3D printing, microprocessors, and intuitive......Making is a relatively new concept applied to describe the increasing attention on constructing activities to enable entertaining, engaging and efficient learning. Making focuses on the process that occurs in digital and/or physical spaces that is not always learning oriented, but enables qualities...... programming languages; posit making as a very promising research area to support the learning processes, especially towards the acquisition of 21st Century learning competences. Collecting learning evidence via rigorous multidimensional and multidisciplinary case studies will allow us to better understand...

Loss of Signal, Aeromedical Lessons Learned from the STS-107 Columbia Space Shuttle Mishap

Science.gov (United States)

Stepaniak, Phillip C.; Patlach, Robert

2014-01-01

Loss of Signal, a NASA publication to be available in May 2014 presents the aeromedical lessons learned from the Columbia accident that will enhance crew safety and survival on human space flight missions. These lessons were presented to limited audiences at three separate Aerospace Medical Association (AsMA) conferences: in 2004 in Anchorage, Alaska, on the causes of the accident; in 2005 in Kansas City, Missouri, on the response, recovery, and identification aspects of the investigation; and in 2011, again in Anchorage, Alaska, on future implications for human space flight. As we embark on the development of new spacefaring vehicles through both government and commercial efforts, the NASA Johnson Space Center Human Health and Performance Directorate is continuing to make this information available to a wider audience engaged in the design and development of future space vehicles. Loss of Signal summarizes and consolidates the aeromedical impacts of the Columbia mishap process-the response, recovery, identification, investigative studies, medical and legal forensic analysis, and future preparation that are needed to respond to spacecraft mishaps. The goal of this book is to provide an account of the aeromedical aspects of the Columbia accident and the investigation that followed, and to encourage aerospace medical specialists to continue to capture information, learn from it, and improve procedures and spacecraft designs for the safety of future crews. This poster presents an outline of Loss of Signal contents and highlights from each of five sections - the mission and mishap, the response, the investigation, the analysis and the future.

Learning how to learn: Meta-learning strategies for the challenges of learning pharmacology.

Science.gov (United States)

Alton, Suzanne

2016-03-01

Nursing students have difficulty with pharmacology courses because of the complicated nomenclature and the difficulty of applying drug information to actual patient care. As part of a new pharmacology course being created, meta-learning strategies designed to diminish the difficulties of learning this difficult content were part of the course pedagogy. Strategies were demonstrated, reviewed in class, and implemented through homework assignments. The setting was an Academic Health Center's School of Nursing in the southern United States. Participants were third-year nursing students in an undergraduate nursing program. Surveys of students' opinions of learning gains were conducted at the end of the course over several semesters. In addition, pharmacology scores on a standardized exit exam were compared prior to implementing the course and after. Students reported learning dry material more easily, having greater confidence, and finding substantial value in the learning strategies. Students indicated the most helpful strategies, in descending order, as follows: making charts to compare and contrast drugs and drug classes, writing out drug flash cards, making or reviewing creative projects, prioritizing information, making or using visual study aids, and using time and repetition to space learning. Implementation of the new course improved pharmacology scores on a standardized exit exam from 67.0% to 74.3%. Overall response to learning strategies was positive, and the increase in the pharmacology standardized exit exam scores demonstrated the effectiveness of this instructional approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

On coherent-state representations of quantum mechanics: Wave mechanics in phase space

DEFF Research Database (Denmark)

Møller, Klaus Braagaard; Jørgensen, Thomas Godsk; Torres-Vega, Gabino

1997-01-01

In this article we argue that the state-vector phase-space representation recently proposed by Torres-Vega and co-workers [introduced in J. Chem. Phys. 98, 3103 (1993)] coincides with the totality of coherent-state representations for the Heisenberg-Weyl group. This fact leads to ambiguities when...

Spaces of Performance in Higher Education

DEFF Research Database (Denmark)

Jørgensen, Kenneth Mølbjerg

2018-01-01

Abstract Purpose — The purpose of the paper is to provide a framework for reflecting on how different ways of configuring spaces in higher education (HE) condition the possibilities of learning. Second, the purpose is to construct a storytelling approach for the configuration of such spaces. Design...... to the potential of HE to produce new and innovative forms of learning. Value — This paper introduces the term “spaces of performance,” which directs attention towards the material, discursive, and relational conditions for learning. It also introduces a space of storytelling as a new principle for learning in HE...

Parameter retrieval of chiral metamaterials based on the state-space approach.

Science.gov (United States)

Zarifi, Davoud; Soleimani, Mohammad; Abdolali, Ali

2013-08-01

This paper deals with the introduction of an approach for the electromagnetic characterization of homogeneous chiral layers. The proposed method is based on the state-space approach and properties of a 4×4 state transition matrix. Based on this, first, the forward problem analysis through the state-space method is reviewed and properties of the state transition matrix of a chiral layer are presented and proved as two theorems. The formulation of a proposed electromagnetic characterization method is then presented. In this method, scattering data for a linearly polarized plane wave incident normally on a homogeneous chiral slab are combined with properties of a state transition matrix and provide a powerful characterization method. The main difference with respect to other well-established retrieval procedures based on the use of the scattering parameters relies on the direct computation of the transfer matrix of the slab as opposed to the conventional calculation of the propagation constant and impedance of the modes supported by the medium. The proposed approach allows avoiding nonlinearity of the problem but requires getting enough equations to fulfill the task which was provided by considering some properties of the state transition matrix. To demonstrate the applicability and validity of the method, the constitutive parameters of two well-known dispersive chiral metamaterial structures at microwave frequencies are retrieved. The results show that the proposed method is robust and reliable.

Library as a Partner in Co-Designing Learning Spaces: A Case Study at Tampere University of Technology, Finland

Science.gov (United States)

Tevaniemi, Johanna; Poutanen, Jenni; Lähdemäki, Riitta

2015-01-01

This article presents a case of co-designed temporary learning spaces at a Finnish academic library, together with the results of a user-survey. The experimental development of the multifunctional spaces offered an opportunity for the library to collaborate with its parent organisation thus broadening the role of the library. Hence, library can be…

How States Use Student Learning Objectives in Teacher Evaluation Systems: A Review of State Websites. REL 2014-013

Science.gov (United States)

Lacireno-Paquet, Natalie; Morgan, Claire; Mello, Daniel

2014-01-01

Motivated by the need to improve teaching and learning and by federal priorities reflected in requirements for grant programs such as Race to the Top and the Teacher Incentive Fund, many states are developing teacher evaluation systems that include measures of individual teachers' contributions to their students' learning growth. One way to…

Quantum computing based on space states without charge transfer

International Nuclear Information System (INIS)

Vyurkov, V.; Filippov, S.; Gorelik, L.

2010-01-01

An implementation of a quantum computer based on space states in double quantum dots is discussed. There is no charge transfer in qubits during a calculation, therefore, uncontrolled entanglement between qubits due to long-range Coulomb interaction is suppressed. Encoding and processing of quantum information is merely performed on symmetric and antisymmetric states of the electron in double quantum dots. Other plausible sources of decoherence caused by interaction with phonons and gates could be substantially suppressed in the structure as well. We also demonstrate how all necessary quantum logic operations, initialization, writing, and read-out could be carried out in the computer.

State Space Reduction of Linear Processes using Control Flow Reconstruction

NARCIS (Netherlands)

van de Pol, Jan Cornelis; Timmer, Mark

2009-01-01

We present a new method for fighting the state space explosion of process algebraic specifications, by performing static analysis on an intermediate format: linear process equations (LPEs). Our method consists of two steps: (1) we reconstruct the LPE's control flow, detecting control flow parameters

State Space Reduction of Linear Processes Using Control Flow Reconstruction

NARCIS (Netherlands)

van de Pol, Jan Cornelis; Timmer, Mark; Liu, Zhiming; Ravn, Anders P.

2009-01-01

We present a new method for fighting the state space explosion of process algebraic specifications, by performing static analysis on an intermediate format: linear process equations (LPEs). Our method consists of two steps: (1) we reconstruct the LPE's control flow, detecting control flow parameters

A non-linear state space approach to model groundwater fluctuations

NARCIS (Netherlands)

Berendrecht, W.L.; Heemink, A.W.; Geer, F.C. van; Gehrels, J.C.

2006-01-01

A non-linear state space model is developed for describing groundwater fluctuations. Non-linearity is introduced by modeling the (unobserved) degree of water saturation of the root zone. The non-linear relations are based on physical concepts describing the dependence of both the actual

Motion state analysis of space target based on optical cross section

Science.gov (United States)

Tian, Qichen; Li, Zhi; Xu, Can; Liu, Chenghao

2017-10-01

In order to solve the problem that the movement state analysis method of the space target based on OCS is not related to the real motion state. This paper proposes a method based on OCS for analyzing the state of space target motion. This paper first establish a three-dimensional model of real STSS satellite, then change the satellite's surface into element, and assign material to each panel according to the actual conditions of the satellite. This paper set up a motion scene according to the orbit parameters of STSS satellite in STK, and the motion states are set to three axis steady state and slowly rotating unstable state respectively. In these two states, the occlusion condition of the surface element is firstly determined, and the effective face element is selected. Then, the coordinates of the observation station and the solar coordinates in the satellite body coordinate system are input into the OCS calculation program, and the OCS variation curves of the three axis steady state and the slow rotating unstable state STSS satellite are obtained. Combining the satellite surface structure and the load situation, the OCS change curve of the three axis stabilized satellite is analyzed, and the conclude that the OCS curve fluctuates up and down when the sunlight is irradiated to the load area; By using Spectral analysis method, autocorrelation analysis and the cross residual method, the rotation speed of OCS satellite in slow rotating unstable state is analyzed, and the rotation speed of satellite is successfully reversed. By comparing the three methods, it is found that the cross residual method is more accurate.

The Role of Architectural and Learning Constraints in Neural Network Models: A Case Study on Visual Space Coding.

Science.gov (United States)

Testolin, Alberto; De Filippo De Grazia, Michele; Zorzi, Marco

2017-01-01

The recent "deep learning revolution" in artificial neural networks had strong impact and widespread deployment for engineering applications, but the use of deep learning for neurocomputational modeling has been so far limited. In this article we argue that unsupervised deep learning represents an important step forward for improving neurocomputational models of perception and cognition, because it emphasizes the role of generative learning as opposed to discriminative (supervised) learning. As a case study, we present a series of simulations investigating the emergence of neural coding of visual space for sensorimotor transformations. We compare different network architectures commonly used as building blocks for unsupervised deep learning by systematically testing the type of receptive fields and gain modulation developed by the hidden neurons. In particular, we compare Restricted Boltzmann Machines (RBMs), which are stochastic, generative networks with bidirectional connections trained using contrastive divergence, with autoencoders, which are deterministic networks trained using error backpropagation. For both learning architectures we also explore the role of sparse coding, which has been identified as a fundamental principle of neural computation. The unsupervised models are then compared with supervised, feed-forward networks that learn an explicit mapping between different spatial reference frames. Our simulations show that both architectural and learning constraints strongly influenced the emergent coding of visual space in terms of distribution of tuning functions at the level of single neurons. Unsupervised models, and particularly RBMs, were found to more closely adhere to neurophysiological data from single-cell recordings in the primate parietal cortex. These results provide new insights into how basic properties of artificial neural networks might be relevant for modeling neural information processing in biological systems.

Negative norm states in de Sitter space and QFT without renormalization procedure

International Nuclear Information System (INIS)

Takook, M.V.

2002-01-01

In recent papers, 1,2 it has been shown that the presence of negative norm states or negative frequency solutions are indispensable for a fully covariant quantization of the minimally coupled scalar field in de Sitter space. Their presence, while leaving unchanged the physical content of the theory, offers the advantage of eliminating any ultraviolet divergence in the vacuum energy 2 and infrared divergence in the two point function. 3 We attempt here to extend this method to the interacting quantum field in Minkowski space-time. As an illustration of the procedure, we consider the λϕ 4 theory in Minkowski space-time. The mathematical consequences of this method is the disappearance of the ultraviolet divergence to the one-loop approximation. This means, the effect of these auxiliary negative norm states is to allow an automatic renormalization of the theory in this approximation. (author)

Learning Styles of Pilots Currently Qualified in United States Air Force Aircraft

Science.gov (United States)

Kanske, Craig A.

2001-01-01

Kolb's Learning Style Inventory was used to identify the predominant learning styles of pilots currently qualified in United States Air Force aircraft. The results indicate that these pilots show a significant preference for facts and things over people and feelings. By understanding the preferred learning styles of the target population, course material can be developed that take advantage of the strengths of these learning styles. This information can be especially useful in the future design of cockpit resource management training. The training program can be developed to demonstrate both that there are different learning styles and that it is possible to take advantage of the relative strengths of each of these learning styles.

Complex network analysis of state spaces for random Boolean networks

Energy Technology Data Exchange (ETDEWEB)

Shreim, Amer [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Berdahl, Andrew [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Sood, Vishal [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Grassberger, Peter [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Paczuski, Maya [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada)

2008-01-15

We apply complex network analysis to the state spaces of random Boolean networks (RBNs). An RBN contains N Boolean elements each with K inputs. A directed state space network (SSN) is constructed by linking each dynamical state, represented as a node, to its temporal successor. We study the heterogeneity of these SSNs at both local and global scales, as well as sample to-sample fluctuations within an ensemble of SSNs. We use in-degrees of nodes as a local topological measure, and the path diversity (Shreim A et al 2007 Phys. Rev. Lett. 98 198701) of an SSN as a global topological measure. RBNs with 2 {<=} K {<=} 5 exhibit non-trivial fluctuations at both local and global scales, while K = 2 exhibits the largest sample-to-sample (possibly non-self-averaging) fluctuations. We interpret the observed 'multi scale' fluctuations in the SSNs as indicative of the criticality and complexity of K = 2 RBNs. 'Garden of Eden' (GoE) states are nodes on an SSN that have in-degree zero. While in-degrees of non-GoE nodes for K > 1 SSNs can assume any integer value between 0 and 2{sup N}, for K = 1 all the non-GoE nodes in a given SSN have the same in-degree which is always a power of two.

Complex network analysis of state spaces for random Boolean networks

International Nuclear Information System (INIS)

Shreim, Amer; Berdahl, Andrew; Sood, Vishal; Grassberger, Peter; Paczuski, Maya

2008-01-01

We apply complex network analysis to the state spaces of random Boolean networks (RBNs). An RBN contains N Boolean elements each with K inputs. A directed state space network (SSN) is constructed by linking each dynamical state, represented as a node, to its temporal successor. We study the heterogeneity of these SSNs at both local and global scales, as well as sample to-sample fluctuations within an ensemble of SSNs. We use in-degrees of nodes as a local topological measure, and the path diversity (Shreim A et al 2007 Phys. Rev. Lett. 98 198701) of an SSN as a global topological measure. RBNs with 2 ≤ K ≤ 5 exhibit non-trivial fluctuations at both local and global scales, while K = 2 exhibits the largest sample-to-sample (possibly non-self-averaging) fluctuations. We interpret the observed 'multi scale' fluctuations in the SSNs as indicative of the criticality and complexity of K = 2 RBNs. 'Garden of Eden' (GoE) states are nodes on an SSN that have in-degree zero. While in-degrees of non-GoE nodes for K > 1 SSNs can assume any integer value between 0 and 2 N , for K = 1 all the non-GoE nodes in a given SSN have the same in-degree which is always a power of two

Using a multi-state Learning Community as an implementation strategy for immediate postpartum long-acting reversible contraception.

Science.gov (United States)

DeSisto, Carla L; Estrich, Cameron; Kroelinger, Charlan D; Goodman, David A; Pliska, Ellen; Mackie, Christine N; Waddell, Lisa F; Rankin, Kristin M

2017-11-21

Implementation strategies are imperative for the successful adoption and sustainability of complex evidence-based public health practices. Creating a learning collaborative is one strategy that was part of a recently published compilation of implementation strategy terms and definitions. In partnership with the Centers for Disease Control and Prevention and other partner agencies, the Association of State and Territorial Health Officials recently convened a multi-state Learning Community to support cross-state collaboration and provide technical assistance for improving state capacity to increase access to long-acting reversible contraception (LARC) in the immediate postpartum period, an evidence-based practice with the potential for reducing unintended pregnancy and improving maternal and child health outcomes. During 2015-2016, the Learning Community included multi-disciplinary, multi-agency teams of state health officials, payers, clinicians, and health department staff from 13 states. This qualitative study was conducted to better understand the successes, challenges, and strategies that the 13 US states in the Learning Community used for increasing access to immediate postpartum LARC. We conducted telephone interviews with each team in the Learning Community. Interviews were semi-structured and organized by the eight domains of the Learning Community. We coded transcribed interviews for facilitators, barriers, and implementation strategies, using a recent compilation of expert-defined implementation strategies as a foundation for coding the latter. Data analysis showed three ways that the activities of the Learning Community helped in policy implementation work: structure and accountability, validity, and preparing for potential challenges and opportunities. Further, the qualitative data demonstrated that the Learning Community integrated six other implementation strategies from the literature: organize clinician implementation team meetings, conduct

Harmonic Instability Assessment Using State-Space Modeling and Participation Analysis in Inverter-Fed Power Systems

DEFF Research Database (Denmark)

Wang, Yanbo; Wang, Xiongfei; Blaabjerg, Frede

2017-01-01

parameters on the harmonic instability of the power system. Moreover, the harmonic-frequency oscillation modes are identified, where participation analysis is presented to evaluate the contributions of different states to these modes and to further reveal how the system gives rise to harmonic instability......This paper presents a harmonic instability analysis method using state-space modeling and participation analysis in the inverter-fed ac power systems. A full-order state-space model for the droop-controlled Distributed Generation (DG) inverter is built first, including the time delay of the digital...... control system, inner current and voltage control loops, and outer droop-based power control loop. Based on the DG inverter model, an overall state-space model of a two-inverter-fed system is established. The eigenvalue-based stability analysis is then presented to assess the influence of controller...

Dissipative differential systems and the state space H∞ control problem

NARCIS (Netherlands)

Trentelman, H.L.; Willems, J.C.

2000-01-01

The purpose of this paper is to apply our very recent results on the synthesis of dissipative linear differential systems to the 'classical' state space H∞ control problem. We first review our general problem set-up, where the problem of rendering a given plant dissipative by general